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Durán, C.* ; Ciucci, S.* ; Palladini, A. ; Ijaz, U.Z.* ; Zippo, A.G.* ; Sterbini, F.P.* ; Masucci, L.* ; Cammarota, G.* ; Ianiro, G.* ; Spuul, P.* ; Schroeder, M.* ; Grill, S.W.* ; Parsons, B.N.* ; Pritchard, D.M.* ; Posteraro, B.* ; Sanguinetti, M.C.* ; Gasbarrini, G.* ; Gasbarrini, A.* ; Cannistraci, C.V.*

Nonlinear machine learning pattern recognition and bacteria-metabolite multilayer network analysis of perturbed gastric microbiome.

Nat. Commun. 12:1926 (2021)

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The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PPIs), or bacterial infection such as Helicobacter pylori, cause significant microbial alterations. Yet, studies revealing how the commensal bacteria re-organize, due to these perturbations of the gastric environment, are in early phase and rely principally on linear techniques for multivariate analysis. Here we disclose the importance of complementing linear dimensionality reduction techniques with nonlinear ones to unveil hidden patterns that remain unseen by linear embedding. Then, we prove the advantages to complete multivariate pattern analysis with differential network analysis, to reveal mechanisms of bacterial network re-organizations which emerge from perturbations induced by a medical treatment (PPIs) or an infectious state (H. pylori). Finally, we show how to build bacteria-metabolite multilayer networks that can deepen our understanding of the metabolite pathways significantly associated to the perturbed microbial communities.

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Publication type Article: Journal article

Document type Scientific Article

Corresponding Author

ISSN (print) / ISBN 2041-1723

e-ISSN 2041-1723

Journal Nature Communications

Quellenangaben Volume: 12, Issue: 1, Article Number: 1926

Publisher Nature Publishing Group

Publishing Place London

Non-patent literature Publications

Reviewing status Peer reviewed

Institute(s) Institute of Pancreatic Islet Research (IPI)

Grants Research Grants-Doctoral Programs in Germany (DAAD)
Estonian Research Council
Dresden International Graduate School for Biomedicine and Bioengineering (DIGS-BB) - Deutsche Forschungsgemeinschaft (DFG)
TUD Forschungspool