ESS: A Tool for Genome-Scale Quantification of Essentiality Score for Reaction/Genes in Constraint-Based Modeling - Zhang, Cheng; Bidkhori, Gholamreza; Benfeitas, Rui; Lee, Sunjae; Arif, Muhammad; Uhlén, Mathias; Mardinoglu, Adil (Frontiers in Physiology, 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 apart from using topologic parameters, and is potentially useful to investigate the metabolic pathway differences between different organisms, cells, tissues and/or cancers. We demonstrate its application in the wild-type and ldh knock-out E. coli core model, 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.