The Cardinium wins on Wolbachia in double-infected mite cultures

The Cardinium wins on Wolbachia in double-infected mite cultures | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Cardinium wins on Wolbachia in double-infected mite cultures Eliska Tresnakova, Eliza Glowska, Jan Hubert This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3848978/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Apr, 2025 Read the published version in mSystems → Version 1 posted You are reading this latest preprint version Abstract The different cultures of stored product mite Tyrophagus putrescentiae are single-infected by intracellular bacteria Cardinium or Wolbachia . No natural double-infected Cardinium / Wolbachia-infected mites are known. Under the experiment, single-infected mite ( Wolbachia 5N, 5P and Cardinium 5L, 5S) cultures were mixed to double-infected cultures (5LP, 5LN, 5SP, 5SN). The mite fitness and symbionts' presence were analyzed during 5-month-long experiment. Cardinium, Wolbachia and mite genomes were assembled and gene expression in single and double-infected cultures was analyzed. In double-infected cultures, Cardinium infection increased with the time of the experiment from 50 to 95% of infected mites. Cardinium + Wolbachia -infected mite individuals proportion ranged from 0 to 20% of mites in double-infected cultures. Wolbachia infection disappeared in all double-infected cultures up to 5 months of the experiment duration. The double-infected cultures had lower fitness than single-infected cultures. After a month of experiment, the fitness of originally double-infected cultures increased to the level of parental cultures. The correlation analyses of gene expression showed that Wolbachia had well-established interactions with mite predicted KEGG gene expression in a single-infected population. The expression of mite protein was strongly influenced by the presence of Wolbachia , but not by Cardinium . The total numbers of Cardinium -expressed genes did not change, while there was a ten-fold decrease in Wolbachia in double-infected cultures. Cardinium and Wolbachia gene expression showed 30% negative and 70% positive (N = 3793) correlations. The number of correlations between Wolbachia and mite gene expression 5 times decreased in double-infected cultures. The Cardinium had a 6-fold higher number of genes than Wolbachia with significantly higher expression in the multiple infected samples. The gene expression analysis provides a suggestion that the presence of Cardinium inhibits the growth of Wolbachia by the disruption of the Wolbachia interaction with mite host. However, we cannot eliminate stochastic processes resulting in the increase of Wolbachia abundance and symbiont change. Importance We sought insight into the intracellular symbionts’ competition in the novel mite host model. The manipulative experiments established double-infected Wolbachia Cardinium cultures, which were unstable due to their low fitness. Cardinium prevailed during five months in all 4 double-infected cultures. The competition disrupted Wolbachia's interaction with its host on the level of gene expression. The genome expression is highly correlated between Wolbachia and mite hosts in single Wolbachia -infected cultures. These correlations disappeared in multi-infected cultures. Differently, the interaction among host and Cardinium genes showed low differences in the gene expression level. Although Cardinium / Wolbachia -infested individuals are rare, the gene expression of Cardinium and Wolbachia had a high number of positive correlations. It indicates that the symbionts reacted to each other. The data indicates that we have established a new model to study Wolbachia and Cardinium interactions. Mite Cardinium Wolbachia Genome Gene expression Interaction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction The intracellular, cytoplasmically inherited bacteria Cardinium and Wolbachia are found mainly in the reproductive tissues of a wide range of arthropods [ 1 – 3 ]. These bacteria can affect host reproduction via cytoplasmic incompatibility, parthenogenesis induction, male-killing and feminization of genetic males [ 4 – 10 ]. Similar to insects, mites may be colonized by intracellular bacteria, mostly by Wolbachia and Cardinium [ 11 , 12 ]. Hosts may be infected by a single bacterium or coinfected by multiple bacteria [ 8 , 13 – 18 ]. The double infections of Cardinium and Wolbachia are reported in several species of Bryobia [ 19 ] and Tetranychus [ 7 , 8 , 19 ]. In natural conditions, symbiotic, single and double-infected populations of the same Tetranychus species can exist in different geographical regions [ 20 ]. Despite that, no double-infected population for stored product mite Tyrophagus putrescentiae has been found. While single Cardinium and Wolbachia -infected populations of T. putrescientiae are known [ 21 ]. In manipulative experiments, the mixing of single Cardinium and Wolbachia in T. putrescentiae cultures resulted in double-infected cultures when Cardinium and Wolbachia co-occur in the same mite individuals [ 22 ]. However, the presence of Cardinium was negatively correlated with the presence of Wolbachia [ 22 ]. It indicates the competition among those symbionts, but the symbiont's mechanisms involved in such competition are not known on mite models yet. The intracellular symbionts of Sogatella furcifera [ 23 ] in both the single and double infection reduce bacterial diversity and change bacterial community structure (including bacterial corrections). In T. putrescentiae , the presence of Cardinium was negatively correlated with the presence of Wolbachia and Bartonella , while Bartonella and Wolbachia were positively correlated with each other [ 22 ]. The coexistence of Cardinium and Wolbachia symbionts leads to various interactions that are usually interpreted only via correlations in the context of their occurrence [ 16 , 24 ]. A few studies, however, have shown the functional effects of their coexistence [ 25 , 26 ]. Mite coinfection with multiple symbiont taxa is a complex system that leads to possible interactions between these symbionts and the host. Such systems lead to altered host physiological responses and survival [ 27 ]. Some studies did not confirm the competition of Cardinium and Wolbachia in the double-infested Thysanoptera host Pezothrips kellyanus [ 28 ]. Cardinium – Wolbachia coinfection can promote fat and amino acid synthesis in the small spider Hylyphantes graminicola [ 29 ], and the symbionts interact in methionine and fatty acid biosynthesis and biotin transport in Pratylenchus penetrans [ 18 ] or increase female fecundity but not longevity in Tetranychus truncatus [ 30 ]. This stands in contradiction to our preliminary results and observations of Cardinium and Wolbachia interactions in T. putrescentiae. Correlation studies of the T. putrescentiae microbiome showed that Cardinium and Wolbachia negatively interact [ 21 , 31 ]. Since mixed populations had lower abundances of Wolbachia , while the abundance of Cardinium did not change, we suggest that the presence of Cardinium inhibits the growth of Wolbachia . The previous study on Cardinium and Dermatophagoides farinae showed that the correlation between gene expression of host and symbionts identifies the most influenced host genes and pathways (i.e. endocytosis, phagocytosis, and apoptosis) [ 32 ]. The suggested interaction is due to the host immune/regulatory pathways. Intracellular bacteria and the host immune system balance two strategies to defend themselves against infections: resistance and tolerance. Resistance is the ability to clear the infection, while tolerance is the ability to reduce the fitness costs of infection without clearing the infection itself [ 33 ]. However, it is not clear which pathways (tolerance, resistance) are involved in the double-infested host. In another study, the manipulative experiments established double-infected S. furcifera [ 23 ]; the study confirmed the effect of symbionts on metabolites (e.g. arginine biosynthesis and nicotinamide metabolism). Cardinium in the single-infected line upregulated metabolic production, while Wolbachia in the double-infected downregulated them [ 23 ]. The model mite species T. putrescentiae is a pest found all over the world, known for causing damage to stored products [ 34 ] and pet foods [ 35 ]. It also produces allergens that can affect humans [ 36 , 37 ]. In experiments where the parental culture of T. putrescentiae was inhabited by either Wolbachia (5N, 5P) or Cardinium (5L, 5S), the resulting culture of stored product mites was double-infected and known as 5LP, 5LN, 5SP, or 5SN. The fitness of mites and their symbionts' composition were analyzed over 5 months in double-infected cultures. The genomes of both bacteria and the mite host were assembled to study Cardinium and Wolbachia interactions. Transcriptome analyses based on correlations between gene expression in single and multiple infected samples and between Cardinium and Wolbachia genes were conducted. Material and methods Single-infected cultures For the experiments, four cultures of Tyrophagus putrescentiae that were infected with either Cardinium or Wolbachia were used (refer to Table 1 ). The cultures were maintained at the Crop Research Institute in Prague, Czechia. The mites were kept in IWAKI 70 mL tissue culture flasks with a surface area of 25 cm2. These flasks were placed in Secador desiccators by Bel-Art Products, which maintained a relative humidity of 85% through a saturated KCl solution. The desiccators were kept in darkness and under controlled conditions of humidity (75% RH) and temperature (25 ± 1°C). The mites were fed a diet called SPMd, which consisted of wheat germ and Mauripan-dried yeast extract ( Saccharomyces cerevisiae ) in a 10:1 w/w proportion. The diet was mill-powdered, sieved (mesh size, 500 µm), and heated to 70°C for 0.5 h before being fed to the mites. Table 1 Cultures of Tyrophagus putrescenitae Cult. Symbiont Collector Year Site 5L Cardinium E. Zdarkova 1996 Grain, Bustehrad, Czechia 5S Cardinium A. Sala 2013 Food-producing factory, Cesena, Italy 5N Wolbachia J. Hubert 2007 Food-producing factory, St. Louis, MO, USA 5P Wolbachia T. W. Phillips 2014 Laboratory strain, Manhattan, KS, USA Table 2 The characteristics of Wolbachia and Cardinium genomes and Tyrophagus putrescentiae genome/transcriptome. genome/ trans. host strain size (bp) Compl. (%) Cont (%) Cover. Contigs GC (%) CDSs KEGG rRNA tRNA Cardinium T. putrescentiae this study 1,051,907 100 0 3541 55 38.9 882 498 3 34 T. putrescentiae JANAVR01 [ 80 ] 914,750 33 39.38 769 446 3 33 Sogatella furcifera NZ_CP022339 [ 79 ] 1,103,593 1 39.23 897 479 3 35 Oedothorax gibbosus NZ_OW441264 [ 81 ] 1,137,202 1 36.7 1046 623 3 35 Wolbachia T. putrescentiae this study 1,043,441 100 0 2118 26 34.5 974 532 3 33 T. putrescentiae GIJY0000000 # 910457 280 35.1 686 404 0 27 Fragariocoptes_setiger JAHRAF010000001 [ 83 ] 1,082,514 30 31.2 1101 573 3 39 Pentalonia_nigronervosa NZ_JACVWV01000004 [ 82 ] 1,457,187 182 34.1 1243 566 3 36 Tyrophagus this study 114,502,572 88 10,330 45.52 13,702 5.841 Double-infected cultures To create mixed cultures, we transferred 10 unsexed adults from a Cardinium -infected culture and another 10 from a Wolbachia -infected culture into a new flask. We made sure to have 5LN, 5LP, 5SN, and 5SP in each flask with 10 mites in every combination. For transcriptome analyses, we prepared 7 replicates, and for the rest of the analyses, we prepared 6 replicates. Each replicate was carried out in a separate flask that contained 0.3 g of SPMd. The flasks containing multiple-infected mites such as 5LN, 5LP, 5SN, and 5PS were stored in desiccators under the same conditions used for mite rearing. Every culture was renewed monthly, by transferring around 5,000 live mites from the cap or surface of the flask into a new flask containing 0.3 g of SPMd. The remaining mites in the parent flask were used for growth tests and DNA extraction. For DNA extraction, the mites were collected from the flask caps and surface, transferred into 70% ethanol, and stored in a freezer at − 40°C prior to extraction. The mites were re-transferred into a new flask every month. The sample of mites for gene expression analyses Both single and double-infected populations of mites were harvested after 42 days of cultivation for transcriptome and genome analyses. This corresponds to a mite culture with exponential growth, which is commonly used for allergenic extracts [ 38 , 39 ]. The preparation of transcriptome and genome samples was previously described [ 40 ]. Mites that were alive were collected from the surfaces of the flasks and plugs, using a brush, and placed into sterile Eppendorf tubes. The samples were weighed on a microbalance to obtain 30–40 mg of fresh weight. The samples for DNA extraction came from the polled mite cultures [ 21 ] and included three technical replicates. DNA extraction from single mite For DNA extraction mites were collected after 2, 3, 4 and 5 months of incubation. To extract DNA from a single mite, we followed the procedure below: Firstly, the mite was cleaned with washing ethanol and dried. Next, the mite was transferred into a 0.2 mL thin wall tube (Thermo Scientific™, cat no: AB0620) that contained 25 µL of DEP-25 START‐Blue reagent (cat no: D226). The tube was then heated to 95°C for 20 minutes using a C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA). After heating, the tube was cooled to room temperature and 25 µl of DEP-25 STOP solution was added and mixed by vortexing. This process was repeated for 30 individuals per child culture, and the resulting samples were stored in a freezer at − 40°C. RNA and DNA extraction All subsequent procedures with the mite samples were carried out on ice. Firstly, mites were surface cleaned using the following method: they were placed in a 100% ethanol solution and vortexed for 5 seconds, followed by centrifugation at 13,000 ×g for 1 minute. Then, the supernatant was replaced with a 1:10 solution of bleach (5% sodium hypochlorite) and ddH2O, vortexed for 5 seconds and centrifuged at 13,000 ×g for 2 minutes. Then, the cleaning solution was removed, the mites were washed in ddH2O, and the previous step was repeated. The mite samples were then homogenized in a glass tissue grinder (Kavalier glass, Prague, Czechia) in 500 µl of lysis buffer for 30 seconds. RNA extraction was performed using the NucleoSpin RNA kit (catalog no. 740984.50; Macherey-Nagel, Duren, Germany) with the following modifications: homogenized samples were centrifuged at 2,000 × g for 3 seconds and DNA was degraded by DNase I at 37°C according to the manufacturer’s protocol (Riboclear plus, catalog no. 313 − 50; GeneAll, Lisbon, Portugal). RNA quality was evaluated using a NanoDrop instrument (NanoDrop One; Thermo Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). First, the homogenates were incubated overnight with 20 µL of proteinase K at 56°C. DNA was then extracted using the QIAamp DNA Micro Kit (Qiagen, Hilden, Germany, cat. No. 56304) following the manufacturer’s protocol for tissue samples. The extracted DNA samples were quantified using a Qubit® dsDNA HS Assay Kit (Life Technologies). The quality of the DNA was determined using a NanoDrop 2000 instrument and the average size of the genomic DNA (gDNA) was determined using an E-Gel SizeSelect 2% Agarose Gel (Invitrogen) with a 1 kb ladder. Samples were sheared with a Covaris G-tube (Covaris Inc.) and the average size of the sheared DNA was determined using a TapeStation 4200 system (Agilent Technologies). The samples were then transported on dry ice to the MrDNA laboratory (Shallowater, TX, USA) for downstream processing and sequencing. Genome and transcriptome sequencing The RNA samples were adjusted to a volume of 30 µL, and the concentration of total RNA was determined using the Qubit® RNA Assay Kit by Life Technologies. To remove ribosomal RNA, 700 ng RNA samples were treated with the Ribo-Zero Plus rRNA Depletion Kit from Illumina. The rRNA-depleted samples were quantified, with RNA concentration ranging from 9.7 to 13.7 ng/µL, and used for library preparation using the KAPA mRNA HyperPrep Kits from Roche, following the manufacturer's instructions. After library preparation, the final concentration of all libraries ranged from 49.4 to 74.20 ng/µL, and the average library size was determined using the Agilent 2100 Bioanalyzer from Agilent Technologies. The libraries were then pooled in equimolar ratios of 0.6nM and sequenced in paired-end mode for 500 cycles with the NovaSeq 6000 system from Illumina. The reads were deposited in GenBank as projects PRJNA493156 and PRJNA990474 (Table S1 ). The concentration of DNA in the original sample was around 90 ng/µL, as measured with the Qubit® dsDNA HS Assay Kit from Life Technologies. The quality of the DNA was determined using the NANODROP 2000 from ThermoFisher Scientific. However, the 260/230 values were low (0.73), so the DNA was cleaned using the DNEasy PowerClean Pro Cleanup Kit from Qiagen. The sample was then sheared using the Covaris G-tube from Covaris Inc. The average size of the sheared library was determined using the Agilent 2100 Bioanalyzer from Agilent Technologies. 500 ng of the sheared DNA was used with the SMRTbell Express Template Prep Kit 2.0 from Pacific Biosciences. During library preparation, the sample underwent DNA damage and end repair, and barcode adapter ligation. After library preparation, final library concentration (about 33 90 ng/µL) was measured using the Qubit® dsDNA HS Assay Kit from ThermoFisher Scientific. Additionally, the average library size (8107 bp) was determined using the Agilent 2100 Bioanalyzer from Agilent Technologies. Finally, the library was sequenced using the 10-hour movie time on the PacBio Sequel from Pacific Biosciences. The libraries for Illumina sequencing were prepared using the Illumina DNA Prep Fragmentation library preparation kit, following the manufacturer's guidelines. 50 ng of DNA was used for library preparation. Fragmentation and adapter addition were performed simultaneously, followed by a limited-cycle PCR to add unique indices to the sample. Afterward, the libraries were pooled in equimolar ratios of 0.6 nM and sequenced paired-end for 500 cycles using the NovaSeq 6000 system from Illumina. The reads have been deposited in GenBank as project PRJNA988410 (Table S1 ). Processing of genome and transcriptome sequences The methods for read processing, genome and transcriptome assembly, and annotation were previously described [ 40 ]. Illumina reads were trimmed with Trim Galore [ 41 ] and analyzed using fastQC [ 42 ]. The reads were then mapped onto reference datasets using Bowtie2 [ 43 , 44 ], and Minimap2 [ 45 ] was used for long sequences. The reference datasets included Cardinium and Wolbachia genomes, as well as astigmatid mite genomes and transcriptomes available in GenBank. The mapped Illumina reads were de novo aligned with the PacBio reads using hybrid SPADES v3.14 [ 46 , 47 ]. The assembled genome was polished using Pilon [ 48 ]. Bacterial sequences were annotated by Prokka [ 49 ] using DFAST [ 50 ] on a web server and predicted proteins were identified by KEGG using GhostKoala [ 51 ]. Bacterial genome annotations were done in Prokka v1.14.6 [ 49 ] and visualized in Proksee [ 52 ]. The genome and transcriptome of T. putrescentiae were annotated using Funannoatate 1.8.15 [ 53 ] on the Galaxy server [ 54 ]. Predicted proteins were assigned to KEGG categories, and metabolic pathways were identified using a KEGG mapper [ 55 ]. Additional analysis was performed using an EggNOG Mapper [ 56 ]. The presence of predicted KEGG proteins was comapared in assemblaged and related KEGG proteins using Venn diagrams [ 57 , 58 ] (package ggVennDiagram in R version 4.3.1) [ 59 ]. Gene expression analyses of the novel bacterial symbiont were performed in CLC Workbench 22 (Qiagen, Venlo, Netherlands). The total numbers of mapped RNA reads were used for expression. Phylogenomic and molecular identification Genomic taxonomic analyses of Cardinium and Wolbachia were conducted by applying the MASH algorithm [ 60 ] in dRep [ 61 ] on the Galaxy server. The available genomes of Cardinium and Wolbachia were compared using this algorithm. Subsequently, the detection of open reading frames (ORFs), identification of orthologous groups, alignment of orthologous sequences [ 62 , 63 ], and inference of a Maximum Likelihood phylogenetic tree using RAxML with 100 bootstrap replicates [ 64 ] were performed using M1CR0B1AL1Z3R [ 65 ]. PCR reaction PCR reactions were carried out using master mix EmeraldAmp (catalogue number: RR310A, Takara Bio). The master mix contained an optimized buffer, PCR enzyme, dNTP mixture, gel loading dye (green), and a density reagent in a 2X premix format. Subsequently, ddH2O and primers were added to the mix. The amplification process was carried out using the C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA). The detection of Wolbachia WpF (5’-TTGTAGCCTGCTATGGTA-3’) and WpR (5’-GAATAGGTATGATTTTCA-3’) primers was done with the following amplification profile: initial denaturation at 94°C for 5 minutes, followed by 35 cycles of 95°C for 60 seconds, 52°C for 60 seconds, and 72°C for 60 seconds. The final extension was done at 72°C for 5 minutes. For the detection of Cardinium , we used the Card4 (5’-CTTAACGCTAGAACTGCGA-3’) and Card6 (5’-TCAAGCTCTACCAACTCC-3’) primers and conducted amplification with the following protocol: initial denaturation at 94°C for 5 minutes, followed by 35 cycles of denaturation at 94°C for 50 seconds, annealing at 56°C for 50 seconds, extension at 72°C for 60 seconds, and final extension at 72°C for 10 minutes. The reaction mixture contained 2 µL of DNA, 12.5 µL of EmeraldAmp master mix, 8.5 µL of ddH2O, and 1 µL of each 10 µM primer. We used a negative control with DNA replaced by ddH2O and a positive control with cloned DNA previously obtained by amplification of mite extracts using universal bacterial primers (F27 and 1492R) [ 66 ]. The PCR products were observed on a 1% gel using the GeneSnap (Syngene InGenius LHR2 Gel Imaging System; cat. no: 316616). For preparing the 1% gel, 1.5 g of agarose (Lonza SeaKem® LE 500 g, cat no: 50004, Lonza, USA) was mixed with 150 mL of buffer (ROTIPHORESE® Buffer 50 x TAE, cat no: R.CL86.2, Carl Roth, Germany). The agarose was dissolved in hot a buffer and then cooled down under constant stirring. After that, 8 µL of SYBR® Safe DNA Gel Stain (cat no: S33102, Invitrogen, USA) was added to the solution. The diluted SYBR® Safe DNA Gel Stain was made by using 10 µL of SYBR® Safe DNA Gel Stain and 90 µL of dimethyl sulfoxide - DMSO. The size of the products was measured using a 50 bp ladder (Generuler 50bp, cat no: SM0373, ThermoFisher Scientific). The amplification process was considered successful when the PCR products were visible and were the expected size. The asymbiotic mite individuals were identified based on the presence of the product from universal bacterial primers, and the absence of the product from Cardinium and/or Wolbachia primers. Mite growth test It was hypothesized that there is a strong correlation between an increase in the number of mites and an increase in their fitness levels [ 67 ]. The population growth of the original double-infected stock cultures was measured at two-month intervals. The first growth test was established after 2 months of incubation. Mites were collected from the plugs and surface of rearing flasks and then transferred to separate Petri dishes. The controls consisted of a single-infected population. Ten unsexed adult mites were moved from a Petri dish to new flasks that contained 0.01 ± 0.005 grams of SPMd. The flasks were kept under controlled conditions. After 21 days, the experiment ended, and mites were counted using a dissection microscope [ 68 ]. Statistical analyses The transcriptome reads data were analyzed unstandardized and standardized by recalculation to the samples with the lowest number of reads, as previously described for amplicon sequencing analyses[ 69 ]. The effect of single and multiple-infected cultures on bacterial and genome expression was evaluated using unstandardized data. The data were analyzed with the nonparametric Mann–Whitney test in PAST 4 [ 70 ]. Two datasets for each taxon were compared, the whole predicted gene expression and the KEGG-assigned gene expression. Two correlation analyses were conducted. Firstly, distance-based redundancy analyses (dbRDA) were used to test the correlation between the expression of the predicted genes and selected factors such as mite culture and symbiont presence. The analyses were performed using the vegan package [ 71 ] in R version 4.3.1. In the models, we compare the dataset as “dependent-gene expression” and “independent-environmental variables” [ 72 ]. The next analysis used gene expression data from bacteria or mites as dependent and independent variables interchangeably [ 32 ]. We calculated the dbRDA using Bray–Curtis distance for standardized data or Robust Atkinson distance for unstandardized data. In order to identify the variables with the highest influence on the model, we used forward variable selection with the ordistep function [ 73 ]. The selected environmental variables were added to new models, and their significance was tested using Monte Carlo permutation tests in the vegan package. We selected the models with the best predictive power based on their explained variability (R2). The final RDA models were visualized using triplots in the vegan package. Secondly, we calculated the correlation among Cardinium , Wolbachia , and mite genome expression datasets independently using Sperman correlation coefficient and bootstrap permutational P values in PAST. Only the correlations with P < 0.05 were included in the heatmap. We constructed the correlation heatmaps using the ComplexHeatmap package [ 74 , 75 ] and clustered them using Ward distance or K-mean (in PAST) clustering for the interaction among symbionts and predicted mite KEGG gene expression in separate pathways. In case of a high number of comparisons, we selected the gene expression based on outliers in the position of the first two axes in dbRDA models. We visualized the numbers of correlations among symbionts and mite genes using the scaterplot3d package [ 76 ] in R. To compare the differences in the expression of the predicted proteins, we first standardized the data for each data set separately. Then, we converted it to a shared file and analyzed it using the METASTATS function [ 77 ] in MOTHUR v.1.48 [ 78 ]. The results were visualized as volcano plots. To construct the abundance heatmaps, we followed the same protocol as for the correlations heatmap. Finally, we used PAST to perform Kmeans clustering. Results Double-infected cultures have reduced fitness when Wolbachia is present The final mite numbers after 21 days of T. putrescentiae population growth showed significant differences among single and double-infected cultures (Kruskal–Wallis test: H(chi 2 ) = 86.27, P < 0.001) (Fig. 1 A). The number of mites at 5S and 5N was twofold high than at 5L in single-infected cultures. The mite population in double-infected cultures decreased 5-fold after 2 and 4 months, indicating lower fitness compared to single-infected cultures. However, after 6 months of cultivating double-infected cultures, the population numbers reached the same density as single-infected cultures (Mann–Whitney pairwise: 5LN, 5L (P = 0.066), 5N (P = 0.066); 5SP, 5P (0.69), 5S (P = 0.47); or the density was twice as high as it was in 5SN (Mann–Whitney pairwise 5S (P = 0.008), 5N (P = 0.005)). The exception occurred in the 5LP culture when the density was two-fold lower (Whitney pairwise: 5L (P = 0.008), 5P (P = 0.005)). The proportion of mites that were infected by bacteria varied significantly between different cultures (GLM: Chi = 33.408, P < 0.001), decreased from 5L, 5S, 5N to 5P and Cardinium - infected higher number of mites than Wolbachia (GLM: Chi = 19.482, P < 0.001) (Fig. 1 B). The percentage of Cardinium infection in double-infected mites increased from 50–95% over time (Fig. 1 B). There were no significant differences observed among the cultures (GLM time: Chi = 62.011, P < 0.001; culture: Chi = 56.011, P = 0.153; interaction: Chi = 31.058, P < 0.001). Differently, Wolbachia infection disappeared (GLM time: Chi = 106.180, P < 0.001; culture: Chi = 51.406 P < 0.001; interaction: Chi = 44.241, P = 0.066) in all multi-infected cultures. In the double-infected cultures, only a small proportion of individuals (up to 20%) were infected with both Cardinium and Wolbachia . However, this proportion decreased over time during the cultivation of double-infected cultures (as shown in Fig. 1 C). Additionally, the cultures also contained a small proportion of mites without bacterial symbionts (asymbiotic), ranging from 0 to 30% of individuals. Wolbachia and Cardinium genomes The characteristics of annotated Cardinium and Wolbachia genomes (JAUEML000000000): are shown in Table 1 and Fig. S1 and Table S2. Average nucleotide identity (ANI) analysis revealed that Cardinium from T. putrescentiae is closely related (forms a sister group) to Cardinium of S. furcifera [ 79 ]. Our genome is very similar to the Cardinium genome from Chinese strain of T. putrescentiae (JANAVR01) [ 80 ] (Fig. S2). These results are supported by a comparison of open reds frames (Fig. S3) using M1CR0B1AL1Z3R pipeline [ 65 ]. It was found that both genome assemblages of Cardinium obtained from T. putrescentiae shared 73% of predicted KEGG genes (375 KEGG proteins). However, it was observed that 2% of predicted KEGG genes were unique to JANAVR1 and 7% were unique to the Cardinium genome assemblage. Altogether, 64% of predicted KEGG genes were shared among all Cardinium , in comparison to the assemblages of Cardinium found in S. furcifera [ 79 ] and Oedothoraz gibbosus [ 81 ]. The Wolbachia genome assembled from T. putrescentiae (Table S3) clustered with Wolbachia from Pentalonia nigronervosa [ 82 ]. The next similar Wolbachia strain was the one found in the Fragariocepes setiger mite [ 83 ] and Chironomus riparius , as confirmed by comparing open reds frames with the M1CR0B1AL1Z3R pipeline [ 65 ] (Fig. S5A). The newly assembled Wolbachia genome has similar numbers of ORF and GC contents as the average known Wolbachia strain (Fig. S6). These findings were supported by an analysis of average nucleotide identities (ANIs) (Fig. S5B). The genome assembly is similar to the previously deposited assembly of Wolbachia from T. putrescentiae (GIJY000000), except that it is incomplete due to the absence of 16S and 23S rRNA. However, there is a difference of 3% (N = 12) in the predicted KEGG genes between this genome assembly (GIJY000000) and the Wolbachia assembly in this study. On the other hand, 20% of the predicted KEGG genes in the Wolbachia assembly of this study were not present in the previously deposited assembly GIJY000000. Among 10 complete KEGG modules, the lipolic acid biosynthesis was identified in Cardinium , while Wolbachia showed 6 complete KEGG modules and no complete vitamin pathway was found. Tyrophagus putrecentiae genome and transcriptome The characteristics of T. putrescentiae genome (SUB13579704) are shown in Table 1 . The transcriptome contained 5,838 KEGG annotated proteins, which forms 66 complete KEGG modules (Table S4). Among them the mites are able to synthesize pantothenate, tetrahydrobiopterin, molybdenum cofactor, C1-unit interconversion and heme. The entire metagenome of the mite, which includes both bacterial symbionts and the mite itself, contained 80 complete KEGG modules. The decrease of Wolbachia reads in the transcriptome of double-infected cultures The predicted number of expressed gene (Fig. 1 D) was different between single and double-infected cultures of T. putrescentiae (U = 82, P < 0.001), however the mean values were 10 6.9 and 10 7.1 , respectively. The gene expression was found to be similar in both the single and double-infected mite culture for Cardinium (U = 173, P = 0.551) and ranged between 10 3 and 10 4 per sample. There was a significant 10-fold decrease in Wolbachia gene expression in multiple-infected samples compared to Wolbachia -infected samples (U = 0, P < 0.001). The expression of predicted Cardinium and Wolbachia proteins differ between hosts with double and single infestations In this study, we focus on two different analyses: (i) the correlation analysis with the presence/absence of symbionts mono or double infection. It enables the identification of up-or down-regulated genes globally; (i.e Table 3 , models 1–4, 7, 8; Table 4 , models 1 and 13) (ii) correlation analyses between host and symbiont genes can identify genes that are downregulated by some genes and upregulated by others. (e.g. Table 3 , models 5–6, 9–18, Table 4 , models 2–12 and 14–23). Table 3 The correlation-based models of Cardinium , Wolbachia and their host T. putrescentiae gene expression in the samples form symbiont single and multi-infected. The distance-based redundancy analyses (dbRDA) were calculated from different datasets in Bray–Curtis distance. The datasets included predicted genes, genes assigned to KEGG and the presence/absence of symbionts in single and multi-infected mite cultures. id. Dependent variable Indeppendant variable df F P R2 1 Cardinium _gene total 3 27.80 0.001 0.687 Wolbachia _presence 1 52.41 0.001 0.567 Wolbachia strain 2 28.24 0.001 0.592 Cardinium _strain 1 4.22 0.019 0.095 2 Cardinium _KEGG total 3 13.80 0.001 0.521 3 Wolbachia _gene total 3 7.70 0.001 0.378 Cardinium _presence 1 12.11 0.001 0.232 Wolbachia strain 1 0.71 0.611 0.017 Cardinium _strain 2 11.01 0.001 0.361 4 Wolbachia _KEGG total 3 9.52 0.001 0.429 5 Cardinium _gene Wolbachia _genes 15 2.93 0.001 0.786 6 Wolbachia _gene Cardinium _gene 18 2.79 0.001 0.848 7 TP_gene total 3 53.75 0.001 0.688 8 TP_KEGG total 3 39.68 0.001 0.620 Wolbachia _presence 1 7.06 0.003 0.086 Cardinium _presence 1 1.50 0.226 0.020 double_infection_presence 1 14.18 0.001 0.159 9 TP_KEGG Wolbachia _genes (single) 8 32.61 0.001 0.981 10 TP_KEGG Wolbachia _genes (double) 22 99.62 0.001 0.997 11 TP_KEGG Cardinium _genes (single) 6 7.15 0.001 0.860 12 TP_KEGG Cardinium _genes (double) 21 77.40 0.001 0.996 13 TP_KEGG Cardinium / Wolbachia _genes 19 66.63 0.001 0.994 14 Wolbachia _genes (single) TP_KEGG 4 4.03 0.001 0.548 15 Wolbachia _genes (double) TP_KEGG 13 3.14 0.001 0.745 16 Cardinium _genes (single) TP_KEGG 4 2.94 0.001 0.566 17 Cardinium _genes (double) TP_KEGG 11 3.83 0.001 0.725 18 Cardinium / Wolbachia _genes TP_KEGG 12 3.12 0.001 0.714 Table 4 The correlation-based models of Cardinium , Wolbachia and their host T. putrescentiae gene expression in the samples form symbiont single and multi-infected. The gens were selcted to be involved in mite immune and regulatory pathways or metabolism. The distance-based redundancy analyses (dbRDA) were calculated from different datasets in Robust Aitkinson distance. The datasets included predicted genes, genes assigned to KEGG and the presence/absence of symbionts in single and multi-infected mite cultures. id. Dependent variable Indeppendant variable df F P R2 1 mite_Pathway_KEGG total 8 5.68 0.001 0.401 Wolbachia _presence 1 11.67 0.001 0.135 Cardinium _presence 1 4.18 0.001 0.053 double_infection_presence 1 2.69 0.002 0.035 2 Wolbachia _genes (single) mite_Pathway_KEGG 11 3.16 0.001 0.584 3 Wolbachia _genes (double) mite_Pathway_KEGG 11 3.16 0.001 0.685 4 Cardinium _genes (single) mite_Pathway_KEGG 3 3.09 0.001 0.481 5 Cardinium _genes (double) mite_Pathway_KEGG 8 4.23 0.001 0.641 6 Cardinium / Wolbachia _genes mite_Pathway_KEGG 10 2.95 0.001 0.635 7 Wolbachia _genes (double mite_Pathway_KEGG + Cardinium 13 3.417 0.001 0.760 8 Cardinium _genes (double) mite_Pathway_KEGG + Wolbachia 9 1.924 0.001 0.491 8 mite_Pathway_KEGG Wolbachia _genes (single) 9 36.29 0.001 0.988 9 mite_Pathway_KEGG Wolbachia _genes (double) 19 18.31 0.001 0.959 10 mite_Pathway_KEGG Cardinium _genes (single) 19 18.31 0.001 0.978 11 mite_Pathway_KEGG Cardinium _genes (double) 18 19.75 0.001 0.975 12 mite_Pathway_KEGG Cardinium / Wolbachia _genes 14 19.05 0.001 0.954 13 mite_Metabolism_sumKEGG total 8 12.87 0.001 0.602 Wolbachia _presence 1 6.08 0.001 0.075 Cardinium _presence 1 3.32 0.004 0.042 double_infection_presence 1 19.49 0.001 0.206 14 Wolbachia _genes (single) mite_Metabolism_sumKEGG 2 1.58 0.001 0.224 15 Wolbachia _genes (double) mite_Metabolism_sumKEGG 6 2.53 0.001 0.420 16 Cardinium _genes (single) mite_Metabolism_sumKEGG 2 1.69 0.001 0.235 17 Cardinium _genes (double) mite_Metabolism_sumKEGG 4 2.29 0.001 0.284 18 Cardinium / Wolbachia _genes mite_Metabolism_sumKEGG 2 2.79 0.001 0.183 19 mite_Metabolism_sumKEGG Wolbachia _genes (single) 8 14.41 0.001 0.958 20 mite_Metabolism_sumKEGG Wolbachia _genes (double) 14 5.55 0.001 0.857 21 mite_Metabolism_sumKEGG Cardinium _genes (single) 3 3.39 0.001 0.744 22 mite_Metabolism_sumKEGG Cardinium _genes (double) 4 6.63 0.001 0.919 23 mite_Metabolism_sumKEGG Cardinium / Wolbachia _genes 19 7.33 0.001 0.946 The standardized transcriptome data revealed differences in predicted gene profiles of Cardinium and Wolbachia between single and double-infected host populations (Fig. 2 ). (Tables S2 and S3). The expression of Cardinium genes was affected by the presence of Wolbachia . There were differences between single- and double-infected cultures (Table 3 , Table S5). The gradient along the x-axis in dbRDA triplots was visible. (Fig. 2 ). There were differences in Cardinium single-infected cultures between 5S and 5L mite cultures, and the gradient was visible on the y-axis in dbRDA triplot. (Fig. 2 ). The gene expression in Wolbachia was found to be different in single-infected and double-infected host cultures. However, the dbRDA models explained less variability in Wolbachia compared to Cardinium . It was surprising to find that Cardinium from the 5S and 5L cultures affected the expression of Wolbachia genes differently, as evidenced by the sample positions along the y-axis. The number of genes present in Cardinium was six times higher than that of Wolbachia . Additionally, the expression of Cardinium was higher in the samples that were double-infected (200 Cardinium and 30 Wolbachia ). The number of genes that had decreasing expression in the double-infected samples were 9 for Cardinium and 31 for Wolbachia , which was comparatively low for both bacteria. (Fig. 3 A). Genes associated with reproduction and cell growth were over-expressed in Cardinium and Wolbachia (Tables S6–S8). The correlation analyses of predicted gene expression (Fig. S8) revealed positive correlations between clusters of Cardinium genes c1 and c2 and w1 and w2 Wolbachia genes, and negative correlations with w3 genes. In addition, Wolbachia clusters w1 and w2 had negative correlations to Cardinium c3 cluster. It provided 102 Cardinium and 250 Wolbachia genes. These genes showed 30% negative and 70% positive (N = 3793) correlations (Table S9). The effect of Cardinium and Wolbachi a on the expression of predicted KEGG genes in T. putrescentiae differs between single and double-infested hosts When comparing the expression of mite genes with KEGG assigned genes (Table 3 , models 9 and 10), the expression of KEGG genes explained almost twice as much variability. Using KEGG-assigned gene expression, we found that the presence of Wolbachia strongly influenced the expression of mite proteins. (Table 3 , model 8). In comparison to Wolbachia , the effect of Cardinium on mite expression was four times lower. ANOSIM analyses showed a similar trend for mite protein assigned to KEGG (One-way Permanova: F = 45.51, P < 0.001). Based on pairwise comparison, the expression of the mite KEGG gene was found to be similar between Cardinium and multiple infested samples (P = 0.9654). This indicates that Cardinium's presence had the same effect on the expression of the mite gene in both single and double-infected cultures. However, Wolbachia did not show the same response, and its genes were affected differently in double-infected cultures. The mite predicted KEGG gene expression (Table S5) showed differences across the cultures (Fig. S9). When comparing all mite cultures, the dbRDA triplot was able to separate the Wolbachia single-infected cultures (5N and 5P) from Cardinium and double-infected cultures based on their x-axis values. While y axes separated double-infected cultures from those without symbionts (5K, 5Tk,5Pi) and single Cardinium -infected cultures (5L and 5S). However, there was no difference in mite gene expression between Cardinium single-infected cultures and asymbiotic cultures (5K, 5Tk and 5Pi) [ 21 ]. The contribution of Cardinium as a variable was insignificant compared to Wolbachia and double-infected cultures in explaining variability. When the mite expression gene was analyzed in the symbiotic cultures, the x axes separated Wolbachia from Cardinium and double-infected cultures. Interestingly, the cultures infected with Cardinium were separated by y axes, and the MDS1 axe was not explained by the dbRDA model. This suggests that the Cardinium present in 5L and 5S had different interactions with the mite KEGG gene expression in single and double-infected cultures (5SP, 5SN versus 5LP and 5LN). The correlation analysis revealed a strong correlation between Wolbachia and predicted mite KEGG genes. The highest number of correlations was observed between the expression of Wolbachia genes and predicted mite KEGG genes in single-infected cultures (Fig. 6 ). It is also illustrated by differences in KEGG predicted gene expression values among the cultures. The heatmap (Fig. S10) confirms correlation analyses, showing a remarkable cluster of highly expressed KEGG genes in Wolbachia -infected cultures, i.e., kelch-like protein 28, serine carboxypeptidase, vacuolar ATPase assembly integral membrane protein VMA21, phagosome associated transport protein, pre-mRNA-processing factor 39 and fluor threonine transaldolase. In double-infected cultures, the number of correlations between Wolbachia and mite gene expression decreased by 5 times. On the other hand, in single-infected cultures, the number of correlations between Cardinium and mite gene expression was 2 times lower than those between Wolbachia and mite gene expression. In double-infected cultures, the number of negative correlations increased up to 80% (Fig. 4 ), compared to single-infected cultures. This was illustrated by the heatmap of mite predicted KEGG gene expression, where these genes did not form any cluster characterized by high expression in Cardinium single or double-infected cultures (Fig. S10). The comparison of correlation numbers between symbionts and mite gene expression (Fig. 3 B) showed that Wolbachia had a higher number of correlations with a lower number of downregulated genes (such as ARHGEF1, pdxJ, ZapA, and TRP75). On the other hand, Cardinium had the highest number of correlations with upregulated genes, as there were 9 downregulated genes (Table S9). The effect of symbiont on mite immune and regulatory pathways and metabolisms in single and double-infected cultures The presence of symbionts in single and double-infected cultures affected the expression of mite KEGG genes in host immune and regulatory pathways similarly to all other KEGG genes (One-Way Permanova: F = 46.43, P < 0.001). The presence of Wolbachia has a greater influence on the pathways compared to Cardinium. This trend is consistent with all KEGG assigned protein expressions. In the correlation triplot, the distribution of KEGG genes indicated that the first axis separated Cardinium from the double-infected samples. The second axis in the triplot separated Wolbachia from Cardinium and Cardinium / Wolbachia double-infected samples (Fig. 5 A). In addition, the separation of the samples from 5S and 5L cultures is apparent as well. Among 826 KEGG genes involved in immune and regulatory pathways 104 were identified as outliers (Table S12). The symbiont genes have a greater influence on mite immune and regulatory pathways than mite proteins from those pathways have on symbiont genes (Fig. 6 ). Partial dbRDA modules clearly show a high influence (R 2 0.55–0.99) of symbiont to mite regulatory pathway' to (Table S11). In opposite analyzes, when mite regulatory pathways effect to symbiont gene expression was analyzed, the explained variablity of the models is lower (R 2 0.12–0.57). It indicates that symbionts expression is influenced by more factors not only by mites’ regulatory pathways. In single-infected cultures, the expression of mite immune and regulatory pathway genes was more affected by Wolbachia genes than Cardinium genes. The independent factor variability explained by Wolbachia gene ranged from 0.84 to 0.99 (with a mean R 2 of 0.93), while for Cardinium genes it ranged from 0.54 to 0.95 (with a mean R 2 of 0.78). The multiple infections resulted in the models using mite immune and regulatory pathways as dependent variables, when was two- or three-fold higher numbers of symbiont genes selected as independent variables in the models (Fig. 6 ). The interpretation is that the interactions are more diversified, as the results of higher number of positive/negative correlations. Phagosome, p53, JAK-STAK, Hedgehog, TGF-beta, mitophagy, apoptosis and phosphatidylinositol signaling pathways exhibited high explained variability due to symbiont genes in both single and double-infected cultures, suggesting their impact on these pathways. It is surprising that a single Cardinium infection did not show any correlation with one-third of the pathways (e.g. endocytosis, ubiquitin mediate proteolysis, autophagy), but it changes with the double-infected cultures (Fig. 6 ). The identified outliers (Table S11) from mite KEGG proteins are listened in Table S12 and their correlations to symbionts outliers in Table S13. In the single-infected cultures Cardinium showed the highest numbers of correlations (Tables S11–S13) with KEGG proteins associated to lysosome (CTSL), PI3K-Akt (HSP90A) and Ras (RALGAPA). While in double-infected cultures the highest correlation numbers showed protein kinase PRKAA and TSC2 (6 and 7 pathways), ECH1 (Peroxisome) and MYL3 (Apelin). The results indicate that the single-infected Wolbachia had the highest number of correlations to LRP5_6 (2 pathways) and CLTC and KIF5 (lysosome and endocytosis), tubulins (phagosome and apoptosis). The lysosomal associated proteins (CD107, CTSF) showed the highest level of correlation with Wolbachia in the double-infected culture. Next, proteins were associated with ubiquitin-mediated proteolysis (UBE2R), peroxisome (PHYH and ECH1), Phospholipase D (AGPAT3_4) and Apelin (MYL3) signaling pathway. The mite cultures exhibited differences in the expression of genes assigned to 61 metabolic pathways (Table S14, Fig. 5 B). In single-infected cultures, the following pathways showed a 10-fold higher expression in Wolbachia -infected cultures compared to Cardinium -infected cultures: Citrate cycle, beta-oxidation, N-glycan precursor trimming and Fatty acid elongation in mitochondria. The same pathways were responsible for differences between Wolbachia -infected and double-infected cultures (Table S14). The presence of Wolbachia and/or Cardinium in single and double-infected cultures explained 30% of the total variability in dbRDA (Table 4 ). The first axis in the triplot separates single and double-infected cultures of Wolbachia while the second axis separates Wolbachia and Cardinium cultures. (Fig. 5 B). It is difficult to distinguish between Cardinium double-infected culture 5SP and both asymbiotic and Cardinium -infected cultures. Similarly, Cardinium single-infected cultures cannot be distinguished from asymbiotic cultures. This suggests that the presence or absence of symbionts has minimal impact on mite metabolism in relation to Cardinium . When the symbiont gene expression was added to partial models (Table 3 ), the gene expression of Cardinium or Wolbachia in single and double-infected cultures explained up to 99% of the variability in the mite metabolic pathway (Table 4 , models 8–12). Although up to 64% of the variability in symbiont gene expression can be explained by mite metabolic pathway expression (Table 4 , models 2–8). It appears that symbionts have a strong influence on mite metabolism, while also being influenced at a lower level by mite genes. Based on dbRDA models, outliers were identified among expressions of Cardinium and Wolbachia genes, with 71 and 74 outliers respectively (Table S15). The numbers of positive and negative Spearman correlations to mite immune, regulatory, and metabolic pathways in both cultures and other symbiont gene expression in double-infected cultures revealed different clusters of the genes. The analysis revealed different clusters of genes with positive and negative Spearman correlations to mite immune, regulatory, and metabolic pathways in both cultures, as well as other symbiont gene expressions in double-infected cultures. Wolbachia and Cardinium genes were clustered using the K-means method, identifying 9 and 5 clusters, respectively (Table S15). Cardinium cluster was formed by genes with a high number of positive correlations to mite immune, regulatory, and metabolic pathways in double-infected cultures and to Wolbachia . The cluster was formed by the genes of an unknown function. The opposite situation, i.e., negative correlation to above mentioned showed the genes from 2 and 3 Cardinium clusters. It included proteins associated with DNA replication (DNA repair proteins RadC, resolvase) and proteins of possible virulence function virulence-associated proteins virE, leucyl aminopeptidase CARP. The 4 cluster represents proteins with high numbers of interaction with Wolbachia but not mites (e.g., possible receptor function C9 antigens, LolA). The last cluster 5 contains proteins with prevailing positive interaction with Wolbachia (i.e., transposases: YhgA, K07486, K07497, K07484, K07497). Wolbachia cluster 1 was associated with a positive correlation to mite in both single and double-infected cultures and both positive and negative correlations were associated to Cardinium genes. Both single and double-infected cultures showed a positive correlation between Wolbachia cluster 1 and mite. Cardinium genes were associated with both positive and negative correlations. These proteins are involved in genetic information and processes, while other proteins serve as surface antigens (Surface_Ag_2). The clusters 2 and 3 were formed by two and three proteins with various correlations to mite immune and regulatory processes and Cardinium . Cluster 4 included proteins (e.g., Zapa, transmembrane proteins) with negative correlations to mite metabolism and Cardinium . Cluster 5 contained proteins with positive correlations to mite regulatory, immune, and metabolic proteins in double-infected cultures and a positive correlation to Cardinium (mainly polymerases). Cluster 6 was formed by proteins with a negative correlation to mite immune, regulatory proteins and metabolism in single-infected cultures (e.g. outer membrane protein). Cluster 7 included those with positive correlations to Cardinium only (e.g. miaB, phage proteins). Cluster 8 included proteins with high numbers of positive and negative correlations to Cardinium only (e,g, A-kinase anchor protein 18 and DeoC/LacD family aldolase). Cluster 9 consists of proteins that predominantly exhibit negative correlations with Cardinium (e.g. DJ-1/PfpI and addA ). Discussion The mite fitness and symbiont competition in double-infected cultures This study manipulated T. putrescentiae mite cultures to prepare double-infected Wolbachia and Cardinium from single-infected parental cultures. Our previous experiments showed that Cardinium decreased the level of Wolbachia by 2.7 times in double-infected T. putrescentiae microbiome based on pooled mite samples [ 22 ]. A study found that the density of Wolbachia , measured as the number of unstandardized reads per sample, decreased in cultures with double infection, but the density of Cardinium was unaffected. This finding is consistent with a previous study on mite T. piercei , which measured symbiont density using qPCR. In mites that were infected with both Wolbachia and Cardinium , the density of Wolbachia was found to be lower compared to those infected with Wolbachia alone. This finding is consistent with results obtained in Tetranychus . On the other hand, the density of Cardinium in females infected with Wolbachia and Cardinium was not significantly different from that in females infected with Cardinium alone [ 8 ]. It has been observed that Tetranychus species infected with both Cardinium and Wolbachia have similar prevalence rates of these symbionts [ 14 ]. This suggests that they may be facilitating each other. However, there have been cases where Wolbachia was more prevalent than Cardinium in double-infected P. kellyanus . Still, the removal of Wolbachia did not affect the density of Cardinium in the host [ 28 ]. This indicates that Cardinium is not dependent on the presence of Wolbachia , but the presence of Cardinium influences the density of Wolbachia . Previous research has shown that when the planthopper S. furcifera is infected with both Cardinium and Wolbachia , its fecundity is reduced compared to when it is infected with only Cardinium [ 23 ]. This finding is consistent with our own observations. We found that mite population growth was much lower in double-infected cultures, which is in line with previous studies on double-infected T. putrescentiae cultures. After six months, the mite population grew substantially and became equal to the parental cultures, while Wolbachia disappeared from the double-infected cultures. It is believed that the disappearance of Wolbachia from the culture was caused by stochastic effects, specifically random genetic drift [ 84 ]. Some populations lost the Wolbachia infection due to a low initial symbiont infection frequency or the presence of only a few individuals. Additionally, it is suggested that the fixation of Cardinium observed in the double-infected cultures was mainly due to CI [ 84 ], rather than the fitness effects of this symbiont and/or drift. The disappearance of Wolbachia infection in multiple Tetranychus mites ( Cardinium , Rickettsia ) after only six months of laboratory rearing was attributed to differences in host genotypes [ 84 ]. Our data shows a significant decline in fitness when both symbionts coexist in double-infected cultures. There could be various reasons for the difference in fitness, such as the cost of symbionts' presence during host development, the cost of feminizing effect on host development based on mothers' infection status, or differences in host genotypes between single-infected and double-infected individuals [ 85 ]. The presence of Cardinium – Wolbachia or Wolbachia – Wolbachia -infected individuals can have various effects on fitness. In some populations, multiple Wolbachia strains can be present and stable within host populations, with double infections resulting in higher fitness than single infections [ 28 , 86 ]. For instance, Cardinium increased female production in P. kellyanus by improving maternal fitness and egg size, leading to higher fertilization rates and offspring fitness. However, Wolbachia reduced the beneficial effects of Cardinium [ 87 ]. In Bemisia tabaci , co-infection of Cardinium and Wolbachia induced male killing and resulted in a higher female sex ratio [ 88 , 89 ]. The presence of Wolbachia in a host did not show any survival benefits for the wasp Encarsia inaron that had the Cardinium infection. When doubly infected individuals were compared to uninfected wasps, there was no significant difference in reproduction observed [ 90 ]. In the parasitoid wasp E. inaron , Wolbachia caused cytoplasmic incompatibility (CI) and manipulated host reproduction, whereas Cardinium did not. In the case of butterfly Eurema hecabe , growth rates evaluated by development time were found to be slower in progenies of Wolbachia double-infected mothers than in those of single-infected mothers. Cardinium and combined Cardinium and Wolbachia infections led to a reduction in bacterial diversity, alteration of bacterial community structure, and metabolic changes, which may have negative fitness effects on the host [ 23 ]. It is currently unknown whether cytoplasmic incompatibility exists for T. putrescentiae infections. Experimental cultures still contained single Wolbachia , Cardinium , and asymbiotic mites, as Cardinium / Wolbachia -infected individuals accounted for up to 20% of all mites. The fitness changes due to different genotypes should be permanent and not temporary. Our data showed significant differences in gene expression, which are connected to the number of Wolbachia in single and double-infected mites. We used nonparametric statistics to eliminate the artifacts of different read numbers among samples. The analysis of correlation in single-infected cultures showed that Wolbachia has a more established interaction than Cardinium Cardinium has a biosynthetic pathway for lipoic acid that enables it to provide lipoate, but not biotin, to mite D. farinae [ 32 ] and T. putrescentiae . Meanwhile, the study found that Wolbachia did not possess a complete vitamin pathway, indicating that it did not provide any new nutrients to the mite. However, other studies have reported that Wolbachia from planthoppers such as Laodelphax striatellus and Nilaparvata lugens can provide biotin and riboflavin [ 91 ]. Recent genome analyses have shown that the provisioning of vitamins and nutrients is more complex than previously thought [ 92 ]. As a result, nutrient provisioning cannot be solely explained by observed correlations. A recent study has found that Wolbachia and Cardinium manipulate host immune, regulatory pathways and hormone production to aid their own uptake as well as transmission [ 93 – 95 ]. In this study, we conducted two different analyses. The first one was a correlation analysis which involved determining the presence or absence of symbionts. This analysis was similar to the ones mentioned earlier and it helped us to identify genes that were globally up or down-regulated. The second analysis involved correlation analyses among symbiont and host genes. This helped us to identify genes that were downregulated by one group of genes and upregulated by other genes. Transcriptome analyses of mite T. putrescentiae revealed that Wolbachia gene expression interacts more with host genes than Cardinium , as shown in the correlation model (Table 3 , models 9–10). It indicates Wolbachia manipulates host genes more than Cardinium in single-infected mite cultures. When opposite models are used, the mite genes manipulate the expression of Wolbachia and Cardinium at similar levels (Table 3 , model 16–20). When opposite models are used, the mite genes control the expression of Wolbachia and Cardinium at similar levels (Table 3 , models 16–20). Proteome analyses revealed that Cardinium infection in B. tabaci upregulated proteins related to immune response (e.g. Calcium, p53, cGMP-PKG signal pathways and apoptosis) and energy metabolism (lipid transport, acyl CoA metabolic processes and biosynthesis) [ 96 ]. While Cardinium was found to downregulate the spliceosome and endocytosis of the host in a study [ 96 ]. The transcriptomic study of Cardinium in Encarsia suzannae identified highly expressed genes involved in manipulating ubiquitination, apoptosis, and host DNA [ 97 ]. The expression levels of ubiquitin-related genes were higher in Cardinium -infected B. tabaci compared to uninfected strains [ 98 ]. Autophagy, ubiquitin-mediated proteolysis, and lysozyme are among the Wolbachia -influenced pathways. Autophagy, which is an intracellular defence mechanism, regulates the size of Wolbachia populations in host tissues [ 99 ]. The following study found that maintaining Wolbachia titer requires fully functional host ubiquitin and proteolysis pathways on an intact host endoplasmic reticulum (ER) [ 100 , 101 ]. Wolbachia increases the expression of lysosome-associated proteins and modulates the Toll/IMD pathway [ 95 ]. These studies involve manipulating protein or transcript levels. Our analyses indicate that symbionts affect p53, JAK-STAK, NF-kappa beta signalling pathways and phagosome in single-infected cultures. In our study, we evaluated the importance of pathway interaction by using the explained variability in the correlation model as a criterion. There are several pathways that regulate Wolbachia , including the HIF-1, TOOL signaling, Lysozome, Mitophagy, and Apoptosis pathways. Wolbachia is transmitted through oocytes [ 102 ]. During cell division, it is selectively passed on to the daughter cell with a larger microtubule organizing center by using dynein and dynactin for transportation [ 103 ]. Wolbachia uses dynamin- and clathrin-mediated endocytosis to enter host cells [ 102 ]. However, it may also use other pathways of entry [ 102 ]. One study found no evidence of up or downregulation of these pathways. In silkworm cell cultures, Wolbachia infection did not alter gene expression or induce or suppress immune responses, while Cardinium infection induced immune-related genes, including antimicrobial peptides, pattern recognition receptors, and a serine protease [ 104 ]. Additionally, the outer membrane protein of Wolbachia interacts with host actin and tubulin to disrupt endosomal trafficking [ 101 , 105 ]. Our data showed that Wolbachia had little effect on endocytoses, although clathrin exhibited high correlation with Wolbachia proteins. However, mite proteins from endocytoses and insulin pathways had the greatest impact on Wolbachia gene expression in double-infected populations [ 95 , 106 ]. Our analysis confirms prior research that indicates lipid and carbon metabolism produce metabolites that function as positive regulators of Wolbachia [ 95 , 106 ]. In comparison to Cardinium samples, we found that these metabolic pathways were upregulated. Previous studies have shown that Cardinium in D. farinae exhibits a negative correlation between bacterial gene expression and expression of mite genes assigned to the glycolysis and citric acid cycle pathways [ 32 ]. However, Wolbachia interacts more with mite metabolic pathways to regulate the citrate cycle and beta-oxidation, which was not observed in Cardinium in this study. Our analysis revealed that Wolbachia has a varied interaction with mite host genes, as evident from the correlation between mite-predicted KEGG genes and Wolbachia gene expression. This demonstrates the impact of Wolbachia on the mite immune system, regulatory pathways, and metabolism. Is the interaction between Wolbachia and mite hosts eliminated in cultures with multiple infections? Although the correlation analysis of all the expressions of mite KEGG genes and Wolbachia genes showed that much interaction disappeared, the analysis of mite immune and regulatory proteins provides an alternative explanation. The variability of immune, regulatory, and metabolic pathways in mites decreased by up to 15% when comparing single to double-infected cultures using the correlations to Cardinium gene expression, but not for Wolbachia . The complexity of the interaction increases as more variables and genes are involved. This is demonstrated by the partial dbRDA models, which show a two- or three-fold increase in degrees of freedom (Fig. 6 ). The changes were made due to the rapid decrease in Wolbachia density. The low density of symbionts may result in two possible outcomes: (i) the correlation disappears when mite infection is low, or (ii) the correlation disappears when the host's immune regulatory pathway reacts differently to low symbiont density. We observed different effects on Encarsia partenopea host reproduction when infected with two strains of the same symbiont species, Cardinium , at different densities [ 107 ]. It was observed that two Cardiniums in B. tabaci [ 107 ] responded differently to high temperature. The high-density Cardinium was found to be strongly influenced, while there was no effect on low-density Cardinium . This could be explained by the fact that the low density of symbionts in the host affects host pathways differently. It is also possible that this is due to sampling artifacts caused by population levels of samples, though we used nonparametric statistical analyses. Do correlation analyses reveal competition between Cardinium and Wolbachia in multiple infected host? Our study did not find any direct evidence of symbiont competition. We didn't observe any genes that had toxic effects on other symbionts among the most influenced ones. However, in cultures with double infections, we noticed that the variability of gene expression in Cardinium was explained similarly when either Wolbachia genes or mite KEGG predicted genes were the influencing factor. This was observed in models 5 and 6 and models 15 and 17, respectively (Table 3 ). In addition, we observe a low proportion of Cardinium–Wolbachia -infected individuals. Co-infections of multiple reproductive symbionts of Wolbachia , Cardinium and Rickettsiaceae within the same individual appear rarely. Too high quantities of transposable elements in all endosymbiont genomes and provide evidence that ancestors of the Cardinium , ‘ Ca . In the past, Tisiphia and Wolbachia endosymbionts have co-infected the same hosts, Oedothorax gibbosus [ 89 ]. The density of Wolbachia was found to be 20 times higher than Cardinium in coinfected individuals of thrips P. kellyanus . Interestingly, removing Wolbachia did not affect the density of Cardinium , which suggests that there is no competition between the two within hosts [ 28 ]. Both single and double infections, especially the latter, reduced the fecundity of the host S. furcifera . Additionally, different lines of the host showed varying levels of metabolites, some of which could potentially influence fecundity (arginine biosynthesis and nicotinamide metabolism were found to be affected). In the single-infected line, Cardinium upregulated metabolic levels, while in the double-infected line, Wolbachia appeared to downregulate them [ 23 ]. In double-infected cultures with Wolbachia and Cardinium , more complex interactions were observed among symbiont genes and mite immune and regulatory pathway gene expressions. This suggests that more symbiont proteins are involved in the interaction with mite immune and regulatory pathways. The presence of symbiont competition through the host is also likely. To test this, individual mites should be analyzed separately. However, this is challenging due to their small size and fresh weight (8 µg) [ 108 ]. The correlation analyses revealed different interactions between two Cardinium strains Our data showed that two cultures infected with Cardinium had different expressions, whereas no such effect was observed for Wolbachia . It was also observed that Wolbachia is a highly prevalent bacterial symbiont of insects, found in approximately 25 to 52% of insect species worldwide [ 93 ], and is more diverse than Cardinium. The NCBI currently contains approximately 150 annotated genomes from different species. However, the assembled genome differs from most of the other genomes and forms a separate cluster with Wolbachia from P. nigronervosa [ 82 ], mite F. setiger [ 83 ] and C. riparius. Wolbachia 's genome is more unique than Cardinium 's and has high similarity to S. furcifera [ 79 ]. In this study, we assembled the genome from all samples, but we cannot rule out the possibility of the existence of two separate Cardinium genomes. Although previous 16SDNA analyses on T. putrescentiae do not support it [ 21 , 109 ]. The genome of Cardinium in T. putrescentiae is surprisingly different from the Cardinium in the house dust mite D. farinae [ 80 , 110 ]. Therefore, it is necessary to compare the Cardinium genes to identify the gene with the same function as those assigned to KEGG. Declarations Statments JH and EG designed experiments; ET run experiments; JH provided bioinformatical and statistical analyses; all authors wrote the manuscript Funding The study was supported by the project of the Czech Science Foundation 22-15841K. Author Contribution JH and EG designed experiments; ET run experiments; JH provided bioinformatical and statistical analyses; all authors wrote the manuscript Acknowledgements The authors are obligated to Marta Nesvorna and Martin Markovic for technical help and Pavel B. Klimov for critical comments. References Pietri JE, DeBruhl H, Sullivan W. The rich somatic life of Wolbachia . MicrobiologyOpen. 2016;5(6):923–36. https://doi.org/10.1002/mbo3.390 . Zchori-Fein E, Perlman SJ. Distribution of the bacterial symbiont Cardinium in arthropods. Mol Ecol 2004;13(7):2009–16. https://doi.org/10.1111/j.1365-294X.2004.02203.x . Groot TVM, Breeuwer JAJ. Cardinium symbionts induce haploid thelytoky in most clones of three closely related Brevipalpus species. Exp Appl Acarol. 2006;39(3–4):257–71. https://doi.org/10.1007/s10493-006-9019-0 . Werren JH. Biology of Wolbachia . Annu Rev Entomol. 1997;42:587–609. https://doi.org/10.1146/annurev.ento.42.1.587 . Landmann F. The Wolbachia endosymbionts. In: Cossart P, Roy CR, Sansonetti P, editors. Microbiology Spectrum. Washington, DC: American Society for Microbiology; 2019. p. 139–53. https://doi.org/10.1128/microbiolspec.BAI-0018-2019 . Santos-Garcia D, Rollat-Farnier P-A, Beitia F, Zchori-Fein E, Vavre F, Mouton L, Moya A, Latorre A, Silva FJ. The genome of Cardinium cBtQ1 provides insights into genome reduction, symbiont motility, and its settlement in Bemisia tabaci . Genome Biol Evol. 2014;6(4):1013–30. https://doi.org/10.1093/gbe/evu077 . Gotoh T, Noda H, Ito S. Cardinium symbionts cause cytoplasmic incompatibility in spider mites. Heredity (Edinb). 2007;98(1):13–20. https://doi.org/10.1038/sj.hdy.6800881 . Zhu L-Y, Zhang K-J, Zhang Y-K, Ge C, Gotoh T, Hong X-Y. Wolbachia strengthens Cardinium -induced cytoplasmic incompatibility in the spider mite Tetranychus piercei McGregor. Curr Microbiol. 2012;65(5):516–23. https://doi.org/10.1007/s00284-012-0190-8 . Wu K, Hoy MA. Extended starvation reduced and eliminated Wolbachia , but not Cardinium , from Metaseiulus occidentalis females (Acari: Phytoseiidae): a need to reassess Wolbachia ’s status in this predatory mite? J Invertebr Pathol. 2012;109(1):20–6. https://doi.org/10.1016/j.jip.2011.09.005 . Wu K, Hoy MA. Cardinium is associated with reproductive incompatibility in the predatory mite Metaseiulus occidentalis (Acari: Phytoseiidae). J Invertebr Pathol. 2012;110(3):359–65. https://doi.org/10.1016/j.jip.2012.03.027 . Breeuwer H, Ros VID, Groot TVM. Cardinium : the next addition to the family of reproductive parasites. In: Zchori-Fein E, Bourtzis K, editors. Manipulative Tenants: Bacteria Associated with Arthropods. Boca Raton, FL: CRC Press; 2012. p. 207–24. https://doi.org/10.1201/b11008-16 . Schneider D, Miller WJ, Riegler M. Arthropods shopping for Wolbachia . In: Zchori-Fein E, Bourtzis K, editors. Manipulative Tenants: Bacteria Associated with Arthropods. Boca Raton, FL: CRC Press; 2012. p. 149–74. https://doi.org/10.1201/b11008-13 . Duron O, Bouchon D, Boutin S, Bellamy L, Zhou L, Engelstadter J, Hurst GD. The diversity of reproductive parasites among arthropods: Wolbachia do not walk alone. BMC Biol. 2008;6:27. https://doi.org/10.1186/1741-7007-6-27 . Zele F, Santos I, Olivieri I, Weill M, Duron O, Magalhaes S. Endosymbiont diversity and prevalence in herbivorous spider mite populations in South-Western Europe. FEMS Microbiol Ecol. 2018;94(4):fiy015. https://doi.org/10.1093/femsec/fiy015 . Zele F, Weill M, Magalhaes S. Identification of spider-mite species and their endosymbionts using multiplex PCR. Exp Appl Acarol. 2018;74(2):123–38. https://doi.org/10.1007/s10493-018-0224-4 . Zytynska SE. Cohabitation and roommate bias of symbiotic bacteria in insect hosts. Mol Ecol. 2019;28(24):5199–202. https://doi.org/10.1111/mec.15295 . Gottlieb Y, Ghanim M, Gueguen G, Kontsedalov S, Vavre F, Fleury F, Zchori-Fein E. Inherited intracellular ecosystem: symbiotic bacteria share bacteriocytes in whiteflies. FASEB J. 2008;22(7):2591–9. https://doi.org/10.1096/fj.07-101162 . Brown AMV, Wasala SK, Howe DK, Peetz AB, Zasada IA, Denver DR. Comparative genomics of Wolbachia – Cardinium dual endosymbiosis in a plant-parasitic nematode. Front Microbiol. 2018;9:2482. https://doi.org/10.3389/fmicb.2018.02482 . Ros VID, Fleming VM, Feil EJ, Breeuwer JAJ. Diversity and recombination in Wolbachia and Cardinium from Bryobia spider mites. BMC Microbiol. 2012;12(Suppl 1):S13. https://doi.org/10.1186/1471-2180-12-S1-S13 . Chen X-L, Xie R-R, Li G-Q, Hong X-Y. Simultaneous detection of endosymbionts Wolbachia and Cardinium in spider mites (Acari: Tetranychidae) by multiplex-PCR. Int J Acarol. 2009;35(5):397–403. https://doi.org/10.1080/01647950903292756 . Hubert J, Nesvorna M, Green SJ, Klimov PB. Microbial communities of stored product mites: variation by species and population. Microb Ecol. 2021;81(2):506–22. https://doi.org/10.1007/s00248-020-01581-y . Hubert J, Nesvorna M, Pekar S, Green SJ, Klimov PB. Cardinium inhibits Wolbachia in its mite host, Tyrophagus putrescentiae , and affects host fitness. FEMS Microbiol Ecol. 2021;97(10):fiab123. https://doi.org/10.1093/femsec/fiab123 . Li T-P, Zhou C-Y, Wang M-K, Zha S-S, Chen J, Bing X-L, Hoffmann AA, Hong X-Y. Endosymbionts reduce microbiome diversity and modify host metabolism and fecundity in the planthopper Sogatella furcifera . mSystems. 2022;7(2):e0151621. https://doi.org/10.1128/msystems.01516-21 . Mathe-Hubert H, Kaech H, Hertaeg C, Jaenike J, Vorburger C. Nonrandom associations of maternally transmitted symbionts in insects: the roles of drift versus biased cotransmission and selection. Mol Ecol. 2019;28(24):5330–46. https://doi.org/10.1111/mec.15206 . Brinker P, Fontaine MC, Beukeboom LW, Salles JF. Host, symbionts, and the microbiome: the missing tripartite interaction. Trends Microbiol. 2019;27(6):480–8. https://doi.org/10.1016/j.tim.2019.02.002 . Bustamante-Brito R, de Leon AV-P, Rosenblueth M, Martinez-Romero JC, Martinez-Romero E. Metatranscriptomic analysis of the bacterial symbiont Dactylopiibacterium carminicum from the carmine cochineal Dactylopius coccus (Hemiptera: Coccoidea: Dactylopiidae). Life (Basel). 2019;9(1):4. https://doi.org/10.3390/life9010004 . Bing X-L, Zhao D-S, Hong X-Y. Bacterial reproductive manipulators in rice planthoppers. Arch Insect Biochem Physiol. 2019;101(2):e21548. https://doi.org/10.1002/arch.21548 . Nguyen DT, Morrow JL, Spooner-Hart RN, Riegler M. Independent cytoplasmic incompatibility induced by Cardinium and Wolbachia maintains endosymbiont coinfections in haplodiploid thrips populations. Evolution. 2017;71(4):995–1008. https://doi.org/10.1111/evo.13197 . Li C, He M, Yun Y, Peng Y. Co-infection with Wolbachia and Cardinium may promote the synthesis of fat and free amino acids in a small spider, Hylyphantes graminicola . J Invertebr Pathol. 2020;169:107307. https://doi.org/10.1016/j.jip.2019.107307 . Zhao D-X, Zhang X-F, Hong X-Y. Host–symbiont interactions in spider mite Tetranychus truncates doubly infected with Wolbachi a and Cardinium . Environ Entomol. 2013;42(3):445–52. https://doi.org/10.1603/EN12354 . Nesvorna M, Sopko B, Hubert J. Cardinium and Wolbachia are negatively correlated in the microbiome of various populations of stored product mite Tyrophagus putrescentiae . Int J Acarol. 2020;46(3):192–9. https://doi.org/10.1080/01647954.2020.1752305 . Hubert J, Nesvorna M, Klimov PB, Erban T, Sopko B, Dowd SE, Scully ED. Interactions of the intracellular bacterium Cardinium with its host, the house dust mite Dermatophagoides farinae , based on gene expression data. mSystems. 2021;6(6):e0091621. https://doi.org/10.1128/mSystems.00916-21 . Schneider DS, Ayres JS. Two ways to survive infection: what resistance and tolerance can teach us about treating infectious diseases. Nat Rev Immunol. 2008;8(11):889–95. https://doi.org/10.1038/nri2432 . Zhang X, Hendrix JD, Campbell YL, Phillips TW, Goddard J, Cheng W-H, Kim T, Wu T-L, Schilling MW. Biology and integrated pest management of Tyrophagus putrescentiae (Schrank) infesting dry cured hams. J Stored Prod Res. 2018;79:16–28. https://doi.org/10.1016/j.jspr.2018.08.001 . Olivry T, Mueller RS. Critically appraised topic on adverse food reactions of companion animals (8): storage mites in commercial pet foods. BMC Vet Res. 2019;15(1):385. https://doi.org/10.1186/s12917-019-2102-7 . van Hage-Hamsten M, Johansson E. Clinical and immunologic aspects of storage mite allergy. Allergy. 1998;53(s48):49–53. https://doi.org/10.1111/j.1398-9995.1998.tb04997.x . Sanchez-Borges M, Suarez Chacon R, Capriles-Hulett A, Caballero-Fonseca F, Fernandez-Caldas E. Anaphylaxis from ingestion of mites: pancake anaphylaxis. J Allergy Clin Immunol. 2013;131(1):31–5. https://doi.org/10.1016/j.jaci.2012.09.026 . Eraso E, Martinez J, Garcia-Ortega P, Martinez A, Palacios R, Cisterna R, Guisantes JA. Influence of mite growth culture phases on the biological standardization of allergenic extracts. J Investig Allergol Clin Immunol. 1998;8(4):201–6. Martinez J, Eraso E, Palacios R, Guisantes JA. Enzymatic analyses of house dust mite extracts from Dermatophagoides pteronyssinus and Dermatophagoides farinae (Acari: Pyroglyphidae) during different phases of culture growth. J Med Entomol. 1999;36(3):370–5. https://doi.org/10.1093/jmedent/36.3.370 . Hubert J, Vrtala S, Sopko B, Dowd SE, He Q, Klimov PB, Harant K, Talacko P, Erban T. Predicting Blomia tropicalis allergens using a multiomics approach. Clin Transl Allergy. 2023;13(10):e12302. https://doi.org/10.1002/clt2.12302 . Krueger F. Trim Galore. Babraham Bioinformatics; 2021. https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/ . Accessed Nov 23 2023. Andrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics; 2019. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ . Accessed Nov 23 2023. Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):R25. https://doi.org/10.1186/gb-2009-10-3-r25 . Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. https://doi.org/10.1038/nmeth.1923 . Li H. Minimap2: pairwise alignment for nucleotide sequences, version 5. arXiv 1708.01492 [q-bio.GN]; 2018. https://doi.org/10.48550/arXiv.1708.01492 . Accessed Nov 23 2023. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–77. https://doi.org/10.1089/cmb.2012.0021 . Antipov D, Korobeynikov A, McLean JS, Pevzner PA. hybridSPAdes: an algorithm for hybrid assembly of short and long reads. Bioinformatics. 2016;32(7):1009–15. https://doi.org/10.1093/bioinformatics/btv688 . Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, Cuomo CA, Zeng Q, Wortman J, Young SK, Earl AM. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One. 2014;9(11):e112963. https://doi.org/10.1371/journal.pone.0112963 . Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068–9. https://doi.org/10.1093/bioinformatics/btu153 . Tanizawa Y, Fujisawa T, Nakamura Y. DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication. Bioinformatics. 2018;34(6):1037–1039. https://doi.org/10.1093/bioinformatics/btx713 . Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428(4):726–31. https://doi.org/10.1016/j.jmb.2015.11.006 . Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C-y, Graham M, Van Domselaar G, Stothard P. Proksee: in-depth characterization and visualization of bacterial genomes. Nucleic Acids Res. 2023;51(W1):W484–92. https://doi.org/10.1093/nar/gkad326 . Palmer JM, Stajich J. Funannotate v1.8.1: eukaryotic genome annotation. Zenodo; 2020. https://zenodo.org/record/4054262 . Accessed Nov 23 2023. The Galaxy Community. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Res. 2022;50(W1):W345–51. https://doi.org/10.1093/nar/gkac247 . Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000;28(1):27–30. https://doi.org/10.1093/nar/28.1.27 . Huerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D, Walter MC, Rattei T, Mende DR, Sunagawa S, Kuhn M, Jensen LJ, von Mering C, Bork P. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016;44(D1):D286–93. https://doi.org/10.1093/nar/gkv1248 . Gao C-H, Yu G, Cai P. ggVennDiagram: an intuitive, easy-to-use, and highly customizable R package to generate Venn diagram. Front Genet. 2021;12:706907. https://doi.org/10.3389/fgene.2021.706907 . Gao C-H. Package ‘ggVennDiagram’, version 1.2.3. CRAN - The Comprehensive R Archive Network; 2023. https://cran.r-project.org/web/packages/ggVennDiagram/ggVennDiagram.pdf . Accessed Nov 23 2023. R Development Core Team. R: a language and environment for statistical computing, version 4.3.1. Vienna: R Foundation for Statistical Computing; 2023. http://www.R-project.org . Accessed Nov 23 2023. Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM. Mash: Fast genome and metagenome distance estimation using MinHash. Genome Biol. 2016;17(1):132. https://doi.org/10.1186/s13059-016-0997-x . Olm MR, Brown CT, Brooks B, Banfield JF. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 2017;11(12):2864–2868. https://doi.org/10.1038/ismej.2017.126 . Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. https://doi.org/10.1186/1471-2105-11-119 . Steinegger M, Soding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017;35(11):1026–8. https://doi.org/10.1038/nbt.3988 . Kreft L, Botzki A, Coppens F, Vandepoele K, Van Bel M. PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization. Bioinformatics. 2017;33(18):2946–7. https://doi.org/10.1093/bioinformatics/btx324 . Avram O, Rapoport D, Portugez S, Pupko T. M1CR0B1AL1Z3R—a user-friendly web server for the analysis of large-scale microbial genomics data. Nucleic Acids Res. 2019;47(W1):W88–92. https://doi.org/10.1093/nar/gkz423 . Lane DJ. 16s/23s rRNA sequencing. In: Stackebrandt E, Goodfellow M (eds), Nucleic Acid Techniques in Bacterial Systematics. Chichester & New York, NY: John Wiley and Sons; 1991. p. 115–75. Matsumoto K. Studies on environmental factors for breeding of grain mites VII. Relationship between reproduction of mites and kind of carbohydrates in the diet. Jpn J Sanit Zool. 1965;16(2):118–22. https://doi.org/10.7601/mez.16.118 . (in Japanese with English summary) Hubert J, Kopecky J, Nesvorna M, Perotti MA, Erban T. Detection and localization of Solitalea -like and Cardinium bacteria in three Acarus siro populations (Astigmata: Acaridae). Exp Appl Acarol. 2016;70(3):309–27. https://doi.org/10.1007/s10493-016-0080-z Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol. 2013;79(17):5112–20. https://doi.org/10.1128/Aem.01043-13 . Hammer O. Past 4 - the past of the future. Oslo: Natural History Museum, University of Oslo; 2020. https://www.nhm.uio.no/english/research/resources/past/ . Accessed Nov 23 2023. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MH, Szoecs E, Wagner H. Package ‘vegan’: community ecology package, version 2.5-6. CRAN - The Comprehensive R Archive Network; 2019. https://cran.r-project.org/web/packages/vegan/vegan.pdf . Accessed Nov 23 2023. jokergoo. Visualize big correlation matrix. A Bioinformagician; 2018. http://web.archive.org/web/20200424071358/http://jokergoo.github.io/blog/html/large_matrix_circular.html . Accessed Apr 24 2020. Zeleny D. Analysis of community ecology data in R: constrained ordination. David Zeleny; 2017. https://www.davidzeleny.net/anadat-r/doku.php/en:forward_sel . Accessed Nov 23 2023. Gu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847–9. https://doi.org/10.1093/bioinformatics/btw313 . Gu Z. Complex heatmap visualization. iMeta. 2022;1(3):e43. https://doi.org/10.1002/imt2.43 . Ligges U, Maechler M, Schnackenberg S. scatterplot3d: 3D scatter plot, version 0.3–44. CRAN - The Comprehensive R Archive Network; 2023. https://cran.r-project.org/web/packages/scatterplot3d/ . Accessed Nov 23 2023. White JR, Nagarajan N, Pop M. Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Comput Biol. 2009;5(4):e1000352. https://doi.org/10.1371/journal.pcbi.1000352 . Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75(23):7537–41. https://doi.org/10.1128/Aem.01541-09 . Zeng Z, Fu Y, Guo D, Wu Y, Ajayi OE, Wu Q. Bacterial endosymbiont Cardinium cSfur genome sequence provides insights for understanding the symbiotic relationship in Sogatella furcifera host. BMC Genomics. 2018;19(1):688. https://doi.org/10.1186/s12864-018-5078-y . Xiong Q, Fung CS-H, Xiao X, Wan AT-Y, Wang M, Klimov P, Ren Y, Yang KY, Hubert J, Cui Y, Liu X, Tsui SK-W. Endogenous plasmids and chromosomal genome reduction in the Cardinium endosymbiont of Dermatophagoides farinae . mSphere. 2023;8(2):e0007423. https://doi.org/10.1128/msphere.00074-23 . Halter T, Hendrickx F, Horn M, Manzano-Marin A. A novel widespread MITE element in the repeat-rich genome of the Cardinium endosymbiont of the spider Oedothorax gibbosus . Microbiol Spectr. 2022;10(6):e0262722. https://doi.org/10.1128/spectrum.02627-22 . Mathers TC, Mugford ST, Hogenhout SA, Tripathi L. Genome sequence of the banana aphid, Pentalonia nigronervosa Coquerel (Hemiptera: Aphididae) and its symbionts. G3 (Bethesda). 2020;10(12):4315–21. https://doi.org/10.1534/g3.120.401358 . Klimov PB, Chetverikov PE, Dodueva IE, Vishnyakov AE, Bolton SJ, Paponova SS, Lutova LA, Tolstikov AV. Symbiotic bacteria of the gall-inducing mite Fragariocoptes setiger (Eriophyoidea) and phylogenomic resolution of the eriophyoid position among Acari. Sci Rep. 2022;12(1):3811. https://doi.org/10.1038/s41598-022-07535-3 . Zele F, Santos I, Matos M, Weill M, Vavre F, Magalhaes S. Endosymbiont diversity in natural populations of Tetranychus mites is rapidly lost under laboratory conditions. Heredity (Edinb). 2020;124(4):603–17. https://doi.org/10.1038/s41437-020-0297-9 . Narita S, Nomura M, Kageyama D. Naturally occurring single and double infection with Wolbachia strains in the butterfly Eurema hecabe : transmission efficiencies and population density dynamics of each Wolbachia strain. FEMS Microbiol Ecol. 2007;61(2):235–45. https://doi.org/10.1111/j.1574-6941.2007.00333.x . Frank SA. Dynamics of cytoplasmic incompatibility with multiple Wolbachia infections. J Theor Biol. 1998;192(2):213–8. https://doi.org/10.1006/jtbi.1998.0652 . Katlav A, Cook JM, Riegler M. Common endosymbionts affect host fitness and sex allocation via egg size provisioning. Proc Biol Sci. 2022;289(1971):20212582. https://doi.org/10.1098/rspb.2021.2582 . Lv N, Peng J, Xin-Yi Chen, Guo C-F, Sang W, Wang X-M, Ahmed MZ, Xu Y-Y, Qiu B-L. Antagonistic interaction between male-killing and cytoplasmic incompatibility induced by Cardinium and Wolbachia in the whitefly, Bemisia tabaci . Insect Sci. 2021;28(2):330–46. https://doi.org/10.1111/1744-7917.12793 . Halter T, Kostlbacher S, Rattei T, Hendrickx F, Manzano-Marin A, Horn M. One to host them all: genomics of the diverse bacterial endosymbionts of the spider Oedothorax gibbosus . Microb Genom. 2023;9(2):mgen000943. https://doi.org/10.1099/mgen.0.000943 . White JA, Kelly SE, Cockburn SN, Perlman SJ, Hunter MS. Endosymbiont costs and benefits in a parasitoid infected with both Wolbachia and Cardinium . Heredity (Edinb). 2011;106(4):585–91. https://doi.org/10.1038/hdy.2010.89 . Ju J-F, Bing X-L, Zhao D-S, Guo Y, Xi Z, Hoffmann AA, Zhang K-J, Huang H-J, Gong J-T, Zhang X, Hong X-Y. Wolbachia supplement biotin and riboflavin to enhance reproduction in planthoppers. ISME J. 2020;14(3):676–87. https://doi.org/10.1038/s41396-019-0559-9 . Newton ILG, Rice DW. The Jekyll and Hyde symbiont: could Wolbachia be a nutritional mutualist? J Bacteriol. 2020;202(4):e00589-00519. https://doi.org/10.1128/JB.00589-19 . Nevalainen LB, Layton EM, Newton ILG. Wolbachia promotes its own uptake by host cells. Infect Immun. 2023;91(2):e0055722. https://doi.org/10.1128/iai.00557-22 . Liu C, Wang J-L, Zheng Y, Xiong E-J, Li J-J, Yuan L-L, Yu X-Q, Wang Y-F. Wolbachia -induced paternal defect in Drosophila is likely by interaction with the juvenile hormone pathway. Insect Biochem Mol Biol. 2014;49:49–58. https://doi.org/10.1016/j.ibmb.2014.03.014 . Dou W, Miao Y, Xiao J, Huang D. Association of Wolbachia with gene expression in Drosophila testes. Microb Ecol. 2021;82(3):805–17. https://doi.org/10.1007/s00248-021-01703-0 . Li H, Harwood JD, Liu T, Chu D. Novel proteome and acetylome of Bemisia tabaci Q in response to Cardinium infection. BMC Genomics. 2018;19(1):523. https://doi.org/10.1186/s12864-018-4907-3 . Mann E, Stouthamer CM, Kelly SE, Dzieciol M, Hunter MS, Schmitz-Esser S. Transcriptome sequencing reveals novel candidate genes for Cardinium hertigii -caused cytoplasmic incompatibility and host-cell interaction. mSystems. 2017;2(6):e00141-00117. https://doi.org/10.1128/mSystems.00141-17 . Yang K, Yuan M-Y, Liu Y, Guo C-L, Liu T-X, Zhang Y-J, Chu D. First evidence for thermal tolerance benefits of the bacterial symbiont Cardinium in an invasive whitefly, Bemisia tabaci . Pest Manag Sci. 2021;77(11):5021–31. https://doi.org/10.1002/ps.6543 . Voronin D, Cook DAN, Steven A, Taylor MJ. Autophagy regulates Wolbachia populations across diverse symbiotic associations. Proc Natl Acad Sci U S A. 2012;109(25):E1638–46. https://doi.org/10.1073/pnas.1203519109 . White PM, Serbus LR, Debec A, Codina A, Bray W, Guichet A, Lokey RS, Sullivan W. Reliance of Wolbachia on high rates of host proteolysis revealed by a genome-wide RNAi screen of Drosophila cells. Genetics. 2017;205(4):1473–88. https://doi.org/10.1534/genetics.116.198903 . Porter J, Sullivan W. The cellular lives of Wolbachia . Nat Rev Microbiol. 2023;21(11):750–66. https://doi.org/10.1038/s41579-023-00918-x . White PM, Pietri JE, Debec A, Russell S, Patel B, Sullivan W. Mechanisms of horizontal cell-to-cell transfer of Wolbachia spp. in Drosophila melanogaster . Appl Environ Microbiol. 2017;83(7):e03425-03416. https://doi.org/10.1128/AEM.03425-16 . Ferree PM, Frydman HM, Li JM, Cao J, Wieschaus E, Sullivan W. Wolbachia utilizes host microtubules and dynein for anterior localization in the Drosophila oocyte. PLoS Pathog. 2005;1(2):e14. https://doi.org/10.1371/journal.ppat.0010014 . Nakamura Y, Gotoh T, Imanishi S, Mita K, Kurtti TJ, Noda H. Differentially expressed genes in silkworm cell cultures in response to infection by Wolbachia and Cardinium endosymbionts. Insect Mol Biol. 2011;20(3):279–89. https://doi.org/10.1111/j.1365-2583.2010.01056.x . Mills MK, McCabe LG, Rodrigue EM, Lechtreck KF, Starai VJ. Wbm0076, a candidate effector protein of the Wolbachia endosymbiont of Brugia malayi , disrupts eukaryotic actin dynamics. PLoS Pathog. 2023;19(2):e1010777. https://doi.org/10.1371/journal.ppat.1010777 . Deehan M, Lin W, Blum B, Emili A, Frydman H. Intracellular density of Wolbachia is mediated by host autophagy and the bacterial cytoplasmic incompatibility gene cifB in a cell type-dependent manner in Drosophila melanogaster . mBio. 2021;12(1):e02205-02220. https://doi.org/10.1128/mBio.02205-20 . Yang K, Qin P-H, Yuan M-Y, Chen L, Zhang Y-J, Chu D. Infection density pattern of Cardinium affects the responses of bacterial communities in an invasive whitefly under heat conditions. Insect Sci. 2023;30(4):1149–64. https://doi.org/10.1111/1744-7917.13141 . Erban T, Klimov PB, Smrz J, Phillips TW, Nesvorna M, Kopecky J, Hubert J. Populations of stored product mite Tyrophagus putrescentiae differ in their bacterial communities. Front Microbiol. 2016;7:1046. https://doi.org/10.3389/fmicb.2016.01046 . Kopecky J, Perotti MA, Nesvorna M, Erban T, Hubert J. Cardinium endosymbionts are widespread in synanthropic mite species (Acari: Astigmata). J Invertebr Pathol. 2013;112(1):20–3. https://doi.org/10.1016/j.jip.2012.11.001 . Erban T, Klimov P, Molva V, Hubert J. Whole genomic sequencing and sex-dependent abundance estimation of Cardinium sp., a common and hyperabundant bacterial endosymbiont of the American house dust mite, Dermatophagoides farinae . Exp Appl Acarol. 2020;80(3):363–80. https://doi.org/10.1007/s10493-020-00475-5 . Additional File 1 Additional File 1 is not available with this version. Additional Declarations No competing interests reported. Supplementary Files Additionalfle2Supplementaryfigures.docx Cite Share Download PDF Status: Published Journal Publication published 17 Apr, 2025 Read the published version in mSystems → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3848978","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":266403500,"identity":"d30a3913-2c27-4518-8678-9e5b37f179f2","order_by":0,"name":"Eliska Tresnakova","email":"","orcid":"","institution":"Czech University of Life Sciences Prague","correspondingAuthor":false,"prefix":"","firstName":"Eliska","middleName":"","lastName":"Tresnakova","suffix":""},{"id":266403501,"identity":"fda8bc84-5f73-4639-8a2c-6a9c6a417479","order_by":1,"name":"Eliza Glowska","email":"","orcid":"","institution":"Adam Mickiewicz University in Poznan","correspondingAuthor":false,"prefix":"","firstName":"Eliza","middleName":"","lastName":"Glowska","suffix":""},{"id":266403502,"identity":"b585507f-a345-4ab2-8eb7-0fd001acdca7","order_by":2,"name":"Jan Hubert","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIiWNgGAWjYPACCwYGCSD1AYjZ2InTIgFGjDNAWphJ0cLMA2IT0sLffvbZgw+/JBK3S/cYf7b5tU2ej5mB8cPHHDzGn0k3N5zZJ5G4c84ZM+ncvtuGbcwMzJIzt+HWYsCQxibN2yORuOFGjhlzbs9tRqAWNmZefFr4n8G1GH+27LltT1iLBNAWnh9gLQbSDD9uJxLUInHjGbvhzAYJ450z0sokextuJ7cxMzbj9Qt/fxrbgw9/bGS3SyRv/vDjz23b+e3NBz98xKMFCNgYGNsYHDeAmEAGiGzAqx6sheEPg70BmP2HkOJRMApGwSgYiQAAfaNO8tgGB1MAAAAASUVORK5CYII=","orcid":"","institution":"Czech University of Life Sciences Prague","correspondingAuthor":true,"prefix":"","firstName":"Jan","middleName":"","lastName":"Hubert","suffix":""}],"badges":[],"createdAt":"2024-01-09 18:29:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3848978/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3848978/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1128/msystems.01769-24","type":"published","date":"2025-04-18T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49543787,"identity":"ff0ab2f5-a6fd-4221-b00b-18cc3792a65b","added_by":"auto","created_at":"2024-01-12 17:45:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":284147,"visible":true,"origin":"","legend":"\u003cp\u003eThe comparison of single and double-infected cultures of \u003cem\u003eTyrophagus putrescentiae;\u003c/em\u003e \u003cstrong\u003eA\u003c/strong\u003e– The population growth of mites after 21 days of cultivation from 10 unsexed adults as an indirect indicator of mite fitness. The numbers of mites are shown and box plots and samples as jitter plots. In double-infected cultures the experiments were done after 2, 4 and 6 months of existence of the new cultures originated from parental (single-infected cultures); \u003cstrong\u003eB\u003c/strong\u003e – The proportion of \u003cem\u003eCardinium \u003c/em\u003eor \u003cem\u003eWolbachia\u003c/em\u003e infected mites. The columns represent predicted proportion and bars 95% confidence intervals. The proportion was established by analyses of 30 (double-infected) or (60 single -infested) mite individuals by PCR with specific primers. In double-infected cultures the experiments were done after 2, 3, 4 and 5 months of existence of the new cultures originated from parental (single-infected cultures); \u003cstrong\u003eC\u003c/strong\u003e – The proportion of \u003cem\u003eCardinium\u003c/em\u003e, \u003cem\u003eWolbachia\u003c/em\u003e, \u003cem\u003eCardinium\u003c/em\u003e+\u003cem\u003eWolbachia\u003c/em\u003e and asymbiotic mites in double-infected cultures of mites; \u003cstrong\u003eD\u003c/strong\u003e – The number of transcriptomes reads of \u003cem\u003eCardinium\u003c/em\u003e, \u003cem\u003eWolbachia\u003c/em\u003eand mite \u003cem\u003eT. putrescentiae\u003c/em\u003e in unstandardized transcriptome datasets. The numbers of transcripts are shown and box plots and samples as jitter plots.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/cd1b8db9698aca8d5b561e9d.png"},{"id":49543792,"identity":"86be014d-d03c-46d3-8ca2-626ee5bf45d5","added_by":"auto","created_at":"2024-01-12 17:45:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75913,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation triplot of distance base redundancy analyses (dbRDA) model showed interaction among \u003cem\u003eCardinium\u003c/em\u003e (\u003cstrong\u003eA\u003c/strong\u003e) and \u003cem\u003eWolbachia\u003c/em\u003e (\u003cstrong\u003eB\u003c/strong\u003e) in the host \u003cem\u003eT. putrescentiae\u003c/em\u003e cultures. The mite cultures were infested with the bacterium, i.e. \u003cem\u003eCardinium\u003c/em\u003e in 5L,5S; \u003cem\u003eWolbachia\u003c/em\u003ein 5P and 5N and multi-infected by both \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e (5LN, 5LP, 5SN, 5SP). The showed environmental variables included bacterial strain and the presence of other symbiont in multi-infested samples. The variable participation for every dbRDA model is shown in Venn diagram.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/b17b320a60ece79fb94da5ee.png"},{"id":49543793,"identity":"640e1f05-2a83-4ff8-9109-8cf37eef3bed","added_by":"auto","created_at":"2024-01-12 17:45:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":142199,"visible":true,"origin":"","legend":"\u003cp\u003eThe \u003cem\u003eCardinium\u003c/em\u003eand \u003cem\u003eWolbachia\u003c/em\u003e gene expression in single and double-infected \u003cem\u003eT. putrescentiae\u003c/em\u003e samples. \u003cstrong\u003eA\u003c/strong\u003e – The volcano plot of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia \u003c/em\u003egenes expression. The dashed bar indicates level of significance (P=0.05). The color indicated up/downregulated genes. All points are listed in Table S6, the most important genes are identified in Tables S7 and S8. The green color indicates gene expression higher in double-infected culture than single-infected (upregulated), while blue those prevailed in single-infected cultures than in double-infected (downregulated). \u003cstrong\u003eB\u003c/strong\u003e – The comparison of\u003cstrong\u003e \u003c/strong\u003ethe numbers of correlations of gene expression between symbionts in double-infected cultures (symbiont) and\u003cstrong\u003e \u003c/strong\u003emite predicted KEGG genes in single and double-infected samples (single and double-infected) using 3D scatter plots. The color schema of the points is the same as for A, light grey indicated no-significant (P=0.05) differences in gene expression level between single and double-infected cultures, dark grey indicate significant differences but low fold changes between cultures (log fold in intervals -2 to 2). The regression plane was added. The correlations were calculated using Spearman correlation coefficients and only those with significant permutation test (P≤0.05) were included.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/79780e1d6940148560ee0a97.png"},{"id":49543789,"identity":"f36e9f03-4a3e-40ff-98c8-09c7fc7be05d","added_by":"auto","created_at":"2024-01-12 17:45:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":786161,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlations heatmap showed correlations between \u003cem\u003eT. putrescentiae\u003c/em\u003e predicted KEGG genes and symbiont genes expression. The correlations were calculated as Spearman’s correlations and those with P\u0026lt;0.05 are shown. \u003cstrong\u003eA\u003c/strong\u003e – The correlation between mite gene and \u003cem\u003eWolbachia\u003c/em\u003e gene expression in single-infected cultures (w1); \u003cstrong\u003eB\u003c/strong\u003e – The correlation between mite gene and \u003cem\u003eWolbachia\u003c/em\u003e gene expression in double-infected culture with \u003cem\u003eCardinium\u003c/em\u003e (w2); \u003cstrong\u003eC\u003c/strong\u003e – The correlation between mite gene and \u003cem\u003eCardinium\u003c/em\u003e gene expression in single-infected cultures (c1); \u003cstrong\u003eD\u003c/strong\u003e – The correlation between mite gene and \u003cem\u003eCardinium\u003c/em\u003e gene expression in double-infected culture with \u003cem\u003eWolbachia\u003c/em\u003e (c2); \u003cstrong\u003eE\u003c/strong\u003e – the comparison of positive and negative correlations between expression of symbiont and mite protein in different cultures. The numbers of correlations with R\u003csup\u003e2\u003c/sup\u003e≥0.5 or R\u003csup\u003e2\u003c/sup\u003e≤-0.5 were divided by numbers for R\u003csup\u003e2\u003c/sup\u003e=0.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/fdc97100adc846a54c599648.png"},{"id":49543790,"identity":"319d00eb-a86d-4218-b44b-fc412d82d8cf","added_by":"auto","created_at":"2024-01-12 17:45:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":149797,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation triplot of distance base redundancy analyses (dbRDA) model showed interaction among \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003ein single and double-infected cultures to the host \u003cem\u003eT. putrescentiae\u003c/em\u003e predicted KEGG genes expression; A – the effect of symbionts to the expression of KEGG in mite immune and regulatory pathways; B - the effect of symbiont to mite metabolic pathways expression (summarized per KEGG). The analyzed data included symbiont free cultures (5K, 5Tk, 5Pi), \u003cem\u003eWolbachia\u003c/em\u003e-infected cultures (5N and 5P), \u003cem\u003eCardinium\u003c/em\u003e-infected cultures (5L and 5S) and experimental double (\u003cem\u003eCardinium\u003c/em\u003e+\u003cem\u003eWolbachia\u003c/em\u003e) infected cultures (5LP, 5LN, 5SN and 5SP). The variables factors in the model were tested based on their presence. The variable participation for every dbRDA model is shown in Venn diagram.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/d683a9f64a8ddf4949533064.png"},{"id":49544714,"identity":"35bfbcaf-3185-487d-bc19-980ee81b96b3","added_by":"auto","created_at":"2024-01-12 17:53:37","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":107998,"visible":true,"origin":"","legend":"\u003cp\u003eThe dbRDA models explaining the correlations between mite immune and regulatory pathways and symbiont (\u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e) genes in single and double-infected cultures. The heatmap visualized explained variability among partial dbRDA models using expression mite KEGG from the analyzed pathways as dependent and symbiont gene expression as factor (independent) and vice versa (i.e., symbiont gene expression dependent). The models are shown in Table S11. Explained variability (R\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e \u003c/sup\u003evalues from dbRDA models using symbiont expression as independent variables were organized into clusters by K-means clustering. The clusters are indicated as the color in the description of pathway.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/0e68fca6cc97952ce7433e70.png"},{"id":95764824,"identity":"7f571e42-7094-4671-a4d4-120c033ea8cc","added_by":"auto","created_at":"2025-11-12 19:19:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3534963,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/8f269a55-cd4c-4c09-bd9e-136f127b4bf0.pdf"},{"id":49543794,"identity":"c5f4fb39-0eec-43d4-9256-abf7fe9d56fe","added_by":"auto","created_at":"2024-01-12 17:45:38","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":1504317,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfle2Supplementaryfigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-3848978/v1/5c45b45a69f22178c4e3e04a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Cardinium wins on Wolbachia in double-infected mite cultures","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe intracellular, cytoplasmically inherited bacteria \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e are found mainly in the reproductive tissues of a wide range of arthropods [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These bacteria can affect host reproduction via cytoplasmic incompatibility, parthenogenesis induction, male-killing and feminization of genetic males [\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Similar to insects, mites may be colonized by intracellular bacteria, mostly by \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Hosts may be infected by a single bacterium or coinfected by multiple bacteria [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14 CR15 CR16 CR17\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The double infections of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e are reported in several species of \u003cem\u003eBryobia\u003c/em\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and \u003cem\u003eTetranychus\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In natural conditions, symbiotic, single and double-infected populations of the same \u003cem\u003eTetranychus\u003c/em\u003e species can exist in different geographical regions [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Despite that, no double-infected population for stored product mite \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e has been found. While single \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e-infected populations of \u003cem\u003eT. putrescientiae\u003c/em\u003e are known [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In manipulative experiments, the mixing of single \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e in \u003cem\u003eT. putrescentiae\u003c/em\u003e cultures resulted in double-infected cultures when \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e co-occur in the same mite individuals [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, the presence of \u003cem\u003eCardinium\u003c/em\u003e was negatively correlated with the presence of \u003cem\u003eWolbachia\u003c/em\u003e [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It indicates the competition among those symbionts, but the symbiont's mechanisms involved in such competition are not known on mite models yet. The intracellular symbionts of \u003cem\u003eSogatella furcifera\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] in both the single and double infection reduce bacterial diversity and change bacterial community structure (including bacterial corrections). In \u003cem\u003eT. putrescentiae\u003c/em\u003e, the presence of \u003cem\u003eCardinium\u003c/em\u003e was negatively correlated with the presence of \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eBartonella\u003c/em\u003e, while \u003cem\u003eBartonella\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e were positively correlated with each other [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe coexistence of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e symbionts leads to various interactions that are usually interpreted only via correlations in the context of their occurrence [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. A few studies, however, have shown the functional effects of their coexistence [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Mite coinfection with multiple symbiont taxa is a complex system that leads to possible interactions between these symbionts and the host. Such systems lead to altered host physiological responses and survival [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Some studies did not confirm the competition of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e in the double-infested Thysanoptera host \u003cem\u003ePezothrips kellyanus\u003c/em\u003e [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. \u003cem\u003eCardinium\u003c/em\u003e\u0026ndash;\u003cem\u003eWolbachia\u003c/em\u003e coinfection can promote fat and amino acid synthesis in the small spider \u003cem\u003eHylyphantes graminicola\u003c/em\u003e [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and the symbionts interact in methionine and fatty acid biosynthesis and biotin transport in \u003cem\u003ePratylenchus penetrans\u003c/em\u003e [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] or increase female fecundity but not longevity in \u003cem\u003eTetranychus truncatus\u003c/em\u003e [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This stands in contradiction to our preliminary results and observations of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e interactions in \u003cem\u003eT. putrescentiae.\u003c/em\u003e Correlation studies of the \u003cem\u003eT. putrescentiae\u003c/em\u003e microbiome showed that \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e negatively interact [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Since mixed populations had lower abundances of \u003cem\u003eWolbachia\u003c/em\u003e, while the abundance of \u003cem\u003eCardinium\u003c/em\u003e did not change, we suggest that the presence of \u003cem\u003eCardinium\u003c/em\u003e inhibits the growth of \u003cem\u003eWolbachia\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe previous study on \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eDermatophagoides farinae\u003c/em\u003e showed that the correlation between gene expression of host and symbionts identifies the most influenced host genes and pathways (i.e. endocytosis, phagocytosis, and apoptosis) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The suggested interaction is due to the host immune/regulatory pathways. Intracellular bacteria and the host immune system balance two strategies to defend themselves against infections: resistance and tolerance. Resistance is the ability to clear the infection, while tolerance is the ability to reduce the fitness costs of infection without clearing the infection itself [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. However, it is not clear which pathways (tolerance, resistance) are involved in the double-infested host. In another study, the manipulative experiments established double-infected \u003cem\u003eS. furcifera\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]; the study confirmed the effect of symbionts on metabolites (e.g. arginine biosynthesis and nicotinamide metabolism). \u003cem\u003eCardinium\u003c/em\u003e in the single-infected line upregulated metabolic production, while \u003cem\u003eWolbachia\u003c/em\u003e in the double-infected downregulated them [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe model mite species \u003cem\u003eT. putrescentiae\u003c/em\u003e is a pest found all over the world, known for causing damage to stored products [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] and pet foods [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It also produces allergens that can affect humans [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In experiments where the parental culture of \u003cem\u003eT. putrescentiae\u003c/em\u003e was inhabited by either \u003cem\u003eWolbachia\u003c/em\u003e (5N, 5P) or \u003cem\u003eCardinium\u003c/em\u003e (5L, 5S), the resulting culture of stored product mites was double-infected and known as 5LP, 5LN, 5SP, or 5SN. The fitness of mites and their symbionts' composition were analyzed over 5 months in double-infected cultures. The genomes of both bacteria and the mite host were assembled to study \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e interactions. Transcriptome analyses based on correlations between gene expression in single and multiple infected samples and between \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e genes were conducted.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSingle-infected cultures\u003c/h2\u003e \u003cp\u003eFor the experiments, four cultures of \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e that were infected with either \u003cem\u003eCardinium\u003c/em\u003e or \u003cem\u003eWolbachia\u003c/em\u003e were used (refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cultures were maintained at the Crop Research Institute in Prague, Czechia. The mites were kept in IWAKI 70 mL tissue culture flasks with a surface area of 25 cm2. These flasks were placed in Secador desiccators by Bel-Art Products, which maintained a relative humidity of 85% through a saturated KCl solution. The desiccators were kept in darkness and under controlled conditions of humidity (75% RH) and temperature (25\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C). The mites were fed a diet called SPMd, which consisted of wheat germ and Mauripan-dried yeast extract (\u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e) in a 10:1 w/w proportion. The diet was mill-powdered, sieved (mesh size, 500 \u0026micro;m), and heated to 70\u0026deg;C for 0.5 h before being fed to the mites.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCultures of \u003cem\u003eTyrophagus putrescenitae\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCult.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSymbiont\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCollector\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eE. Zdarkova\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGrain, Bustehrad, Czechia\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eA. Sala\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFood-producing factory, Cesena, Italy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJ. Hubert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFood-producing factory, St. Louis, MO, USA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5P\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT. W. Phillips\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLaboratory strain, Manhattan, KS, USA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe characteristics of \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e genomes and \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e genome/transcriptome.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenome/\u003c/p\u003e \u003cp\u003etrans.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehost\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003estrain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esize (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCompl.\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCont (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCover.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eContigs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eGC (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCDSs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eKEGG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003erRNA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003etRNA\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eT. putrescentiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ethis study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,051,907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eT. putrescentiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJANAVR01 [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e914,750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e39.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSogatella furcifera\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNZ_CP022339 [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,103,593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e39.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eOedothorax gibbosus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNZ_OW441264 [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,137,202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e36.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eT. putrescentiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ethis study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,043,441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e974\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eT. putrescentiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGIJY0000000\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e910457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e35.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e686\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eFragariocoptes_setiger\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJAHRAF010000001 [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,082,514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e573\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePentalonia_nigronervosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNZ_JACVWV01000004 [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,457,187\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e34.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTyrophagus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ethis study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e114,502,572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e10,330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e45.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e13,702\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDouble-infected cultures\u003c/h2\u003e \u003cp\u003eTo create mixed cultures, we transferred 10 unsexed adults from a \u003cem\u003eCardinium\u003c/em\u003e-infected culture and another 10 from a \u003cem\u003eWolbachia\u003c/em\u003e-infected culture into a new flask. We made sure to have 5LN, 5LP, 5SN, and 5SP in each flask with 10 mites in every combination. For transcriptome analyses, we prepared 7 replicates, and for the rest of the analyses, we prepared 6 replicates. Each replicate was carried out in a separate flask that contained 0.3 g of SPMd.\u003c/p\u003e \u003cp\u003eThe flasks containing multiple-infected mites such as 5LN, 5LP, 5SN, and 5PS were stored in desiccators under the same conditions used for mite rearing. Every culture was renewed monthly, by transferring around 5,000 live mites from the cap or surface of the flask into a new flask containing 0.3 g of SPMd. The remaining mites in the parent flask were used for growth tests and DNA extraction. For DNA extraction, the mites were collected from the flask caps and surface, transferred into 70% ethanol, and stored in a freezer at \u0026minus;\u0026thinsp;40\u0026deg;C prior to extraction. The mites were re-transferred into a new flask every month.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eThe sample of mites for gene expression analyses\u003c/h2\u003e \u003cp\u003eBoth single and double-infected populations of mites were harvested after 42 days of cultivation for transcriptome and genome analyses. This corresponds to a mite culture with exponential growth, which is commonly used for allergenic extracts [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The preparation of transcriptome and genome samples was previously described [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Mites that were alive were collected from the surfaces of the flasks and plugs, using a brush, and placed into sterile Eppendorf tubes. The samples were weighed on a microbalance to obtain 30\u0026ndash;40 mg of fresh weight. The samples for DNA extraction came from the polled mite cultures [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and included three technical replicates.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDNA extraction from single mite\u003c/h2\u003e \u003cp\u003eFor DNA extraction mites were collected after 2, 3, 4 and 5 months of incubation. To extract DNA from a single mite, we followed the procedure below: Firstly, the mite was cleaned with washing ethanol and dried. Next, the mite was transferred into a 0.2 mL thin wall tube (Thermo Scientific\u0026trade;, cat no: AB0620) that contained 25 \u0026micro;L of DEP-25 START‐Blue reagent (cat no: D226). The tube was then heated to 95\u0026deg;C for 20 minutes using a C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA). After heating, the tube was cooled to room temperature and 25 \u0026micro;l of DEP-25 STOP solution was added and mixed by vortexing. This process was repeated for 30 individuals per child culture, and the resulting samples were stored in a freezer at \u0026minus;\u0026thinsp;40\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eRNA and DNA extraction\u003c/h2\u003e \u003cp\u003eAll subsequent procedures with the mite samples were carried out on ice. Firstly, mites were surface cleaned using the following method: they were placed in a 100% ethanol solution and vortexed for 5 seconds, followed by centrifugation at 13,000 \u0026times;g for 1 minute. Then, the supernatant was replaced with a 1:10 solution of bleach (5% sodium hypochlorite) and ddH2O, vortexed for 5 seconds and centrifuged at 13,000 \u0026times;g for 2 minutes. Then, the cleaning solution was removed, the mites were washed in ddH2O, and the previous step was repeated. The mite samples were then homogenized in a glass tissue grinder (Kavalier glass, Prague, Czechia) in 500 \u0026micro;l of lysis buffer for 30 seconds. RNA extraction was performed using the NucleoSpin RNA kit (catalog no. 740984.50; Macherey-Nagel, Duren, Germany) with the following modifications: homogenized samples were centrifuged at 2,000 \u0026times; g for 3 seconds and DNA was degraded by DNase I at 37\u0026deg;C according to the manufacturer\u0026rsquo;s protocol (Riboclear plus, catalog no. 313\u0026thinsp;\u0026minus;\u0026thinsp;50; GeneAll, Lisbon, Portugal). RNA quality was evaluated using a NanoDrop instrument (NanoDrop One; Thermo Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA).\u003c/p\u003e \u003cp\u003eFirst, the homogenates were incubated overnight with 20 \u0026micro;L of proteinase K at 56\u0026deg;C. DNA was then extracted using the QIAamp DNA Micro Kit (Qiagen, Hilden, Germany, cat. No. 56304) following the manufacturer\u0026rsquo;s protocol for tissue samples. The extracted DNA samples were quantified using a Qubit\u0026reg; dsDNA HS Assay Kit (Life Technologies). The quality of the DNA was determined using a NanoDrop 2000 instrument and the average size of the genomic DNA (gDNA) was determined using an E-Gel SizeSelect 2% Agarose Gel (Invitrogen) with a 1 kb ladder. Samples were sheared with a Covaris G-tube (Covaris Inc.) and the average size of the sheared DNA was determined using a TapeStation 4200 system (Agilent Technologies). The samples were then transported on dry ice to the MrDNA laboratory (Shallowater, TX, USA) for downstream processing and sequencing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGenome and transcriptome sequencing\u003c/h2\u003e \u003cp\u003eThe RNA samples were adjusted to a volume of 30 \u0026micro;L, and the concentration of total RNA was determined using the Qubit\u0026reg; RNA Assay Kit by Life Technologies. To remove ribosomal RNA, 700 ng RNA samples were treated with the Ribo-Zero Plus rRNA Depletion Kit from Illumina. The rRNA-depleted samples were quantified, with RNA concentration ranging from 9.7 to 13.7 ng/\u0026micro;L, and used for library preparation using the KAPA mRNA HyperPrep Kits from Roche, following the manufacturer's instructions. After library preparation, the final concentration of all libraries ranged from 49.4 to 74.20 ng/\u0026micro;L, and the average library size was determined using the Agilent 2100 Bioanalyzer from Agilent Technologies. The libraries were then pooled in equimolar ratios of 0.6nM and sequenced in paired-end mode for 500 cycles with the NovaSeq 6000 system from Illumina. The reads were deposited in GenBank as projects PRJNA493156 and PRJNA990474 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe concentration of DNA in the original sample was around 90 ng/\u0026micro;L, as measured with the Qubit\u0026reg; dsDNA HS Assay Kit from Life Technologies. The quality of the DNA was determined using the NANODROP 2000 from ThermoFisher Scientific. However, the 260/230 values were low (0.73), so the DNA was cleaned using the DNEasy PowerClean Pro Cleanup Kit from Qiagen. The sample was then sheared using the Covaris G-tube from Covaris Inc. The average size of the sheared library was determined using the Agilent 2100 Bioanalyzer from Agilent Technologies. 500 ng of the sheared DNA was used with the SMRTbell Express Template Prep Kit 2.0 from Pacific Biosciences. During library preparation, the sample underwent DNA damage and end repair, and barcode adapter ligation. After library preparation, final library concentration (about 33 90 ng/\u0026micro;L) was measured using the Qubit\u0026reg; dsDNA HS Assay Kit from ThermoFisher Scientific. Additionally, the average library size (8107 bp) was determined using the Agilent 2100 Bioanalyzer from Agilent Technologies. Finally, the library was sequenced using the 10-hour movie time on the PacBio Sequel from Pacific Biosciences.\u003c/p\u003e \u003cp\u003eThe libraries for Illumina sequencing were prepared using the Illumina DNA Prep Fragmentation library preparation kit, following the manufacturer's guidelines. 50 ng of DNA was used for library preparation. Fragmentation and adapter addition were performed simultaneously, followed by a limited-cycle PCR to add unique indices to the sample. Afterward, the libraries were pooled in equimolar ratios of 0.6 nM and sequenced paired-end for 500 cycles using the NovaSeq 6000 system from Illumina. The reads have been deposited in GenBank as project PRJNA988410 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eProcessing of genome and transcriptome sequences\u003c/h2\u003e \u003cp\u003eThe methods for read processing, genome and transcriptome assembly, and annotation were previously described [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Illumina reads were trimmed with Trim Galore [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and analyzed using fastQC [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The reads were then mapped onto reference datasets using Bowtie2 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and Minimap2 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] was used for long sequences. The reference datasets included \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e genomes, as well as astigmatid mite genomes and transcriptomes available in GenBank. The mapped Illumina reads were de novo aligned with the PacBio reads using hybrid SPADES v3.14 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. The assembled genome was polished using Pilon [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBacterial sequences were annotated by Prokka [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] using DFAST [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] on a web server and predicted proteins were identified by KEGG using GhostKoala [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Bacterial genome annotations were done in Prokka v1.14.6 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] and visualized in Proksee [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe genome and transcriptome of \u003cem\u003eT. putrescentiae\u003c/em\u003e were annotated using Funannoatate 1.8.15 [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] on the Galaxy server [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Predicted proteins were assigned to KEGG categories, and metabolic pathways were identified using a KEGG mapper [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Additional analysis was performed using an EggNOG Mapper [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The presence of predicted KEGG proteins was comapared in assemblaged and related KEGG proteins using Venn diagrams [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] (package ggVennDiagram in R version 4.3.1) [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Gene expression analyses of the novel bacterial symbiont were performed in CLC Workbench 22 (Qiagen, Venlo, Netherlands). The total numbers of mapped RNA reads were used for expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenomic and molecular identification\u003c/h2\u003e \u003cp\u003eGenomic taxonomic analyses of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e were conducted by applying the MASH algorithm [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] in dRep [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] on the Galaxy server. The available genomes of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e were compared using this algorithm. Subsequently, the detection of open reading frames (ORFs), identification of orthologous groups, alignment of orthologous sequences [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], and inference of a Maximum Likelihood phylogenetic tree using RAxML with 100 bootstrap replicates [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] were performed using M1CR0B1AL1Z3R [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePCR reaction\u003c/h2\u003e \u003cp\u003ePCR reactions were carried out using master mix EmeraldAmp (catalogue number: RR310A, Takara Bio). The master mix contained an optimized buffer, PCR enzyme, dNTP mixture, gel loading dye (green), and a density reagent in a 2X premix format. Subsequently, ddH2O and primers were added to the mix. The amplification process was carried out using the C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA).\u003c/p\u003e \u003cp\u003eThe detection of \u003cem\u003eWolbachia\u003c/em\u003e WpF (5\u0026rsquo;-TTGTAGCCTGCTATGGTA-3\u0026rsquo;) and WpR (5\u0026rsquo;-GAATAGGTATGATTTTCA-3\u0026rsquo;) primers was done with the following amplification profile: initial denaturation at 94\u0026deg;C for 5 minutes, followed by 35 cycles of 95\u0026deg;C for 60 seconds, 52\u0026deg;C for 60 seconds, and 72\u0026deg;C for 60 seconds. The final extension was done at 72\u0026deg;C for 5 minutes.\u003c/p\u003e \u003cp\u003eFor the detection of \u003cem\u003eCardinium\u003c/em\u003e, we used the Card4 (5\u0026rsquo;-CTTAACGCTAGAACTGCGA-3\u0026rsquo;) and Card6 (5\u0026rsquo;-TCAAGCTCTACCAACTCC-3\u0026rsquo;) primers and conducted amplification with the following protocol: initial denaturation at 94\u0026deg;C for 5 minutes, followed by 35 cycles of denaturation at 94\u0026deg;C for 50 seconds, annealing at 56\u0026deg;C for 50 seconds, extension at 72\u0026deg;C for 60 seconds, and final extension at 72\u0026deg;C for 10 minutes. The reaction mixture contained 2 \u0026micro;L of DNA, 12.5 \u0026micro;L of EmeraldAmp master mix, 8.5 \u0026micro;L of ddH2O, and 1 \u0026micro;L of each 10 \u0026micro;M primer. We used a negative control with DNA replaced by ddH2O and a positive control with cloned DNA previously obtained by amplification of mite extracts using universal bacterial primers (F27 and 1492R) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe PCR products were observed on a 1% gel using the GeneSnap (Syngene InGenius LHR2 Gel Imaging System; cat. no: 316616). For preparing the 1% gel, 1.5 g of agarose (Lonza SeaKem\u0026reg; LE 500 g, cat no: 50004, Lonza, USA) was mixed with 150 mL of buffer (ROTIPHORESE\u0026reg; Buffer 50 x TAE, cat no: R.CL86.2, Carl Roth, Germany). The agarose was dissolved in hot a buffer and then cooled down under constant stirring. After that, 8 \u0026micro;L of SYBR\u0026reg; Safe DNA Gel Stain (cat no: S33102, Invitrogen, USA) was added to the solution. The diluted SYBR\u0026reg; Safe DNA Gel Stain was made by using 10 \u0026micro;L of SYBR\u0026reg; Safe DNA Gel Stain and 90 \u0026micro;L of dimethyl sulfoxide - DMSO. The size of the products was measured using a 50 bp ladder (Generuler 50bp, cat no: SM0373, ThermoFisher Scientific). The amplification process was considered successful when the PCR products were visible and were the expected size. The asymbiotic mite individuals were identified based on the presence of the product from universal bacterial primers, and the absence of the product from \u003cem\u003eCardinium\u003c/em\u003e and/or \u003cem\u003eWolbachia\u003c/em\u003e primers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMite growth test\u003c/h2\u003e \u003cp\u003eIt was hypothesized that there is a strong correlation between an increase in the number of mites and an increase in their fitness levels [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. The population growth of the original double-infected stock cultures was measured at two-month intervals. The first growth test was established after 2 months of incubation. Mites were collected from the plugs and surface of rearing flasks and then transferred to separate Petri dishes. The controls consisted of a single-infected population. Ten unsexed adult mites were moved from a Petri dish to new flasks that contained 0.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.005 grams of SPMd. The flasks were kept under controlled conditions. After 21 days, the experiment ended, and mites were counted using a dissection microscope [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eThe transcriptome reads data were analyzed unstandardized and standardized by recalculation to the samples with the lowest number of reads, as previously described for amplicon sequencing analyses[\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. The effect of single and multiple-infected cultures on bacterial and genome expression was evaluated using unstandardized data. The data were analyzed with the nonparametric Mann\u0026ndash;Whitney test in PAST 4 [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTwo datasets for each taxon were compared, the whole predicted gene expression and the KEGG-assigned gene expression. Two correlation analyses were conducted. Firstly, distance-based redundancy analyses (dbRDA) were used to test the correlation between the expression of the predicted genes and selected factors such as mite culture and symbiont presence. The analyses were performed using the vegan package [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] in R version 4.3.1.\u003c/p\u003e \u003cp\u003eIn the models, we compare the dataset as \u0026ldquo;dependent-gene expression\u0026rdquo; and \u0026ldquo;independent-environmental variables\u0026rdquo; [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. The next analysis used gene expression data from bacteria or mites as dependent and independent variables interchangeably [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. We calculated the dbRDA using Bray\u0026ndash;Curtis distance for standardized data or Robust Atkinson distance for unstandardized data. In order to identify the variables with the highest influence on the model, we used forward variable selection with the ordistep function [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. The selected environmental variables were added to new models, and their significance was tested using Monte Carlo permutation tests in the vegan package. We selected the models with the best predictive power based on their explained variability (R2). The final RDA models were visualized using triplots in the vegan package.\u003c/p\u003e \u003cp\u003eSecondly, we calculated the correlation among \u003cem\u003eCardinium\u003c/em\u003e, \u003cem\u003eWolbachia\u003c/em\u003e, and mite genome expression datasets independently using Sperman correlation coefficient and bootstrap permutational P values in PAST. Only the correlations with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were included in the heatmap. We constructed the correlation heatmaps using the ComplexHeatmap package [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] and clustered them using Ward distance or K-mean (in PAST) clustering for the interaction among symbionts and predicted mite KEGG gene expression in separate pathways. In case of a high number of comparisons, we selected the gene expression based on outliers in the position of the first two axes in dbRDA models. We visualized the numbers of correlations among symbionts and mite genes using the scaterplot3d package [\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] in R.\u003c/p\u003e \u003cp\u003eTo compare the differences in the expression of the predicted proteins, we first standardized the data for each data set separately. Then, we converted it to a shared file and analyzed it using the METASTATS function [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e] in MOTHUR v.1.48 [\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. The results were visualized as volcano plots. To construct the abundance heatmaps, we followed the same protocol as for the correlations heatmap. Finally, we used PAST to perform Kmeans clustering.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eDouble-infected cultures have reduced fitness when\u003c/b\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003eis present\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe final mite numbers after 21 days of \u003cem\u003eT. putrescentiae\u003c/em\u003e population growth showed significant differences among single and double-infected cultures (Kruskal\u0026ndash;Wallis test: H(chi\u003csup\u003e2\u003c/sup\u003e)\u0026thinsp;=\u0026thinsp;86.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). The number of mites at 5S and 5N was twofold high than at 5L in single-infected cultures.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe mite population in double-infected cultures decreased 5-fold after 2 and 4 months, indicating lower fitness compared to single-infected cultures. However, after 6 months of cultivating double-infected cultures, the population numbers reached the same density as single-infected cultures (Mann\u0026ndash;Whitney pairwise: 5LN, 5L (P\u0026thinsp;=\u0026thinsp;0.066), 5N (P\u0026thinsp;=\u0026thinsp;0.066); 5SP, 5P (0.69), 5S (P\u0026thinsp;=\u0026thinsp;0.47); or the density was twice as high as it was in 5SN (Mann\u0026ndash;Whitney pairwise 5S (P\u0026thinsp;=\u0026thinsp;0.008), 5N (P\u0026thinsp;=\u0026thinsp;0.005)). The exception occurred in the 5LP culture when the density was two-fold lower (Whitney pairwise: 5L (P\u0026thinsp;=\u0026thinsp;0.008), 5P (P\u0026thinsp;=\u0026thinsp;0.005)).\u003c/p\u003e \u003cp\u003eThe proportion of mites that were infected by bacteria varied significantly between different cultures (GLM: Chi\u0026thinsp;=\u0026thinsp;33.408, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), decreased from 5L, 5S, 5N to 5P and \u003cem\u003eCardinium -\u003c/em\u003einfected higher number of mites than \u003cem\u003eWolbachia\u003c/em\u003e (GLM: Chi\u0026thinsp;=\u0026thinsp;19.482, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). The percentage of \u003cem\u003eCardinium\u003c/em\u003e infection in double-infected mites increased from 50\u0026ndash;95% over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). There were no significant differences observed among the cultures (GLM time: Chi\u0026thinsp;=\u0026thinsp;62.011, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; culture: Chi\u0026thinsp;=\u0026thinsp;56.011, P\u0026thinsp;=\u0026thinsp;0.153; interaction: Chi\u0026thinsp;=\u0026thinsp;31.058, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Differently, \u003cem\u003eWolbachia\u003c/em\u003e infection disappeared (GLM time: Chi\u0026thinsp;=\u0026thinsp;106.180, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; culture: Chi\u0026thinsp;=\u0026thinsp;51.406 P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; interaction: Chi\u0026thinsp;=\u0026thinsp;44.241, P\u0026thinsp;=\u0026thinsp;0.066) in all multi-infected cultures. In the double-infected cultures, only a small proportion of individuals (up to 20%) were infected with both \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e. However, this proportion decreased over time during the cultivation of double-infected cultures (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Additionally, the cultures also contained a small proportion of mites without bacterial symbionts (asymbiotic), ranging from 0 to 30% of individuals.\u003c/p\u003e \u003cp\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eCardinium\u003c/b\u003e \u003cb\u003egenomes\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe characteristics of annotated \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e genomes (JAUEML000000000): are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table S2. Average nucleotide identity (ANI) analysis revealed that \u003cem\u003eCardinium\u003c/em\u003e from T. putrescentiae is closely related (forms a sister group) to \u003cem\u003eCardinium\u003c/em\u003e of \u003cem\u003eS. furcifera\u003c/em\u003e [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. Our genome is very similar to the \u003cem\u003eCardinium\u003c/em\u003e genome from Chinese strain of \u003cem\u003eT. putrescentiae\u003c/em\u003e (JANAVR01) [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e] (Fig. S2). These results are supported by a comparison of open reds frames (Fig. S3) using M1CR0B1AL1Z3R pipeline [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. It was found that both genome assemblages of \u003cem\u003eCardinium\u003c/em\u003e obtained from T. putrescentiae shared 73% of predicted KEGG genes (375 KEGG proteins). However, it was observed that 2% of predicted KEGG genes were unique to JANAVR1 and 7% were unique to the \u003cem\u003eCardinium\u003c/em\u003e genome assemblage. Altogether, 64% of predicted KEGG genes were shared among all \u003cem\u003eCardinium\u003c/em\u003e, in comparison to the assemblages of \u003cem\u003eCardinium\u003c/em\u003e found in \u003cem\u003eS. furcifera\u003c/em\u003e [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e] and \u003cem\u003eOedothoraz gibbosus\u003c/em\u003e [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eWolbachia\u003c/em\u003e genome assembled from \u003cem\u003eT. putrescentiae\u003c/em\u003e (Table S3) clustered with \u003cem\u003eWolbachia\u003c/em\u003e from \u003cem\u003ePentalonia nigronervosa\u003c/em\u003e [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. The next similar \u003cem\u003eWolbachia\u003c/em\u003e strain was the one found in the \u003cem\u003eFragariocepes setiger\u003c/em\u003e mite [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e] and \u003cem\u003eChironomus riparius\u003c/em\u003e, as confirmed by comparing open reds frames with the M1CR0B1AL1Z3R pipeline [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] (Fig. S5A). The newly assembled \u003cem\u003eWolbachia\u003c/em\u003e genome has similar numbers of ORF and GC contents as the average known \u003cem\u003eWolbachia\u003c/em\u003e strain (Fig. S6). These findings were supported by an analysis of average nucleotide identities (ANIs) (Fig. S5B).\u003c/p\u003e \u003cp\u003eThe genome assembly is similar to the previously deposited assembly of \u003cem\u003eWolbachia\u003c/em\u003e from \u003cem\u003eT. putrescentiae\u003c/em\u003e (GIJY000000), except that it is incomplete due to the absence of 16S and 23S rRNA. However, there is a difference of 3% (N\u0026thinsp;=\u0026thinsp;12) in the predicted KEGG genes between this genome assembly (GIJY000000) and the \u003cem\u003eWolbachia\u003c/em\u003e assembly in this study. On the other hand, 20% of the predicted KEGG genes in the \u003cem\u003eWolbachia\u003c/em\u003e assembly of this study were not present in the previously deposited assembly GIJY000000. Among 10 complete KEGG modules, the lipolic acid biosynthesis was identified in \u003cem\u003eCardinium\u003c/em\u003e, while \u003cem\u003eWolbachia\u003c/em\u003e showed 6 complete KEGG modules and no complete vitamin pathway was found.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTyrophagus putrecentiae\u003c/b\u003e \u003cb\u003egenome and transcriptome\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe characteristics of \u003cem\u003eT. putrescentiae\u003c/em\u003e genome (SUB13579704) are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The transcriptome contained 5,838 KEGG annotated proteins, which forms 66 complete KEGG modules (Table S4). Among them the mites are able to synthesize pantothenate, tetrahydrobiopterin, molybdenum cofactor, C1-unit interconversion and heme. The entire metagenome of the mite, which includes both bacterial symbionts and the mite itself, contained 80 complete KEGG modules.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe decrease of\u003c/b\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003ereads in the transcriptome of double-infected cultures\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe predicted number of expressed gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) was different between single and double-infected cultures of \u003cem\u003eT. putrescentiae\u003c/em\u003e (U\u0026thinsp;=\u0026thinsp;82, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), however the mean values were 10 \u003csup\u003e6.9\u003c/sup\u003e and 10 \u003csup\u003e7.1\u003c/sup\u003e, respectively. The gene expression was found to be similar in both the single and double-infected mite culture for \u003cem\u003eCardinium\u003c/em\u003e (U\u0026thinsp;=\u0026thinsp;173, P\u0026thinsp;=\u0026thinsp;0.551) and ranged between 10\u003csup\u003e3\u003c/sup\u003e and 10\u003csup\u003e4\u003c/sup\u003e per sample. There was a significant 10-fold decrease in \u003cem\u003eWolbachia\u003c/em\u003e gene expression in multiple-infected samples compared to \u003cem\u003eWolbachia\u003c/em\u003e-infected samples (U\u0026thinsp;=\u0026thinsp;0, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe expression of predicted\u003c/b\u003e \u003cb\u003eCardinium\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003eproteins differ between hosts with double and single infestations\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn this study, we focus on two different analyses: (i) the correlation analysis with the presence/absence of symbionts mono or double infection. It enables the identification of up-or down-regulated genes globally; (i.e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, models 1\u0026ndash;4, 7, 8; Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, models 1 and 13) (ii) correlation analyses between host and symbiont genes can identify genes that are downregulated by some genes and upregulated by others. (e.g. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, models 5\u0026ndash;6, 9\u0026ndash;18, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, models 2\u0026ndash;12 and 14\u0026ndash;23).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe correlation-based models of \u003cem\u003eCardinium\u003c/em\u003e, \u003cem\u003eWolbachia\u003c/em\u003e and their host \u003cem\u003eT. putrescentiae\u003c/em\u003e gene expression in the samples form symbiont single and multi-infected. The distance-based redundancy analyses (dbRDA) were calculated from different datasets in Bray\u0026ndash;Curtis distance. The datasets included predicted genes, genes assigned to KEGG and the presence/absence of symbionts in single and multi-infected mite cultures.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eid.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndeppendant variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eR2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.687\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e strain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e28.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_strain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.095\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.378\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.232\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e strain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_strain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.848\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_gene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e53.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e39.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edouble_infection_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.981\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e77.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e66.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.994\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.566\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTP_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.714\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe correlation-based models of \u003cem\u003eCardinium\u003c/em\u003e, \u003cem\u003eWolbachia\u003c/em\u003e and their host \u003cem\u003eT. putrescentiae\u003c/em\u003e gene expression in the samples form symbiont single and multi-infected. The gens were selcted to be involved in mite immune and regulatory pathways or metabolism. The distance-based redundancy analyses (dbRDA) were calculated from different datasets in Robust Aitkinson distance. The datasets included predicted genes, genes assigned to KEGG and the presence/absence of symbionts in single and multi-infected mite cultures.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eid.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIndeppendant variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eR2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.401\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edouble_infection_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u0026thinsp;+\u0026thinsp;\u003cem\u003eCardinium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.760\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Pathway_KEGG\u0026thinsp;+\u0026thinsp;\u003cem\u003eWolbachia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e36.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.959\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e18.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Pathway_KEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e12.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.602\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003edouble_infection_presence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.420\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.958\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (single)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e_genes (double)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.919\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emite_Metabolism_sumKEGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e_genes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe standardized transcriptome data revealed differences in predicted gene profiles of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e between single and double-infected host populations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). (Tables S2 and S3). The expression of \u003cem\u003eCardinium\u003c/em\u003e genes was affected by the presence of \u003cem\u003eWolbachia\u003c/em\u003e. There were differences between single- and double-infected cultures (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S5). The gradient along the x-axis in dbRDA triplots was visible. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). There were differences in \u003cem\u003eCardinium\u003c/em\u003e single-infected cultures between 5S and 5L mite cultures, and the gradient was visible on the y-axis in dbRDA triplot. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The gene expression in \u003cem\u003eWolbachia\u003c/em\u003e was found to be different in single-infected and double-infected host cultures. However, the dbRDA models explained less variability in \u003cem\u003eWolbachia\u003c/em\u003e compared to \u003cem\u003eCardinium\u003c/em\u003e. It was surprising to find that \u003cem\u003eCardinium\u003c/em\u003e from the 5S and 5L cultures affected the expression of \u003cem\u003eWolbachia\u003c/em\u003e genes differently, as evidenced by the sample positions along the y-axis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe number of genes present in \u003cem\u003eCardinium\u003c/em\u003e was six times higher than that of \u003cem\u003eWolbachia\u003c/em\u003e. Additionally, the expression of \u003cem\u003eCardinium\u003c/em\u003e was higher in the samples that were double-infected (200 \u003cem\u003eCardinium\u003c/em\u003e and 30 \u003cem\u003eWolbachia\u003c/em\u003e). The number of genes that had decreasing expression in the double-infected samples were 9 for \u003cem\u003eCardinium\u003c/em\u003e and 31 for \u003cem\u003eWolbachia\u003c/em\u003e, which was comparatively low for both bacteria. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Genes associated with reproduction and cell growth were over-expressed in \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e (Tables S6\u0026ndash;S8). The correlation analyses of predicted gene expression (Fig. S8) revealed positive correlations between clusters of \u003cem\u003eCardinium\u003c/em\u003e genes c1 and c2 and w1 and w2 \u003cem\u003eWolbachia\u003c/em\u003e genes, and negative correlations with w3 genes. In addition, \u003cem\u003eWolbachia\u003c/em\u003e clusters w1 and w2 had negative correlations to \u003cem\u003eCardinium\u003c/em\u003e c3 cluster. It provided 102 \u003cem\u003eCardinium\u003c/em\u003e and 250 \u003cem\u003eWolbachia\u003c/em\u003e genes. These genes showed 30% negative and 70% positive (N\u0026thinsp;=\u0026thinsp;3793) correlations (Table S9).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of\u003c/b\u003e \u003cb\u003eCardinium\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eWolbachi\u003c/b\u003e\u003cb\u003ea on the expression of predicted KEGG genes in\u003c/b\u003e \u003cb\u003eT. putrescentiae\u003c/b\u003e \u003cb\u003ediffers between single and double-infested hosts\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhen comparing the expression of mite genes with KEGG assigned genes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, models 9 and 10), the expression of KEGG genes explained almost twice as much variability. Using KEGG-assigned gene expression, we found that the presence of \u003cem\u003eWolbachia\u003c/em\u003e strongly influenced the expression of mite proteins. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, model 8). In comparison to \u003cem\u003eWolbachia\u003c/em\u003e, the effect of \u003cem\u003eCardinium\u003c/em\u003e on mite expression was four times lower. ANOSIM analyses showed a similar trend for mite protein assigned to KEGG (One-way Permanova: F\u0026thinsp;=\u0026thinsp;45.51, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Based on pairwise comparison, the expression of the mite KEGG gene was found to be similar between \u003cem\u003eCardinium\u003c/em\u003e and multiple infested samples (P\u0026thinsp;=\u0026thinsp;0.9654). This indicates that Cardinium's presence had the same effect on the expression of the mite gene in both single and double-infected cultures. However, \u003cem\u003eWolbachia\u003c/em\u003e did not show the same response, and its genes were affected differently in double-infected cultures.\u003c/p\u003e \u003cp\u003eThe mite predicted KEGG gene expression (Table S5) showed differences across the cultures (Fig. S9). When comparing all mite cultures, the dbRDA triplot was able to separate the \u003cem\u003eWolbachia\u003c/em\u003e single-infected cultures (5N and 5P) from \u003cem\u003eCardinium\u003c/em\u003e and double-infected cultures based on their x-axis values. While y axes separated double-infected cultures from those without symbionts (5K, 5Tk,5Pi) and single \u003cem\u003eCardinium\u003c/em\u003e-infected cultures (5L and 5S). However, there was no difference in mite gene expression between \u003cem\u003eCardinium\u003c/em\u003e single-infected cultures and asymbiotic cultures (5K, 5Tk and 5Pi) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The contribution of \u003cem\u003eCardinium\u003c/em\u003e as a variable was insignificant compared to \u003cem\u003eWolbachia\u003c/em\u003e and double-infected cultures in explaining variability. When the mite expression gene was analyzed in the symbiotic cultures, the x axes separated \u003cem\u003eWolbachia\u003c/em\u003e from \u003cem\u003eCardinium\u003c/em\u003e and double-infected cultures. Interestingly, the cultures infected with \u003cem\u003eCardinium\u003c/em\u003e were separated by y axes, and the MDS1 axe was not explained by the dbRDA model. This suggests that the \u003cem\u003eCardinium\u003c/em\u003e present in 5L and 5S had different interactions with the mite KEGG gene expression in single and double-infected cultures (5SP, 5SN versus 5LP and 5LN).\u003c/p\u003e \u003cp\u003eThe correlation analysis revealed a strong correlation between \u003cem\u003eWolbachia\u003c/em\u003e and predicted mite KEGG genes. The highest number of correlations was observed between the expression of \u003cem\u003eWolbachia\u003c/em\u003e genes and predicted mite KEGG genes in single-infected cultures (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). It is also illustrated by differences in KEGG predicted gene expression values among the cultures. The heatmap (Fig. S10) confirms correlation analyses, showing a remarkable cluster of highly expressed KEGG genes in \u003cem\u003eWolbachia\u003c/em\u003e-infected cultures, i.e., kelch-like protein 28, serine carboxypeptidase, vacuolar ATPase assembly integral membrane protein VMA21, phagosome associated transport protein, pre-mRNA-processing factor 39 and fluor threonine transaldolase.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn double-infected cultures, the number of correlations between \u003cem\u003eWolbachia\u003c/em\u003e and mite gene expression decreased by 5 times. On the other hand, in single-infected cultures, the number of correlations between \u003cem\u003eCardinium\u003c/em\u003e and mite gene expression was 2 times lower than those between \u003cem\u003eWolbachia\u003c/em\u003e and mite gene expression. In double-infected cultures, the number of negative correlations increased up to 80% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003e), compared to single-infected cultures. This was illustrated by the heatmap of mite predicted KEGG gene expression, where these genes did not form any cluster characterized by high expression in \u003cem\u003eCardinium\u003c/em\u003e single or double-infected cultures (Fig. S10).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe comparison of correlation numbers between symbionts and mite gene expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) showed that \u003cem\u003eWolbachia\u003c/em\u003e had a higher number of correlations with a lower number of downregulated genes (such as ARHGEF1, pdxJ, ZapA, and TRP75). On the other hand, \u003cem\u003eCardinium\u003c/em\u003e had the highest number of correlations with upregulated genes, as there were 9 downregulated genes (Table S9).\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe effect of symbiont on mite immune and regulatory pathways and metabolisms in single and double-infected cultures\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe presence of symbionts in single and double-infected cultures affected the expression of mite KEGG genes in host immune and regulatory pathways similarly to all other KEGG genes (One-Way Permanova: F\u0026thinsp;=\u0026thinsp;46.43, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The presence of \u003cem\u003eWolbachia\u003c/em\u003e has a greater influence on the pathways compared to Cardinium. This trend is consistent with all KEGG assigned protein expressions. In the correlation triplot, the distribution of KEGG genes indicated that the first axis separated \u003cem\u003eCardinium\u003c/em\u003e from the double-infected samples. The second axis in the triplot separated \u003cem\u003eWolbachia\u003c/em\u003e from \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e double-infected samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In addition, the separation of the samples from 5S and 5L cultures is apparent as well. Among 826 KEGG genes involved in immune and regulatory pathways 104 were identified as outliers (Table S12).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe symbiont genes have a greater influence on mite immune and regulatory pathways than mite proteins from those pathways have on symbiont genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Partial dbRDA modules clearly show a high influence (R\u003csup\u003e2\u003c/sup\u003e 0.55\u0026ndash;0.99) of symbiont to mite regulatory pathway' to (Table S11). In opposite analyzes, when mite regulatory pathways effect to symbiont gene expression was analyzed, the explained variablity of the models is lower (R\u003csup\u003e2\u003c/sup\u003e 0.12\u0026ndash;0.57). It indicates that symbionts expression is influenced by more factors not only by mites\u0026rsquo; regulatory pathways.\u003c/p\u003e \u003cp\u003eIn single-infected cultures, the expression of mite immune and regulatory pathway genes was more affected by \u003cem\u003eWolbachia\u003c/em\u003e genes than \u003cem\u003eCardinium\u003c/em\u003e genes. The independent factor variability explained by \u003cem\u003eWolbachia\u003c/em\u003e gene ranged from 0.84 to 0.99 (with a mean R\u003csup\u003e2\u003c/sup\u003e of 0.93), while for \u003cem\u003eCardinium\u003c/em\u003e genes it ranged from 0.54 to 0.95 (with a mean R\u003csup\u003e2\u003c/sup\u003e of 0.78). The multiple infections resulted in the models using mite immune and regulatory pathways as dependent variables, when was two- or three-fold higher numbers of symbiont genes selected as independent variables in the models (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The interpretation is that the interactions are more diversified, as the results of higher number of positive/negative correlations. Phagosome, p53, JAK-STAK, Hedgehog, TGF-beta, mitophagy, apoptosis and phosphatidylinositol signaling pathways exhibited high explained variability due to symbiont genes in both single and double-infected cultures, suggesting their impact on these pathways. It is surprising that a single \u003cem\u003eCardinium\u003c/em\u003e infection did not show any correlation with one-third of the pathways (e.g. endocytosis, ubiquitin mediate proteolysis, autophagy), but it changes with the double-infected cultures (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The identified outliers (Table S11) from mite KEGG proteins are listened in Table S12 and their correlations to symbionts outliers in Table S13.\u003c/p\u003e \u003cp\u003eIn the single-infected cultures \u003cem\u003eCardinium\u003c/em\u003e showed the highest numbers of correlations (Tables S11\u0026ndash;S13) with KEGG proteins associated to lysosome (CTSL), PI3K-Akt (HSP90A) and Ras (RALGAPA). While in double-infected cultures the highest correlation numbers showed protein kinase PRKAA and TSC2 (6 and 7 pathways), ECH1 (Peroxisome) and MYL3 (Apelin). The results indicate that the single-infected \u003cem\u003eWolbachia\u003c/em\u003e had the highest number of correlations to LRP5_6 (2 pathways) and CLTC and KIF5 (lysosome and endocytosis), tubulins (phagosome and apoptosis). The lysosomal associated proteins (CD107, CTSF) showed the highest level of correlation with \u003cem\u003eWolbachia\u003c/em\u003e in the double-infected culture. Next, proteins were associated with ubiquitin-mediated proteolysis (UBE2R), peroxisome (PHYH and ECH1), Phospholipase D (AGPAT3_4) and Apelin (MYL3) signaling pathway.\u003c/p\u003e \u003cp\u003eThe mite cultures exhibited differences in the expression of genes assigned to 61 metabolic pathways (Table S14, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). In single-infected cultures, the following pathways showed a 10-fold higher expression in \u003cem\u003eWolbachia\u003c/em\u003e-infected cultures compared to \u003cem\u003eCardinium\u003c/em\u003e-infected cultures: Citrate cycle, beta-oxidation, N-glycan precursor trimming and Fatty acid elongation in mitochondria. The same pathways were responsible for differences between \u003cem\u003eWolbachia\u003c/em\u003e-infected and double-infected cultures (Table S14). The presence of \u003cem\u003eWolbachia\u003c/em\u003e and/or \u003cem\u003eCardinium\u003c/em\u003e in single and double-infected cultures explained 30% of the total variability in dbRDA (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The first axis in the triplot separates single and double-infected cultures of \u003cem\u003eWolbachia\u003c/em\u003e while the second axis separates \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e cultures. (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). It is difficult to distinguish between \u003cem\u003eCardinium\u003c/em\u003e double-infected culture 5SP and both asymbiotic and \u003cem\u003eCardinium\u003c/em\u003e-infected cultures. Similarly, \u003cem\u003eCardinium\u003c/em\u003e single-infected cultures cannot be distinguished from asymbiotic cultures. This suggests that the presence or absence of symbionts has minimal impact on mite metabolism in relation to \u003cem\u003eCardinium\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eWhen the symbiont gene expression was added to partial models (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the gene expression of \u003cem\u003eCardinium\u003c/em\u003e or \u003cem\u003eWolbachia\u003c/em\u003e in single and double-infected cultures explained up to 99% of the variability in the mite metabolic pathway (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, models 8\u0026ndash;12). Although up to 64% of the variability in symbiont gene expression can be explained by mite metabolic pathway expression (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, models 2\u0026ndash;8). It appears that symbionts have a strong influence on mite metabolism, while also being influenced at a lower level by mite genes.\u003c/p\u003e \u003cp\u003eBased on dbRDA models, outliers were identified among expressions of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e genes, with 71 and 74 outliers respectively (Table S15). The numbers of positive and negative Spearman correlations to mite immune, regulatory, and metabolic pathways in both cultures and other symbiont gene expression in double-infected cultures revealed different clusters of the genes. The analysis revealed different clusters of genes with positive and negative Spearman correlations to mite immune, regulatory, and metabolic pathways in both cultures, as well as other symbiont gene expressions in double-infected cultures. \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e genes were clustered using the K-means method, identifying 9 and 5 clusters, respectively (Table S15).\u003c/p\u003e \u003cp\u003e \u003cem\u003eCardinium\u003c/em\u003e cluster was formed by genes with a high number of positive correlations to mite immune, regulatory, and metabolic pathways in double-infected cultures and to \u003cem\u003eWolbachia\u003c/em\u003e. The cluster was formed by the genes of an unknown function. The opposite situation, i.e., negative correlation to above mentioned showed the genes from 2 and 3 \u003cem\u003eCardinium\u003c/em\u003e clusters. It included proteins associated with DNA replication (DNA repair proteins RadC, resolvase) and proteins of possible virulence function virulence-associated proteins virE, leucyl aminopeptidase CARP. The 4 cluster represents proteins with high numbers of interaction with \u003cem\u003eWolbachia\u003c/em\u003e but not mites (e.g., possible receptor function C9 antigens, LolA). The last cluster 5 contains proteins with prevailing positive interaction with \u003cem\u003eWolbachia\u003c/em\u003e (i.e., transposases: YhgA, K07486, K07497, K07484, K07497).\u003c/p\u003e \u003cp\u003e \u003cem\u003eWolbachia\u003c/em\u003e cluster 1 was associated with a positive correlation to mite in both single and double-infected cultures and both positive and negative correlations were associated to \u003cem\u003eCardinium\u003c/em\u003e genes. Both single and double-infected cultures showed a positive correlation between \u003cem\u003eWolbachia\u003c/em\u003e cluster 1 and mite. \u003cem\u003eCardinium\u003c/em\u003e genes were associated with both positive and negative correlations. These proteins are involved in genetic information and processes, while other proteins serve as surface antigens (Surface_Ag_2). The clusters 2 and 3 were formed by two and three proteins with various correlations to mite immune and regulatory processes and \u003cem\u003eCardinium\u003c/em\u003e. Cluster 4 included proteins (e.g., Zapa, transmembrane proteins) with negative correlations to mite metabolism and \u003cem\u003eCardinium\u003c/em\u003e. Cluster 5 contained proteins with positive correlations to mite regulatory, immune, and metabolic proteins in double-infected cultures and a positive correlation to \u003cem\u003eCardinium\u003c/em\u003e (mainly polymerases). Cluster 6 was formed by proteins with a negative correlation to mite immune, regulatory proteins and metabolism in single-infected cultures (e.g. outer membrane protein). Cluster 7 included those with positive correlations to \u003cem\u003eCardinium\u003c/em\u003e only (e.g. miaB, phage proteins). Cluster 8 included proteins with high numbers of positive and negative correlations to \u003cem\u003eCardinium\u003c/em\u003e only (e,g, A-kinase anchor protein 18 and DeoC/LacD family aldolase). Cluster 9 consists of proteins that predominantly exhibit negative correlations with \u003cem\u003eCardinium\u003c/em\u003e (e.g. DJ-1/PfpI and addA ).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eThe mite fitness and symbiont competition in double-infected cultures\u003c/h2\u003e \u003cp\u003eThis study manipulated \u003cem\u003eT. putrescentiae\u003c/em\u003e mite cultures to prepare double-infected \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e from single-infected parental cultures. Our previous experiments showed that \u003cem\u003eCardinium\u003c/em\u003e decreased the level of \u003cem\u003eWolbachia\u003c/em\u003e by 2.7 times in double-infected \u003cem\u003eT. putrescentiae\u003c/em\u003e microbiome based on pooled mite samples [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. A study found that the density of \u003cem\u003eWolbachia\u003c/em\u003e, measured as the number of unstandardized reads per sample, decreased in cultures with double infection, but the density of \u003cem\u003eCardinium\u003c/em\u003e was unaffected. This finding is consistent with a previous study on mite \u003cem\u003eT. piercei\u003c/em\u003e, which measured symbiont density using qPCR. In mites that were infected with both \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e, the density of \u003cem\u003eWolbachia\u003c/em\u003e was found to be lower compared to those infected with \u003cem\u003eWolbachia\u003c/em\u003e alone. This finding is consistent with results obtained in \u003cem\u003eTetranychus\u003c/em\u003e. On the other hand, the density of \u003cem\u003eCardinium\u003c/em\u003e in females infected with \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e was not significantly different from that in females infected with \u003cem\u003eCardinium\u003c/em\u003e alone [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. It has been observed that \u003cem\u003eTetranychus\u003c/em\u003e species infected with both \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e have similar prevalence rates of these symbionts [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This suggests that they may be facilitating each other. However, there have been cases where \u003cem\u003eWolbachia\u003c/em\u003e was more prevalent than \u003cem\u003eCardinium\u003c/em\u003e in double-infected \u003cem\u003eP. kellyanus\u003c/em\u003e. Still, the removal of \u003cem\u003eWolbachia\u003c/em\u003e did not affect the density of \u003cem\u003eCardinium\u003c/em\u003e in the host [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This indicates that \u003cem\u003eCardinium\u003c/em\u003e is not dependent on the presence of \u003cem\u003eWolbachia\u003c/em\u003e, but the presence of \u003cem\u003eCardinium\u003c/em\u003e influences the density of \u003cem\u003eWolbachia\u003c/em\u003e.\u003c/p\u003e \u003cp\u003ePrevious research has shown that when the planthopper \u003cem\u003eS. furcifera\u003c/em\u003e is infected with both \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e, its fecundity is reduced compared to when it is infected with only \u003cem\u003eCardinium\u003c/em\u003e [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This finding is consistent with our own observations. We found that mite population growth was much lower in double-infected cultures, which is in line with previous studies on double-infected \u003cem\u003eT. putrescentiae\u003c/em\u003e cultures. After six months, the mite population grew substantially and became equal to the parental cultures, while \u003cem\u003eWolbachia\u003c/em\u003e disappeared from the double-infected cultures.\u003c/p\u003e \u003cp\u003eIt is believed that the disappearance of \u003cem\u003eWolbachia\u003c/em\u003e from the culture was caused by stochastic effects, specifically random genetic drift [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. Some populations lost the \u003cem\u003eWolbachia\u003c/em\u003e infection due to a low initial symbiont infection frequency or the presence of only a few individuals. Additionally, it is suggested that the fixation of \u003cem\u003eCardinium\u003c/em\u003e observed in the double-infected cultures was mainly due to CI [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e], rather than the fitness effects of this symbiont and/or drift. The disappearance of \u003cem\u003eWolbachia\u003c/em\u003e infection in multiple \u003cem\u003eTetranychus\u003c/em\u003e mites (\u003cem\u003eCardinium\u003c/em\u003e, \u003cem\u003eRickettsia\u003c/em\u003e) after only six months of laboratory rearing was attributed to differences in host genotypes [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur data shows a significant decline in fitness when both symbionts coexist in double-infected cultures. There could be various reasons for the difference in fitness, such as the cost of symbionts' presence during host development, the cost of feminizing effect on host development based on mothers' infection status, or differences in host genotypes between single-infected and double-infected individuals [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. The presence of \u003cem\u003eCardinium\u003c/em\u003e\u0026ndash;\u003cem\u003eWolbachia\u003c/em\u003e or \u003cem\u003eWolbachia\u003c/em\u003e\u0026ndash;\u003cem\u003eWolbachia\u003c/em\u003e-infected individuals can have various effects on fitness. In some populations, multiple \u003cem\u003eWolbachia\u003c/em\u003e strains can be present and stable within host populations, with double infections resulting in higher fitness than single infections [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. For instance, \u003cem\u003eCardinium\u003c/em\u003e increased female production in \u003cem\u003eP. kellyanus\u003c/em\u003e by improving maternal fitness and egg size, leading to higher fertilization rates and offspring fitness. However, \u003cem\u003eWolbachia\u003c/em\u003e reduced the beneficial effects of \u003cem\u003eCardinium\u003c/em\u003e [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. In \u003cem\u003eBemisia tabaci\u003c/em\u003e, co-infection of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e induced male killing and resulted in a higher female sex ratio [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The presence of \u003cem\u003eWolbachia\u003c/em\u003e in a host did not show any survival benefits for the wasp \u003cem\u003eEncarsia inaron\u003c/em\u003e that had the \u003cem\u003eCardinium\u003c/em\u003e infection. When doubly infected individuals were compared to uninfected wasps, there was no significant difference in reproduction observed [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. In the parasitoid wasp \u003cem\u003eE. inaron\u003c/em\u003e, \u003cem\u003eWolbachia\u003c/em\u003e caused cytoplasmic incompatibility (CI) and manipulated host reproduction, whereas \u003cem\u003eCardinium\u003c/em\u003e did not. In the case of butterfly \u003cem\u003eEurema hecabe\u003c/em\u003e, growth rates evaluated by development time were found to be slower in progenies of \u003cem\u003eWolbachia\u003c/em\u003e double-infected mothers than in those of single-infected mothers. \u003cem\u003eCardinium\u003c/em\u003e and combined \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e infections led to a reduction in bacterial diversity, alteration of bacterial community structure, and metabolic changes, which may have negative fitness effects on the host [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is currently unknown whether cytoplasmic incompatibility exists for \u003cem\u003eT. putrescentiae\u003c/em\u003e infections. Experimental cultures still contained single \u003cem\u003eWolbachia\u003c/em\u003e, \u003cem\u003eCardinium\u003c/em\u003e, and asymbiotic mites, as \u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e-infected individuals accounted for up to 20% of all mites. The fitness changes due to different genotypes should be permanent and not temporary. Our data showed significant differences in gene expression, which are connected to the number of \u003cem\u003eWolbachia\u003c/em\u003e in single and double-infected mites. We used nonparametric statistics to eliminate the artifacts of different read numbers among samples.\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe analysis of correlation in single-infected cultures showed that\u003c/b\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003ehas a more established interaction than\u003c/b\u003e \u003cb\u003eCardinium\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eCardinium\u003c/em\u003e has a biosynthetic pathway for lipoic acid that enables it to provide lipoate, but not biotin, to mite \u003cem\u003eD. farinae\u003c/em\u003e [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and \u003cem\u003eT. putrescentiae\u003c/em\u003e. Meanwhile, the study found that \u003cem\u003eWolbachia\u003c/em\u003e did not possess a complete vitamin pathway, indicating that it did not provide any new nutrients to the mite. However, other studies have reported that \u003cem\u003eWolbachia\u003c/em\u003e from planthoppers such as \u003cem\u003eLaodelphax striatellus\u003c/em\u003e and \u003cem\u003eNilaparvata lugens\u003c/em\u003e can provide biotin and riboflavin [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. Recent genome analyses have shown that the provisioning of vitamins and nutrients is more complex than previously thought [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. As a result, nutrient provisioning cannot be solely explained by observed correlations.\u003c/p\u003e \u003cp\u003eA recent study has found that \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e manipulate host immune, regulatory pathways and hormone production to aid their own uptake as well as transmission [\u003cspan additionalcitationids=\"CR94\" citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. In this study, we conducted two different analyses. The first one was a correlation analysis which involved determining the presence or absence of symbionts. This analysis was similar to the ones mentioned earlier and it helped us to identify genes that were globally up or down-regulated. The second analysis involved correlation analyses among symbiont and host genes. This helped us to identify genes that were downregulated by one group of genes and upregulated by other genes. Transcriptome analyses of mite \u003cem\u003eT. putrescentiae\u003c/em\u003e revealed that \u003cem\u003eWolbachia\u003c/em\u003e gene expression interacts more with host genes than \u003cem\u003eCardinium\u003c/em\u003e, as shown in the correlation model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, models 9\u0026ndash;10). It indicates \u003cem\u003eWolbachia\u003c/em\u003e manipulates host genes more than \u003cem\u003eCardinium\u003c/em\u003e in single-infected mite cultures. When opposite models are used, the mite genes manipulate the expression of \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e at similar levels (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, model 16\u0026ndash;20). When opposite models are used, the mite genes control the expression of \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e at similar levels (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, models 16\u0026ndash;20).\u003c/p\u003e \u003cp\u003eProteome analyses revealed that \u003cem\u003eCardinium\u003c/em\u003e infection in \u003cem\u003eB. tabaci\u003c/em\u003e upregulated proteins related to immune response (e.g. Calcium, p53, cGMP-PKG signal pathways and apoptosis) and energy metabolism (lipid transport, acyl CoA metabolic processes and biosynthesis) [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. While \u003cem\u003eCardinium\u003c/em\u003e was found to downregulate the spliceosome and endocytosis of the host in a study [\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e]. The transcriptomic study of \u003cem\u003eCardinium\u003c/em\u003e in \u003cem\u003eEncarsia suzannae\u003c/em\u003e identified highly expressed genes involved in manipulating ubiquitination, apoptosis, and host DNA [\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. The expression levels of ubiquitin-related genes were higher in \u003cem\u003eCardinium\u003c/em\u003e-infected \u003cem\u003eB. tabaci\u003c/em\u003e compared to uninfected strains [\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e]. Autophagy, ubiquitin-mediated proteolysis, and lysozyme are among the \u003cem\u003eWolbachia\u003c/em\u003e-influenced pathways. Autophagy, which is an intracellular defence mechanism, regulates the size of \u003cem\u003eWolbachia\u003c/em\u003e populations in host tissues [\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e]. The following study found that maintaining \u003cem\u003eWolbachia\u003c/em\u003e titer requires fully functional host ubiquitin and proteolysis pathways on an intact host endoplasmic reticulum (ER) [\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e, \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e]. \u003cem\u003eWolbachia\u003c/em\u003e increases the expression of lysosome-associated proteins and modulates the Toll/IMD pathway [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e]. These studies involve manipulating protein or transcript levels. Our analyses indicate that symbionts affect p53, JAK-STAK, NF-kappa beta signalling pathways and phagosome in single-infected cultures.\u003c/p\u003e \u003cp\u003eIn our study, we evaluated the importance of pathway interaction by using the explained variability in the correlation model as a criterion. There are several pathways that regulate \u003cem\u003eWolbachia\u003c/em\u003e, including the HIF-1, TOOL signaling, Lysozome, Mitophagy, and Apoptosis pathways. \u003cem\u003eWolbachia\u003c/em\u003e is transmitted through oocytes [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. During cell division, it is selectively passed on to the daughter cell with a larger microtubule organizing center by using dynein and dynactin for transportation [\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e]. \u003cem\u003eWolbachia\u003c/em\u003e uses dynamin- and clathrin-mediated endocytosis to enter host cells [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. However, it may also use other pathways of entry [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e]. One study found no evidence of up or downregulation of these pathways. In silkworm cell cultures, \u003cem\u003eWolbachia\u003c/em\u003e infection did not alter gene expression or induce or suppress immune responses, while \u003cem\u003eCardinium\u003c/em\u003e infection induced immune-related genes, including antimicrobial peptides, pattern recognition receptors, and a serine protease [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e]. Additionally, the outer membrane protein of \u003cem\u003eWolbachia\u003c/em\u003e interacts with host actin and tubulin to disrupt endosomal trafficking [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur data showed that \u003cem\u003eWolbachia\u003c/em\u003e had little effect on endocytoses, although clathrin exhibited high correlation with \u003cem\u003eWolbachia\u003c/em\u003e proteins. However, mite proteins from endocytoses and insulin pathways had the greatest impact on \u003cem\u003eWolbachia\u003c/em\u003e gene expression in double-infected populations [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. Our analysis confirms prior research that indicates lipid and carbon metabolism produce metabolites that function as positive regulators of \u003cem\u003eWolbachia\u003c/em\u003e [\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. In comparison to \u003cem\u003eCardinium\u003c/em\u003e samples, we found that these metabolic pathways were upregulated. Previous studies have shown that \u003cem\u003eCardinium\u003c/em\u003e in \u003cem\u003eD. farinae\u003c/em\u003e exhibits a negative correlation between bacterial gene expression and expression of mite genes assigned to the glycolysis and citric acid cycle pathways [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, \u003cem\u003eWolbachia\u003c/em\u003e interacts more with mite metabolic pathways to regulate the citrate cycle and beta-oxidation, which was not observed in \u003cem\u003eCardinium\u003c/em\u003e in this study.\u003c/p\u003e \u003cp\u003eOur analysis revealed that \u003cem\u003eWolbachia\u003c/em\u003e has a varied interaction with mite host genes, as evident from the correlation between mite-predicted KEGG genes and \u003cem\u003eWolbachia\u003c/em\u003e gene expression. This demonstrates the impact of \u003cem\u003eWolbachia\u003c/em\u003e on the mite immune system, regulatory pathways, and metabolism.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIs the interaction between\u003c/b\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003eand mite hosts eliminated in cultures with multiple infections?\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAlthough the correlation analysis of all the expressions of mite KEGG genes and \u003cem\u003eWolbachia\u003c/em\u003e genes showed that much interaction disappeared, the analysis of mite immune and regulatory proteins provides an alternative explanation.\u003c/p\u003e \u003cp\u003eThe variability of immune, regulatory, and metabolic pathways in mites decreased by up to 15% when comparing single to double-infected cultures using the correlations to \u003cem\u003eCardinium\u003c/em\u003e gene expression, but not for \u003cem\u003eWolbachia\u003c/em\u003e. The complexity of the interaction increases as more variables and genes are involved. This is demonstrated by the partial dbRDA models, which show a two- or three-fold increase in degrees of freedom (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The changes were made due to the rapid decrease in \u003cem\u003eWolbachia\u003c/em\u003e density. The low density of symbionts may result in two possible outcomes: (i) the correlation disappears when mite infection is low, or (ii) the correlation disappears when the host's immune regulatory pathway reacts differently to low symbiont density.\u003c/p\u003e \u003cp\u003eWe observed different effects on \u003cem\u003eEncarsia partenopea\u003c/em\u003e host reproduction when infected with two strains of the same symbiont species, \u003cem\u003eCardinium\u003c/em\u003e, at different densities [\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e]. It was observed that two \u003cem\u003eCardiniums\u003c/em\u003e in \u003cem\u003eB. tabaci\u003c/em\u003e [\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e] responded differently to high temperature. The high-density \u003cem\u003eCardinium\u003c/em\u003e was found to be strongly influenced, while there was no effect on low-density \u003cem\u003eCardinium\u003c/em\u003e. This could be explained by the fact that the low density of symbionts in the host affects host pathways differently. It is also possible that this is due to sampling artifacts caused by population levels of samples, though we used nonparametric statistical analyses.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDo correlation analyses reveal competition between\u003c/b\u003e \u003cb\u003eCardinium\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eWolbachia\u003c/b\u003e \u003cb\u003ein multiple infected host?\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur study did not find any direct evidence of symbiont competition. We didn't observe any genes that had toxic effects on other symbionts among the most influenced ones. However, in cultures with double infections, we noticed that the variability of gene expression in \u003cem\u003eCardinium\u003c/em\u003e was explained similarly when either \u003cem\u003eWolbachia\u003c/em\u003e genes or mite KEGG predicted genes were the influencing factor. This was observed in models 5 and 6 and models 15 and 17, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, we observe a low proportion of \u003cem\u003eCardinium\u0026ndash;Wolbachia\u003c/em\u003e-infected individuals. Co-infections of multiple reproductive symbionts of \u003cem\u003eWolbachia\u003c/em\u003e, \u003cem\u003eCardinium\u003c/em\u003e and Rickettsiaceae within the same individual appear rarely. Too high quantities of transposable elements in all endosymbiont genomes and provide evidence that ancestors of the \u003cem\u003eCardinium\u003c/em\u003e, \u0026lsquo;\u003cem\u003eCa\u003c/em\u003e. In the past, \u003cem\u003eTisiphia\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e endosymbionts have co-infected the same hosts, \u003cem\u003eOedothorax gibbosus\u003c/em\u003e [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The density of \u003cem\u003eWolbachia\u003c/em\u003e was found to be 20 times higher than \u003cem\u003eCardinium\u003c/em\u003e in coinfected individuals of thrips \u003cem\u003eP. kellyanus\u003c/em\u003e. Interestingly, removing Wolbachia did not affect the density of \u003cem\u003eCardinium\u003c/em\u003e, which suggests that there is no competition between the two within hosts [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Both single and double infections, especially the latter, reduced the fecundity of the host \u003cem\u003eS. furcifera\u003c/em\u003e. Additionally, different lines of the host showed varying levels of metabolites, some of which could potentially influence fecundity (arginine biosynthesis and nicotinamide metabolism were found to be affected). In the single-infected line, \u003cem\u003eCardinium\u003c/em\u003e upregulated metabolic levels, while in the double-infected line, \u003cem\u003eWolbachia\u003c/em\u003e appeared to downregulate them [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn double-infected cultures with \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e, more complex interactions were observed among symbiont genes and mite immune and regulatory pathway gene expressions. This suggests that more symbiont proteins are involved in the interaction with mite immune and regulatory pathways. The presence of symbiont competition through the host is also likely. To test this, individual mites should be analyzed separately. However, this is challenging due to their small size and fresh weight (8 \u0026micro;g) [\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eThe correlation analyses revealed different interactions between two\u003c/b\u003e \u003cb\u003eCardinium\u003c/b\u003e \u003cb\u003estrains\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOur data showed that two cultures infected with \u003cem\u003eCardinium\u003c/em\u003e had different expressions, whereas no such effect was observed for \u003cem\u003eWolbachia\u003c/em\u003e. It was also observed that \u003cem\u003eWolbachia\u003c/em\u003e is a highly prevalent bacterial symbiont of insects, found in approximately 25 to 52% of insect species worldwide [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e], and is more diverse than \u003cem\u003eCardinium.\u003c/em\u003e The NCBI currently contains approximately 150 annotated genomes from different species. However, the assembled genome differs from most of the other genomes and forms a separate cluster with \u003cem\u003eWolbachia\u003c/em\u003e from \u003cem\u003eP. nigronervosa\u003c/em\u003e [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e], mite \u003cem\u003eF. setiger\u003c/em\u003e [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e] and \u003cem\u003eC. riparius. Wolbachia\u003c/em\u003e's genome is more unique than \u003cem\u003eCardinium\u003c/em\u003e's and has high similarity to \u003cem\u003eS. furcifera\u003c/em\u003e [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we assembled the genome from all samples, but we cannot rule out the possibility of the existence of two separate \u003cem\u003eCardinium\u003c/em\u003e genomes. Although previous 16SDNA analyses on \u003cem\u003eT. putrescentiae\u003c/em\u003e do not support it [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e]. The genome of \u003cem\u003eCardinium\u003c/em\u003e in \u003cem\u003eT. putrescentiae\u003c/em\u003e is surprisingly different from the \u003cem\u003eCardinium\u003c/em\u003e in the house dust mite \u003cem\u003eD. farinae\u003c/em\u003e [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e]. Therefore, it is necessary to compare the \u003cem\u003eCardinium\u003c/em\u003e genes to identify the gene with the same function as those assigned to KEGG.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eStatments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJH and EG designed experiments; ET run experiments; JH provided bioinformatical and statistical analyses; all authors wrote the manuscript\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was supported by the project of the Czech Science Foundation 22-15841K.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJH and EG designed experiments; ET run experiments; JH provided bioinformatical and statistical analyses; all authors wrote the manuscript\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors are obligated to Marta Nesvorna and Martin Markovic for technical help and Pavel B. Klimov for critical comments.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePietri JE, DeBruhl H, Sullivan W. The rich somatic life of \u003cem\u003eWolbachia\u003c/em\u003e. MicrobiologyOpen. 2016;5(6):923\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/mbo3.390\u003c/span\u003e\u003cspan address=\"10.1002/mbo3.390\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZchori-Fein E, Perlman SJ. Distribution of the bacterial symbiont \u003cem\u003eCardinium\u003c/em\u003e in arthropods. Mol Ecol 2004;13(7):2009\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-294X.2004.02203.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-294X.2004.02203.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroot TVM, Breeuwer JAJ. \u003cem\u003eCardinium\u003c/em\u003e symbionts induce haploid thelytoky in most clones of three closely related \u003cem\u003eBrevipalpus\u003c/em\u003e species. Exp Appl Acarol. 2006;39(3\u0026ndash;4):257\u0026ndash;71. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10493-006-9019-0\u003c/span\u003e\u003cspan address=\"10.1007/s10493-006-9019-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWerren JH. Biology of \u003cem\u003eWolbachia\u003c/em\u003e. Annu Rev Entomol. 1997;42:587\u0026ndash;609. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev.ento.42.1.587\u003c/span\u003e\u003cspan address=\"10.1146/annurev.ento.42.1.587\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLandmann F. The \u003cem\u003eWolbachia\u003c/em\u003e endosymbionts. In: Cossart P, Roy CR, Sansonetti P, editors. Microbiology Spectrum. Washington, DC: American Society for Microbiology; 2019. p. 139\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/microbiolspec.BAI-0018-2019\u003c/span\u003e\u003cspan address=\"10.1128/microbiolspec.BAI-0018-2019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantos-Garcia D, Rollat-Farnier P-A, Beitia F, Zchori-Fein E, Vavre F, Mouton L, Moya A, Latorre A, Silva FJ. The genome of \u003cem\u003eCardinium\u003c/em\u003e cBtQ1 provides insights into genome reduction, symbiont motility, and its settlement in \u003cem\u003eBemisia tabaci\u003c/em\u003e. Genome Biol Evol. 2014;6(4):1013\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/gbe/evu077\u003c/span\u003e\u003cspan address=\"10.1093/gbe/evu077\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGotoh T, Noda H, Ito S. \u003cem\u003eCardinium\u003c/em\u003e symbionts cause cytoplasmic incompatibility in spider mites. Heredity (Edinb). 2007;98(1):13\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/sj.hdy.6800881\u003c/span\u003e\u003cspan address=\"10.1038/sj.hdy.6800881\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu L-Y, Zhang K-J, Zhang Y-K, Ge C, Gotoh T, Hong X-Y. \u003cem\u003eWolbachia\u003c/em\u003e strengthens \u003cem\u003eCardinium\u003c/em\u003e-induced cytoplasmic incompatibility in the spider mite \u003cem\u003eTetranychus piercei\u003c/em\u003e McGregor. Curr Microbiol. 2012;65(5):516\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00284-012-0190-8\u003c/span\u003e\u003cspan address=\"10.1007/s00284-012-0190-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu K, Hoy MA. Extended starvation reduced and eliminated \u003cem\u003eWolbachia\u003c/em\u003e, but not \u003cem\u003eCardinium\u003c/em\u003e, from \u003cem\u003eMetaseiulus occidentalis\u003c/em\u003e females (Acari: Phytoseiidae): a need to reassess \u003cem\u003eWolbachia\u003c/em\u003e\u0026rsquo;s status in this predatory mite? J Invertebr Pathol. 2012;109(1):20\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jip.2011.09.005\u003c/span\u003e\u003cspan address=\"10.1016/j.jip.2011.09.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu K, Hoy MA. \u003cem\u003eCardinium\u003c/em\u003e is associated with reproductive incompatibility in the predatory mite \u003cem\u003eMetaseiulus occidentalis\u003c/em\u003e (Acari: Phytoseiidae). J Invertebr Pathol. 2012;110(3):359\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jip.2012.03.027\u003c/span\u003e\u003cspan address=\"10.1016/j.jip.2012.03.027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBreeuwer H, Ros VID, Groot TVM. \u003cem\u003eCardinium\u003c/em\u003e: the next addition to the family of reproductive parasites. In: Zchori-Fein E, Bourtzis K, editors. Manipulative Tenants: Bacteria Associated with Arthropods. Boca Raton, FL: CRC Press; 2012. p. 207\u0026ndash;24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1201/b11008-16\u003c/span\u003e\u003cspan address=\"10.1201/b11008-16\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchneider D, Miller WJ, Riegler M. Arthropods shopping for \u003cem\u003eWolbachia\u003c/em\u003e. In: Zchori-Fein E, Bourtzis K, editors. Manipulative Tenants: Bacteria Associated with Arthropods. Boca Raton, FL: CRC Press; 2012. p. 149\u0026ndash;74. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1201/b11008-13\u003c/span\u003e\u003cspan address=\"10.1201/b11008-13\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuron O, Bouchon D, Boutin S, Bellamy L, Zhou L, Engelstadter J, Hurst GD. The diversity of reproductive parasites among arthropods: \u003cem\u003eWolbachia\u003c/em\u003e do not walk alone. BMC Biol. 2008;6:27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1741-7007-6-27\u003c/span\u003e\u003cspan address=\"10.1186/1741-7007-6-27\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZele F, Santos I, Olivieri I, Weill M, Duron O, Magalhaes S. Endosymbiont diversity and prevalence in herbivorous spider mite populations in South-Western Europe. FEMS Microbiol Ecol. 2018;94(4):fiy015. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/femsec/fiy015\u003c/span\u003e\u003cspan address=\"10.1093/femsec/fiy015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZele F, Weill M, Magalhaes S. Identification of spider-mite species and their endosymbionts using multiplex PCR. Exp Appl Acarol. 2018;74(2):123\u0026ndash;38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10493-018-0224-4\u003c/span\u003e\u003cspan address=\"10.1007/s10493-018-0224-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZytynska SE. Cohabitation and roommate bias of symbiotic bacteria in insect hosts. Mol Ecol. 2019;28(24):5199\u0026ndash;202. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.15295\u003c/span\u003e\u003cspan address=\"10.1111/mec.15295\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGottlieb Y, Ghanim M, Gueguen G, Kontsedalov S, Vavre F, Fleury F, Zchori-Fein E. Inherited intracellular ecosystem: symbiotic bacteria share bacteriocytes in whiteflies. FASEB J. 2008;22(7):2591\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1096/fj.07-101162\u003c/span\u003e\u003cspan address=\"10.1096/fj.07-101162\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrown AMV, Wasala SK, Howe DK, Peetz AB, Zasada IA, Denver DR. Comparative genomics of \u003cem\u003eWolbachia\u003c/em\u003e\u0026ndash;\u003cem\u003eCardinium\u003c/em\u003e dual endosymbiosis in a plant-parasitic nematode. Front Microbiol. 2018;9:2482. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmicb.2018.02482\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2018.02482\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRos VID, Fleming VM, Feil EJ, Breeuwer JAJ. Diversity and recombination in \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e from \u003cem\u003eBryobia\u003c/em\u003e spider mites. BMC Microbiol. 2012;12(Suppl 1):S13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2180-12-S1-S13\u003c/span\u003e\u003cspan address=\"10.1186/1471-2180-12-S1-S13\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen X-L, Xie R-R, Li G-Q, Hong X-Y. Simultaneous detection of endosymbionts \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e in spider mites (Acari: Tetranychidae) by multiplex-PCR. Int J Acarol. 2009;35(5):397\u0026ndash;403. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/01647950903292756\u003c/span\u003e\u003cspan address=\"10.1080/01647950903292756\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubert J, Nesvorna M, Green SJ, Klimov PB. Microbial communities of stored product mites: variation by species and population. Microb Ecol. 2021;81(2):506\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00248-020-01581-y\u003c/span\u003e\u003cspan address=\"10.1007/s00248-020-01581-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubert J, Nesvorna M, Pekar S, Green SJ, Klimov PB. \u003cem\u003eCardinium\u003c/em\u003e inhibits \u003cem\u003eWolbachia\u003c/em\u003e in its mite host, \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e, and affects host fitness. FEMS Microbiol Ecol. 2021;97(10):fiab123. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/femsec/fiab123\u003c/span\u003e\u003cspan address=\"10.1093/femsec/fiab123\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi T-P, Zhou C-Y, Wang M-K, Zha S-S, Chen J, Bing X-L, Hoffmann AA, Hong X-Y. Endosymbionts reduce microbiome diversity and modify host metabolism and fecundity in the planthopper \u003cem\u003eSogatella furcifera\u003c/em\u003e. mSystems. 2022;7(2):e0151621. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/msystems.01516-21\u003c/span\u003e\u003cspan address=\"10.1128/msystems.01516-21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMathe-Hubert H, Kaech H, Hertaeg C, Jaenike J, Vorburger C. Nonrandom associations of maternally transmitted symbionts in insects: the roles of drift versus biased cotransmission and selection. Mol Ecol. 2019;28(24):5330\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.15206\u003c/span\u003e\u003cspan address=\"10.1111/mec.15206\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrinker P, Fontaine MC, Beukeboom LW, Salles JF. Host, symbionts, and the microbiome: the missing tripartite interaction. Trends Microbiol. 2019;27(6):480\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tim.2019.02.002\u003c/span\u003e\u003cspan address=\"10.1016/j.tim.2019.02.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBustamante-Brito R, de Leon AV-P, Rosenblueth M, Martinez-Romero JC, Martinez-Romero E. Metatranscriptomic analysis of the bacterial symbiont \u003cem\u003eDactylopiibacterium carminicum\u003c/em\u003e from the carmine cochineal \u003cem\u003eDactylopius coccus\u003c/em\u003e (Hemiptera: Coccoidea: Dactylopiidae). Life (Basel). 2019;9(1):4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/life9010004\u003c/span\u003e\u003cspan address=\"10.3390/life9010004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBing X-L, Zhao D-S, Hong X-Y. Bacterial reproductive manipulators in rice planthoppers. Arch Insect Biochem Physiol. 2019;101(2):e21548. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/arch.21548\u003c/span\u003e\u003cspan address=\"10.1002/arch.21548\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen DT, Morrow JL, Spooner-Hart RN, Riegler M. Independent cytoplasmic incompatibility induced by \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e maintains endosymbiont coinfections in haplodiploid thrips populations. Evolution. 2017;71(4):995\u0026ndash;1008. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/evo.13197\u003c/span\u003e\u003cspan address=\"10.1111/evo.13197\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi C, He M, Yun Y, Peng Y. Co-infection with \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e may promote the synthesis of fat and free amino acids in a small spider, \u003cem\u003eHylyphantes graminicola\u003c/em\u003e. J Invertebr Pathol. 2020;169:107307. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jip.2019.107307\u003c/span\u003e\u003cspan address=\"10.1016/j.jip.2019.107307\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao D-X, Zhang X-F, Hong X-Y. Host\u0026ndash;symbiont interactions in spider mite \u003cem\u003eTetranychus truncates\u003c/em\u003e doubly infected with \u003cem\u003eWolbachi\u003c/em\u003ea and \u003cem\u003eCardinium\u003c/em\u003e. Environ Entomol. 2013;42(3):445\u0026ndash;52. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1603/EN12354\u003c/span\u003e\u003cspan address=\"10.1603/EN12354\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNesvorna M, Sopko B, Hubert J. \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e are negatively correlated in the microbiome of various populations of stored product mite \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e. Int J Acarol. 2020;46(3):192\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/01647954.2020.1752305\u003c/span\u003e\u003cspan address=\"10.1080/01647954.2020.1752305\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubert J, Nesvorna M, Klimov PB, Erban T, Sopko B, Dowd SE, Scully ED. Interactions of the intracellular bacterium \u003cem\u003eCardinium\u003c/em\u003e with its host, the house dust mite \u003cem\u003eDermatophagoides farinae\u003c/em\u003e, based on gene expression data. mSystems. 2021;6(6):e0091621. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/mSystems.00916-21\u003c/span\u003e\u003cspan address=\"10.1128/mSystems.00916-21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchneider DS, Ayres JS. Two ways to survive infection: what resistance and tolerance can teach us about treating infectious diseases. Nat Rev Immunol. 2008;8(11):889\u0026ndash;95. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nri2432\u003c/span\u003e\u003cspan address=\"10.1038/nri2432\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X, Hendrix JD, Campbell YL, Phillips TW, Goddard J, Cheng W-H, Kim T, Wu T-L, Schilling MW. Biology and integrated pest management of \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e (Schrank) infesting dry cured hams. J Stored Prod Res. 2018;79:16\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jspr.2018.08.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jspr.2018.08.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlivry T, Mueller RS. Critically appraised topic on adverse food reactions of companion animals (8): storage mites in commercial pet foods. BMC Vet Res. 2019;15(1):385. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12917-019-2102-7\u003c/span\u003e\u003cspan address=\"10.1186/s12917-019-2102-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Hage-Hamsten M, Johansson E. Clinical and immunologic aspects of storage mite allergy. Allergy. 1998;53(s48):49\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1398-9995.1998.tb04997.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1398-9995.1998.tb04997.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanchez-Borges M, Suarez Chacon R, Capriles-Hulett A, Caballero-Fonseca F, Fernandez-Caldas E. Anaphylaxis from ingestion of mites: pancake anaphylaxis. J Allergy Clin Immunol. 2013;131(1):31\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jaci.2012.09.026\u003c/span\u003e\u003cspan address=\"10.1016/j.jaci.2012.09.026\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEraso E, Martinez J, Garcia-Ortega P, Martinez A, Palacios R, Cisterna R, Guisantes JA. Influence of mite growth culture phases on the biological standardization of allergenic extracts. J Investig Allergol Clin Immunol. 1998;8(4):201\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartinez J, Eraso E, Palacios R, Guisantes JA. Enzymatic analyses of house dust mite extracts from \u003cem\u003eDermatophagoides pteronyssinus\u003c/em\u003e and \u003cem\u003eDermatophagoides farinae\u003c/em\u003e (Acari: Pyroglyphidae) during different phases of culture growth. J Med Entomol. 1999;36(3):370\u0026ndash;5. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/jmedent/36.3.370\u003c/span\u003e\u003cspan address=\"10.1093/jmedent/36.3.370\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubert J, Vrtala S, Sopko B, Dowd SE, He Q, Klimov PB, Harant K, Talacko P, Erban T. Predicting \u003cem\u003eBlomia tropicalis\u003c/em\u003e allergens using a multiomics approach. Clin Transl Allergy. 2023;13(10):e12302. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/clt2.12302\u003c/span\u003e\u003cspan address=\"10.1002/clt2.12302\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrueger F. Trim Galore. Babraham Bioinformatics; 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndrews S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics; 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.bioinformatics.babraham.ac.uk/projects/fastqc/\u003c/span\u003e\u003cspan address=\"http://www.bioinformatics.babraham.ac.uk/projects/fastqc/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLangmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):R25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/gb-2009-10-3-r25\u003c/span\u003e\u003cspan address=\"10.1186/gb-2009-10-3-r25\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLangmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nmeth.1923\u003c/span\u003e\u003cspan address=\"10.1038/nmeth.1923\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi H. Minimap2: pairwise alignment for nucleotide sequences, version 5. arXiv 1708.01492 [q-bio.GN]; 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.48550/arXiv.1708.01492\u003c/span\u003e\u003cspan address=\"10.48550/arXiv.1708.01492\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455\u0026ndash;77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1089/cmb.2012.0021\u003c/span\u003e\u003cspan address=\"10.1089/cmb.2012.0021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntipov D, Korobeynikov A, McLean JS, Pevzner PA. hybridSPAdes: an algorithm for hybrid assembly of short and long reads. Bioinformatics. 2016;32(7):1009\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btv688\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btv688\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, Cuomo CA, Zeng Q, Wortman J, Young SK, Earl AM. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One. 2014;9(11):e112963. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0112963\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0112963\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30(14):2068\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btu153\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btu153\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTanizawa Y, Fujisawa T, Nakamura Y. DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication. Bioinformatics. 2018;34(6):1037\u0026ndash;1039. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btx713\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btx713\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428(4):726\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jmb.2015.11.006\u003c/span\u003e\u003cspan address=\"10.1016/j.jmb.2015.11.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C-y, Graham M, Van Domselaar G, Stothard P. Proksee: in-depth characterization and visualization of bacterial genomes. Nucleic Acids Res. 2023;51(W1):W484\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gkad326\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkad326\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalmer JM, Stajich J. Funannotate v1.8.1: eukaryotic genome annotation. Zenodo; 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zenodo.org/record/4054262\u003c/span\u003e\u003cspan address=\"https://zenodo.org/record/4054262\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThe Galaxy Community. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update. Nucleic Acids Res. 2022;50(W1):W345\u0026ndash;51. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gkac247\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkac247\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 2000;28(1):27\u0026ndash;30. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/28.1.27\u003c/span\u003e\u003cspan address=\"10.1093/nar/28.1.27\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D, Walter MC, Rattei T, Mende DR, Sunagawa S, Kuhn M, Jensen LJ, von Mering C, Bork P. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016;44(D1):D286\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gkv1248\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkv1248\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao C-H, Yu G, Cai P. ggVennDiagram: an intuitive, easy-to-use, and highly customizable R package to generate Venn diagram. Front Genet. 2021;12:706907. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fgene.2021.706907\u003c/span\u003e\u003cspan address=\"10.3389/fgene.2021.706907\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGao C-H. Package \u0026lsquo;ggVennDiagram\u0026rsquo;, version 1.2.3. CRAN - The Comprehensive R Archive Network; 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/ggVennDiagram/ggVennDiagram.pdf\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/ggVennDiagram/ggVennDiagram.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eR Development Core Team. R: a language and environment for statistical computing, version 4.3.1. Vienna: R Foundation for Statistical Computing; 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.R-project.org\u003c/span\u003e\u003cspan address=\"http://www.R-project.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOndov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM. Mash: Fast genome and metagenome distance estimation using MinHash. Genome Biol. 2016;17(1):132. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s13059-016-0997-x\u003c/span\u003e\u003cspan address=\"10.1186/s13059-016-0997-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOlm MR, Brown CT, Brooks B, Banfield JF. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 2017;11(12):2864\u0026ndash;2868. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/ismej.2017.126\u003c/span\u003e\u003cspan address=\"10.1038/ismej.2017.126\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2105-11-119\u003c/span\u003e\u003cspan address=\"10.1186/1471-2105-11-119\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSteinegger M, Soding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nat Biotechnol. 2017;35(11):1026\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/nbt.3988\u003c/span\u003e\u003cspan address=\"10.1038/nbt.3988\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKreft L, Botzki A, Coppens F, Vandepoele K, Van Bel M. PhyD3: a phylogenetic tree viewer with extended phyloXML support for functional genomics data visualization. Bioinformatics. 2017;33(18):2946\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btx324\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btx324\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAvram O, Rapoport D, Portugez S, Pupko T. M1CR0B1AL1Z3R\u0026mdash;a user-friendly web server for the analysis of large-scale microbial genomics data. Nucleic Acids Res. 2019;47(W1):W88\u0026ndash;92. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/nar/gkz423\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkz423\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLane DJ. 16s/23s rRNA sequencing. In: Stackebrandt E, Goodfellow M (eds), Nucleic Acid Techniques in Bacterial Systematics. Chichester \u0026amp; New York, NY: John Wiley and Sons; 1991. p. 115\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsumoto K. Studies on environmental factors for breeding of grain mites VII. Relationship between reproduction of mites and kind of carbohydrates in the diet. Jpn J Sanit Zool. 1965;16(2):118\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7601/mez.16.118\u003c/span\u003e\u003cspan address=\"10.7601/mez.16.118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. (in Japanese with English summary)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHubert J, Kopecky J, Nesvorna M, Perotti MA, Erban T. Detection and localization of \u003cem\u003eSolitalea\u003c/em\u003e-like and \u003cem\u003eCardinium\u003c/em\u003e bacteria in three \u003cem\u003eAcarus siro\u003c/em\u003e populations (Astigmata: Acaridae). Exp Appl Acarol. 2016;70(3):309\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10493-016-0080-z\u003c/span\u003e\u003cspan address=\"10.1007/s10493-016-0080-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol. 2013;79(17):5112\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/Aem.01043-13\u003c/span\u003e\u003cspan address=\"10.1128/Aem.01043-13\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHammer O. Past 4 - the past of the future. Oslo: Natural History Museum, University of Oslo; 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nhm.uio.no/english/research/resources/past/\u003c/span\u003e\u003cspan address=\"https://www.nhm.uio.no/english/research/resources/past/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O\u0026rsquo;Hara RB, Simpson GL, Solymos P, Stevens MH, Szoecs E, Wagner H. Package \u0026lsquo;vegan\u0026rsquo;: community ecology package, version 2.5-6. CRAN - The Comprehensive R Archive Network; 2019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/vegan/vegan.pdf\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/vegan/vegan.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ejokergoo. Visualize big correlation matrix. A Bioinformagician; 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://web.archive.org/web/20200424071358/http://jokergoo.github.io/blog/html/large_matrix_circular.html\u003c/span\u003e\u003cspan address=\"http://web.archive.org/web/20200424071358/http://jokergoo.github.io/blog/html/large_matrix_circular.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Apr 24 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeleny D. Analysis of community ecology data in R: constrained ordination. David Zeleny; 2017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.davidzeleny.net/anadat-r/doku.php/en:forward_sel\u003c/span\u003e\u003cspan address=\"https://www.davidzeleny.net/anadat-r/doku.php/en:forward_sel\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu Z, Eils R, Schlesner M. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016;32(18):2847\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/bioinformatics/btw313\u003c/span\u003e\u003cspan address=\"10.1093/bioinformatics/btw313\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu Z. Complex heatmap visualization. iMeta. 2022;1(3):e43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/imt2.43\u003c/span\u003e\u003cspan address=\"10.1002/imt2.43\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLigges U, Maechler M, Schnackenberg S. scatterplot3d: 3D scatter plot, version 0.3\u0026ndash;44. CRAN - The Comprehensive R Archive Network; 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cran.r-project.org/web/packages/scatterplot3d/\u003c/span\u003e\u003cspan address=\"https://cran.r-project.org/web/packages/scatterplot3d/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed Nov 23 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite JR, Nagarajan N, Pop M. Statistical methods for detecting differentially abundant features in clinical metagenomic samples. PLoS Comput Biol. 2009;5(4):e1000352. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pcbi.1000352\u003c/span\u003e\u003cspan address=\"10.1371/journal.pcbi.1000352\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75(23):7537\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/Aem.01541-09\u003c/span\u003e\u003cspan address=\"10.1128/Aem.01541-09\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZeng Z, Fu Y, Guo D, Wu Y, Ajayi OE, Wu Q. Bacterial endosymbiont \u003cem\u003eCardinium\u003c/em\u003e cSfur genome sequence provides insights for understanding the symbiotic relationship in \u003cem\u003eSogatella furcifera\u003c/em\u003e host. BMC Genomics. 2018;19(1):688. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12864-018-5078-y\u003c/span\u003e\u003cspan address=\"10.1186/s12864-018-5078-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiong Q, Fung CS-H, Xiao X, Wan AT-Y, Wang M, Klimov P, Ren Y, Yang KY, Hubert J, Cui Y, Liu X, Tsui SK-W. Endogenous plasmids and chromosomal genome reduction in the \u003cem\u003eCardinium\u003c/em\u003e endosymbiont of \u003cem\u003eDermatophagoides farinae\u003c/em\u003e. mSphere. 2023;8(2):e0007423. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/msphere.00074-23\u003c/span\u003e\u003cspan address=\"10.1128/msphere.00074-23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHalter T, Hendrickx F, Horn M, Manzano-Marin A. A novel widespread MITE element in the repeat-rich genome of the \u003cem\u003eCardinium\u003c/em\u003e endosymbiont of the spider \u003cem\u003eOedothorax gibbosus\u003c/em\u003e. Microbiol Spectr. 2022;10(6):e0262722. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/spectrum.02627-22\u003c/span\u003e\u003cspan address=\"10.1128/spectrum.02627-22\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMathers TC, Mugford ST, Hogenhout SA, Tripathi L. Genome sequence of the banana aphid, \u003cem\u003ePentalonia nigronervosa\u003c/em\u003e Coquerel (Hemiptera: Aphididae) and its symbionts. G3 (Bethesda). 2020;10(12):4315\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1534/g3.120.401358\u003c/span\u003e\u003cspan address=\"10.1534/g3.120.401358\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlimov PB, Chetverikov PE, Dodueva IE, Vishnyakov AE, Bolton SJ, Paponova SS, Lutova LA, Tolstikov AV. Symbiotic bacteria of the gall-inducing mite \u003cem\u003eFragariocoptes setiger\u003c/em\u003e (Eriophyoidea) and phylogenomic resolution of the eriophyoid position among Acari. Sci Rep. 2022;12(1):3811. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-022-07535-3\u003c/span\u003e\u003cspan address=\"10.1038/s41598-022-07535-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZele F, Santos I, Matos M, Weill M, Vavre F, Magalhaes S. Endosymbiont diversity in natural populations of \u003cem\u003eTetranychus\u003c/em\u003e mites is rapidly lost under laboratory conditions. Heredity (Edinb). 2020;124(4):603\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41437-020-0297-9\u003c/span\u003e\u003cspan address=\"10.1038/s41437-020-0297-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNarita S, Nomura M, Kageyama D. Naturally occurring single and double infection with \u003cem\u003eWolbachia\u003c/em\u003e strains in the butterfly \u003cem\u003eEurema hecabe\u003c/em\u003e: transmission efficiencies and population density dynamics of each \u003cem\u003eWolbachia\u003c/em\u003e strain. FEMS Microbiol Ecol. 2007;61(2):235\u0026ndash;45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1574-6941.2007.00333.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1574-6941.2007.00333.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrank SA. Dynamics of cytoplasmic incompatibility with multiple \u003cem\u003eWolbachia\u003c/em\u003e infections. J Theor Biol. 1998;192(2):213\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1006/jtbi.1998.0652\u003c/span\u003e\u003cspan address=\"10.1006/jtbi.1998.0652\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatlav A, Cook JM, Riegler M. Common endosymbionts affect host fitness and sex allocation via egg size provisioning. Proc Biol Sci. 2022;289(1971):20212582. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2021.2582\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2021.2582\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv N, Peng J, Xin-Yi Chen, Guo C-F, Sang W, Wang X-M, Ahmed MZ, Xu Y-Y, Qiu B-L. Antagonistic interaction between male-killing and cytoplasmic incompatibility induced by \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e in the whitefly, \u003cem\u003eBemisia tabaci\u003c/em\u003e. Insect Sci. 2021;28(2):330\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1744-7917.12793\u003c/span\u003e\u003cspan address=\"10.1111/1744-7917.12793\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHalter T, Kostlbacher S, Rattei T, Hendrickx F, Manzano-Marin A, Horn M. One to host them all: genomics of the diverse bacterial endosymbionts of the spider \u003cem\u003eOedothorax gibbosus\u003c/em\u003e. Microb Genom. 2023;9(2):mgen000943. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1099/mgen.0.000943\u003c/span\u003e\u003cspan address=\"10.1099/mgen.0.000943\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite JA, Kelly SE, Cockburn SN, Perlman SJ, Hunter MS. Endosymbiont costs and benefits in a parasitoid infected with both \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e. Heredity (Edinb). 2011;106(4):585\u0026ndash;91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/hdy.2010.89\u003c/span\u003e\u003cspan address=\"10.1038/hdy.2010.89\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJu J-F, Bing X-L, Zhao D-S, Guo Y, Xi Z, Hoffmann AA, Zhang K-J, Huang H-J, Gong J-T, Zhang X, Hong X-Y. \u003cem\u003eWolbachia\u003c/em\u003e supplement biotin and riboflavin to enhance reproduction in planthoppers. ISME J. 2020;14(3):676\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41396-019-0559-9\u003c/span\u003e\u003cspan address=\"10.1038/s41396-019-0559-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewton ILG, Rice DW. The Jekyll and Hyde symbiont: could \u003cem\u003eWolbachia\u003c/em\u003e be a nutritional mutualist? J Bacteriol. 2020;202(4):e00589-00519. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/JB.00589-19\u003c/span\u003e\u003cspan address=\"10.1128/JB.00589-19\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNevalainen LB, Layton EM, Newton ILG. \u003cem\u003eWolbachia\u003c/em\u003e promotes its own uptake by host cells. Infect Immun. 2023;91(2):e0055722. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/iai.00557-22\u003c/span\u003e\u003cspan address=\"10.1128/iai.00557-22\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu C, Wang J-L, Zheng Y, Xiong E-J, Li J-J, Yuan L-L, Yu X-Q, Wang Y-F. \u003cem\u003eWolbachia\u003c/em\u003e-induced paternal defect in \u003cem\u003eDrosophila\u003c/em\u003e is likely by interaction with the juvenile hormone pathway. Insect Biochem Mol Biol. 2014;49:49\u0026ndash;58. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ibmb.2014.03.014\u003c/span\u003e\u003cspan address=\"10.1016/j.ibmb.2014.03.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDou W, Miao Y, Xiao J, Huang D. Association of \u003cem\u003eWolbachia\u003c/em\u003e with gene expression in \u003cem\u003eDrosophila\u003c/em\u003e testes. Microb Ecol. 2021;82(3):805\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00248-021-01703-0\u003c/span\u003e\u003cspan address=\"10.1007/s00248-021-01703-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi H, Harwood JD, Liu T, Chu D. Novel proteome and acetylome of \u003cem\u003eBemisia tabaci\u003c/em\u003e Q in response to \u003cem\u003eCardinium\u003c/em\u003e infection. BMC Genomics. 2018;19(1):523. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12864-018-4907-3\u003c/span\u003e\u003cspan address=\"10.1186/s12864-018-4907-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMann E, Stouthamer CM, Kelly SE, Dzieciol M, Hunter MS, Schmitz-Esser S. Transcriptome sequencing reveals novel candidate genes for \u003cem\u003eCardinium hertigii\u003c/em\u003e-caused cytoplasmic incompatibility and host-cell interaction. mSystems. 2017;2(6):e00141-00117. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/mSystems.00141-17\u003c/span\u003e\u003cspan address=\"10.1128/mSystems.00141-17\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang K, Yuan M-Y, Liu Y, Guo C-L, Liu T-X, Zhang Y-J, Chu D. First evidence for thermal tolerance benefits of the bacterial symbiont \u003cem\u003eCardinium\u003c/em\u003e in an invasive whitefly, \u003cem\u003eBemisia tabaci\u003c/em\u003e. Pest Manag Sci. 2021;77(11):5021\u0026ndash;31. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ps.6543\u003c/span\u003e\u003cspan address=\"10.1002/ps.6543\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVoronin D, Cook DAN, Steven A, Taylor MJ. Autophagy regulates \u003cem\u003eWolbachia\u003c/em\u003e populations across diverse symbiotic associations. Proc Natl Acad Sci U S A. 2012;109(25):E1638\u0026ndash;46. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1203519109\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1203519109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite PM, Serbus LR, Debec A, Codina A, Bray W, Guichet A, Lokey RS, Sullivan W. Reliance of \u003cem\u003eWolbachia\u003c/em\u003e on high rates of host proteolysis revealed by a genome-wide RNAi screen of \u003cem\u003eDrosophila\u003c/em\u003e cells. Genetics. 2017;205(4):1473\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1534/genetics.116.198903\u003c/span\u003e\u003cspan address=\"10.1534/genetics.116.198903\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePorter J, Sullivan W. The cellular lives of \u003cem\u003eWolbachia\u003c/em\u003e. Nat Rev Microbiol. 2023;21(11):750\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41579-023-00918-x\u003c/span\u003e\u003cspan address=\"10.1038/s41579-023-00918-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhite PM, Pietri JE, Debec A, Russell S, Patel B, Sullivan W. Mechanisms of horizontal cell-to-cell transfer of \u003cem\u003eWolbachia\u003c/em\u003e spp. in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e. Appl Environ Microbiol. 2017;83(7):e03425-03416. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/AEM.03425-16\u003c/span\u003e\u003cspan address=\"10.1128/AEM.03425-16\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerree PM, Frydman HM, Li JM, Cao J, Wieschaus E, Sullivan W. \u003cem\u003eWolbachia\u003c/em\u003e utilizes host microtubules and dynein for anterior localization in the \u003cem\u003eDrosophila\u003c/em\u003e oocyte. PLoS Pathog. 2005;1(2):e14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.ppat.0010014\u003c/span\u003e\u003cspan address=\"10.1371/journal.ppat.0010014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamura Y, Gotoh T, Imanishi S, Mita K, Kurtti TJ, Noda H. Differentially expressed genes in silkworm cell cultures in response to infection by \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e endosymbionts. Insect Mol Biol. 2011;20(3):279\u0026ndash;89. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1365-2583.2010.01056.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1365-2583.2010.01056.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMills MK, McCabe LG, Rodrigue EM, Lechtreck KF, Starai VJ. Wbm0076, a candidate effector protein of the \u003cem\u003eWolbachia\u003c/em\u003e endosymbiont of \u003cem\u003eBrugia malayi\u003c/em\u003e, disrupts eukaryotic actin dynamics. PLoS Pathog. 2023;19(2):e1010777. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.ppat.1010777\u003c/span\u003e\u003cspan address=\"10.1371/journal.ppat.1010777\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDeehan M, Lin W, Blum B, Emili A, Frydman H. Intracellular density of \u003cem\u003eWolbachia\u003c/em\u003e is mediated by host autophagy and the bacterial cytoplasmic incompatibility gene \u003cem\u003ecifB\u003c/em\u003e in a cell type-dependent manner in \u003cem\u003eDrosophila melanogaster\u003c/em\u003e. mBio. 2021;12(1):e02205-02220. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/mBio.02205-20\u003c/span\u003e\u003cspan address=\"10.1128/mBio.02205-20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang K, Qin P-H, Yuan M-Y, Chen L, Zhang Y-J, Chu D. Infection density pattern of \u003cem\u003eCardinium\u003c/em\u003e affects the responses of bacterial communities in an invasive whitefly under heat conditions. Insect Sci. 2023;30(4):1149\u0026ndash;64. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1744-7917.13141\u003c/span\u003e\u003cspan address=\"10.1111/1744-7917.13141\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErban T, Klimov PB, Smrz J, Phillips TW, Nesvorna M, Kopecky J, Hubert J. Populations of stored product mite \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e differ in their bacterial communities. Front Microbiol. 2016;7:1046. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fmicb.2016.01046\u003c/span\u003e\u003cspan address=\"10.3389/fmicb.2016.01046\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKopecky J, Perotti MA, Nesvorna M, Erban T, Hubert J. \u003cem\u003eCardinium\u003c/em\u003e endosymbionts are widespread in synanthropic mite species (Acari: Astigmata). J Invertebr Pathol. 2013;112(1):20\u0026ndash;3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jip.2012.11.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jip.2012.11.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErban T, Klimov P, Molva V, Hubert J. Whole genomic sequencing and sex-dependent abundance estimation of \u003cem\u003eCardinium\u003c/em\u003e sp., a common and hyperabundant bacterial endosymbiont of the American house dust mite, \u003cem\u003eDermatophagoides farinae\u003c/em\u003e. Exp Appl Acarol. 2020;80(3):363\u0026ndash;80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10493-020-00475-5\u003c/span\u003e\u003cspan address=\"10.1007/s10493-020-00475-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Additional File 1","content":"\u003cp\u003eAdditional File 1 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mite, Cardinium, Wolbachia, Genome, Gene expression, Interaction","lastPublishedDoi":"10.21203/rs.3.rs-3848978/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3848978/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe different cultures of stored product mite \u003cem\u003eTyrophagus putrescentiae\u003c/em\u003e are single-infected by intracellular bacteria \u003cem\u003eCardinium\u003c/em\u003e or \u003cem\u003eWolbachia\u003c/em\u003e. No natural double-infected \u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia-infected\u003c/em\u003e mites are known. Under the experiment, single-infected mite (\u003cem\u003eWolbachia\u003c/em\u003e 5N, 5P and \u003cem\u003eCardinium\u003c/em\u003e 5L, 5S) cultures were mixed to double-infected cultures (5LP, 5LN, 5SP, 5SN). The mite fitness and symbionts' presence were analyzed during 5-month-long experiment. \u003cem\u003eCardinium, Wolbachia\u003c/em\u003e and mite genomes were assembled and gene expression in single and double-infected cultures was analyzed. In double-infected cultures, \u003cem\u003eCardinium\u003c/em\u003e infection increased with the time of the experiment from 50 to 95% of infected mites. \u003cem\u003eCardinium\u003c/em\u003e\u0026thinsp;+\u0026thinsp;\u003cem\u003eWolbachia\u003c/em\u003e-infected mite individuals proportion ranged from 0 to 20% of mites in double-infected cultures. \u003cem\u003eWolbachia\u003c/em\u003e infection disappeared in all double-infected cultures up to 5 months of the experiment duration. The double-infected cultures had lower fitness than single-infected cultures. After a month of experiment, the fitness of originally double-infected cultures increased to the level of parental cultures. The correlation analyses of gene expression showed that \u003cem\u003eWolbachia\u003c/em\u003e had well-established interactions with mite predicted KEGG gene expression in a single-infected population. The expression of mite protein was strongly influenced by the presence of \u003cem\u003eWolbachia\u003c/em\u003e, but not by \u003cem\u003eCardinium\u003c/em\u003e. The total numbers of \u003cem\u003eCardinium\u003c/em\u003e-expressed genes did not change, while there was a ten-fold decrease in \u003cem\u003eWolbachia\u003c/em\u003e in double-infected cultures. \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e gene expression showed 30% negative and 70% positive (N\u0026thinsp;=\u0026thinsp;3793) correlations. The number of correlations between \u003cem\u003eWolbachia\u003c/em\u003e and mite gene expression 5 times decreased in double-infected cultures. The \u003cem\u003eCardinium\u003c/em\u003e had a 6-fold higher number of genes than \u003cem\u003eWolbachia\u003c/em\u003e with significantly higher expression in the multiple infected samples. The gene expression analysis provides a suggestion that the presence of \u003cem\u003eCardinium\u003c/em\u003e inhibits the growth of \u003cem\u003eWolbachia\u003c/em\u003e by the disruption of the \u003cem\u003eWolbachia\u003c/em\u003e interaction with mite host. However, we cannot eliminate stochastic processes resulting in the increase of \u003cem\u003eWolbachia\u003c/em\u003e abundance and symbiont change.\u003c/p\u003e \u003cp\u003e \u003cb\u003eImportance\u003c/b\u003e We sought insight into the intracellular symbionts\u0026rsquo; competition in the novel mite host model. The manipulative experiments established double-infected \u003cem\u003eWolbachia Cardinium\u003c/em\u003e cultures, which were unstable due to their low fitness. \u003cem\u003eCardinium\u003c/em\u003e prevailed during five months in all 4 double-infected cultures. The competition disrupted \u003cem\u003eWolbachia's\u003c/em\u003e interaction with its host on the level of gene expression. The genome expression is highly correlated between \u003cem\u003eWolbachia\u003c/em\u003e and mite hosts in single \u003cem\u003eWolbachia\u003c/em\u003e-infected cultures. These correlations disappeared in multi-infected cultures. Differently, the interaction among host and \u003cem\u003eCardinium\u003c/em\u003e genes showed low differences in the gene expression level. Although \u003cem\u003eCardinium\u003c/em\u003e/\u003cem\u003eWolbachia\u003c/em\u003e-infested individuals are rare, the gene expression of \u003cem\u003eCardinium\u003c/em\u003e and \u003cem\u003eWolbachia\u003c/em\u003e had a high number of positive correlations. It indicates that the symbionts reacted to each other. The data indicates that we have established a new model to study \u003cem\u003eWolbachia\u003c/em\u003e and \u003cem\u003eCardinium\u003c/em\u003e interactions.\u003c/p\u003e","manuscriptTitle":"The Cardinium wins on Wolbachia in double-infected mite cultures","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-12 17:45:32","doi":"10.21203/rs.3.rs-3848978/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03b9f335-0665-4f36-bef7-bb87f60879b6","owner":[],"postedDate":"January 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-12T19:19:48+00:00","versionOfRecord":{"articleIdentity":"rs-3848978","link":"https://doi.org/10.1128/msystems.01769-24","journal":{"identity":"msystems","isVorOnly":true,"title":"mSystems"},"publishedOn":"2025-04-18 00:00:00","publishedOnDateReadable":"April 18th, 2025"},"versionCreatedAt":"2024-01-12 17:45:32","video":"","vorDoi":"10.1128/msystems.01769-24","vorDoiUrl":"https://doi.org/10.1128/msystems.01769-24","workflowStages":[]},"version":"v1","identity":"rs-3848978","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3848978","identity":"rs-3848978","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}