Analysis of Two-Liquid-Phase Multistep Biooxidation Based on a Process Model:  Indications for Biological Energy Shortage

Abstract

A process model for whole-cell biocatalysis in a two-liquid-phase system including cell growth and bioconversion kinetics was developed. The reaction considered is the kinetically controlled multistep oxidation of pseudocumene to 3,4-dimethylbenzaldehyde catalyzed by recombinant Escherichia coli expressing the Pseudomonas putida genes encoding xylene monooxygenase (XMO). XMO catalyzes the successive oxygenation of one methyl group of xylenes to corresponding alcohols, aldehydes, and acids. The biocatalytic process includes cells growing in fed-batch mode and a two-liquid-phase system consisting of bis-(2-ethylhexyl)phthalate as organic carrier solvent and an aqueous minimal medium in a phase ratio of 1:1. The process model comprises a description of the bioconversion kinetics, mass transfer kinetics, cell growth, and mass balances for both the aqueous and the organic phase. Bioconversion kinetics and consistent process simulation indicated the occurrence of direct substrate uptake from the organic phase and provided evidence for a pH-influenced competition for NADH between XMO and the respiratory chain with its consequential impact on bioconversion and cell growth. For the simulation of such differential NADH limitation, a pH-dependent feedback inhibition of the NADH consuming bioconversions was introduced as a modeling tool, which allowed good simulations of biotransformation experiments performed at varying pH, scale, and initial substrate concentration. Moreover, modeling indicated a product inhibition in the second oxidation step, which could be confirmed experimentally. A sensitivity analysis for the aqueous-organic mass transfer coefficient showed that this transfer is not critical for the process performance and emphasized the efficient substrate-cell transfer in the investigated two-liquidphase process. Based on a process model, this study provides an in-depth analysis of a biooxidation process based on growing cells with indications for biological energy shortage as a limiting factor.

NADH Availability Limits Asymmetric Biocatalytic Epoxidation in a Growing Recombinant Escherichia coli Strain

“…7). This is reasonable, as mass transfer over the phase boundary has been shown not to be limiting in the system under investigation and recombinant E. coli strains have been found to take up aromatic hydrocarbons such as styrene and pseudocumene directly from the organic phase (9,54). Such direct styrene uptake also becomes obvious considering the kinetics given by the curve in Fig.…”

“…However, during cell growth, various reactions-especially oxidative phosphorylation-consume high amounts of reduction equivalents (59). The synthesis and presence of an active NAD(P)H-consuming oxygenase will thus also influence the metabolism of growing cells; decrease growth yields on energy sources; cause stress; and reduce growth rate, viability, and metabolic activity (4,9,58).…”

Application of modeling and simulation tools for the evaluation of biocatalytic processes: A future perspective

“…When the focus of the model is on reactor design, mass balances are also included to describe/compare various reactor configurations (batch or fed-batch vs. continuous). Moreover, mass transfer limitations are considered particularly when building models for immobilized enzyme systems 29 as well as biphasic systems (e.g., between organic and aqueous phases when organic solvents are used in the biocatalytic process 17,19,31 ). The effects of mixing and hydrodynamics in reactors have typically been neglected by assuming ideally mixed conditions (homogenous concentration throughout the reactor), which were described using the continuously stirred tank reactor (CSTR) concept.…”

“…Furthermore, the identification of these kinetic models is done using typical progress-time curve measurements with substrate-enzyme tests in batch and also enantiomeric excess curves. On the other hand, the process models developed with the aim of describing conversion performance in various reactor configurations naturally contain more parameters, e.g., 23 in the case of the whole-cell biocatalysis study of Buhler et al 19 These process models can also explain more variables, e.g., upto seven variables in the case of Buhler et al 19 The higher the number of model parameters, however, the more measurements-or better put, the more informationrich measurements-are needed for their identification. Hence, studies dealing with process models require measurements of substrate consumption and product formation in reactors.…”

“…Another important anecdote related to the unidentifiability issue can be found in the whole-cell biocatalysis study of Buhler et al, 19 which reports that different parameter values had to be used when describing process performance data obtained from batch runs at different scales (2 L vs. 30 L). The authors attributed this issue to poor understanding of external influences on the cell metabolism.…”