Evaluating E. coli genome-scale metabolic model accuracy with high-throughput mutant fitness data.

Autor: Bernstein DB; Department of Bioengineering, University of California, Berkeley, CA, USA., Akkas B; Department of Bioengineering, University of California, Berkeley, CA, USA., Price MN; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA., Arkin AP; Department of Bioengineering, University of California, Berkeley, CA, USA.; Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Jazyk: angličtina
Zdroj: Molecular systems biology [Mol Syst Biol] 2023 Dec 06; Vol. 19 (12), pp. e11566. Date of Electronic Publication: 2023 Oct 27.
DOI: 10.15252/msb.202311566
Abstrakt: The Escherichia coli genome-scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision-recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene-protein-reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high-throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.
(© 2023 The Authors. Published under the terms of the CC BY 4.0 license.)
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje