The Use of In Silico Genome-Scale Models for the Rational Design of Minimal Cells

Abstract

Organism-specific genome-scale metabolic models (GEMs) can be reconstructed using genome annotation and biochemical data available in literature. The systematic inclusion of biochemical reactions into a coherent metabolic network combined with the formulation of appropriate constraints reveals the set of metabolic capabilities harbored by an organism, hereby allowing the computation of growth phenotypes from genotype information. GEMs have been used thoroughly to assess growth capabilities under varying conditions and determine gene essentiality. This simulation process can rapidly generate testable hypotheses that can be applied for the systematic evaluation of growth capabilities in genome reduction efforts and the definition of a minimal cell. Here we review the most recent computational methods and protocols available for the reconstruction of genome-scale models, the formulation of objective functions, and the applications of models in the prediction of gene essentiality. These methods and applications are suited to the emerging field of genome reduction and the development of minimal cells as biological factories.