(190a) IMPACT Of Intracellular Crowding Conditions On Reaction Rates

Several chemicals are produced by microbial fermentation, for example the succinic acid that can be synthesized from glycerol by sundry microorganisms, among them Actinobacillus succionogenes which we have been studying in the past few years [1,2].

However, the synthesis of a metabolite of interest is in general accompanied by the formation of by-products. The simulation and analysis of the factors that affect the metabolism allow its further manipulation in order to improve the production of the target metabolite and minimize the by-products one.

The environmental conditions play an important role on reactions, and the cell contains a complex, heterogeneous, and crowded media, where the volume occupied by the molecules represent about 40% of the total volume. Moreover, the number of enzymes and metabolites in a fraction of the cellular space can be large [3].

Due to the impossibility that two molecules occupy the same at the same time, the intracellular crowding conditions affect the reactions rate in two opposite ways: 1) decreasing the diffusion of the molecules, and 2) increasing their thermodynamic activity [4]. 

Several methodologies have been proposed to simulate reaction-diffusion systems, among them is kinetic Monte Carlo (kMC), where each molecules is tracked during its journey, although this respects the impenetrability of the molecules it become a computationally expensive task for long times simulation and/or large number of molecules.

On the other hand Lattice Boltzmann Method (LBM) can efficiently handle a large number of molecules, nevertheless their volume is neglected, and therefore also the steric repulsion.

The aim of this work is to propose a new LBM-based methodology (called cLBM) that incorporates the macromolecular crowding effects on the simulation of reaction-diffusion systems as those carried out inside the cell.

In order to validate this new methodology the results are compared with those obtained from an in-house developed lattice kMC algorithm. We use a small system of enzymatic reactions in presence of inert molecules at different concentrations as case study. Although discrepancies are found between both methodologies, cLBM provides the basis for the further simulation of metabolic networks under crowding conditions. 

References

1. Vlysidis, A., Binns, M., Webb, C., and Theodoropoulos, C. 2011. Glycerol utilisation for the production of chemicals: conversion to succinic acid, a combined experimental and computational study. Biochemical Engineering Journal, 58-59: 1-11.
2. Angeles-Martinez, L., and Theodoropoulos, C. 2012. Thermodymanic constraints in Flux Balance Analysis. Manuscript in preparation.
3. Goodsell, D.S. 1991. Inside a living cell. Trends in Biochemical Sciences 16, 203-206.
4. Chebotareva, N.A., Kurganov, B.I., and Livanova, N.B. 2004. Biochemical effects of molecular crowding. Biochemistry (Moscow) 69:1239-1251.