Multivariate Analysis in Microbiome Description: Correlation of Human Gut Protein Degraders, Metabolites, and Predicted Metabolic Functions

• Published in: Frontiers in microbiology Vol. 12; p. 723479
• Main Authors: Raimondi, Stefano, Calvini, Rosalba, Candeliere, Francesco, Leonardi, Alan, Ulrici, Alessandro, Rossi, Maddalena, Amaretti, Alberto
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 17-09-2021
• Subjects: ASCA; data fusion; function prediction; gut microbiota; metagenomics; Microbiology; protein fermentation
• ISSN: 1664-302X; 1664-302X
• DOI: 10.3389/fmicb.2021.723479

Protein catabolism by intestinal bacteria is infamous for releasing many harmful compounds, negatively affecting the health status, both locally and systemically. In a previous study, we enriched in protein degraders the fecal microbiota of five subjects, utilizing a medium containing protein and peptides as sole fermentable substrates and we monitored their evolution by 16S rRNA gene profiling. In the present study, we fused the microbiome data and the data obtained by the analysis of the volatile organic compounds (VOCs) in the headspace of the cultures. Then, we utilized ANOVA simultaneous component analysis (ASCA) to establish a relationship between metabolites and bacteria. In particular, ASCA allowed to separately assess the effect of subject, time, inoculum concentration, and their binary interactions on both microbiome and volatilome data. All the ASCA submodels pointed out a consistent association between indole and
Escherichia–Shigella
, and the relationship of butyric, 3-methyl butanoic, and benzenepropanoic acids with some bacterial taxa that were major determinants of cultures at 6 h, such as Lachnoclostridiaceae (
Lachnoclostridium
), Clostridiaceae (
Clostridium sensu stricto
), and Sutterellaceae (
Sutterella
and
Parasutterella
). The metagenome reconstruction with PICRUSt2 and its functional annotation indicated that enrichment in a protein-based medium affected the richness and diversity of functional profiles, in the face of a decrease of richness and evenness of the microbial community. Linear discriminant analysis (LDA) effect size indicated a positive differential abundance (
p
< 0.05) for the modules of amino acid catabolism that may be at the basis of the changes of VOC profile. In particular, predicted genes encoding functions belonging to the superpathways of ornithine, arginine, and putrescine transformation to GABA and eventually to succinyl-CoA, of methionine degradation, and various routes of breakdown of aromatic compounds yielding succinyl-CoA or acetyl-CoA became significantly more abundant in the metagenome of the bacterial community.