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Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes

BACKGROUND: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is thought to involve alterations in the gut microbiome, but robust microbial signatures have been challenging to identify. As prior studies have primarily focused on composition, we hypothesized that multi-omics a...

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Autores principales: Jacobs, Jonathan P., Lagishetty, Venu, Hauer, Megan C., Labus, Jennifer S., Dong, Tien S., Toma, Ryan, Vuyisich, Momchilo, Naliboff, Bruce D., Lackner, Jeffrey M., Gupta, Arpana, Tillisch, Kirsten, Mayer, Emeran A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830758/
https://www.ncbi.nlm.nih.gov/pubmed/36624530
http://dx.doi.org/10.1186/s40168-022-01450-5
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author Jacobs, Jonathan P.
Lagishetty, Venu
Hauer, Megan C.
Labus, Jennifer S.
Dong, Tien S.
Toma, Ryan
Vuyisich, Momchilo
Naliboff, Bruce D.
Lackner, Jeffrey M.
Gupta, Arpana
Tillisch, Kirsten
Mayer, Emeran A.
author_facet Jacobs, Jonathan P.
Lagishetty, Venu
Hauer, Megan C.
Labus, Jennifer S.
Dong, Tien S.
Toma, Ryan
Vuyisich, Momchilo
Naliboff, Bruce D.
Lackner, Jeffrey M.
Gupta, Arpana
Tillisch, Kirsten
Mayer, Emeran A.
author_sort Jacobs, Jonathan P.
collection PubMed
description BACKGROUND: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is thought to involve alterations in the gut microbiome, but robust microbial signatures have been challenging to identify. As prior studies have primarily focused on composition, we hypothesized that multi-omics assessment of microbial function incorporating both metatranscriptomics and metabolomics would further delineate microbial profiles of IBS and its subtypes. METHODS: Fecal samples were collected from a racially/ethnically diverse cohort of 495 subjects, including 318 IBS patients and 177 healthy controls, for analysis by 16S rRNA gene sequencing (n = 486), metatranscriptomics (n = 327), and untargeted metabolomics (n = 368). Differentially abundant microbes, predicted genes, transcripts, and metabolites in IBS were identified by multivariate models incorporating age, sex, race/ethnicity, BMI, diet, and HAD-Anxiety. Inter-omic functional relationships were assessed by transcript/gene ratios and microbial metabolic modeling. Differential features were used to construct random forests classifiers. RESULTS: IBS was associated with global alterations in microbiome composition by 16S rRNA sequencing and metatranscriptomics, and in microbiome function by predicted metagenomics, metatranscriptomics, and metabolomics. After adjusting for age, sex, race/ethnicity, BMI, diet, and anxiety, IBS was associated with differential abundance of bacterial taxa such as Bacteroides dorei; metabolites including increased tyramine and decreased gentisate and hydrocinnamate; and transcripts related to fructooligosaccharide and polyol utilization. IBS further showed transcriptional upregulation of enzymes involved in fructose and glucan metabolism as well as the succinate pathway of carbohydrate fermentation. A multi-omics classifier for IBS had significantly higher accuracy (AUC 0.82) than classifiers using individual datasets. Diarrhea-predominant IBS (IBS-D) demonstrated shifts in the metatranscriptome and metabolome including increased bile acids, polyamines, succinate pathway intermediates (malate, fumarate), and transcripts involved in fructose, mannose, and polyol metabolism compared to constipation-predominant IBS (IBS-C). A classifier incorporating metabolites and gene-normalized transcripts differentiated IBS-D from IBS-C with high accuracy (AUC 0.86). CONCLUSIONS: IBS is characterized by a multi-omics microbial signature indicating increased capacity to utilize fermentable carbohydrates—consistent with the clinical benefit of diets restricting this energy source—that also includes multiple previously unrecognized metabolites and metabolic pathways. These findings support the need for integrative assessment of microbial function to investigate the microbiome in IBS and identify novel microbiome-related therapeutic targets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01450-5.
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spelling pubmed-98307582023-01-11 Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes Jacobs, Jonathan P. Lagishetty, Venu Hauer, Megan C. Labus, Jennifer S. Dong, Tien S. Toma, Ryan Vuyisich, Momchilo Naliboff, Bruce D. Lackner, Jeffrey M. Gupta, Arpana Tillisch, Kirsten Mayer, Emeran A. Microbiome Research BACKGROUND: Irritable bowel syndrome (IBS) is a common gastrointestinal disorder that is thought to involve alterations in the gut microbiome, but robust microbial signatures have been challenging to identify. As prior studies have primarily focused on composition, we hypothesized that multi-omics assessment of microbial function incorporating both metatranscriptomics and metabolomics would further delineate microbial profiles of IBS and its subtypes. METHODS: Fecal samples were collected from a racially/ethnically diverse cohort of 495 subjects, including 318 IBS patients and 177 healthy controls, for analysis by 16S rRNA gene sequencing (n = 486), metatranscriptomics (n = 327), and untargeted metabolomics (n = 368). Differentially abundant microbes, predicted genes, transcripts, and metabolites in IBS were identified by multivariate models incorporating age, sex, race/ethnicity, BMI, diet, and HAD-Anxiety. Inter-omic functional relationships were assessed by transcript/gene ratios and microbial metabolic modeling. Differential features were used to construct random forests classifiers. RESULTS: IBS was associated with global alterations in microbiome composition by 16S rRNA sequencing and metatranscriptomics, and in microbiome function by predicted metagenomics, metatranscriptomics, and metabolomics. After adjusting for age, sex, race/ethnicity, BMI, diet, and anxiety, IBS was associated with differential abundance of bacterial taxa such as Bacteroides dorei; metabolites including increased tyramine and decreased gentisate and hydrocinnamate; and transcripts related to fructooligosaccharide and polyol utilization. IBS further showed transcriptional upregulation of enzymes involved in fructose and glucan metabolism as well as the succinate pathway of carbohydrate fermentation. A multi-omics classifier for IBS had significantly higher accuracy (AUC 0.82) than classifiers using individual datasets. Diarrhea-predominant IBS (IBS-D) demonstrated shifts in the metatranscriptome and metabolome including increased bile acids, polyamines, succinate pathway intermediates (malate, fumarate), and transcripts involved in fructose, mannose, and polyol metabolism compared to constipation-predominant IBS (IBS-C). A classifier incorporating metabolites and gene-normalized transcripts differentiated IBS-D from IBS-C with high accuracy (AUC 0.86). CONCLUSIONS: IBS is characterized by a multi-omics microbial signature indicating increased capacity to utilize fermentable carbohydrates—consistent with the clinical benefit of diets restricting this energy source—that also includes multiple previously unrecognized metabolites and metabolic pathways. These findings support the need for integrative assessment of microbial function to investigate the microbiome in IBS and identify novel microbiome-related therapeutic targets. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-022-01450-5. BioMed Central 2023-01-10 /pmc/articles/PMC9830758/ /pubmed/36624530 http://dx.doi.org/10.1186/s40168-022-01450-5 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jacobs, Jonathan P.
Lagishetty, Venu
Hauer, Megan C.
Labus, Jennifer S.
Dong, Tien S.
Toma, Ryan
Vuyisich, Momchilo
Naliboff, Bruce D.
Lackner, Jeffrey M.
Gupta, Arpana
Tillisch, Kirsten
Mayer, Emeran A.
Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
title Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
title_full Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
title_fullStr Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
title_full_unstemmed Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
title_short Multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
title_sort multi-omics profiles of the intestinal microbiome in irritable bowel syndrome and its bowel habit subtypes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830758/
https://www.ncbi.nlm.nih.gov/pubmed/36624530
http://dx.doi.org/10.1186/s40168-022-01450-5
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