Revealing the dynamics and mechanisms of bacterial interactions in cheese production with metabolic modelling

IF 6.8 1区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Maxime Lecomte , Wenfan Cao , Julie Aubert , David James Sherman , Hélène Falentin , Clémence Frioux , Simon Labarthe
{"title":"Revealing the dynamics and mechanisms of bacterial interactions in cheese production with metabolic modelling","authors":"Maxime Lecomte ,&nbsp;Wenfan Cao ,&nbsp;Julie Aubert ,&nbsp;David James Sherman ,&nbsp;Hélène Falentin ,&nbsp;Clémence Frioux ,&nbsp;Simon Labarthe","doi":"10.1016/j.ymben.2024.02.014","DOIUrl":null,"url":null,"abstract":"<div><p>Cheese taste and flavour properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of <em>Lactococcus lactis</em>, <em>Lactobacillus plantarum</em> and <em>Propionibacterium freudenreichii</em> during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This model accurately predicts the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration revealed additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added value of dynamic metabolic modeling for the comprehension of fermented food processes.</p></div>","PeriodicalId":18483,"journal":{"name":"Metabolic engineering","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1096717624000302/pdfft?md5=ff6cbb44138856d374b3d067863cae70&pid=1-s2.0-S1096717624000302-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Metabolic engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1096717624000302","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Cheese taste and flavour properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of Lactococcus lactis, Lactobacillus plantarum and Propionibacterium freudenreichii during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This model accurately predicts the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration revealed additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added value of dynamic metabolic modeling for the comprehension of fermented food processes.

利用代谢模型揭示奶酪生产中细菌相互作用的动态和机制。
奶酪的口感和风味特性源于微生物群落中复杂的新陈代谢过程。深入了解这些机制,就有可能通过设计微生物群落来改进工业生产过程和最终产品的质量。在这项研究中,我们分析了由乳酸乳球菌、植物乳杆菌和弗氏丙酸杆菌组成的三物种群落在为期七周的奶酪生产过程中的新陈代谢特征。利用基因组尺度代谢模型和 omics 数据集成,我们通过单培养实验对个体动力学进行了建模和校准,并将这些模型耦合起来以捕捉群落的新陈代谢。该模型准确预测了群落的动态,揭示了每个微生物物种对感官化合物生产的贡献。进一步的新陈代谢探索揭示了细菌物种之间更多可能的相互作用。这项工作为预测整个群落的新陈代谢提供了一个方法框架,并凸显了动态新陈代谢建模在理解发酵食品过程方面的附加价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Metabolic engineering
Metabolic engineering 工程技术-生物工程与应用微生物
CiteScore
15.60
自引率
6.00%
发文量
140
审稿时长
44 days
期刊介绍: Metabolic Engineering (MBE) is a journal that focuses on publishing original research papers on the directed modulation of metabolic pathways for metabolite overproduction or the enhancement of cellular properties. It welcomes papers that describe the engineering of native pathways and the synthesis of heterologous pathways to convert microorganisms into microbial cell factories. The journal covers experimental, computational, and modeling approaches for understanding metabolic pathways and manipulating them through genetic, media, or environmental means. Effective exploration of metabolic pathways necessitates the use of molecular biology and biochemistry methods, as well as engineering techniques for modeling and data analysis. MBE serves as a platform for interdisciplinary research in fields such as biochemistry, molecular biology, applied microbiology, cellular physiology, cellular nutrition in health and disease, and biochemical engineering. The journal publishes various types of papers, including original research papers and review papers. It is indexed and abstracted in databases such as Scopus, Embase, EMBiology, Current Contents - Life Sciences and Clinical Medicine, Science Citation Index, PubMed/Medline, CAS and Biotechnology Citation Index.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信