Stool microbiome and metabolome differences between colorectal cancer patients and healthy adults

Study information

Reviewed Marked as Reviewed by Atrayees on 2023-8-10

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

23940645

DOI Digital object identifier for electronic documents.

10.1371/journal.pone.0070803

URI

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3735522/

Authors

Weir TL, Manter DK, Sheflin AM, Barnett BA, Heuberger AL, Ryan EP

Journal

PloS one

Year

2013

In this study we used stool profiling to identify intestinal bacteria and metabolites that are differentially represented in humans with colorectal cancer (CRC) compared to healthy controls to identify how microbial functions may influence CRC development. Stool samples were collected from healthy adults (n = 10) and colorectal cancer patients (n = 11) prior to colon resection surgery at the University of Colorado Health-Poudre Valley Hospital in Fort Collins, CO. The V4 region of the 16s rRNA gene was pyrosequenced and both short chain fatty acids and global stool metabolites were extracted and analyzed utilizing Gas Chromatography-Mass Spectrometry (GC-MS). There were no significant differences in the overall microbial community structure associated with the disease state, but several bacterial genera, particularly butyrate-producing species, were under-represented in the CRC samples, while a mucin-degrading species, Akkermansia muciniphila, was about 4-fold higher in CRC (p<0.01). Proportionately higher amounts of butyrate were seen in stool of healthy individuals while relative concentrations of acetate were higher in stools of CRC patients. GC-MS profiling revealed higher concentrations of amino acids in stool samples from CRC patients and higher poly and monounsaturated fatty acids and ursodeoxycholic acid, a conjugated bile acid in stool samples from healthy adults (p<0.01). Correlative analysis between the combined datasets revealed some potential relationships between stool metabolites and certain bacterial species. These associations could provide insight into microbial functions occurring in a cancer environment and will help direct future mechanistic studies. Using integrated "omics" approaches may prove a useful tool in identifying functional groups of gastrointestinal bacteria and their associated metabolites as novel therapeutic and chemopreventive targets.

Experiment 1

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Reviewed Marked as Reviewed by Svetlana up on 2024-10-18

Curated date: 2022/01/06

Curator: Itslanapark

Revision editor(s): WikiWorks, Itslanapark, Atrayees, Victoria, Barrakat

Subjects

Location of subjects: United States of America

Host species Species from which microbiome was sampled. Contact us to have more species added.: Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: Colorectal carcinoma

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Healthy controls

Group 1 name Corresponds to the case (exposed) group for case-control studies: Colorectal Cancer patients (CRC)

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Patients recently diagnosed with Colorectal cancer prior to surgery for colonic resection.

Group 0 sample size Number of subjects in the control (unexposed) group: 11

Group 1 sample size Number of subjects in the case (exposed) group: 10

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 2 months

Lab analysis

Sequencing type: 16S

16S variable region One or more hypervariable region(s) of the bacterial 16S gene: V4

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).: raw counts

Statistical test: T-Test

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.01

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: No

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: unchanged

Chao1 Abundance-based estimator of species richness: decreased

Richness Number of species: decreased

Signature 1

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Curated date: 2022/01/06

Curator: Itslanapark

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Source: Table 3

Description: Bacterial species significantly over-represented in CRC stool samples.

Abundance in Group 1: increased abundance in Colorectal Cancer patients (CRC)

NCBI	Quality Control	Links
Akkermansia muciniphila
Phascolarctobacterium
Citrobacter farmeri
unclassified Acidaminobacter

Revision editor(s): WikiWorks, Itslanapark, Atrayees, Aiyshaaaa

Signature 2

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Source: Table 2

Description: Bacterial species that were significantly more abundant in the stool of healthy individuals compared to CRC patients

Abundance in Group 1: decreased abundance in Colorectal Cancer patients (CRC)

NCBI	Quality Control	Links
Bacteroides finegoldii
Bacteroides intestinalis
Blautia obeum
Dialister invisus
Dialister pneumosintes
Dorea formicigenerans
Lachnobacterium bovis
Lachnospira pectinoschiza
Megamonas hypermegale
Segatella copri
Segatella oris
Pseudobutyrivibrio ruminis
Pseudoflavonifractor capillosus
Ruminococcus albus

Revision editor(s): Itslanapark, Aiyshaaaa, WikiWorks