Mapping high-growth phenotypes in the flux space of microbial metabolism
Author(s) -
Oriol Güell,
Francesco Alessandro Massucci,
Francesc Font-Clos,
Francesc Sagués,
M. Ángeles Serrano
Publication year - 2015
Publication title -
journal of the royal society interface
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.655
H-Index - 139
eISSN - 1742-5689
pISSN - 1742-5662
DOI - 10.1098/rsif.2015.0543
Subject(s) - flux balance analysis , flux (metallurgy) , benchmark (surveying) , metabolic flux analysis , phenotype , yield (engineering) , biochemical engineering , computational biology , biological system , biology , computer science , metabolism , chemistry , genetics , physics , biochemistry , thermodynamics , gene , engineering , organic chemistry , geodesy , geography
Experimental and empirical observations on cell metabolism cannot be understood as a whole without their integration into a consistent systematic framework. However, the characterization of metabolic flux phenotypes is typically reduced to the study of a single optimal state, such as maximum biomass yield that is by far the most common assumption. Here, we confront optimal growth solutions to the whole set of feasible flux phenotypes (FFPs), which provides a benchmark to assess the likelihood of optimal and high-growth states and their agreement with experimental results. In addition, FFP maps are able to uncover metabolic behaviours, such as aerobic fermentation accompanying exponential growth on sugars at nutrient excess conditions, that are unreachable using standard models based on optimality principles. The information content of the full FFP space provides us with a map to explore and evaluate metabolic behaviour and capabilities, and so it opens new avenues for biotechnological and biomedical applications.
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