K-Clique Multiomics Framework: A Novel Protocol to Decipher the Role of Gut Microbiota Communities in Nutritional Intervention Trials.

faecal metabolomics k-clique communities machine learning metagenomics network of interactions volatilome

Journal

Metabolites
ISSN: 2218-1989
Titre abrégé: Metabolites
Pays: Switzerland
ID NLM: 101578790

Informations de publication

Date de publication:
10 Aug 2022
Historique:
received: 27 06 2022
revised: 03 08 2022
accepted: 04 08 2022
entrez: 25 8 2022
pubmed: 26 8 2022
medline: 26 8 2022
Statut: epublish

Résumé

The availability of omics data providing information from different layers of complex biological processes that link nutrition to human health would benefit from the development of integrated approaches combining holistically individual omics data, including those associated with the microbiota that impacts the metabolisation and bioavailability of food components. Microbiota must be considered as a set of populations of interconnected consortia, with compensatory capacities to adapt to different nutritional intake. To study the consortium nature of the microbiome, we must rely on specially designed data analysis tools. The purpose of this work is to propose the construction of a general correlation network-based explorative tool, suitable for nutritional clinical trials, by integrating omics data from faecal microbial taxa, stool metabolome (1H NMR spectra) and GC-MS for stool volatilome. The presented approach exploits a descriptive paradigm necessary for a true multiomics integration of data, which is a powerful tool to investigate the complex physiological effects of nutritional interventions.

Identifiants

pubmed: 36005608
pii: metabo12080736
doi: 10.3390/metabo12080736
pmc: PMC9412844
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : European Union
ID : FP7 grant agreement n° 311876: Pathway-27.

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Auteurs

Carlo Mengucci (C)

Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.

Lorenzo Nissen (L)

Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
Interdepartmental Centre for Agri-Food Industrial Research (CIRI Agrifood), University of Bologna, 47521 Cesena, Italy.

Gianfranco Picone (G)

Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.

Corinne Malpuech-Brugère (C)

Unité de Nutrition Humaine (UNH), Université Clermont Auvergne, INRAE, CRNH Auvergne, F-63000 Clermont-Ferrand, France.

Caroline Orfila (C)

School of Food Science and Nutrition, University of Leeds, Leeds LS2 9JT, UK.

Luigi Ricciardiello (L)

Gastroenterological Unit, Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40138 Bologna, Italy.

Alessandra Bordoni (A)

Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
Interdepartmental Centre for Agri-Food Industrial Research (CIRI Agrifood), University of Bologna, 47521 Cesena, Italy.

Francesco Capozzi (F)

Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
Interdepartmental Centre for Agri-Food Industrial Research (CIRI Agrifood), University of Bologna, 47521 Cesena, Italy.

Andrea Gianotti (A)

Department of Agricultural and Food Sciences (DISTAL), University of Bologna, 47521 Cesena, Italy.
Interdepartmental Centre for Agri-Food Industrial Research (CIRI Agrifood), University of Bologna, 47521 Cesena, Italy.

Classifications MeSH