Zhang Cheng, Bidkhori Gholamreza, Benfeitas Rui, Lee Sunjae, Arif Muhammad, Uhlén Mathias, Mardinoglu Adil
Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
Front Physiol. 2018 Sep 28;9:1355. doi: 10.3389/fphys.2018.01355. eCollection 2018.
Genome-scale metabolic models (GEMs) are comprehensive descriptions of cell metabolism and have been extensively used to understand biological responses in health and disease. One such application is in determining metabolic adaptation to the absence of a gene or reaction, i.e., essentiality analysis. However, current methods do not permit efficiently and accurately quantifying reaction/gene essentiality. Here, we present Essentiality Score Simulator (ESS), a tool for quantification of gene/reaction essentialities in GEMs. ESS quantifies and scores essentiality of each reaction/gene and their combinations based on the stoichiometric balance using synthetic lethal analysis. This method provides an option to weight metabolic models which currently rely mostly on topologic parameters, and is potentially useful to investigate the metabolic pathway differences between different organisms, cells, tissues, and/or diseases. We benchmarked the proposed method against multiple network topology parameters, and observed that our method displayed higher accuracy based on experimental evidence. In addition, we demonstrated its application in the wild-type and knock-out E. coli core model, as well as two human cell lines, and revealed the changes of essentiality in metabolic pathways based on the reactions essentiality score. ESS is available without any limitation at https://sourceforge.net/projects/essentiality-score-simulator.
基因组规模代谢模型（GEMs）是细胞代谢的全面描述，已被广泛用于理解健康和疾病中的生物学反应。其中一个应用是确定对基因或反应缺失的代谢适应性，即必需性分析。然而，目前的方法无法有效且准确地量化反应/基因的必需性。在此，我们提出了必需性评分模拟器（ESS），这是一种用于量化GEMs中基因/反应必需性的工具。ESS基于合成致死分析，利用化学计量平衡对每个反应/基因及其组合的必需性进行量化和评分。该方法为目前主要依赖拓扑参数的代谢模型提供了加权选项，对于研究不同生物体、细胞、组织和/或疾病之间的代谢途径差异可能有用。我们将所提出的方法与多个网络拓扑参数进行了基准测试，并根据实验证据观察到我们的方法显示出更高的准确性。此外，我们展示了其在野生型和基因敲除大肠杆菌核心模型以及两种人类细胞系中的应用，并基于反应必需性评分揭示了代谢途径中必需性的变化。ESS可在https://sourceforge.net/projects/essentiality-score-simulator上免费获取且无任何限制。
