A novel engineered strain of Methylorubrum extorquens for methylotrophic production of glycolic acid

Abstract

The conversion of CO₂ into methanol depicts one of the most promising emerging renewable routes for the chemical and biotech industry. Under this regard, native methylotrophs have a large potential for converting methanol into value-added products but require targeted engineering approaches to enhance their performances and to widen their product spectrum. Here we use a systems-based approach to analyze and engineer M. extorquens TK 0001 for production of glycolic acid. Application of constraint-based metabolic modeling reveals the great potential of M. extorquens for that purpose, which is not yet described in literature. In particular, a superior theoretical product yield of 1.0 C-mol_{Glycolic acid} C-mol_Methanol^-1 is predicted by our model, surpassing theoretical yields of sugar fermentation. Following this approach, we show here that strain engineering is viable and present 1st generation strains producing glycolic acid via a heterologous NADPH-dependent glyoxylate reductase. It was found that lactic acid is a surprising by-product of glycolic acid formation in M. extorquens, most likely due to a surplus of available NADH upon glycolic acid synthesis. Finally, the best performing strain was tested in a fed-batch fermentation producing a mixture of up to total 1.2 g L^-1 glycolic acid and lactic acid. Several key performance indicators of our glycolic acid producer strain are superior to state-of-the-art synthetic methylotrophs. The presented results open the door for further strain engineering of the native methylotroph M. extorquens and pave the way to produce two promising biopolymer building blocks from green methanol, i.e., glycolic acid and lactic acid.

Keywords: Bioeconomy; Bioengineering; Bioprocess development; C1 fermentation; COBRA modeling; Glycolate; Glycolic acid; Glyoxylate reductase; Lactate; Lactic acid; Metabolic core model; Methylotrophy; Serine cycle; Synthetic methylotrophy; Systems biotechnology; Systems metabolic engineering.

Fig. 1

Yield-space analysis based on EFMs with GA production. EFMs with GA production of the core network with NADPH- or NADH-dependent glyoxylate reductase (white and grey circles, respectively) were plotted with respect to their biomass and GA yields (Y_X/MeOH and Y_GA/MeOH). Effects of genetic perturbations on yield space calculations were simulated by in silico deletion of formate dehydrogenases (FDHs; non-affected EFMs shown by blue circles) and phosphoenolpyruvate carboxylase (PPC; non-affected EFMs shown by red circles) reactions. To simulate the reaction deletion, only EFMs were selected which do not use the corresponding reaction (zero flux)

Fig. 2

Map of the central carbon metabolism of the Mextorquens CoreModel displaying an EFM with maximal GA yield of 0.5 mol_GA mol_MeOH⁻¹. Shown are exchange of metabolites, methanol and formate uptake and oxidation, C₁-interconversions (THMPT/THF-node), Serine Cycle (SC), Citric Acid Cycle (TCA), Ethylmalonyl-CoA Pathway (EMCP), Pentose Phosphate Pathway (PPP), Entner-Doudoroff Pathway (EDP), respiratory processes, transhydrogenase, ATP generation, growth rate µ, non-growth-associated ATP demand (ATPM_NGAM), and a compressed methylglyoxal pathway for LA formation. The gradual arrow color changes indicate the fluxes in % relative to methanol uptake (see Figure Legend). Green boxes indicate active reactions (and their flux value) and red boxes inactive reactions. A summary of abbreviations of metabolites is given in supplement file S01

Fig. 3

Product tolerance of M. extorquens TK 0001 + pTE1887 (Mea-C) in microbioreactor cultivations. A Growth profiles of Mea-C in the BioLector experiments applying GA concentrations in the range between 0 and 15 g L⁻¹. B Inhibition curve of growth rate µ in relation of the applied GA concentrations. Data and standard deviation represent three independent biological replicates (n = 3)

Fig. 4

Glyoxylate reductase screening in M. extorquens TK 0001. Measured enzyme activities of the expressed glyoxylate reductases during enzyme assay using A NADPH and B NADH as redox cofactors. C Associated GA production in the corresponding shake flask cultures of the engineered strains using methanol minimal medium. The control strain Mea-C was used as reference (dashed red line). Data and standard deviation represent three independent biological replicates (n = 3)

Fig. 5

Growth and production behavior of M. extorquens TK 0001 strains Mea-C and GA producing Mea-GA1 expressing ghrA from E. coli. The figures correspond to cultivations using the strains A Mea-C, B Mea-GA1, C Mea-C with glyoxylate feeding, D Mea-GA1 with glyoxylate feeding. Feed of 1.5 g L⁻¹ glyoxylate boosts GA production. Growth phases I–III are separated by dashed lines. Data reflect mean values and standard deviation from independent biological duplicates

Fig. 6

Growth and production behavior of GA producing M. extorquens TK 0001 strains Mea-GA2 and Mea-GA3 expressing ghrA_eco from E. coli and ecm_mea or ecm_rsh from M. extorquens or R. sphaeroides, respectively. The figures correspond to cultivations using the strains A Mea-GA2, B Mea-GA3, C Mea-GA2 with glyoxylate feeding, D Mea-GA3 with glyoxylate feeding. Supplementation of 1.5 g L⁻¹ glyoxylate boosts GA production. Growth phases I–III are indicated by grey boxes with dashed lines. Data reflect mean values and standard deviation from independent biological duplicates

Fig. 7

Growth and production behavior of GA producing Mea-GA1 in fed-batch fermentation. Shown is A the time-dependent development of optical density measured at 600 nm (black circles), methanol concentration (grey squares), GA concentration (green diamonds), and LA concentration (red triangle). B Development of biomass-substrate yield Y_X/MeOH during the three growth phases. The slopes of the linear fits represent Y_X/MeOH in the three phases I (red dashed line), II (green dashed line), and III (blue dashed line). C Development of product-substrate yield Y_P/S during the three growth phases for GA (green diamonds), and LA (red triangles). The slopes of the linear fits represent Y_P/S for GA (green dashed line) and LA (red dashed line). Growth phases are indicated by colored boxes: I (grey), II (rose), III (light red). D Carbon recovery (CR) of measured products in relation to utilized methanol. The time points represent the end of batch phase prior to IPTG induction (17.38 h) the end of production phase (40.57 h). Carbon recovery includes the proportion of carbon captured in biomass (estimated from average biomass composition of bacteria [105]) and CO₂ evolution, which is an estimated value (leading to 100% carbon recovery) since CO₂ release was not measured during the fermentation. Data reflect mean values and deviation from independent biological duplicates

Fig. 8

Simulated GA-LA yield-space formed by EFMs which support GA and LA production either with growth (green filled circles) or without growth (blue filled circles) of the Mextorquens CoreModel. The red reference lines depict measured Y_GA/MeOH and Y_LA/MeOH in growth phase II of Mea-GA1 during the fed-batch fermentation. No EFM exists at the intersection of the reference lines indicating that no single EFM exists in the model that can (alone) resolve the metabolic state of the network for the measured Y_P/S, hence, a combination of EFMs is likely to occur