Genome-Scale Metabolic Network Models of Bacillus Species Suggest that Model Improvement is Necessary for Biotechnological Applications

Abstract

Background:A genome-scale metabolic network model (GEM) is a mathematical representation of an organism's metabolism. Today, GEMs are popular tools for computationally simulating the biotechnological processes and for predicting biochemical properties of (engineered) strains. Objectives: In the present study, we have evaluated the predictive power of two GEMs, namely iBsu1103 (for Bacillus subtilis 168) and iMZ1055 (for Bacillus megaterium WSH002). Materials and Methods: For comparing the predictive power of Bacillus subtilis and Bacillus megaterium GEMs, experimental data were obtained from previous wet-lab studies included in PubMed. By using these data, we set the environmental, stoichiometric and thermodynamic constraints on the models, and FBA is performed to predict the biomass production rate, and the values of other fluxes. For simulating experimental conditions in this study, COBRA toolbox was used. Results: By using the wealth of data in the literature, we evaluated the accuracy of in silico simulations of these GEMs. Our results suggest that there are some errors in these two models which make them unreliable for predicting the biochemical capabilities of these species. The inconsistencies between experimental and computational data are even greater where B. subtilis and B. megaterium do not have similar phenotypes. Conclusions: Our analysis suggests that literature-based improvement of genome-scale metabolic network models of the two Bacillus species is essential if these models are to be successfully applied in biotechnology and metabolic engineering.

Critical assessment of genome-scale metabolic models of Arabidopsis thaliana

“…16 Later, it was shown that Bacillus GEMs also suffer from the same problem. 17 1.2 Genome-scale-metabolic models for plants…”

New Insights on Metabolic Features of Bacillus subtilis Based on Multistrain Genome-Scale Metabolic Modeling

“…Finally, the latest model updates ( i Bsu1147 and i Bsu1144) were aiming to optimize the production of relevant added-value compounds including riboflavin, Egl-237, isobutanol, butanodiol, and serine protease. Despite the efforts in the reconstruction of B. subtilis metabolism, it has been recently shown that the current models are far from accurately predicting well-known metabolic traits of this strain [ 16 ]. Overall, any discrepancies with experimental data were mainly due to incorrect or incomplete annotations, missing reactions and/or pathways, and/or inaccurate formulation of the biomass reaction.…”