The need for an integrated multi‐OMICs approach in microbiome science in the food system

微生物群 蛋白质组 杠杆(统计) 基因组 数据科学 背景(考古学) 功能(生物学) 计算机科学 生物技术 生物 生物信息学 人工智能 生物化学 进化生物学 基因 古生物学
作者
Ilario Ferroncono,Kalliopi Rantsiou,Ryan McClure,Tanja Kostić,Rafael Soares Correa de Souza,Lene Lange,Jamie A. FitzGerald,Aïcha Kriaa,Paul D. Cotter,Emmanuelle Maguin,Bettina Schelkle,Michael Schloter,Gabriele Berg,Angela Sessitsch,Luca Simone Cocolin,The MicrobiomeSupport Consortium
出处
期刊:Comprehensive Reviews in Food Science and Food Safety [Wiley]
卷期号:22 (2): 1082-1103 被引量:5
标识
DOI:10.1111/1541-4337.13103
摘要

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.
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