Cell design in bacteria as a convex optimization problem

Abstract

International audienceIn this paper, we investigate the prediction of the cell composition of bacteria with respect to their medium. By modeling the bacterium as an interconnection of subsystems, the problem is written as a nonsmooth convex optimization problem equivalent to a Linear Programming feasibility problem. We then obtain a new method, called Resource Balance Analysis (RBA), predicting the distribution of the available resources in the medium among the various cellular subsystems. Beyond its predictive capability, the proposed approach grasps some fundamental aspects of the bacterium physiology by including a refined model. This method reveals the existence of an intrinsic bottleneck in the system resource distribution of the bacterium, leading to the existence of a structural limitation of its growth rate which can be predicted. RBA is also able to predict the configuration of the metabolic network for a given medium at steadystate regimen which nicely fits the available experimental results for the gram-positive model bacterium Bacillus subtilis

Comprehensive Absolute Quantification of the Cytosolic Proteome of Bacillus subtilis by Data Independent, Parallel Fragmentation in Liquid Chromatography/Mass Spectrometry (LC/MSE)

“…3). For higher growth rates (condition S : ϭ 0.47 h Ϫ1 , condition CH : ϭ 1.01 h Ϫ1 ), the portion of translational apparatus is increasing from 22 to 27% of the total protein mass in agreement with theoretical expectations and experimental results (44,46) (Table III). As expected, the investment of B. subtilis in amino acid synthesis is decreasing from 13% in condition S to 5% in condition CH because of presence of amino acids in the growth medium while the proportion of amino acid degradation is increasing from 1 to 10%.…”

Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth

“…Building upon previous works (1,6,15,18,23,25,26), our approach is based on the fact that growth is inherently autocatalytic: The cellular machinery to sustain metabolism is itself a product of metabolism. Our foci have therefore been the net stoichiometric and energetic implications of diurnal growth on the de novo synthesis of proteins and other cellular macromolecules.…”

“…1. In contrast to conventional FBA, and following recent developments in constraint-based analysis (18,(23)(24)(25)(26), the capacity constraints of individual reactions are explicitly part of the model.…”

“…Our model significantly improves upon previous computational analyses of diurnal phototrophic growth (14,(16)(17)(18) and takes recent developments in constraintbased analysis into account (19)(20)(21)(22). Our approach is closely related to resource balance analysis (23,24) and dynamic enzymecost flux balance analysis (25), as well as integrated metabolism and gene expression (ME) models (21,26), but explicitly accounts for the properties of diurnal phototrophic growth.…”

Modelling and multiobjective optimization for simulation of cyanobacterial metabolism

“…Resource Balance Analysis (RBA) (Goelzer et al, 2011), one of the firsts approaches in this direction, introduces three additional design constraints (metabolic capability constraint, translation capability constraint and density constraint) that account for structural and resource limitations that are found in real cells. The arising problem is equivalent to an LP optimisation problem, and its solution describes more accurately how the available resources in the medium are distributed among the various cellular subsystems.…”