A review and prospects: Multi-omics and artificial intelligence-based approaches to understanding the effects of lactic acid bacteria and yeast interactions on fermented foods
Jiaman Yuan , Donglin Ma , Yatao Yang , Yuzong Zhao , Haiwei Ren , Xiaogang Liu , Minghui Tan , Kuntai Li
{"title":"A review and prospects: Multi-omics and artificial intelligence-based approaches to understanding the effects of lactic acid bacteria and yeast interactions on fermented foods","authors":"Jiaman Yuan , Donglin Ma , Yatao Yang , Yuzong Zhao , Haiwei Ren , Xiaogang Liu , Minghui Tan , Kuntai Li","doi":"10.1016/j.ifset.2024.103874","DOIUrl":null,"url":null,"abstract":"<div><div>There are numerous reports on the effect of co-culturing lactic acid bacteria (LAB) and yeast on the quality of fermented foods. The interactions between LAB and yeast affect the flavour, texture and even safety of fermented foods. Examining the specific mechanisms of these interactions becomes essential, but existing research methods are insufficient to meet the growing demands of scientific research. Multi-omics analysis provides more comprehensive information on LAB and yeast interactions than the widely used single-omics. Additionally, although the use of bioinformatics tools such as ModelSEED and CarveMe has simplified the construction of metabolic network models, there are still shortcomings in terms of accuracy and convenience. There is an urgent need to explore new methods to accelerate the study of microbial interaction mechanisms. This review summarizes the interaction between LAB and yeast in fermented foods, as well as the current research progress in revealing their interaction using multi-omics and bioinformatics tools. In the future, artificial intelligence will be a powerful aid in constructing metabolic models and obtaining models conveniently. Elucidation of interaction mechanisms at the spatial level will become more common, and more comprehensive research results will lead to further improvements in industrial practice.</div></div>","PeriodicalId":329,"journal":{"name":"Innovative Food Science & Emerging Technologies","volume":"99 ","pages":"Article 103874"},"PeriodicalIF":6.3000,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Innovative Food Science & Emerging Technologies","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1466856424003138","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
There are numerous reports on the effect of co-culturing lactic acid bacteria (LAB) and yeast on the quality of fermented foods. The interactions between LAB and yeast affect the flavour, texture and even safety of fermented foods. Examining the specific mechanisms of these interactions becomes essential, but existing research methods are insufficient to meet the growing demands of scientific research. Multi-omics analysis provides more comprehensive information on LAB and yeast interactions than the widely used single-omics. Additionally, although the use of bioinformatics tools such as ModelSEED and CarveMe has simplified the construction of metabolic network models, there are still shortcomings in terms of accuracy and convenience. There is an urgent need to explore new methods to accelerate the study of microbial interaction mechanisms. This review summarizes the interaction between LAB and yeast in fermented foods, as well as the current research progress in revealing their interaction using multi-omics and bioinformatics tools. In the future, artificial intelligence will be a powerful aid in constructing metabolic models and obtaining models conveniently. Elucidation of interaction mechanisms at the spatial level will become more common, and more comprehensive research results will lead to further improvements in industrial practice.
期刊介绍:
Innovative Food Science and Emerging Technologies (IFSET) aims to provide the highest quality original contributions and few, mainly upon invitation, reviews on and highly innovative developments in food science and emerging food process technologies. The significance of the results either for the science community or for industrial R&D groups must be specified. Papers submitted must be of highest scientific quality and only those advancing current scientific knowledge and understanding or with technical relevance will be considered.