Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Chalmers University of Technology, Gothenburg, Sweden.
Department of Biotechnology and Biomedicine, Technical University of Denmark, Kgs. Lyngby, Denmark.
Biotechnol Bioeng. 2018 Oct;115(10):2604-2612. doi: 10.1002/bit.26739. Epub 2018 Jul 25.
Modeling of metabolism at the genome-scale has proved to be an efficient method for explaining the phenotypic traits observed in living organisms. Further, it can be used as a means of predicting the effect of genetic modifications for example, development of microbial cell factories. With the increasing amount of genome sequencing data available, there exists a need to accurately and efficiently generate such genome-scale metabolic models (GEMs) of nonmodel organisms, for which data is sparse. In this study, we present an automatic reconstruction approach applied to 24 Penicillium species, which have potential for production of pharmaceutical secondary metabolites or use in the manufacturing of food products, such as cheeses. The models were based on the MetaCyc database and a previously published Penicillium GEM and gave rise to comprehensive genome-scale metabolic descriptions. The models proved that while central carbon metabolism is highly conserved, secondary metabolic pathways represent the main diversity among species. The automatic reconstruction approach presented in this study can be applied to generate GEMs of other understudied organisms, and the developed GEMs are a useful resource for the study of Penicillium metabolism, for example, for the scope of developing novel cell factories.
对基因组规模的代谢进行建模已被证明是解释生物体内观察到的表型特征的有效方法。此外，它还可以作为预测遗传修饰效果的一种手段，例如，微生物细胞工厂的开发。随着越来越多的基因组测序数据可用，需要准确有效地生成非模式生物的此类基因组规模代谢模型（GEM），因为这些生物的数据很少。在这项研究中，我们提出了一种自动重建方法，应用于 24 种青霉属物种，这些物种具有生产药物次生代谢物或用于生产奶酪等食品的潜力。这些模型基于 MetaCyc 数据库和之前发表的青霉属 GEM，生成了全面的基因组规模代谢描述。这些模型证明，虽然中心碳代谢高度保守，但次生代谢途径是物种之间的主要多样性。本研究中提出的自动重建方法可用于生成其他研究较少的生物体的 GEM，所开发的 GEM 是研究青霉属代谢的有用资源，例如，用于开发新型细胞工厂的范围。
