Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum

Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum | 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 Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum Nabil Radouane, Khaoula Errafii, Salma Mouhib, Khadija Ait SiMhand, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4423289/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Sep, 2024 Read the published version in Microbial Ecology → Version 1 posted 12 You are reading this latest preprint version Abstract Microbiota associated with host–parasite relationships offer an opportunity to explore interactions among plants, parasites, and microbes, thereby contributing to the overall complexity of community structures. The dynamics of ecological interactions between parasitic plants and their hosts in arid environments remain largely understudied, especially in Africa. This study aimed to examine the bacterial communities of Cuscuta epithymum L. (clover dodder), an epiphytic parasitic plant, and its host, Ziziphus lotus L. (jujuba) , in an arid environment. Our goal was to uncover the ecological complexities of microbial communities within the framework of plant–plant interactions. We conducted a comprehensive analysis of the bacterial composition and diversity within populations of the C. epithymum parasite, the infected- and non-infected jujuba host, and their interface at the shoots of the host. This involved amplicon sequencing, targeting the V5–V6 regions of the 16S rRNA gene. A total of 5680 amplicon sequence variants (ASVs) were identified, with Pseudomonadota , Bacillota , and Actinobacteriota being prevalent phyla. Among the bacterial communities, three genera were dominant: Cutibacterium , Staphylococcus , and Acinetobacter . Interestingly, analyses of alpha- and beta-diversities revealed no significant difference between jujuba and its parasite, suggesting a shared shoot endophytic bacteriome. This finding advances our comprehension of microbial communities linked to plant–parasite interactions in the arid environments of Africa. Further studies on functional diversity and elucidation of the mechanisms by which bacterial communities transfer between host and parasite are needed. 16S rRNA Gene Metabarcoding Arid Environment Complex Interaction Cuscuta epi-thymum Microbial diversity Parasitic plant Ziziphus lotus Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Parasitic plants are fascinating components of terrestrial ecosystems, influencing ecological dynamics and the structure of plant ecology. Among these parasitic plants, the genus Cuscuta , which comprises plant holoparasites belonging to the tribe Cuscutaceaeand family Convolvulaceae [1], stands out as an important and economically significant genus known for its detrimental effects on agriculture, especially in sub-humid and semi-arid areas of Africa and Asia [2]. These plants are categorized as obligate parasites because they lack chlorophyll, rendering them unable to perform photosynthesis [3]. Consequently, they rely entirely on their host plants for water, nutrients, and carbohydrates. Cuscuta spp. typically exhibit filament-like, yellow to orange stems with flowers that emerge at maturity, entwining around the stems and leaves of their host plants. Cuscuta spp. are distributed worldwide, inhabiting various ecosystems from tropical to temperate regions [3]. Due to their parasitic nature, Cuscuta spp. are often considered detrimental to agriculture. If not managed effectively, they can significantly reduce the growth and yield of host plants. However, they also play ecological roles within their ecosystems by altering the competitive balance between host and non-host species, thereby influencing community structure, vegetation zonation, and population dynamics [4]. Moreover, they have been studied for their interactions with host plants, as well as their potential medicinal properties [3]. The genus Cuscuta encompasses numerous species, including C. campestris and C. epithymum , known to be the most widespread and aggressive species within this genus [5]. Cuscuta spp. initiate their parasitic phase by forming specialized structures called haustoria. These haustoria penetrate the host plant’s stem, providing Cuscuta spp. with a physical connection through which they not only extract nutrients but also secure themselves by attaching to the host. As the parasitic relationship progresses, Cuscuta spp. continue to proliferate, forming a dense network of intertwining stems that further magnify their impact, eventually leading to detrimental effects on host growth, development, and reproduction [6-8]. In this study, sampling was conducted in the Rhamna region of Morocco, where the Cuscuta epithymum species attacks the jujube shrub ( Ziziphus lotus L .), commonly referred to as “Sedra”. Z. lotus is a resilient species commonly found in arid environments where it forms shrub clusters or patchy vegetation. It is well adapted to survive in harsh conditions with limited water availability and plays a crucial role in ecosystem dynamics. It forms a deep root system that enables it to access water from deep within the soil, allowing it to thrive even in dry conditions. The shrub provides valuable shade and shelter for various arid fauna, contributing to local biodiversity and mitigating soil erosion via wind and water [9].Furthermore, Z. lotus holds a prominent place in traditional medicine due to its various medicinal properties, as well as the ecological services it provides [9-12].However, Z. lotus faces threats from habitat loss and degradation due to human activities, such as overgrazing and agricultural expansion, as well as potential risks caused by Cuscuta spp. attacks. Conservation efforts are important for protecting this species and preserving its ecological significance in arid environments, especially within the context of global climate change. Despite the ecological importance of jujube– Cuscuta associations, there is a gap in scientific research regarding their microbial composition and diversity. To date, no studies have specifically investigated the interactions between Z. lotus and its parasite C. epithymum and their associated microbiota. This represents a significant knowledge gap, considering the pivotal role of microbial communities in mediating plant health, nutrient cycling, and ecosystem functioning. Although a previous study shed light on the rhizospheric microbial communities associated with both native and cultivated plant species affected by Cuscuta parasitism[13], the objective of this study is to document the diversity and community structure of bacteria associated with Z. lotus and C. epithymum , using amplicon sequencing that targets the 16S rRNA gene [14-16]. This tool has revolutionized the study of microbial diversity, allowing for the rapid and comprehensive characterization of previously unexplored microbial communities in various environments [17]. Through this study, we aimed to advance our understanding of the microbial ecology associated with parasitic plants and their hosts and explore the implications of these interactions with respect to ecosystem dynamics and potential implications for conservation programs. We hypothesize that Z. lotus and its parasite C. epithymum share an endophytic bacterial community because of the physical connections between their stems via haustoria, which act as a pathway for bacterial transmission between host and parasite. To test this hypothesis, we conducted a sampling campaign in arid environments where the jujube shrub naturally thrives and dominates the landscape. Shoot samples were collected from shrubs infected by C. epithymum. We performed 16S rRNA gene amplicon sequencing, targeting the V5–V6 regions, which allows for more specific amplification of bacterial 16S rDNA compared to the V3–V4 regions, thereby minimizing contamination from the plant's chloroplast. Materials and methods 1. Sampling: A two-day sampling campaign was conducted on June 10 th and 11 th in Benguerir, Rhamna, Morocco (N32°12’11.67”, W7°56’8.451”). The site features patchy vegetation that is primarily dominated by jujube shrubs, as shown in Figure 1A. Each patch represents a cluster with a diameter approximately ranging from 1 to 5 meters. Nine shrubs of Ziziphus lotus L. infected by Cuscuta epithymum were sampled, as illustrated in Figure 1B. The sample collection involved obtaining young stems (approximately 20 cm long) from various parts of each cluster, including non-infected stems, stems infected by Cuscuta , and Cuscuta stems alone (yellow to orange stems, Figure 1C). Additionally, a control sample was obtained from a non-infected plant situated away from the infection site (at the periphery of the cluster). All samples were placed in 20x30 cm Ziploc plastic bags, which were then placed on an ice pack and transported to the laboratory (African Genome Center, Benguerir, Morocco). In the laboratory, the non-infected Z. lotus stems were processed as follows: From each sample, two to three 5 cm long top stems were cut; disinfected with 70% ethanol, followed by a bleach solution; and rinsed three times using autoclaved water. They were then placed on autoclaved paper towels for drying. For infected samples (Figure 1D), only the fragments of Z. lotus coiled by Cuscuta stems were cut and subjected to the same disinfection, cleaning, and washing procedures as described above. Finally, Cuscuta stems were also disinfected, cleaned, and washed. The dried samples were stored in 15 ml containers at -20°C until further use. 2. DNA extraction and polymerase chain reaction (PCR) quantification Total DNA extraction was conducted on 50 mg of lyophilized stem fragments from each sample type, including non-infected jujuba, infected jujuba, and Cuscuta alone. Samples were ground using a TissueLyser II and 2 mm Tungsten beads (QIAGEN, Global Diagnostic Distribution, Témara, Morocco) in 2 ml tubes for 15 minutes at a frequency of 24 Hz. The DNeasy Plant Pro kit (QIAGEN, Global Diagnostic Distribution, Témara, Morocco) was used to extract total DNA following the manufacturer's instructions. The quality and quantity of the extracted DNA were evaluated via gel electrophoresis and DNA quantification with a BioSpectrophotometer (Eppendorf, Hamburg, Germany). 3. PCR amplification The V5–V6 hypervariable region of the 16S rRNA gene from each sample was amplified using the primer pair with custom sequence (CS) adapters at the 5’ end: CS1 -719F/ ACACTGACGACATGGTTCTACA- AACMGGATTAGATACCCKG and CS2 -1115R TACGGTAGCAGAGACTTGGTCT- AGGGTTGCGCTCGTTG[18]. PCR amplification was performed using the Platinum Direct PCR Universal Master Mix (ThermoFisher, Rabat, Morocco) in a final volume of 25 μL. Each PCR contained 1X of the PCR Universal Master Mix, 0.2 µM of each primer, and approximately 10 ng of genomic DNA. The PCRs were run in a thermocycler Mastercycler X50s (Eppendorf, Hamburg, Germany) following this program: initial denaturation at 94°C for 3 minutes, followed by 35 cycles consisting of denaturation at 94°C for 30 seconds, annealing at 55°C for 30 seconds, elongation at 72°C for 1 minute, and a final extension step at 72°C for 5 minutes before being held at 4°C. Each reaction, including negative controls with sterile Milli-Q water and positive controls, was carried out in duplicate. 4. Library Preparation and Sequencing The bacterial 16S rRNA gene amplicon library preparation was generated using Agencourt AMPure XP beads (Beckman Coulter, USA) to clean the PCR products. Two ethanol washes were performed, followed by air drying. Purified PCR products were then resuspended in 10 mM Tris (pH 8.5). A second PCR was performed to attach Illumina sequencing adapters and index tags. PCRs for indexing contained 5 µL of purified PCR product, 2.5 µL of Fluidigm Access Array Barcode 384, and 1X KAPA HiFi HotStart ReadyMix (Roche Sequencing Solutions). The PCR volume was 50 µL per reaction. The PCR was run under the following conditions: an initial denaturation at 95°C for 3 minutes, followed by 8 cycles of denaturation at 95°C for 30 seconds, annealing at 55°C for 30 seconds, extension at 72°C for 30 seconds, and a final extension at 72°C for 5 minutes. The indexed amplicons were subsequently purified using Agencourt ampure XP beads and quantified using a Qubit assay and the DNA HS kit (ThermoFisher, Témara Morocco). Library quantification, normalization, and pooling were performed following Illumina’s instructions. The bacterial 16S rRNA gene libraries were sequenced on an Illumina MiSeq sequencing instrument (Illumina, Paris, France) using a MiSeq reagent V3 kit (300 cycles of paired-end sequencing). 5. Bioinformatics analysis The resulting fastq files were processed using R version 4.3.3 (the R Project for Statistical Computing). The quality profile of the reads was inspected using the DADA2 pipeline implemented in R [19], and the raw sequence reads with poor average quality scores (< 30) were discarded. The bacterial reads were filtered and trimmed using DADA2 to eliminate primer and adaptor sequences. In addition, error rates for each consensus quality score were evaluated. The denoised forward and reverse reads longer than 10 bp were merged into a multiple sequence alignment using the DECIPHER package, and amplicon sequence variances (ASVs) were obtained. Taxonomic annotation was performed using the most updated and extensive SILVA database for bacteria for the resulting amplicon sequence variants (ASVs) [20, 21]. 6. Statistical analyses Bacterial alpha diversity was calculated through the Shannon and Simpson indices at the ASV level using the phyloseq package [22]. Beta diversity was assessed by computing the Bray–Curtis distance across different microbial taxa, and it was tested through PERMANOVA using the adonis command of the vegan package [23]. The command betadispers from the vegan package was also used to test the difference in dispersion between different conditions. The hub taxa of the communities were determined using the SpiecEasi [24] and igraph package of R [25] by calculating the betweenness of each taxon. The betweenness represents the number of times an ASV is present on an edge connecting other ASVs. Thus, it indicates a probability that the organism corresponding to this ASV mediates interactions in the community. Random forest models were created using the randomForest package of R [26] and 100 repeated trees. The best models created with this package were then evaluated in terms of the strength of their predictive power with respect to discriminating between conditions based on communities; the best predictor taxa were listed. Significant associations of taxa with respect to the conditions were calculated using the indicspecies package [27]. Results Taxonomic composition A total of 1323845 16S reads were detected, which were then assigned to 3644 bacterial ASVs comprising 652 genera, 245 families, 134 orders, 62 classes, and 27 phyla. In total, 1947 ASVs were present in jujube samples, 1656 ASVs were present in Cuscuta samples, and 1686 were present in interaction samples. Among these ASVs, 22% were only found in Cuscuta , and 29.8% were only found in jujube. The most abundant phyla in the samples were Pseudomonadota (44%), Bacillota (27%), and Actinobacteriota (21%) (Figure 2A, 2B). The most abundant genera were Cutibacterium (10%), Staphylococcus (8%), and Acinetobacter (8%), with a substantial number of ASVs of unknown genus (25%). Alpha and beta diversities For alpha diversity, both the Shannon and Simpson indices showed no significant differences when comparing origins or samples (with respective p -values of 0.3 and 0.5). Additionally, clustering did not significantly influence the Shannon and Simpson indices (with respective p -values of 0.1 and 0.4). Overall, no parameter was found to significantly affect alpha diversity. There were also no significant differences in beta diversity observed either according to the origin or the cluster (PERMANOVA, with respective p -values of 0.6 and 0.3) (Figure 4 and Table 1). However, a betadispers test revealed significant differences in dispersion among communities within certain clusters ( p = 0.047), although no significant differences in dispersion were found due to the origin ( p = 0.3). Core taxa Two ASVs—ASV18 from the Staphylococcus genus and ASV21 from the Cutibacterium genus—were present in over 90% of all samples. Therefore, these two ASVs can be considered core taxa associated with Ziziphus lotus and jujube-infecting Cuscuta epithymum in our sampling. Additionally, three other ASVs were found in six out of seven control Ziziphus lotus samples: ASV20 from the Staphylococcus genus, ASV22 from the Neisseriaceae family, and ASV26 from the Staphylococcus genus. At the family and genus levels, the only core taxa detected were those containing the ASV18 and ASV21 mentioned earlier; thus, no additional core taxa were identified at higher taxonomic levels. Following an analysis of network betweenness, one ASV from the Staphylococcus genus exhibited the highest betweenness score (1534) among all taxa and can be described as a hub ASV (Figure 5). Furthermore, as no other ASV has a betweenness score exceeding 95% of this value, it can be considered the sole hub taxon within the community. Associated and predictor taxa Interestingly, 40 ASVs from 29 genera (Table 2) were found to be significantly associated with control shrubs (non-infected jujube shrubs away from the infection by C. epithymum ), whereas infected shrubs had only one ASV from the genus Caulobacter , which was significantly associated with their group. No taxa showed differential associations with C. epithymum , infected jujube shrubs, or the interaction zone. A random forest model successfully discriminated between control and non-control samples with an error rate of 8.05%. However, when another model was developed to differentiate between C. epithymum , infected Z. lotus , and interaction samples, the error rate increased to 50%, indicating the model's inability to discriminate between these sample types (Figure 6). The 20 most important ASVs for predicting differences between control and non-infected samples are detailed in Table 3. Among these predictor ASVs, four belonged to the Cutibacterium genus, three to the Staphylococcus genus, and one to the Acinetobacter genus. Discussion Investigating bacterial diversity within the interaction of Cuscuta epithymum and Ziziphus lotus through a metabarcoding approach is crucial for obtaining a thorough understanding of the intricate dynamics of plant microbiota. This becomes especially significant given the scarcity of research in this domain, which impedes our comprehension of African microbiomes [28]. Among the identified phyla, Pseudomonadota, Bacillota, and Actinobacteriota were the predominant taxa in the bacteriome of both the jujube shrubs and their parasite C. epithymum . Together, these phyla constituted the majority of bacterial sequences in the samples. Pseudomonadota was the predominant phylum, comprising 44% of the bacterial community, followed by Bacillota at 27% and Actinobacteriota at 21%. These results align with previous research, which has highlighted the prevalent presence of bacterial taxa such as Pseudomonadota, Acidobacteriota, and Actinomycetota in the phyllosphere of plants thriving in hyper-arid environments[29]. Pseudomonadota, in particular, serves as a notable example of a copiotrophic bacterial phylum, as highlighted in various studies [30-32]. Moreover, two ASVs—ASV18 belonging to the Staphylococcus genus and ASV21 belonging to the Cutibacterium genus—were found in more than 90% of all samples of this study. ASV18 belongs to the Staphylococcus genus and is a core taxon; it was found to be phylogenetically related to Staphylococcus hominis , which has been characterized as a plant endophyte of jute seeds and exhibited antimicrobial activity through antibiotic (homicorcin) production [33]. Staphylococci, frequently associated with humans and recognized for their potential pathogenicity, have been consistently found in plant environments. Notably, metabarcoding studies have revealed their presence as endophytes in seeds, such as those of Anadenanthera colubrina , a legume tree [34], and rice [35]. Furthermore, they have been identified in various plant tissues, including soybeans [36]. The second identified ASV21 belongs to the Cutibacterium genus, which has been reported to be present in both Citrus limon seeds and shoots [36]. Nevertheless, this genus has also been observed as an endophyte in the cultivated grapevine Vitis vinifera , comprising 5% of the total sequence reads [37], and it is a constituent of the human skin microbiota. Despite the disinfection of our samples and the high abundance of this taxon, potential contamination is unlikely [36, 38]. Furthermore, the majority of the genera identified in this study from the shoot microbiota are known to exhibit plant-growth promotion activities [39]. This study on the endophytic bacteriome of C. epithymum and its host plant Z. lotus revealed that both partners in the parasitic relationship share a common bacteriome. Microbial species may experience either promotion or inhibition due to the parasitic relationship, thus resulting in diversity affected by plant parasitism [13]. Shifts in the prevalence of certain taxa related to parasitism may impact plant performance. For example, the reduction in the abundance of identified species could affect plant stress tolerance [40, 41]. Cuscuta parasitism has also been reported to influence the expression levels of genes essential for bacterial survival and sporulation [42, 43]. In contrast to previous findings suggesting a high degree of host specificity within the microbiota of Cuscuta pedicellata and its host plant [44], our results indicate a lack of discernible variation in bacterial communities among the studied samples. The diversity and composition of this shared bacteriome did not exhibit any significant differences or distinct groups among the analyzed samples, including the control. These results indicate that the parasitic relationship between C. epithymum and Z. lotus does not alter the composition of the Z. lotus bacteriome. Instead, they share the same endophytic community, supporting our hypothesis, which posited that Z. lotus and its parasite C. epithymum share an endophytic bacterial community due to the physical connections between their stems via haustoria, which act as a pathway for bacterial transmission between host and parasite. While previous studies have identified distinct bacterial and fungal species as endophytes and epiphytes, our findings challenge the notion of host specificity within the phyllosphere microbiota associated with C. pedicellata and its host plants [45]. Cuscuta spp. establish direct connections with the vascular system of their host plants, including the xylem and phloem [46]. The linkage with the host's phloem has been demonstrated through experimental findings. For instance, studies using the phloem-specific dye carboxyfluorescein have shown movement from the host into Cuscuta tissues [47, 48]. Additionally, research on transgenic tobacco plants expressing green fluorescent proteins in companion cells has indicated the potential transfer of proteins to C uscuta , implying the possibility of direct macromolecule transfer [49]. In our sampling, the infection of C. epithymum extended across a vast area, encompassing numerous shoots of various individuals within the cluster (Figure 1 B and C). Hence, it is probable that C. epithymum shoots acted as a transmission vector, thereby homogenizing the endophytic bacteriome of Z. lotus ,including both infected and control samples. A well-documented phenomenon is the transmission of viruses between the host and Cuscuta spp. It has been observed that a single Cuscuta plant parasitizing two hosts simultaneously may facilitate the transmission of plant viruses from one host to the other[46]. Apart from these direct vascular connections, Cuscuta also exhibits cytoplasmic continuity with its host through plasmodesmata[50]. Cuscuta spp. introduce significant challenges in agricultural settings due to their broad host range and non-specific attack patterns. Moreover, studies have confirmed the capability of Cuscuta species to transmit viruses between plants by establishing haustoria connections with the vascular tissues of the host. This method of transmission shares similarities with grafting, yet dodder distinguishes itself by transmitting viruses across distantly related plants, a feat not achievable through grafting, which usually involves closely related species. Furthermore, dodder can passively facilitate virus transmission, particularly under experimental conditions conducive to the movement of nutrients from infected to uninfected plants. Consequently, dodder has been employed in experimental research to transfer viruses from challenging-to-study hosts to more accessible experimental plants [46]. Conclusion This study investigated the endophytic bacteriome of C. epithymum and its host plant Z. lotus , revealing a shared bacteriome between both partners in the parasitic relationship. The diversity and composition of this shared bacteriome did not display any significant differences or distinct groups among the analyzed samples. These findings suggest that the parasitic relationship between Cuscuta and Z. lotus does not alter the composition of the Z. lotus bacteriome; instead, they share the same endophytic community, supporting our hypothesis. Cuscuta spp. establish direct connections with the vascular system of their host plants, including the xylem and phloem. Experimental findings have demonstrated the physical connection with the host's vascular system. In addition to these direct vascular connections, Cuscuta also exhibits cytoplasmic continuity with its host through plasmodesmata. Drawing from this, it is probable that C. epithymum plays a role in linking the jujube plants and potentially homogenizing their microbiome, as indicated by the capability to predict control plants using specific ASVs with the random forest model. The isolation and characterization of bacterial endophytes from the shoots of both Cuscuta and jujube could aid in designing future investigations to validate the potential transmission of bacterial endophytes between jujube shrubs and its parasite Cuscuta using the isolated taxa transformed with fluorescent proteins. Declarations Acknowledgements : This work was funded by the OCP Group (Projects AS-77 and AS-85) and UM6P. We express our gratitude to Dr Zineb Rchiad for her help and support with sample collection and sample preparation. We also thank SIMLAB of UM6P for providing the computational infrastructure used for bioinformatics data processing. Author contributions: N.R. performed the experiments, analyzed the data, and wrote the manuscript draft. K.E. performed the MiSeq and wrote the manuscript draft. S.M. and K.A.M. contributed to sample preparation and performing experiment. J.L analyzed the data. 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De Caceres M, Legendre P (2009) Associations between species and groups of sites: indices and statistical inference. Ecology 90: 3566-3574. doi: 10.1890/08-1823.1 Makhalanyane TP, Bezuidt OKI, Pierneef RE, Mizrachi E, Zeze A, Fossou RK, Kouadjo CG, Duodu S, Chikere CB, Babalola OO, Klein A, Keyster M, du Plessis M, Yorou NS, Hijri M, Rossouw T, Kamutando CN, Venter S, Moleleki LN, Murrell C (2023) African microbiomes matter. Nat Rev Microbiol 21: 479-481. doi: 10.1038/s41579-023-00925-y Liu J, Sun X, Zuo Y, Hu Q, He X (2023) Plant species shape the bacterial communities on the phyllosphere in a hyper-arid desert. Microbiol Res 269: 127314. doi: 10.1016/j.micres.2023.127314 Nie Y, Wang M, Zhang W, Ni Z, Hashidoko Y, Shen W (2018) Ammonium nitrogen content is a dominant predictor of bacterial community composition in an acidic forest soil with exogenous nitrogen enrichment. 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Sci Rep 11: 11211. doi: 10.1038/s41598-021-90613-9 Alibrandi P, Cardinale M, Rahman MDM, Strati F, Ciná P, de Viana ML, Giamminola EM, Gallo G, Schnell S, De Filippo C, Ciaccio M, Puglia AM (2017) The seed endosphere of Anadenanthera colubrina is inhabited by a complex microbiota, including Methylobacteriumspp. and Staphylococcus spp. with potential plant-growth promoting activities. Plant and Soil 422: 81-99. doi: 10.1007/s11104-017-3182-4 Chaudhry V, Sharma S, Bansal K, Patil PB (2016) Glimpse into the Genomes of Rice Endophytic Bacteria: Diversity and Distribution of Firmicutes. Front Microbiol 7: 2115. doi: 10.3389/fmicb.2016.02115 Faddetta T, Abbate L, Alibrandi P, Arancio W, Siino D, Strati F, De Filippo C, Fatta Del Bosco S, Carimi F, Puglia AM, Cardinale M, Gallo G, Mercati F (2021) The endophytic microbiota of Citrus limon is transmitted from seed to shoot highlighting differences of bacterial and fungal community structures. Sci Rep 11: 7078. doi: 10.1038/s41598-021-86399-5 Aleynova OA, Nityagovsky NN, Dubrovina AS, Kiselev KV (2022) The Biodiversity of Grapevine Bacterial Endophytes of Vitis amurensis Rupr. Plants (Basel) 11. doi: 10.3390/plants11091128 Campisano A, Ometto L, Compant S, Pancher M, Antonielli L, Yousaf S, Varotto C, Anfora G, Pertot I, Sessitsch A, Rota-Stabelli O (2014) Interkingdom transfer of the acne-causing agent, Propionibacterium acnes, from human to grapevine. Mol Biol Evol 31: 1059-1065. doi: 10.1093/molbev/msu075 Sinha S, Thakuria D, Chaliha C, Uzir P, Hazarika S, Dutta P, Singh AK, Laloo B (2023) Plant growth-promoting traits of culturable seed microbiome of citrus species from Purvanchal Himalaya. Front Plant Sci 14: 1104927. doi: 10.3389/fpls.2023.1104927 Benvenuti S, Dinelli G, Bonetti A, Catizone P (2005) Germination ecology, emergence and host detection in Cuscuta campestris. Weed Research 45: 270-278. doi: 10.1111/j.1365-3180.2005.00460.x Khalid AN, Iqbal SH (1995) Mycotrophy in a vascular stem parasite Cuscuta reflexa. Mycorrhiza 6: 69-71. doi: 10.1007/s005720050109 Hutchison EA, Miller DA, Angert ER (2014) Sporulation in Bacteria: Beyond the Standard Model. Microbiol Spectr 2. doi: 10.1128/microbiolspec.TBS-0013-2012 Kakeshita H, Takamatsu H, Amikura R, Nakamura K, Watabe K, Yamane K (2001) Effect of depletion of FtsY on spore morphology and the protein composition of the spore coat layer in Bacillus subtilis. FEMS Microbiol Lett 195: 41-46. doi: 10.1111/j.1574-6968.2001.tb10495.x Irum Mukhtar IM, Sobia Mushtaq SM, Amna Ali AA, Ibatsam Khokhar IK (2012) Phyllospheric microflora of Cuscuta pedicillata Ledeb. and its host Trifolium alexandrinum L. Sivakumar N, Sathishkumar R, Selvakumar G, Shyamkumar R, Arjunekumar K (2020) Phyllospheric Microbiomes: Diversity, Ecological Significance, and Biotechnological Applications. In: Yadav, AN, Singh, J, Rastegari, AA, Yadav, N (eds.) Plant Microbiomes for Sustainable Agriculture. Springer International Publishing, Cham, pp. 113-172 Hull R (2014) Chapter 12 - Plant to Plant Movement. In: Hull, R (ed.) Plant Virology, Fifth Edition edn. Academic Press, pp. 667-751 Furuhashi T, Furuhashi K, Weckwerth W (2011) The parasitic mechanism of the holostemparasitic plantCuscuta. Journal of Plant Interactions 6: 207-219. doi: 10.1080/17429145.2010.541945 Birschwilks M, Haupt S, Hofius D, Neumann S (2006) Transfer of phloem-mobile substances from the host plants to the holoparasite Cuscuta sp. J Exp Bot 57: 911-921. doi: 10.1093/jxb/erj076 Haupt S, Oparka KJ, Sauer N, Neumann S (2001) Macromolecular trafficking between Nicotiana tabacum and the holoparasite Cuscuta reflexa . J Exp Bot 52: 173–177. Vaughn KC (2003) Dodder hyphae invade the host: a structural and immunocytochemical characterization. Protoplasma 220: 189-200. doi: 10.1007/s00709-002-0038-3 Tables Table 1: PERMANOVA test of the phylum using the Aitchison method. Degrees of freedom Sum Of Sqs R2 F Pr(>F) Cluster 9 725.3854 0.1030068 1.020762 0.454 Residual 80 6316.7252 0.8969932 NA NA Total 89 7042.1106 1.0000000 NA NA Table 2: Genera significantly associated with the control trees. Genus stat P-value Acinetobacter 0.412 0.003 ** Actinotignum 0.308 0.042 * Aggregatibacter 0.386 0.020 * Aliicoccus 0.378 0.014 * Alloprevotella 0.332 0.022 * Altererythrobacter 0.368 0.016 * Bacillus 0.415 0.005 ** Blautia 0.385 0.008 ** Caulobacter 0.308 0.022 * Chungangia 0.297 0.036 * Corynebacterium 0.356 0.019 * Deinococcus 0.408 0.015 * Enteractinococcus 0.316 0.046 * Escherichia-Shigella 0.399 0.007 ** Fusobacterium 0.303 0.031 * Geodermatophilus 0.369 0.013 * Haemophilus 0.381 0.011 * Kocuria 0.408 0.015 * Methylobacterium-Methylorubrum 0.281 0.035 * Microvirga 0.329 0.017 * Neisseria 0.395 0.017 * Pantoea 0.272 0.022 * Peptoniphilus 0.398 0.017 * Peredibacter 0.361 0.029 * Porphyromonas 0.373 0.013 * Streptococcus 0.271 0.050 * Streptomyces 0.323 0.028 * Tannerella 0.332 0.033 * Weissella 0.364 0.022 * Table 3: The 20 taxa with the highest predictive power for distinguishing between control and infected samples. ASV_ID Phylum Class Order Family Genus ASV_9 Pseudomonadota Gammaproteobacteria Enterobacterales Erwiniaceae Unknown ASV_14 Pseudomonadota Gammaproteobacteria Pseudomonadales Moraxellaceae Acinetobacter ASV_18 Bacillota Bacilli Staphylococcales Staphylococcaceae Staphylococcus ASV_20 Bacillota Bacilli Staphylococcales Staphylococcaceae Staphylococcus ASV_23 Actinobacteriota Actinobacteria Propionibacteriales Propionibacteriaceae Cutibacterium ASV_26 Actinobacteriota Actinobacteria Propionibacteriales Propionibacteriaceae Cutibacterium ASV_29 Pseudomonadota Gammaproteobacteria Burkholderiales Neisseriaceae Unknown ASV_30 Actinobacteriota Actinobacteria Propionibacteriales Propionibacteriaceae Cutibacterium ASV_36 Actinobacteriota Actinobacteria Propionibacteriales Propionibacteriaceae Cutibacterium ASV_44 Actinobacteriota Actinobacteria Corynebacteriales Corynebacteriaceae Lawsonella ASV_45 Actinobacteriota Actinobacteria Corynebacteriales Corynebacteriaceae Corynebacterium ASV_48 Proteobacteria Alphaproteobacteria Sphingomonadales Sphingomonadaceae Sphingomonas ASV_52 Bacillota Bacilli Staphylococcales Staphylococcaceae Staphylococcus ASV_56 Bacillota Bacilli Lactobacillales Enterococcaceae Enterococcus ASV_58 Actinobacteriota Actinobacteria Corynebacteriales Corynebacteriaceae Corynebacterium ASV_169 Actinobacteriota Actinobacteria Micrococcales Micrococcaceae Micrococcus ASV_197 Pseudomonadota Gammaproteobacteria Enterobacterales Aeromonadaceae Aeromonas ASV_200 Actinobacteriota Actinobacteria Actinomycetales Actinomycetaceae Actinomyces ASV_430 Bacillota Bacilli Lactobacillales Carnobacteriaceae Alloiococcus ASV_480 Pseudomonadota Alphaproteobacteria Rhodobacterales Rhodobacteraceae Paracoccus Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Sep, 2024 Read the published version in Microbial Ecology → Version 1 posted Editorial decision: Revision requested 17 Jun, 2024 Reviews received at journal 16 Jun, 2024 Reviews received at journal 11 Jun, 2024 Reviews received at journal 02 Jun, 2024 Reviewers agreed at journal 20 May, 2024 Reviewers agreed at journal 17 May, 2024 Reviewers agreed at journal 16 May, 2024 Reviewers agreed at journal 15 May, 2024 Reviewers invited by journal 15 May, 2024 Editor assigned by journal 15 May, 2024 Submission checks completed at journal 15 May, 2024 First submitted to journal 15 May, 2024 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-4423289","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304765224,"identity":"9bdb786a-dcad-4f86-a4fa-832f209d9fd4","order_by":0,"name":"Nabil Radouane","email":"","orcid":"","institution":"University Mohammed VI Polytechnic (UM6P)","correspondingAuthor":false,"prefix":"","firstName":"Nabil","middleName":"","lastName":"Radouane","suffix":""},{"id":304765225,"identity":"fbc71e27-384c-453c-8be7-57ea6fe838bf","order_by":1,"name":"Khaoula Errafii","email":"","orcid":"","institution":"University Mohammed VI Polytechnic (UM6P)","correspondingAuthor":false,"prefix":"","firstName":"Khaoula","middleName":"","lastName":"Errafii","suffix":""},{"id":304765226,"identity":"ccc02f37-1c21-401f-a06f-f98579e4ae2a","order_by":2,"name":"Salma Mouhib","email":"","orcid":"","institution":"University Mohammed VI Polytechnic (UM6P)","correspondingAuthor":false,"prefix":"","firstName":"Salma","middleName":"","lastName":"Mouhib","suffix":""},{"id":304765228,"identity":"3d3c30a6-bbd3-488f-967a-7465a3c04487","order_by":3,"name":"Khadija Ait SiMhand","email":"","orcid":"","institution":"University Mohammed VI Polytechnic (UM6P)","correspondingAuthor":false,"prefix":"","firstName":"Khadija","middleName":"Ait","lastName":"SiMhand","suffix":""},{"id":304765230,"identity":"2ee1f6ed-34f8-4516-89dc-db9211a4fc6d","order_by":4,"name":"Jean Legeay","email":"","orcid":"","institution":"University Mohammed VI Polytechnic (UM6P)","correspondingAuthor":false,"prefix":"","firstName":"Jean","middleName":"","lastName":"Legeay","suffix":""},{"id":304765233,"identity":"8db1f18a-5b38-441b-a2c6-9d4916a96d4f","order_by":5,"name":"Mohamed Hijri","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYFACHhDBzGDAzJDAkFABF7YgVssZCAcIJIjQAqIY24jQotvee/DTjQprBnN2hmcfHs47HM0v3X/sw4caCQb+9gNYtZidOZcsnXMmncGymSF5RuK2w7kz5xxmnjnjmASDxJkE7Fpu5BhI57YdZjA4zJDMANKy4UYyMzMPmwTQqTi1GP/O/QfTMgeq5c8/oBb+B7i0mEnnNsC0NEC1MLYBtUjgsOXMGTPrnGPpPGAtCcfSc2fOSDZm7O2T4JG4gcOW4z3Gt3NqrOUMzp9JZvxRY53bL5H4mOHHNxs5/n7stsAAMHZ4EtBFCAL2A0QoGgWjYBSMgpEIAFiPXDG6pQMPAAAAAElFTkSuQmCC","orcid":"","institution":"Institut de Recherche en Biologie Végétale, Université de Montréal","correspondingAuthor":true,"prefix":"","firstName":"Mohamed","middleName":"","lastName":"Hijri","suffix":""}],"badges":[],"createdAt":"2024-05-15 07:21:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4423289/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4423289/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00248-024-02421-z","type":"published","date":"2024-09-28T15:58:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57069473,"identity":"17b32595-82f1-46d8-853e-46d04d35f3f1","added_by":"auto","created_at":"2024-05-24 07:53:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":720122,"visible":true,"origin":"","legend":"\u003cp\u003eSample collection from the studied region. A) Aerial view of the region; B) \u003cem\u003eZiziphus\u003c/em\u003e \u003cem\u003elotus\u003c/em\u003e infected with \u003cem\u003eCuscuta\u003c/em\u003e \u003cem\u003eepithymum\u003c/em\u003e; C) \u003cem\u003eC.\u003c/em\u003e \u003cem\u003eepithymum\u003c/em\u003e; D) parasitic relationship between jujube and \u003cem\u003eC.\u003c/em\u003e \u003cem\u003eepithymum\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/e5d21ee21e2b86bf7ecd4192.png"},{"id":57070004,"identity":"551c7f8d-fe89-4e45-91e7-a15cffbc2246","added_by":"auto","created_at":"2024-05-24 08:01:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":107621,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of the 20 most prevalent taxa categorized by A) phyla and B) genera. Taxa not listed among the top 20 most common are grouped under \"Others\". * indicates that Patescibacteria is not classified as a phylum but rather as a candidate phyla radiation group.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/4d5ed5aa1ee986296feae378.png"},{"id":57069476,"identity":"ed9e5c64-9c90-48fd-985a-26deccc8ef8b","added_by":"auto","created_at":"2024-05-24 07:53:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":127081,"visible":true,"origin":"","legend":"\u003cp\u003eVenn diagrams illustrating the taxa present in various biotopes categorized by A) genera and B) ASVs.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/c9c923f1f17b413178128b3e.png"},{"id":57070005,"identity":"e9af5287-1cb4-456e-88c7-1b0ba96ec921","added_by":"auto","created_at":"2024-05-24 08:01:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":67275,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal coordinate analysis (PCoA) plot illustrating the samples (nine sampled jujube clusters) based on their biotopes.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/3a55ae173254ccfbfada743a.png"},{"id":57069471,"identity":"926c9b31-9311-4988-8df3-facf6b1579f9","added_by":"auto","created_at":"2024-05-24 07:53:30","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":183245,"visible":true,"origin":"","legend":"\u003cp\u003eThe network betweenness analysis revealed that one ASV from the \u003cem\u003eStaphylococcus\u003c/em\u003e genus had the highest score among all taxa, indicating its role as a hub ASV.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/428c107b989e10ec56ddfe9e.png"},{"id":57070582,"identity":"2cf9ad04-bddb-4a94-b764-97c0105d7e9f","added_by":"auto","created_at":"2024-05-24 08:09:30","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":55914,"visible":true,"origin":"","legend":"\u003cp\u003eGINI index calculated for the 20 most predictive taxa for distinguishing between control and infected samples, as determined via a random forest model.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/ba3c58c7020cfede3e04e783.png"},{"id":65627360,"identity":"3c3e6bbf-f961-47f3-8bf8-423410869ac6","added_by":"auto","created_at":"2024-09-30 16:15:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1835832,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4423289/v1/6d8acd39-704f-4b56-9055-16735564d873.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum","fulltext":[{"header":"Introduction","content":"\u003cp\u003eParasitic plants are fascinating components of terrestrial ecosystems, influencing ecological dynamics and the structure of plant ecology. Among these parasitic plants, the genus \u003cem\u003eCuscuta\u003c/em\u003e, which comprises plant holoparasites belonging to the tribe Cuscutaceaeand family Convolvulaceae\u0026nbsp;[1], stands out as an important and economically significant genus known for its detrimental effects on agriculture, especially in sub-humid and semi-arid areas of Africa and Asia\u0026nbsp;[2]. These plants are categorized as obligate parasites because they lack chlorophyll, rendering them unable to perform photosynthesis\u0026nbsp;[3]. Consequently, they rely entirely on their host plants for water, nutrients, and carbohydrates. \u003cem\u003eCuscuta\u003c/em\u003e spp. typically exhibit filament-like, yellow to orange stems with flowers that emerge at maturity, entwining around the stems and leaves of their host plants. \u003cem\u003eCuscuta\u003c/em\u003e spp. are distributed worldwide, inhabiting various ecosystems from tropical to temperate regions\u0026nbsp;[3]. Due to their parasitic nature, \u003cem\u003eCuscuta\u003c/em\u003e spp. are often considered detrimental to agriculture. If not managed effectively, they can significantly reduce the growth and yield of host plants. However, they also play ecological roles within their ecosystems by altering the competitive balance between host and non-host species, thereby influencing community structure, vegetation zonation, and population dynamics\u0026nbsp;[4]. Moreover, they have been studied for their interactions with host plants, as well as their potential medicinal properties\u0026nbsp;[3].\u003c/p\u003e\n\u003cp\u003eThe genus \u003cem\u003eCuscuta\u003c/em\u003e encompasses numerous species, including \u003cem\u003eC. campestris\u003c/em\u003e and\u003cem\u003e\u0026nbsp;C. epithymum\u003c/em\u003e, known to be the most widespread and aggressive species within this genus\u0026nbsp;[5]. \u003cem\u003eCuscuta\u0026nbsp;\u003c/em\u003espp. initiate their parasitic phase by forming specialized structures called haustoria. These haustoria penetrate the host plant’s stem, providing \u003cem\u003eCuscuta\u003c/em\u003e spp. with a physical connection through which they not only extract nutrients but also secure themselves by attaching to the host. As the parasitic relationship progresses, \u003cem\u003eCuscuta\u003c/em\u003e spp. continue to proliferate, forming a dense network of intertwining stems that further magnify their impact, eventually leading to detrimental effects on host growth, development, and reproduction\u0026nbsp;[6-8].\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In this study, sampling was conducted in the Rhamna region of Morocco, where the \u003cem\u003eCuscuta epithymum\u0026nbsp;\u003c/em\u003especies attacks the jujube shrub (\u003cem\u003eZiziphus lotus\u0026nbsp;\u003c/em\u003eL\u003cem\u003e.),\u0026nbsp;\u003c/em\u003ecommonly referred to as\u003cem\u003e\u0026nbsp;“Sedra”. Z. lotus\u0026nbsp;\u003c/em\u003eis a resilient species commonly found in arid environments where it forms shrub clusters or patchy vegetation. It is well adapted to survive in harsh conditions with limited water availability and plays a crucial role in ecosystem dynamics. It forms a deep root system that enables it to access water from deep within the soil, allowing it to thrive even in dry conditions. The shrub provides valuable shade and shelter for various arid fauna, contributing to local biodiversity and mitigating soil erosion via wind and water\u0026nbsp;[9].Furthermore, \u003cem\u003eZ. lotus\u0026nbsp;\u003c/em\u003eholds a prominent place in traditional medicine due to its various medicinal properties, as well as the ecological services it provides\u0026nbsp;[9-12].However, \u003cem\u003eZ. lotus\u003c/em\u003e faces threats from habitat loss and degradation due to human activities, such as overgrazing and agricultural expansion, as well as potential risks caused by \u003cem\u003eCuscuta\u003c/em\u003e spp. attacks. Conservation efforts are important for protecting this species and preserving its ecological significance in arid environments, especially within the context of global climate change.\u003c/p\u003e\n\u003cp\u003eDespite the ecological importance of jujube–\u003cem\u003eCuscuta\u003c/em\u003e associations, there is a gap in scientific research regarding their microbial composition and diversity. To date, no studies have specifically investigated the interactions between \u003cem\u003eZ. lotus\u003c/em\u003e and its parasite \u003cem\u003eC. epithymum\u003c/em\u003e and their associated microbiota. This represents a significant knowledge gap, considering the pivotal role of microbial communities in mediating plant health, nutrient cycling, and ecosystem functioning. Although a previous study shed light on the rhizospheric microbial communities associated with both native and cultivated plant species affected by \u003cem\u003eCuscuta\u003c/em\u003e parasitism[13], the objective of this study is to document the diversity and community structure of bacteria associated with \u003cem\u003eZ. lotus\u003c/em\u003e and \u003cem\u003eC. epithymum\u003c/em\u003e, using amplicon sequencing that targets the 16S rRNA gene\u0026nbsp;[14-16]. This tool has revolutionized the study of microbial diversity, allowing for the rapid and comprehensive characterization of previously unexplored microbial communities in various environments\u0026nbsp;[17].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThrough this study, we aimed to advance our understanding of the microbial ecology associated with parasitic plants and their hosts and explore the implications of these interactions with respect to ecosystem dynamics and potential implications for conservation programs. We hypothesize that \u003cem\u003eZ. lotus\u003c/em\u003e and its parasite \u003cem\u003eC. epithymum\u003c/em\u003e share an endophytic bacterial community because of the physical connections between their stems via haustoria, which act as a pathway for bacterial transmission between host and parasite. To test this hypothesis, we conducted a sampling campaign in arid environments where the jujube shrub naturally thrives and dominates the landscape. Shoot samples were collected from shrubs infected by \u003cem\u003eC. epithymum.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe performed 16S rRNA gene amplicon sequencing, targeting the V5–V6 regions, which allows for more specific amplification of bacterial 16S rDNA compared to the V3–V4 regions, thereby minimizing contamination from the plant's chloroplast.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cem\u003e1.\u0026nbsp; \u0026nbsp;Sampling:\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA two-day sampling campaign was conducted on June 10\u003csup\u003eth\u003c/sup\u003e and 11\u003csup\u003eth\u003c/sup\u003e in Benguerir, Rhamna, Morocco (N32°12’11.67”, W7°56’8.451”). The site features patchy vegetation that is primarily dominated by jujube shrubs, as shown in Figure 1A. Each patch represents a cluster with a diameter approximately ranging from 1 to 5 meters. Nine shrubs of \u003cem\u003eZiziphus lotus\u003c/em\u003e L. infected by \u003cem\u003eCuscuta epithymum\u003c/em\u003e were sampled, as illustrated in Figure 1B. The sample collection involved obtaining young stems (approximately 20 cm long) from various parts of each cluster, including non-infected stems, stems infected by \u003cem\u003eCuscuta\u003c/em\u003e, and \u003cem\u003eCuscuta\u003c/em\u003e stems alone (yellow to orange stems, Figure 1C). Additionally, a control sample was obtained from a non-infected plant situated away from the infection site (at the periphery of the cluster). All samples were placed in 20x30 cm Ziploc plastic bags, which were then placed on an ice pack and transported to the laboratory (African Genome Center, Benguerir, Morocco). In the laboratory, the non-infected \u003cem\u003eZ. lotus\u003c/em\u003e stems were processed as follows: From each sample, two to three 5 cm long top stems were cut; disinfected with 70% ethanol, followed by a bleach solution; and rinsed three times using autoclaved water. They were then placed on autoclaved paper towels for drying. For infected samples (Figure 1D), only the fragments of \u003cem\u003eZ. lotus\u003c/em\u003e coiled by \u003cem\u003eCuscuta\u0026nbsp;\u003c/em\u003estems were cut and subjected to the same disinfection, cleaning, and washing procedures as described above. Finally, \u003cem\u003eCuscuta\u003c/em\u003e stems were also disinfected, cleaned, and washed. The dried samples were stored in 15 ml containers at -20°C until further use.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.\u0026nbsp; \u0026nbsp;DNA extraction and polymerase chain reaction (PCR) quantification\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTotal DNA extraction was conducted on 50 mg of\u0026nbsp;lyophilized stem fragments from each\u0026nbsp;sample type, including non-infected jujuba, infected jujuba, and \u003cem\u003eCuscuta\u003c/em\u003e alone. Samples were ground using a TissueLyser II and 2 mm Tungsten beads (QIAGEN, Global Diagnostic Distribution, Témara, Morocco) in 2 ml tubes for 15 minutes at a frequency of 24 Hz. The DNeasy Plant Pro kit (QIAGEN, Global Diagnostic Distribution, Témara, Morocco) was used to extract total DNA following the manufacturer's instructions. The quality and quantity of the extracted DNA were evaluated via gel electrophoresis and DNA quantification with a BioSpectrophotometer (Eppendorf, Hamburg, Germany).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.\u0026nbsp; \u0026nbsp;PCR amplification\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe V5–V6 hypervariable region of the 16S rRNA gene from each sample was amplified using the primer pair with custom sequence (CS) adapters at the 5’ end: \u003cstrong\u003e\u003cem\u003eCS1\u003c/em\u003e\u003c/strong\u003e-719F/\u003cstrong\u003e\u003cem\u003e\u0026nbsp;ACACTGACGACATGGTTCTACA-\u003c/em\u003e\u003c/strong\u003eAACMGGATTAGATACCCKG and \u003cstrong\u003e\u003cem\u003eCS2\u003c/em\u003e\u003c/strong\u003e-1115R\u003cstrong\u003e\u003cem\u003e\u0026nbsp;TACGGTAGCAGAGACTTGGTCT-\u003c/em\u003e\u003c/strong\u003eAGGGTTGCGCTCGTTG[18]. PCR amplification was performed using the Platinum Direct PCR Universal Master Mix (ThermoFisher, Rabat, Morocco) in a final volume of 25 μL. Each PCR contained 1X of the PCR Universal Master Mix, 0.2 µM of each primer, and approximately 10 ng of genomic DNA. The PCRs were run in a thermocycler Mastercycler X50s (Eppendorf, Hamburg, Germany) following this program: initial denaturation at 94°C for 3 minutes, followed by 35 cycles consisting of denaturation at 94°C for 30 seconds, annealing at 55°C for 30 seconds, elongation at 72°C for 1 minute, and a final extension step at 72°C for 5 minutes before being held at 4°C. Each reaction, including negative controls with sterile Milli-Q water and positive controls, was carried out in duplicate.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.\u0026nbsp; \u0026nbsp;\u003c/em\u003eLibrary Preparation and Sequencing\u003c/p\u003e\n\u003cp\u003eThe bacterial 16S rRNA gene amplicon library preparation was generated using Agencourt AMPure XP beads (Beckman Coulter, USA) to clean the PCR products.\u0026nbsp;Two ethanol washes were performed, followed by air drying. Purified PCR products were then resuspended in 10 mM Tris (pH 8.5).\u0026nbsp;A second PCR was performed to attach Illumina sequencing adapters and index tags. PCRs for indexing contained 5 µL of purified PCR product, 2.5 µL of Fluidigm Access Array Barcode 384, and 1X KAPA HiFi HotStart ReadyMix (Roche Sequencing Solutions). The PCR volume was 50 µL per reaction. The PCR was run under the following conditions: an initial denaturation at 95°C for 3 minutes, followed by 8 cycles of denaturation at 95°C for 30 seconds, annealing at 55°C for 30 seconds, extension at 72°C for 30 seconds, and a final extension at 72°C for 5 minutes.\u003c/p\u003e\n\u003cp\u003eThe indexed amplicons were subsequently purified using Agencourt ampure XP beads and quantified using a Qubit assay and the DNA HS kit (ThermoFisher, Témara Morocco).\u0026nbsp;Library quantification, normalization, and pooling were performed following Illumina’s instructions. The bacterial 16S rRNA gene libraries were sequenced on an Illumina MiSeq sequencing instrument (Illumina, Paris, France) using a MiSeq reagent V3 kit (300 cycles\u0026nbsp;of\u0026nbsp;paired-end\u0026nbsp;sequencing).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e5.\u0026nbsp; \u0026nbsp;Bioinformatics analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe resulting fastq files were processed using R version 4.3.3 (the R Project for Statistical Computing).\u0026nbsp;The quality profile of the reads was inspected using the DADA2 pipeline implemented in R\u0026nbsp;[19], and the raw sequence reads with poor average quality scores \u003cstrong\u003e\u003cem\u003e\u003cu\u003e(\u0026lt; 30)\u003c/u\u003e\u003c/em\u003e\u003c/strong\u003e were discarded.\u003c/p\u003e\n\u003cp\u003eThe bacterial reads were filtered and trimmed using DADA2 to eliminate primer and adaptor sequences. In addition, error rates for each consensus quality score were evaluated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe denoised forward and reverse reads longer than 10 bp were merged into a multiple sequence alignment using the DECIPHER package, and amplicon sequence variances (ASVs) were obtained.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTaxonomic annotation was performed using the most updated and extensive SILVA database for bacteria for the\u0026nbsp;resulting amplicon sequence variants (ASVs)\u0026nbsp;[20, 21].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e6.\u0026nbsp; \u0026nbsp;\u003c/em\u003eStatistical analyses\u003c/p\u003e\n\u003cp\u003eBacterial alpha diversity \u0026nbsp;was calculated through the Shannon and Simpson indices at the ASV level using the \u003cem\u003ephyloseq\u003c/em\u003e package\u0026nbsp;[22]. Beta diversity was assessed by computing the Bray–Curtis distance across different microbial taxa, and it was tested through PERMANOVA using the adonis command of the \u003cem\u003evegan\u0026nbsp;\u003c/em\u003epackage\u0026nbsp;[23]. The command betadispers from the vegan package was also used to test the difference in dispersion between different conditions.\u003c/p\u003e\n\u003cp\u003eThe hub taxa of the communities were determined using the SpiecEasi\u0026nbsp;[24]\u0026nbsp;and igraph package of R\u0026nbsp;[25]\u0026nbsp;by calculating the betweenness of each taxon. The betweenness represents the number of times an ASV is present on an edge connecting other ASVs. Thus, it indicates a probability that the organism corresponding to this ASV mediates interactions in the community.\u003c/p\u003e\n\u003cp\u003eRandom forest models were created using the \u003cem\u003erandomForest\u0026nbsp;\u003c/em\u003epackage of R\u0026nbsp;[26]\u0026nbsp;and 100 repeated trees. The best models created with this package were then evaluated in terms of the strength of their predictive power with respect to discriminating between conditions based on communities; the best predictor taxa were listed. Significant associations of taxa with respect to the conditions were calculated using the\u0026nbsp;\u003cem\u003eindicspecies\u003c/em\u003e package\u0026nbsp;[27].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eTaxonomic composition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1323845 16S reads were detected, which were then assigned to 3644 bacterial ASVs comprising 652 genera, 245 families, 134 orders, 62 classes, and 27 phyla. In total, 1947 ASVs were present in jujube samples, 1656 ASVs were present in \u003cem\u003eCuscuta\u003c/em\u003e samples, and 1686 were present in interaction samples. Among these ASVs, 22% were only found in \u003cem\u003eCuscuta\u003c/em\u003e, and 29.8% were only found in jujube. The most abundant phyla in the samples were \u003cem\u003ePseudomonadota\u0026nbsp;\u003c/em\u003e(44%), \u003cem\u003eBacillota\u003c/em\u003e (27%), and \u003cem\u003eActinobacteriota\u003c/em\u003e (21%) (Figure 2A, 2B). The most abundant genera were \u003cem\u003eCutibacterium\u003c/em\u003e (10%),\u003cem\u003e\u0026nbsp;Staphylococcus\u003c/em\u003e (8%), and \u003cem\u003eAcinetobacter\u0026nbsp;\u003c/em\u003e(8%), with a substantial number of ASVs of unknown genus (25%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAlpha and beta diversities\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor alpha diversity, both the Shannon and Simpson indices showed no significant differences when comparing origins or samples (with respective \u003cem\u003ep\u003c/em\u003e-values of 0.3 and 0.5). Additionally, clustering did not significantly influence the Shannon and Simpson indices (with respective \u003cem\u003ep\u003c/em\u003e-values of 0.1 and 0.4). Overall, no parameter was found to significantly affect alpha diversity. There were also no significant differences in beta diversity observed either according to the origin or the cluster (PERMANOVA, with respective \u003cem\u003ep\u003c/em\u003e-values of 0.6 and 0.3) (Figure 4 and Table 1). However, a \u003cem\u003ebetadispers\u003c/em\u003e test revealed significant differences in dispersion among communities within certain clusters (\u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.047), although no significant differences in dispersion were found due to the origin (\u003cem\u003ep\u003c/em\u003e = 0.3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCore taxa\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo ASVs—ASV18 from the \u003cem\u003eStaphylococcus\u003c/em\u003e genus and ASV21 from the \u003cem\u003eCutibacterium\u003c/em\u003e genus—were present in over 90% of all samples. Therefore, these two ASVs can be considered core taxa associated with \u003cem\u003eZiziphus lotus\u003c/em\u003e and jujube-infecting \u003cem\u003eCuscuta epithymum\u003c/em\u003e in our sampling. Additionally, three other ASVs were found in six out of seven control \u003cem\u003eZiziphus lotus\u003c/em\u003e samples: ASV20 from the \u003cem\u003eStaphylococcus\u0026nbsp;\u003c/em\u003egenus, ASV22 from the Neisseriaceae family, and ASV26 from the \u003cem\u003eStaphylococcus\u003c/em\u003e genus. At the family and genus levels, the only core taxa detected were those containing the ASV18 and ASV21 mentioned earlier; thus, no additional core taxa were identified at higher taxonomic levels. Following an analysis of network betweenness, one ASV from the \u003cem\u003eStaphylococcus\u0026nbsp;\u003c/em\u003egenus exhibited the highest betweenness score (1534) among all taxa and can be described as a hub ASV (Figure 5). Furthermore, as no other ASV has a betweenness score exceeding 95% of this value, it can be considered the sole hub taxon within the community.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociated and predictor taxa\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInterestingly, 40 ASVs from 29 genera (Table 2) were found to be significantly associated with control shrubs (non-infected jujube shrubs away from the infection by \u003cem\u003eC. epithymum\u003c/em\u003e), whereas infected shrubs had only one ASV from the genus \u003cem\u003eCaulobacter\u003c/em\u003e, which was significantly associated with their group. No taxa showed differential associations with \u003cem\u003eC. epithymum\u003c/em\u003e, infected jujube shrubs, or the interaction zone. A random forest model successfully discriminated between control and non-control samples with an error rate of 8.05%. However, when another model was developed to differentiate between \u003cem\u003eC. epithymum\u003c/em\u003e, infected \u003cem\u003eZ. lotus\u003c/em\u003e, and interaction samples, the error rate increased to 50%, indicating the model's inability to discriminate between these sample types (Figure 6). The 20 most important ASVs for predicting differences between control and non-infected samples are detailed in Table 3. Among these predictor ASVs, four belonged to the \u003cem\u003eCutibacterium\u0026nbsp;\u003c/em\u003egenus, three to the \u003cem\u003eStaphylococcus\u0026nbsp;\u003c/em\u003egenus, and one to the \u003cem\u003eAcinetobacter\u0026nbsp;\u003c/em\u003egenus.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eInvestigating bacterial diversity within the interaction of \u003cem\u003eCuscuta epithymum\u003c/em\u003e and \u003cem\u003eZiziphus lotus\u003c/em\u003e through a metabarcoding approach is crucial for obtaining a thorough understanding of the intricate dynamics of plant microbiota. This becomes especially significant given the scarcity of research in this domain, which impedes our comprehension of African microbiomes\u0026nbsp;[28].\u003c/p\u003e\n\u003cp\u003eAmong the identified phyla, Pseudomonadota, Bacillota, and Actinobacteriota were the predominant taxa in the bacteriome of both the jujube shrubs and their parasite \u003cem\u003eC. epithymum\u003c/em\u003e. Together, these phyla constituted the majority of bacterial sequences in the samples. Pseudomonadota was the predominant phylum, comprising 44% of the bacterial community, followed by Bacillota at 27% and Actinobacteriota at 21%. These results align with previous research, which has highlighted the prevalent presence of bacterial taxa such as Pseudomonadota, Acidobacteriota, and Actinomycetota in the phyllosphere of plants thriving in hyper-arid environments[29]. Pseudomonadota, in particular, serves as a notable example of a copiotrophic bacterial phylum, as highlighted in various studies\u0026nbsp;[30-32].\u003c/p\u003e\n\u003cp\u003eMoreover, two ASVs—ASV18 belonging to the \u003cem\u003eStaphylococcus\u003c/em\u003e genus and ASV21 belonging to the \u003cem\u003eCutibacterium\u003c/em\u003e genus—were found in more than 90% of all samples of this study. ASV18 belongs to the \u003cem\u003eStaphylococcus\u003c/em\u003e genus and is a core taxon; it was found to be phylogenetically related to\u0026nbsp;\u003cem\u003eStaphylococcus\u003c/em\u003e \u003cem\u003ehominis\u003c/em\u003e, which has been characterized as a plant endophyte of jute\u0026nbsp;seeds and exhibited antimicrobial activity through antibiotic (homicorcin) production\u0026nbsp;[33]. Staphylococci, frequently associated with humans and recognized for their potential pathogenicity, have been consistently found in plant environments. Notably, metabarcoding studies have revealed their presence as endophytes in seeds, such as those of \u003cem\u003eAnadenanthera colubrina\u003c/em\u003e, a legume tree\u0026nbsp;[34], and rice\u0026nbsp;[35]. Furthermore, they have been identified in various plant tissues, including soybeans\u0026nbsp;[36].\u003c/p\u003e\n\u003cp\u003eThe second identified ASV21 belongs to the \u003cem\u003eCutibacterium\u003c/em\u003e genus, which has been reported to be present in both \u003cem\u003eCitrus limon\u003c/em\u003e seeds and shoots\u0026nbsp;[36]. Nevertheless, this genus has also been observed as an endophyte in the cultivated grapevine \u003cem\u003eVitis vinifera\u003c/em\u003e, comprising 5% of the total sequence reads\u0026nbsp;[37], and it is a constituent of the human skin microbiota. Despite the disinfection of our samples and the high abundance of this taxon, potential contamination is unlikely\u0026nbsp;[36, 38]. Furthermore, the majority of the genera identified in this study from the shoot microbiota are known to exhibit plant-growth promotion activities\u0026nbsp;[39].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study on the endophytic bacteriome of \u003cem\u003eC. epithymum\u003c/em\u003e and its host plant \u003cem\u003eZ. lotus\u003c/em\u003e revealed that both partners in the parasitic relationship share a common bacteriome. Microbial species may experience either promotion or inhibition due to the parasitic relationship, thus resulting in diversity affected by plant parasitism\u0026nbsp;[13]. Shifts in the prevalence of certain taxa related to parasitism may impact plant performance. For example, the reduction in the abundance of identified species could affect plant stress tolerance\u0026nbsp;[40, 41]. \u003cem\u003eCuscuta\u003c/em\u003e parasitism has also been reported to influence the expression levels of genes essential for bacterial survival and sporulation\u0026nbsp;[42, 43].\u0026nbsp;In contrast to previous findings suggesting a high degree of host specificity within the microbiota of \u003cem\u003eCuscuta pedicellata\u003c/em\u003e and its host plant\u0026nbsp;[44], our results indicate a lack of discernible variation in bacterial communities among the studied samples. The diversity and composition of this shared bacteriome did not exhibit any significant differences or distinct groups among the analyzed samples, including the control. These results indicate that the parasitic relationship between \u003cem\u003eC. epithymum\u003c/em\u003e and \u003cem\u003eZ. lotus\u003c/em\u003e does not alter the composition of the \u003cem\u003eZ. lotus\u003c/em\u003e bacteriome. Instead, they share the same endophytic community, supporting our hypothesis, which posited that \u003cem\u003eZ. lotus\u003c/em\u003e and its parasite \u003cem\u003eC. epithymum\u003c/em\u003e share an endophytic bacterial community due to the physical connections between their stems via haustoria, which act as a pathway for bacterial transmission between host and parasite.\u003c/p\u003e\n\u003cp\u003eWhile previous studies have identified distinct bacterial and fungal species as endophytes and epiphytes, our findings challenge the notion of host specificity within the phyllosphere microbiota associated with \u003cem\u003eC. pedicellata\u003c/em\u003e and its host plants\u0026nbsp;[45].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCuscuta\u0026nbsp;\u003c/em\u003espp. establish direct connections with the vascular system of their host plants, including the xylem and phloem\u0026nbsp;[46]. The linkage with the host's phloem has been demonstrated through experimental findings. For instance, studies using the phloem-specific dye carboxyfluorescein have shown movement from the host into \u003cem\u003eCuscuta\u003c/em\u003e tissues\u0026nbsp;[47, 48]. Additionally, research on transgenic tobacco plants expressing green fluorescent proteins in companion cells has indicated the potential transfer of proteins to C\u003cem\u003euscuta\u003c/em\u003e, implying the possibility of direct macromolecule transfer\u0026nbsp;[49]. In our sampling, the infection of \u003cem\u003eC. epithymum\u003c/em\u003e extended across a vast area, encompassing numerous shoots of various individuals within the cluster (Figure 1 B and C). Hence, it is probable that \u003cem\u003eC. epithymum\u003c/em\u003e shoots acted as a transmission vector, thereby homogenizing the endophytic bacteriome of \u003cem\u003eZ. lotus\u003c/em\u003e,including both infected and control samples.\u0026nbsp;A well-documented phenomenon is the transmission of viruses between the host and \u003cem\u003eCuscuta\u003c/em\u003e spp. It has been observed that a single \u003cem\u003eCuscuta\u003c/em\u003e plant parasitizing two hosts simultaneously may facilitate the transmission of plant viruses from one host to the other[46]. Apart from these direct vascular connections, \u003cem\u003eCuscuta\u003c/em\u003e also exhibits cytoplasmic continuity with its host through plasmodesmata[50].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCuscuta\u003c/em\u003e spp. introduce significant challenges in agricultural settings due to their broad host range and non-specific attack patterns. Moreover, studies have confirmed the capability of \u003cem\u003eCuscuta\u003c/em\u003e species to transmit viruses between plants by establishing haustoria connections with the vascular tissues of the host. This method of transmission shares similarities with grafting, yet dodder distinguishes itself by transmitting viruses across distantly related plants, a feat not achievable through grafting, which usually involves closely related species. Furthermore, dodder can passively facilitate virus transmission, particularly under experimental conditions conducive to the movement of nutrients from infected to uninfected plants. Consequently, dodder has been employed in experimental research to transfer viruses from challenging-to-study hosts to more accessible experimental plants\u0026nbsp;[46].\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study investigated the endophytic bacteriome of \u003cem\u003eC. epithymum\u003c/em\u003e and its host plant \u003cem\u003eZ. lotus\u003c/em\u003e, revealing a shared bacteriome between both partners in the parasitic relationship. The diversity and composition of this shared bacteriome did not display any significant differences or distinct groups among the analyzed samples. These findings suggest that the parasitic relationship between \u003cem\u003eCuscuta\u003c/em\u003e and \u003cem\u003eZ. lotus\u003c/em\u003e does not alter the composition of the \u003cem\u003eZ. lotus\u003c/em\u003e bacteriome; instead, they share the same endophytic community, supporting our hypothesis. \u003cem\u003eCuscuta\u0026nbsp;\u003c/em\u003espp. establish direct connections with the vascular system of their host plants, including the xylem and phloem. Experimental findings have demonstrated the physical connection with the host's vascular system. In addition to these direct vascular connections, \u003cem\u003eCuscuta\u003c/em\u003e also exhibits cytoplasmic continuity with its host through plasmodesmata.\u003c/p\u003e\n\u003cp\u003eDrawing from this, it is probable that \u003cem\u003eC. epithymum\u003c/em\u003e plays a role in linking the jujube plants and potentially homogenizing their microbiome, as indicated by the capability to predict control plants using specific ASVs with the random forest model. The isolation and characterization of bacterial endophytes from the shoots of both \u003cem\u003eCuscuta\u0026nbsp;\u003c/em\u003eand jujube could aid in designing future investigations to validate the potential transmission of bacterial endophytes between jujube shrubs and its parasite \u003cem\u003eCuscuta\u003c/em\u003e using the isolated taxa transformed with fluorescent proteins.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThis work was funded by the OCP Group (Projects AS-77 and AS-85) and UM6P. We express our gratitude to Dr Zineb Rchiad for her help and support with sample collection and sample preparation. We also thank SIMLAB of UM6P for providing the computational infrastructure used for bioinformatics data processing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eN.R. performed the experiments, analyzed the data, and wrote the manuscript draft. K.E. performed the MiSeq and wrote the manuscript draft. S.M. and K.A.M. contributed to sample preparation and performing experiment. J.L analyzed the data. M.H. contributed to the conceptualization, design, supervision, and manuscript writing. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData accessibility\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw reads corresponding to the control, infected and non-infected jujube as well as \u003cem\u003eCuscuta\u003c/em\u003e samples were submitted to NCBI (https://www.ncbi.nlm.nih.gov/) with accession numbers provided under the BioProject ID: PRJNA1111547.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eStefanovic S, Olmstead RG (2004) Testing the phylogenetic position of a parasitic plant (Cuscuta, Convolvulaceae, asteridae): Bayesian inference and the parametric bootstrap on data drawn from three genomes. 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Protoplasma 220: 189-200. doi: 10.1007/s00709-002-0038-3\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e PERMANOVA test of the phylum using the Aitchison method.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"601\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eDegrees of freedom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eSum Of Sqs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003ePr(\u0026gt;F)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eCluster \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e725.3854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.1030068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e1.020762 \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e6316.7252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e0.8969932 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eTotal \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e7042.1106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003e1.0000000 \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.666666666666668%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 2:\u003c/strong\u003e Genera significantly associated with the control trees.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"526\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003eGenus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003estat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAcinetobacter \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.003 **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eActinotignum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.042 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAggregatibacter \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.020 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAliicoccus \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.014 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAlloprevotella\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.022 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAltererythrobacter \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.016 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eBacillus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.415\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.005 **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eBlautia \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.008 **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCaulobacter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.022 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eChungangia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.036 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCorynebacterium \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.356\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.019 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eDeinococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.408\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.015 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eEnteractinococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.316\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.046 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eEscherichia-Shigella \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.399\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.007 **\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eFusobacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.031 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eGeodermatophilus \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.369\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.013 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eHaemophilus \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.381\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.011 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eKocuria \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.408\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.015 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eMethylobacterium-Methylorubrum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.281\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.035 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eMicrovirga\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.017 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eNeisseria \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.395\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.017 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003ePantoea\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.022 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003ePeptoniphilus \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.017 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003ePeredibacter \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.361\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.029 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003ePorphyromonas \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.013 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eStreptococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.050 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eStreptomyces\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.323\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.028 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eTannerella \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.033 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"44.106463878327%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eWeissella \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.954372623574145%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.364\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.93916349809886%\" valign=\"bottom\"\u003e\n \u003cp\u003e0.022 *\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 3:\u003c/strong\u003e The 20 taxa with the highest predictive power for distinguishing between control and infected samples.\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"695\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_ID\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003ePhylum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eClass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eOrder\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eFamily\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003eGenus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003ePseudomonadota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eGammaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eEnterobacterales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eErwiniaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003ePseudomonadota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eGammaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003ePseudomonadales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eMoraxellaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAcinetobacter\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacillota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacilli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eStaphylococcales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eStaphylococcaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacillota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacilli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eStaphylococcales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eStaphylococcaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCutibacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCutibacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003ePseudomonadota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eGammaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eBurkholderiales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eNeisseriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCutibacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003ePropionibacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCutibacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eCorynebacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eCorynebacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eLawsonella\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eCorynebacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eCorynebacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCorynebacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eProteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eAlphaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eSphingomonadales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eSphingomonadaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eSphingomonas\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacillota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacilli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eStaphylococcales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eStaphylococcaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eStaphylococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacillota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacilli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eLactobacillales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eEnterococcaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eEnterococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eCorynebacteriales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eCorynebacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eCorynebacterium\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eMicrococcales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eMicrococcaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eMicrococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003ePseudomonadota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eGammaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eEnterobacterales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eAeromonadaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAeromonas\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteriota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinomycetales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eActinomycetaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eActinomyces\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacillota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eBacilli\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eLactobacillales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eCarnobacteriaceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eAlloiococcus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"9.626436781609195%\" valign=\"bottom\"\u003e\n \u003cp\u003eASV_480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.948275862068966%\" valign=\"bottom\"\u003e\n \u003cp\u003ePseudomonadota\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.54597701149425%\" valign=\"bottom\"\u003e\n \u003cp\u003eAlphaproteobacteria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.95977011494253%\" valign=\"bottom\"\u003e\n \u003cp\u003eRhodobacterales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.54022988505747%\" valign=\"bottom\"\u003e\n \u003cp\u003eRhodobacteraceae\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.379310344827587%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eParacoccus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\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":"microbial-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meco","sideBox":"Learn more about [Microbial Ecology](https://www.springer.com/journal/248)","snPcode":"248","submissionUrl":"https://submission.nature.com/new-submission/248/3","title":"Microbial Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"16S rRNA Gene Metabarcoding, Arid Environment, Complex Interaction, Cuscuta epi-thymum, Microbial diversity, Parasitic plant, Ziziphus lotus","lastPublishedDoi":"10.21203/rs.3.rs-4423289/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4423289/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMicrobiota associated with host–parasite relationships offer an opportunity to explore interactions among plants, parasites, and microbes, thereby contributing to the overall complexity of community structures. The dynamics of ecological interactions between parasitic plants and their hosts in arid environments remain largely understudied, especially in Africa. This study aimed to examine the bacterial communities of \u003cem\u003eCuscuta epithymum\u003c/em\u003e L. (clover dodder), an epiphytic parasitic plant, and its host, \u003cem\u003eZiziphus lotus \u003c/em\u003eL. (jujuba)\u003cem\u003e,\u003c/em\u003ein an arid environment. Our goal was to uncover the ecological complexities of microbial communities within the framework of plant–plant interactions. We conducted a comprehensive analysis of the bacterial composition and diversity within populations of the \u003cem\u003eC. epithymum\u003c/em\u003e parasite, the infected- and non-infected \u0026nbsp;jujuba host, and their interface at the shoots of the host. This involved amplicon sequencing, targeting the V5–V6 regions of the 16S rRNA gene. A total of 5680 amplicon sequence variants (ASVs) were identified, with \u003cem\u003ePseudomonadota\u003c/em\u003e, \u003cem\u003eBacillota\u003c/em\u003e, and \u003cem\u003eActinobacteriota\u003c/em\u003e being prevalent phyla. Among the bacterial communities, three genera were dominant: \u003cem\u003eCutibacterium\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, and \u003cem\u003eAcinetobacter\u003c/em\u003e. Interestingly, analyses of alpha- and beta-diversities revealed no significant difference between jujuba and its parasite, suggesting a shared shoot endophytic bacteriome. This finding advances our comprehension of microbial communities linked to plant–parasite interactions in the arid environments of Africa. Further studies on functional diversity and elucidation of the mechanisms by which bacterial communities transfer between host and parasite are needed.\u003c/p\u003e","manuscriptTitle":"Potential Plant-to-Plant Transmission: Shared Endophytic Bacterial Community between Ziziphus lotus and its Parasite Cuscuta epithymum","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-24 07:53:25","doi":"10.21203/rs.3.rs-4423289/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-17T15:39:53+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-16T14:34:46+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-12T02:05:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-03T00:05:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216245192337745572588666713824543730231","date":"2024-05-21T01:34:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"265198732197097719821538447915488037670","date":"2024-05-17T08:14:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323976293263628340487606161796166960277","date":"2024-05-16T09:45:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66416333801173703549686983246292459794","date":"2024-05-15T21:50:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-15T21:14:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-15T07:56:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-15T07:56:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"Microbial Ecology","date":"2024-05-15T07:18:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"microbial-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meco","sideBox":"Learn more about [Microbial Ecology](https://www.springer.com/journal/248)","snPcode":"248","submissionUrl":"https://submission.nature.com/new-submission/248/3","title":"Microbial Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"63cf9e86-b2af-4b60-87a7-4d3e0f3d3cb9","owner":[],"postedDate":"May 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-30T16:08:08+00:00","versionOfRecord":{"articleIdentity":"rs-4423289","link":"https://doi.org/10.1007/s00248-024-02421-z","journal":{"identity":"microbial-ecology","isVorOnly":false,"title":"Microbial Ecology"},"publishedOn":"2024-09-28 15:58:12","publishedOnDateReadable":"September 28th, 2024"},"versionCreatedAt":"2024-05-24 07:53:25","video":"","vorDoi":"10.1007/s00248-024-02421-z","vorDoiUrl":"https://doi.org/10.1007/s00248-024-02421-z","workflowStages":[]},"version":"v1","identity":"rs-4423289","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4423289","identity":"rs-4423289","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}