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Describing the fecal metabolome in cryogenically collected samples from healthy participants.

ABSTRACT: The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography and time of flight mass spectrometry. Lipids were detected using ultra high-performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry. 2326 metabolic features were detected. Out of a total of 298 metabolites that were annotated we report here 185 that showed a technical variation of x?

SUBMITTER: Trost K

PROVIDER: S-EPMC6972823 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Describing the fecal metabolome in cryogenically collected samples from healthy participants.

Trošt Kajetan K Ahonen Linda L Suvitaival Tommi T Christiansen Nina N Nielsen Trine T Thiele Maja M Jacobsen Suganya S Krag Aleksander A Rossing Peter P Hansen Torben T Dragsted Lars Ove LO Legido-Quigley Cristina C

Scientific reports 20200121 1

The chemical composition of feces plays an important role in human metabolism. Metabolomics and lipidomics are valuable tools for screening the metabolite composition in feces. Here we set out to describe fecal metabolite composition in healthy participants in frozen stools. Frozen stool samples were collected from 10 healthy volunteers and cryogenically drilled in four areas along the specimen. Polar metabolites were analyzed using derivatization followed by two-dimensional gas chromatography a ...[more]

PMID: 31965056

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Project description:BACKGROUNDThere has been a striking generational increase in the prevalence of food allergies. We have proposed that this increase can be explained, in part, by alterations in the commensal microbiome.METHODSTo identify bacterial signatures and metabolic pathways that may influence the expression of this disease, we collected fecal samples from a unique, well-controlled cohort of twins concordant or discordant for food allergy. Samples were analyzed by integrating 16S rRNA gene amplicon sequencing and liquid chromatography-tandem mass spectrometry metabolite profiling.RESULTSA bacterial signature of 64 operational taxonomic units (OTUs) distinguished healthy from allergic twins; the OTUs enriched in the healthy twins were largely taxa from the Clostridia class. We detected significant enrichment in distinct metabolite pathways in each group. The enrichment of diacylglycerol in healthy twins is of particular interest for its potential as a readily measurable fecal biomarker of health. In addition, an integrated microbial-metabolomic analysis identified a significant association between healthy twins and Phascolarctobacterium faecium and Ruminococcus bromii, suggesting new possibilities for the development of live microbiome-modulating biotherapeutics.CONCLUSIONTwin pairs exhibited significant differences in their fecal microbiomes and metabolomes through adulthood, suggesting that the gut microbiota may play a protective role in patients with food allergies beyond the infant stage.TRIAL REGISTRATIONParticipants in this study were recruited as part of an observational study (ClinicalTrials.gov NCT01613885) at multiple sites from 2014 to 2018.FUNDINGThis work was supported by the Sunshine Charitable Foundation; the Moss Family Foundation; the National Institute of Allergy and Infectious Diseases (NIAID) (R56AI134923 and R01AI 140134); the Sean N. Parker Center for Allergy and Asthma Research; the National Heart, Lung, and Blood Institute (R01 HL 118612); the Orsak family; the Kepner family; and the Stanford Institute for Immunity, Transplant and Infection.

Project description:Background and aimsInvestigation of microbe-metabolite relationships in the gut is needed to understand and potentially reduce colorectal cancer (CRC) risk.MethodsMicrobiota and metabolomics profiling were performed on lyophilized feces from 42 CRC cases and 89 matched controls. Multivariable logistic regression was used to identify statistically independent associations with CRC. First principal coordinate-component pair (PCo1-PC1) and false discovery rate (0.05)-corrected P-values were calculated for 116,000 Pearson correlations between 530 metabolites and 220 microbes in a sex*case/control meta-analysis.ResultsOverall microbe-metabolite PCo1-PC1 was more strongly correlated in cases than in controls (Rho 0.606 vs 0.201, P = 0.01). CRC was independently associated with lower levels of Clostridia, Lachnospiraceae, p-aminobenzoate and conjugated linoleate, and with higher levels of Fusobacterium, Porphyromonas, p-hydroxy-benzaldehyde, and palmitoyl-sphingomyelin. Through postulated effects on cell shedding (palmitoyl-sphingomyelin), inflammation (conjugated linoleate), and innate immunity (p-aminobenzoate), metabolites mediated the CRC association with Fusobacterium and Porphyromonas by 29% and 34%, respectively. Overall, palmitoyl-sphingomyelin correlated directly with abundances of Enterobacteriaceae (Gammaproteobacteria), three Actinobacteria and five Firmicutes. Only Parabacteroides correlated inversely with palmitoyl-sphingomyelin. Other lipids correlated inversely with Alcaligenaceae (Betaproteobacteria). Six Bonferroni-significant correlations were found, including low indolepropionate and threnoylvaline with Actinobacteria and high erythronate and an uncharacterized metabolite with Enterobacteriaceae.ConclusionsFeces from CRC cases had very strong microbe-metabolite correlations that were predominated by Enterobacteriaceae and Actinobacteria. Metabolites mediated a direct CRC association with Fusobacterium and Porphyromonas, but not an inverse association with Clostridia and Lachnospiraceae. This study identifies complex microbe-metabolite networks that may provide insights on neoplasia and targets for intervention.

Dataset Information

Describing the fecal metabolome in cryogenically collected samples from healthy participants.

Publications

Describing the fecal metabolome in cryogenically collected samples from healthy participants.

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