Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Phylogeny-corrected identification of microbial gene families relevant to human gut colonization

View ORCID ProfilePatrick H. Bradley, Stephen Nayfach, View ORCID ProfileKatherine S. Pollard
doi: https://doi.org/10.1101/189795
Patrick H. Bradley
1Gladstone Institutes, San Francisco, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Patrick H. Bradley
Stephen Nayfach
1Gladstone Institutes, San Francisco, CA USA
2DOE Joint Genome Institute, Walnut Creek, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Katherine S. Pollard
1Gladstone Institutes, San Francisco, CA USA
3Department of Epidemiology & Biostatistics, Institute for Human Genetics, Quantitative Biology Institute and Institute for Computational Health Sciences, University of California, San Francisco, CA USA
4Chan-Zuckerberg Biohub, San Francisco, CA USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Katherine S. Pollard
  • For correspondence: katherine.pollard@gladstone.ucsf.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

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 having 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.

Author Summary Why do certain microbes and not others colonize our gut, and why do they differ between healthy and sick people? One explanation is the genes in their genomes. If we can find microbial genes involved in gut adaptation, we may be able to keep out pathogens and encourage the growth of beneficial microbes. One could look for genes that were present more often in prevalent microbes, and less often in rare ones.

However, this ignores that related species are more likely to share an environment and also share many unrelated phenotypes simply because of common ancestry. To solve this problem, we used a method from ecology that accounts for phylogenetic relatedness. We first calculated gut prevalence for thousands of species using a compendium of shotgun sequencing data, then tested for genes associated with prevalence, adjusting for phylogenetic relationships. We found genes that are associated with overall gut prevalence, with a preference for the gut over other body sites, and with the gut in Crohn’s disease versus health. Many of these findings have biological plausibility based on existing literature. We also showed agreement with the results of a previously published high-throughput screen of bacterial gene knockouts in mice. These results, and this type of analysis, may eventually lead to new strategies for maintaining gut health.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted March 22, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Phylogeny-corrected identification of microbial gene families relevant to human gut colonization
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Phylogeny-corrected identification of microbial gene families relevant to human gut colonization
Patrick H. Bradley, Stephen Nayfach, Katherine S. Pollard
bioRxiv 189795; doi: https://doi.org/10.1101/189795
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Phylogeny-corrected identification of microbial gene families relevant to human gut colonization
Patrick H. Bradley, Stephen Nayfach, Katherine S. Pollard
bioRxiv 189795; doi: https://doi.org/10.1101/189795

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (3602)
  • Biochemistry (7569)
  • Bioengineering (5523)
  • Bioinformatics (20789)
  • Biophysics (10328)
  • Cancer Biology (7980)
  • Cell Biology (11638)
  • Clinical Trials (138)
  • Developmental Biology (6603)
  • Ecology (10202)
  • Epidemiology (2065)
  • Evolutionary Biology (13617)
  • Genetics (9541)
  • Genomics (12846)
  • Immunology (7920)
  • Microbiology (19541)
  • Molecular Biology (7657)
  • Neuroscience (42095)
  • Paleontology (308)
  • Pathology (1258)
  • Pharmacology and Toxicology (2202)
  • Physiology (3267)
  • Plant Biology (7041)
  • Scientific Communication and Education (1294)
  • Synthetic Biology (1951)
  • Systems Biology (5426)
  • Zoology (1117)