Resource Balance Analysis: a promising tool for the quantitative prediction of genome-wide resource allocation in bacteria

Growth is a highly optimized process in bacteria since the battle for the conquest of ecological niches is though. Understanding the key elements governing the growth rate management is then crucial to further understand and predict the bacterium behavior with respect to various environmental conditions. In this context, we have proposed in [Goelzer et al, Automatica 2011], a promising theoretical framework, so-called Resource Balance Analysis (RBA) formalizing the problem of resource repartition at the cell scale as a convex optimization problem. In this talk, we present the biological validation of this theoretical framework by applying it on the Gram-positive model bacterium Bacillus subtilis. To this end, through the European Project BasynTech, we have generated a dedicated and large fluxomic and proteomic datasets for grown in various conditions. We have used these data to calibrate/validate our RBA method leading to successful identification of over 600 parameters, including estimated activities of individual enzymes under various conditions. We then show in this talk that calibrated RBA predicted accurately and quantitatively the allocation of resources between 72 cellular processes in a new condition. Based on our in silico framework, we inferred suboptimal pathways (expressed above cellular demand) and validated experimentally that inactivation of some of these pathways entailed increased growth rate under appropriate conditions.

References:

Goelzer, A., Fromion, V., & Scorletti, G. (2011). Cell design in bacteria as a convex optimization problem. Automatica, 47(6), 1210-1218.