Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany; Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany.
Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany; Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany.
Biotechnol Adv. 2023 Oct;67:108203. doi: 10.1016/j.biotechadv.2023.108203. Epub 2023 Jun 20.
Temperature affects cellular processes at different spatiotemporal scales, and identifying the genetic and molecular mechanisms underlying temperature responses paves the way to develop approaches for mitigating the effects of future climate scenarios. A systems view of the effects of temperature on cellular physiology can be obtained by focusing on metabolism since: (i) its functions depend on transcription and translation and (ii) its outcomes support organisms' development, growth, and reproduction. Here we provide a systematic review of modelling efforts directed at investigating temperature effects on properties of single biochemical reactions, system-level traits, metabolic subsystems, and whole-cell metabolism across different prokaryotes and eukaryotes. We compare and contrast computational approaches and theories that facilitate modelling of temperature effects on key properties of enzymes and their consideration in constraint-based as well as kinetic models of metabolism. In addition, we provide a summary of insights from computational approaches, facilitating integration of omics data from temperature-modulated experiments with models of metabolic networks, and review the resulting biotechnological applications. Lastly, we provide a perspective on how different types of metabolic modelling can profit from developments in machine learning and models of different cellular layers to improve model-driven insights into the effects of temperature relevant for biotechnological applications.
温度会在不同时空尺度上影响细胞过程，而确定温度响应背后的遗传和分子机制为开发减轻未来气候情景影响的方法铺平了道路。通过关注代谢，可以从系统的角度了解温度对细胞生理学的影响，因为：(i) 代谢的功能取决于转录和翻译，(ii) 其结果支持生物体的发育、生长和繁殖。在这里，我们对针对单个生化反应、系统水平特征、代谢子系统和不同原核生物和真核生物整个细胞代谢的温度对其性质的影响进行建模的研究进行了系统的综述。我们比较和对比了促进酶的温度效应的关键特性建模的计算方法和理论，并在代谢的约束性和动力学模型中考虑了这些特性。此外，我们还总结了来自计算方法的见解，这些见解促进了从温度调节实验获得的组学数据与代谢网络模型的整合，并回顾了由此产生的生物技术应用。最后，我们提供了一个视角，说明不同类型的代谢建模如何从机器学习的发展和不同细胞层的模型中受益，以改善对与生物技术应用相关的温度影响的模型驱动洞察。
