Overall biomass yield on multiple nutrient sources.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Ohad Golan, Olivia Gampp, Lina Eckert, Uwe Sauer
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Abstract

Microorganisms primarily utilize nutrients to generate biomass and replicate. When a single nutrient source is available, the produced biomass typically increases linearly with the initial amount of that nutrient. This linear trend can be accurately predicted by "black box models", which conceptualize growth as a single chemical reaction, treating nutrients as substrates and biomass as a product. However, natural environments usually present multiple nutrient sources, prompting us to extend the black box framework to incorporate catabolism, anabolism, and biosynthesis of biomass precursors. This modification allows for the quantification of co-utilization effects among multiple nutrients on microbial biomass production. The extended model differentiates between different types of nutrients: non-degradable nutrients, which can only serve as a biomass precursor, and degradable nutrients, which can also be used as an energy source. We experimentally demonstrated using Escherichia coli that, in contrast to initial model predictions, different nutrients affect each other's utilization in a mutually dependent manner; i.e., for some combinations, the produced biomass was no longer proportional to the initial amounts of nutrients present. To account for these mutual effects within a black box framework, we phenomenologically introduced an interaction between the metabolic processes involved in utilizing the nutrient sources. This phenomenological model qualitatively captures the experimental observations and, unexpectedly, predicts that the total produced biomass is influenced not only by the combination of nutrient sources but also by their relative initial amounts - a prediction we subsequently validated experimentally. Moreover, the model identifies which metabolic processes - catabolism, anabolism, or precursor biosynthesis-is affected in each specific nutrient combination, offering insights into microbial metabolic coordination.

多种营养源的总生物量产量。
微生物主要利用营养物质产生生物量并进行复制。当单一营养源可用时,所产生的生物量通常随该营养源的初始量线性增加。这种线性趋势可以通过“黑箱模型”准确预测,该模型将生长概念化为单一的化学反应,将营养物质视为基质,将生物量视为产物。然而,自然环境通常存在多种营养来源,这促使我们将黑箱框架扩展到分解代谢、合成代谢和生物质前体的生物合成。这种修改允许量化多种营养物质对微生物生物量生产的共同利用效应。扩展模型区分了不同类型的营养物质:不可降解的营养物质,只能作为生物质前体;可降解的营养物质,也可以作为能量来源。我们用大肠杆菌实验证明,与最初的模型预测相反,不同的营养物质以相互依赖的方式影响彼此的利用;也就是说,对于某些组合,产生的生物量不再与初始存在的养分量成比例。为了在黑箱框架内解释这些相互作用,我们从现象学上介绍了利用营养源所涉及的代谢过程之间的相互作用。这个现象学模型定性地捕获了实验观察结果,并且出乎意料地预测了总生物量不仅受到营养来源组合的影响,而且还受到其相对初始量的影响——我们随后通过实验验证了这一预测。此外,该模型确定了每种特定营养组合影响的代谢过程-分解代谢,合成代谢或前体生物合成,为微生物代谢协调提供了见解。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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