(192r) Modeling of Lactic Acid Production From Lignocellulosic Residues Using a Hybrid Cybernetic Approach
Over recent years lactic acid has received considerable attention as a potential raw material for several industrial chemicals (e.g. ethyl lactate, propylene oxide, acetaldehyde, acrylic acid) and as a feedstock monomer for biodegradable lactic acid based plastics (PLA). Lignocellulosic residues are considered to be attractive sustainable raw materials for the microbial production of lactic acid because they are renewable, inexpensive and available in large quantities. However, the composition of monosaccharide of lignocellulosic biomass varies considerably depending on its plant origin, which makes substrate screening and process optimization expensive.
In this work, we present a comprehensive model for lactic acid production, which incorporates metabolism of all quantitatively relevant sugars (glucose, galactose, mannose, arabinose, xylose) present in lignocellulosic biomass. As a model microorganism we selected the lactic acid bacteria Pediococcus pentosaceus DSM 20336 due to its ability to ferment pentoses. In our approach we used the hybrid cybernetic framework (HCM) (Kim et al., 2008; Song et al., 2009) which views the uptake fluxes of substrates being distributed among different elementary modes (EMs) of a metabolic network in a regulatory manner. We use this feature to predict simultaneous and sequential consumption of mixed substrates and lactic acid yield. We constructed a metabolic network for Pediococcus pentosaceus based on literature data reported for lactic acid bacteria and pathway information obtained from internet databases. The kinetic parameters of the HCM were estimated from batch-fermentation experiments using the respective monosaccharides as carbon sources. The model shows close agreement with various data sets of mixed-sugars fermentation experiments. Thus, the model can be a tool for time- and cost-saving evaluation of any lignocellulosic substrate and could also be employed for process optimization. By this, we attempt to contribute to the implementation of lignocellulosic residues in industrial lactic acid fermentation.
We gratefully aknowledge financial support by Max Buchner Research Foundation (MBFSt 2824) and the German Academic Exchange Service (DAAD).
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