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Resource allocation explains lactic acid production in mixed‐culture anaerobic fermentations
Author(s) -
Regueira Alberte,
Rombouts Julius. L.,
Wahl S. Aljoscha,
MauricioIglesias Miguel,
Lema Juan M.,
Kleerebezem Robbert
Publication year - 2021
Publication title -
biotechnology and bioengineering
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.27605
Subject(s) - fermentation , lactic acid , auxotrophy , biochemistry , microorganism , food science , amino acid , anaerobic exercise , biochemical engineering , bacteria , chemistry , biology , microbiology and biotechnology , pulp and paper industry , escherichia coli , physiology , genetics , gene , engineering
Lactate production in anaerobic carbohydrate fermentations with mixed cultures of microorganisms is generally observed only in very specific conditions: the reactor should be run discontinuously and peptides and B vitamins must be present in the culture medium as lactic acid bacteria (LAB) are typically auxotrophic for amino acids. State-of-the-art anaerobic fermentation models assume that microorganisms optimise the adenosine triphosphate (ATP) yield on substrate and therefore they do not predict the less ATP efficient lactate production, which limits their application for designing lactate production in mixed-culture fermentations. In this study, a metabolic model taking into account cellular resource allocation and limitation is proposed to predict and analyse under which conditions lactate production from glucose can be beneficial for microorganisms. The model uses a flux balances analysis approach incorporating additional constraints from the resource allocation theory and simulates glucose fermentation in a continuous reactor. This approach predicts lactate production is predicted at high dilution rates, provided that amino acids are in the culture medium. In minimal medium and lower dilution rates, mostly butyrate and no lactate is predicted. Auxotrophy for amino acids of LAB is identified to provide a competitive advantage in rich media because less resources need to be allocated for anabolic machinery and higher specific growth rates can be achieved. The Matlab™ codes required for performing the simulations presented in this study are available at https://doi.org/10.5281/zenodo.4031144.