Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-10-31

AUTHORS

Vanessa L. Hale, Patricio Jeraldo, Jun Chen, Michael Mundy, Janet Yao, Sambhawa Priya, Gary Keeney, Kelly Lyke, Jason Ridlon, Bryan A. White, Amy J. French, Stephen N. Thibodeau, Christian Diener, Osbaldo Resendis-Antonio, Jaime Gransee, Tumpa Dutta, Xuan-Mai Petterson, Jaeyun Sung, Ran Blekhman, Lisa Boardman, David Larson, Heidi Nelson, Nicholas Chia

ABSTRACT

BackgroundLinks between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology.MethodsWe collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks.ResultsWe demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC.ConclusionsIntegrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers. More... »

PAGES

78

References to SciGraph publications

  • 2017-09-14. Distinct gut microbiome patterns associate with consensus molecular subtypes of colorectal cancer in SCIENTIFIC REPORTS
  • 2016-05-23. DADA2: High-resolution sample inference from Illumina amplicon data in NATURE METHODS
  • 2016-11-28. Generation of genome-scale metabolic reconstructions for 773 members of the human gut microbiota in NATURE BIOTECHNOLOGY
  • 2017-11-29. High-resolution bacterial 16S rRNA gene profile meta-analysis and biofilm status reveal common colorectal cancer consortia in NPJ BIOFILMS AND MICROBIOMES
  • 2015-10-12. The consensus molecular subtypes of colorectal cancer in NATURE MEDICINE
  • 2017-10-02. Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium in NATURE BIOTECHNOLOGY
  • 2010-03. What is flux balance analysis? in NATURE BIOTECHNOLOGY
  • 2016-09-02. MMinte: an application for predicting metabolic interactions among the microbial species in a community in BMC BIOINFORMATICS
  • 2014-03-06. Fusobacterium nucleatum associates with stages of colorectal neoplasia development, colorectal cancer and disease outcome in EUROPEAN JOURNAL OF CLINICAL MICROBIOLOGY & INFECTIOUS DISEASES
  • 2017-06-06. Global metabolic interaction network of the human gut microbiota for context-specific community-scale analysis in NATURE COMMUNICATIONS
  • 2014-09-03. Microbial genomic analysis reveals the essential role of inflammation in bacteria-induced colorectal cancer in NATURE COMMUNICATIONS
  • 2014-09-08. The gut microbiota, bacterial metabolites and colorectal cancer in NATURE REVIEWS MICROBIOLOGY
  • Journal

    TITLE

    Genome Medicine

    ISSUE

    1

    VOLUME

    10

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s13073-018-0586-6

    DOI

    http://dx.doi.org/10.1186/s13073-018-0586-6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1107832002

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30376889


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