Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism.
Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism.
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DOI：
10.1186/s12864-018-4905-5
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发表时间：
2018-07-04
期刊：
影响因子：
4.4
通讯作者：
Breitling R
中科院分区：
文献类型：
--
作者：
Amara A;Takano E;Breitling R
链霉菌种类产生大量具有临床和生物技术重要性的次生代谢物，特别是抗生素。代谢工程、合成和系统生物学的最新发展为利用链霉菌的次生代谢提供了新的机会，但在不耗时优化的情况下实现工业水平的生产仍然具有挑战性。基因组尺度的代谢建模已被证明是指导代谢工程策略以加速菌株优化的有力工具，为此已经开发了几代链霉菌代谢模型。在这里，我们提出了一种基于基因组尺度化学计量学约束的coelicolor链霉菌代谢模型的最新更新，该模型是该属抗生素生产的主要模式生物。我们表明，更新的模型能够更好地预测代谢通量和生物量，并促进多组学数据的整合分析，如转录组学，蛋白质组学和代谢组学。本文提出的更新模型为链霉菌的下一代代谢工程尝试提供了增强的基础。本文的在线版本（10.1186/s12864-018-4905-5）包含补充材料，授权用户可以使用。
Streptomyces species produce a vast diversity of secondary metabolites of clinical and biotechnological importance, in particular antibiotics. Recent developments in metabolic engineering, synthetic and systems biology have opened new opportunities to exploit Streptomyces secondary metabolism, but achieving industry-level production without time-consuming optimization has remained challenging. Genome-scale metabolic modelling has been shown to be a powerful tool to guide metabolic engineering strategies for accelerated strain optimization, and several generations of models of Streptomyces metabolism have been developed for this purpose. Here, we present the most recent update of a genome-scale stoichiometric constraint-based model of the metabolism of Streptomyces coelicolor, the major model organism for the production of antibiotics in the genus. We show that the updated model enables better metabolic flux and biomass predictions and facilitates the integrative analysis of multi-omics data such as transcriptomics, proteomics and metabolomics. The updated model presented here provides an enhanced basis for the next generation of metabolic engineering attempts in Streptomyces. The online version of this article (10.1186/s12864-018-4905-5) contains supplementary material, which is available to authorized users.
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影响因子：
11.9
作者：
Carbonell P;Currin A;Jervis AJ;Rattray NJ;Swainston N;Yan C;Takano E;Breitling R
通讯作者：
Breitling R
影响因子：
14.9
作者：
Caspi R;Billington R;Ferrer L;Foerster H;Fulcher CA;Keseler IM;Kothari A;Krummenacker M;Latendresse M;Mueller LA;Ong Q;Paley S;Subhraveti P;Weaver DS;Karp PD
通讯作者：
Karp PD
影响因子：
4.4
作者：
Borodina, I;Schöller, C;Nielsen, J
通讯作者：
Nielsen, J
DOI：
10.1016/j.csbj.2014.08.005
发表时间：
2014-08
影响因子：
6
作者：
Fong, Stephen S
通讯作者：
Fong, Stephen S
影响因子：
4.4
作者：
Alam MT;Merlo ME;STREAM Consortium;Hodgson DA;Wellington EM;Takano E;Breitling R
通讯作者：
Breitling R