The synergistic effect of formate dehydrogenase and carbonic anhydrase accelerates the ethanol fermentation process and improves carbon recovery

Ying He a, Yimin Li a, Jiaxin Liu a, Liming Su a, Cong Du *a and Wenjie Yuan *ab
aMOE Key Laboratory of Bio-Intelligent Manufacturing, School of Bioengineering, Dalian University of Technology, Dalian, Liaoning 116024, PR China. E-mail: heying2093@163.com; yiminli@dlut.edu.cn; 1124862238@qq.com; 2154949663@qq.com; 18742515846@163.com; ywj@dlut.edu.cn
bNingbo Research Institute, Dalian University of Technology, Ningbo, Zhejiang 315000, PR China

Received 21st February 2025 , Accepted 4th April 2025

First published on 8th April 2025


Abstract

Bioethanol is a significant product in the two-carbon strategy, but the CO2 generated during ethanol fermentation incurs substantial carbon losses. To tackle this issue, we explored a prospective dual-enzyme approach, using formate dehydrogenase (FDH) and carbonic anhydrase (CA), aiming to convert CO2 to formate in situ, transforming the process from carbon-neutral to carbon-negative. TsFDH was selected among four FDH candidates due to its high enzymatic activity. To overcome the low solubility of CO2, CA was co-expressed with FDH, facilitating CO2 hydration. The recombinant strain S. cerevisiae-tsfdh-ca efficiently converted CO2 to formate and exhibited rapid glucose consumption, which produced 76.3 mg L−1 formate during fermentation, with a 69% increase in the glucose fermentation rate and a 108% increase in formate yield. Additionally, it reduced CO2 emissions significantly, and the ratio of CO2 release and ethanol production decreased from 1.89 to 1.39. The dual-enzyme system, FDH/CA, as elucidated by transcriptomic analysis, amplifies fermentation efficiency. It achieves this by concurrently sustaining the integrity and optimal efficiency of the electron transport chain and optimizing metabolic fluxes, particularly those in the TCA cycle and oxidative phosphorylation. Consequently, it offers a promising strategy for mitigating carbon emissions and enhancing the production of biofuels and chemicals and thus holds immense potential for contributing to a more sustainable and environmentally friendly energy future.


1 Introduction

Energy supply dominated by fossil energy has always been one of the important factors influencing the global economy and international political relations. From a scientific perspective, the excessive reliance of industry, agriculture, and economic development on fossil fuels not only leads to energy supply issues but simultaneously releases a substantial amount of carbon dioxide and other greenhouse gases, resulting in an increasingly severe greenhouse effect. It is projected that by the year 2100, the concentration of CO2 will further increase by 60% at the current rate.1 Numerous environmental issues have emerged owing to the intensification of the greenhouse effect. To solve this problem, it is urgent to develop new clean renewable energy sources and also to reduce the production of CO2.2

Bioethanol has gained prominence due to its high energy density, transportability, and regenerative properties. In particular, lignocellulosic bioethanol offers environmentally beneficial alternatives to fossil fuels and avoids the emission of greenhouse gases. The utilization of waste and residues (such as straw and corn cobs) for bioethanol production helps address the challenge of the “food vs. fuel” dilemma.3 A recent report indicates that the global demand for biofuels is expected to grow by more than 20% between 2022 and 2027.4 However, regardless of the raw material used, the bioethanol production process invariably releases an equal amount of CO2. Notably, approximately one-third of the substrate is lost as CO2, thereby resulting in a substantial and concerning loss of carbon resources.5 Therefore, utilizing CO2 for various energy applications, including ethanol fermentation, provides a promising pathway to address environmental challenges and advance sustainable energy solutions.6

Low dissolved CO2 from the gas phase diffuses into water, making it better to convert CO2 to soluble one-carbon (C1) compounds.7 Among various C1 compounds like formaldehyde and methanol, formate shows distinct advantages over the lowest standard reduction potentials. On this basis, formate has been widely used as feedstock for the production of various C2–Cn compounds.8,9 Formate dehydrogenase (FDH) is one of the most promising CO2 fixation enzymes, which has received much attention for its ability to convert CO2 to formate without any other organic compounds except for energy in the form of electrons. However, the problems of low reduction efficiency, poor enzyme stability, and high cost of NADH hinder the industrial scale-up of FDHs. Strategies such as immobilizing FDHs on metal–organic frameworks (MOFs),10 sol–gel carriers,11 and membranes12 have been investigated to enhance the recycling stability, conversion efficiency, and formate yield. Considering the high cost of NADH, cofactor regeneration is desperately necessary. Chen et al. established a bioelectrocatalytic system combining enzymatic reactions with the electrochemical regeneration of cofactors using an electrochemical reaction, converting CO2 to formate at a rate of 79 ± 3.4 mM h−1.10 The biocatalytic method, which can activate CO2 and reduce the activation energy required for the reaction, is commonly preferred due to its superior selectivity, low energy consumption and relatively mild reaction conditions.13 In particular, the process of glucose fermentation for ethanol production generates excessive NADH which would integrate with CO2 reduction. Researchers endeavored to fix CO2 generated during bioethanol production and it was found that fixing CO2 promoted ethanol yield.14,15 However, the mechanism of CO2 reduction contributing to ethanol production still remained unspecified. Additionally, due to the low solubility of CO2 and the low reduction activity of FDH, the recovery efficiency of CO2 and the yield of formate are relatively low. Carbonic anhydrase (CA) can efficiently catalyze 106 molecules of CO2 per second under ideal conditions,16 playing a pivotal role in maintaining equilibrium between CO2 and HCO3 to facilitate cellular processes rather than just CO2 fixation. Indeed, these advantages drive CA to be widely applied in assisting absorption, separation, and precipitation techniques.17,18 Given the distinctive capabilities of both FDH and CA, the combination of these enzymes for CO2 capture applications has gained significant attention.19–21

To address the above issue, this work demonstrated an efficient CO2 reductase FDH for constructing a feasible CO2 utilization system in Saccharomyces cerevisiae to stimulate ethanol fermentation by accelerating CO2 to formate. The combination of CO2 fixation with ethanol production by the collaboration of FDH and CA enabled the efficient use of carbon from raw materials, promoted fermentation, and reduced carbon emissions in the environment. The mechanism of boosting glucose fermentation efficiency and ethanol yield was clarified. The present study provided a collaborative advantage strategy that enhanced production yield. Moreover, it put forward a novel first-step approach for biocatalytic carbon capture and utilization, aiming at both CO2 reduction and the substitution of important commodity chemicals.

2 Materials and methods

2.1 Materials

The genes (scfdh from S. cerevisiae, tsfdh from Thiobacillus sp. KNK65MA, atfdh from Arabidopsis thaliana, mtfdh from Myceliophthora thermophila, and ca from Bos taurus) used in this study were codon optimized and synthesized by BBI Life Sciences (Shanghai, China). Plasmids pET-32a(+), pACYCDuet-1, and pRS424 and competent cells Escherichia coli DH5α/BL21(DE3) and S. cerevisiae S288C were purchased from Merck (Massachusetts, USA). Analytical grade sodium bicarbonate (A610482), sodium formate (A500851), reduced β-nicotinamide adenine dinucleotide (NADH, A600642), β-nicotinamide adenine dinucleotide (NAD+, A600641), yeast nitrogen base (YNB, A610507), and isopropyl-β-D-thiogalactopyranoside (IPTG, A100487) were purchased from BBI Life Sciences (Shanghai, China). Amino acids were purchased from Solarbio Life Sciences (Beijing, China). All molecular biology enzymes were from Takara Bio (Beijing, China). The His-Trap and PD-10 columns were purchased from GE Healthcare (Little Chalfont, UK).

2.2 Cloning, overexpression, and purification of FDHs and CA

The genes of fdh and ca with His-tag were PCR-amplified and ligated with pET-32a(+) and pACYCDuet-1 by restriction enzymes, respectively (Table S1). Recombinant plasmids (pET32a(+)- scfdh/tsfdh/atfdh/mtfdh and pACYCDuet-ca) were then transformed into the competent E. coli BL21 (DE3). Expression and purification of the target proteins in recombinant strains were performed following reported methods.22,23 His-tagged proteins were purified using Ni-NTA resin, and protein concentration was determined via the BCA assay. SDS-PAGE was used to assess protein expression and molecular weight, with gels stained with Coomassie Brilliant Blue R-250.

2.3 Activities assay of FDHs

The enzymatic activities of FDHs were assayed by measuring the changes in the absorbance of NADH at 340 nm. The standard curve of NADH is shown in Fig. S1, characterizing the OD340 values corresponding to different concentrations of NADH. The oxidative activity was defined as the amount of enzyme required to produce NADH, and the reductive activity was defined as the amount of enzyme required to consume NADH. To calculate the specific activity of formate oxidation, 200 mM sodium formate and 2 mM NAD+ were used as the substrate and electron acceptor at 30 °C with different pH values (5–8). The reduction assay was conducted in 50 mM sodium bicarbonate and 0.3 mM NADH at 30 °C with different pH values (5–8). For the optimal carbon source for FDH reduction, 200 mM sodium bicarbonate and purged CO2 (100%) were used as substrates, respectively.

2.4 Construction of recombinant S. cerevisiae with FDHs and CA

After verifying the activity of FDHs and CA in the E. coli system, the selected formate dehydrogenase (TsFDH) was transformed into S. cerevisiae S288C. The PCR amplification, enzyme ligation, and other plasmid construction methods are described in Section 2.2 (Table S2). Yeast transformation was performed using the standard lithium acetate transformation method.24S. cerevisiae S288C trpΔ with pRS424 (S. cerevisiae-control, NC), S. cerevisiae-tsfdh, S. cerevisiae-scfdh, S. cerevisiae-tsfdh-ca and S. cerevisiae-tsfdh-ca-bica were constructed.

2.5 Fermentation experiments and analytical methods

The recombinant S. cerevisiae was activated and cultured in SD-trp medium (20 g L−1 glucose, 6.7 g L−1 YNB, and appropriate amino acids but without tryptophan) at 30 °C and 180 rpm. Then the cells were harvested and transferred to the fermentation medium according to the experimental needs. Cell growth was measured by measuring the optical density at 620 nm (OD620 nm). Glucose and ethanol concentrations were measured using an HPLC system (Acchrom S6000) equipped with a BIO-RAD Aminex HPX-87H column and reflective index detector at 50 °C. Formate concentration was measured using a UV detector at 210 nm. The mobile phase was 0.01 N H2SO4 with a flow rate of 0.5 mL min−1. All experiments were replicated three times, and the error bars denote the standard deviation. In this study, P < 0.05 was considered as a significant difference and P < 0.001 was a highly significant difference.

2.6 Off-gas analysis

Parallel bioreactors from T&J Bioscience Co., Ltd (Shanghai, China) were used to analyze the ratio between released CO2 and produced ethanol r(C/E) of S. cerevisiae-tsfdh-ca and S. cerevisiae-control, with each connected to an off-gas analyzer to record CO2 emissions. Fermentations were performed in SC media containing 40 g L−1 glucose, with an initial inoculum of 1 OD620. The process was conducted at 30 °C and 180 rpm, with aeration maintained at 0.5 vvm.

2.7 Transcriptome analysis

In order to explore the beneficial effects of carbon dioxide fixation on fermentation, transcriptome analysis was performed. Total RNA was extracted from the tissue using TRIzol® reagent according to the manufacturer's instructions (Invitrogen) and genomic DNA was removed using DNase I (TaKara). Then RNA quality was determined using a 2100 Bioanalyser (Agilent) and quantified using an ND-2000 (NanoDrop Technologies). RNA-seq transcriptome libraries were prepared using a TruSeq™ RNA sample preparation kit from Illumina (San Diego, CA), using 1 μg of total RNA. Paired-end libraries were sequenced by Illumina NovaSeq 6000 sequencing (150 bp × 2, Shanghai BIOZERON Co., Ltd). To remove any low-quality sequences, we assessed reads in FASTQC and filtered clean reads using Trimmomatic. The reads were then mapped to the S. cerevisiae S288C genome (NCBI accession no. PRJNA43747). TPM analysis was carried out using String Tie, and differential expression analysis was performed using the DESeq R package (1.18.0), where we assigned p ≤ 0.05 and log2|FoldChange| ≥ 1 as differentially expressed genes. All analyses had three biological replicates.

3 Results and discussion

3.1 Exploration and characterization of efficient FDHs for CO2 reduction

FDHs are capable of reversibly interconverting CO2 and formate (Fig. 1a), normally classified into two types: metal-dependent and metal-independent FDHs.25,26 Metal-dependent FDHs generally exhibit higher activity toward CO2 reduction than the metal-independent FDHs, but the oxygen-sensitive catalytic components limit the metal-dependent FDHs for industrial application.27 In light of this, we selected previously reported metal-independent FDH candidates to explore FDHs with high CO2 reduction activity to facilitate ethanol yield. Sequence comparison revealed that the absolute homology of metal-independent FDHs was more significant than 80%, with bacterial FDHs containing an N-terminal loop and C-terminal loop, which were more stable than eukaryotic derived FDHs (Fig. S2). Indeed, after evaluating the catalytic turnover rate (kcat), binding affinity (Km) and the optimal pH (Table S3) considering the reduction ability of CO2, we selected four promising FDHs (ScFDH, TsFDH, AtFDH, and MtFDH) for further study. The SDS-PAGE gel exhibited the FDHs expressed correctly with a high purity (Fig. S3).
image file: d5gc00705d-f1.tif
Fig. 1 (a) CO2 reduction and formate oxidation activity of FDHs. (b) 200 mM sodium bicarbonate and purged CO2 (100%) were used as substrates, respectively. Enzyme activities of FDHs for (c) formate oxidation and (d) CO2 reduction at different pH (5, 6, 7, and 8) values. The temperature was controlled at 30 °C. ScFDH: FDH from S. cerevisiae, TsFDH: FDH from Thiobacillus sp. KNK65MA, AtFDH: FDH from A. thaliana, and MtFDH: FDH from M. thermophila.

For the purpose of elucidating the effect of different CO2 sources on the reduction and ethanol yield, purged CO2 (100%) or 200 mM sodium bicarbonate was used as the substrate, respectively. As presented in Fig. 1b, the four FDHs exhibited the same trend and the reducing activity of FDHs was significantly higher with CO2 (100%) as the substrate than sodium bicarbonate, supporting the discovery of Popov et al.28 In particular, TsFDH has the highest CO2 reduction activity and formate production, and the reducing activity was 0.46 U mg−1 enzyme and 0.40 U mg−1 enzyme when CO2 and sodium bicarbonate were used as a substrate. Consistent with previous findings in electrochemistry and biocatalysis, the reaction rate of formate production by CbFDH increased in proportion to the concentration of CO2 in the reaction solution.29,30 However, CO2 has limited solubility in water and is not easily manipulated, while sodium bicarbonate can slowly release CO2. In subsequent in vitro experiments, we therefore chose sodium bicarbonate as the source of CO2.

Reaction conditions are crucial for enzyme activity, as metal-independent FDH reportedly exhibited optimal reductive activity under acidic or neutral conditions. Therefore, considering the potential application in the yeast, we examined the reductive capacity of FDHs within the pH range of 5 to 8.31 The oxidative and reducing activities of the four FDHs at different pH values are shown in Fig. 1c and d, respectively. As previously reported, all the FDHs were able to successfully catalyze both the oxidation of formate and the reduction of CO2. Additionally, they exhibited strong oxidizing abilities and relatively weak reducing abilities.22 The oxidative specific enzyme activities of the four FDHs ranged from 11.96 to 26.40 U mg−1 (Table S4) and the reducing specific enzyme activity ranged from 0.09 to 0.53 U mg−1 (Table S4). Promisingly, TsFDH exhibited outstanding CO2 reduction activity regardless of the pH conditions. As shown in Fig. 1d, TsFDH exhibited the highest enzyme activity in terms of the reduction ratio at pH 6, reaching 0.53 U mg−1. This activity was 2.1-fold higher than that of AtFDH, which was the enzyme with the second-highest activity. The effect of pH variation on reductase activity was non-proportional, and the activity of TsFDH in a mildly acidic environment (pH 5) was decreased but still statistically higher than the other FDHs. Alternatively, the reductase activity of ScFDH showed a trend consistent with that observed in the oxidation process. As the pH value increased, the reductase activity of MtFDH gradually decreased, dropping from 0.14 U mg−1 to 0.09 U mg−1. Although MtFDH demonstrated robust oxidative activity, its capacity to reduce CO2 was rather weak, particularly at pH 5.

After considering the facts that TsFDH exhibited 4.32-fold higher reduction specific enzyme activity compared with ScFDH during in vitro enzyme assays, TsFDH has the potential as CO2 reductase for ethanol production integrated with CO2 fixation under acidic conditions, which might facilitate more carbon recycling subsequently.

3.2 TsFDH serves as a key mediator in recycling CO2 obtained from ethanol production

Ethanol fermentation and formate production of the TsFDH overexpression strains S. cerevisiae-tsfdh (S. cerevisiae-scfdh as a control) were investigated. As was easily seen, TsFDH exhibited excellent CO2 fixation capacity compared to S. cerevisiae's native FDH. As shown in Fig. 2b, formate produced by S. cerevisiae-tsfdh increased by 39.0%, from 22.3 to 31.0 mg L−1 compared with S. cerevisiae-scfdh. Meanwhile, S. cerevisiae-tsfdh achieved better glucose fermentation performance in conjunction with ethanol productivity. In Fig. 2a, the glucose consumption rate of S. cerevisiae-tsfdh was significantly superior compared with S. cerevisiae-scfdh, increased by 20.5% from 1.27 g L−1 h−1 to 1.53 g L−1 h−1 within 36 h and produced 15.11 g L−1 of ethanol, with a 6.0% increase in ethanol production. It proved that TsFDH exhibited more advanced CO2 reduction activity than ScFDH, accompanied by improved glucose fermentation and ethanol yield.
image file: d5gc00705d-f2.tif
Fig. 2 Fermentation properties of S. cerevisiae-tsfdh (TsFDH) and S. cerevisiae-scfdh (ScFDH) investigated at 30 °C and 180 rpm in SD media. (a–c) 40 g L−1 glucose, initial inoculum was 1 OD620; (d–f) 60 g L−1 glucose, initial inoculum was 3 OD620.

When initial inoculum and glucose concentration increased to 3 OD620 nm and 60 g L−1, formate and glucose consumption rates were both boosted (Fig. 2d–f). In the illustration of our previous work, a higher initial cell biomass meant that more target enzymes were added and allowed more FDH to fix CO2 in a timely manner and reduce its overflow.15 Accordingly, more formate was produced for more FDH and more CO2 from ethanol fermentation with initial inoculum 3 OD and a higher glucose concentration. Formate production of S. cerevisiae-tsfdh increased by 37.6%, from 46.3 to 63.7 mg L−1. Beyond that, efficient CO2 fixation also facilitated glucose fermentation, and more inoculation resulted in upgraded fermentation performance as shown in Fig. 2d. S. cerevisiae-tsfdh almost depleted 60 g L−1 glucose at 24 h, with the production of 22.83 g L−1 ethanol, while S. cerevisiae-scfdh only produced 19.29 g L−1 ethanol. The glucose consumption rate increased by 14.6% from 2.12 g L−1 h−1 to 2.43 g L−1 h−1. The fermentation results showed that TsFDH could fix CO2 released during ethanol fermentation in situ more efficiently, and the fixation of CO2 could promote the glucose fermentation process and improve the productivity of ethanol. The promotion effect was positively correlated with the enzyme activity or enzyme dose.

Glycerol is a major by-product in ethanol production because yeast generates an excess of NADH during fermentation, and the production of glycerol helps to maintain the intracellular redox balance.32 In the present study, glycerol production of S. cerevisiae-tsfdh was noticed to decrease by 26.7% from 0.95 g L−1 to 0.75 g L−1 compared with S. cerevisiae-scfdh. This indicated that NADH-dependent TsFDH oxidized the excess NADH while fixing CO2 produced from ethanol fermentation in situ, thereby reducing glycerol production and increasing the ethanol yield. Mitochondrial NADH dehydrogenase (NDE) is responsible for catalyzing the oxidation of NADH in the cytoplasm. It was reported that overexpressing NDE1/2 decreased the intracellular NADH/NAD+ ratio and glycerol yield.33 Here, TsFDH fixed CO2 requiring NADH, so that glycerol production was no longer needed to consume excess NADH for redox balance. Consequently, more CO2-derived formate means less glycerol production, indicating that fixing CO2 from ethanol production reduced the formation of the by-product and further improved carbon recovery.

Various applications highlight FDH-driven electroenzymatic and photoenzymatic CO2 reduction systems in vitro, in which a whole-cell biocatalytic strategy to utilize CO2 as a sustainable feedstock has also been attempted. Whole-cell catalysis has received widespread attention as it avoids enzyme purification, and provides optimum conditions for the enzyme and facilitates its maintenance. Alissandratos et al. overexpressed FDH from Pyrococcus furiosus (PfFDH) in E. coli JM109 for whole-cell catalysis of formate production, and this engineered strain produced 44 mM formate from sodium bicarbonate and gaseous hydrogen with a productivity of 22.7 mM h−1.34 Schwarz and Müller recently implemented efficient whole-cell biocatalytic CO2 hydrogenation to formate by the TkFDH from Themoanaerobacter kivui with a yield of 130 mM and a productivity of 270 mM h−1.35 Although enzymatic synthesis of formate from CO2 with electrons supplied from hydrogenase-driven H2 oxidation exhibits many advantages, these reactions require highly purified and expensive hydrogen gas, leading to an increase in storage and transportation costs, as well as safety issues. In this work, glucose fermentation for ethanol production provided cofactor NADH for CO2 fixation, which established a win–win strategy for ethanol production accompanied by CO2 fixation with environmentally and economically beneficial effects. It not only reduced carbon emissions, but also provided insight into CO2 conversion to valuable chemicals and fuels by whole-cell biocatalysis.

3.3 Harnessing FDH and CA powered CO2 reduction

For whole-cell catalysis, the low solubility of CO2 in water presents a significant challenge to CO2 fixation. CA was reported to promote the hydration reaction of CO2, so we first investigated the effect of different concentrations of purified CA on CO2 reduction.20 The fermentation performance of S. cerevisiae-tsfdh (TsFDH) with different concentrations of CA (0, 0.1, and 0.5 g L−1) is shown in Fig. S4, and both glucose consumption and ethanol yield increased after CA addition. Glucose consumption rates were 1.49, 1.53, and 1.69 g L−1 h−1, which increased by 2.7% and 13.4% compared with the control, respectively. Meanwhile, the ethanol yields were 0.36, 0.37, and 0.39 g g−1, which increased by 2.8% and 8.3%, respectively. Obviously, S. cerevisiae-tsfdh had a higher glucose consumption rate and ethanol yield as enough CA was added. There were almost no differences in formate and glycerol yields with CA addition, perhaps because the enzyme was unstable and inactive in an acidic and ion-rich environment. As shown in Fig. S5, the overexpression of TsFDH and CA individually resulted in a 51.1% and 50.3% increase in glucose fermentation rates, respectively, and a 71.3% and 54% increase in formate production. Overexpression of TsFDH increased the concentration of FDH, thereby enhancing glucose utilization, whereas overexpression of CA alone significantly improved the CO2 recovery efficiency mediated by the endogenous FDH in S. cerevisiae. These results highlighted the critical roles both enzymes play in carbon recycling.

To further the research, a whole-cell biocatalysis system with FDH and CA harness was constructed to enable continuous production of FDH and CA and to maintain a relatively stable pH and environment that was more favorable for CO2 capture. Formate production and ethanol fermentation of S. cerevisiae-tsfdh and S. cerevisiae-tsfdh-ca at different glucose concentrations were examined. As shown in Fig. 3, S. cerevisiae-tsfdh and S. cerevisiae-tsfdh-ca produced 26.7 mg L−1, 49.7 mg L−1, 63.3 mg L−1 and 27.7 mg L−1, 56.3 mg L−1, and 76.3 mg L−1 formate, respectively, while the glucose concentrations were 20 g L−1, 40 g L−1, and 60 g L−1. S. cerevisiae-tsfdh-ca produced more formate at the same glucose concentration, and the trend became more pronounced with a higher sugar concentration. Dual enzymes of TsFDH and CA made great effort on the CO2 hydration reaction and reduction. Consistent with this, S. cerevisiae-tsfdh-ca exhibited superior glucose metabolism, specifically a higher ethanol yield and a faster glucose consumption rate. As shown in Table 1, the glucose consumption rate of S. cerevisiae-tsfdh-ca was 1.15 g L−1 h−1 when 20 g L−1 glucose was used, which was a 15.8% increase compared to S. cerevisiae-tsfdh. At 40 g L−1 glucose, S. cerevisiae-tsfdh and S. cerevisiae-tsfdh-ca produced 12.12 g L−1 and 14.18 g L−1 of ethanol in 48 h. The yield increased from 0.31 g g−1 to 0.34 g g−1, with an increase of 9.68%. In addition, the glucose consumption rate of S. cerevisiae-tsfdh-ca increased from 1.10 g L−1 h−1 to 1.30 g L−1 h−1, an increase of 15.38%, compared to S. cerevisiae-tsfdh. Similar results were revealed at 60 g L−1 glucose, S. cerevisiae-tsfdh and S. cerevisiae-tsfdh-ca with ethanol yields of 0.31 g g−1 and 0.34 g g−1, and glucose consumption rates of 1.32 g L−1 h−1 and 1.43 g L−1 h−1, an increase of 8.33%. The above results indicated that the co-expression of FDH and CA had meaningful and long-term effects on both CO2 reduction and glucose fermentation.


image file: d5gc00705d-f3.tif
Fig. 3 Fermentation properties of S. cerevisiae-tsfdh (TsFDH) and S. cerevisiae-tsfdh-ca (TsFDH + CA) at different glucose concentrations investigated at 30 °C and 180 rpm in SC media. (a) 20 g L−1 glucose, (b) 40 g L−1 glucose, and (c) 60 g L−1 glucose.
Table 1 Fermentation parameters of S. cerevisiae-tsfdh (TsFDH) and S. cerevisiae-tsfdh-ca (TsFDH + CA)a
Strain Glucose (g L−1) Formate (mg L−1) Glucose consumption rate (g L−1 h−1)
a Fermentation was conducted in SC media using glucose as the carbon source.
TsFDH 20.96 26.67 ± 3.06 0.996 ± 0.022
41.22 49.67 ± 4.04 1.100 ± 0.039
60.69 63.33 ± 3.22 1.323 ± 0.060
TsFDH + CA 20.75 27.67 ± 4.04 1.153 ± 0.009
41.38 56.33 ± 5.69 1.295 ± 0.005
60.21 76.33 ± 10.97 1.428 ± 0.087


Formate is a useful source of microbial energy because it can be bio-electrochemically produced with high solar-to-product energy conversion efficiency and is easy to store and transport. Compared to soluble formate, the kinetic limitations of gaseous CO2 supply result in lower intracellular CO2 concentrations, reducing the CO2 fixation rate. It is anticipated that the production of formate itself from CO2 can be enhanced by using CA as previously mentioned. CA is attributed with the most rapid turnover frequency related to converting CO2 to bicarbonate, speeding up metabolic processes involving dissolved CO2 efficiently, and helping the pH balance through its buffering action. Integrating CA with microorganisms enables the efficient production of a broader range of chemicals, as metabolic pathway engineering expands product diversity, while CA-driven CO2 hydration supplies more CO2 for various conversion processes. Photoautotrophic microorganisms, like microalgae and cyanobacteria, offer valuable platforms for metabolic engineering, as they can sustainably produce target compounds such as carotenoids and lipids directly from CO2 using light energy. It has been demonstrated that CA immobilized on microalgae cell surface increased its growth by 1.6-fold and lipid production by 1.7-fold without the need for the addition of other carbon sources.36 In the context of CO2 reduction, the synergy between CA and FDH has been found to enhance the reaction rate. As a result, the cascade system involving FDH and CA has attracted widespread attention, due to its potential implications in various industrial and environmental applications. Sato et al.37 constructed a dual-enzyme system using FDH and CA, demonstrating that the use of CA to convert CO2 into bicarbonate and the use of FDH to reduce CO2 to formate in CCUS systems are coordinated. However, the activity and stability of enzymes in vitro present challenges, and there are issues with poor synergy when coupled with cofactor regeneration. Constructing microbial cell factories can provide a stable environment for enzymes, and the diverse endogenous or exogenous metabolic pathways in microorganisms can supply cofactors. Moreover, designing and optimizing metabolic pathways can also synthesize higher value-added products. In this study, we constructed a cellular factory that co-expresses FDH and CA to in situ fix the byproduct CO2 from ethanol fermentation into formate, with glucose fermentation providing the cofactors. Formate production increased by 20.52%. Adding formate as a promising carbon-energy coupling carrier for bioproduction provides a new idea for the resourceful utilization of CO2.

3.4 S. cerevisiae-tsfdh-ca exhibited the fastest fermentation rate and the highest formate production

Cyanobacteria possess an environmental adaptation known as a CO2 concentrating mechanism (CCM) that evolved to improve photosynthetic performance, particularly under CO2-limiting conditions, which contains inorganic carbon transporters that actively transport extracellular CO2 and HCO3 into the cell.38 To increase the intracellular CO2 concentration, we attempted to overexpress the HCO3 transporter (BicA) from cyanobacteria in S. cerevisiae, and the S. cerevisiae-tsfdh-ca-bica strain was successfully constructed and the fermentation parameters are shown in Fig. 4. There was no significant difference in both glucose metabolism and formate production of S. cerevisiae-tsfdh-ca and S. cerevisiae-tsfdh-ca-bica. It was possible because the complex expression pattern of membrane proteins failed to enhance the affinity between distant species such as cyanobacteria and yeast. What's more, the expression of multiple heterologous genes brought a specific metabolic burden, which affected the fermentation ability of the strain. It needs to be stressed again that the overexpression of TsFDH and CA exhibited significant advantages in terms of glucose consumption rate and formate production capacity compared to S. cerevisiae-control. S. cerevisiae-tsfdh-ca exhibited the fastest fermentation rate and the highest formate production. Compared with S. cerevisiae-control, the glucose consumption rate, ethanol production, and formate production of S. cerevisiae-tsfdh-ca were 69%, 83%, and 108% higher, respectively. There was no doubt that the TsFDH screened in this study had strong power to simultaneously fix CO2in situ during ethanol production and further achieve the conversion of CO2 to formate by enhancing the rate of CO2 hydration by CA. Considering that high concentrations of formate are harmful to cells, future work will focus on converting formate to less toxic methanol by formaldehyde dehydrogenase (FaldDH) and alcohol dehydrogenase (ADH).39
image file: d5gc00705d-f4.tif
Fig. 4 Fermentation properties of the S. cerevisiae-control, S. cerevisiae-tsfdh (TsFDH), S. cerevisiae-tsfdh-ca (TsFDH + CA) and S. cerevisiae-tsfdh-ca-bica (TsFDH + CA + BicA) investigated at 30 °C and 180 rpm in SC media. (a) Glucose and ethanol concentrations, (b) formate concentrations, and (c) glucose consumption rate.

3.5 Reducing CO2 leakage during glucose fermentation

To verify the recovery of CO2 during ethanol fermentation, a tail gas analyzer monitored the CO2 released during the fermentation process in real time (Fig. S6). Both strains exhibited a rapid increase in CO2 production at the start of the fermentation process as shown in Fig. 5a, the green line reached its peak CO2 emission faster and higher than the yellow line, indicating that the S. cerevisiae-tsfdh-ca strain had a stronger glucose metabolic performance during the initial fermentation phase. After reaching the peak, both strains showed a decline in CO2 production, but consistent with the trend of formate production, the CO2 of S. cerevisiae-tsfdh-ca dropped off more rapidly than that of the control. The statement highlighted the outstanding CO2 reduction capability of S. cerevisiae-tsfdh-ca, which can promptly reduce the CO2 produced by yeast cells back into formate, minimizing carbon loss. Throughout the entire fermentation, the S. cerevisiae-tsfdh-ca strain reduced CO2 emissions by about 3.12% compared to the control strain.
image file: d5gc00705d-f5.tif
Fig. 5 (a) Real-time measurement of CO2 release during fermentation; (b) r(C/E, CO2 released/ethanol produced) of S. cerevisiae-tsfdh-ca (Ts + CA), S. cerevisiae-tsfdh (Ts), S. cerevisiae-ca (CA) and the control (NC).

A new parameter, r(C/E), was also introduced to represent the ratio between the amount of CO2 released and ethanol produced in the fermentation system. A lower r(C/E) indicated less CO2 released per ethanol unit. During the initial 12 hours, both yeast strains were in the rapid growth phase. At this point, the r(C/E) values for S. cerevisiae-tsfdh-ca and the control strain were 1.13 and 1.30, respectively. S. cerevisiae-tsfdh-ca displayed superior glucose fermentation performance and CO2 fixation capability. From 12 and 36 hours, both strains transitioned to the main fermentation phase, where ethanol production and CO2 emission were most significant. At this stage, the r(C/E) values increased to 1.74 for S. cerevisiae-tsfdh-ca and 2.20 for the control strain. This shift underscores the enhanced CO2 reduction capability of S. cerevisiae-tsfdh-ca. With elevated FDH and CA expression, the strain effectively converted the CO2 into formate, significantly reducing carbon loss. When fermentation neared completion, S. cerevisiae-tsfdh-ca finished earlier than the control strain, which continued to release CO2. Considering the entire fermentation phase, as shown in Fig. 5b, the r(C/E) of S. cerevisiae-tsfdh-ca (co-expressing TsFDH and CA), S. cerevisiae-tsfdh (expressing only TsFDH), S. cerevisiae-ca (expressing only CA), and the control (NC) were 1.39, 1.50, 1.70, and 1.89, respectively. Statistical analysis also showed a significant difference between the recombinant strains and the control strain. The lower r(C/E) values indicate that the recombinant strains lost less carbon in the form of CO2 during fermentation. These r(C/E) data further support the conclusions previously. Overexpression of TsFDH increased FDH concentration, thereby enhancing carbon fixation. In contrast, overexpression of CA alone significantly improved CO2 recovery efficiency mediated by endogenous FDH in S. cerevisiae. Furthermore, the synergistic effect of TsFDH and CA further improved carbon recovery efficiency beyond the individual contributions of each enzyme.

Due to its carbon-reducing properties, the recovery of CO2 from ethanol production has been spotlighted. The pioneering research on CO2 fixation in ethanol fermentation was realized by introducing heterologous phosphoribulokinase (PRK) and ribulose-1,5-bisphosphate carboxylase (RuBisCO) in S. cerevisiae to reconstruct the pentose phosphate pathway (PPP).40 The primary role of CO2 in this pathway was as an electron acceptor and CO2 was incorporated as a co-substrate in the fermentation with a sparging gas (10% CO2 and 90% N2). The ethanol production was increased by 10%, but the efficiency of CO2 fixation was poor. Cell growth and fermentation efficiency were negatively affected, and the fermentation time was delayed from nearly 40 h to nearly 50 h. Xia et al. achieved a phase coupling of PPP and xylose metabolic pathway in S. cerevisiae with a 3.7% increase in ethanol yield.41 The primary role of CO2 in this pathway was also as an electron acceptor, meanwhile, the imbalance of cofactor utilization of NADPH and NAD+ by xylose reductase (XR)/xylitol dehydrogenase (XDH) in xylose metabolism affected the CO2 fixation efficiency. Finally, there was a severe inhibition of glucose on xylose metabolism. This limitation allowed the PPP pathway to fix CO2 only at low glucose concentrations (20 g L−1), making industrial-scale ethanol production infeasible. The above studies achieved CO2 fixation during ethanol fermentation by constructing a heterologous PPP, but apparently the performance was not satisfactory. In contrast, the co-expression system of FDH and CA in this study overcame the problems containing energy imbalance, low enzyme stability and glucose inhibition. The r(C/E) value significantly decreased from 1.89 to 1.39, indicating the effective reduction of CO2. It achieved a win–win result of CO2 fixation and ethanol production simultaneously under a wider range of fermentation conditions, which showed better practicality.

3.6 Mechanism of enhanced fermentation efficiency by FDH and CA

To reveal the mechanism by which the CO2 reduction process catalyzed by FDH and CA enhanced fermentation efficiency, RNA-seq analysis was performed. Differential expressed genes (DEG) analysis of S. cerevisiae-tsfdh-ca and the control strain was shown in Fig. 6a. DEGs involved in the glycolytic pathway were down-regulated, such as those encoding glyceraldehyde-3-phosphate dehydrogenase (GAP), phosphoglycerate mutase (GPM), and enolase (ENO). This indicated that S. cerevisiae had already consumed most of the glucose, gradually shifting its metabolic flux from primary metabolism (glucose catabolism for energy production) to secondary metabolism. The downregulation of GPP1 and GPP2 encoding glycerol-3-phosphatase (GPP), suggested the decrease of glycerol production. In S. cerevisiae, glycerol synthesis typically served as a secondary metabolic pathway to help the cell balance redox states under anaerobic conditions or when excess NADH needed to be re-oxidized, which was consistent with the conjecture in Section 3.3 that producing more formate rather than glycerol was related to the competitive production of NADH. Previous reports proved that introducing the PRK-RuBisCO pathway or overexpressed A-ALD can re-oxidize NADH to reduce glycerol production, consisting of oxidizing excess NADH by FDHs for CO2 fixation can effectively decrease glycerol production and improve ethanol yield in this study.40–42 The up-regulation of ADH4, encoding alcohol dehydrogenase, supported the increased ethanol yield as well.
image file: d5gc00705d-f6.tif
Fig. 6 (a) Differentially expressed gene (DEG) analysis of central carbon metabolism; (b) oxidative phosphorylation up-regulated gene; and (c) oxidative phosphorylation gene set enrichment analysis (GSEA).

The tricarboxylic acid (TCA) cycle also showed a notable upregulation trend, including IDP2 and SDH3 encoding isocitrate dehydrogenase and succinate dehydrogenase. The TCA cycle is one of the important energy-producing pathways. The NADH and FADH2 generated by the TCA cycle are important substrates in the process of oxidative phosphorylation. In the case of S. cerevisiae-tsfdh-ca, more formate is produced through CO2 fixation. Formate has been reported to be harmful to the electron transport chain (ETC).43 However, SDH3, which participated in FADH2 oxidation and linked the TCA cycle to the ETC, was significantly upregulated in Fig. 6b. This suggested that the enhanced CO2 fixation process by FDH and CA not only increased energy production but also modulated the TCA cycle and oxidative phosphorylation pathways. The upregulation of SDH3 may play a role in maintaining the integrity and efficiency of the ETC, thereby counteracting the potential negative effects of formate on the ETC. This regulatory mechanism could be crucial for optimizing glucose fermentation and ethanol yield in the presence of increased formate production. Additionally, PMA2 encoded a proton pump that was upregulated, which helps maintain the proton gradient required for ATP synthesis across the mitochondrial membrane. NDE2 encoding the mitochondrial NADH dehydrogenase (NDE), which catalyzed the oxidation of cytosolic NADH was upregulated. Theoretically, NADH is primarily generated from NAD+ through the catabolism of glucose, serving as the reducing equivalent for various redox reactions.44,45 This excess NADH could be oxidized by external NDE, which was localized on the outer surface of the inner mitochondrial membrane, directly oxidized cytosolic NADH and shuttled the electrons to the quinone pool of the respiratory chain.46 This pathway operated independently of the TCA cycle but relied on the capacity of the ETC. It has been proven in various microorganisms that enhancing NADH oxidation can effectively improve glucose metabolism rate and target metabolite production intensity.47–49 Here, the upregulation of multiple genes in the TCA pathway and oxidative phosphorylation pathway indicates that the enhanced CO2 fixation process by FDH and CA has increased energy production. Moreover, FDH-mediated NADH oxidation has a similar effect to NDE, thereby improving glucose fermentation and ethanol yield.

The enrichment analysis of the gene set (GSEA) involved in the oxidative phosphorylation process was then performed (Fig. 6c). The oxidative phosphorylation gene set exhibited an overall upregulation trend, releasing more energy to enhance glucose fermentation and ethanol yield in S. cerevisiae-tsfdh-ca. In summary, the upregulated DEGs involved in oxidative phosphorylation suggested an increase in ATP production. Enhanced activity in the TCA cycle (especially through SDH3) fed more electron donors (NADH and FADH2) into the oxidative phosphorylation pathway, maximizing energy output and supporting cellular metabolic demands. This coordination between the TCA cycle and oxidative phosphorylation enabled efficient energy production, crucial for high-energy-demand processes. This work explained the mechanism of CO2 fixation contributing to the glucose consumption rate in S. cerevisiae-tsfdh-ca. This regulatory mechanism could be crucial for optimizing biomanufacturing in the presence of increased formate derived from CO2 reduction.

4 Conclusions

Since the co-expression of FDH and CA addressed the issues of low solubility and low reduction efficiency of CO2, the dilemma of CO2 emissions during ethanol production is alleviated. As a win–win strategy, glucose fermentation and formate production of S. cerevisiae-tsfdh-ca increased by 69% and 108%, respectively, and reduced CO2 emissions by approximately 3.12%. Furthermore, the mechanism of the advantageous effect on fermentation performance by harnessing FDH and CA was revealed. The in situ CO2 fixation mediated by them enhanced the TCA cycle and oxidative phosphorylation processes, thereby counteracting the potential negative effects of formate. The FDH-mediated oxidation of NADH for CO2 reduction has a function similar to NDE, leading to an improved ethanol yield. This approach offers a dual benefit, which includes reducing CO2 emissions and supplying carbon-based fuels and chemicals. These dual benefits have a substantial impact on ethanol production and other renewable fuels and chemicals.

Author contributions

Ying He: methodology, data curation, and writing. Yimin Li: conceptualization and writing – review. Liming Su: validation and methodology. Jiaxin Liu: investigation and methodology. Cong Du: conceptualization and writing – review. Wenjie Yuan: conceptualization, data curation, and writing – review.

Data availability

The data supporting this article have been included as part of the ESI.

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study was supported by the National Key Research and Development Program of China (2021YFC2101305) and the National Natural Science Foundation of China (22408041). The authors acknowledge the assistance of DUT Core Facilities of the School of Bioengineering.

References

  1. M. Kumar, A. Gupta and I. S. Thakur, Bioresour. Technol., 2016, 213, 249–256 CrossRef CAS PubMed .
  2. A. S. Alothaim, J. King Saud Univ., Sci., 2023, 35, 102939 CrossRef .
  3. D. Tilman, R. Socolow, J. A. Foley, J. Hill, E. Larson, L. Lynd, S. Pacala, J. Reilly, T. Searchinger, C. Somerville and R. Williams, Science, 2009, 325, 270–271 CrossRef CAS PubMed .
  4. IEA – International Energy Agency, https://www.iea.org, (accessed March 22, 2023).
  5. A. Nisar, S. Khan, M. Hameed, A. Nisar, H. Ahmad and S. A. Mehmood, Microbiol. Res., 2021, 251, 126813 CrossRef CAS PubMed .
  6. M. Orlić, C. Hochenauer, R. Nagpal and V. Subotić, Energy Convers. Manage., 2024, 314, 118601 CrossRef .
  7. S. Jin, Z. Hao, K. Zhang, Z. Yan and J. Chen, Angew. Chem., Int. Ed., 2021, 60, 20627–20648 CrossRef CAS PubMed .
  8. J. Tian, W. Deng, Z. Zhang, J. Xu, G. Yang, G. Zhao, S. Yang, W. Jiang and Y. Gu, Nat. Commun., 2023, 14, 7758 CrossRef CAS PubMed .
  9. W. Jiang, D. Hernández Villamor, H. Peng, J. Chen, L. Liu, V. Haritos and R. Ledesma-Amaro, Nat. Chem. Biol., 2021, 17, 845–855 CrossRef CAS PubMed .
  10. Y. Chen, P. Li, H. Noh, C.-W. Kung, C. T. Buru, X. Wang, X. Zhang and O. K. Farha, Angew. Chem., Int. Ed., 2019, 58, 7682–7686 CrossRef CAS PubMed .
  11. Y. Lu, Z.-Y. Jiang, S.-W. Xu and H. Wu, Catal. Today, 2006, 115, 263–268 CrossRef CAS .
  12. J. Luo, A. S. Meyer, R. V. Mateiu and M. Pinelo, New Biotechnol., 2015, 32, 319–327 CrossRef CAS PubMed .
  13. A. Ünlü, Z. E. Duman-Özdamar, B. Çaloğlu and B. Binay, Protein J., 2021, 40, 489–503 CrossRef PubMed .
  14. Y. J. Li, M. M. Wang, Y. W. Chen, M. Wang, L. H. Fan and T. W. Tan, Sci. Rep., 2017, 7, 43875 CrossRef PubMed .
  15. C. Du, Y. Li, Y. He, L. Su, H. Wang, W. Yuan and F. Bai, Green Chem., 2022, 24, 6989–6999 RSC .
  16. H. Rasouli, I. Iliuta, F. Bougie, A. Garnier and M. C. Iliuta, Chem. Eng. J., 2022, 432, 134029 CrossRef CAS .
  17. M. S. Mesbahuddin, A. Ganesan and S. Kalyaanamoorthy, Protein Eng., Des. Sel., 2021, 34, gzab021 CrossRef PubMed .
  18. T. Sharma, S. Sharma, H. Kamyab and A. Kumar, J. Cleaner Prod., 2020, 247, 119138 CrossRef CAS .
  19. X. Ji, Z. Su, P. Wang, G. Ma and S. Zhang, ACS Nano, 2015, 9, 4600–4610 CrossRef CAS PubMed .
  20. S. Zaidi, N. Srivastava and S. Kumar Khare, Bioresour. Technol., 2022, 365, 128174 CrossRef CAS PubMed .
  21. X. Zhang, W. Shao, B. Chen and M. Wang, Enzyme Microb. Technol., 2021, 146, 109763 CrossRef CAS PubMed .
  22. K. Min, Y.-S. Park, G. W. Park, J.-P. Lee, M. Moon, C. H. Ko and J.-S. Lee, Bioresour. Technol., 2020, 305, 123155 CrossRef CAS PubMed .
  23. U. K. Laemmli, Nature, 1970, 227, 680–685 CrossRef CAS PubMed .
  24. D. Gietz and R. A. Woods, Yeast Gene Anal., 1998, 26, 53–66 Search PubMed .
  25. M. Moon, G. W. Park, J.-P. Lee, J.-S. Lee and K. Min, J. CO2 Util., 2020, 42, 101353 CrossRef CAS .
  26. C. F. Nielsen, L. Lange and A. S. Meyer, Biotechnol. Adv., 2019, 37, 107408 CrossRef CAS PubMed .
  27. L. Calzadiaz-Ramirez and A. S. Meyer, Curr. Opin. Biotechnol., 2022, 73, 95–100 CrossRef CAS PubMed .
  28. V. O. Popov and V. S. Lamzin, Biochem. J., 1994, 301, 625–643 CrossRef CAS PubMed .
  29. R. Sato and Y. Amao, New J. Chem., 2020, 44, 11922–11926 RSC .
  30. M. Meneghello, A. R. Oliveira, A. Jacq-Bailly, I. A. C. Pereira, C. Léger and V. Fourmond, Angew. Chem., Int. Ed., 2021, 60, 9964–9967 CrossRef CAS PubMed .
  31. G. Ÿzgün, N. G. Karagüler, O. Turunen, N. J. Turner and B. Binay, J. Mol. Catal. B: Enzym., 2015, 122, 212–217 CrossRef .
  32. M. Persson, M. Galbe and O. Wallberg, Biotechnol. Biofuels, 2020, 13, 156 CrossRef CAS PubMed .
  33. J.-W. Kim, S.-O. Seo, G.-C. Zhang, Y.-S. Jin and J.-H. Seo, Bioresour. Technol., 2015, 191, 512–519 CrossRef CAS PubMed .
  34. A. Alissandratos, H.-K. Kim and C. J. Easton, Bioresour. Technol., 2014, 164, 7–11 CrossRef CAS PubMed .
  35. F. M. Schwarz and V. Müller, Biotechnol. Biofuels, 2020, 13, 32 CrossRef CAS PubMed .
  36. S. K. You, Y. J. Ko, S. K. Shin, D. H. Hwang, D. H. Kang, H. M. Park and S. O. Han, Bioresour. Technol., 2020, 318, 124072 CrossRef CAS PubMed .
  37. R. Sato and Y. Amao, React. Chem. Eng., 2022, 7, 181–191 RSC .
  38. G. D. Price, Photosynth. Res., 2011, 109, 47–57 CrossRef CAS PubMed .
  39. Q. Liao, W. Liu and Z. Meng, Biotechnol. Adv., 2022, 60, 108024 CrossRef CAS PubMed .
  40. V. Guadalupe-Medina, H. W. Wisselink, M. A. H. Luttik, E. de Hulster, J.-M. Daran, J. T. Pronk and A. J. A. van Maris, Biotechnol. Biofuels, 2013, 6, 125 CrossRef CAS PubMed .
  41. P.-F. Xia, G.-C. Zhang, B. Walker, S.-O. Seo, S. Kwak, J.-J. Liu, H. Kim, D. R. Ort, S.-G. Wang and Y.-S. Jin, ACS Synth. Biol., 2017, 6, 276–283 CrossRef CAS PubMed .
  42. A. C. A. van Aalst, I. S. van der Meulen, M. L. A. Jansen, R. Mans and J. T. Pronk, Metab. Eng., 2023, 80, 151–162 CrossRef CAS PubMed .
  43. Z. Zhu, P. Geng, M. Li, H. Yin, C. Li, X. Cao and J. Tian, Chem. Eng. J., 2024, 488, 151182 CrossRef CAS .
  44. B. M. Bakker, K. M. Overkamp, A. J. A. van Maris, P. Kötter, M. A. H. Luttik, J. P. van Dijken and J. T. Pronk, FEMS Microbiol. Rev., 2001, 25, 15–37 CrossRef CAS PubMed .
  45. V. E. Balderas-Hernández, K. Correia and R. Mahadevan, J. Ind. Microbiol. Biotechnol., 2018, 45, 735–751 CrossRef PubMed .
  46. P. J. Gommers, B. J. van Schie, J. P. van Dijken and J. G. Kuenen, Biotechnol. Bioeng., 1988, 32, 86–94 CrossRef CAS PubMed .
  47. Z. Dong, X. Li, L. Liu, G. Du and J. Chen, Acta Microbiol. Sin. (Engl. Transl.), 2008, 48, 1061–1066 CAS .
  48. S. J. Bae, S. Kim, H. J. Park, J. Kim, H. Jin, B. G. Kim and J. S. Hahn, Metab. Eng., 2021, 66, 68–78 CrossRef CAS PubMed .
  49. Y. G. Lee, Y. S. Jin, Y. L. Cha and J. H. Seo, Bioresour. Technol., 2017, 228, 355–361 CrossRef CAS PubMed .

Footnote

Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d5gc00705d

This journal is © The Royal Society of Chemistry 2025
Click here to see how this site uses Cookies. View our privacy policy here.