Microorganisms play a central role in biotechnology and it is key that we develop strategies to engineer and optimize their functionality. To this end, most efforts have focused on introducing genetic manipulations in microorganisms which are then grown either in monoculture or in mixed‐species consortia. An alternative strategy to optimize microbial processes is to rationally engineer the environment in which microbes grow. The microbial environment is multidimensional, including factors such as temperature, pH, salinity, nutrient composition, etc. These environmental factors all influence the growth and phenotypes of microorganisms and they generally “interact” with one another, combining their effects in complex, non‐additive ways. In this piece, we overview the origins and consequences of these “interactions” between environmental factors and discuss how they have been built into statistical, bottom‐up predictive models of microbial function to identify optimal environmental conditions for monocultures and microbial consortia. We also overview alternative “top‐down” approaches, such as genetic algorithms, to finding optimal combinations of environmental factors. By providing a brief summary of the state of this field, we hope to stimulate further work on the rational manipulation and optimization of the microbial environment.

中文翻译：

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通过合理的环境操纵优化微生物功能

微生物在生物技术中发挥着核心作用，我们制定策略来设计和优化其功能至关重要。为此，大多数努力都集中在对微生物进行基因操作，然后将其在单一栽培或混合物种联合体中生长。优化微生物过程的另一种策略是合理设计微生物生长的环境。微生物环境是多维的，包括温度、pH、盐度、营养成分等因素。这些环境因素都会影响微生物的生长和表型，并且它们通常会相互“相互作用”，以复杂的、非特定的方式将其影响结合起来。加法方式。在这篇文章中，我们概述了环境因素之间这些“相互作用”的起源和后果，并讨论了如何将它们构建到微生物功能的统计、自下而上的预测模型中，以确定单一栽培和微生物群落的最佳环境条件。我们还概述了替代的“自上而下”方法，例如遗传算法，以寻找环境因素的最佳组合。通过对该领域的现状进行简要总结，我们希望能够促进在微生物环境的合理操纵和优化方面的进一步工作。