Biology subjects

Schirmer, M.

Publications and source records attributed to Schirmer, M..

8 recordsLinked to original sources

bioRxiv2026

Probiotic formula intervention in infants leads to colonization and competitive strain displacement independent of IgA binding

Early-life microbiota assembly is affected by environmental exposure, diet, and immunity. We performed shotgun metagenomics sequencing of fecal samples (N=401) from a controlled infant intervention trial to evaluate how pre- and probiotic exposure affects bacterial strain dynamics, maternal-to-offspring strain transmissibility, strain persistence, and host immune responses. Species- and strain-level analyses revealed that the early-life intervention with Bifidobacterium longum subsp. infantis (BL subsp. infantis), Bifidobacterium breve, and galacto-oligosaccharides (GOS) replaced main resident strains of these species unlike breast-feeding and exclusive infant formula. BL subsp. infantis low-diversity clusters were representative of several populations and were enriched for genes linked to recombination, mobilization, and antimicrobial activity. lnterestingly, Bifidobacterium bifidum but not Bifidobacterium longum or B. breve was heavily targeted by mucosal lgA, regardless of feeding type. These findings suggest that early-life pro- and prebiotic interventions promote colonization of specific dominant strains, potentially by outcompeting and displacing existing strains, independently of host immune responses.

microbiology↗

bioRxiv2026

MetaGEAR Explorer: Rapid interactive searches and cross-cohort analyses of microbiome gene associations in disease

Background: Investigating functional gut microbiome signals remains challenging due to the large scale and sparsity of gene-level metagenomic profiles and reproducibility of microbial gene associations across microbiome studies is limited. Further, interactive tools for phenotype-aware cross-study meta-analysis are currently lacking. Results: We developed MetaGEAR Explorer, a web platform for interactive and programmatic gene-centric analyses that enables users to rapidly search genes of interest across 33 million gene families from 24 metagenomic cohorts spanning inflammatory bowel disease (IBD), colorectal cancer (CRC), and healthy individuals. To demonstrate our platform's capabilities, we first used narG, a well-characterized nitrate reductase gene in Enterobacteriaceae (including Escherichia coli and Klebsiella species), to evaluate the detection of remotely related, disease-relevant homologs. While sequence-based searches using the E. coli narG gene as a query failed to capture the known diversity of narG, MetaGEAR Explorer's domain-based search expansion identified 160 NarG-like gene families with consistent IBD enrichment across cohorts. This included narG homologs from Veillonella parvula and Veillonella atypica that have been recently implicated in intestinal inflammation. We further applied MetaGEAR Explorer to investigate the underexplored diversity of clbS, the self-protection gene against the bacterial genotoxin colibactin, which is implicated in CRC tumorigenesis. The canonical clbS is part of the E. coli clb operon, which produces colibactin. Our analysis showed that E. coli-associated clbS was rare in healthy individuals but increased in disease (1.85% in Healthy, 6.21% in IBD, and 7.62% in CRC). In contrast, domain-based expansion revealed widespread clbS-domain (DUF1706) homologs, present in 95.15% of healthy individuals, while disease-associated contributors shift from commensal Clostridia to Gammaproteobacteria. Notably, Proteus mirabilis was identified as a novel potential ClbS-like carrier enriched in IBD. Furthermore, much of this prevalence was driven by a single unclassified gene family, present in 63.40% of healthy individuals. Conclusions: MetaGEAR Explorer facilitates rapid cross-cohort functional meta-analyses and can identify reproducible, biologically interpretable microbial gene signatures in IBD and CRC, such as newly identified sequence-domain dynamics in nitrate respiration and colibactin self-protection.

bioinformatics↗

bioRxiv2026

Extensive genomic diversity in Desulfovibrio species reveals species-specific functional traits associated with disease

Desulfovibrio spp. are associated with inflammatory diseases and human health, yet limited representative genomes and isolates hinder our understanding of their role in disease. Here, we assembled a comprehensive database of 2,658 Desulfovibrio genomes across 90 diseases and 32 countries, including 24 human isolates. Genomic analyses showed extensive species diversity and revealed disease-associated functional traits, including flagellin and virulence genes (i.e. ureases). Flagellin-mediated Toll-like receptor 5 activation was species-specific and D. desulfuricans flagellin downregulated TGF-beta signalling in murine small intestinal organoids, suggesting impaired immune tolerance. Additionally, we investigated genomic capacity for hydrogen sulfide (H2S) production, a main Desulfovibrio metabolite. While health- and disease-associated Desulfovibrio spp. mainly encoded dissimilatory sulfate reduction, tetrathionate metabolism-encoding bacteria were exclusively detected in inflammatory bowel diseases, including Proteus mirabilis and Morganella morganii. Overall, our study provides a comprehensive genomic Desulfovibrio resource and identifies new links associating strain variation, functional traits and H2S-production with inflammatory diseases.

genomics↗

bioRxiv2025

Gene-centric metagenomic analyses reveal microbiome functional insights into diseases

The microbiome encodes millions of genes; however, understanding their role in human health remains challenging. Here, we developed MetaGEAR, a gene-centric analysis framework for metagenomic data. MetaGEAR constructs cohort-specific databases for efficient retrieval of gene annotations, abundances, and co-localization, while providing enhanced taxonomic resolution by integrating reference- and assembly-based approaches. This is combined with a Metagenomic Assembled Graph (MAGraph) capturing gene neighborhood information. Using MetaGEAR, we built a multi-cohort database comprising >33 million gene families to investigate microbiome functionality across 24 cohorts of inflammatory bowel disease, colorectal cancer, and healthy populations and identified disease signature genes. Furthermore, the MAGraph revealed mobile genetic elements acting as hubs for tetracycline resistance spreading among Enterococcus, Streptococcus, and Veillonella species. Also, a duplicated nitrate reduction operon in Klebsiella pneumoniae was linked to differential gene expression under stress and virulence-inducing conditions. In summary, gene-centric metagenomic analyses reveal important insights into microbiome functionality in diseases.

microbiology↗

bioRxiv2025

Microbial oral-gut translocation in advanced chronic liver disease is linked to exacerbation of intestinal barrier dysfunction and hepatic fibrosis

While microbiome perturbations are associated with advanced chronic liver disease (ACLD), microbial disease mechanisms are poorly understood. Using multi-omics analyses of paired saliva and faecal samples from an ACLD cohort, we identified next-to-identical oral and gut bacterial strains (including Veillonella and Streptococcus spp.) which increased in absolute abundance in the gut of ACLD patients. These translocators uniquely encoded a collagenase-like proteinase (prtC) with the potential for gut barrier disruption and prtC faecal abundance was a robust ACLD biomarker (auPR=0.91). CCl4-treated mice inoculated with Veillonella and Streptococcus prtC-encoding patient isolates showed exacerbation of gut barrier impairment and hepatic fibrosis. Furthermore, faecal collagenase activity was increased in ACLD patients and experimentally confirmed for the prtC gene from translocating Veillonella parvula. Overall, our study establishes mechanistic links between oral-gut translocation and ACLD pathobiology, and identifies the oral microbiome as an important contributing factor with potential for microbial diagnostics and therapeutics.

microbiology↗

bioRxiv2023

Diurnal rhythmicity of fecal microbiota and metabolite profiles in the first year of life: a randomized controlled interventional trial with infant formula

Microbiota assembly in the infant gut is influenced by time and duration of dietary exposure to breast-milk, infant formula and solid foods. In this randomized controlled intervention study, longitudinal sampling of infant stool (n=998) showed similar development of fecal bacterial communities (16S rRNA/shallow metagenomics sequencing) between formula- and breast-fed infants during the first year of life (N=210). Infant formula supplemented with galacto-oligosaccharides (GOS) was most efficient to sustain high levels of bifidobacteria compared to formula containing B. longum and B. breve or placebo. In addition to primary endpoints, metabolite and bacterial profiling revealed 24-hour oscillations and data integration identified circadian networks. Rhythmicity in bacterial diversity, specific taxa and functional pathways increased with age and was strongest following breast-feeding and GOS-supplementation. Circadian rhythms in dominant taxa were discovered ex-vivo in a chemostat model. Hence, microbiota rhythmicity develops early in life, likely via bacterial intrinsic clock mechanism and is affected by diet.

microbiology↗

bioRxiv2020

Population Structure Discovery in Meta-Analyzed Microbial Communities and Inflammatory Bowel Disease

Microbial community studies in general, and of the human microbiome in inflammatory bowel disease (IBD) in particular, have now achieved a scale at which it is practical to associate features of the microbiome with environmental exposures and health outcomes across multiple large-scale populations. This permits the development of rigorous meta-analysis methods, of particular importance in IBD as a means by which the heterogeneity of disease etiology and treatment response might be explained. We have thus developed MMUPHin (Meta-analysis Methods with a Uniform Pipeline for Heterogeneity in microbiome studies) for joint normalization, meta-analysis, and population structure discovery using microbial community taxonomic and functional profiles. Applying this method to ten IBD cohorts (5,151 total samples), we identified a single consistent axis of microbial associations among studies, including newly associated taxa such as Acinetobacter and Turicibacter detected due to the sensitivity of meta-analysis. Linear random effects models further revealed associations with medications, disease location, and interaction effects consistent within and between studies. Finally, multiple unsupervised clustering metrics and dissimilarity measures agreed on a lack of discrete microbiome "types" in the IBD gut microbiome. These results thus provide a benchmark for consistent characterization of the IBD gut microbiome and a general framework applicable to meta-analysis of any microbial community types.

genomics↗

bioRxiv2019

Brain connectivity measures improve modeling of functional outcome after acute ischemic stroke

BackgroundThe ability to model long-term functional outcomes after acute ischemic stroke (AIS) represents a major clinical challenge. One approach to potentially improve prediction modeling involves the analysis of connectomics. The field of connectomics represents the brains connectivity as a graph, whose topological properties have helped uncover underlying mechanisms of brain function in health and disease. Specifically, we assessed the impact of stroke lesions on rich club (RC) organization, a high capacity backbone system of brain function.\n\nMethodsIn a hospital-based cohort of 41 AIS patients, we investigated the effect of acute infarcts on the brains pre-stroke RC backbone and post-stroke functional connectomes with respect to post-stroke outcome. Functional connectomes were created utilizing three anatomical atlases and characteristic path-length (L) was calculated for each connectome. The number of RC regions (NRC) affected were manually determined using each patients diffusion weighted image (DWI). We investigated differences in L with respect to outcome (modified Rankin Scale score (mRS); 90-days; poor: mRS>2) and the National Institutes of Health Stroke Scale (NIHSS; early: 2-5 days; late: 90-day follow-up). Furthermore, we assessed the effect of including NRC and L in outcome models, using linear regression and assessing the explained variance (R2).\n\nResultsOf 41 patients (mean age (range): 70 (45-89) years), 61% were male. There were differences in L between patients with good and poor outcome (mRS). Including NRC in the backward selection models of outcome, R2 increased between 1.3- and 2.6-fold beyond that of traditional markers (age and acute lesion volume) for NIHSS and mRS.\n\nConclusionIn this proof-of-concept study, we showed that information on network topology can be leveraged to improve modeling of post-stroke functional outcome. Future studies are warranted to validate this approach in larger prospective studies of outcome prediction in stroke.

neuroscience↗