Gut microbiota response to Enterocytozoon bieneusi infection: enhanced vitamin B and K 2 pathways

Gut microbiota response to Enterocytozoon bieneusi infection: enhanced vitamin B and K 2 pathways | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Gut microbiota response to Enterocytozoon bieneusi infection: enhanced vitamin B and K 2 pathways Xiao-Xuan Zhang, He Zhang, Ji-Xin Zhao, Hai-Long Yu, Chun-Ren Wang, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7835059/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Feb, 2026 Read the published version in BMC Genomics → Version 1 posted 14 You are reading this latest preprint version Abstract Enterocytozoon bieneusi ( E. bieneusi ) is a highly pathogenic parasite that infects immunocompromised individuals, especially HIV patients, and is a leading cause of diarrhea in these populations. It significantly impacts human health, causing severe gastrointestinal symptoms, malnutrition, and potentially life-threatening complications. However, the microbial mechanisms behind E. bieneusi infection and its effects on host nutrition are not well understood. Wild rodents have long been considered a valuable model for studying human diseases due to their similar gut microbiota dynamics and immune responses to humans, making them particularly relevant for investigating parasitic infections. Here, we assembled a comprehensive catalog of 9,929 non-redundant micr obial genomes from wild rodent gut metagenomes and evaluated their potential for B vitamin and vitamin K 2 biosynthesis using comparative functional genomics. We identified 2,307 genomes encoding complete pathways for de novo biosynthesis of at least one essential vitamin, though no single genome encoded all pathways, indicating a distributed metabolic capacity within the microbial community. Infection with E. bieneusi significantly altered the microbial composition and the potential for vitamin biosynthesis, with a notable expansion of Methanobacteriota and reprogramming of pyridoxine (vitamin B 6 ) biosynthesis pathways. These changes reveal a functional shift in microbial metabolism in response to parasitic pressure. By elucidating the microbial basis of vitamin biosynthesis in wild rodents and the impact of E. bieneusi infection on microbial functions, this study offers new insights into the role of gut microbiota in maintaining host health and nutrient provisioning under parasitic stress. Moreover, the findings will also provide valuable insights into prevention and control of E. bieneusi infection in a variety of host, including humans. Enterocytozoon bieneusi Wild Rodents Gut Microbiota Host-Microbe Interactions Vitamin Synthesis Comparative Genomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Enterocytozoon bieneusi ( E. bieneusi ) is eukaryotic parasites that opportunistically infect immunocompromised individuals, particularly HIV-infected patients, becoming one of the main causes of diarrhea in these individuals[ 1 ]. A recent meta-analysis estimated the overall prevalence of E. bieneusi infection in humans at 7.9%, but with significant variation depending on the presence of digestive symptoms and immune status[ 2 ]. A study conducted in the Czech Republic in 2007 reported a seroprevalence of 19% for E. bieneusi. Among HIV-positive patients, the seroprevalence was 20%, while in populations with reported animal contact, the rate reached 33%[ 3 ]. The gut microbiome of wild rodents exhibits diversity and dynamic changes similar to those of humans, influenced by social interactions and environmental pressures, making them a valuable model for studying human diseases[ 4 , 5 ]. Therefore, understanding the gut microbiome of wild rodents provides valuable insights for the prevention and control of human E. bieneusi . Previous studies have demonstrated that gut microbiota can synthesize substantial proportions of the host's B vitamin requirements, with vitamin K 2 being almost exclusively microbial in origin [ 6 , 7 ]. This microbial contribution is particularly important in wild animals, such as rodents, which do not receive dietary vitamin supplementation and depend largely on their gut microbiota for micronutrient acquisition [ 8 , 9 ]. Wild rodents, inhabiting diverse ecological niches and feeding on variable natural diets [ 8 , 10 , 11 ], represent an ecologically relevant model for studying microbiota-driven nutrient synthesis under fluctuating environmental conditions. However, the functionality of this microbial ecosystem can be disrupted by pathogenic infections, with potential consequences for host nutrient acquisition. E. bieneusi , an obligate intracellular parasite of the phylum Microsporidia, frequently infects the intestinal epithelium of wild rodents and other mammals, including humans [ 12 ]. It is associated with impaired gut barrier integrity, dysbiosis, and reduced nutrient absorption [ 13 , 14 ]. Although E. bieneusi is widely present and poses a zoonotic risk [ 15 , 16 ], the impact of E. bieneusi infection on the gut microbiota’s functional role—particularly in the biosynthesis of B vitamins and vitamin K—remains poorly characterized. This gap is concerning given that micronutrient deficiencies can exacerbate infection severity, compromise host survival, and affect reproductive fitness—factors with important implications for both ecological dynamics and public health. To address this knowledge gap, we investigate how gut microbial communities contribute to vitamin biosynthesis in wild rodents under both healthy and pathogen-challenged conditions. In this study, we aim to systematically characterize the capacity of the wild rodent gut microbiota to synthesize B vitamins and vitamin K 2 and to assess how this functional potential is altered during E. bieneusi infection. By leveraging a comprehensive metagenomic dataset comprising 17,137 microbial genomes and integrating taxonomic and functional analyses, we provide new insights into the ecological and metabolic resilience of wild rodent microbiomes. This work advances our understanding of environmentally shaped microbiome functionality and highlights the metabolic vulnerabilities introduced by parasitic perturbation, providing insights that are relevant to ecosystem health, wildlife conservation, and zoonotic disease management. Methods Metagenome assembly and taxonomic classification of wild rodent gut genomes A total of 17,137 wild rodent gut genomes were retrieved from the Figshare repository ( https://doi.org/10.6084/m9.figshare.28752050 ). Taxonomic classification was performed using the GTDB-Tk v2.3.2 classify_wf workflow [ 17 ], based on the Genome Taxonomy Database (GTDB). To remove redundancy, strain-level de-duplication at 99% average nucleotide identity (ANI) was performed using dRep v3.4.3 [ 18 ] with the parameters ‘-pa 0.9 -sa 0.99 -nc 0.30 -cm larger --S_algorithm fastANI,’ resulting in 9,929 unique genomes. To further resolve species-level diversity, ANI was re-estimated among genomes sharing identical genus-level taxonomic classifications using dRep (v3.4.3) with the parameters ‘-pa 0.9 -sa 0.95 -nc 0.30 -cm larger --S_algorithm fastANI’. This analysis identified 5,312 species-level genome bins (SGBs). The phylogenetic tree generated by GTDB-Tk was visualized using iTOL v6.9.1 ( https://itol.embl.de/ ). Functional analysis of vitamin-related microbial gene catalog Open reading frames (ORFs) were predicted from 9,929 genomes using Prodigal v2.6.3 [ 19 ] with the parameter '-p single'. The resulting ORFs were clustered using MMseqs easy-cluster workflows [ 20 ] with the parameters: ‘--split-mode 2 --cov-mode 2 -c 0.9 --min-seq-id 0.95 --cluster-mode 2 --cluster-reassign 1’. This resulted in a non-redundant microbial gene catalog containing 260,273 genes, with redundancy reduced by clustering sequences sharing > 95% identity to ensure a unique representation of microbial gene diversity. Functional annotation was performed by comparing the clustered genes to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database using DIAMOND v2.1.8.162 (15) with the following parameters: ‘--min-score 60 --query-cover 70 --max-target-seqs 5 --masking 1.’ For each gene, the alignment with the highest bit score was used for functional classification. Functional roles were defined as specific biological functions associated with KEGG gene categories, with a particular focus on those involved in the biosynthesis of B vitamins and menaquinone. These roles were identified based on KEGG annotations to ensure accurate classification of genes involved in key metabolic pathways. Phylogenetic, taxonomic, and functional analyses of 3,522 high-quality genomes To ensure data quality, all 17,137 genomes were re-evaluated using CheckM2 v1.0.1 [ 21 ], and only genomes with ≥ 90% completeness and < 5% contamination were retained. Strain-level de-redundancy at 99% ANI was performed using dRep v3.4.5 with the parameters ‘-pa 0.9 -sa 0.99 -nc 0.30 -cm larger --S_algorithm fastANI,’ resulting in 3,522 high-quality, non-redundant genomes. Functional annotation was conducted using DIAMOND v2.1.8.162 via BLASTP searches against the KEGG database. We defined a set of essential functional roles required for a genome to be considered as a de novo producer of vitamins B and menaquinone. Based on these criteria, 2,307 genomes were predicted to possess the capability to synthesize vitamin B and menaquinone de novo . Effects of infection on the gut microbiota Effects of E. bieneusi infection on the gut microbiota We reanalyzed metagenomic data from project PRJNA1175865, which comprises 20 gut metagenomic samples from wild rodents. As described in our previous study [ 22 ], the dataset includes 10 control (CON) and 10 E. bieneusi -infected samples. To ensure high data quality, raw reads were processed using fastp v0.23.0 [ 23 ] with the following parameters ‘-u 30 -n 5 -q 20 -y -Y 30 -l 80 --trim_poly_g’. Host-derived sequences were removed by aligning the quality-filtered reads to the rodent reference genome (NCBI RefSeq assembly: GCF_036323735.1) using Bowtie2 v2.5.0 [ 24 ]. The resulting clean reads were retained for downstream analyses. For functional profiling, clean reads were aligned to a non-redundant microbial gene catalog using Bowtie2 v2.5.0. as a reference, we assigned metagenomic reads to the respective groups with Bowtie2 v2.5.0. Read counts were normalized to transcripts per million (TPM), and the relative abundances of KEGG orthologs (KOs) were calculated. For taxonomic profiling, total abundance was determined by summing the abundances of all genes assigned to each taxonomic unit. Functional roles related to vitamin biosynthesis were defined based on KO annotations, and their relative abundances were calculated by summing the TPM values of associated genes. Statistical analyses and visualization Statistical analyses were conducted using R version 4.2.2. Alpha diversity metrices, including Shannon diversity and richness indices, were calculated for each sample based on both taxonomic and functional gene abundance data. Beta diversity was evaluated using Principal Coordinate Analysis (PCoA) based on Bray-Curtis dissimilarity, with group differences evaluated using permutational multivariate analysis of variance (PERMANOVA). The Wilcoxon rank-sum test was applied to identify significant differences in diversity indices and the relative abundance of taxa and functional features between groups. Rarefaction curves were generated using the ‘vegan’ package (v2.6-4). Chord diagrams were generated with the ‘circlize’ package (v2.8.0), and Sankey plots were constructed using ‘networkD3’ (v4.2.3). Network graphs were visualized using Gephi (v0.10.1). Additional plots were generated using the ‘ggplot2’ package in R. Results Construction and taxonomic profiling of a wild rodent gut microbiome genome catalog To characterize the gut microbiota of wild rodents, we constructed a bacterial genome catalog by integrating 17,137 publicly available genomes, including 16,856 metagenome-assembled genomes (MAGs) and 281 genomes from cultured isolates. Genomes were filtered based on quality criteria (≥ 50% completeness, < 5% contamination, and [completeness – (5 × contamination)] ≥ 50) and dereplicated at a 99% ANI threshold. This process yielded 9,929 non-redundant genomes for downstream analysis (Supplementary Table 1). These genomes ranged in size from 0.26 Mb to 9.54 Mb (mean: 2.15 Mb), with an average N50 of 55,631 bp, 82.77% completeness, and 1.18% contamination (Fig. 1 B-C). Interestingly, 3,522 genomes met high-quality standards (completeness ≥ 90%, contamination < 5%), providing a robust dataset for investigating microbial functional diversity. To assess species-level diversity, we clustered the genomes at a 95% ANI threshold, resulting in 5,312 species-level genome bins (SGBs). These genomes had an average GC content of 48.54% (range: 22.21%–73.68%) and contained, on average, 2,074 ORFs per genome (range: 400–8,705). Taxonomic classification using GTDB-Tk database assigned the genomes to 24 phyla, 31 classes, 78 orders, 164 families, and 712 genera. At the phylum level, Bacillota_A ( n = 2,731) and Bacteroidota ( n = 1,312) were most abundant, followed by Bacillota ( n = 354), Actinomycetota ( n = 241), and Pseudomonadota ( n = 195). At the family level, Lachnospiraceae ( n = 1,069) and Muribaculaceae ( n = 862) were most common, followed by Ruminococcaceae (n = 393), Oscillospiraceae ( n = 358), and Acutalibacteraceae ( n = 236) (Figure. 1A). Together, these genomes form a high-resolution reference dataset for exploring microbial diversity and function in wild rodents, including the genomic basis for traits such as vitamin biosynthesis that may contribute to host adaptation in dynamic environments. Identification and characterization of vitamin synthesis genes in the wild rodent gut microbiome Using the 9,929 high-quality genomes described above, we investigated the potential for vitamin synthesis within the wild rodent gut microbiota. Protein-coding genes from these genomes were annotated against the KEGG database to assess their functional roles. In total, 464,312 genes corresponding to 199 KOs were identified as being involved in the biosynthesis of eight vitamin B compounds (biotin, cobalamin, folate, niacin, pantothenic acid, pyridoxine, riboflavin, and thiamine) as well as menaquinone (Supplementary Table 2). To reduce redundancy, these genes were clustered using MMseqs, resulting in a non-redundant catalog of 260,273 genes with an average length of 895 bp. This catalog offers a valuable resource for functional classification and exploration of gut microbiota-mediated vitamin synthesis in wild rodents. Further pathway analysis based on this gene set revealed that all eight vitamin B compounds are synthesized directly by the gut microbiota, whereas menaquinone synthesis proceeds via indirect microbial pathways (Supplementary Fig. 1–3). These findings highlight the significant metabolic contributions of the gut microbiome to host vitamin availability. The presence of diverse and complete biosynthetic pathways across multiple taxa underscores a distributed metabolic architecture that may help sustain micronutrient levels in the host, particularly under nutrient-limited conditions. Host-specific genomic potential for de novo vitamin biosynthesis in gut microbiomes Building upon the curated gene sets for vitamin synthesis, we investigated the genome-level potential for de novo synthesis of B vitamins and menaquinone in the gut microbiome of wild rodents. From the 9,929 high-quality MAGs, we selected 3,522 with ≥ 90% completeness and < 5% contamination for downstream analysis (Supplementary Table 3). Functional annotation revealed that 2,307 genomes encoded complete pathways for synthesizing at least one B vitamin or menaquinone (Fig. 2 A and Supplementary Table 4), signifying widespread but uneven biosynthetic potential across the microbiome. These genomes exhibited broad genomic diversity, with sizes ranging from 0.97 to 9.54 Mbp (mean = 2.64 Mbp), average N50 of 103,843 bp, and GC content spanning 26.58% to 73.42% (mean = 48.19%) (Fig. 2 B-C). Taxonomic analysis showed that Bacteroidota (37.06%,, 855 genomes) and Bacillota_A (36.11%, 833 genomes) predominated among vitamin-producing genomes, followed by Bacillota (6.07%, 140 genomes), Desulfobacterota (5.21%, 118 genomes), and Pseudomonadota (3.80%, 90 genomes). This taxonomic distribution highlights key bacterial lineages contributing to gut-derived micronutrient synthesis in wild rodents. Functional analysis of vitamin synthesis capabilities revealed that 961 genomes encoded the capacity to synthesize a single vitamin, while 1,314 were capable of producing 2 to 6 vitamins. Interestingly, 32 genomes were equipped to produce 7 or 8 vitamins, but none harbored complete biosynthetic pathways for all nine, underscoring the metabolic interdependence among microbial taxa and the likely necessity of cross-feeding in vitamin provisioning (Fig. 2 D and Supplementary Table 4 ) . Among the biosynthetic targets, the most commonly encoded pathways were for niacin (1,664 genomes), riboflavin (1,106), and pyridoxine (713), with fewer genomes able to synthesize pantothenate, folate, biotin, thiamine, and cobalamin (Fig. 2 E). The distribution of biosynthetic capacity was taxon-specific. Bacteroidota and Bacillota_A were the dominant phyla facilitating vitamin biosynthesis in wild rodents. Niacin, riboflavin, pyridoxine, and pantothenate were primarily synthesized by Bacteroidota (44.83%, 48.10%, 17.95%, and 25.45%, respectively) and Bacillota_A (35.52%, 25.86%, 32.96%, and 25.45%, respectively). Folate synthesis was mostly mediated by Bacteroidota (38.76%) and Pseudomonadota (23.17%). Biotin synthesis was mainly supported by Pseudomonadota (38.17%) and Campylobacterota (16.67%). Menaquinone synthesis was dominated by Desulfobacterota (45.33%) and Campylobacterota (31.33%). Thiamine synthesis was chiefly attributed to Bacillota_A (32.77%) and Bacillota (21.85%). Cobalamin synthesis was more evenly split between Bacillota (19.66%) and Pseudomonadota (19.66%) (Fig. 2 F). To explore whether this biosynthetic landscape was conserved across host species, we extended our analysis to 1,707 MAGs from the laboratory mouse gut microbiome (CMMG). Comparative profiling revealed distinct host-specific taxonomic patterns in vitamin synthesis. In cats, the predominant contributors were Bacillota_A (40.54%) and Actinobacteria (20.84%), whereas in ruminants, Bacteroidota (43.28%) and Bacillota (38.25%) were most prominent. In chickens, vitamin synthesis was primarily associated with Bacteroidota (28.21%) and Bacillota_A (25.66%). Although Bacteroidota and Bacillota_A were dominant in both wild rodents and laboratory mice, their relative contributions shifted— Bacteroidota led in wild rodents (37.06%), while Bacillota_A dominated in laboratory mice (52.9%) (Supplementary Fig. 4). These host-specific microbial vitamin profiles underscore variation in the taxonomic architecture of vitamin biosynthesis, reflecting differences in gut microbial composition between species. Impact of E. bieneusi infection on vitamin synthesis by the gut microbiota in wild rodents Having established the capacity of wild rodent gut microbiota for de novo vitamin biosynthesis, we next investigated how E. bieneusi infection alters this functional potential. Although gut microbes are central to host vitamin metabolism, the effects of parasitic infection on microbial vitamin-producing capacity remain poorly characterized. To address this, we reanalyzed gut metagenomic data from infected and uninfected rodents, focusing on genomes annotated with vitamin biosynthetic pathways. Rarefaction analysis confirmed sufficient sequencing depth to capture the diversity of vitamin-producing genomes, with cumulative curves reaching saturation (Fig. 3 A). Alpha diversity analysis revealed a significant increase in the richness of vitamin-synthesizing genomes in infected rodents, indicating enhanced within-sample diversity post-infection (Fig. 3 B–C). Beta diversity assessed via principal coordinates analysis (PCoA) explained 43.48% of the variation across the first two axes. Although a shift in community composition was observed between infected and uninfected groups, this difference did not reach statistical significance (PERMANOVA: R² = 0.0894, p = 0.075) (Fig. 3 D). To identify specific taxa driving these changes, we conducted a differential abundance analysis of vitamin-producing phyla. Importantly, Methanobacteriota showed a significant increase in relative abundance following E. bieneusi infection (Fig. 3 E and Supplementary Fig. 5), while other phyla remained stable. Interestingly, Methanobacteriota contributed exclusively to pyridoxine (vitamin B 6 ) synthesis and was not implicated in the biosynthesis of any of the other eight vitamins, suggesting a targeted functional enrichment. These findings indicate that E. bieneusi infection selectively enriches microbial taxa involved in specific vitamin biosynthetic pathways, particularly pyridoxine. This functional shift implies a potential microbial adaptation to parasitic stress, wherein vitamin B 6 production may confer a survival or ecological advantage within the altered gut environment. Pyridoxine biosynthesis and its modulation by E. bieneusi infection in wild rodent gut microbiota As part of our broader investigation into gut microbial vitamin production, we focused on pyridoxine, a coenzyme essential for amino acid metabolism, immune regulation, neurotransmitter synthesis, and environmental stress adaptation. Pyridoxine is synthesized by the gut microbiota and can, in turn, shape microbial community structure and function. We examined how E. bieneusi infection influences the genetic capacity for pyridoxine biosynthesis in the wild rodent gut. We identified two pyridoxine biosynthetic routes within the gut microbiota: a direct pathway catalyzed by pyridoxine 5′-phosphate synthase (involving Pdx proteins), and an alternative route using 4-hydroxy-L-threonine (4-HTL) as a precursor. Both pathways were constrained by the low abundance of the gene epd , which encodes erythrose-4-phosphate dehydrogenase, a key enzyme required for the biosynthesis of vitamin B6. Despite this bottleneck, E. bieneusi infection led to a moderate increase in the relative abundance of several pyridoxine-related genes, including serC , thrC , and pdxK . Core biosynthetic genes ( pdxD , pdxA , pdxJ ) were predominantly associated with the phylum Bacillota_A , whereas epd was enriched in Pseudomonadota . Auxiliary precursor-synthesis genes were largely contributed by Bacteroidota (Fig. 4 ). These data reveal a phylum-specific distribution of pyridoxine biosynthesis genes in the wild rodent gut microbiota. Following E. bieneusi infection, an increase in key biosynthetic genes suggests altered functional potential in vitamin B6 synthesis. Discussion This study presents a comprehensive genomic and functional analysis of the gut microbiome in wild rodents, emphasizing its critical role in vitamin biosynthesis and the modulatory effects of E. bieneusi infection on microbial community structure and metabolic function. A key novel finding is the significant enrichment of pyridoxine (vitamin B 6 ), producing Methanobacteriota in infected hosts, unveiling an adaptive microbial response to parasitic stress that has not been previously documented. By integrating publicly available datasets and implementing rigorous quality control measures, we assembled a curated collection of 9,929 high-quality bacterial genomes, providing a robust framework for future investigations into microbiome-mediated host–parasite interactions, functional diversity, and adaptations in fluctuating environments. Our study reveals a remarkable taxonomic richness within the wild rodent gut microbiota, comprising 5,312 SGBs across 24 bacterial phyla, underscoring the complexity of host-microbiome interactions in natural environments. The dominance of Bacillota_A and Bacteroidota aligns with their well-established roles in fiber degradation [ 25 ] and energy harvesting [ 26 ]. However, our data provide new insights into their relative contributions under wild dietary regimes. Importantly, members of Lachnospiraceae and Muribaculaceae emerge as important taxa critical for maintaining gut homeostasis through short-chain fatty acid (SCFA) production— metabolites fundamental for host energy balance and immune regulation [ 27 , 28 ]. With 712 genera identified, this microbial consortium exhibits multifaceted functionality, mediating nutrient metabolism, immunomodulation, and environmental adaptability [ 29 , 30 ]. Our findings highlight how such extensive microbial diversity equips wild rodents with a dynamic gut ecosystem capable of responding to fluctuating dietary inputs and ecological pressures, thereby shaping host physiology and resilience in natural habitats [ 9 , 31 – 33 ]. Our study reveals that the wild rodent gut microbiome possesses extensive metabolic potential to support host vitamin nutrition, underscoring its functional importance beyond digestion. Functional annotation of 464,312 protein-coding genes identified 199 KOs involved in the biosynthesis of essential vitamins—including all eight B vitamins (biotin, cobalamin, folate, niacin, pantothenic acid, pyridoxine, riboflavin, and thiamine) as well as vitamin K₂. This comprehensive repertoire reflects a metabolically versatile microbiome capable of supplementing host micronutrient requirements, potentially alleviating dependence on dietary vitamin intake [ 34 ]. The detection of menaquinone synthesis pathways suggests complex syntrophic and cross-feeding interactions within the microbial community—ecological dynamics that enhance nutrient accessibility and stabilize microbial consortia [ 35 ]. These cooperative interactions exemplify the microbiome’s contribution to host metabolic homeostasis, immune development, and resilience [ 36 , 37 ]. Moreover, the observed inter-individual variation in vitamin biosynthesis capacity may modulate host fitness and disease susceptibility under differing environmental or nutritional pressures [ 38 , 39 ]. The identification of diverse microbial vitamin biosynthesis pathways underscores the evolutionary co-adaptation of the gut microbiome to the host’s diet and ecological niche [ 31 , 40 ]. Wild rodents, whose diets are predominantly plant-based and often low in bioavailable vitamins, face significant micronutrient constraints. Our findings suggest that the gut microbiota has functionally adapted to offset these limitations, providing a complementary source of essential vitamins and thereby reinforcing a mutualistic, co-evolved relationship with the host [ 41 ]. This microbial compensation likely reflects long-term selective pressures favoring hosts with microbiomes capable of nutrient provisioning under fluctuating dietary conditions. Such functional plasticity may enhance host survival and fitness in resource-variable environments, positioning the microbiome as a key adaptive partner in the evolutionary trajectory of wild rodents. Our analysis of de novo vitamin biosynthesis in the wild rodent gut microbiome reveals a complex, distributed metabolic architecture involving diverse microbial taxa and cooperative synthesis strategies. Rather than relying on a single dominant species, vitamin production is partitioned across multiple microbial contributors—each encoding different components of biosynthetic pathways. This decentralized, community-level organization, not previously described in wild rodent systems [ 42 ], highlights the microbiome’s functional integration and its critical role in sustaining host vitamin homeostasis [ 6 ]. While dominant taxa orchestrate core biosynthetic processes, less-abundant phyla, such as Desulfobacterota and Pseudomonadota , play secondary roles, enhancing overall pathway completeness, metabolic flexibility, and niche specialization [ 43 , 44 ]. This functional redundancy likely confers resilience to the system, enabling wild rodents to maintain micronutrient sufficiency even under dietary or environmental stress. A critical insight from this study is that no single microbial genome within the gut microbiome encodes the complete biosynthetic machinery for all nine essential vitamins. Instead, vitamin synthesis is a cooperative function—shared among taxonomically and functionally diverse microbes. This underscores the gut microbiome’s role as an integrated metabolic network rather than a sum of isolated organisms [ 45 ]. Such interdependent biosynthesis networks suggest that evolutionary selection has favored microbial consortia capable of buffering the host against nutrient variability. However, this dependency also implies vulnerability: disruptions from dietary shifts, environmental stressors, or disease may destabilize cooperative functions, potentially leading to vitamin deficiencies [ 46 , 47 ]. Understanding these microbial interdependencies is therefore crucial for predicting host resilience and guiding future interventions to preserve microbiome-mediated nutrition under ecological change. Our comparative analysis of gut microbiomes across diverse host species—including wild rodents, laboratory mice, cats, ruminants, and chickens—reveals striking host-specific patterns in microbial vitamin biosynthesis. In wild rodents, Bacteroidota emerged as the dominant contributor to vitamin pathways, whereas Bacillota_A predominated in carnivorous hosts such as cats, reflecting the influence of host diet, gut morphology, and microbial adaptation to distinct ecological niches [ 48 ]. We observed marked divergence between the microbiomes of wild rodents and laboratory mice, particularly in the relative abundance and biosynthetic contributions of Bacillota_A . These differences raise important questions about the extent to which domestication, controlled housing conditions, and standardized diets shape microbiome composition and functional capacity [ 49 ]. The reduced ecological and dietary complexity in laboratory settings likely narrows microbial diversity and metabolic flexibility, with implications for host physiology and experimental outcomes. Our findings challenge the assumption that laboratory rodents adequately model natural host–microbiome dynamics. The metabolically versatile microbiomes of wild rodents, shaped by exposure to diverse environments and variable diets, may better reflect the adaptive potential of host-associated microbial communities [ 50 , 51 ]. Incorporating wild-derived microbiome data into experimental frameworks could enhance the ecological validity and translational relevance of studies in nutrition, immunity, and disease modeling. One of the most interesting findings from our study is the infection-induced enrichment of Methanobacteriota species with the genetic potential to synthesize pyridoxine. This observation not only uncovers a novel dimension of microbial functional resilience under parasitic stress but also suggests that the microbiota may engage in compensatory nutrient provisioning to mitigate the impact of infection on host health. Building on our characterization of the healthy microbiome's metabolic potential, we investigated how E. bieneusi infection perturbs these dynamics. E. bieneusi is known to disrupt intestinal barrier integrity, altering nutrient absorption and immune status—particularly in immunocompromised or juvenile hosts [ 52 , 53 ]. These physiological disruptions may impose selective pressures on the gut microbiota, potentially leading to shifts in both community structure and function. Our results reveal that E. bieneusi infection leads to a reorganization of microbial metabolic pathways, including altered vitamin biosynthesis and reduced microbial diversity. Despite this disturbance, the enrichment of certain taxa with vitamin-synthesizing capabilities—such as Methanobacteriota —suggests a compensatory mechanism aimed at preserving host-microbe homeostasis. These findings contribute new insights into how parasitic infections can induce functional reprogramming within the microbiome, with potential implications for host resilience and recovery [ 54 ]. An unexpected and counterintuitive observation from our study was the increase in microbial diversity following E. bieneusi infection, as indicated by elevated Shannon diversity and species richness indices. This pattern may reflect an adaptive restructuring of the gut microbiota to sustain homeostasis under stress or, alternatively, an opportunistic expansion of taxa that thrive under altered gut conditions [ 55 , 56 ]. Despite this increase in diversity, the overall microbial community structure remained statistically stable, as confirmed by PERMANOVA analysis, suggesting that infection does not induce broad taxonomic disruption but instead drives more subtle functional reprogramming. Most importantly, E. bieneusi infection induced a significant increase in the number of microbial genomes encoding vitamin biosynthesis pathways, particularly those associated with pyridoxine. This shift was linked to an increased abundance of Methanobacteriota , marking the first evidence that E. bieneusi infection enriches gut microbial populations capable of synthesizing vitamin B 6 —revealing a novel, infection-induced functional adaptation [ 57 ]. Further analysis uncovered two distinct pyridoxine biosynthesis pathways (via Pdx proteins and 4-hydroxythreonine-4-phosphate dehydrogenase, 4-HTL), underscoring the metabolic versatility of the microbial community [ 58 ]. However, the observed limitation in epd gene abundance may constrain total pyridoxine production, suggesting partial—but not complete—compensatory capacity. Importantly, post-infection upregulation of key pyridoxine biosynthesis genes ( serC , thrC , pdxK ) suggests a targeted microbial response aimed at sustaining host immune function under parasitic stress [ 59 ]. This functional resilience, despite relatively stable community composition, provides compelling evidence for E. bieneusi -driven metabolic reprogramming within the gut microbiome. These adaptations may represent a microbiota-mediated buffering mechanism to preserve host-microbe equilibrium or, conversely, an opportunistic metabolic shift that facilitates parasite infection [ 60 ]. These findings highlight the dynamic nature of host-microbe-parasite interactions and underscore the potential for microbiota-targeted strategies to enhance infection resilience and support nutrient homeostasis during enteric parasitic challenges. Conclusions In summary, this study presents a high-resolution genomic framework that reveals the complex taxonomic and functional architecture of wild rodent gut microbiomes. By uncovering the dynamic capacity of these microbial communities to adapt metabolically—particularly through the reprogramming of vitamin biosynthesis pathways in response to parasitic infection—we highlight the microbiome’s critical role in maintaining host physiological balance under ecological and pathogenic stress. The infection-induced upregulation of pyridoxine synthesis exemplifies the functional resilience and cooperative potential of the gut microbiota, offering new insights into host–microbe co-adaptation. Importantly, our findings extend beyond ecological microbiology by offering a reference point for evaluating microbiome responses in natural versus controlled environments. They underscore the translational relevance of wild microbiome models for improving our understanding of microbial contributions to health, immunity, and disease tolerance. While further validation is needed, the functional adaptations observed here provide conceptual frameworks for understanding microbiome resilience and nutrient provisioning during infection. Declarations Ethics approval and consent to participate Not applicable Clinical trial number Not applicable Consent for publication Not applicable. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 32170538), the National Key R&D Program of China (2022YFF0710503), the Natural Science Foundation of Heilongjiang Province (ZD2022C006), and the Horizontal Project of Qingdao Agricultural University (Grant No. 667/2424025). Author Contribution Xiao-Xuan Zhang: Conceptualization, Funding acquisition, Resources, Supervision, Writing-original draft. He Zhang: Funding acquisition, Writing-review and editing. Ji-Xin Zhao: Data curation, Software, Writing-review and editing. Hai-Long Yu: Software, Writing-original draft. Chun-Ren Wang: Funding acquisition, Writing-review and editing. Kai-Meng Shang: Resources, Formal analysis, Visualization, Writing-review and editing. Yong-Jie Wei: Formal analysis, Visualization, Writing-review and editing. Ya Qin: Resources, Writing-review and editing. Jian-Ming Li: Resources, Writing-review and editing. Zi-Yu Zhao: Resources, Writing-review and editing. Chang-You Xia: Conceptualization, Project administration, Writing-review and editing. Bei-Ni Chen: Conceptualization, Supervision, Writing-review and editing. Hany M. Elsheikha: Conceptualization, Validation, Writing-original draft. He Ma: Conceptualization, Funding acquisition, Supervision, Methodology, Writing-review and editing. All authors reviewed the manuscript. Acknowledgements Not applicable Data Availability The wild gut microbial genomes used in this study are obtained in the Figshare repository(https://doi.org/10.6084/m9.figshare.28752050). The metagenomic sample analyzed in this study are available under accession numbers PRJNA117586, which were published in our previous study. References Chozas M, Dashti A, Prieto-Pérez L, Pérez-Tanoira R, Cobo E, Bailo B, Del Palacio M, Hernández-Castro C, González-Barrio D, Carmena D et al. Enterocytozoon bieneusi and Encephalitozoon intestinalis (microsporidia) in HIV-positive patients in central Spain. Med Mycol 2023, 61(4). Ruan Y, Xu X, He Q, Li L, Guo J, Bao J, Pan G, Li T, Zhou Z. The largest meta-analysis on the global prevalence of microsporidia in mammals, avian and water provides insights into the epidemic features of these ubiquitous pathogens. Parasites vectors. 2021;14(1):186. Sak B, Kucerova Z, Kvac M, Kvetonova D, Rost M, Secor EW. 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07:08:20","extension":"pdf","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":945488,"visible":true,"origin":"","legend":"","description":"","filename":"Figure4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/ef87933a4789726b5242fed0.pdf"},{"id":96917396,"identity":"3ac3ebb0-87c6-4912-a9ce-e51461a57dc8","added_by":"auto","created_at":"2025-11-27 14:09:41","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":160555,"visible":true,"origin":"","legend":"","description":"","filename":"b68a478551024a2db6ef2caeb251ac101structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/05c106d480b4d92ad83bdd5b.xml"},{"id":96916897,"identity":"e6e82c21-3a0b-4bb7-97bc-7cd4a8d2279e","added_by":"auto","created_at":"2025-11-27 14:09:03","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":171735,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/710c946f4bc52011d3ed8716.html"},{"id":96793333,"identity":"4e6fd1be-6f1c-43a1-a775-6bb096abd095","added_by":"auto","created_at":"2025-11-26 07:08:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":192152,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenetic and genomic characteristics of 5,312 species-level genomes.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Phylogenetic relationships among 5,312 species-level genomes, with each clade color-coded according to its phylum-level classification. From the inside to the outside, the first outer ring represents genus-level classification, the second outer ring depicts GC content, and the third outer ring indicates the number of open reading frames (ORFs) in each genome. (\u003cstrong\u003eB\u003c/strong\u003e) Assessment of genome completeness and contamination rates. (\u003cstrong\u003eC\u003c/strong\u003e) Distribution of N50 values and genome sizes.\u003c/p\u003e","description":"","filename":"Figure1271.png","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/132c581ce0221384f878a0fc.png"},{"id":96916722,"identity":"0bf759fd-4dcf-44ba-b437-c34d77c126a7","added_by":"auto","created_at":"2025-11-27 14:08:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":199973,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGenomic identification and phylogenetic distribution of vitamin synthesis potential. \u003c/strong\u003e(\u003cstrong\u003eA\u003c/strong\u003e) Workflow for identifying genomes capable of synthesizing B and K\u003csub\u003e2\u003c/sub\u003e vitamins. (\u003cstrong\u003eB-C\u003c/strong\u003e) Genomic statistics for 2,307 genomes. (\u003cstrong\u003eD\u003c/strong\u003e) Maximum-likelihood phylogenetic tree of 2,307 genomes, with clades color-coded according to genome source. Outer-layer heatmaps indicate the presence (colored) or absence (blank) of vitamin synthesis capabilities. (\u003cstrong\u003eE\u003c/strong\u003e) Chord diagram showing the distribution of genomes with vitamin synthesis potential across different phyla. Each vitamin and phylum is represented by a distinct color. (\u003cstrong\u003eF\u003c/strong\u003e) Sankey diagram illustrating the relationships between taxonomic levels (phylum, class, order, family, and genus) and vitamin types.\u003c/p\u003e","description":"","filename":"Figure1272.png","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/fa92af578bfb5d9de869e073.png"},{"id":96793324,"identity":"f67d7eae-b55f-4b4b-b2a9-af58cbfa3783","added_by":"auto","created_at":"2025-11-26 07:08:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":59073,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiversity and taxonomic distribution of microbial genomes involved in vitamin B and K\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e biosynthesis.\u003c/strong\u003e (\u003cstrong\u003eA\u003c/strong\u003e) Rarefaction curve analysis illustrating the relationship between genome accumulation and increasing sample size. (\u003cstrong\u003eB-C\u003c/strong\u003e) Raincloud plots combining dot plots, boxplots, and distribution plots. The distribution plot represents probability density, the dot plot visualizes sample data point distribution, and the boxplot displays the richness and Shannon index of microbial genomes associated with vitamin B and K\u003csub\u003e2\u003c/sub\u003e biosynthesis. Statistical significance was determined using the Wilcoxon rank sum test: * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. (\u003cstrong\u003eD\u003c/strong\u003e) Scatter plots depicting beta diversity, highlighting compositional changes in microbial genomes related to vitamin B and K\u003csub\u003e2\u003c/sub\u003e biosynthesis. Samples are plotted based on the first and second principal coordinates (PCoA1 and PCoA2), with explained variance percentages indicated. Ellipsoids represent the 95% confidence interval for each group. Line graphs above and to the right illustrate sample distribution along PCoA1 and PCoA2, reflecting density variations between groups. (\u003cstrong\u003eE\u003c/strong\u003e) Bar graph showing the phylum-level taxonomic distribution of gene sets associated with vitamin B and K\u003csub\u003e2\u003c/sub\u003e biosynthesis.\u003c/p\u003e","description":"","filename":"Figure1273.png","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/5c6a6a707ba7ae031b403a00.png"},{"id":96793317,"identity":"495a2fe2-21c8-4f40-8491-6d40ddf23c77","added_by":"auto","created_at":"2025-11-26 07:08:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":82851,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylogenetic distribution of genes involved in pyridoxine biosynthesis.\u003c/strong\u003e Large circles represent functional roles in the \u003cem\u003ede novo\u003c/em\u003e biosynthetic pathway of pyridoxine. Within each large circle, circular stacked bar charts depict the distribution of genes associated with these functional roles across different phylum-level classifications, with each phylum represented by a distinct color. Small circles indicate metabolites involved in the pyridoxine biosynthetic process.\u003c/p\u003e","description":"","filename":"Figure1274.png","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/0feaf570fabdfa14431f91f7.png"},{"id":102234978,"identity":"220a2daa-002b-4711-be8c-b636c3de16b9","added_by":"auto","created_at":"2026-02-09 16:14:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1586920,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/ae6edc1b-8733-4513-809b-0b9742959ec3.pdf"},{"id":96793315,"identity":"60bb047d-2540-406c-b899-40c78485fbe7","added_by":"auto","created_at":"2025-11-26 07:08:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1008970,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/eb3ccc0159b6ccad640e2a5d.pdf"},{"id":96793316,"identity":"81b5e1f4-806c-4a51-9e1c-fbf07ac9a5ed","added_by":"auto","created_at":"2025-11-26 07:08:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":737485,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/847dcb03a820c875d0d65a2e.pdf"},{"id":96915931,"identity":"da0b355c-74fc-418e-bb51-e0c283bea5c6","added_by":"auto","created_at":"2025-11-27 14:07:47","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":737441,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/3c41c9cf24f1560fc95bb9c3.pdf"},{"id":96793332,"identity":"baec4e3d-2151-4e6c-ab24-909b4b3effc4","added_by":"auto","created_at":"2025-11-26 07:08:18","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":470287,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/aa1beb4817c1f00da6f64540.pdf"},{"id":96793334,"identity":"f4ed87bc-d1e6-4b45-b907-f571d9ae1e72","added_by":"auto","created_at":"2025-11-26 07:08:19","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":34289,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure5.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/ef76225278ffef2de67b0bdf.pdf"},{"id":96916712,"identity":"bf396989-395d-4c6a-962d-ad4abfa89f00","added_by":"auto","created_at":"2025-11-27 14:08:51","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1889155,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables14.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/c4721118731314895399fb53.xlsx"},{"id":96917409,"identity":"b90f22d4-1654-4219-84cb-9687678ee62e","added_by":"auto","created_at":"2025-11-27 14:09:42","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":18980,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigurestable.docx","url":"https://assets-eu.researchsquare.com/files/rs-7835059/v1/0c904567f5ba4b91ce6e9946.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Gut microbiota response to Enterocytozoon bieneusi infection: enhanced vitamin B and K 2 pathways","fulltext":[{"header":"Introduction","content":"\u003cp\u003e\u003cem\u003eEnterocytozoon bieneusi\u003c/em\u003e (\u003cem\u003eE. bieneusi\u003c/em\u003e) is eukaryotic parasites that opportunistically infect immunocompromised individuals, particularly HIV-infected patients, becoming one of the main causes of diarrhea in these individuals[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A recent meta-analysis estimated the overall prevalence of \u003cem\u003eE. bieneusi\u003c/em\u003e infection in humans at 7.9%, but with significant variation depending on the presence of digestive symptoms and immune status[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A study conducted in the Czech Republic in 2007 reported a seroprevalence of 19% for \u003cem\u003eE. bieneusi.\u003c/em\u003e Among HIV-positive patients, the seroprevalence was 20%, while in populations with reported animal contact, the rate reached 33%[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe gut microbiome of wild rodents exhibits diversity and dynamic changes similar to those of humans, influenced by social interactions and environmental pressures, making them a valuable model for studying human diseases[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, understanding the gut microbiome of wild rodents provides valuable insights for the prevention and control of human \u003cem\u003eE. bieneusi\u003c/em\u003e.\u003c/p\u003e\u003cp\u003ePrevious studies have demonstrated that gut microbiota can synthesize substantial proportions of the host's B vitamin requirements, with vitamin K\u003csub\u003e2\u003c/sub\u003e being almost exclusively microbial in origin [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This microbial contribution is particularly important in wild animals, such as rodents, which do not receive dietary vitamin supplementation and depend largely on their gut microbiota for micronutrient acquisition [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Wild rodents, inhabiting diverse ecological niches and feeding on variable natural diets [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], represent an ecologically relevant model for studying microbiota-driven nutrient synthesis under fluctuating environmental conditions.\u003c/p\u003e\u003cp\u003eHowever, the functionality of this microbial ecosystem can be disrupted by pathogenic infections, with potential consequences for host nutrient acquisition. \u003cem\u003eE. bieneusi\u003c/em\u003e, an obligate intracellular parasite of the phylum Microsporidia, frequently infects the intestinal epithelium of wild rodents and other mammals, including humans [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It is associated with impaired gut barrier integrity, dysbiosis, and reduced nutrient absorption [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although \u003cem\u003eE. bieneusi\u003c/em\u003e is widely present and poses a zoonotic risk [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], the impact of \u003cem\u003eE. bieneusi\u003c/em\u003e infection on the gut microbiota\u0026rsquo;s functional role\u0026mdash;particularly in the biosynthesis of B vitamins and vitamin K\u0026mdash;remains poorly characterized. This gap is concerning given that micronutrient deficiencies can exacerbate infection severity, compromise host survival, and affect reproductive fitness\u0026mdash;factors with important implications for both ecological dynamics and public health.\u003c/p\u003e\u003cp\u003eTo address this knowledge gap, we investigate how gut microbial communities contribute to vitamin biosynthesis in wild rodents under both healthy and pathogen-challenged conditions. In this study, we aim to systematically characterize the capacity of the wild rodent gut microbiota to synthesize B vitamins and vitamin K\u003csub\u003e2\u003c/sub\u003e and to assess how this functional potential is altered during \u003cem\u003eE. bieneusi\u003c/em\u003e infection. By leveraging a comprehensive metagenomic dataset comprising 17,137 microbial genomes and integrating taxonomic and functional analyses, we provide new insights into the ecological and metabolic resilience of wild rodent microbiomes. This work advances our understanding of environmentally shaped microbiome functionality and highlights the metabolic vulnerabilities introduced by parasitic perturbation, providing insights that are relevant to ecosystem health, wildlife conservation, and zoonotic disease management.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMetagenome assembly and taxonomic classification of wild rodent gut genomes\u003c/h2\u003e\u003cp\u003eA total of 17,137 wild rodent gut genomes were retrieved from the Figshare repository (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.6084/m9.figshare.28752050\u003c/span\u003e\u003cspan address=\"10.6084/m9.figshare.28752050\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Taxonomic classification was performed using the GTDB-Tk v2.3.2 classify_wf workflow [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], based on the Genome Taxonomy Database (GTDB). To remove redundancy, strain-level de-duplication at 99% average nucleotide identity (ANI) was performed using dRep v3.4.3 [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] with the parameters \u0026lsquo;-pa 0.9 -sa 0.99 -nc 0.30 -cm larger --S_algorithm fastANI,\u0026rsquo; resulting in 9,929 unique genomes. To further resolve species-level diversity, ANI was re-estimated among genomes sharing identical genus-level taxonomic classifications using dRep (v3.4.3) with the parameters \u0026lsquo;-pa 0.9 -sa 0.95 -nc 0.30 -cm larger --S_algorithm fastANI\u0026rsquo;. This analysis identified 5,312 species-level genome bins (SGBs). The phylogenetic tree generated by GTDB-Tk was visualized using iTOL v6.9.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://itol.embl.de/\u003c/span\u003e\u003cspan address=\"https://itol.embl.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eFunctional analysis of vitamin-related microbial gene catalog\u003c/h3\u003e\n\u003cp\u003eOpen reading frames (ORFs) were predicted from 9,929 genomes using Prodigal v2.6.3 [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] with the parameter '-p single'. The resulting ORFs were clustered using MMseqs easy-cluster workflows [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] with the parameters: \u0026lsquo;--split-mode 2 --cov-mode 2 -c 0.9 --min-seq-id 0.95 --cluster-mode 2 --cluster-reassign 1\u0026rsquo;. This resulted in a non-redundant microbial gene catalog containing 260,273 genes, with redundancy reduced by clustering sequences sharing\u0026thinsp;\u0026gt;\u0026thinsp;95% identity to ensure a unique representation of microbial gene diversity. Functional annotation was performed by comparing the clustered genes to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database using DIAMOND v2.1.8.162 (15) with the following parameters: \u0026lsquo;--min-score 60 --query-cover 70 --max-target-seqs 5 --masking 1.\u0026rsquo; For each gene, the alignment with the highest bit score was used for functional classification. Functional roles were defined as specific biological functions associated with KEGG gene categories, with a particular focus on those involved in the biosynthesis of B vitamins and menaquinone. These roles were identified based on KEGG annotations to ensure accurate classification of genes involved in key metabolic pathways.\u003c/p\u003e\n\u003ch3\u003ePhylogenetic, taxonomic, and functional analyses of 3,522 high-quality genomes\u003c/h3\u003e\n\u003cp\u003eTo ensure data quality, all 17,137 genomes were re-evaluated using CheckM2 v1.0.1 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], and only genomes with \u0026ge;\u0026thinsp;90% completeness and \u0026lt;\u0026thinsp;5% contamination were retained. Strain-level de-redundancy at 99% ANI was performed using dRep v3.4.5 with the parameters \u0026lsquo;-pa 0.9 -sa 0.99 -nc 0.30 -cm larger --S_algorithm fastANI,\u0026rsquo; resulting in 3,522 high-quality, non-redundant genomes. Functional annotation was conducted using DIAMOND v2.1.8.162 via BLASTP searches against the KEGG database. We defined a set of essential functional roles required for a genome to be considered as a \u003cem\u003ede novo\u003c/em\u003e producer of vitamins B and menaquinone. Based on these criteria, 2,307 genomes were predicted to possess the capability to synthesize vitamin B and menaquinone \u003cem\u003ede novo\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eEffects of infection on the gut microbiota\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eEffects of \u003cem\u003eE. bieneusi\u003c/em\u003e infection on the gut microbiota\u003c/div\u003e\u003cp\u003eWe reanalyzed metagenomic data from project PRJNA1175865, which comprises 20 gut metagenomic samples from wild rodents. As described in our previous study [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], the dataset includes 10 control (CON) and 10 \u003cem\u003eE. bieneusi\u003c/em\u003e-infected samples. To ensure high data quality, raw reads were processed using fastp v0.23.0 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] with the following parameters \u0026lsquo;-u 30 -n 5 -q 20 -y -Y 30 -l 80 --trim_poly_g\u0026rsquo;. Host-derived sequences were removed by aligning the quality-filtered reads to the rodent reference genome (NCBI RefSeq assembly: GCF_036323735.1) using Bowtie2 v2.5.0 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The resulting clean reads were retained for downstream analyses. For functional profiling, clean reads were aligned to a non-redundant microbial gene catalog using Bowtie2 v2.5.0. as a reference, we assigned metagenomic reads to the respective groups with Bowtie2 v2.5.0. Read counts were normalized to transcripts per million (TPM), and the relative abundances of KEGG orthologs (KOs) were calculated. For taxonomic profiling, total abundance was determined by summing the abundances of all genes assigned to each taxonomic unit. Functional roles related to vitamin biosynthesis were defined based on KO annotations, and their relative abundances were calculated by summing the TPM values of associated genes.\u003c/p\u003e\n\u003ch3\u003eStatistical analyses and visualization\u003c/h3\u003e\n\u003cp\u003eStatistical analyses were conducted using R version 4.2.2. Alpha diversity metrices, including Shannon diversity and richness indices, were calculated for each sample based on both taxonomic and functional gene abundance data. Beta diversity was evaluated using Principal Coordinate Analysis (PCoA) based on Bray-Curtis dissimilarity, with group differences evaluated using permutational multivariate analysis of variance (PERMANOVA). The Wilcoxon rank-sum test was applied to identify significant differences in diversity indices and the relative abundance of taxa and functional features between groups. Rarefaction curves were generated using the \u0026lsquo;vegan\u0026rsquo; package (v2.6-4). Chord diagrams were generated with the \u0026lsquo;circlize\u0026rsquo; package (v2.8.0), and Sankey plots were constructed using \u0026lsquo;networkD3\u0026rsquo; (v4.2.3). Network graphs were visualized using Gephi (v0.10.1). Additional plots were generated using the \u0026lsquo;ggplot2\u0026rsquo; package in R.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eConstruction and taxonomic profiling of a wild rodent gut microbiome genome catalog\u003c/h2\u003e\u003cp\u003eTo characterize the gut microbiota of wild rodents, we constructed a bacterial genome catalog by integrating 17,137 publicly available genomes, including 16,856 metagenome-assembled genomes (MAGs) and 281 genomes from cultured isolates. Genomes were filtered based on quality criteria (\u0026ge;\u0026thinsp;50% completeness, \u0026lt; 5% contamination, and [completeness \u0026ndash; (5 \u0026times; contamination)]\u0026thinsp;\u0026ge;\u0026thinsp;50) and dereplicated at a 99% ANI threshold. This process yielded 9,929 non-redundant genomes for downstream analysis (Supplementary Table\u0026nbsp;1). These genomes ranged in size from 0.26 Mb to 9.54 Mb (mean: 2.15 Mb), with an average N50 of 55,631 bp, 82.77% completeness, and 1.18% contamination (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB-C). Interestingly, 3,522 genomes met high-quality standards (completeness\u0026thinsp;\u0026ge;\u0026thinsp;90%, contamination\u0026thinsp;\u0026lt;\u0026thinsp;5%), providing a robust dataset for investigating microbial functional diversity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo assess species-level diversity, we clustered the genomes at a 95% ANI threshold, resulting in 5,312 species-level genome bins (SGBs). These genomes had an average GC content of 48.54% (range: 22.21%\u0026ndash;73.68%) and contained, on average, 2,074 ORFs per genome (range: 400\u0026ndash;8,705). Taxonomic classification using GTDB-Tk database assigned the genomes to 24 phyla, 31 classes, 78 orders, 164 families, and 712 genera. At the phylum level, \u003cem\u003eBacillota_A\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2,731) and \u003cem\u003eBacteroidota\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,312) were most abundant, followed by \u003cem\u003eBacillota\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;354), \u003cem\u003eActinomycetota\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;241), and \u003cem\u003ePseudomonadota\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;195). At the family level, \u003cem\u003eLachnospiraceae\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1,069) and \u003cem\u003eMuribaculaceae\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;862) were most common, followed by \u003cem\u003eRuminococcaceae (n\u003c/em\u003e\u0026thinsp;=\u0026thinsp;393), \u003cem\u003eOscillospiraceae\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;358), and \u003cem\u003eAcutalibacteraceae\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;236) (Figure. 1A). Together, these genomes form a high-resolution reference dataset for exploring microbial diversity and function in wild rodents, including the genomic basis for traits such as vitamin biosynthesis that may contribute to host adaptation in dynamic environments.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eIdentification and characterization of vitamin synthesis genes in the wild rodent gut microbiome\u003c/h3\u003e\n\u003cp\u003eUsing the 9,929 high-quality genomes described above, we investigated the potential for vitamin synthesis within the wild rodent gut microbiota. Protein-coding genes from these genomes were annotated against the KEGG database to assess their functional roles. In total, 464,312 genes corresponding to 199 KOs were identified as being involved in the biosynthesis of eight vitamin B compounds (biotin, cobalamin, folate, niacin, pantothenic acid, pyridoxine, riboflavin, and thiamine) as well as menaquinone (Supplementary Table\u0026nbsp;2). To reduce redundancy, these genes were clustered using MMseqs, resulting in a non-redundant catalog of 260,273 genes with an average length of 895 bp. This catalog offers a valuable resource for functional classification and exploration of gut microbiota-mediated vitamin synthesis in wild rodents. Further pathway analysis based on this gene set revealed that all eight vitamin B compounds are synthesized directly by the gut microbiota, whereas menaquinone synthesis proceeds via indirect microbial pathways (Supplementary Fig.\u0026nbsp;1\u0026ndash;3). These findings highlight the significant metabolic contributions of the gut microbiome to host vitamin availability. The presence of diverse and complete biosynthetic pathways across multiple taxa underscores a distributed metabolic architecture that may help sustain micronutrient levels in the host, particularly under nutrient-limited conditions.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eHost-specific genomic potential for \u003cem\u003ede novo\u003c/em\u003e vitamin biosynthesis in gut microbiomes\u003c/h2\u003e\u003cp\u003eBuilding upon the curated gene sets for vitamin synthesis, we investigated the genome-level potential for \u003cem\u003ede novo\u003c/em\u003e synthesis of B vitamins and menaquinone in the gut microbiome of wild rodents. From the 9,929 high-quality MAGs, we selected 3,522 with \u0026ge;\u0026thinsp;90% completeness and \u0026lt;\u0026thinsp;5% contamination for downstream analysis (Supplementary Table\u0026nbsp;3). Functional annotation revealed that 2,307 genomes encoded complete pathways for synthesizing at least one B vitamin or menaquinone (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA and Supplementary Table\u0026nbsp;4), signifying widespread but uneven biosynthetic potential across the microbiome. These genomes exhibited broad genomic diversity, with sizes ranging from 0.97 to 9.54 Mbp (mean\u0026thinsp;=\u0026thinsp;2.64 Mbp), average N50 of 103,843 bp, and GC content spanning 26.58% to 73.42% (mean\u0026thinsp;=\u0026thinsp;48.19%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB-C). Taxonomic analysis showed that \u003cem\u003eBacteroidota\u003c/em\u003e (37.06%,, 855 genomes) and \u003cem\u003eBacillota_A\u003c/em\u003e (36.11%, 833 genomes) predominated among vitamin-producing genomes, followed by \u003cem\u003eBacillota\u003c/em\u003e (6.07%, 140 genomes), \u003cem\u003eDesulfobacterota\u003c/em\u003e (5.21%, 118 genomes), and \u003cem\u003ePseudomonadota\u003c/em\u003e (3.80%, 90 genomes). This taxonomic distribution highlights key bacterial lineages contributing to gut-derived micronutrient synthesis in wild rodents.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFunctional analysis of vitamin synthesis capabilities revealed that 961 genomes encoded the capacity to synthesize a single vitamin, while 1,314 were capable of producing 2 to 6 vitamins. Interestingly, 32 genomes were equipped to produce 7 or 8 vitamins, but none harbored complete biosynthetic pathways for all nine, underscoring the metabolic interdependence among microbial taxa and the likely necessity of cross-feeding in vitamin provisioning (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD and Supplementary Table\u0026nbsp;4\u003cb\u003e)\u003c/b\u003e. Among the biosynthetic targets, the most commonly encoded pathways were for niacin (1,664 genomes), riboflavin (1,106), and pyridoxine (713), with fewer genomes able to synthesize pantothenate, folate, biotin, thiamine, and cobalamin (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). The distribution of biosynthetic capacity was taxon-specific. \u003cem\u003eBacteroidota\u003c/em\u003e and \u003cem\u003eBacillota_A\u003c/em\u003e were the dominant phyla facilitating vitamin biosynthesis in wild rodents. Niacin, riboflavin, pyridoxine, and pantothenate were primarily synthesized by \u003cem\u003eBacteroidota\u003c/em\u003e (44.83%, 48.10%, 17.95%, and 25.45%, respectively) and \u003cem\u003eBacillota_A\u003c/em\u003e (35.52%, 25.86%, 32.96%, and 25.45%, respectively). Folate synthesis was mostly mediated by \u003cem\u003eBacteroidota\u003c/em\u003e (38.76%) and \u003cem\u003ePseudomonadota\u003c/em\u003e (23.17%). Biotin synthesis was mainly supported by \u003cem\u003ePseudomonadota\u003c/em\u003e (38.17%) and \u003cem\u003eCampylobacterota\u003c/em\u003e (16.67%). Menaquinone synthesis was dominated by \u003cem\u003eDesulfobacterota\u003c/em\u003e (45.33%) and \u003cem\u003eCampylobacterota\u003c/em\u003e (31.33%). Thiamine synthesis was chiefly attributed to \u003cem\u003eBacillota_A\u003c/em\u003e (32.77%) and \u003cem\u003eBacillota\u003c/em\u003e (21.85%). Cobalamin synthesis was more evenly split between \u003cem\u003eBacillota\u003c/em\u003e (19.66%) and \u003cem\u003ePseudomonadota\u003c/em\u003e (19.66%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e\u003cp\u003eTo explore whether this biosynthetic landscape was conserved across host species, we extended our analysis to 1,707 MAGs from the laboratory mouse gut microbiome (CMMG). Comparative profiling revealed distinct host-specific taxonomic patterns in vitamin synthesis. In cats, the predominant contributors were \u003cem\u003eBacillota_A\u003c/em\u003e (40.54%) and \u003cem\u003eActinobacteria\u003c/em\u003e (20.84%), whereas in ruminants, \u003cem\u003eBacteroidota\u003c/em\u003e (43.28%) and \u003cem\u003eBacillota\u003c/em\u003e (38.25%) were most prominent. In chickens, vitamin synthesis was primarily associated with \u003cem\u003eBacteroidota\u003c/em\u003e (28.21%) and \u003cem\u003eBacillota_A\u003c/em\u003e (25.66%). Although \u003cem\u003eBacteroidota\u003c/em\u003e and \u003cem\u003eBacillota_A\u003c/em\u003e were dominant in both wild rodents and laboratory mice, their relative contributions shifted\u0026mdash;\u003cem\u003eBacteroidota\u003c/em\u003e led in wild rodents (37.06%), while \u003cem\u003eBacillota_A\u003c/em\u003e dominated in laboratory mice (52.9%) (Supplementary Fig.\u0026nbsp;4). These host-specific microbial vitamin profiles underscore variation in the taxonomic architecture of vitamin biosynthesis, reflecting differences in gut microbial composition between species.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eImpact of \u003cem\u003eE. bieneusi\u003c/em\u003e infection on vitamin synthesis by the gut microbiota in wild rodents\u003c/h2\u003e\u003cp\u003eHaving established the capacity of wild rodent gut microbiota for \u003cem\u003ede novo\u003c/em\u003e vitamin biosynthesis, we next investigated how \u003cem\u003eE. bieneusi\u003c/em\u003e infection alters this functional potential. Although gut microbes are central to host vitamin metabolism, the effects of parasitic infection on microbial vitamin-producing capacity remain poorly characterized. To address this, we reanalyzed gut metagenomic data from infected and uninfected rodents, focusing on genomes annotated with vitamin biosynthetic pathways. Rarefaction analysis confirmed sufficient sequencing depth to capture the diversity of vitamin-producing genomes, with cumulative curves reaching saturation (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlpha diversity analysis revealed a significant increase in the richness of vitamin-synthesizing genomes in infected rodents, indicating enhanced within-sample diversity post-infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u0026ndash;C). Beta diversity assessed via principal coordinates analysis (PCoA) explained 43.48% of the variation across the first two axes. Although a shift in community composition was observed between infected and uninfected groups, this difference did not reach statistical significance (PERMANOVA: R\u0026sup2; = 0.0894, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.075) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003eTo identify specific taxa driving these changes, we conducted a differential abundance analysis of vitamin-producing phyla. Importantly, \u003cem\u003eMethanobacteriota\u003c/em\u003e showed a significant increase in relative abundance following \u003cem\u003eE. bieneusi\u003c/em\u003e infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and Supplementary Fig.\u0026nbsp;5), while other phyla remained stable. Interestingly, \u003cem\u003eMethanobacteriota\u003c/em\u003e contributed exclusively to pyridoxine (vitamin B\u003csub\u003e6\u003c/sub\u003e) synthesis and was not implicated in the biosynthesis of any of the other eight vitamins, suggesting a targeted functional enrichment. These findings indicate that \u003cem\u003eE. bieneusi\u003c/em\u003e infection selectively enriches microbial taxa involved in specific vitamin biosynthetic pathways, particularly pyridoxine. This functional shift implies a potential microbial adaptation to parasitic stress, wherein vitamin B\u003csub\u003e6\u003c/sub\u003e production may confer a survival or ecological advantage within the altered gut environment.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003ePyridoxine biosynthesis and its modulation by\u003c/b\u003e \u003cb\u003eE. bieneusi\u003c/b\u003e \u003cb\u003einfection in wild rodent gut microbiota\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eAs part of our broader investigation into gut microbial vitamin production, we focused on pyridoxine, a coenzyme essential for amino acid metabolism, immune regulation, neurotransmitter synthesis, and environmental stress adaptation. Pyridoxine is synthesized by the gut microbiota and can, in turn, shape microbial community structure and function. We examined how \u003cem\u003eE. bieneusi\u003c/em\u003e infection influences the genetic capacity for pyridoxine biosynthesis in the wild rodent gut. We identified two pyridoxine biosynthetic routes within the gut microbiota: a direct pathway catalyzed by pyridoxine 5\u0026prime;-phosphate synthase (involving Pdx proteins), and an alternative route using 4-hydroxy-L-threonine (4-HTL) as a precursor. Both pathways were constrained by the low abundance of the gene \u003cem\u003eepd\u003c/em\u003e, which encodes erythrose-4-phosphate dehydrogenase, a key enzyme required for the biosynthesis of vitamin B6. Despite this bottleneck, \u003cem\u003eE. bieneusi\u003c/em\u003e infection led to a moderate increase in the relative abundance of several pyridoxine-related genes, including \u003cem\u003eserC\u003c/em\u003e, \u003cem\u003ethrC\u003c/em\u003e, and \u003cem\u003epdxK\u003c/em\u003e. Core biosynthetic genes (\u003cem\u003epdxD\u003c/em\u003e, \u003cem\u003epdxA\u003c/em\u003e, \u003cem\u003epdxJ\u003c/em\u003e) were predominantly associated with the phylum \u003cem\u003eBacillota_A\u003c/em\u003e, whereas \u003cem\u003eepd\u003c/em\u003e was enriched in \u003cem\u003ePseudomonadota\u003c/em\u003e. Auxiliary precursor-synthesis genes were largely contributed by \u003cem\u003eBacteroidota\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These data reveal a phylum-specific distribution of pyridoxine biosynthesis genes in the wild rodent gut microbiota. Following \u003cem\u003eE. bieneusi\u003c/em\u003e infection, an increase in key biosynthetic genes suggests altered functional potential in vitamin B6 synthesis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study presents a comprehensive genomic and functional analysis of the gut microbiome in wild rodents, emphasizing its critical role in vitamin biosynthesis and the modulatory effects of \u003cem\u003eE. bieneusi\u003c/em\u003e infection on microbial community structure and metabolic function. A key novel finding is the significant enrichment of pyridoxine (vitamin B\u003csub\u003e6\u003c/sub\u003e), producing \u003cem\u003eMethanobacteriota\u003c/em\u003e in infected hosts, unveiling an adaptive microbial response to parasitic stress that has not been previously documented. By integrating publicly available datasets and implementing rigorous quality control measures, we assembled a curated collection of 9,929 high-quality bacterial genomes, providing a robust framework for future investigations into microbiome-mediated host\u0026ndash;parasite interactions, functional diversity, and adaptations in fluctuating environments.\u003c/p\u003e\u003cp\u003eOur study reveals a remarkable taxonomic richness within the wild rodent gut microbiota, comprising 5,312 SGBs across 24 bacterial phyla, underscoring the complexity of host-microbiome interactions in natural environments. The dominance of \u003cem\u003eBacillota_A\u003c/em\u003e and \u003cem\u003eBacteroidota\u003c/em\u003e aligns with their well-established roles in fiber degradation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] and energy harvesting [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, our data provide new insights into their relative contributions under wild dietary regimes. Importantly, members of \u003cem\u003eLachnospiraceae\u003c/em\u003e and \u003cem\u003eMuribaculaceae\u003c/em\u003e emerge as important taxa critical for maintaining gut homeostasis through short-chain fatty acid (SCFA) production\u0026mdash; metabolites fundamental for host energy balance and immune regulation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. With 712 genera identified, this microbial consortium exhibits multifaceted functionality, mediating nutrient metabolism, immunomodulation, and environmental adaptability [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Our findings highlight how such extensive microbial diversity equips wild rodents with a dynamic gut ecosystem capable of responding to fluctuating dietary inputs and ecological pressures, thereby shaping host physiology and resilience in natural habitats [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur study reveals that the wild rodent gut microbiome possesses extensive metabolic potential to support host vitamin nutrition, underscoring its functional importance beyond digestion. Functional annotation of 464,312 protein-coding genes identified 199 KOs involved in the biosynthesis of essential vitamins\u0026mdash;including all eight B vitamins (biotin, cobalamin, folate, niacin, pantothenic acid, pyridoxine, riboflavin, and thiamine) as well as vitamin K₂. This comprehensive repertoire reflects a metabolically versatile microbiome capable of supplementing host micronutrient requirements, potentially alleviating dependence on dietary vitamin intake [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The detection of menaquinone synthesis pathways suggests complex syntrophic and cross-feeding interactions within the microbial community\u0026mdash;ecological dynamics that enhance nutrient accessibility and stabilize microbial consortia [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. These cooperative interactions exemplify the microbiome\u0026rsquo;s contribution to host metabolic homeostasis, immune development, and resilience [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Moreover, the observed inter-individual variation in vitamin biosynthesis capacity may modulate host fitness and disease susceptibility under differing environmental or nutritional pressures [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe identification of diverse microbial vitamin biosynthesis pathways underscores the evolutionary co-adaptation of the gut microbiome to the host\u0026rsquo;s diet and ecological niche [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Wild rodents, whose diets are predominantly plant-based and often low in bioavailable vitamins, face significant micronutrient constraints. Our findings suggest that the gut microbiota has functionally adapted to offset these limitations, providing a complementary source of essential vitamins and thereby reinforcing a mutualistic, co-evolved relationship with the host [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This microbial compensation likely reflects long-term selective pressures favoring hosts with microbiomes capable of nutrient provisioning under fluctuating dietary conditions. Such functional plasticity may enhance host survival and fitness in resource-variable environments, positioning the microbiome as a key adaptive partner in the evolutionary trajectory of wild rodents.\u003c/p\u003e\u003cp\u003eOur analysis of \u003cem\u003ede novo\u003c/em\u003e vitamin biosynthesis in the wild rodent gut microbiome reveals a complex, distributed metabolic architecture involving diverse microbial taxa and cooperative synthesis strategies. Rather than relying on a single dominant species, vitamin production is partitioned across multiple microbial contributors\u0026mdash;each encoding different components of biosynthetic pathways. This decentralized, community-level organization, not previously described in wild rodent systems [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], highlights the microbiome\u0026rsquo;s functional integration and its critical role in sustaining host vitamin homeostasis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While dominant taxa orchestrate core biosynthetic processes, less-abundant phyla, such as \u003cem\u003eDesulfobacterota\u003c/em\u003e and \u003cem\u003ePseudomonadota\u003c/em\u003e, play secondary roles, enhancing overall pathway completeness, metabolic flexibility, and niche specialization [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This functional redundancy likely confers resilience to the system, enabling wild rodents to maintain micronutrient sufficiency even under dietary or environmental stress.\u003c/p\u003e\u003cp\u003eA critical insight from this study is that no single microbial genome within the gut microbiome encodes the complete biosynthetic machinery for all nine essential vitamins. Instead, vitamin synthesis is a cooperative function\u0026mdash;shared among taxonomically and functionally diverse microbes. This underscores the gut microbiome\u0026rsquo;s role as an integrated metabolic network rather than a sum of isolated organisms [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Such interdependent biosynthesis networks suggest that evolutionary selection has favored microbial consortia capable of buffering the host against nutrient variability. However, this dependency also implies vulnerability: disruptions from dietary shifts, environmental stressors, or disease may destabilize cooperative functions, potentially leading to vitamin deficiencies [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Understanding these microbial interdependencies is therefore crucial for predicting host resilience and guiding future interventions to preserve microbiome-mediated nutrition under ecological change.\u003c/p\u003e\u003cp\u003eOur comparative analysis of gut microbiomes across diverse host species\u0026mdash;including wild rodents, laboratory mice, cats, ruminants, and chickens\u0026mdash;reveals striking host-specific patterns in microbial vitamin biosynthesis. In wild rodents, \u003cem\u003eBacteroidota\u003c/em\u003e emerged as the dominant contributor to vitamin pathways, whereas \u003cem\u003eBacillota_A\u003c/em\u003e predominated in carnivorous hosts such as cats, reflecting the influence of host diet, gut morphology, and microbial adaptation to distinct ecological niches [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. We observed marked divergence between the microbiomes of wild rodents and laboratory mice, particularly in the relative abundance and biosynthetic contributions of \u003cem\u003eBacillota_A\u003c/em\u003e. These differences raise important questions about the extent to which domestication, controlled housing conditions, and standardized diets shape microbiome composition and functional capacity [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. The reduced ecological and dietary complexity in laboratory settings likely narrows microbial diversity and metabolic flexibility, with implications for host physiology and experimental outcomes. Our findings challenge the assumption that laboratory rodents adequately model natural host\u0026ndash;microbiome dynamics. The metabolically versatile microbiomes of wild rodents, shaped by exposure to diverse environments and variable diets, may better reflect the adaptive potential of host-associated microbial communities [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Incorporating wild-derived microbiome data into experimental frameworks could enhance the ecological validity and translational relevance of studies in nutrition, immunity, and disease modeling.\u003c/p\u003e\u003cp\u003eOne of the most interesting findings from our study is the infection-induced enrichment of \u003cem\u003eMethanobacteriota\u003c/em\u003e species with the genetic potential to synthesize pyridoxine. This observation not only uncovers a novel dimension of microbial functional resilience under parasitic stress but also suggests that the microbiota may engage in compensatory nutrient provisioning to mitigate the impact of infection on host health. Building on our characterization of the healthy microbiome's metabolic potential, we investigated how \u003cem\u003eE. bieneusi\u003c/em\u003e infection perturbs these dynamics. \u003cem\u003eE. bieneusi\u003c/em\u003e is known to disrupt intestinal barrier integrity, altering nutrient absorption and immune status\u0026mdash;particularly in immunocompromised or juvenile hosts [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. These physiological disruptions may impose selective pressures on the gut microbiota, potentially leading to shifts in both community structure and function. Our results reveal that \u003cem\u003eE. bieneusi\u003c/em\u003e infection leads to a reorganization of microbial metabolic pathways, including altered vitamin biosynthesis and reduced microbial diversity. Despite this disturbance, the enrichment of certain taxa with vitamin-synthesizing capabilities\u0026mdash;such as \u003cem\u003eMethanobacteriota\u003c/em\u003e\u0026mdash;suggests a compensatory mechanism aimed at preserving host-microbe homeostasis. These findings contribute new insights into how parasitic infections can induce functional reprogramming within the microbiome, with potential implications for host resilience and recovery [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAn unexpected and counterintuitive observation from our study was the increase in microbial diversity following \u003cem\u003eE. bieneusi\u003c/em\u003e infection, as indicated by elevated Shannon diversity and species richness indices. This pattern may reflect an adaptive restructuring of the gut microbiota to sustain homeostasis under stress or, alternatively, an opportunistic expansion of taxa that thrive under altered gut conditions [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Despite this increase in diversity, the overall microbial community structure remained statistically stable, as confirmed by PERMANOVA analysis, suggesting that infection does not induce broad taxonomic disruption but instead drives more subtle functional reprogramming. Most importantly, \u003cem\u003eE. bieneusi\u003c/em\u003e infection induced a significant increase in the number of microbial genomes encoding vitamin biosynthesis pathways, particularly those associated with pyridoxine. This shift was linked to an increased abundance of \u003cem\u003eMethanobacteriota\u003c/em\u003e, marking the first evidence that \u003cem\u003eE. bieneusi\u003c/em\u003e infection enriches gut microbial populations capable of synthesizing vitamin B\u003csub\u003e6\u003c/sub\u003e\u0026mdash;revealing a novel, infection-induced functional adaptation [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFurther analysis uncovered two distinct pyridoxine biosynthesis pathways (via Pdx proteins and 4-hydroxythreonine-4-phosphate dehydrogenase, 4-HTL), underscoring the metabolic versatility of the microbial community [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. However, the observed limitation in \u003cem\u003eepd\u003c/em\u003e gene abundance may constrain total pyridoxine production, suggesting partial\u0026mdash;but not complete\u0026mdash;compensatory capacity. Importantly, post-infection upregulation of key pyridoxine biosynthesis genes (\u003cem\u003eserC\u003c/em\u003e, \u003cem\u003ethrC\u003c/em\u003e, \u003cem\u003epdxK\u003c/em\u003e) suggests a targeted microbial response aimed at sustaining host immune function under parasitic stress [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. This functional resilience, despite relatively stable community composition, provides compelling evidence for \u003cem\u003eE. bieneusi\u003c/em\u003e-driven metabolic reprogramming within the gut microbiome. These adaptations may represent a microbiota-mediated buffering mechanism to preserve host-microbe equilibrium or, conversely, an opportunistic metabolic shift that facilitates parasite infection [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. These findings highlight the dynamic nature of host-microbe-parasite interactions and underscore the potential for microbiota-targeted strategies to enhance infection resilience and support nutrient homeostasis during enteric parasitic challenges.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study presents a high-resolution genomic framework that reveals the complex taxonomic and functional architecture of wild rodent gut microbiomes. By uncovering the dynamic capacity of these microbial communities to adapt metabolically\u0026mdash;particularly through the reprogramming of vitamin biosynthesis pathways in response to parasitic infection\u0026mdash;we highlight the microbiome\u0026rsquo;s critical role in maintaining host physiological balance under ecological and pathogenic stress. The infection-induced upregulation of pyridoxine synthesis exemplifies the functional resilience and cooperative potential of the gut microbiota, offering new insights into host\u0026ndash;microbe co-adaptation. Importantly, our findings extend beyond ecological microbiology by offering a reference point for evaluating microbiome responses in natural versus controlled environments. They underscore the translational relevance of wild microbiome models for improving our understanding of microbial contributions to health, immunity, and disease tolerance. While further validation is needed, the functional adaptations observed here provide conceptual frameworks for understanding microbiome resilience and nutrient provisioning during infection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eClinical trial number\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eConsent for publication\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 32170538), the National Key R\u0026amp;D Program of China (2022YFF0710503), the Natural Science Foundation of Heilongjiang Province (ZD2022C006), and the Horizontal Project of Qingdao Agricultural University (Grant No. 667/2424025).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXiao-Xuan Zhang: Conceptualization, Funding acquisition, Resources, Supervision, Writing-original draft. He Zhang: Funding acquisition, Writing-review and editing. Ji-Xin Zhao: Data curation, Software, Writing-review and editing. Hai-Long Yu: Software, Writing-original draft. Chun-Ren Wang: Funding acquisition, Writing-review and editing. Kai-Meng Shang: Resources, Formal analysis, Visualization, Writing-review and editing. Yong-Jie Wei: Formal analysis, Visualization, Writing-review and editing. Ya Qin: Resources, Writing-review and editing. Jian-Ming Li: Resources, Writing-review and editing. Zi-Yu Zhao: Resources, Writing-review and editing. Chang-You Xia: Conceptualization, Project administration, Writing-review and editing. Bei-Ni Chen: Conceptualization, Supervision, Writing-review and editing. Hany M. Elsheikha: Conceptualization, Validation, Writing-original draft. He Ma: Conceptualization, Funding acquisition, Supervision, Methodology, Writing-review and editing. All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe wild gut microbial genomes used in this study are obtained in the Figshare repository(https://doi.org/10.6084/m9.figshare.28752050). The metagenomic sample analyzed in this study are available under accession numbers PRJNA117586, which were published in our previous study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChozas M, Dashti A, Prieto-P\u0026eacute;rez L, P\u0026eacute;rez-Tanoira R, Cobo E, Bailo B, Del Palacio M, Hern\u0026aacute;ndez-Castro C, Gonz\u0026aacute;lez-Barrio D, Carmena D et al. Enterocytozoon bieneusi and Encephalitozoon intestinalis (microsporidia) in HIV-positive patients in central Spain. 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Front Immunol. 2022;13:1018567.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Enterocytozoon bieneusi, Wild Rodents, Gut Microbiota, Host-Microbe Interactions, Vitamin Synthesis, Comparative Genomics","lastPublishedDoi":"10.21203/rs.3.rs-7835059/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7835059/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003eEnterocytozoon bieneusi\u003c/em\u003e (\u003cem\u003eE. bieneusi\u003c/em\u003e) is a highly pathogenic parasite that infects immunocompromised individuals, especially HIV patients, and is a leading cause of diarrhea in these populations. It significantly impacts human health, causing severe gastrointestinal symptoms, malnutrition, and potentially life-threatening complications. However, the microbial mechanisms behind \u003cem\u003eE. bieneusi\u003c/em\u003e infection and its effects on host nutrition are not well understood. Wild rodents have long been considered a valuable model for studying human diseases due to their similar gut microbiota dynamics and immune responses to humans, making them particularly relevant for investigating parasitic infections. Here, we assembled a comprehensive catalog of 9,929 non-redundant micr obial genomes from wild rodent gut metagenomes and evaluated their potential for B vitamin and vitamin K\u003csub\u003e2\u003c/sub\u003e biosynthesis using comparative functional genomics. We identified 2,307 genomes encoding complete pathways for \u003cem\u003ede novo\u003c/em\u003e biosynthesis of at least one essential vitamin, though no single genome encoded all pathways, indicating a distributed metabolic capacity within the microbial community. Infection with \u003cem\u003eE. bieneusi\u003c/em\u003e significantly altered the microbial composition and the potential for vitamin biosynthesis, with a notable expansion of \u003cem\u003eMethanobacteriota\u003c/em\u003e and reprogramming of \u003cem\u003epyridoxine\u003c/em\u003e (vitamin B\u003csub\u003e6\u003c/sub\u003e) biosynthesis pathways. These changes reveal a functional shift in microbial metabolism in response to parasitic pressure. By elucidating the microbial basis of vitamin biosynthesis in wild rodents and the impact of \u003cem\u003eE. bieneusi\u003c/em\u003e infection on microbial functions, this study offers new insights into the role of gut microbiota in maintaining host health and nutrient provisioning under parasitic stress. Moreover, the findings will also provide valuable insights into prevention and control of \u003cem\u003eE. bieneusi\u003c/em\u003e infection in a variety of host, including humans.\u003c/p\u003e","manuscriptTitle":"Gut microbiota response to Enterocytozoon bieneusi infection: enhanced vitamin B and K 2 pathways","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-26 07:08:11","doi":"10.21203/rs.3.rs-7835059/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-09T09:10:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-04T22:32:47+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-29T10:04:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"69345643457854444696433430747652020195","date":"2025-11-24T12:55:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214372013449657159928252212504501108676","date":"2025-11-24T07:41:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T07:08:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"29430476019921968871260820995378607041","date":"2025-11-21T07:42:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94993505418994042900640199725535602190","date":"2025-11-21T07:38:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"115557124864316379499120905345082226481","date":"2025-11-14T11:52:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-14T09:59:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-14T14:08:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-14T00:41:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-14T00:40:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-10-11T12:02:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"13204261-c7a1-4d2a-b4e3-f88f607e075f","owner":[],"postedDate":"November 26th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-09T16:09:59+00:00","versionOfRecord":{"articleIdentity":"rs-7835059","link":"https://doi.org/10.1186/s12864-026-12575-4","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2026-02-05 15:59:20","publishedOnDateReadable":"February 5th, 2026"},"versionCreatedAt":"2025-11-26 07:08:11","video":"","vorDoi":"10.1186/s12864-026-12575-4","vorDoiUrl":"https://doi.org/10.1186/s12864-026-12575-4","workflowStages":[]},"version":"v1","identity":"rs-7835059","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7835059","identity":"rs-7835059","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}