Biology subjects

Schmidt, T. S.

Publications and source records attributed to Schmidt, T. S..

15 recordsLinked to original sources

bioRxiv2026

A global genomic survey of prokaryotic carbon fixation reveals an oxygen-tolerant rTCA cycle in the surface ocean

Autotrophic carbon fixation, the conversion of inorganic carbon into biomass, underpins life on Earth. Prokaryotes can carry out this process via at least seven biochemically distinct pathways, yet the phylogenetic and environmental distribution of most remains poorly resolved. Screening approximately 40 billion genes from reference genomes, metagenome-assembled genomes (MAGs) and unbinned metagenomic contigs, we provide a global assessment of the phylogeny and ecophysiology of prokaryotic autotrophs. Most pathway marker genes occurred in unbinned contigs and low-quality MAGs, representing phylogenetically distinct lineages absent from isolate genomes and quality filtered MAGs. Established autotrophs accounted for the large majority of pathway detections in quality filtered MAGs, largely recapitulating known biology from cultivated model organisms. Against this backdrop, the reductive TriCarboxylic Acid (rTCA) cycle, long considered restricted to anoxic environments, was detected in three phylogenetically distinct Campylobacterota lineages from oxygenated surface seawater, suggesting a previously unrecognized and unexpected niche for this pathway. We show that all three MAGs share an enzyme variant, previously described in other oxygen-tolerant lineages, that likely underlies their presence in the oxygenated surface ocean. Read mapping across global ocean metagenomes indicates that the organisms carrying it could be far more widespread than the scarcity of recovered MAGs alone would suggest. Together, these findings illustrate that the current view of global autotrophic carbon fixation is largely shaped by what genome-resolved methods can readily recover, while the true phylogenetic and ecological distribution of autotrophic carbon fixation appears to be much broader.

microbiology↗

bioRxiv2026

microntology: a lightweight, data-driven controlled vocabulary to describe Earth's microbial habitats

SummaryWe introduce microntology v1.0, a pragmatic controlled vocabulary of 148 terms to describe microbial habitats and lifestyles, and provide manually curated microntology annotations for >300k metagenomic samples from public repositories. Data Availabilitymicrontology controlled vocabulary terms and term hierarchies 1, and curated annotations for 305,626 metagenomic samples 2 are available via Zenodo and as supplemental tables S1 and S2. User feedback, suggestions and bug reports are welcome under https://github.com/grp-schmidt/microntology/issues.

bioinformatics↗

bioRxiv2025

A novel approach to Caudoviricetes taxonomy utilising whole proteome structure-structure comparison

Viral proteins often evolve so rapidly that sequence similarity is lost even among conserved functional genes, complicating phylogenetic analysis and classification. This challenge is acute for Caudoviricetes, a highly diverse class of dsDNA tailed bacteriophages recently redefined by the International Committee on Taxonomy of Viruses (ICTV). To address the limitations of sequence-based taxonomy, we present a structure-based classification framework using whole-proteome structural clustering. From 4,082 exemplar genomes, we predicted 445,098 protein structures with ESMFold and clustered them using Foldseek. Genomes were encoded as binary profiles of structural fold presence, and phylogenetic distances were inferred and normalized using Relative Evolutionary Divergence (RED). This yielded a revised structural taxonomy comprising 159 orders, 267 families, 502 subfamilies, and 1,189 genera. We also introduce PhagePleats, a Python tool for classifying novel phage genomes based on structural similarity. Our approach highlights the utility of protein structure for resolving distant viral relationships.

microbiology↗

bioRxiv2024

Refined Enterotyping Reveals Dysbiosis in Global Fecal Metagenomes

BackgroundEnterotypes describe human fecal microbiomes grouped by similarity into clusters of microbial community composition, often associated with disease, medications, diet, and lifestyle. Numbers and determinants of enterotypes have been derived by diverse frameworks and applied to cohorts that often lack diversity or inter-cohort comparability. ResultsTo overcome these limitations, we selected 16,772 fecal metagenomes collected from 38 countries to revisit the enterotypes using state-of-the-art fuzzy clustering and found robust clustering regardless of underlying taxonomy, consistent with previous findings. Quantifying the strength of enterotype classifications enriched the enterotype landscape, also reflecting some continuity of microbial compositions. As the classification strength was associated with the patients health status, we established an "Enterotype Dysbiosis Score" (EDS) as a latent covariate for various diseases. ConclusionThis global study confirms the enterotypes, reveals a dysbiosis signal within the enterotype landscape, and enables robust classification of metagenomes with an online "Enterotyper" tool, allowing reproducible analysis in future studies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/607711v3_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1611a2org.highwire.dtl.DTLVardef@dfbb57org.highwire.dtl.DTLVardef@848ac0org.highwire.dtl.DTLVardef@1b15808_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2024

Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations

The microbiota in individual habitats differ both in relative composition and absolute abundance. While sequencing approaches determine only the relative abundances of taxa and genes, experimental techniques for absolute abundance determination are rarely applied to large-scale microbiome studies. Here, we developed a machine learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data. Applied to large-scale datasets (n = 34,539), we demonstrate that microbial load is the major determinant of gut microbiome variation and associated with numerous host factors. We found that for several diseases, the altered microbial load, not the disease itself, was the main driver of the gut microbiome changes. Adjusting for this effect substantially reduced the significance of more than half of the disease-associated species. Our analysis reveals that the fecal microbial load is a major confounder in microbiome studies, highlighting its importance for understanding microbiome variation in health and disease.

microbiology↗

bioRxiv2022

Development of non-alcoholic steatohepatitis is associated with gut microbiota but not oxysterol synthesis

Liver steatosis is the most frequent liver disorder and its advanced stage, non-alcoholic steatohepatitis (NASH), will soon become the main reason for liver fibrosis and cirrhosis. The "multiple hits hypothesis" suggests that progression from simple steatosis to NASH is triggered by multiple factors including the gut microbiota composition. The Epstein Barr virus induced gene 2 (EBI2) is a receptor for the oxysterol 7a, 25-dihydroxycholesterol synthesized by the enzymes CH25H and CYP7B1. EBI2 and its ligand control activation of immune cells in secondary lymphoid organs and the gut. Here we show a concurrent study of the microbial dysregulation and perturbation of the EBI2 axis in a mice model of NASH. We used mice with wildtype, or littermates with CH25H-/-, EBI2-/-, or CYP7B1-/- genotypes fed with a high-fat diet (HFD) containing high amounts of fat, cholesterol, and fructose for 20 weeks to induce liver steatosis and NASH. Fecal and small intestinal microbiota samples were collected, and microbiota signatures were compared according to genotype and NASH disease state. We found pronounced differences in microbiota composition of mice with HFD developing NASH compared to mice did not developing NASH. In mice with NASH, we identified significantly increased 33 taxa mainly belonging to the Clostridiales order and/ or the family, and significantly decreased 17 taxa. Using an Elastic Net algorithm, we suggest a microbiota signature that predicts NASH in animals with a HFD from the microbiota composition with moderate accuracy (area under the receiver operator characteristics curve=0.64). In contrast, no microbiota differences regarding the studied genotypes (wildtype vs knock-out CH25H-/-, EBI2-/-, or CYP7B1-/-) were observed. In conclusion, our data confirm previous studies identifying the intestinal microbiota composition as a relevant marker for NASH pathogenesis. Further, no link of the EBI2 - oxysterol axis to the intestinal microbiota was detectable in the current study.

microbiology↗

bioRxiv2022

C. difficile is overdiagnosed in adults and a commensal in infants

Clostridioides difficile is an urgent threat in hospital-acquired infections world-wide, yet the microbial composition associated with C. difficile, in particular in C. difficile infection (CDI) cases, remains poorly characterised. To investigate the gut microbiome composition in CDI patients, we analysed 534 metagenomes from 10 publicly available CDI study populations. We then tracked C. difficile on a global scale, screening 42,900 metagenomes from 253 public studies. Among the CDI cohorts, we detected C. difficile in only 30% of the stool samples from CDI patients. However, we found that multiple other toxigenic species capable of inducing CDI-like symptomatology were prevalent. In addition, the majority of the investigated studies did not adhere to the recommended guidelines for a correct CDI diagnosis. In the global survey, we found that C. difficile prevalence, abundance and biotic context were age-dependent. C. difficile is a rare taxon associated with reduced diversity in healthy adults, but common and associated with increased diversity in infants. We identified a group of species co-occurring with C. difficile exclusively in healthy infants, enriched in obligate anaerobes and in species typical of the healthy adult gut microbiome. C. difficile in healthy infants was therefore associated with multiple indicators of healthy gut microbiome maturation. Our analysis raises concerns about potential CDI overdiagnosis and suggests that C. difficile is an important commensal in infants and that its asymptomatic carriage in adults depends on microbial context.

microbiology↗

bioRxiv2022

Alterations of oral microbiota and impact on the gut microbiome in type 1 diabetes mellitus revealed by multi-omic analysis

BackgroundAlterations of the gut microbiome have been linked to multiple chronic diseases. However, the drivers of such changes remain largely unknown. The oral cavity acts as a major route of exposure to exogenous factors including pathogens, and processes therein may affect the communities in the subsequent compartments of the gastrointestinal tract. Here, we perform strain-resolved, integrated multi-omic analyses of saliva and stool samples collected from eight families with multiple cases of type 1 diabetes mellitus (T1DM). ResultsWe identified distinct oral microbiota mostly reflecting competition between streptococcal species. More specifically, we found a decreased abundance of the commensal Streptococcus salivarius in the oral cavity of T1DM individuals, which is linked to its apparent competition with the pathobiont Streptococcus mutans. The decrease in S. salivarius in the oral cavity was also associated with its decrease in the gut as well as higher abundances in facultative anaerobes including Enterobacteria. In addition, we found evidence of gut inflammation in T1DM as reflected in the expression profiles of the Enterobacteria as well as in the human gut proteome. Finally, we were able to follow transmitted strain-variants from the oral cavity to the gut at the metagenomic, metatranscriptomic and metaproteomic levels, highlighting not only the transfer, but also the activity of the transmitted taxa along the gastrointestinal tract. ConclusionsAlterations of the oral microbiome in the context of T1DM impact the microbial communities in the lower gut, in particular through the reduction of "oral-to-gut" transfer of Streptococcus salivarius. Our results indicate that the observed oral-cavity-driven gut microbiome changes may contribute towards the inflammatory processes involved in T1DM. Through the integration of multi-omic analyses, we resolve strain-variant "mouth-to-gut" transfer in a disease context.

microbiology↗

bioRxiv2022

Functional and evolutionary significance of unknown genes from uncultivated taxa

Most microbes on our planet remain uncultured and poorly studied. Recent efforts to catalog their genetic diversity have revealed that a significant fraction of the observed microbial genes are functional and evolutionary untraceable, lacking homologs in reference databases. Despite their potential biological value, these apparently unrelated orphan genes from uncultivated taxa have been routinely discarded in metagenomics surveys. Here, we analyzed a global multi-habitat dataset covering 151,697 medium and high-quality metagenome assembled genomes (MAGs), 5,969 single-amplified genomes (SAGs), and 19,642 reference genomes, and identified 413,335 highly curated novel protein families under strong purifying selection out of previously considered orphan genes. These new protein families, representing a three-fold increase over the total number of prokaryotic orthologous groups described to date, spread out across the prokaryote phylogeny, can span multiple habitats, and are notably overrepresented in recently discovered taxa. By genomic context analysis, we pinpointed thousands of unknown protein families to phylogenetically conserved operons linked to energy production, xenobiotic metabolism and microbial resistance. Most remarkably, we found 980 previously neglected protein families that can accurately distinguish entire uncultivated phyla, classes, and orders, likely representing synapomorphic traits that fostered their divergence. The systematic curation and evolutionary analysis of the unique genetic repertoire of uncultivated taxa opens new avenues for understanding the biology and ecological roles of poorly explored lineages at a global scale.

microbiology↗

bioRxiv2021

Drivers and Determinants of Strain Dynamics Following Faecal Microbiota Transplantation

Faecal microbiota transplantation (FMT) is an efficacious therapeutic intervention, but its clinical mode of action and underlying microbiome dynamics remain poorly understood. Here, we analysed the metagenomes associated with 142 FMTs, in a time series-based meta-study across five disease indications. We quantified strain-level dynamics of 1,089 microbial species based on their pangenome, complemented with 47,548 newly constructed metagenome-assembled genomes. Using subsets of procedural-, host- and microbiome-based variables, LASSO-regularised regression models accurately predicted the colonisation and resilience of donor and recipient microbes, as well as turnover of individual species. Linking this to putative ecological mechanisms, we found these sets of variables to be informative of the underlying processes that shape the post-FMT gut microbiome. Recipient factors and complementarity of donor and recipient microbiomes, encompassing entire communities to individual strains, were the main determinants of individual strain population dynamics, and mostly independent of clinical outcomes. Recipient community state and the degree of residual strain depletion provided a neutral baseline for donor strain colonisation success, in addition to inhibitive priority effects between species and conspecific strains, as well as putatively adaptive processes. Our results suggest promising tunable parameters to enhance donor flora colonisation or recipient flora displacement in clinical practice, towards the development of more targeted and personalised therapies.

microbiology↗

bioRxiv2020

GUNC: Detection of Chimerism and Contamination in Prokaryotic Genomes

Genomes are critical units in microbiology, yet ascertaining quality in prokaryotic genomes remains a formidable challenge. We present GUNC (the Genome UNClutterer), a tool that accurately detects and quantifies genome chimerism based on the lineage homogeneity of individual contigs using a genomes full complement of genes. GUNC complements existing approaches by targeting previously underdetected types of contamination: we conservatively estimate that 5.7% of genomes in GenBank, 5.2% in RefSeq, and 15-30% of pre-filtered high quality metagenome-assembled genomes in recent studies are undetected chimeras. GUNC provides a fast and robust tool to substantially improve prokaryotic genome quality. Source code (GPLv3+): https://github.com/grp-bork/gunc

bioinformatics↗

bioRxiv2020

treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

The arrangement of hypotheses in a hierarchical structure (e.g., phylogenies, cell types) appears in many research fields and indicates different resolutions at which data can be interpreted. A common goal is to find a representative resolution that gives high sensitivity to identify relevant entities (e.g., microbial taxa or cell subpopulations) that are related to a phenotypic outcome (e.g. disease status) while controlling false detections, therefore providing a more compact view of detected entities and summarizing characteristics shared among them. Current methods, either performing hypothesis tests at an arbitrary resolution or testing hypotheses at all possible resolutions leading to nested results, are suboptimal. Moreover, they are not flexible enough to work in situations where each entity has multiple features to consider and different resolutions might be required for different features. For example, in single cell RNA-seq data, an increasing focus is to find differential state genes that change expression within a cell subpopulation in response to an external stimulus. Such differential expression might occur at different resolutions (e.g., all cells or a small set of cells) for different genes. Our new algorithm treeclimbR is designed to fill this gap by exploiting a hierarchical tree of entities, proposing multiple candidates that capture the latent signal and pinpointing branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

bioinformatics↗

bioRxiv2019

Disentangling the impact of environmental and phylogenetic constraints on prokaryotic strain diversity

Microbial organisms inhabit virtually all environments and encompass a vast biological diversity. The pan-genome concept aims to facilitate an understanding of diversity within defined phylogenetic groups. Hence, pan-genomes are increasingly used to characterize the strain diversity of prokaryotic species. To understand the interdependency of pan-genome features (such as numbers of core and accessory genes) and to study the impact of environmental and phylogenetic constraints on the evolution of conspecific strains, we computed pan-genomes for 155 phylogenetically diverse species using 7000 high-quality genomes. We show that many pan-genome features such as functional diversity and core genome nucleotide diversity are correlated to each other. Further, habitat flexibility as approximated by species ubiquity is associated with several pan-genome features, particularly core genome size. In general, environment had a stronger impact on pan-genome features than phylogenetic signal. Similar environmental preferences led to convergent evolution of pan-genomic features in distant phylogenetic clades. For example, the soil environment promotes expansion of pan-genome size, while host-associated habitats lead to its reduction.

genomics↗

bioRxiv2018

Extensive Transmission of Microbes along the Gastrointestinal Tract

The gastrointestinal tract is abundantly colonized by microbes, yet the translocation of oral species to the intestine is considered a rare aberrant event, and a hallmark of disease. By studying salivary and fecal microbial strain populations of 310 species in 470 individuals from five countries, we found that transmission to, and subsequent colonization of, the large intestine by oral microbes is common and extensive among healthy individuals. We found evidence for a vast majority of oral species to be transferable, with increased levels of transmission in colorectal cancer and rheumatoid arthritis patients and, more generally, for species described as opportunistic pathogens. This establishes the oral cavity as an endogenous reservoir for gut microbial strains, and oral-fecal transmission as an important process that shapes the gastrointestinal microbiome in health and disease.

microbiology↗

bioRxiv2017

MAPseq: Improved Speed, Accuracy And Consistency In Ribosomal RNA Sequence Analysis

Metagenomic sequencing has become crucial to studying microbial communities, but meaningful taxonomic analysis and inter-comparison of such data are still hampered by technical limitations, between-study design variability and inconsistencies between taxonomies used. Here we present MAPseq, a framework for reference-based rRNA metagenomic analysis that is up to 30% more accurate (F1/2 score) and up to one hundred times faster than existing solutions, providing in a single run multiple taxonomy classifications and hierarchical OTU mappings, for both amplicon and shotgun sequencing strategies, and for datasets of virtually any size. Availability: Source code and binaries are freely available at http://meringlab.org/software/mapseq/

bioinformatics↗