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

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 BoardmanDavid Larson, Heidi Nelson, Nicholas Chia

Research output: Contribution to journalArticle

Abstract

BACKGROUND: Links 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: Integrating 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.

Original languageEnglish (US)
Number of pages1
JournalGenome medicine
Volume10
Issue number1
DOIs
StatePublished - Oct 31 2018

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DNA Mismatch Repair
Microbiota
Ecology
Colorectal Neoplasms
Microbial Interactions
Bacteroides fragilis
Metabolomics
Neoplasms
Fusobacterium nucleatum
Amino Acids
Hydrogen Sulfide
Colectomy
Volatile Fatty Acids
Proxy
rRNA Genes
Colon
Carcinogenesis
Mucous Membrane
Genome

ASJC Scopus subject areas

  • Molecular Medicine
  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers. / Hale, Vanessa L.; Jeraldo, Patricio; Chen, Jun; Mundy, Michael; Yao, Janet; Priya, Sambhawa; Keeney, Gary; Lyke, Kelly; Ridlon, Jason; White, Bryan A.; French, Amy J.; Thibodeau, Stephen N.; Diener, Christian; Resendis-Antonio, Osbaldo; Gransee, Jaime; Dutta, Tumpa; Petterson, Xuan Mai; Sung, Jaeyun; Blekhman, Ran; Boardman, Lisa; Larson, David; Nelson, Heidi; Chia, Nicholas.

In: Genome medicine, Vol. 10, No. 1, 31.10.2018.

Research output: Contribution to journalArticle

Hale, VL, Jeraldo, P, Chen, J, Mundy, M, Yao, J, Priya, S, Keeney, G, Lyke, K, Ridlon, J, White, BA, French, AJ, Thibodeau, SN, Diener, C, Resendis-Antonio, O, Gransee, J, Dutta, T, Petterson, XM, Sung, J, Blekhman, R, Boardman, L, Larson, D, Nelson, H & Chia, N 2018, 'Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers', Genome medicine, vol. 10, no. 1. https://doi.org/10.1186/s13073-018-0586-6
Hale, Vanessa L. ; Jeraldo, Patricio ; Chen, Jun ; Mundy, Michael ; Yao, Janet ; Priya, Sambhawa ; Keeney, Gary ; Lyke, Kelly ; Ridlon, Jason ; White, Bryan A. ; French, Amy J. ; Thibodeau, Stephen N. ; Diener, Christian ; Resendis-Antonio, Osbaldo ; Gransee, Jaime ; Dutta, Tumpa ; Petterson, Xuan Mai ; Sung, Jaeyun ; Blekhman, Ran ; Boardman, Lisa ; Larson, David ; Nelson, Heidi ; Chia, Nicholas. / Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers. In: Genome medicine. 2018 ; Vol. 10, No. 1.
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abstract = "BACKGROUND: Links 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: Integrating 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.",
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T1 - Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers

AU - Hale, Vanessa L.

AU - Jeraldo, Patricio

AU - Chen, Jun

AU - Mundy, Michael

AU - Yao, Janet

AU - Priya, Sambhawa

AU - Keeney, Gary

AU - Lyke, Kelly

AU - Ridlon, Jason

AU - White, Bryan A.

AU - French, Amy J.

AU - Thibodeau, Stephen N.

AU - Diener, Christian

AU - Resendis-Antonio, Osbaldo

AU - Gransee, Jaime

AU - Dutta, Tumpa

AU - Petterson, Xuan Mai

AU - Sung, Jaeyun

AU - Blekhman, Ran

AU - Boardman, Lisa

AU - Larson, David

AU - Nelson, Heidi

AU - Chia, Nicholas

PY - 2018/10/31

Y1 - 2018/10/31

N2 - BACKGROUND: Links 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: Integrating 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.

AB - BACKGROUND: Links 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. METHODS: We 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. RESULTS: We 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. CONCLUSIONS: Integrating 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.

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