ESS: A Tool for Genome-Scale Quantification of Essentiality Score for Reaction/Genes in Constraint-Based Modeling
Artikel i vetenskaplig tidskrift, 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 ldh 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.

systems biology

gene essentiality

reaction essentiality

genome-scale metabolic models

constraint-based modeling

Författare

C. Zhang

Kungliga Tekniska Högskolan (KTH)

G. Bidkhori

Kungliga Tekniska Högskolan (KTH)

Rui Benfeitas

Kungliga Tekniska Högskolan (KTH)

Sunjae Lee

Kungliga Tekniska Högskolan (KTH)

Muhammad Arif

Kungliga Tekniska Högskolan (KTH)

Mathias Uhlen

Kungliga Tekniska Högskolan (KTH)

Adil Mardinoglu

King's College London

Kungliga Tekniska Högskolan (KTH)

Chalmers, Biologi och bioteknik, Systembiologi

Frontiers in Physiology

1664-042X (ISSN)

Vol. 9 1355

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Medicinsk bioteknologi (med inriktning mot cellbiologi (inklusive stamcellsbiologi), molekylärbiologi, mikrobiologi, biokemi eller biofarmaci)

Bioinformatik och systembiologi

DOI

10.3389/fphys.2018.01355

Mer information

Senast uppdaterat

2021-01-18