ArticlePLoS computational biology2018
Phylogeny-corrected identification of microbial gene families relevant to human gut colonization.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- An atlas of colonization factors in the human gut microbiome reveals ecological strategies and inflammatory bowel disease signatures.Nature communications · 2026Article
- Article
- Phylogenize2: robust phylogenetic methods link genes to phenotypes across host-associated and environmental microbiomes.bioRxiv : the preprint server for biology · 2026Article
- A robust, sensitive phylogenetic method enables gene-level metagenomic analyses.bioRxiv : the preprint server for biology · 2026Article
- Article
- Microbiological Characteristics of the Gastrointestinal Tracts of Jersey and Holstein Cows.Animals : an open access journal from MDPI · 2024Article
- Culturing of a complex gut microbial community in mucin-hydrogel carriers reveals strain- and gene-associated spatial organization.Nature communications · 2023Article
- Article
- Within-host evolution of the gut microbiome.Current opinion in microbiology · 2023Review
- Efficient computation of contributional diversity metrics from microbiome data with FuncDiv.Bioinformatics (Oxford, England) · 2023Article
- Integrating phylogenetic and functional data in microbiome studies.Bioinformatics (Oxford, England) · 2022Article
- Host and gut bacteria share metabolic pathways for anti-cancer drug metabolism.Nature microbiology · 2022Article
- Tree-aggregated predictive modeling of microbiome data.Scientific reports · 2021Article
- phylogenize: correcting for phylogeny reveals genes associated with microbial distributions.Bioinformatics (Oxford, England) · 2020Article
- The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health.Frontiers in microbiology · 2020Review
- Article
- Computational Structural Biology: Successes, Future Directions, and Challenges.Molecules (Basel, Switzerland) · 2019Review
- Article
- The Glutaminase-Dependent Acid Resistance System: Qualitative and Quantitative Assays and Analysis of Its Distribution in Enteric Bacteria.Frontiers in microbiology · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The mechanisms by which different microbes colonize the healthy human gut versus other body sites, the gut in disease states, or other environments remain largely unknown. Identifying microbial genes influencing fitness in the gut could lead to new ways to engineer probiotics or disrupt pathogenesis. We approach this problem by measuring the statistical association between a species having a gene and the probability that the species is present in the gut microbiome. The challenge is that closely related species tend to be jointly present or absent in the microbiome and also share many genes, only a subset of which are involved in gut adaptation. We show that this phylogenetic correlation indeed leads to many false discoveries and propose phylogenetic linear regression as a powerful solution. To apply this method across the bacterial tree of life, where most species have not been experimentally phenotyped, we use metagenomes from hundreds of people to quantify each species' prevalence in and specificity for the gut microbiome. This analysis reveals thousands of genes potentially involved in adaptation to the gut across species, including many novel candidates as well as processes known to contribute to fitness of gut bacteria, such as acid tolerance in Bacteroidetes and sporulation in Firmicutes. We also find microbial genes associated with a preference for the gut over other body sites, which are significantly enriched for genes linked to fitness in an in vivo competition experiment. Finally, we identify gene families associated with higher prevalence in patients with Crohn's disease, including Proteobacterial genes involved in conjugation and fimbria regulation, processes previously linked to inflammation. These gene targets may represent new avenues for modulating host colonization and disease. Our strategy of combining metagenomics with phylogenetic modeling is general and can be used to identify genes associated with adaptation to any environment.
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