The need for an integrated multi‐OMICs approach in microbiome science in the food system. Issue 2 (12th January 2023)

• Record Type: Journal Article
• Authors: Ferrocino, Ilario; Rantsiou, Kalliopi; McClure, Ryan; Kostic, Tanja; de Souza, Rafael Soares Correa; Lange, Lene; FitzGerald, Jamie; Kriaa, Aicha; Cotter, Paul; Maguin, Emmanuelle; Schelkle, Bettina; Schloter, Michael; Berg, Gabriele; Sessitsch, Angela; Cocolin, Luca
• Is Part Of: Comprehensive reviews in food science and food safety. Volume 22:Issue 2(2023)
• Page Start: 1082
• Page End: 1103
• Publication Date: 2023-01-12
• Subjects: Omics integration -- microbiome -- food system -- metagenomics -- metatranscriptomics -- metaproteomics -- metabolomics; Food -- Research -- Periodicals; Food -- Safety measures -- Periodicals; 664.0072
• DOI: 10.1111/1541-4337.13103
• Languages: English
• ISSNs: 1541-4337

Abstract

Abstract: Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome‐based technologies that provide added‐value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different ‐omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex ‐omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/ ), a project supported by the European Commission, the workshop "Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research" gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome‐based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.