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

Study information

Reviewed Marked as Reviewed by Peace Sandy on 2024-1-26

study design

case-control

Citation

PMID PubMed identifier for scientific articles.

36624530

DOI Digital object identifier for electronic documents.

10.1186/s40168-022-01450-5

URI

Authors

Jacobs JP, Lagishetty V, Hauer MC, Labus JS, Dong TS, Toma R, Vuyisich M, Naliboff BD, Lackner JM, Gupta A, Tillisch K, Mayer EA

Journal

Microbiome

Year

2023

Keywords:

Biomarkers, Bowel habit subtypes, Irritable bowel syndrome, Metabolomics, Metatranscriptomics, Microbiome, Multi-omics

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. Video Abstract.

Experiment 1

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Curated date: 2023/10/14

Curator: Chisom

Revision editor(s): WikiWorks, Peace Sandy, Chisom, Fiddyhamma, KateRasheed

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

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: Irritable Bowel Syndrome

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Patients diagnosed with Irritable Bowel Syndrome via Rome III criteria

Group 0 sample size Number of subjects in the control (unexposed) group: 177

Group 1 sample size Number of subjects in the case (exposed) group: 318

Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 3 months

Lab analysis

Sequencing type: 16S

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

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Illumina

Statistical Analysis

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

Statistical test: Random Forest Analysis

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): 0.05

MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?: Yes

Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, anxiety disorder, body mass index, diet, race, sex

Alpha Diversity

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

Signature 1

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Reviewed Marked as Reviewed by Peace Sandy on 2024-1-26

Curated date: 2023/10/15

Curator: Chisom

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Source: Figure 2B

Description: Differentially abundant bacterial taxa (q < 0.25) between IBS subjects and HC were identified in multivariate models adjusting for batch, age, sex, race/ethnicity, BMI, dietary category, and HAD-A. The result of assessing the taxonomic profiles of the metatranscriptome.

Abundance in Group 1: increased abundance in Irritable Bowel Syndrome

NCBI	Quality Control	Links
Actinomyces
Bacteroides fluxus
Blautia hydrogenotrophica
Catonella morbi
Eggerthella lenta
Phascolarctobacterium succinatutens
Phocaeicola dorei
Hoylesella timonensis CRIS 5C-B1
[Clostridium] hylemonae

Revision editor(s): Chisom, WikiWorks

Signature 2

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Reviewed Marked as Reviewed by Peace Sandy on 2024-1-26

Curated date: 2023/10/15

Curator: Chisom

Revision editor(s): Chisom, WikiWorks

Source: Figure 2B

Description: Differentially abundant bacterial taxa (q < 0.25) between IBS subjects and HC were identified in multivariate models adjusting for batch, age, sex, race/ethnicity, BMI, dietary category, and HAD-A. The result of assessing the taxonomic profiles of the metatranscriptome.

Abundance in Group 1: decreased abundance in Irritable Bowel Syndrome

NCBI	Quality Control	Links
Bilophila wadsworthia
Roseburia inulinivorans
Bifidobacterium animalis
Phocaeicola plebeius CAG:211
Phocaeicola barnesiae

Revision editor(s): Chisom, WikiWorks