Prediction of proton exchange and bacterial growth on various substrates using constraint-based modeling approach

Abstract

Proton exchange between cells and medium is one of the most important factors affecting culture pH, and hence its prediction is advantageous. In this research, proton exchange flux across the cell membrane was predicted using a genome-scale model. Calculated proton exchange flux was then exploited as a criterion to predict the trends and intensities of pH changes in cultures of Bacillus subtilis containing various C-sources, i.e. glucose, sucrose, glycerol, lactate, and citrate, as well as N-sources, i.e. ammonium chloride, sodium nitrate, urea, and histidine. The results showed that glucose, sucrose, and glycerol lowered culture pH as compared to citrate and lactate, which raised it. With regard to N-sources, the model predicted that ammonium chloride lowered culture pH while other sources raised pH. Furthermore, maximum theoretical biomass yield using the various C&N-sources was calculated, and sensitivity of microbial growth to proton exchange flux was investigated using robustness analysis to identify the effect of pH on growth of B. subtilis using different substrates. Finally, the effect of ammonium nitrate, a widely used nitrogen source, on growth of B. subtilis was studied. Experimental data obtained by cultivation of B. subtilis DSM 3256 on mineral salt media containing various C&N-sources were used to confirm model predictions. Model predictions were in good agreement with the experimental results for all of the examined C-sources as well as ammonium chloride and sodium nitrate as N-sources. However, the predictions for the N-sources urea and histidine showed deviations, possibly because these two compounds serve as both C&N-sources.

Computational tools for metabolic engineering

“…Constraint-based modeling has also been used in bioprocess applications for optimization of media composition (Varma and Palsson, 1994), pH balance (Motamedian and Naeimpoor, 2011), aerobic versus anaerobic switch times (Hjersted and Henson, 2006), and microbial co-cultures (Hanly and Henson, 2011). …”