Flux balance analysis-based metabolic modeling of microbial secondary metabolism: Current status and outlook.

IF 4.3 2区 生物学 PLoS Computational Biology Pub Date : 2023-08-24 eCollection Date: 2023-08-01 DOI:10.1371/journal.pcbi.1011391
Sizhe Qiu, Aidong Yang, Hong Zeng
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引用次数: 1

Abstract

In microorganisms, different from primary metabolism for cellular growth, secondary metabolism is for ecological interactions and stress responses and an important source of natural products widely used in various areas such as pharmaceutics and food additives. With advancements of sequencing technologies and bioinformatics tools, a large number of biosynthetic gene clusters of secondary metabolites have been discovered from microbial genomes. However, due to challenges from the difficulty of genome-scale pathway reconstruction and the limitation of conventional flux balance analysis (FBA) on secondary metabolism, the quantitative modeling of secondary metabolism is poorly established, in contrast to that of primary metabolism. This review first discusses current efforts on the reconstruction of secondary metabolic pathways in genome-scale metabolic models (GSMMs), as well as related FBA-based modeling techniques. Additionally, potential extensions of FBA are suggested to improve the prediction accuracy of secondary metabolite production. As this review posits, biosynthetic pathway reconstruction for various secondary metabolites will become automated and a modeling framework capturing secondary metabolism onset will enhance the predictive power. Expectedly, an improved FBA-based modeling workflow will facilitate quantitative study of secondary metabolism and in silico design of engineering strategies for natural product production.

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基于通量平衡分析的微生物二次代谢代谢建模:现状与展望。
在微生物中,与细胞生长的初级代谢不同,次级代谢用于生态相互作用和应激反应,是广泛应用于制药和食品添加剂等各个领域的天然产物的重要来源。随着测序技术和生物信息学工具的进步,从微生物基因组中发现了大量次生代谢产物的生物合成基因簇。然而,由于基因组规模通路重建的困难和传统通量平衡分析(FBA)对次级代谢的限制,与初级代谢相比,次级代谢的定量建模建立得很差。这篇综述首先讨论了目前在基因组规模代谢模型(GSMMs)中重建次级代谢途径的努力,以及相关的基于FBA的建模技术。此外,建议对FBA进行潜在的扩展,以提高次级代谢产物产生的预测准确性。正如这篇综述所述,各种次级代谢产物的生物合成途径重建将实现自动化,捕捉次级代谢开始的建模框架将增强预测能力。不出所料,一种改进的基于FBA的建模工作流程将有助于二次代谢的定量研究和天然产品生产工程策略的计算机设计。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology 生物-生化研究方法
CiteScore
7.10
自引率
4.70%
发文量
820
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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