Phlebotomus duboscqi gut microbiota dynamics in the context of Leishmania infection

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Rogerio, Laura Willen, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7384237/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The manipulation of the gut microbiota of disease vectors has emerged as a new approach to use in the integrated control of vector-borne diseases. For this purpose, a deep knowledge of the gut microbial communities of disease vectors is essential. However, while for some vectors, including mosquitoes, such characterization has been extensive, for others, including some sand fly species, there is limited data available. To our knowledge, to date, no study has documented the gut microbiome dynamics of Phlebotomus duboscqi sand flies over the entire time-period required for the maturation of a Leishmania infection. To address this limitation, here, we looked at the differences of the gut microbiome of laboratory-reared P. duboscqi sand flies both before, and after infection with Leishmania major parasites, with the necessary temporal resolution to understand the dynamics of sand fly gut microbial communities in the context of Leishmania infection. Results We observed a decrease in the number of Amplicon Sequence Variants (ASVs) at two key time points: a significant decrease early after infection (Day 2), and a trend toward reduction at late after infection (Day 12). These results were accompanied by noticeable changes in the relative abundance of multiple bacterial families and respective genera with the progression of Leishmania infection in the sand fly midgut, with e.g. Sphingomonas , Ochrobactrum , and Serratia as the most prevalent genera detected, before, early after, and late after infection, respectively. While these results did not overall translate into significant differences in alpha diversity metrics, they did lead to a separation between the 3 groups in the context of a beta diversity analysis, with statistical relevance. Importantly, via an ANCOM-BC analysis we were able to establish Corynebacterium spp. and Enterococcus spp. as potential markers of non-infected and infected sand flies, respectively, as well as Streptococcus spp., Sphingomonas spp., Ralstonia spp., and Abiotrophia spp. as potential specific markers of late infections. Conclusions Overall, we show that the composition of the gut microbiota of P. duboscqi sand flies changes significantly over the course of an infection with L. major parasites. Sand fly Leishmania infection gut microbiota relative abundance diversity Figures Figure 1 Figure 2 Figure 3 Background Although often not recognized as so, sand flies are among the insects of significant public-health concern. Like mosquitoes, sand flies show a worldwide distribution, depend on blood to complete their life cycle, and can transmit a variety of pathogens [ 1 ]. Among these, Leishmania spp. parasites, the causative agents of human leishmaniasis, are the ones associated with the highest disease/socioeconomic burden [ 2 , 3 ]; over one million leishmaniasis cases are estimated to occur each year, most of them referring to the non-fatal cutaneous form [ 4 ]. Of note, most Leishmania parasites that cause disease in humans are zoonotic agents [ 1 ], a vaccine for human leishmaniasis (either prophylactic or therapeutic) is yet to be approved, and the molecules available for the treatment of human cases are limited and increasingly compromised by the emergence of drug resistance [ 5 , 6 ]. Therefore, the control of leishmaniasis is extremely challenging, requiring a multifaceted approach that needs to have a major focus on the sand fly vector, instead of relying solely in case-control strategies. While there are a few sand fly-based approaches in use for the control of leishmaniasis, they all rely on the prevention of sand fly-human contact [ 7 ]. These, that include the use of repellents and insecticides, are not without limitations, including the emergence of resistant insect populations [ 7 ]. Of note, contrary to the reality for other disease vectors [ 8 ], no control method targeting specifically the infection within sand flies is available for application [ 7 ]. Yet, recent studies reported that, if depleted from their natural gut microbiota, sand flies are no longer able to sustain the development of Leishmania spp. parasites within their midguts [ 9 , 10 ]. This suggests a crucial role for sand fly midgut bacteria in the establishment of Leishmania spp. in sand flies; thus, we should be able to make sand flies refractory to infection via the manipulation of their gut microbiota. Our recent work shows the potential of such an approach. By introducing a mosquito symbiont, Delftia tsuruhatensis TC1, in the sand fly midgut, we induced a state of sand fly gut dysbiosis that negatively impacted the development of Leishmania major parasites in the vector [ 11 ]. Importantly, this led to a decreased potential of effective transmission of L. major to hosts, associated with a lower risk of disease development in an animal model of cutaneous leishmaniasis [ 11 ]. For the development of similar approaches, there is the need for a comprehensive understanding of the composition and dynamics of the gut microbiota of sand flies. However, while the gut microbiota of some species of medical importance, including Lutzomyia longipalpis and Phlebotomus papatasi , has been extensively characterized, the information available on the subject for other species is limited [ 12 , 13 ]. Among the latter, we find Phlebotomus duboscqi sand flies, the main West African vectors of L. major -caused cutaneous leishmaniasis [ 14 ]. Only four studies looked at the sand fly gut microbiota of colony-reared P. duboscqi sand flies [ 10 , 15 – 17 ]. The older studies focused either on culturable bacteria [ 17 ], or on temperature-gradient gel electrophoresis of whole DNA [ 16 ] and only in the context of non-infected sand flies. The two most recent studies used more modern 16S-based sequencing methods, including in the context of infected sand flies, but looking only at a single time-point after infection (either early [ 15 ] or late [ 10 ]). To our knowledge, no study documented the gut microbiome dynamics of P. duboscqi sand flies over the entire time-period required for the maturation of a Leishmania infection. Here, to address this limitation, we looked at the differences of the gut microbiome of laboratory-reared P. duboscqi sand flies before and after L. major infection, with the necessary temporal resolution to understand the dynamics of sand fly gut microbial communities throughout the infection timeline. Results To investigate the dynamic changes in P. duboscqi gut microbial communities in the context of Leishmania infection, pools of sand fly midguts were collected one day before (day 0), as well as 2, 5, 7, 9, and 12 days after infection with L. major parasites, and subjected to metagenomics analysis. The infection followed a healthy pattern, with the number of parasites per midgut plateauing after day 7 of infection (Supplementary Fig. 1A), and the frequency of metacyclic parasites increasing dramatically from day 7 onward (Supplementary Fig. 1B). For analysis purposes, samples were either considered by individual time-point, or joined together in the frame of three major groups: before infection, early after infection (days 2 and 5 post-infection, when blood or blood remnants may still be found in the midgut), and late after infection (days 7, 9, and 12 post-infection, when metacyclic promastigotes start to be present in the sand fly midgut; Supplementary Fig. 1B). First, we looked at the number of observed Amplicon Sequence Variants (ASVs) as a reflection of the richness of bacteria found in the sand fly gut microbiota. A significant difference was detected, particularly when we compared the sand fly gut microbiota before and early after infection, with a lower number of ASVs observed in the latter group (Fig. 1 A; Supplementary Table 1 - adjusted p = 0.041). This was mostly due to a decrease in the number of ASVs 2 days post-infection (Supplementary Fig. 2A; Supplementary Table 2). Later after infection, a partial recovery in the number of observed ASVs was evident, although to median group levels still lower than those observed before infection (Fig. 1 A). Of note, considering the individual time-points pertaining to this period, a tendency of reduction of the number of observed ASVs was observed for the last one (12 days post-infection; Supplementary Fig. 2A). Next, we characterized the abundance of major bacterial groups (the 10 most abundant) found in the gut microbiota of P. duboscqi sand flies throughout the Leishmania infection timeline. While some heterogeneity was visible among individual samples collected at the same time-point (something not unexpected since we are looking at pools collected from 20 sand flies each), some changes were evident, particularly in the context of our infection status-based analysis approach (Fig. 1 B; Supplementary Fig. 2B). Before infection, more than 85% or relative abundance was attributed to 4 main genera: Sphingomonas , Leifsonia , Ochrobactrum , and Serratia (27.7%, 27.2%, 19.3%, 12.0% relative abundance at the group level, respectively; Fig. 1 B, right panel; Supplementary Table 3). This translated into the dominance of 4 main families before Leishmania -infection (each including one of the abovementioned genera, in the respective order): Sphingomonadaceae, Microbacteriaceae, Rhizobiaceae, and Yersiniaceae (27.7%, 27.2%, 21.8%, and 12.1% relative abundance at the group level, respectively; Supplementary Fig. 2B, right panel; Supplementary Table 4). Early after infection, the most evident change was an increase in the relative abundance of the Ochrobactrum genus (and the Rhizobiaceae family) to around 50% (Fig. 1 B and Supplementary Fig. 2B; right panels). Additionally, two other families, Alcaligenaceae (no genus attributed; listed under the unknown genera category) and Pseudomonadaceae (mainly referring to the Pseudomonas genus) also increased in abundance to values above 6% at the group level; in the latter case, this was mostly due to the contribution of an individual sample (Fig. 1 B and Supplementary Fig. 2B; left panels; Supplementary Tables 3 and 4). Conversely, all other abundance-wise relevant genera/families either maintained or decreased their prevalence early after infection, at the group level. Leifsonia (Microbacteriaceae family) contracted the most in relative terms, followed by Sphingomonas (Sphingomonadaceae family); for the sake of comparison relative abundance values at the genus level dropped to 3.0%, and 11.3%, respectively as compared to values of 27.2% and 27.7%, before infection (Fig. 1 B and Supplementary Fig. 2B; right panels; Supplementary Tables 3 and 4). Of note, Serratia (Yersiniaceae family) seemed to maintain a relative abundance weight (as compared to the before infection scenario) of around 13% (Fig. 1 B and Supplementary Fig. 2B; Supplementary Tables 3 and 4). Late after infection both the Ochrobactrum and Sphingomonas genera (and the Rhizobiaceae and Sphingomonadaceae families, respectively) returned to the relative abundance levels observed before infection, with a contraction of the former and an expansion of the latter when comparing with the early after infection status (e.g. relative abundance values 19.7% and 24.0%, respectively at the genus level; Fig. 1 B and Supplementary Fig. 2B; Supplementary Tables 3 and 4). The same was true for the Alcaligenaceae and Pseudomonadaceae families; both lost relevance later after infection, returning to the low relative abundance values (below 1%) detected before infection (Supplementary Fig. 2B; Supplementary Table 4). On the other hand, Leifsonia (Microbacteriaceae family) did not recover, maintaining an even lower relative abundance late after infection (e.g. at the genus level, 0.9% versus the 3.0% determined early after infection; Fig. 1 B and Supplementary Fig. 2B; Supplementary Tables 3 and 4). In contrast, 3 genera/families increased in relative abundance to levels above those detected for both the pre-infection and early infection statuses. Serratia (Yersiniaceae family) became the most prevalent late after infection (25.8% both at the genus and family level; Fig. 1 B and Supplementary Fig. 2B; Supplementary Tables 3 and 4). Additionally, the Tsukamurella and Asaia genera (and the Tsukamurellacea and Acetobacteraceae families, respectively) also increased in relative abundance from less than 0.5% before and early after infection to around 5% late after infection (Fig. 1 B and Supplementary Fig. 2B; right panels; Supplementary Tables 3 and 4). Interestingly, both were detected in higher abundance from day 9 post-infection onward, as per individual sample data (Fig. 1 B, and Supplementary Fig. 2B; left panels). Of note, one other genus (family), Ralstonia (Burkholderiaceae) showed relevant, although lower relative abundance values throughout the experimental timeline; these contracted from 3.6% before infection to 1.1% early after infection and then expanded to 2.8% late after infection (Fig. 1 B and Supplementary Fig. 2B; Supplementary Tables 3 and 4). The combined relative abundance of all remaining genera (families) varied from around 6% before infection to around 9% late after infection. The above-reported changes highlighted possible dynamic alterations in the composition of the microbial communities of the sand fly midgut in the context of Leishmania infection. Therefore, next we looked specifically at bacterial diversity. With respect to alpha diversity metrics, referring to within-sample diversity and considering overall both the richness and evenness of bacterial communities in a sample, no statistically significant differences were observed (Fig. 2 A-C). Regarding both Shannon index and Pielou evenness metrics, the distribution of individual samples overlapped in the context of the 3 groups studied, with a higher dispersion of values early after infection, and a tendentiously higher median late after infection (Fig. 2 A and B, respectively). On the other hand, the profile with regards to the Faith PD metric (Fig. 2 C), was quite similar to that seen in the context of the Observed ASVs (Fig. 1 A), with a decrease in the values for early after infection samples, although to an extent not enough to reach statistical relevance. On the other hand, with respect to beta diversity metrics (weighted UniFrac distance), reflecting the overall composition at the group level, statistically significant differences were detected. A separation between the 3 groups was evident [p(adonis) = 0.003], and to a greater extend between before infection and early after infection samples (Fig. 2 D). This translated into significant differences when we compared specifically the before infection and early after infection groups [p(PERMANOVA) = 0.024; Supplementary Table 5], as well as almost significant differences when we compared both the before infection and late after infection groups [p(PERMANOVA) = 0.0959; Supplementary Table 5], and the early after infection and late after infection groups [p(PERMANOVA) = 0.054; Supplementary Table 5]. Of note, no major differences in terms of sample dispersion within groups (or group heterogeneity) were observed [p(betadisp) and p(PERMDISP) > 0.2; Fig. 2 D; Supplementary Table 5]. Overall, these results suggest that the composition of the sandfly gut microbiota changes dynamically with the progression of Leishmania infection in sand flies. Last, we focused on differences in estimated absolute abundance values (ANCOM-BC analysis) looking for potential markers of early and/or late infection, considering not only highly abundant genera/families, but also those with lower relative abundance values. Importantly, a few of the above-reported apparent differences in terms of relative abundance values for the highly abundant genera/families were still noted in the context of absolute numbers (Fig. 3 A and B; Supplementary Tables 6 and 7). For instance, a significant decrease in the number of Microbacteriaceae late after versus before infection was noted (Fig. 3 B; Supplementary Table 7). More so, a significant increase in the number of Ralstonia , and consequently of Burkholderiaceae at the family level, as well as of Sphingomonas (only at the genus level in this case) was detected late versus early after infection (Fig. 3 A and B; Supplementary Tables 6 and 7). Interestingly, via this estimated absolute abundance-based differential analysis, nine new genera/families were noted to change significantly in the context of Leishmania infection. Cutibacterium and Porphyromonas (Propionibacteriaceae and Porphyromonadaceae, respectively, at the family level) showed significantly lower numbers early after versus before infection (Fig. 3 A and B; Supplementary Tables 6 and 7). Corynebacterium (and Corynebacteriaceae at the family level) also showed significantly lower numbers early after versus before infection, as well as late after versus before infection, making this genus/family a potential marker of non-infected sand flies (Fig. 3 A and B; Supplementary Tables 6 and 7). Conversely, the genus Enterococcus (and the family Enterococcaceae) showed significantly higher absolute abundance both early and late after infection, highlighting them as potential general markers of Leishmania -infected sand flies in our experimental context (Fig. 3 A and B; Supplementary Tables 6 and 7). More so, our results also revealed a decrease in the numbers of Peptostreptococcaceae late after versus before infection (Fig. 3 B; Supplementary Table 7). Importantly, we also detected significant changes when we compared the late versus early after infection statuses. In this context, we observed a significant increase in the absolute numbers of the Streptococcus and Abiotrophia genera (and the Streptococcaceae and Aerococcaceae families, respectively), as well as of the order Saccharimonadales, to which we could not assign a family/genera (Fig. 3 A and B; Supplementary Tables 6 and 7). Overall, these results align with relative abundance/bacterial diversity ones, further supporting the notion that the gut microbiota of P. duboscqi sand flies change dramatically in the context of Leishmania infection. Discussion With this study, we aimed to characterize the gut microbial communities of P. duboscqi sand flies, with emphasis on the potential dynamic changes resulting from the development of a Leishmania infection. Overall, we show that the composition of the gut microbiota of P. duboscqi sand flies changes significantly over the course of an infection with L. major parasites. One curious observation in this study was the decrease in the number of observed ASVs in 2 different occasions: early after infection in a significant fashion, particularly at day 2, and late after infection, specifically at day 12. Interestingly, these results are in line with those previously reported for Lu. longipalpis sand flies infected with L. infantum parasites, both in the context of observed operational taxonomic units - OTUs - and of phylogenetic diversity [ 9 ]. Together, both studies point to two distinct events of “microbial richness loss”, likely driven by selective pressures of different origins. The first decrease in richness is probably a result of the apport of new nutrients after the ingestion of blood by the sand fly. The second can be a consequence of both a bacteria-bacteria and bacteria-parasite competition for limited resources within a midgut now populated by high Leishmania numbers, and/or the result of a re-arrangement of microbial communities shaped by Leishmania excreted byproducts. Of note, our beta diversity results do not show a recovery in the composition of the gut microbiota of sand flies after the defecation of blood meal remnants (before versus late after infection). This further supports the occurrence of independent selective pressure events that shape the midgut microbiota of adult Leishmania -infected female sand flies. In line with the variation in sand fly midgut bacterial richness with the course of infection, we also detected changes in the relative abundance of different bacterial genera/families. In this context, we can try to establish some parallels with the reported in previous studies. For instance, an apparent dominance of Ochrobactrum spp. in the gut microbiota of P. duboscqi sand flies was previously reported by Volf et al, including in blood-fed insects [ 17 ]. A dominance of the family Rhizobiaceae, of which Ochrobactrum spp. is part of, was also reported in the gut microbiota of P. duboscqi sand flies both before, and after taking a non-infected bloodmeal by Tabbabi et al [ 15 ], and 14 days after infection by Louradour and colleagues [ 10 ]. Our data, showing the relative dominance of Ochrobactrum spp. early after infection, as well as a significant relative abundance both before and late after infection, may align with these published data. We do need to consider that the study by Volf et al only looked at culturable bacteria [ 17 ] and thus the relative values reported are probably over-estimated, while the study by Tabbabi et al was based on a limited number of samples[ 15 ], lacking the resolution necessary to account for the expected sample-to-sample heterogeneity. Of note, other studies have reported the presence of Ochrobactrum spp. in sand fly larval rearing sites, and the ability of these bacteria to be transtadially transmitted from larvae to adults, explaining the presence of this bacterial genus in the gut microbiota of different lab-reared and wild-caught sand fly species [ 13 , 18 – 21 ]. Additionally, the increase in the relative abundance of Tsukamurella spp. late after infection observed in this study was also previously reported in Lu. longipalpis sand flies infected with L. infantum parasites [ 9 ]; the same parallel can be made with the Acetobacteraceae family, albeit with a much lower proportional increase late after infection in our study. Of note, the P. duboscqi and Lu. longipalpis sand flies used in this study and in [ 9 ], respectively, are reared in the same environment and with the same food and sugar sources. However, while previously Tsukamurella spp. together with the Actinobacteria/Actinomycetota phylum (among others) were statistically defined, via linear discriminant analysis, as potential markers of infected sand flies [ 9 ], that was not the case in our context, after an ANCOM-BC analysis; for Tsukamurella spp. this was likely due to the observed sample heterogeneity. Instead, in this study, the genus Enterococcus and the family Enterococcaceae were defined as potential markers of infected sand flies, while the genus Corynebacterium and the family Corynebacteriaceae (curiously belonging to the Actinobacteria/Actinomycetota phylum) were defined as potential markers of non-infected sand flies. While we cannot exclude the hypothesis that these contradictory results may be just a consequence of the different statistical methods used in the two studies, overall, they seem to suggest that the diet is, likely, not the only factor that influences the microbiota of adult sand flies, in line with what was reported for mosquitoes [ 22 ]. The hypothesis that, not only the genetic background, but also the infectious agent (different in the two contexts mentioned above) may condition the gut microbiota of adult sand flies is something to consider. A future side-by-side study of the gut microbiota of Lu. longipalpis and P. duboscqi sand flies infected with L. infantum and L. major parasites, respectively is warranted, both to address this hypothesis, and to disclose potential vector-parasite specific microbial signatures. Interestingly, our ANCOM-BC analysis also revealed some bacterial genera significantly more abundant in sand flies late versus early after infection, including Streptococcus , Sphingomonas , Ralstonia and Abiotrophia spp. The fact that these genera increase in absolute abundance in sand flies with heavier Leishmania infectious burdens may indicate a favorable parasite-bacteria relationship. These bacteria may proliferate in response to Leishmania growth, and/or they may be important to sustain the development of Leishmania parasites in the sand fly midgut. Of note, previous Leishmania infection studies in the context of antibiotic-treated sand flies, reported that Leishmania parasites need an undisturbed sand fly gut microbiota to establish themselves in the vector [ 9 , 10 ]. We can, therefore, speculate that some bacterial species within the abovementioned genera are Leishmania infection/metacyclogenesis promoters; none of these were previously identified as such. Future studies aiming at isolating these bacteria and characterizing their role in the context of Leishmania infection will help us to address this possibility. Of note, in this context there is a precedent. Louradour et al. reported that Serratia rubidaea bacteria are Leishmania infection-enhancers in the context of sand fly gut dysbiosis [ 10 ]. In our study Serratia spp. was the genus with the higher relative weight detected late after infection, and within the Serratia species we were able to attribute via our metagenomics analysis we found Serratia rubidaea (Supplementary Data 1). This study is not without limitations. For instance, our experimental settings differ from what is expected to occur in the field: i) sand flies take an infected bloodmeal from a living host [ 1 ] (whose species may vary), and not via artificial membrane feeding; and ii) sand flies are expected to take multiple bloodmeals throughout their adult life span with consequences for vector competence [ 23 ]. Future studies on the effect of multiple blood meals (and different blood sources) on the gut microbiota of naturally infected sand flies are warranted. Additionally, we characterized the microbiota of the whole sand fly midgut, thus lacking the spatial resolution achieved by Louradour et al, that, albeit using cloning and PCR, analyzed the microbiome of different midgut regions [ 10 ]. The use of higher depth techniques associated with a more compartmentalized analysis, may provide useful insights into the dynamics of the sand fly gut microbiota as Leishmania spp. infection matures. Lastly, we analyzed the microbiota in the context of pooled samples and thus were neither able to look at potential individual variability, nor to establish potential associations between gut microbial composition and infection burden. Future studies looking at the gut microbiota of individual sand fly specimens are also warranted. Conclusions Here, we show that the composition of the gut microbiota of P. duboscqi sand flies changes significantly over the course of an infection with L. major parasites. Our data contribute to the body of work in this field and may guide future studies aiming to: i) characterize different Leishmania -bacteria interactions in the sand fly midgut, ii) isolate bacteria beneficial and detrimental for the development of Leishmania parasites, and iii) leverage bacterial isolates/byproducts to manipulate the sand fly gut microbiota and negatively impact the development of Leishmania spp. parasites in their respective vectors. Methods Ethics Statement All animal experiments were carried out in accordance with the National Institute of Allergy and Infectious Diseases (NIAID) Animal Care and Use Committee under the animal protocol LMVR4E. Parasites A cloned line of Leishmania major (WR 2885) was used [ 24 ]. Promastigotes were maintained at 26°C in Schneider’s insect medium supplemented with 20% heat-inactivated fetal bovine serum, 100 U/mL penicillin, and 100 mg/mL streptomycin (all Thermo Fischer Scientific). Sand Flies Phlebotomus duboscqi sand flies were mass reared at the Laboratory of Malaria and Vector Research insectary as previously described [ 25 ]. Adult females were maintained on a 30% sucrose diet and were starved for 12 hours before feeding. Sand Fly Infection After an overnight starving period, sand flies were infected by artificial feeding through a chick membrane on defibrinated rabbit blood (Spring Valley Laboratories, MD, USA) containing L. major promastigotes (5x10 6 /ml), as previously described [ 26 ]. After infection, blood-fed females were sorted and kept on a 30% sucrose diet. Metagenomics Analysis – Layout and Samples Sand fly midguts were dissected under a sterile-like environment [ 27 ] at different time-points: before blood feeding (D0), and different days after blood feeding (D2, D5, D7, D9, and D12). Dissected midguts were washed three times in sterile PBS drops and then transferred to a 1.5 ml Eppendorf centrifuge tube containing 50 µL of sterile PBS; pools of 20 midguts were collected per condition at least in triplicate. Genomic DNA was then extracted using the, and the samples were subjected to 16S rRNA amplification and sequencing (approximately 100,000 reads per sample) as reported elsewhere [ 9 ]; the V3-V4 hypervariable regions of the 16S rRNA was targeted via the use of the primers 341F – CCTAYGGGRBGCASCAG, and 806R – GGACTACNNGGGTATCTAAT. Overall, a total of 21 samples were analyzed. For the analysis, frequently, samples were grouped by time-point. Additionally, in some instances, samples were grouped based on the status of infection: before infection (D0), early after infection (days 2 and 5), and late after infection (days 7, 9 and 12). Metagenomics Analysis - Amplicon Sequence Variant Calling, Phylogenetic Tree, and Taxonomy Classification This paper results from a re-analysis of the data collected in a different study [ 11 ], and previously deposited at NCBI under the BioProject number PRJNA1079352 ( https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1079352/con ); only CTRL samples are relevant to the present study. The initial analysis steps were common to the ones previously reported (code available at https://github.com/GaryZhangYue/Cecilio_2024_TC1_sandflies ). Briefly, 16S rRNA amplicon reads were demultiplexed and trimmed using Novogene in-house scripts. The trimmed demultiplexed reads were then imported into QIIME2 version 2021.4 [ 28 ] for downstream analysis. DADA2 [ 29 ] was used to call amplicon sequence variants (ASVs). Chimeric sequences were identified and removed by setting the flag “--p-min-fold-parent-over-abundance” to 10, which discards chimeric sequences showing an at least ten times lower abundant than their parent sequences. A rooted phylogenetic tree was generated using FastTree [ 30 ] based on ASV multiple alignment with MAFFT [ 31 ]. The ASVs were taxonomically classified with a Naïve Bayes classifier pre-trained on SILVA rRNA database (release 138 SSURef NR99) [ 32 ]. After DADA2 quality filtering, and considering only the CTRL samples, a total of 3,477,690 reads (165,604 ± 4,990 reads/sample) were retained. The samples were then rarefied to a subsampling depth of 149,894 reads/sample to ensure an even sequencing depth. After rarefaction, 1,844 ASVs and all samples were retained. Metagenomics Analysis - Microbial Diversity Calculation, Statistical Testing, and Differential Abundance Testing The diversity metrics were calculated using the QIIME2 core-metrics-phylogenetic function. The rarefied feature table was used to compute Shannon’s diversity metrics [ 33 ], observed features, Faith’s phylogenetic diversity index [ 34 ], Pielou’s evenness index [ 35 ], and UniFrac distance [ 36 ]. Statistical comparisons in this context were made using the Kruskal-Wallis test followed by a post-hoc analysis, when applicable, using the Dunn’s test. To visualize the dissimilarities in microbial communities across groups, the weighted UniFrac distance metrics was used to generate PCoA coordinates after Cailliez transformation [ 37 ] to correct for negative eigenvalues. Permutational multivariate analysis of variance (PERMANOVA) [ 38 ] and permutational multivariate analysis of group dispersion homogeneity (PERMDISP) [ 39 ] were applied to compare the centroid location and within-group dispersion level, respectively, in the weighed UniFrac distance metrics across groups. Analysis of compositions of Microbiomes with Bias Correction (ANCOM-BC, version 2.0.3) [ 40 ] was also used to find differentially abundant genera between conditions on each day and between each pair of phases (early after versus before infection, late after versus before infection, and late versus early after infection). The unrarefied features table was used as input to ANCOM-BC as per the standard recommendations. Declarations Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing Interests: The authors declare that they have no competing interests. Authors’ contributions PC and FO conceived the study and designed the experiments. KT, PC, LAR, LW, EI, and FO performed the experiments and analyzed the data. YZ did the metagenomics analysis. CM reared the sand flies. JGV, and FO assured the funding. SK, and JGV contributed with reagents, materials, analysis tools. PC and KT wrote the original draft. All authors critically discussed the results, and revised, edited, and approved the manuscript. Funding: This research was supported by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services. Author Contribution PC and FO conceived the study and designed the experiments. KT, PC, LAR, LW, EI, and FO performed the experiments and analyzed the data. YZ did the metagenomics analysis. CM reared the sand flies. JGV, and FO assured the funding. SK, and JGV contributed with reagents, materials, analysis tools. PC and KT wrote the original draft. All authors critically discussed the results, and revised, edited, and approved the manuscript. Data Availability The datasets analyzed within the current study have been deposited in the NCBI GeneBank database, under the BioProject number PRJNA1079352 ( https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1079352/con ); only CTRL samples are relevant to this study. The analysis script is available at GitHub (https://github.com/GaryZhangYue/Tang_2025_Sandfly_Gut_Microbiota_16S ). References Cecilio P, Cordeiro-da-Silva A, Oliveira F: Sand flies: Basic information on the vectors of leishmaniasis and their interactions with Leishmania parasites. Commun Biol 2022, 5: 305. Okwor I, Uzonna J: Social and Economic Burden of Human Leishmaniasis. Am J Trop Med Hyg 2016, 94: 489-493. Scheufele CJ, Giesey RL, Delost GR: The global, regional, and national burden of leishmaniasis: An ecologic analysis from the Global Burden of Disease Study 1990-2017. J Am Acad Dermatol 2021, 84: 1203-1205. WHO Leishmaniasis Fact Sheet [https://www.who.int/news-room/fact-sheets/detail/leishmaniasis] Cecílio P, Oliveira F, Cordeiro da Silva A: Vaccines for Human Leishmaniasis: Where Do We Stand and What Is Still Missing? In Leishmaniases as Re-emerging Diseases. Edited by Farhat A, Hassan H. Rijeka: IntechOpen; 2018: Ch. 5 Ponte-Sucre A, Gamarro F, Dujardin JC, Barrett MP, Lopez-Velez R, Garcia-Hernandez R, Pountain AW, Mwenechanya R, Papadopoulou B: Drug resistance and treatment failure in leishmaniasis: A 21st century challenge. PLoS Negl Trop Dis 2017, 11: e0006052. Balaska S, Fotakis EA, Chaskopoulou A, Vontas J: Chemical control and insecticide resistance status of sand fly vectors worldwide. PLoS Negl Trop Dis 2021, 15: e0009586. Minwuyelet A, Petronio GP, Yewhalaw D, Sciarretta A, Magnifico I, Nicolosi D, Di Marco R, Atenafu G: Symbiotic Wolbachia in mosquitoes and its role in reducing the transmission of mosquito-borne diseases: updates and prospects. Front Microbiol 2023, 14: 1267832. Kelly PH, Bahr SM, Serafim TD, Ajami NJ, Petrosino JF, Meneses C, Kirby JR, Valenzuela JG, Kamhawi S, Wilson ME: The Gut Microbiome of the Vector Lutzomyia longipalpis Is Essential for Survival of Leishmania infantum. mBio 2017, 8 . Louradour I, Monteiro CC, Inbar E, Ghosh K, Merkhofer R, Lawyer P, Paun A, Smelkinson M, Secundino N, Lewis M, et al: The midgut microbiota plays an essential role in sand fly vector competence for Leishmania major. Cell Microbiol 2017, 19 . Cecilio P, Rogerio LA, Serafim TD, Tang K, Willen L, Iniguez E, Meneses C, Chaves LF, Zhang Y, dos Santos Felix L, et al: Leishmania sand fly-transmission is disrupted by Delftia tsuruhatensis TC1 bacteria. Nature Communications 2025. Vaselek S: Overview of microbial studies in sandflies and their progress toward development of paratransgenic approach for the control of Leishmania sp. Front Trop Dis 2024, 5:1369077 . Telleria EL, Martins-da-Silva A, Tempone AJ, Traub-Cseko YM: Leishmania, microbiota and sand fly immunity. Parasitology 2018, 145: 1336-1353. Cecilio P, Oristian J, Meneses C, Serafim TD, Valenzuela JG, Cordeiro da Silva A, Oliveira F: Engineering a vector-based pan-Leishmania vaccine for humans: proof of principle. Sci Rep 2020, 10: 18653. Tabbabi A, Mizushima D, Yamamoto DS, Kato H: Effects of host species on microbiota composition in Phlebotomus and Lutzomyia sand flies. Parasit Vectors 2023, 16: 310. Guernaoui S, Garcia D, Gazanion E, Ouhdouch Y, Boumezzough A, Pesson B, Fontenille D, Sereno D: Bacterial flora as indicated by PCR-temperature gradient gel electrophoresis (TGGE) of 16S rDNA gene fragments from isolated guts of phlebotomine sand flies (Diptera: Psychodidae). J Vector Ecol 2011, 36 Suppl 1: S144-147. Volf P, Kiewegova A, Nemec A: Bacterial colonisation in the gut of Phlebotomus duboseqi (Diptera: Psychodidae): transtadial passage and the role of female diet. Folia Parasitol (Praha) 2002, 49: 73-77. Karakus M, Karabey B, Orcun Kalkan S, Ozdemir G, Oguz G, Erisoz Kasap O, Alten B, Toz S, Ozbel Y: Midgut Bacterial Diversity of Wild Populations of Phlebotomus (P.) papatasi, the Vector of Zoonotic Cutaneous Leishmaniasis (ZCL) in Turkey. Sci Rep 2017, 7: 14812. Monteiro CC, Villegas LE, Campolina TB, Pires AC, Miranda JC, Pimenta PF, Secundino NF: Bacterial diversity of the American sand fly Lutzomyia intermedia using high-throughput metagenomic sequencing. Parasit Vectors 2016, 9: 480. Vaselek S, Sarac BE, Uzunkaya AD, Yilmaz A, Karaaslan C, Alten B: Identification of Ochrobactrum as a bacteria with transstadial transmission and potential for application in paratransgenic control of leishmaniasis. Parasitol Res 2024, 123: 82. Vivero RJ, Castaneda-Monsalve VA, Romero LR, G DH, Cadavid-Restrepo G, Moreno-Herrera CX: Gut Microbiota Dynamics in Natural Populations of Pintomyia evansi under Experimental Infection with Leishmania infantum. Microorganisms 2021, 9 . Saab SA, Dohna HZ, Nilsson LKJ, Onorati P, Nakhleh J, Terenius O, Osta MA: The environment and species affect gut bacteria composition in laboratory co-cultured Anopheles gambiae and Aedes albopictus mosquitoes. Sci Rep 2020, 10: 3352. Cecilio P, Iniguez E, Huffcutt P, Ribeiro SP, Kamhawi S, Valenzuela JG, Serafim TD: The impact of blood on vector-borne diseases with emphasis on mosquitoes and sand flies. Trends Parasitol 2025, 41: 196-209. Cecilio P, Pires A, Valenzuela JG, Pimenta PFP, Cordeiro-da-Silva A, Secundino NFC, Oliveira F: Exploring Lutzomyia longipalpis Sand Fly Vector Competence for Leishmania major Parasites. J Infect Dis 2020, 222: 1199-1203. Lawyer P, Killick-Kendrick M, Rowland T, Rowton E, Volf P: Laboratory colonization and mass rearing of phlebotomine sand flies (Diptera, Psychodidae). Parasite 2017, 24: 42. DeSouza-Vieira T, Iniguez E, Serafim TD, de Castro W, Karmakar S, Disotuar MM, Cecilio P, Lacsina JR, Meneses C, Nagata BM, et al: Heme Oxygenase-1 Induction by Blood-Feeding Arthropods Controls Skin Inflammation and Promotes Disease Tolerance. Cell Rep 2020, 33: 108317. Serafim TD, Iniguez E, Barletta ABF, Cecilio P, Doehl JSP, Short M, Lack J, Nair V, Disotuar M, Wilson T, et al: Leishmania genetic exchange is mediated by IgM natural antibodies. Nature 2023, 623: 149-156. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, Alexander H, Alm EJ, Arumugam M, Asnicar F, et al: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 2019, 37: 852-857. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP: DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods 2016, 13: 581-583. Price MN, Dehal PS, Arkin AP: FastTree 2--approximately maximum-likelihood trees for large alignments. PLoS One 2010, 5: e9490. Katoh K, Standley DM: MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 2013, 30: 772-780. Yilmaz P, Parfrey LW, Yarza P, Gerken J, Pruesse E, Quast C, Schweer T, Peplies J, Ludwig W, Glockner FO: The SILVA and "All-species Living Tree Project (LTP)" taxonomic frameworks. Nucleic Acids Res 2014, 42: D643-648. Shannon CE, Weaver W: The mathematical theory of communication. Urbana,: University of Illinois Press; 1949. Faith DP: Conservation evaluation and phylogenetic diversity. Biological Conservation 1992, 61: 1-10. Pielou EC: The measurement of diversity in different types of biological collections. Journal of Theoretical Biology 1966, 13: 131-144. Chen J, Bittinger K, Charlson ES, Hoffmann C, Lewis J, Wu GD, Collman RG, Bushman FD, Li H: Associating microbiome composition with environmental covariates using generalized UniFrac distances. Bioinformatics 2012, 28: 2106-2113. Cailliez F: The analytical solution of the additive constant problem. Psychometrika 1983, 48: 305-308. Anderson MJ: A new method for non-parametric multivariate analysis of variance. Austral Ecology 2001, 26: 32-46. Anderson MJ, Ellingsen KE, McArdle BH: Multivariate dispersion as a measure of beta diversity. Ecology Letters 2006, 9: 683-693. Lin H, Peddada SD: Analysis of compositions of microbiomes with bias correction. Nature Communications 2020, 11: 3514. Additional Declarations No competing interests reported. Supplementary Files Tangetal2025AdditionalFiles.docx Additional Files Supplementary Figures 1 and 2 Supplementary Tables 1 to 7 Supplementary Data 1 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-7384237","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502719145,"identity":"d8555a34-d440-4214-a0a1-c924dcafd9db","order_by":0,"name":"Kristina Tang","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Kristina","middleName":"","lastName":"Tang","suffix":""},{"id":502719146,"identity":"d31b9c6f-be00-404a-8d3c-d169de33138b","order_by":1,"name":"Yue Zhang","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Zhang","suffix":""},{"id":502719147,"identity":"8b011d90-8224-487a-9ef0-005e4ecb89cc","order_by":2,"name":"Claudio Meneses","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Claudio","middleName":"","lastName":"Meneses","suffix":""},{"id":502719148,"identity":"e4bf05bd-0e27-4360-a5b5-6730bf0d6c36","order_by":3,"name":"Luana A. Rogerio","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Luana","middleName":"A.","lastName":"Rogerio","suffix":""},{"id":502719149,"identity":"068a515b-f55c-4178-a452-acfff607e2e2","order_by":4,"name":"Laura Willen","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Willen","suffix":""},{"id":502719150,"identity":"50c0cdee-4a9d-45e2-b7fd-fe0da3abcd01","order_by":5,"name":"Eva Iniguez","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Eva","middleName":"","lastName":"Iniguez","suffix":""},{"id":502719152,"identity":"63d7c539-8ed6-4b28-a895-198b128d4f73","order_by":6,"name":"Shaden Kamhawi","email":"","orcid":"","institution":"National Institutes of Health","correspondingAuthor":false,"prefix":"","firstName":"Shaden","middleName":"","lastName":"Kamhawi","suffix":""},{"id":502719154,"identity":"847e9eaa-9876-4fa6-ad03-1042b39d50c5","order_by":7,"name":"Jesus G. 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(\u003cstrong\u003eA\u003c/strong\u003e) Variation in the number of observed Amplicon Sequence Variants ASVs with the status of infection. Box-and-whisker graphs show an overview of the calculated values per pool of sand fly midguts collected before infection (day 0; grey; n=4), early after \u003cem\u003eLeishmania\u003c/em\u003e infection (days 2 and 5; red; n=8), and late after \u003cem\u003eLeishmania\u003c/em\u003e infection (days 7, 9, and 12; orange; n=9). Statistical significance was determined using the Kruskal-Wallis test followed by post-hoc analysis and is highlighted (*p\u0026lt;0.05). (\u003cstrong\u003eB\u003c/strong\u003e) Relative abundance at the genus level per sample pool and time-point (left panel), as well as per infection status (right panel). The most abundant families are color-coded. All results were obtained in three independent experiments.\u003c/p\u003e","description":"","filename":"Figure1New.png","url":"https://assets-eu.researchsquare.com/files/rs-7384237/v1/9eebbc85911e054942440b88.png"},{"id":89628927,"identity":"ddf404bf-df47-4388-85cc-dcf56bf57770","added_by":"auto","created_at":"2025-08-22 06:25:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":647035,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBacterial diversity metrics. \u003c/strong\u003ePools of P. \u003cem\u003eduboscqi\u003c/em\u003esand fly midguts were collected one day before (day 0), as well as 2, 5, 7, 9, and 12 days after infection with \u003cem\u003eL. major\u003c/em\u003e parasites and subjected to metagenomics analysis. Three different indicators were used to evaluate the alpha diversity at the infection status level: (\u003cstrong\u003eA\u003c/strong\u003e) Shannon Index, (\u003cstrong\u003eB\u003c/strong\u003e) Pielou Evenness, and (\u003cstrong\u003eC\u003c/strong\u003e) Faith PD. Box-and-whisker graphs show an overview of the calculated values per pool of sand fly midguts collected before infection (day 0; grey; n=4), early after \u003cem\u003eLeishmania\u003c/em\u003e infection (days 2 and 5; red; n=8), and late after \u003cem\u003eLeishmania\u003c/em\u003einfection (days 7, 9, and 12; orange; n=9). Statistical significance was determined using the Kruskal-Wallis test followed by post-hoc analysis and is highlighted. (\u003cstrong\u003eD\u003c/strong\u003e) PCA plot referring to the beta-diversity weighed analysis at the infection status level. Each dot represents and individual sample, which is color coded: samples collected before (day 0), early (days 2 and 5) after, and late (days 7, 9, and 12) after \u003cem\u003eLeishmania \u003c/em\u003einfection are highlighted in grey, red, and orange, respectively. Statistical significance (permutational ANOVA and beta dispersion analyses) is denoted in the graph. All results were obtained in three independent experiments.\u003c/p\u003e","description":"","filename":"Figure2New.png","url":"https://assets-eu.researchsquare.com/files/rs-7384237/v1/a92b709682f3b619576c4fb9.png"},{"id":89630773,"identity":"0ed6c292-d462-4a63-9a82-b0e3f294aaa7","added_by":"auto","created_at":"2025-08-22 06:41:29","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":577263,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbsolute abundance-based infection stage-specific markers. \u003c/strong\u003ePools of P. \u003cem\u003eduboscqi\u003c/em\u003e sand fly midguts were collected one day before (day 0), as well as 2, 5, 7, 9, and 12 days after infection with \u003cem\u003eL. major\u003c/em\u003e parasites and subjected to metagenomics analysis. Analysis was done in the frame of three major groups: before infection (day 0), early after infection (days 2 and 5), and late after infection (days 7, 9, and 12). (\u003cstrong\u003eA\u003c/strong\u003e) Significant changes in the estimated absolute abundance of different bacterial genera in the sand fly midgut early after \u003cem\u003eversus \u003c/em\u003ebefore \u003cem\u003eLeishmania\u003c/em\u003e infection (left panel), late after \u003cem\u003eversus \u003c/em\u003ebefore \u003cem\u003eLeishmania\u003c/em\u003e infection (center panel), and late \u003cem\u003eversus \u003c/em\u003eearly after \u003cem\u003eLeishmania\u003c/em\u003e infection (right panel). Data are represented by effect size (LogFC) and Standard Error bars (two-sided; Bonferroni adjusted) derived from the ANCOM-BC model. All effect sizes with adjusted p \u0026lt; 0.1 (q value) are indicated: \u003csup\u003es\u003c/sup\u003e, *, **, and *** significant at 10%, 5%, 1%, and 0.1% level of significance, respectively. Exact adjusted p values can be found in Supplementary Table 6. (\u003cstrong\u003eB\u003c/strong\u003e) Significant changes in the estimated absolute abundance of different bacterial families in the sand fly midgut early after \u003cem\u003eversus \u003c/em\u003ebefore \u003cem\u003eLeishmania\u003c/em\u003e infection (left panel), late after \u003cem\u003eversus \u003c/em\u003ebefore \u003cem\u003eLeishmania\u003c/em\u003e infection (center panel), and late \u003cem\u003eversus \u003c/em\u003eearly after \u003cem\u003eLeishmania\u003c/em\u003e infection (right panel). Data are represented by effect size (LogFC) and Standard Error bars (two-sided; Bonferroni adjusted) derived from the ANCOM-BC model. All effect sizes with adjusted p \u0026lt; 0.1 (q value) are indicated: \u003csup\u003es\u003c/sup\u003e, *, **, and *** significant at 10%, 5%, 1%, and 0.1% level of significance, respectively. Exact adjusted p values can be found in Supplementary Table 7. All results were obtained in three independent experiments.\u003c/p\u003e","description":"","filename":"Figure3New.png","url":"https://assets-eu.researchsquare.com/files/rs-7384237/v1/a6407b69dd49082f9f44310c.png"},{"id":90577188,"identity":"05c420f7-d82a-48e0-9b8e-4154b5612aaa","added_by":"auto","created_at":"2025-09-04 09:32:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4363406,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7384237/v1/798d8623-7706-4c85-b307-4ad41264b094.pdf"},{"id":89631524,"identity":"bff4e9b6-2797-40ab-8047-6036a8f3c573","added_by":"auto","created_at":"2025-08-22 06:49:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":195251,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional Files\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary Figures 1 and 2\u003c/p\u003e\n\u003cp\u003eSupplementary Tables 1 to 7\u003c/p\u003e\n\u003cp\u003eSupplementary Data 1\u003c/p\u003e","description":"","filename":"Tangetal2025AdditionalFiles.docx","url":"https://assets-eu.researchsquare.com/files/rs-7384237/v1/ee8ea17921e0c68e2b03f7d1.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Phlebotomus duboscqi gut microbiota dynamics in the context of Leishmania infection","fulltext":[{"header":"Background","content":"\u003cp\u003eAlthough often not recognized as so, sand flies are among the insects of significant public-health concern. Like mosquitoes, sand flies show a worldwide distribution, depend on blood to complete their life cycle, and can transmit a variety of pathogens [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Among these, \u003cem\u003eLeishmania\u003c/em\u003e spp. parasites, the causative agents of human leishmaniasis, are the ones associated with the highest disease/socioeconomic burden [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]; over one million leishmaniasis cases are estimated to occur each year, most of them referring to the non-fatal cutaneous form [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Of note, most \u003cem\u003eLeishmania\u003c/em\u003e parasites that cause disease in humans are zoonotic agents [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], a vaccine for human leishmaniasis (either prophylactic or therapeutic) is yet to be approved, and the molecules available for the treatment of human cases are limited and increasingly compromised by the emergence of drug resistance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, the control of leishmaniasis is extremely challenging, requiring a multifaceted approach that needs to have a major focus on the sand fly vector, instead of relying solely in case-control strategies.\u003c/p\u003e\u003cp\u003eWhile there are a few sand fly-based approaches in use for the control of leishmaniasis, they all rely on the prevention of sand fly-human contact [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These, that include the use of repellents and insecticides, are not without limitations, including the emergence of resistant insect populations [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Of note, contrary to the reality for other disease vectors [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], no control method targeting specifically the infection within sand flies is available for application [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Yet, recent studies reported that, if depleted from their natural gut microbiota, sand flies are no longer able to sustain the development of \u003cem\u003eLeishmania\u003c/em\u003e spp. parasites within their midguts [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This suggests a crucial role for sand fly midgut bacteria in the establishment of \u003cem\u003eLeishmania\u003c/em\u003e spp. in sand flies; thus, we should be able to make sand flies refractory to infection via the manipulation of their gut microbiota. Our recent work shows the potential of such an approach. By introducing a mosquito symbiont, \u003cem\u003eDelftia tsuruhatensis\u003c/em\u003e TC1, in the sand fly midgut, we induced a state of sand fly gut dysbiosis that negatively impacted the development of \u003cem\u003eLeishmania major\u003c/em\u003e parasites in the vector [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Importantly, this led to a decreased potential of effective transmission of \u003cem\u003eL. major\u003c/em\u003e to hosts, associated with a lower risk of disease development in an animal model of cutaneous leishmaniasis [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor the development of similar approaches, there is the need for a comprehensive understanding of the composition and dynamics of the gut microbiota of sand flies. However, while the gut microbiota of some species of medical importance, including \u003cem\u003eLutzomyia longipalpis\u003c/em\u003e and \u003cem\u003ePhlebotomus papatasi\u003c/em\u003e, has been extensively characterized, the information available on the subject for other species is limited [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Among the latter, we find \u003cem\u003ePhlebotomus duboscqi\u003c/em\u003e sand flies, the main West African vectors of \u003cem\u003eL. major\u003c/em\u003e-caused cutaneous leishmaniasis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Only four studies looked at the sand fly gut microbiota of colony-reared \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The older studies focused either on culturable bacteria [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], or on temperature-gradient gel electrophoresis of whole DNA [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] and only in the context of non-infected sand flies. The two most recent studies used more modern 16S-based sequencing methods, including in the context of infected sand flies, but looking only at a single time-point after infection (either early [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] or late [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]). To our knowledge, no study documented the gut microbiome dynamics of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies over the entire time-period required for the maturation of a \u003cem\u003eLeishmania\u003c/em\u003e infection. Here, to address this limitation, we looked at the differences of the gut microbiome of laboratory-reared \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies before and after \u003cem\u003eL. major\u003c/em\u003e infection, with the necessary temporal resolution to understand the dynamics of sand fly gut microbial communities throughout the infection timeline.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTo investigate the dynamic changes in \u003cem\u003eP. duboscqi\u003c/em\u003e gut microbial communities in the context of \u003cem\u003eLeishmania\u003c/em\u003e infection, pools of sand fly midguts were collected one day before (day 0), as well as 2, 5, 7, 9, and 12 days after infection with \u003cem\u003eL. major\u003c/em\u003e parasites, and subjected to metagenomics analysis. The infection followed a healthy pattern, with the number of parasites per midgut plateauing after day 7 of infection (Supplementary Fig.\u0026nbsp;1A), and the frequency of metacyclic parasites increasing dramatically from day 7 onward (Supplementary Fig.\u0026nbsp;1B). For analysis purposes, samples were either considered by individual time-point, or joined together in the frame of three major groups: before infection, early after infection (days 2 and 5 post-infection, when blood or blood remnants may still be found in the midgut), and late after infection (days 7, 9, and 12 post-infection, when metacyclic promastigotes start to be present in the sand fly midgut; Supplementary Fig.\u0026nbsp;1B).\u003c/p\u003e\u003cp\u003eFirst, we looked at the number of observed Amplicon Sequence Variants (ASVs) as a reflection of the richness of bacteria found in the sand fly gut microbiota. A significant difference was detected, particularly when we compared the sand fly gut microbiota before and early after infection, with a lower number of ASVs observed in the latter group (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA; Supplementary Table\u0026nbsp;1 - adjusted p\u0026thinsp;=\u0026thinsp;0.041). This was mostly due to a decrease in the number of ASVs 2 days post-infection (Supplementary Fig.\u0026nbsp;2A; Supplementary Table\u0026nbsp;2). Later after infection, a partial recovery in the number of observed ASVs was evident, although to median group levels still lower than those observed before infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Of note, considering the individual time-points pertaining to this period, a tendency of reduction of the number of observed ASVs was observed for the last one (12 days post-infection; Supplementary Fig.\u0026nbsp;2A).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNext, we characterized the abundance of major bacterial groups (the 10 most abundant) found in the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies throughout the \u003cem\u003eLeishmania\u003c/em\u003e infection timeline. While some heterogeneity was visible among individual samples collected at the same time-point (something not unexpected since we are looking at pools collected from 20 sand flies each), some changes were evident, particularly in the context of our infection status-based analysis approach (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB; Supplementary Fig.\u0026nbsp;2B). Before infection, more than 85% or relative abundance was attributed to 4 main genera: \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eLeifsonia\u003c/em\u003e, \u003cem\u003eOchrobactrum\u003c/em\u003e, and \u003cem\u003eSerratia\u003c/em\u003e (27.7%, 27.2%, 19.3%, 12.0% relative abundance at the group level, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, right panel; Supplementary Table\u0026nbsp;3). This translated into the dominance of 4 main families before \u003cem\u003eLeishmania\u003c/em\u003e-infection (each including one of the abovementioned genera, in the respective order): Sphingomonadaceae, Microbacteriaceae, Rhizobiaceae, and Yersiniaceae (27.7%, 27.2%, 21.8%, and 12.1% relative abundance at the group level, respectively; Supplementary Fig.\u0026nbsp;2B, right panel; Supplementary Table\u0026nbsp;4).\u003c/p\u003e\u003cp\u003eEarly after infection, the most evident change was an increase in the relative abundance of the \u003cem\u003eOchrobactrum\u003c/em\u003e genus (and the Rhizobiaceae family) to around 50% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; right panels). Additionally, two other families, Alcaligenaceae (no genus attributed; listed under the unknown genera category) and Pseudomonadaceae (mainly referring to the \u003cem\u003ePseudomonas\u003c/em\u003e genus) also increased in abundance to values above 6% at the group level; in the latter case, this was mostly due to the contribution of an individual sample (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; left panels; Supplementary Tables\u0026nbsp;3 and 4). Conversely, all other abundance-wise relevant genera/families either maintained or decreased their prevalence early after infection, at the group level. \u003cem\u003eLeifsonia\u003c/em\u003e (Microbacteriaceae family) contracted the most in relative terms, followed by \u003cem\u003eSphingomonas\u003c/em\u003e (Sphingomonadaceae family); for the sake of comparison relative abundance values at the genus level dropped to 3.0%, and 11.3%, respectively as compared to values of 27.2% and 27.7%, before infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; right panels; Supplementary Tables\u0026nbsp;3 and 4). Of note, \u003cem\u003eSerratia\u003c/em\u003e (Yersiniaceae family) seemed to maintain a relative abundance weight (as compared to the before infection scenario) of around 13% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; Supplementary Tables\u0026nbsp;3 and 4).\u003c/p\u003e\u003cp\u003eLate after infection both the \u003cem\u003eOchrobactrum\u003c/em\u003e and \u003cem\u003eSphingomonas\u003c/em\u003e genera (and the Rhizobiaceae and Sphingomonadaceae families, respectively) returned to the relative abundance levels observed before infection, with a contraction of the former and an expansion of the latter when comparing with the early after infection status (e.g. relative abundance values 19.7% and 24.0%, respectively at the genus level; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; Supplementary Tables\u0026nbsp;3 and 4). The same was true for the Alcaligenaceae and Pseudomonadaceae families; both lost relevance later after infection, returning to the low relative abundance values (below 1%) detected before infection (Supplementary Fig.\u0026nbsp;2B; Supplementary Table\u0026nbsp;4). On the other hand, \u003cem\u003eLeifsonia\u003c/em\u003e (Microbacteriaceae family) did not recover, maintaining an even lower relative abundance late after infection (e.g. at the genus level, 0.9% versus the 3.0% determined early after infection; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; Supplementary Tables\u0026nbsp;3 and 4). In contrast, 3 genera/families increased in relative abundance to levels above those detected for both the pre-infection and early infection statuses. \u003cem\u003eSerratia\u003c/em\u003e (Yersiniaceae family) became the most prevalent late after infection (25.8% both at the genus and family level; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; Supplementary Tables\u0026nbsp;3 and 4). Additionally, the \u003cem\u003eTsukamurella\u003c/em\u003e and \u003cem\u003eAsaia\u003c/em\u003e genera (and the Tsukamurellacea and Acetobacteraceae families, respectively) also increased in relative abundance from less than 0.5% before and early after infection to around 5% late after infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; right panels; Supplementary Tables\u0026nbsp;3 and 4). Interestingly, both were detected in higher abundance from day 9 post-infection onward, as per individual sample data (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB, and Supplementary Fig.\u0026nbsp;2B; left panels). Of note, one other genus (family), \u003cem\u003eRalstonia\u003c/em\u003e (Burkholderiaceae) showed relevant, although lower relative abundance values throughout the experimental timeline; these contracted from 3.6% before infection to 1.1% early after infection and then expanded to 2.8% late after infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;2B; Supplementary Tables\u0026nbsp;3 and 4). The combined relative abundance of all remaining genera (families) varied from around 6% before infection to around 9% late after infection.\u003c/p\u003e\u003cp\u003eThe above-reported changes highlighted possible dynamic alterations in the composition of the microbial communities of the sand fly midgut in the context of \u003cem\u003eLeishmania\u003c/em\u003e infection. Therefore, next we looked specifically at bacterial diversity. With respect to alpha diversity metrics, referring to within-sample diversity and considering overall both the richness and evenness of bacterial communities in a sample, no statistically significant differences were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA-C). Regarding both Shannon index and Pielou evenness metrics, the distribution of individual samples overlapped in the context of the 3 groups studied, with a higher dispersion of values early after infection, and a tendentiously higher median late after infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and B, respectively). On the other hand, the profile with regards to the Faith PD metric (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), was quite similar to that seen in the context of the Observed ASVs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), with a decrease in the values for early after infection samples, although to an extent not enough to reach statistical relevance. On the other hand, with respect to beta diversity metrics (weighted UniFrac distance), reflecting the overall composition at the group level, statistically significant differences were detected. A separation between the 3 groups was evident [p(adonis)\u0026thinsp;=\u0026thinsp;0.003], and to a greater extend between before infection and early after infection samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). This translated into significant differences when we compared specifically the before infection and early after infection groups [p(PERMANOVA)\u0026thinsp;=\u0026thinsp;0.024; Supplementary Table\u0026nbsp;5], as well as almost significant differences when we compared both the before infection and late after infection groups [p(PERMANOVA)\u0026thinsp;=\u0026thinsp;0.0959; Supplementary Table\u0026nbsp;5], and the early after infection and late after infection groups [p(PERMANOVA)\u0026thinsp;=\u0026thinsp;0.054; Supplementary Table\u0026nbsp;5]. Of note, no major differences in terms of sample dispersion within groups (or group heterogeneity) were observed [p(betadisp) and p(PERMDISP)\u0026thinsp;\u0026gt;\u0026thinsp;0.2; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD; Supplementary Table\u0026nbsp;5]. Overall, these results suggest that the composition of the sandfly gut microbiota changes dynamically with the progression of \u003cem\u003eLeishmania\u003c/em\u003e infection in sand flies.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eLast, we focused on differences in estimated absolute abundance values (ANCOM-BC analysis) looking for potential markers of early and/or late infection, considering not only highly abundant genera/families, but also those with lower relative abundance values. Importantly, a few of the above-reported apparent differences in terms of relative abundance values for the highly abundant genera/families were still noted in the context of absolute numbers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B; Supplementary Tables\u0026nbsp;6 and 7). For instance, a significant decrease in the number of Microbacteriaceae late after versus before infection was noted (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB; Supplementary Table\u0026nbsp;7). More so, a significant increase in the number of \u003cem\u003eRalstonia\u003c/em\u003e, and consequently of Burkholderiaceae at the family level, as well as of \u003cem\u003eSphingomonas\u003c/em\u003e (only at the genus level in this case) was detected late versus early after infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B; Supplementary Tables\u0026nbsp;6 and 7). Interestingly, via this estimated absolute abundance-based differential analysis, nine new genera/families were noted to change significantly in the context of \u003cem\u003eLeishmania\u003c/em\u003e infection. \u003cem\u003eCutibacterium\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e (Propionibacteriaceae and Porphyromonadaceae, respectively, at the family level) showed significantly lower numbers early after versus before infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B; Supplementary Tables\u0026nbsp;6 and 7). \u003cem\u003eCorynebacterium\u003c/em\u003e (and Corynebacteriaceae at the family level) also showed significantly lower numbers early after versus before infection, as well as late after versus before infection, making this genus/family a potential marker of non-infected sand flies (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B; Supplementary Tables\u0026nbsp;6 and 7). Conversely, the genus \u003cem\u003eEnterococcus\u003c/em\u003e (and the family Enterococcaceae) showed significantly higher absolute abundance both early and late after infection, highlighting them as potential general markers of \u003cem\u003eLeishmania\u003c/em\u003e-infected sand flies in our experimental context (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B; Supplementary Tables\u0026nbsp;6 and 7). More so, our results also revealed a decrease in the numbers of Peptostreptococcaceae late after versus before infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB; Supplementary Table\u0026nbsp;7). Importantly, we also detected significant changes when we compared the late versus early after infection statuses. In this context, we observed a significant increase in the absolute numbers of the \u003cem\u003eStreptococcus\u003c/em\u003e and \u003cem\u003eAbiotrophia\u003c/em\u003e genera (and the Streptococcaceae and Aerococcaceae families, respectively), as well as of the order Saccharimonadales, to which we could not assign a family/genera (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and B; Supplementary Tables\u0026nbsp;6 and 7). Overall, these results align with relative abundance/bacterial diversity ones, further supporting the notion that the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies change dramatically in the context of \u003cem\u003eLeishmania\u003c/em\u003e infection.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith this study, we aimed to characterize the gut microbial communities of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies, with emphasis on the potential dynamic changes resulting from the development of a \u003cem\u003eLeishmania\u003c/em\u003e infection. Overall, we show that the composition of the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies changes significantly over the course of an infection with \u003cem\u003eL. major\u003c/em\u003e parasites.\u003c/p\u003e\u003cp\u003eOne curious observation in this study was the decrease in the number of observed ASVs in 2 different occasions: early after infection in a significant fashion, particularly at day 2, and late after infection, specifically at day 12. Interestingly, these results are in line with those previously reported for \u003cem\u003eLu. longipalpis\u003c/em\u003e sand flies infected with \u003cem\u003eL. infantum\u003c/em\u003e parasites, both in the context of observed operational taxonomic units - OTUs - and of phylogenetic diversity [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Together, both studies point to two distinct events of \u0026ldquo;microbial richness loss\u0026rdquo;, likely driven by selective pressures of different origins. The first decrease in richness is probably a result of the apport of new nutrients after the ingestion of blood by the sand fly. The second can be a consequence of both a bacteria-bacteria and bacteria-parasite competition for limited resources within a midgut now populated by high \u003cem\u003eLeishmania\u003c/em\u003e numbers, and/or the result of a re-arrangement of microbial communities shaped by \u003cem\u003eLeishmania\u003c/em\u003e excreted byproducts. Of note, our beta diversity results do not show a recovery in the composition of the gut microbiota of sand flies after the defecation of blood meal remnants (before versus late after infection). This further supports the occurrence of independent selective pressure events that shape the midgut microbiota of adult \u003cem\u003eLeishmania\u003c/em\u003e-infected female sand flies.\u003c/p\u003e\u003cp\u003eIn line with the variation in sand fly midgut bacterial richness with the course of infection, we also detected changes in the relative abundance of different bacterial genera/families. In this context, we can try to establish some parallels with the reported in previous studies. For instance, an apparent dominance of \u003cem\u003eOchrobactrum\u003c/em\u003e spp. in the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies was previously reported by Volf et al, including in blood-fed insects [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A dominance of the family Rhizobiaceae, of which \u003cem\u003eOchrobactrum\u003c/em\u003e spp. is part of, was also reported in the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies both before, and after taking a non-infected bloodmeal by Tabbabi et al [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and 14 days after infection by Louradour and colleagues [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Our data, showing the relative dominance of \u003cem\u003eOchrobactrum\u003c/em\u003e spp. early after infection, as well as a significant relative abundance both before and late after infection, may align with these published data. We do need to consider that the study by Volf et al only looked at culturable bacteria [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and thus the relative values reported are probably over-estimated, while the study by Tabbabi et al was based on a limited number of samples[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], lacking the resolution necessary to account for the expected sample-to-sample heterogeneity. Of note, other studies have reported the presence of \u003cem\u003eOchrobactrum\u003c/em\u003e spp. in sand fly larval rearing sites, and the ability of these bacteria to be transtadially transmitted from larvae to adults, explaining the presence of this bacterial genus in the gut microbiota of different lab-reared and wild-caught sand fly species [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAdditionally, the increase in the relative abundance of \u003cem\u003eTsukamurella\u003c/em\u003e spp. late after infection observed in this study was also previously reported in \u003cem\u003eLu. longipalpis\u003c/em\u003e sand flies infected with \u003cem\u003eL. infantum\u003c/em\u003e parasites [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; the same parallel can be made with the Acetobacteraceae family, albeit with a much lower proportional increase late after infection in our study. Of note, the \u003cem\u003eP. duboscqi\u003c/em\u003e and \u003cem\u003eLu. longipalpis\u003c/em\u003e sand flies used in this study and in [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], respectively, are reared in the same environment and with the same food and sugar sources. However, while previously \u003cem\u003eTsukamurella\u003c/em\u003e spp. together with the Actinobacteria/Actinomycetota phylum (among others) were statistically defined, via linear discriminant analysis, as potential markers of infected sand flies [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], that was not the case in our context, after an ANCOM-BC analysis; for \u003cem\u003eTsukamurella\u003c/em\u003e spp. this was likely due to the observed sample heterogeneity. Instead, in this study, the genus \u003cem\u003eEnterococcus\u003c/em\u003e and the family Enterococcaceae were defined as potential markers of infected sand flies, while the genus \u003cem\u003eCorynebacterium\u003c/em\u003e and the family Corynebacteriaceae (curiously belonging to the Actinobacteria/Actinomycetota phylum) were defined as potential markers of non-infected sand flies. While we cannot exclude the hypothesis that these contradictory results may be just a consequence of the different statistical methods used in the two studies, overall, they seem to suggest that the diet is, likely, not the only factor that influences the microbiota of adult sand flies, in line with what was reported for mosquitoes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The hypothesis that, not only the genetic background, but also the infectious agent (different in the two contexts mentioned above) may condition the gut microbiota of adult sand flies is something to consider. A future side-by-side study of the gut microbiota of \u003cem\u003eLu. longipalpis\u003c/em\u003e and \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies infected with \u003cem\u003eL. infantum\u003c/em\u003e and \u003cem\u003eL. major\u003c/em\u003e parasites, respectively is warranted, both to address this hypothesis, and to disclose potential vector-parasite specific microbial signatures.\u003c/p\u003e\u003cp\u003eInterestingly, our ANCOM-BC analysis also revealed some bacterial genera significantly more abundant in sand flies late versus early after infection, including \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eRalstonia\u003c/em\u003e and \u003cem\u003eAbiotrophia\u003c/em\u003e spp. The fact that these genera increase in absolute abundance in sand flies with heavier \u003cem\u003eLeishmania\u003c/em\u003e infectious burdens may indicate a favorable parasite-bacteria relationship. These bacteria may proliferate in response to \u003cem\u003eLeishmania\u003c/em\u003e growth, and/or they may be important to sustain the development of \u003cem\u003eLeishmania\u003c/em\u003e parasites in the sand fly midgut. Of note, previous \u003cem\u003eLeishmania\u003c/em\u003e infection studies in the context of antibiotic-treated sand flies, reported that \u003cem\u003eLeishmania\u003c/em\u003e parasites need an undisturbed sand fly gut microbiota to establish themselves in the vector [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. We can, therefore, speculate that some bacterial species within the abovementioned genera are \u003cem\u003eLeishmania\u003c/em\u003e infection/metacyclogenesis promoters; none of these were previously identified as such. Future studies aiming at isolating these bacteria and characterizing their role in the context of \u003cem\u003eLeishmania\u003c/em\u003e infection will help us to address this possibility. Of note, in this context there is a precedent. Louradour et al. reported that \u003cem\u003eSerratia rubidaea\u003c/em\u003e bacteria are \u003cem\u003eLeishmania\u003c/em\u003e infection-enhancers in the context of sand fly gut dysbiosis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In our study Serratia spp. was the genus with the higher relative weight detected late after infection, and within the \u003cem\u003eSerratia\u003c/em\u003e species we were able to attribute via our metagenomics analysis we found \u003cem\u003eSerratia rubidaea\u003c/em\u003e (Supplementary Data 1).\u003c/p\u003e\u003cp\u003eThis study is not without limitations. For instance, our experimental settings differ from what is expected to occur in the field: i) sand flies take an infected bloodmeal from a living host [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] (whose species may vary), and not via artificial membrane feeding; and ii) sand flies are expected to take multiple bloodmeals throughout their adult life span with consequences for vector competence [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Future studies on the effect of multiple blood meals (and different blood sources) on the gut microbiota of naturally infected sand flies are warranted. Additionally, we characterized the microbiota of the whole sand fly midgut, thus lacking the spatial resolution achieved by Louradour et al, that, albeit using cloning and PCR, analyzed the microbiome of different midgut regions [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The use of higher depth techniques associated with a more compartmentalized analysis, may provide useful insights into the dynamics of the sand fly gut microbiota as \u003cem\u003eLeishmania\u003c/em\u003e spp. infection matures. Lastly, we analyzed the microbiota in the context of pooled samples and thus were neither able to look at potential individual variability, nor to establish potential associations between gut microbial composition and infection burden. Future studies looking at the gut microbiota of individual sand fly specimens are also warranted.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eHere, we show that the composition of the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies changes significantly over the course of an infection with \u003cem\u003eL. major\u003c/em\u003e parasites. Our data contribute to the body of work in this field and may guide future studies aiming to: i) characterize different \u003cem\u003eLeishmania\u003c/em\u003e-bacteria interactions in the sand fly midgut, ii) isolate bacteria beneficial and detrimental for the development of \u003cem\u003eLeishmania\u003c/em\u003e parasites, and iii) leverage bacterial isolates/byproducts to manipulate the sand fly gut microbiota and negatively impact the development of \u003cem\u003eLeishmania\u003c/em\u003e spp. parasites in their respective vectors.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eEthics Statement\u003c/h2\u003e\u003cp\u003eAll animal experiments were carried out in accordance with the National Institute of Allergy and Infectious Diseases (NIAID) Animal Care and Use Committee under the animal protocol LMVR4E.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParasites\u003c/h3\u003e\n\u003cp\u003eA cloned line of \u003cem\u003eLeishmania major\u003c/em\u003e (WR 2885) was used [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Promastigotes were maintained at 26\u0026deg;C in Schneider\u0026rsquo;s insect medium supplemented with 20% heat-inactivated fetal bovine serum, 100 U/mL penicillin, and 100 mg/mL streptomycin (all Thermo Fischer Scientific).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSand Flies\u003c/h2\u003e\u003cp\u003e\u003cem\u003ePhlebotomus duboscqi\u003c/em\u003e sand flies were mass reared at the Laboratory of Malaria and Vector Research insectary as previously described [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Adult females were maintained on a 30% sucrose diet and were starved for 12 hours before feeding.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSand Fly Infection\u003c/h3\u003e\n\u003cp\u003eAfter an overnight starving period, sand flies were infected by artificial feeding through a chick membrane on defibrinated rabbit blood (Spring Valley Laboratories, MD, USA) containing \u003cem\u003eL. major\u003c/em\u003e promastigotes (5x10\u003csup\u003e6\u003c/sup\u003e/ml), as previously described [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. After infection, blood-fed females were sorted and kept on a 30% sucrose diet.\u003c/p\u003e\n\u003ch3\u003eMetagenomics Analysis – Layout and Samples\u003c/h3\u003e\n\u003cp\u003eSand fly midguts were dissected under a sterile-like environment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] at different time-points: before blood feeding (D0), and different days after blood feeding (D2, D5, D7, D9, and D12). Dissected midguts were washed three times in sterile PBS drops and then transferred to a 1.5 ml Eppendorf centrifuge tube containing 50 \u0026micro;L of sterile PBS; pools of 20 midguts were collected per condition at least in triplicate. Genomic DNA was then extracted using the, and the samples were subjected to 16S rRNA amplification and sequencing (approximately 100,000 reads per sample) as reported elsewhere [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; the V3-V4 hypervariable regions of the 16S rRNA was targeted via the use of the primers 341F \u0026ndash; CCTAYGGGRBGCASCAG, and 806R \u0026ndash; GGACTACNNGGGTATCTAAT. Overall, a total of 21 samples were analyzed. For the analysis, frequently, samples were grouped by time-point. Additionally, in some instances, samples were grouped based on the status of infection: before infection (D0), early after infection (days 2 and 5), and late after infection (days 7, 9 and 12).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMetagenomics Analysis - Amplicon Sequence Variant Calling, Phylogenetic Tree, and Taxonomy Classification\u003c/h2\u003e\u003cp\u003eThis paper results from a re-analysis of the data collected in a different study [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], and previously deposited at NCBI under the BioProject number PRJNA1079352 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/bioproject/PRJNA1079352/con\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1079352/con\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); only CTRL samples are relevant to the present study. The initial analysis steps were common to the ones previously reported (code available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/GaryZhangYue/Cecilio_2024_TC1_sandflies\u003c/span\u003e\u003cspan address=\"https://github.com/GaryZhangYue/Cecilio_2024_TC1_sandflies\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBriefly, 16S rRNA amplicon reads were demultiplexed and trimmed using Novogene in-house scripts. The trimmed demultiplexed reads were then imported into QIIME2 version 2021.4 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] for downstream analysis. DADA2 [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] was used to call amplicon sequence variants (ASVs). Chimeric sequences were identified and removed by setting the flag \u0026ldquo;--p-min-fold-parent-over-abundance\u0026rdquo; to 10, which discards chimeric sequences showing an at least ten times lower abundant than their parent sequences. A rooted phylogenetic tree was generated using FastTree [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] based on ASV multiple alignment with MAFFT [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The ASVs were taxonomically classified with a Na\u0026iuml;ve Bayes classifier pre-trained on SILVA rRNA database (release 138 SSURef NR99) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. After DADA2 quality filtering, and considering only the CTRL samples, a total of 3,477,690 reads (165,604 \u0026plusmn; 4,990 reads/sample) were retained. The samples were then rarefied to a subsampling depth of 149,894 reads/sample to ensure an even sequencing depth. After rarefaction, 1,844 ASVs and all samples were retained.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eMetagenomics Analysis - Microbial Diversity Calculation, Statistical Testing, and Differential Abundance Testing\u003c/h2\u003e\u003cp\u003eThe diversity metrics were calculated using the QIIME2 core-metrics-phylogenetic function. The rarefied feature table was used to compute Shannon\u0026rsquo;s diversity metrics [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], observed features, Faith\u0026rsquo;s phylogenetic diversity index [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], Pielou\u0026rsquo;s evenness index [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], and UniFrac distance [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Statistical comparisons in this context were made using the Kruskal-Wallis test followed by a post-hoc analysis, when applicable, using the Dunn\u0026rsquo;s test. To visualize the dissimilarities in microbial communities across groups, the weighted UniFrac distance metrics was used to generate PCoA coordinates after Cailliez transformation [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] to correct for negative eigenvalues. Permutational multivariate analysis of variance (PERMANOVA) [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and permutational multivariate analysis of group dispersion homogeneity (PERMDISP) [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] were applied to compare the centroid location and within-group dispersion level, respectively, in the weighed UniFrac distance metrics across groups. Analysis of compositions of Microbiomes with Bias Correction (ANCOM-BC, version 2.0.3) [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] was also used to find differentially abundant genera between conditions on each day and between each pair of phases (early after \u003cem\u003eversus\u003c/em\u003e before infection, late after \u003cem\u003eversus\u003c/em\u003e before infection, and late \u003cem\u003eversus\u003c/em\u003e early after infection). The unrarefied features table was used as input to ANCOM-BC as per the standard recommendations.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests:\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003ePC and FO conceived the study and designed the experiments. KT, PC, LAR, LW, EI, and FO performed the experiments and analyzed the data. YZ did the metagenomics analysis. CM reared the sand flies. JGV, and FO assured the funding. SK, and JGV contributed with reagents, materials, analysis tools. PC and KT wrote the original draft. All authors critically discussed the results, and revised, edited, and approved the manuscript.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eThis research was supported by the Intramural Research Program of the National Institutes of Health (NIH). The contributions of the NIH author(s) were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements, and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003ePC and FO conceived the study and designed the experiments. KT, PC, LAR, LW, EI, and FO performed the experiments and analyzed the data. YZ did the metagenomics analysis. CM reared the sand flies. JGV, and FO assured the funding. SK, and JGV contributed with reagents, materials, analysis tools. PC and KT wrote the original draft. All authors critically discussed the results, and revised, edited, and approved the manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe datasets analyzed within the current study have been deposited in the NCBI GeneBank database, under the BioProject number PRJNA1079352 ( https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1079352/con ); only CTRL samples are relevant to this study. The analysis script is available at GitHub (https://github.com/GaryZhangYue/Tang_2025_Sandfly_Gut_Microbiota_16S ).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCecilio P, Cordeiro-da-Silva A, Oliveira F: \u003cstrong\u003eSand flies: Basic information on the vectors of leishmaniasis and their interactions with Leishmania parasites.\u003c/strong\u003e \u003cem\u003eCommun Biol \u003c/em\u003e2022, \u003cstrong\u003e5:\u003c/strong\u003e305.\u003c/li\u003e\n\u003cli\u003eOkwor I, Uzonna J: \u003cstrong\u003eSocial and Economic Burden of Human Leishmaniasis.\u003c/strong\u003e \u003cem\u003eAm J Trop Med Hyg \u003c/em\u003e2016, \u003cstrong\u003e94:\u003c/strong\u003e489-493.\u003c/li\u003e\n\u003cli\u003eScheufele CJ, Giesey RL, Delost GR: \u003cstrong\u003eThe global, regional, and national burden of leishmaniasis: An ecologic analysis from the Global Burden of Disease Study 1990-2017.\u003c/strong\u003e \u003cem\u003eJ Am Acad Dermatol \u003c/em\u003e2021, \u003cstrong\u003e84:\u003c/strong\u003e1203-1205.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eWHO Leishmaniasis Fact Sheet \u003c/strong\u003e[https://www.who.int/news-room/fact-sheets/detail/leishmaniasis]\u003c/li\u003e\n\u003cli\u003eCec\u0026iacute;lio P, Oliveira F, Cordeiro da Silva A: \u003cstrong\u003eVaccines for Human Leishmaniasis: Where Do We Stand and What Is Still Missing?\u003c/strong\u003e In \u003cem\u003eLeishmaniases as Re-emerging Diseases.\u003c/em\u003e Edited by Farhat A, Hassan H. 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\u003cstrong\u003e11:\u003c/strong\u003e3514.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Sand fly, Leishmania infection, gut microbiota, relative abundance, diversity","lastPublishedDoi":"10.21203/rs.3.rs-7384237/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7384237/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe manipulation of the gut microbiota of disease vectors has emerged as a new approach to use in the integrated control of vector-borne diseases. For this purpose, a deep knowledge of the gut microbial communities of disease vectors is essential. However, while for some vectors, including mosquitoes, such characterization has been extensive, for others, including some sand fly species, there is limited data available. To our knowledge, to date, no study has documented the gut microbiome dynamics of \u003cem\u003ePhlebotomus duboscqi\u003c/em\u003e sand flies over the entire time-period required for the maturation of a \u003cem\u003eLeishmania\u003c/em\u003e infection. To address this limitation, here, we looked at the differences of the gut microbiome of laboratory-reared \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies both before, and after infection with \u003cem\u003eLeishmania major\u003c/em\u003e parasites, with the necessary temporal resolution to understand the dynamics of sand fly gut microbial communities in the context of \u003cem\u003eLeishmania\u003c/em\u003e infection.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe observed a decrease in the number of Amplicon Sequence Variants (ASVs) at two key time points: a significant decrease early after infection (Day 2), and a trend toward reduction at late after infection (Day 12). These results were accompanied by noticeable changes in the relative abundance of multiple bacterial families and respective genera with the progression of \u003cem\u003eLeishmania\u003c/em\u003e infection in the sand fly midgut, with e.g. \u003cem\u003eSphingomonas\u003c/em\u003e, \u003cem\u003eOchrobactrum\u003c/em\u003e, and \u003cem\u003eSerratia\u003c/em\u003e as the most prevalent genera detected, before, early after, and late after infection, respectively. While these results did not overall translate into significant differences in alpha diversity metrics, they did lead to a separation between the 3 groups in the context of a beta diversity analysis, with statistical relevance. Importantly, via an ANCOM-BC analysis we were able to establish \u003cem\u003eCorynebacterium\u003c/em\u003e spp. and \u003cem\u003eEnterococcus\u003c/em\u003e spp. as potential markers of non-infected and infected sand flies, respectively, as well as \u003cem\u003eStreptococcus\u003c/em\u003e spp., \u003cem\u003eSphingomonas\u003c/em\u003e spp., \u003cem\u003eRalstonia\u003c/em\u003e spp., and \u003cem\u003eAbiotrophia\u003c/em\u003e spp. as potential specific markers of late infections.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOverall, we show that the composition of the gut microbiota of \u003cem\u003eP. duboscqi\u003c/em\u003e sand flies changes significantly over the course of an infection with \u003cem\u003eL. major\u003c/em\u003e parasites.\u003c/p\u003e","manuscriptTitle":"Phlebotomus duboscqi gut microbiota dynamics in the context of Leishmania infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-22 06:25:25","doi":"10.21203/rs.3.rs-7384237/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b4ed73db-c380-46f7-abbd-e4860828a3b3","owner":[],"postedDate":"August 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-04T09:23:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-22 06:25:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7384237","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7384237","identity":"rs-7384237","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}