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Niche Construction: A Rational Engineering Strategy for Regulating Microbial Assembly to Enhance Flavor and Bioactivity of Fermented Foods

生物制造 利基 生态位 生化工程 生物 发酵 风味 生态学 代谢工程 生物技术 适应(眼睛) 计算机科学 生态位分化 计算生物学 质量(理念) 生态位建设 微生物代谢 原材料 系统生物学
作者
Na Li,Ao Zhang,Jiarong Hu,Mengting Yu,Yaao Zhou,Kai Liang,Juan J. Román-Camacho,Yanbing Shen,Jia Song,Min Wang,Yu Zheng
出处
期刊:Comprehensive Reviews in Food Science and Food Safety [Wiley]
卷期号:25 (5): e70623-e70623
标识
DOI:10.1111/1541-4337.70623
摘要

Microbial communities serve as metabolic engines that determine the flavor and bioactivity of traditional fermented foods. Nonetheless, the stochastic nature of spontaneous fermentation often leads to niche uncertainty, resulting in inconsistent product quality and unstable functional expression. Transitioning traditional, empirically driven fermentation processes into precisely controllable modern biomanufacturing systems therefore requires an urgent paradigm shift from passive observation to active ecological engineering. In this review, we propose niche construction as a core strategy for the directional manipulation of microbial community assembly. We systematically examine the major dimensions of ecological niches in fermentation systems, including resource, environmental, spatial, and biotic niches, and further discuss how their temporal dynamics regulate microbial community assembly through dispersal, selection, ecological drift, and diversification. In addition, we assess specific engineering strategies based on niche construction, including the precise design of raw material substrates and the dynamic feedback regulation of fermentation parameters. Niche construction can reduce assembly stochasticity by guiding microorganisms from the occupation of available realized niches toward the expression of desired functional niches, thereby stabilizing flavor formation, bioactive metabolite production, and safety-related functions. Looking ahead, we explore the integration of artificial intelligence with multi-omics approaches for real-time niche prediction and the use of 3D printing to create spatially structured substrates, thereby enabling the precise manipulation of microbial spatial niches.
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