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In-depth characterization of genome-scale network reconstructions for the in vitro synthesis in cell-free systems.
Biotechnology and Bioengineering ( IF 3.5 ) Pub Date : 2020-01-11 , DOI: 10.1002/bit.27249
Lisa Katharina Schuh 1 , Christian Weyler 1 , Elmar Heinzle 1
Affiliation  

Cell‐free systems containing multiple enzymes are becoming an increasingly interesting tool for one‐pot syntheses of biochemical compounds. To extensively explore the enormous wealth of enzymes in the biological space, we present methods for assembling and curing data from databases to apply them for the prediction of pathway candidates for directed enzymatic synthesis. We use Kyoto Encyclopedia of Genes and Genomes to establish single organism models and a pan‐organism model that is combining the available data from all organisms listed there. We introduce a filtering scheme to remove data that are not suitable, for example, generic metabolites and general reactions. In addition, a valid stoichiometry of reactions is required for acceptance. The networks created are analyzed by graph theoretical methods to identify a set of metabolites that are potentially reachable from a defined set of starting metabolites. Thus, metabolites not connected to such starting metabolites cannot be produced unless new starting metabolites or reactions are introduced. The network models also comprise stoichiometric and thermodynamic data that allow the definition of constraints to identify potential pathways. The resulting data can be directly applied using existing or future pathway finding tools.

中文翻译:

在无细胞系统中进行体外合成的基因组规模网络重建的深入表征。

包含多种酶的无细胞系统正成为一锅合成生化化合物的越来越有趣的工具。为了广泛地探索生物空间中酶的巨大财富,我们提出了从数据库中组装和固化数据的方法,将其用于预测定向酶合成的候选途径。我们使用《京都议定书基因与基因组百科全书》建立了单一生物体模型和一个泛生物体模型,该模型结合了此处列出的所有生物体的可用数据。我们引入了一种过滤方案,以删除不适当的数据,例如,一般代谢物和一般反应。另外,需要有效的反应化学计量才能被接受。通过图论方法对创建的网络进行分析,以从一组定义的起始代谢物中识别出一组潜在的代谢物。因此,除非引入新的起始代谢物或反应,否则不能产生与这些起始代谢物不相关的代谢物。网络模型还包括化学计量和热力学数据,允许定义约束条件以识别潜在途径。可以使用现有或将来的路径查找工具直接应用所得数据。网络模型还包括化学计量和热力学数据,允许定义约束条件以识别潜在途径。可以使用现有或将来的路径查找工具直接应用所得数据。网络模型还包括化学计量和热力学数据,允许定义约束条件以识别潜在途径。可以使用现有或将来的路径查找工具直接应用所得数据。
更新日期:2020-03-09
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