群落和单一微生物优化系统(COSMOS)。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Lavanya Raajaraam, Karthik Raman
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引用次数: 0

摘要

生物加工利用微生物单一培养和群落将可再生资源转化为有价值的产品。虽然单一栽培提供了简单性,但群落提供了代谢多样性和合作生物合成。为了系统地评估这些系统,我们开发了群落和单一微生物优化系统(COSMOS),这是一个动态计算框架,可以模拟和比较单一培养和共培养,以确定适合特定环境的最佳微生物系统。COSMOS揭示了影响生物合成性能的关键因素,如环境条件、微生物相互作用和碳源。值得注意的是,它预测在厌氧条件下,希瓦氏菌-肺炎克雷伯菌共培养是最有效的1,3-丙二醇生产者,与实验数据密切相关,包括最佳碳源浓度和接种比。其他研究结果强调了微生物群落在营养有限的过程中的恢复能力,并强调了计算工具在平衡生产力和操作简单性方面的作用。总体而言,本研究促进了微生物系统的合理设计,为可持续生物过程和循环生物经济铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

COmmunity and Single Microbe Optimisation System (COSMOS).

COmmunity and Single Microbe Optimisation System (COSMOS).

COmmunity and Single Microbe Optimisation System (COSMOS).

COmmunity and Single Microbe Optimisation System (COSMOS).

Bioprocessing utilises microbial monocultures and communities to convert renewable resources into valuable products. While monocultures offer simplicity, communities provide metabolic diversity and cooperative biosynthesis. To systematically evaluate these systems, we developed COmmunity and Single Microbe Optimisation System (COSMOS), a dynamic computational framework that simulates and compares monocultures and co-cultures to determine optimal microbial systems tailored to a specific environment. COSMOS revealed key factors shaping biosynthetic performance, such as environmental conditions, microbial interactions, and carbon sources. Notably, it predicted the Shewanella oneidensis-Klebsiella pneumoniae co-culture as the most efficient producer of 1,3-propanediol under anaerobic conditions, aligning closely with experimental data, including optimal carbon source concentrations and inoculum ratios. Additional findings highlight the resilience of microbial communities in nutrient-limited processes and emphasise the role of computational tools in balancing productivity with operational simplicity. Overall, this study advances the rational design of microbial systems, paving the way for sustainable bioprocesses and circular bio-economies.

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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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