Modelling microbial communities using biochemical resource allocation analysis
Modelling microbial communities using biochemical resource allocation analysis
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DOI：
10.1098/rsif.2019.0474
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发表时间：
2019-11-01
影响因子：
3.9
通讯作者：
Steuer, Ralf
中科院分区：
文献类型：
--
作者：
Sharma, Suraj;Steuer, Ralf
了解微生物群落的功能和动态是当前生物学的一个基本挑战。为了应对这一挑战，构建相互作用微生物的计算模型是不可或缺的工具。然而，在当前许多生态系统模拟中使用的微生物生长的生态动机描述与在系统和合成生物学背景下开发的详细代谢途径和基于基因组的描述之间存在巨大鸿沟。在这里，我们试图证明微生物生长的资源分配模型如何提供推进生态系统模拟及其参数化的潜力。特别是，最近在定量资源分配方面的工作使我们能够制定微生物生长的机制模型，这些模型在生理上有意义，同时在计算上易于处理。这些模型超越了Michaelis-Menten和monod型生长模型，能够解释微生物生长的显著可塑性背后的涌现特性。通过考虑蓝藻生长的粗粒度模型，我们概述了使用生化资源分配模型的效用和优势，并展示了该模型如何使我们能够解决与海洋微生物生态系统模拟相关的具体问题，包括蛋白质表达对不同环境的生理适应，几种营养物质共同限制的描述以及替代营养来源的差异使用。以及基于我们对定量细胞生理学知识的不断增加的代谢多样性的描述。
To understand the functioning and dynamics of microbial communities is a fundamental challenge in current biology. To tackle this challenge, the construction of computational models of interacting microbes is an indispensable tool. There is, however, a large chasm between ecologically motivated descriptions of microbial growth used in many current ecosystems simulations, and detailed metabolic pathway and genome-based descriptions developed in the context of systems and synthetic biology. Here, we seek to demonstrate how resource allocation models of microbial growth offer the potential to advance ecosystem simulations and their parametrization. In particular, recent work on quantitative resource allocation allow us to formulate mechanistic models of microbial growth that are physiologically meaningful while remaining computationally tractable. These models go beyond Michaelis-Menten and Monod-type growth models, and are capable of accounting for emergent properties that underlie the remarkable plasticity of microbial growth. We outline the utility and advantages of using biochemical resource allocation models by considering a coarse-grained model of cyanobacterial growth and demonstrate how the model allows us to address specific questions of relevance for the simulation of marine microbial ecosystems, including the physiological acclimation of protein expression to different environments, the description of co-limitation by several nutrients and the differential use of alternative nutrient sources, as well as the description of metabolic diversity based on our increasing knowledge about quantitative cell physiology.