Biology subjects

Wilmes, P.

Publications and source records attributed to Wilmes, P..

At least 19 recordsLinked to original sources

bioRxiv2026

A microbiota-derived protease links phage susceptibility to host epithelial responses

Bacteriophages are major ecological drivers of gut microbial ecology, yet whether bacterial mechanisms that determine phage susceptibility have consequences for the mammalian host remains poorly understood. Here, we identify dipeptidyl peptidase 11 (Dpp11a), the predominant active serine protease of the prevalent gut commensal Phocaeicola vulgatus, as an unexpected bacterial defence factor. Dpp11a protects against environmental proteases and confers resistance to bacteriophage infection. Metatranscriptomic analyses further reveal increased expression of both dpp11a and P. vulgatus-associated phage transcripts in ulcerative colitis stool samples, indicating that both components of this interaction are transcriptionally active in disease-associated human microbiomes. Using the microfluidic gut-on-a-chip co-culture model HuMiX, we show that the absence of Dpp11 is accompanied by altered epithelial tight-junction remodelling during phage-bacterial infection. Together, our findings reveal that the consequences of bacterial phage defence can extend beyond phage-bacterium interactions to the mammalian epithelium.

microbiology↗

bioRxiv2026

MAP: a comprehensive pipeline for mobilome annotation and cargo gene characterisation in prokaryotic (meta)genomic assemblies

Mobile genetic elements (MGEs) drive horizontal gene transfer in prokaryotes, disseminating antimicrobial resistance genes (ARGs), virulence factors (VFs) and biosynthetic gene clusters (BGCs). Given their importance, there is a pressing need for a single, open source tool that annotates the MGE repertoire together with its functional cargo. We present MAP (Mobilome Annotation Pipeline), a Nextflow pipeline that predicts plasmids, viral sequences, prophages, integrons, insertion sequences, transposons, integrative and conjugative elements, and non-autonomous compositional outliers, removes redundant predictions, and labels genes within MGE boundaries. MAP outputs a GFF3 formatted file, a FASTA file of MGE sequences, and a combined report placing ARGs, VFs, toxins and BGCs in their mobilome context, enabling the identification of composite elements such as ARG-carrying integrons within plasmids. We demonstrate its use on genomes from the MGnify soil genome catalogue.

bioinformatics↗

bioRxiv2025

Evaluation of statistical approaches for differential metaproteomics

BackgroundMetaproteomics characterizes and compares molecular phenotypes of organisms in communities by comprehensively analyzing their protein expression profiles using statistical methods. However, not all statistical methods are suitable for determining differentially abundant protein groups in metaproteomic analyses. Statistical challenges in metaproteomics include: data sparsity, non-normality, compositionality, and large between-sample variability. These challenges can potentially be addressed with several data processing steps, including imputation, normalization, transformation, and selection of the appropriate statistical tests. The potential combinations of different processing methods create a complex matrix of analysis options and it is currently unclear how these combinations impact the results of statistical tests on metaproteomic data. ResultsTo determine what data processing methods and statistical tests are best for identifying differentially abundant proteins in metaproteomics datasets, we generated a set of thirteen metaproteomic samples with known compositions, known differences, and differing levels of complexity. These defined metaproteomes address the general challenges outlined above, using various scenarios in metaproteomic data analyses. We compared over 110 different statistical analysis combination options, including regression-based tools, general statistics inference, and machine learning techniques. We found that several combinations within the frameworks of limma, edgeR, MaAslin2, custom linear and Bayesian linear models, and random forests all offer suitable evaluation options. ConclusionsWe highlight key recommendations for differential expression analysis in metaproteomics. Our work enables improved assessment of statistical methods for metaproteomics by establishing a framework for testing statistical approaches, including comprehensive raw mass spectrometry data and reproducible benchmarking code.

molecular biology↗

bioRxiv2025

A conserved sRNA regulates mucin adhesion and gut colonization across the Enterococcaceae

Enterococci, particularly E. faecalis, can survive in diverse settings within and outside human hosts. The capacity of E. faecalis to colonize these locations relies on its ability to adapt by altering gene expression in response to environmental exposures. One mechanism for quickly altering gene expression is through regulation by small noncoding RNAs (sRNAs); sRNAs can regulate one or many target genes and either up- or down-regulate transcript stability and protein expression. While many sRNAs have been predicted in E. faecalis, few have experimentally established target mRNAs or physiological functions. Here, we investigate the targets, function, and mechanism of Enterococcus sRNA 84. We found that sRNA 84 is conserved within the family Enterococcaceae, suggesting that it plays a role in the regulation of core genes and functions. RNA sequencing and proteomic analysis revealed that the absence of sRNA 84 led to downregulation of many cell surface proteins, including mucin-binding proteins. Consistent with these findings, an sRNA 84 knockout strain had reduced binding to mucin in vitro and impaired intestinal colonization of specific-pathogen-free mice. Taken together, these data support a model whereby sRNA 84 upregulates cell surface adhesins, which subsequently facilitate host colonization through binding to mucin. sRNA 84 is one of the first sRNAs in enterococci with demonstrated targets and function. This finding establishes the conserved sRNA 84 as a potential key regulator of enterococcal host adaptation, providing insight into how these organisms adapt their gene expression to survive both within and outside animal hosts.

microbiology↗

bioRxiv2025

Phylum-wide propionate degradation and its potential connection to poly- γ-glutamate biosynthesis in Candidatus Cloacimonadota

The candidate phylum Cloacimonadota is frequently detected in anaerobic environments such as anaerobic digestion (AD) reactors, hydrothermal vents, and deep-sea sediments, yet its metabolism remains poorly understood due to the lack of cultured representatives. Metagenomic evidence suggests capacities for amino acid fermentation, cellulose degradation, and production of carbohydrate-active enzymes, with particular interest in their presumed role in syntrophic propionate oxidation (SPO), a key bottleneck in AD. However, a complete methylmalonyl-CoA (mmc) pathway, central to SPO, has not been previously identified in Cloacimonadota genomes. Here, we report results from a lab-scale anaerobic baffled reactor fed with sugar beet pulp, where a sharp increase in an uncultured Cloacimonadota OTU coincided with recovery of methanogenesis and enhanced methane production. Metagenomic and metatranscriptomic analyses enabled metabolic reconstruction of this OTU, complemented by a curated database of 47 genome-resolved Cloacimonadota species. Comparative genomics revealed conserved protein clusters indicative of an alternative mmc pathway, suggesting that this variant of the SPO pathway is a widespread, phylum-specific trait potentially linked to protein degradation and poly-{gamma}-glutamate biosynthesis. Network analysis identified the methanogenic archaeon Methanothrix as a primary syntrophic partner, an interaction further supported by propionate-fed enrichment cultures showing co-occurrence of Cloacimonadota and Methanothrix species. Our study sheds light on the Cloacimonadota metabolism, advancing our understanding of their ecological roles and potential for biotechnological applications.

microbiology↗

bioRxiv2025

Integrative Analysis of the Mouse Cecal Microbiome Across Diet, Age, and Metabolic State in the Diverse BXD Population

BackgroundThe gut microbiota adapts to and shapes the hosts metabolic state through affecting circulating metabolites and consequent gene regulatory networks, resulting in systemic influences in diverse organs via connections such as the gut-liver axis. Numerous variables such as diet, age, and host genetics modulate the composition of the gut microbiome, but their interactions and specific associative and mechanistic links to host molecular phenotypes remain incompletely unannotated. Integrated multi-omics approaches in genetically diverse populations offer an opportunity to dissect these interactions and identify predictive microbial signatures for host phenotypes, such as body weight, and molecular associations with gene expression pathways in gut and liver. ResultsWe sequenced, aligned, and integrated the cecal metagenome, metatranscriptome, and host transcriptome from 232 mice across 175 distinct cohorts according to a low fat chow diet (CD) or a high-fat diet (HF), four adult ages (between roughly 180 to 730 days of age), and 43 distinct genotypes (inbred BXD strains). Genetics and diet exerted the strongest influence on microbiota abundance and activity, followed by age. HF feeding significantly reduced diversity across all ages and all genotypes, altering >300 species. Machine learning models based on microbial profiles reliably predicted body weight within dietary group (AUC = 0.84 for CD, 0.79 for HF) and chronological age (AUC = 0.84), with model performance rising of age prediction rising to 0.95 when integrating top microbial features with liver proteomics. Network analyses of expression data revealed links between genes, pathways, and specific microbes, including a negative association between cecal Ido1 expression and short-chain fatty acid (SCFA)-producing Lachnospiraceae, suggesting dietary fat may modulate host tryptophan metabolism through microbiota shifts. ConclusionsWhole metagenome and metatranscriptome sequencing approaches have massively expanded the landscape of microbiome analysis compared to earlier short-read 16S analyses. The resulting datasets quantify hundreds of uniquely identifiable microbes, which can be used to create sets of highly predictive microbial biomarkers for aging and obesity. When trained on controlled mouse populations, these results demonstrate that microbiome profiling can achieve high predictive capacity (AUC = 0.95 with multi-omics integration) for complex readouts such as age and body weight (AUC = 0.84), even considering genetic and dietary variation, establishing a framework for biomarker development. While at present many bacteria are still functionally unannotated at the species level, multi-omics approaches -- including gene expression from the host tissues -- provide insights into the functional associations of specific taxa in the microbiome.

microbiology↗

bioRxiv2025

Acinetobacter enrichment shapes composition and function of the bacterial microbiota of field-grown tomato plants

Tomato is a staple crop and an excellent model to study host-microbiota interactions in the plant food chain. In this study we describe a lab-in-the-field approach to investigate the microbiota of field-grown tomato plants. High-throughput amplicon sequencing revealed a three-microhabitat partition, phyllosphere, rhizosphere and root interior, differentiating host-associated communities from the environmental microbiota. An individual bacterium, classified as Acinetobacter sp., emerged as a dominant member of the microbiota at the plant-soil continuum. To gain insights into the functional significance of this enrichment, we subjected rhizosphere specimens to shotgun metagenomics. Similar to the amplicon sequencing survey, a microhabitat effect defined by a set of rhizosphere-enriched functions was identified. Mobilisation of mineral nutrients, as well as adaptation to salinity and polymicrobial communities, including antimicrobial resistance genes (ARGs), emerged as a functional requirement sustaining metagenomic diversification. A metagenome-assembled genome (MAG) representative of Acinetobacter calcoaceticus was retrieved and metagenomic reads associated to this species identified a functional specialisation for plant-growth promotion traits (PGPTs), such as phosphate solubilization, siderophores production and reactive oxygen species detoxification, which were similarly represented in across tomato genotype-independent fashion. Our results revealed that the enrichment of a beneficial bacterium capable of alleviating plants abiotic stresses appears decoupled from ARGs facilitating microbiota persistence at the root-soil interface. IMPORTANCETomatoes are at centre-stage in global food security due to their high nutritional value, widespread cultivation, and versatility. Tomatoes provide essential vitamins and minerals, contribute to diverse diets, and support farmer livelihoods, making them a cornerstone of sustainable food systems. Beyond direct dietary benefits, the intricate relationship between tomatoes, their associated microbiota, and ARG is increasingly recognised. Tomato plants host diverse microbial communities in association with their organs, which influence plant health and productivity. Crop management impacts on composition and function of these communities, contributing to the prevalence of ARG in the soil and on the plants themselves. These genes can potentially transfer to human pathogens, posing a food safety and public health risk. Understanding these complex interactions is critical for developing sustainable agricultural practices capable of mitigating the impact of climatic modifications and the global threat of antimicrobial resistance.

plant biology↗

bioRxiv2025

Critical Assessment of MetaProteome Investigation 2 (CAMPI-2): Multi-laboratory assessment of sample processing methods to stabilize fecal microbiome for functional analysis

BackgroundFecal samples are widely used as a proxy for studying gut microbiome composition in both human and animal research. Fecal metaproteomics provides valuable insights by tracking changes in the relative abundance of microbial taxa and their protein functions. To ensure reliable results, it is crucial to minimize alterations in the metaproteome occurring from sample collection to protein extraction. Therefore, employing effective stabilization methods is essential to preserve the integrity of the fecal metaproteome from sample collection to laboratory analysis, particularly over long distances or when rapid freezing options are not readily available. In line with these needs, the second edition of the Critical Assessment of MetaProteome Investigation (CAMPI-2) was specifically focused on testing sample stabilization protocols to be applied before metaproteomic analysis. ResultsThis collaborative multicenter study assessed the ability of five different stabilization methods, based on two commercial devices and three specific reagents (acetone, lithium dodecyl sulfate, and an RNAlater-like buffer), respectively, to stabilize the fecal metaproteome during room-temperature storage (14 days) and shipment to mass spectrometry facilities. The five methods were tested simultaneously by eight different laboratories across Europe, using aliquots from the same fecal sample. After protein extraction and digestion, duplicate aliquots of the resulting peptides were analyzed independently by two mass spectrometry facilities at distinct international locations. Analysis of the mass spectrometric data using two different search engines revealed that the fecal metaproteome profile differed considerably depending on the stabilization method used in terms of richness, alpha and beta diversity, reproducibility, and quantitative distribution of main taxa and functions. Although each method showed unique strengths and weaknesses, a commercial swab-based device stood out for its remarkable reproducibility and ranked highest for most of the metrics measured. ConclusionsCAMPI-2 allowed a robust evaluation of five different methods for preserving fecal metaproteome samples. The present investigation provides useful data for the design of metaproteomics and multi-omics studies where fecal sampling cannot be immediately followed by long-term storage at -80{degrees}C. Further optimization of the tested protocols is necessary to improve stabilization efficiency and control bias in the taxonomic and functional profile of the gut microbiome.

microbiology↗

bioRxiv2024

Human gut microbiome gene co-expression network reveals a loss in taxonomic and functional diversity in Parkinson's disease

Alterations of gut microbiome structure have been observed in a panoply of human diseases including neurodegeneration. However, the ecological and functional deficits of microbiome dysbiosis have yet to be understood. Here, using integrated multi-omics (metagenomics and metatranscriptomics), we resolve microbiome gene co-expression networks in individuals with Parkinsons disease (PD) and healthy individuals. We uncover network modules with high closeness and degree centrality that represent core ecological functions, and identify key features lost in PD. More specifically, we observe a significant depletion in specific functions including secondary bile acid biosynthesis and flagellar assembly (FA) in PD. Strikingly, most hub genes, particularly those involved in bacterial microcompartments (BMCs) and FA, are predominantly found in healthy individuals. Blautia and Anaerobutyricum genera are the main contributors to these functions, showing significantly lower expression of BMC genes in PD. Additionally, we identify a strong correlation between the expression of BMC and FA genes, but also an apparent dysregulation in cross feeding between commensals in PD. Importantly, gene expression in PD was tied to reduced diversity in expressed genes, whereas in healthy individuals, higher expression levels were linked to higher diversity. Our findings reveal disruptions in key gut metabolic functions at both functional and taxonomic levels, potentially driving disease progression. Notably, we identify crucial microbiome-wide ecological features that should be restored in future gut microbiome rewilding efforts.

microbiology↗

bioRxiv2024

Integrated multi-omics highlights alterations of gut microbiome functions in prodromal and idiopathic Parkinson's disease

Parkinsons disease (PD) is associated with gut microbiome shifts, but the functional consequences remain unclear. Here, we use an integrated multi-omics approach to compare the gut microbiomes of individuals with PD and prodromal PD as well as healthy individuals. After analyzing each omics, meta-metabolomic was selected to inform the analysis as it represents the most discriminatory and robust ome. We identified 11 metabolites that were differentially abundant between the groups, amongst which {beta}-glutamate was increased in PD and prodromal PD, and correlated with the transcriptional activities of Methanobrevibacter smithii and Clostridium spp. We identified decreases in transcripts, but not in gene abundances, related to glutamate metabolism, bile acids, chemotaxis and flagellar assembly in PD, particularly in keystone genera such as Roseburia, Agathobacter and Blautia. Our findings, integrated into the Expobiome map, reveal multifactorial microbiome alterations which converge with PD pathways. Our study highlights the importance of investigating the gut microbiomes functional dimensions to better resolve microbiome-host interactions in health and disease.

systems biology↗

bioRxiv2024

PathoFact 2.0: An Integrative Pipeline for Predicting Antimicrobial Resistance Genes, Virulence Factors, Toxins and Biosynthetic Gene Clusters in Metagenomes

SummaryAntimicrobial resistance genes (ARGs) and virulence factors (VFs) are central contributors to the global health crisis surrounding drug-resistant infections. PathoFact, a bioinformatics pipeline introduced in 2021, provides insights into ARGs, VFs, and bacterial toxins from metagenomic data. However, recent advancements in bioinformatics highlight the need for an updated version of PathoFact. We introduce PathoFact 2.0, an enhanced pipeline for improved ARG, VF, and toxin prediction. Key updates include an updated machine learning (ML) model for VF identification, a new ML model for toxin identification, expanded hidden Markov model profiles, and the antiSMASH 7.0 integration for predicting biosynthetic gene clusters. These upgrades make PathoFact 2.0 a more powerful, user-friendly platform for predicting microbiome-based pathogenicity and resistance, offering a crucial tool for better understanding and addressing the challenges posed by antimicrobial resistance and infectious diseases. Availability and ImplementationPathoFact 2.0 is available for download at https://gitlab.lcsb.uni.lu/ESB/PathoFact2/.

bioinformatics↗

bioRxiv2024

Fetal programming by the maternal microbiome of offspring behavior, and DNA methylation and gene expression within the hippocampus

BackgroundThe microorganisms colonizing the gastrointestinal tract of animals, collectively referred to as the gut microbiome, affect numerous host behaviors dependent on the central nervous system (CNS). Studies comparing germ-free mice to normally colonized mice have demonstrated influences of the microbiome on anxiety-related behaviors, voluntary activity, and gene expression in the CNS. Additionally, there is epidemiologic evidence supporting an intergenerational influence of the maternal microbiome on neurodevelopment of offspring and behavior later in life. There is limited experimental evidence however directly linking the maternal microbiome to long-term neurodevelopmental outcomes, or knowledge regarding mechanisms responsible for such effects. ResultsHere we show that that the maternal microbiome has a dominant influence on several offspring phenotypes including anxiety-related behavior, voluntary activity, and body weight. Adverse outcomes in offspring were associated with features of the maternal microbiome including bile salt hydrolase activity gene expression (bsh), abundance of certain bile acids, and hepatic expression of Slc10a1. In cross-foster experiments, offspring resembled their birth dam phenotypically, despite faithful colonization in the postnatal period with the surrogate dam microbiome. Genome-wide methylation analysis of hippocampal DNA identified microbiome- associated differences in methylation of 196 loci in total, 176 of which show conserved profiles between mother and offspring. Further, single-cell transcriptional analysis revealed accompanying differences in expression of several differentially methylated genes within certain hippocampal cell clusters, and vascular expression of genes associated with bile acid transport. Inferred cell-to-cell communication in the hippocampus based on coordinated ligand-receptor expression revealed differences in expression of neuropeptides associated with satiety. ConclusionsCollectively, these data provide proof-of-principle that the maternal gut microbiome has a dominant influence on the neurodevelopment underlying certain offspring behaviors and activities, and selectively affects genome methylation and gene expression in the offspring CNS in conjunction with that neurodevelopment.

microbiology↗

bioRxiv2023

The response to ketogenic diet in colorectal cancer is mediated by lasting functional alterations of the gut microbiome

Colorectal cancer (CRC) patients have been shown to possess an altered gut microbiome. Diet is a well-established modulator of the microbiome, and thus, dietary interventions might have a beneficial effect on CRC. An attenuating effect of the ketogenic diet (KD) on CRC cell growth has been previously observed, however the role of the gut microbiome in driving this effect remains unknown. Here, we describe a reduced colonic tumor burden upon KD consumption in a CRC mouse model with a humanized microbiome. Importantly, we demonstrate a causal relationship through microbiome transplantation into germ-free mice, whereby alterations in the gut microbiota were maintained in the absence of continued selective pressure from the KD. Specifically, we identify a shift toward bacterial species that produce stearic acid in ketogenic conditions, whereas consumers were depleted, resulting in elevated levels of free stearate in the gut lumen. This microbial product demonstrated tumor-suppressing properties by inducing apoptosis in cancer cells and decreasing colonic Th17 immune cell populations. Taken together, the beneficial effects of the KD are mediated through alterations in the gut microbiome, including, among others, increased stearic acid production, which in turn significantly reduces intestinal tumor growth.

cancer biology↗

bioRxiv2023

Functional assignment of gut-specific archaeal proteins in the human gut microbiome

The human gastrointestinal tract contains diverse microbial communities, including archaea. Among them, Methanobrevibacter smithii represents a highly active and clinically relevant methanogenic archaeon, being involved in gastrointestinal disorders, such as IBD and obesity. Herein, we present an integrated approach using sequence and structure information to improve the annotation of M. smithii proteins using advanced protein structure prediction and annotation tools, such as AlphaFold2, trRosetta, ProFunc, and DeepFri. Of an initial set of 873 481 archaeal proteins, we found 707 754 proteins exclusively present in the human gut. Having analysed archaeal proteins together with 87 282 994 bacterial proteins, we identified unique archaeal proteins and archaeal-bacterial homologs. We then predicted and characterized functional domains and structures of 73 unique and homologous archaeal protein clusters linked the human gut and M. smithii. We refined annotations based on the predicted structures, extending existing sequence similarity-based annotations. We identified gut-specific archaeal proteins that may be involved in defense mechanisms, virulence, adhesion, and the degradation of toxic substances. Interestingly, we identified potential glycosyltransferases that could be associated with N-linked and O-glycosylation. Additionally, we found preliminary evidence for interdomain horizontal gene transfer between Clostridia species and M. smithii, which includes sporulation stage V proteins AE and AD. Our study broadens the understanding of archaeal biology, particularly M. smithii, and highlights the importance of considering both sequence and structure for the prediction of protein function.

microbiology↗

bioRxiv2023

Cross-domain interactions induce community stability to benthic biofilms in proglacial streams

Cross-domain interactions are an integral part of the success of complex biofilms in natural environments. Here, we report on cross-domain interactions in biofilms of streams draining proglacial floodplains in the Swiss Alps. These streams, as a consequence of the retreat of glaciers, are characterized by multiple environmental gradients and stability that depend on the time since deglaciation. We estimate co-occurrence of prokaryotic and eukaryotic communities along this gradient and show that key community members have disproportionate effects on the stability of co-occurrence networks. The topology of the networks was similar independent of environmental gradients and stability. However, network stability was higher in the streams draining proglacial terrain that was more recently deglaciated. We find that both pro- and eukaryotes are central to the stability of these networks, which fragment upon the removal of both pro- and eukaryotic taxa. These keyplayers are not always abundant, suggesting an underlying functional component to their contributions. Thus, we show that there is a key role played by individual taxa in determining microbial community stability of glacier-fed streams.

microbiology↗

bioRxiv2022

Forecasting of a complex microbial community using meta-omics

Microbial communities are complex assemblages whose dynamics are shaped by abiotic and biotic factors. A major challenge concerns correctly forecasting the community behaviour in the future. In this context, communities in biological wastewater treatment plants (BWWTPs) represent excellent model systems, because forecasting them is required to ultimately control and operate the plants in a sustainable manner. Here, we forecast the microbial community from the water-air interface of the anaerobic tank of a BWWTP via longitudinal meta-omics (metagenomics, metatranscriptomics and metaproteomics) data covering 14 months at weekly intervals. We extracted all the available time-dependent information, summarised it in 17 temporal signals (explaining 91.1% of the temporal variance) and linked them over time to rebuild the sequence of ecological phenomena behind the community dynamics. We forecasted the signals over the following five years and tested the predictions with 21 extra samples. We were able to correctly forecast five signals accounting for 22.5% of the time-dependent information in the system and generate mechanistic predictions on the ecological events in the community (e.g. a predation cycle involving bacteria, viruses and amoebas). Through the forecasting of the 17 signals and the environmental variables readings we reconstructed the gene abundance and expression for the following 5 years, showing a nearly perfect trend prediction (coefficient of determination [≥] 0.97) for the first 2 years. The study demonstrates the maturity of microbial ecology to forecast composition and gene expression of open microbial ecosystems using year-spanning interactions between community cycles and environmental parameters.

microbiology↗

bioRxiv2022

Altered infective competence of the human gut microbiome in COVID-19

ObjectivesInfections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. DesignWe used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group. ResultsWe found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19 positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19 positive individuals compared to healthy controls. ConclusionOur analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients.

microbiology↗

bioRxiv2022

Multi-omics analysis of mouse fecal microbiome reveals supplier-dependent functional differences and novel metagenome-assembled genomes

Host genetics, sex, and other within-source factors have been associated with characteristic effects on the fecal microbiome in mice, however, the commercial source of mice remains the dominant factor. Increasing evidence indicates that supplier-specific microbiomes in particular confer differences in disease susceptibility in models of inflammatory conditions, as well as baseline behavior and body morphology. However, current knowledge regarding the compositional differences between suppliers is based on 16S rRNA amplicon sequencing data, and functional differences between these communities remain poorly defined. Here, we applied a meta-omic (metagenomic and metatranscriptomic) approach to biomolecules (DNA/RNA) extracted from murine fecal samples representative of two large U.S. suppliers of research mice, which differ in composition, and influence baseline physiology and behavior as well as disease severity in mouse models of intestinal disease. We reconstructed high-quality metagenome-assembled genomes (MAGs), frequently containing genomic content unique to each supplier. These differences were observed both within pangenomes of dominant taxa as well as the epibiont Saccharimonadaceae. Additionally, transcriptional activity and pathway analyses revealed key functional differences between the metagenomes associated with each supplier, including differences in carbohydrate enzyme activity and dissimilatory sulfate reduction by sulfate-reducing bacteria (SRB). These data provide a detailed characterization of the baseline differences in the fecal metagenome of laboratory mice from two U.S. commercial suppliers suggesting that these functional differences are influenced by differences in the initial inoculum of colony founders, as well as additional taxa gained during growth of the production colony.

microbiology↗