DOI:
10.1039/D5GC03349G
(Tutorial Review)
Green Chem., 2026,
28, 21-36
Recent advancements in microbial carbon dioxide fixation: metabolic engineering strategies
Received
1st July 2025
, Accepted 7th October 2025
First published on 9th October 2025
Abstract
Global warming driven by rising CO2 emissions has spurred intense interest in biological carbon fixation as a sustainable alternative to physicochemical approaches. This review explores natural, engineering, and synthetic CO2 fixation strategies in both microbial and cell-free systems. We first outline canonical natural pathways, then highlight recent metabolic engineering approaches that enhance flux through native enzymes, optimize cofactor balances, and leverage CRISPR- and evolution-based tools to improve growth on CO2 or mixed C1 substrates. Next, we describe emerging synthetic routes, as well as electrochemical–microbial hybrid systems that couple renewable electricity with biocatalysis. We then discuss downstream engineering tactics for metabolic-flux redirection, energy-supply augmentation, regulatory-gene editing, and enzyme-design via directed evolution to overcome kinetic and thermodynamic barriers. High-density cultivation, omics-guided optimization, and non-traditional hosts (acetogens, sulfate reducers, methanotrophs, methylotrophs, and yeasts) are surveyed for their industrial potential. Finally, we evaluate integration with waste-gas streams, direct-air-capture platforms and biomass conversion, consider techno-economic and scale-up challenges, and identify opportunities for artificial-intelligence driven pathway design. By uniting advances across biology, chemistry, and engineering, this review charts a roadmap toward efficient and scalable CO2-to-chemical bioproduction. Future progress in microbial CO2 fixation is expected to rely on the development of more efficient CO2-fixing enzymes and metabolic pathways, together with the incorporation of electro-biotechnology and optimized bioprocesses to enhance scalability and carbon conversion efficiency.
Green foundation
1. As metabolic engineering of microbes emerges as a prominent combative force to mitigate greenhouse gas (GHG) emissions such as CO2, we provide a rundown of natural and synthetic pathways utilized by microbes to accomplish this task. Various strategies for engineering and optimizing CO2-fixing microbes have been discussed.
2. Utilizing microbes as a green platform not only to reduce atmospheric CO2 but also to produce valuable compounds holds promise, as it can turn 37.8 Gt of pollutants into a potential industrial feedstock. We highlight techniques that bring the synthetic biology, process engineering, electrochemistry, and computational domains together to improve this technology in the future.
3. Although much work has been focused on industrializing the concept, the scalability of this technology remains a challenge as of now. The review summarizes various industrial bottlenecks and addresses them with multidisciplinary strategies.
|
1. Introduction
Global warming is one of the most pressing challenges facing the world today, with carbon dioxide (CO2) being a major contributor. Each year, CO2 emissions continue to rise at an alarming rate, reaching 41.6 billion tons in 2024.1 To address this challenge, various strategies have been implemented, including reforestation, afforestation, and soil carbon sequestration, to help reduce CO2 levels and mitigate global warming.2 Microorganism-based approaches have also been explored, enabling the fixation of CO2 into products such as biofuels, bioplastics, and other industrially important compounds.3,4
Microorganisms naturally use CO2 fixation pathways, which can be enhanced through metabolic engineering strategies to improve efficiency. Enzyme engineering has significantly contributed to enhancing CO2 fixation efficiency, as demonstrated by both direct and indirect modifications of the ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO) enzyme.5,6 Additionally, synthetic pathways have been designed to channel CO2 into the production of valuable compounds.7 Recent advancements, particularly the integration of artificial intelligence, have further accelerated the optimization of metabolic pathways and enzyme engineering, enabling more efficient and precise CO2 fixation strategies.
Despite recent advancements, major challenges persist, most notably the low efficiency of carbon utilization and limited bioproduction. The current capacity of CO2 fixation technologies remains insufficient to meet global sustainability demands. To address these gaps, this review examines natural, engineered, and synthetic metabolic pathways for CO2 fixation. It explores the key enzymes and cofactors involved, metabolic pathway kinetics, and electron transport mechanisms. Additionally, we discuss recent advancements in sustainable bioproduction from CO2, along with the expanding role of artificial intelligence in accelerating progress in this field.
2. Microbial CO2 fixation pathways and chemical conversion
2.1. Natural CO2 fixation pathways
Natural CO2 fixation pathways are fundamental to converting atmospheric CO2 into organic biomass, sustaining life, and maintaining global carbon cycles. The CBB cycle, predominant in plants, algae, and cyanobacteria, relies on RubisCO to catalyze CO2 assimilation.8 In contrast, anaerobic bacteria and archaea utilize alternative pathways tailored to their environmental constraints. For instance, the reductive tricarboxylic acid (rTCA) cycle fixes CO2 by running the oxidative TCA cycle in reverse, while the 3-hydroxypropionate bicycle, found in Chloroflexus bacteria, and the Wood–Ljungdahl pathway (WLP), used by acetogens and methanogens, function efficiently under anaerobic conditions (Fig. 1).
 |
| | Fig. 1 The illustration of multiple natural CO2 fixation pathways into central carbon metabolism. The pathways include the Calvin–Benson–Bassham (CBB) cycle, the Wood–Ljungdahl pathway, the 3-hydroxypropionate (3HP) bicycle, the 3-hydroxypropionate/4-hydroxybutyrate (DC/4HB) cycle, and the reductive tricarboxylic acid (rTCA) cycle. Carbon fixation steps are marked by the incorporation of CO2 or HCO3−, catalyzed by key enzymes such as ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO), acetyl-CoA carboxylase (ACC), carbon monoxide dehydrogenase/acetyl-CoA synthase (CODH/ACS), phosphoenolpyruvate synthase and carboxylase (Ps & Ppc), isocitrate dehydrogenase (ICDH), and propionyl-CoA carboxylase (Pcc). The figure also highlights metabolic energy requirements via ATP consumption and redox balancing through NADPH use. Abbreviations of metabolites are as follows: R5P – ribulose 5-phosphate; F6P – fructose 6-phosphate; G3P – glyceraldehyde 3-phosphate; PYR – pyruvate; Ac-CoA – acetyl-CoA; M-CoFeS – methyl-CoFeS; MTFH – methenyl-tetrahydrofolate; MeTHF – methyl-tetrahydrofolate; 10-FTHF – 10-formyl-tetrahydrofolate; FOR – formate; Mal-CoA – malonyl-CoA; MeC4-CoA – methylsuccinyl-CoA; 3HP – 3-hydroxypropionate; 3Pp-CoA, 3-propionyl-CoA; mm-CoA – methylmalonyl-CoA; OAA – oxaloacetate; MAL – malate; FUM – fumarate; SUC – succinate; Suc-CoA – succinyl-CoA; CIT – citrate; 2OG – 2-oxoglutarate (α-ketoglutarate); Cr-CoA – crotonyl-CoA; PEP – phosphoenolpyruvate; 4-HB-CoA – 4-hydroxybutyryl-CoA; 4-HB – 4-hydroxybutyrate; and Ssa – succinic semialdehyde. | |
Expanding this metabolic diversity, certain archaea in extreme environments, such as thermoacidophilic archaea (Sulfolobus, Acidianus, and Metallosphaera), employ the 3-hydroxypropionate/4-hydroxybutyrate (3-HP/4-HB) cycle, which merges 3-HP and 4-HB intermediates to optimize CO2 fixation. Similarly, the dicarboxylate/4-hydroxybutyrate (DC/4-HB) cycle, used by anaerobic archaea like Ignicoccus, integrates dicarboxylate and 4-HB metabolism to fix CO2 with minimal ATP consumption, making it energy-efficient for nutrient-limited settings.9
2.2. Synthetic CO2 fixation pathways
Synthetic CO2 fixation pathways represent innovative biochemical routes designed to enhance carbon capture and utilization beyond natural pathways like the Calvin cycle. The CETCH cycle (crotonyl-CoA/ethylmalonyl-CoA/hydroxybutyryl-CoA) is a notable example, combining enzymes from diverse organisms to achieve higher ATP efficiency than those in natural cycles.10 An engineered variant of the serine cycle, incorporating an alternative CO2 fixation pathway via pyruvate, has been successfully demonstrated in E. coli.11 The ASAP (artificial starch anabolic pathway), a chemical–biochemical hybrid pathway for starch synthesis from CO2 and hydrogen, has been established in a cell-free system.12 Similarly, formolase catalyzes the formation of a carbon–carbon bond by condensing three molecules of formaldehyde into one molecule of the three-carbon compound dihydroxyacetone.13 The SACA (synthetic acetyl-CoA) pathway, a synthetic, ATP-independent pathway, has been developed to produce acetyl-CoA from one-carbon substrates such as formaldehyde.14 These pathways highlight the potential of synthetic biology to reimagine carbon fixation, offering scalable solutions for sustainable bioproduction and climate change mitigation. Fig. 2 illustrates engineered and synthetic variants of CO2 fixation, and Fig. 3 compares their energy demands and engineering complexity. Table 1 complements these figures by summarizing core CO2 fixation pathway characteristics.
 |
| | Fig. 2 A network of engineered CO2 assimilation pathways integrated into central metabolism. Highlighted pathways include the GED (Gnd-Edd-Eda) pathway, the reductive glycine (rGly) pathway, the modified serine cycle, the reductive glyoxylate and pyruvate synthesis (rGPS) cycle, the TaCo (tartronyl-CoA) pathway, the CETCH cycle, the THETA cycle, and the HOPAC cycle. Key enzymatic steps for carbon fixation and C1 assimilation are labeled, including 6-phosphogluconate dehydrogenase (Gnd), Entner–Doudoroff enzymes (Edd, Eda), serine hydroxymethyltransferase (SHMT), the glycine cleavage system and tetrahydrofolate pathway (Gcv/THP), methylene-THF dehydrogenase (MtdA), formyl-THF cyclohydrolase (Fch) and formyl-THF ligase (Fti), phosphoenolpyruvate carboxylase (Ppc), the glycine cleavage system (GCS), glyoxylate carboxylase (GCC), crotonyl-CoA carboxylase/reductase (Ccr), malonyl-CoA synthase (MAS), and propionyl-CoA carboxylase (Pcc). Abbreviations of metabolites are as follows: R5P – ribulose 5-phosphate; F6P – fructose 6-phosphate; G3P – glyceraldehyde 3-phosphate; 6PG – 6-phosphogluconate; KGPG – 2-keto-3-deoxy-6-phosphogluconate; PYR – pyruvate; SER – serine; PEP – phosphoenolpyruvate; OAA – oxaloacetate; MAL – malate; MTFH – methenyl-tetrahydrofolate; MeTHF – methyl-tetrahydrofolate; 10-FTHF – 10-formyl-tetrahydrofolate; FOR – formate; Mal-CoA – malonyl-CoA; Ma-CoA – malyl-CoA; Cr-CoA – crotonyl-CoA; Ace-CoA – acetyl-CoA; Gly – glycine; Go – glyoxylate; Ga – glycolate; Gc – glycerate; Gl-CoA – glyceryl-CoA; Tt-CoA – tartronyl-CoA; 4HB – 4-hydroxybutyrate; Em-CoA – ethylmalonyl-CoA; Prp-CoA – propionyl-CoA; Acr-CoA – acryloyl-CoA; Me-CoA – methylmalonyl-CoA; Suc – succinate; Suc-CoA – succinyl-CoA; Fum-CoA – fumaroyl-CoA; Ala-CoA – alanoyl-CoA; Ala – alanine; 3HP – 3-hydroxypropionate; and 3HP-CoA – 3-hydroxypropionyl-CoA. | |
 |
| | Fig. 3 Comparison of natural and synthetic CO2 fixation pathways. Natural pathways (e.g., CBB cycle, 3HP bicycle, rTCA cycle, WLP, 4HB pathway) are typically hosted in autotrophs such as C. necator and cyanobacteria, offering robustness but posing challenges for genetic engineering. Synthetic pathways (e.g., CORE, CETCH, rGly, ASAP, HOPAC, SACA, formolase) have been implemented in tractable hosts like E. coli and S. cerevisiae, enabling easier engineering and product diversification. Trade-offs between energy/redox requirements, host choice, and engineering complexity determine their suitability for applications ranging from biofuels to bioplastics. | |
Table 1 Comparison of natural and synthetic carbon dioxide fixation pathways in terms of various parameters
| Pathway |
No. of enzymes involved |
Key enzymes involved in the pathway |
Oxygen sensitivity |
End products |
Energy efficiency (per carbon) |
Ref. |
|
Natural pathways
|
| Calvin–Benson–Bassham (CBB) cycle |
11 |
RubisCO |
Aerobic |
Glyceraldehyde-3-phosphate |
3 ATP and 2 NAD(P)H |
25
|
| Reductive tricarboxylic acid (rTCA) |
8 |
2-Oxoglutarate synthase, isocitrate, dehydrogenase, fumarate reductase |
Anaerobic |
Acetyl-CoA |
1 ATP and 2 NAD(P)H |
26
|
| Wood–Ljungdahl (WL) pathway |
8–10 |
NAD-independent formate dehydrogenase, acetyl-CoA synthase-CO dehydrogenase |
Anaerobic |
Acetyl-CoA |
0.5 ATP and 2 NAD(P)H |
27
|
| 3-Hydroxypropionate bicycle |
13 |
Acetyl-CoA carboxylase, propionyl-CoA carboxylase |
Aerobic |
Pyruvate |
1.67 ATP and 2 NAD(P)H |
28
|
| 3-Hydroxypropionate/4-hydroxybutyrate (3-HP/4-HB) cycle |
15 |
Acetyl-CoA carboxylase, propionyl-CoA carboxylase |
Aerobic |
Acetyl-CoA |
2 ATP and 2 NAD(P)H |
29
|
| Dicarboxylate/4-hydroxybutyrate (DC/4-HB) cycle |
14 |
Pyruvate synthase, PEP carboxylase |
Anaerobic |
Acetyl-CoA |
1.5 ATP and 2 NAD(P)H |
30
|
|
Synthetic pathways
|
| Crotonyl-CoA/ethyl malonyl-CoA/hydroxybutyryl-CoA (CETCH) pathway (version 5.4) |
17 |
CoA-dependent carboxylase |
Aerobic |
Glyoxylate |
0.5 ATP and 2 NAD(P)H |
10
|
| Reductive glycine pathway |
8,9 |
Formate dehydrogenase, glycine cleavage system |
Aerobic |
Pyruvate |
2 ATP and 3NAD(P)H |
25
|
| Artificial starch anabolic pathway (ASAP) (version 3.0 and 3.1) |
10 (plus CO2 to methanol chemical reaction) |
Formolase, Dihydroxyacetone kinase, ADP-glucose pyrophosphorylase |
N/A |
Amylose/amylopectin |
2 ATP per C6 (~0.33 ATP /CO2) |
12
|
| Synthetic acetyl Co-A (SACA) pathway |
3 (from formaldehyde; +2 if from CO2) |
Glycolaldehyde synthase |
Aerobic and anaerobic |
Acetyl-CoA |
No ATP or NAD(P)H required from formaldehyde. Starting from CO2 requires 2 NAD(P)H |
14
|
| HydrOxyPropionyl-CoA/Acrylyl-CoA (HOPAC) cycle (version 4.0) |
11 |
Acetyl-CoA carboxylase, propionyl-CoA carboxylase, cinnamoyl-CoA reductase |
Aerobic |
Glyoxylate |
1ATP, 1.5 NAD(P)H |
31
|
| Formolase pathway |
5 |
Acetyl-CoA synthase, acetaldehyde dehydrogenase, formolase (FLS) |
Aerobic and anaerobic |
Dihydroxyacetone |
2 ATP and 2 NAD(P)H |
13
|
| CO2 reduction (CORE) cycle (CoA-transferase variant) |
6 |
β-Keto acid cleavage enzyme (BKACE) |
Aerobic |
Acetyl-CoA |
1 ATP and 1 NAD(P)H |
32
|
2.3. Chemical conversion of CO2
Electrochemical CO2 conversion utilizes renewable electricity to reduce CO2 into value-added chemicals (e.g., hydrocarbons, alcohols, syngas) which can then be harnessed by microorganisms as feedstocks for the sustainable production of biofuels and bioplastics. Central to this process are catalysts (e.g., copper, zinc, or molecular complexes) that lower the energy barrier for CO2 activation and steer selectivity toward desired products. Key pathways include the reduction of CO2 to CO pathway (via CO2-to-CO electrocatalysts like Cu, Sb), the formic acid and methane pathway (using Cu/Zn), and the multi-carbon product pathway (e.g., ethylene/ethanol on Cu-based catalysts).15–17 A representative biohybrid strategy demonstrated gram-scale PHB production by integrating electrochemical CO2 reduction with microbial fermentation. In this system, CO2 was electrochemically reduced to formate using Sn-based gas diffusion electrodes (GDEs), which then served as the carbon source for C. necator. The cells accumulated PHB up to 83% of dry cell weight, and with a 4 cm2 Sn-GDE the process yielded 1.38 g of PHB, demonstrating the feasibility of direct CO2-to-bioplastic conversion.18 Beyond polymers, engineered C. necator LH74D has been applied for electrobiosynthesis of liquid fuels, including isobutanol and 3-methyl-1-butanol. In this integrated electro-microbial system, CO2 was first reduced to formate, which functioned as both a carbon and an energy source. Operating within a single reactor, the platform produced over 140 mg L−1 of biofuels directly from electricity and CO2, illustrating the potential of electro-microbial coupling for sustainable fuel synthesis.19
Beyond electrochemical reduction, chemical CO2 conversion also encompasses thermochemical and photochemical approaches. Thermochemical routes, such as catalytic hydrogenation using metals like Ru, Ni, or Fe, convert CO2 into methanol, dimethyl ether, or hydrocarbons under high temperature and pressure.20,21 Photocatalytic systems, often employing TiO2 or metal–organic frameworks (MOFs), enable solar-driven CO2 reduction to fuels such as methane and methanol.22 In one study, photocatalyst-assisted PHB production was demonstrated using C. necator in combination with cadmium sulfide (CdS) nanorods. Under light irradiation, the CdS nanorods transferred photoexcited charges to C. necator, facilitating CO2 reduction and channeling the fixed carbon into PHB biosynthesis. This hybrid system achieved a yield of 28 mg of PHB from CO2 within 48 hours.23 In another study, a biohybrid system was developed using the acetogen Sporomusa ovata coupled with a photocatalyst sheet to overcome the challenge of external electricity input. The photocatalyst sheet was composed of two particulate semiconductors La and Rh co-doped SrTiO3 (SrTiO3:La,Rh) and Mo-doped BiVO4 (BiVO4:Mo). Under sunlight, CO2, and H2O, the system simultaneously oxidized water to generate O2 while transferring electrons and H2 to S. ovata, which selectively converted CO2 into acetate (CH3COO−). This hybrid approach achieved a solar-to-acetate conversion efficiency of 0.7% under ambient conditions.24 Taken together, these integrated chemical–biological systems represent a promising route toward carbon-neutral manufacturing of sustainable materials and energy carriers.
3. Recent advances in genetic and system engineering for CO2 fixation
Microbial carbon dioxide fixation can be improved through a combination of genetic, metabolic, and process-level strategies (Fig. 4). Techniques such as enzyme engineering and CRISPR-based gene editing allow for precise modifications to pathways, enhancing fixation efficiency. Optimizing metabolic flux, electron donors, and energy balance ensures effective CO2 assimilation by maintaining resource equilibrium. Adaptive laboratory evolution and omics-based approaches help identify and develop high-performance strains. Additionally, optimizing high cell-density cultures enhances carbon capture efficiency in industrial settings. These integrated strategies collectively contribute to advancing microbial CO2 fixation.
 |
| | Fig. 4 The framework of key optimization strategies for enhancing microbial carbon dioxide fixation, including enzyme engineering, CRISPR-based editing, metabolic flux and electron donor optimization, adaptive laboratory evolution, omics-driven approaches, high cell-density culture optimization, and energy optimization. | |
3.1 Metabolic flux optimization
Microbial CO2 fixation is vital for reducing carbon emissions but is often limited by inefficient enzymes or metabolic pathways. Enhancing the expression of native carbon fixation genes or introducing more effective heterologous genes can address this limitation. For instance, a heterotrophic E. coli strain engineered to express korA and korB from Chlorobaculum tepidum encoding ferredoxin oxidoreductase demonstrated enhanced incorporation of CO2 in the rTCA cycle metabolites such as citrate, pyruvate, α-ketoglutarate, and succinate.33 Enhancing metabolic flux by supporting the function of key enzymes can help overcome carbon fixation inefficiencies. In autotrophs, the primary limitation is the low carbon capture efficiency of RubisCO. Introducing exogenous carbonic anhydrase, which converts CO2 to bicarbonate, increases carbon availability to RubisCO. This has improved the RubisCO efficiency in microalgae like Chlorella sp. by boosting enzyme levels by up to 25% and reducing oxygenation rates.34 It has been shown that increases in concentrations of succinate and malate also positively influence the rate efficiency of carbon dioxide assimilation by directing the carbon flux to efficient pathways and reducing carbon loss.34 Heterologous expression of phosphoenolpyruvate carboxylase and phosphoenolpyruvate carboxykinase in a type I methanotroph increased CO2-dependent succinate production by 46% compared to the wild type.35
3.1.1. Optimization of energy supply.
The high energy requirements of the associated enzymes, which vary depending on the process, present a significant obstacle to biological CO2 fixation. For instance, the CBB cycle depends on ATP and NADPH, while the WL pathway in Clostridium and Acetobacterium uses reducing agents like H2 or formate.36 In E. coli, the expression of korA and korB enabled electron transfer analogous to the rTCA cycle, which in organisms such as Desulfobacter and Chlorobaculum depends on ferredoxin-linked enzymes with high reducing power requirements.37 Thus, boosting the availability of cofactors such as ATP, NAD(P)H, or noncanonical redox cofactors (NCRCs) is a promising strategy to overcome these energy constraints.38 Since these pathways face significant energy barriers, advanced metabolic engineering is needed. For instance, redirecting ATP toward RubisCO carboxylation in E. coli has been reported to increase CO2 fixation by 870%.39 The cyanobacteria Synechocystis sp. PCC 6803′s capacity to fix carbon was increased by 3.2 times when the NAD(P) transhydrogenase gene was overexpressed to improve the reduced power supply.40 In cell-free systems, ATP regeneration can be improved via engineered ATP synthases or light-driven proton pumps.41 Bio-electrochemical systems combining electrode-derived energy with microbial metabolism have also shown promise.42 However, excess ATP or NADPH can lead to metabolic stress and hinder growth, which may be resolved by combining this strategy with other techniques such as optimization of cell culture conditions.
3.1.2 Engineering of regulatory genes for CO2 assimilation.
Engineering of assimilation genes enhances CO2 fixation efficiency in both natural autotrophs and engineered microbial systems. In the CBB cycle of cyanobacteria, the CO2 fixation during day and night can be improved by deleting the regulatory protein CP12, which normally inhibits the activities of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and phosphoribulokinase (PRK) in the dark. Removing CP12 lifts this inhibition, allowing continuous enzyme activity and promoting more consistent carbon fixation from Ru5P to R15P across light and dark cycles.43
In another study involving the rGly pathway in E. coli for enhanced growth on formic acid and CO2, deletion of the ppsR gene encoding the regulatory protein of phosphoenolpyruvate synthase was implemented to block the conversion of pyruvate to phosphoenolpyruvate (PEP). This genetic modification prevented carbon loss through the reverse reaction and redirected carbon flux toward biomass formation, resulting in improved carbon assimilation and growth efficiency.44
RubisCO expression in many autotrophs is directly controlled by the LysR-type transcriptional activator CbbR; elevating CbbR levels boosts transcription of the cbb operon and drives higher CO2-fixation rates. In C. necator H16, an additional tier of control is provided by the RegB/RegA two-component system, which senses the cellular redox state and further modulates CBB cycle gene expression, ensuring that RubisCO and associated enzymes are expressed in tune with metabolic demands.45 Artificial intelligence (AI)-driven omics analyses are increasingly important for identifying regulatory genes involved in CO2 fixation. By analyzing large-scale genomic, transcriptomic, and metabolomic data, artificial intelligence helps uncover key regulatory elements. Manipulating these genes offers new opportunities to improve CO2 assimilation in both natural and engineered microbial systems.
3.1.3 Enzyme engineering.
Enzyme engineering approaches have emerged as transformative strategies to overcome the intrinsic limitations of natural CO2 fixing enzymes and to boost carbon assimilation efficiency in both autotrophic organisms and engineered microbial platforms. By applying techniques such as site-directed mutagenesis, directed evolution, and rational design, researchers have been able to enhance the catalytic turnover and substrate specificity of key enzymes like RubisCO, whose sluggish kinetics and oxygenase activity limit overall carbon fixation rates.6 Directed evolution of RubisCO from Synechococcus PCC6301 enhanced its carboxylation activity by up to 85%. Similarly, heterologous expression of RubisCO from Thermosynechococcus elongatus BP1 in E. coli resulted in an improved carboxylation rate, efficiency, and CO2/O2 specificity. Expression of Rhodobacter sphaeroides RubisCO in E. coli resulted in a 27% increase in carboxylation rate and a 17% improvement in carboxylation efficiency, while maintaining stable CO2/O2 specificity; however, the holoenzyme biogenesis capacity was reduced by 40%. Furthermore, site-directed mutagenesis of R. sphaeroides RubisCO (C329A and A332 V) expressed in E. coli led to a 60% increase in carboxylation rate, a 22% improvement in carboxylation efficiency in air, and a 7% enhancement in CO2/O2 specificity.6 Beyond natural RubisCO variants, a synthetic CO2-fixing enzyme, glycolyl-CoA carboxylase (GCC), was generated through rational design coupled with high-throughput microfluidic screening and microplate-based assays. GCC's catalytic efficiency improved by three orders of magnitude, achieving levels comparable to those of natural CO2-fixing enzymes.46 Taken together, these studies highlight both natural and synthetic strategies for enhancing CO2 fixation efficiency beyond the limits of native RubisCO.
3.2 Process regulation of high cell-density culture
High cell density cultivation is critical in bioprocessing to boost the volumetric productivity of target products. High-density cultures face limitations from suboptimal carbon sources, substrate depletion, and cofactor shortages, which can be improved to increase growth and productivity.47 High concentrations of substrates, such as glucose or sucrose, are often necessary to support biomass and product formation.48
3.2.1 Optimization of carbon sources.
The choice of carbon sources plays a crucial role in microbial growth and CO2 fixation efficiency. Heterotrophic organisms like E. coli and Saccharomyces cerevisiae often require organic co-substrates to provide reduced power for CO2 assimilation. For instance, a CBB-engineered E. coli strain showed a 45% increase in CO2 fixation and improved biomass when grown on xylose instead of glucose. This strain was engineered with deletion of genes zwf and pfkAB which direct the flux towards the pentose phosphate pathway and glycolysis respectively. This strategy ensured that the flux shifted to favor the CBB pathway for carbon assimilation in a xylose medium.49 Formate, a low-energy carbon source, was also optimized in autotrophic algal–bacterial consortia, leading to 0.15 g L−1 biomass accumulation and 90% carbon assimilation efficiency under low light. Utilization of formate bypasses the gas–liquid mass transfer limitation of using bicarbonate as a carbon source due to its increased solubility and stability.50 Although ideally, microbes would use CO2 as the sole carbon source, its low solubility particularly as bicarbonate limits its uptake. This can be improved by delivering CO2via pressurized gas or continuous gas streams, enhancing its bioavailability.51 However, such methods can alter culture pH and require careful monitoring.
3.2.2 Optimization of electron donors.
Electron donors are vital for supplying the reducing power and energy required in microbial CO2 fixation.52 Increasing their availability in the culture medium can enhance carbon capture. For instance, supplying high levels of hydrogen to Clostridium autoethanogenum improves CO2 fixation by boosting the reduction potential.53 While hydrogen-oxidizing bacteria efficiently fix CO2 using H2, the scalability is limited due to H2 cost and safety concerns. Alternatives like formate or methanol show promise; for example, a Pichia pastoris strain engineered with the CBB cycle achieved autotrophic growth using methanol-derived reducing power, theoretically fixing up to 62 kg of CO2.54 Another strategy can be coupling microbes with electrochemical/photochemical systems which offers direct electron delivery, bypassing the need for organic donors.42 In one study, C. necator expressing rhodopsin was exposed to a light-driven photoelectric system and showed a 20% increase in CO2 assimilation, replacing organic donors with an electrode for efficient electron transfer.55 This photoelectric system replaces the need for organic electron donors with an electrode and drives maximum electron transfer efficiency in the strain. Inorganic donors like H2, sulfide (S2−), and thiosulfate (S2O32−) are also viable in heterotrophic systems. Combining multiple donors can create synergistic effects; for example, deep-sea chemoautotrophs achieved CO2 fixation rates of 6.209 mg (L h)−1 using a mix of NaNO2, Na2S2O3, and Na2S.56 Additionally, NCRCs such as NMN+ and NCD+ can substitute natural cofactors like NAD+ in engineered enzymes for efficient electron transfer.57 Ultimately, optimizing energy flow, redox balance, and culture conditions is key to maximizing microbial CO2 fixation, but strategies must be tailored to specific strains and process needs.
3.3 CRISPR-based genome editing in autotrophic microbes
CRISPR-based genome editing has emerged as a powerful tool to precisely modify the genomes of autotrophic microbes, thereby accelerating the development of strains with enhanced CO2 fixation capabilities and improved bioproduct yields. In cyanobacteria such as Synechocystis sp. PCC 6803 and Synechococcus elongatus as well as in chemolithoautotrophs like C. necator, CRISPR-Cas systems have enabled marker-less gene knockouts, precise insertions, and transcriptional regulation via CRISPR interference (CRISPRi).15,58–60 These advancements allow researchers to systematically dissect and rewire metabolic pathways, fine-tuning the expression of key genes involved in carbon assimilation and energy conversion. Moreover, the capacity for multiplex genome editing enables simultaneous modifications at several loci, which is critical for overcoming complex regulatory networks inherent to autotrophs. Despite challenges such as efficient DNA delivery and off-target effects, continuous improvements in CRISPR technology are rapidly expanding its utility in autotrophic systems, paving the way for the creation of robust microbial cell factories that can contribute to sustainable biofuel production and global carbon sequestration.
3.4 Adaptive laboratory evolution for improving CO2 fixation efficiency
Adaptive laboratory evolution (ALE) has emerged as a powerful tool for improving CO2 fixation efficiency and bioproduction yields across diverse microbial systems. ALE improved C. necator growth on volatile fatty acids (VFAs), with key mutations identified in phaR, the histidine kinase-response regulatory pair (H16_A1372/H16_A1373), and the tripartite transporter system (H16_A2296-A2298). These mutations enhanced growth, reduced NADH levels, and increased tolerance to higher VFA concentrations.61 Engineered E. coli strains, previously incapable of autotrophic growth, have 86 mutations and achieve CO2 fixation with doubling times reduced to approximately 3.8 hours. Mutations in AtoA altered its substrate preference, enabling more efficient activation of acetoacetate with formyl-CoA, supporting better integration into the engineered pathway.32 Adaptive evolution increased the CO2-specific growth rate from 0.008 h−1 to 0.018 h−1. Mutations were identified in the phosphoribulokinase (PRK) gene (A2G, T5A), which may influence ATP consumption and the supply of D-ribulose-5-phosphate for biosynthesis. Another mutation in nicotinic acid mononucleotide adenylyltransferase (NMA1; T358I) could affect intracellular NADH and ATP levels.54
3.5 Omics-driven strategies (genomics, transcriptomics, and metabolomics)
Genomic analyses of model lithoautotrophs routinely confirm the presence of canonical CO2 fixation operons. For example, the C. necator H16 genome encodes complete CBB cycle operons on both its chromosome and plasmid (including rbcL/S, prk, etc.). RNA-seq studies (DESeq2) under autotrophic (H2/CO2) versus heterotrophic conditions show hundreds of differentially expressed genes: overexpression of CBB regulators (CbbR/RegA) drives >2-fold induction of cbbL/S and adjacent CBB enzymes (with many TCA and PHB-biosynthesis genes also upregulated).62 The corresponding proteomic profiling by LC-MS/MS (e.g. MaxQuant) confirms these patterns: abundant RubisCO and other CBB enzymes are detected even under heterotrophic growth.63 Targeted metabolomics (GC/LC-MS) in engineered cyanobacteria revealed altered pools of Calvin-cycle intermediates (for instance, elevated G3P and F15P with depleted 3-PG consistent with enhanced carbon fixation) and identified bottlenecks that were relieved by overexpression of GAPDH.64 Finally, quantitative 13C–metabolic flux analysis mapped carbon flows through these pathways: e.g. steady-state 13C labeling in C. necator showed that the CBB cycle remained active (mixotrophically) even on organic substrates, with the Entner–Doudoroff pathway as the main sugar catabolism route and elevated oxidative pentose-phosphate flux feeding the CBB cycle.65 Taken together, these multi-omics studies (genomics, transcriptomics, proteomics, metabolomics and fluxomics) quantitatively validate microbial CO2 fixation machinery and pinpoint metabolic control points.
4. Synthetic biology application to non-traditional microbes and co-substrates for enhanced CO2 fixation
4.1 Acetogens and sulfate-reducing bacteria
Acetogens, such as Acetobacterium woodii, Moorella thermoacetica, and C. autoethanogenum, and sulfate-reducing bacteria like Desulfovibrio desulfuricans and Desulfovibrio vulgaris, are anaerobic microorganisms capable of fixing CO2via pathways such as the WLP and the rGly pathway. Metabolic engineering has significantly enhanced their CO2 fixation efficiency and production of valuable products. For instance, ethanol production in C. ljungdahlii increased by 1.5-fold following adhE1 gene induction, while C. autoethanogenum saw a 1.2-fold increase in ethanol production with CODH/ACS gene overexpression.66–68A. woodii doubled its ethanol production after adh4 gene deletion.69D. desulfuricans fixed CO2 through the reductive glycine pathway, the seventh known CO2 fixation route. In this pathway, CO2 was sequentially reduced to formate, then to glycine, which was further processed into acetyl-CoA via glycine reductase. Acetyl-CoA was then combined with another CO2 to produce pyruvate.70 Additionally, introducing the mevalonate pathway into C. ljungdahlii enabled isoprenoid production.71 These advancements highlight the potential of metabolic engineering in enhancing CO2 fixation and biofuel production in acetogens and sulfate-reducing bacteria, with applications in bioenergy production and environmental remediation.
4.2 Methanotrophs and methylotrophs
Type II methanotrophs and certain methylotrophs utilize the serine cycle and the reductive glycine pathway for CO2 fixation and energy metabolism, allowing efficient assimilation of C1 compounds. The yeast P. pastoris can grow on mixed C1 substrates, such as CO2 combined with methanol or formate, using its native enzymes. This is achieved without the need for overexpression by redirecting methylene-THF flux toward glycine formation, accomplished through deletion of the mitochondrial serine hydroxymethyltransferase gene.11 Type I methanotrophs can fix CO2 using the CBB cycle. Methylomirabilis oxyfera encodes and actively transcribes genes of the CBB cycle, enabling carbon assimilation via this autotrophic pathway.72 CO2 was essential for the growth of the RubisCO-encoding Methylococcus capsulatus Bath in a bioreactor with continuous gas inflow and outflow. RNA sequencing revealed active transcription of several carboxylating enzymes, including pyruvate carboxylase, phosphoenolpyruvate carboxylase, and ferredoxin oxidoreductase. Mutagenesis enabled the strain to assimilate CO2 alongside methane, facilitating its growth.73
5. Biotechnological applications and industrial potential
5.1 CO2-based biomanufacturing of biofuels, bioplastics, and high-value chemicals
Microbial CO2 sequestration technologies not only reduce carbon footprints but also serve as biorefineries, producing high-value chemicals such as bioethanol, polyhydroxyalkanoates (PHA), and succinate (Table 2). Microalgae and cyanobacteria fix CO2via photosynthesis into biomass, which can subsequently be converted into biofuels like bioethanol, biodiesel, and biohydrogen.74 Genetic engineering further enhances these processes; for example, S. elongatus has been modified to direct carbon flux toward fermentation pathways, increasing PHA production, while A. woodii achieves PHB accumulation up to 33.3% of cell content in high-pressure reactors.75,76 Other acetogens facilitate chain elongation to generate medium-chain fatty acids, and engineered R. sphaeroides produces β-farnesene from CO2 at levels 23 times higher than previous benchmarks. These examples highlight the potential of combining genetic technologies with biomass conversion as a strategy to mitigate CO2 emissions while generating valuable chemicals.77,78 Industrial implementation requires balancing microbial traits such as temperature tolerance, biomass yield, and carbon capture efficiency.74
Table 2 Biomanufacturing valuable compounds using CO2 as a carbon source
| Product |
Host strain |
Metabolic engineering strategy |
Cultivation conditions |
Yield |
Ref. |
| Ethanol |
Saccharomyces cerevisiae
|
C. necator H16 was the source of the overexpressed genes cbbL1, cbbS1, and cfxP1, whereas S. cerevisiae D452–2 was the source of tHSP60 and tHSP10. |
The yeast strains were inoculated into YP medium with 40 g L−1 xylose at 0.5 g DCW L−1 in 125 mL nitrogen-flushed, sealed serum bottles after being aerobically cultivated in YP medium and glucose, 10 ml and 20 g L−1 respectively, for 24 hours at 30 °C. Anaerobic fermentation was subsequently conducted at 30 °C, 130 rpm. |
14.5 g L−1 |
79
|
| 1,2-Propanediol |
Synechocystis sp. PCC6803 |
To convert dihydroxyacetone phosphate to methylglyoxal, which is subsequently reduced to acetol and then to 1,2-propanediol, native genes adh (alcohol dehydrogenase), yqhD (aldehyde reductase), and mgsA (methylglyoxal synthase) were overexpressed. |
Synechocystis was grown on BG11 or YBG11 agar with antibiotics under 25 μmol m−2 s−1 light, ambient CO2, 30 °C, and 75% humidity for 10 days. Then it was transferred to YBG11 with 50 mM HEPES; liquid cultures (50 mL) were grown in 250 mL baffled flasks at 30 °C, 150 rpm, 2% CO2, increasing light, and 75% humidity; main cultures were inoculated at OD750 = 0.2. |
1 g L−1 |
80
|
| Ethylene |
Synechocystis sp. PCC6803 |
Overexpression of phosphoenol pyruvate carboxylase. |
For two to three days, Synechocystis strains that overexpressed native gene or carried a kanamycin resistance cassette were cultivated in BG11 medium with kanamycin. |
16.77 ± 4.48 μg per mL per OD per day |
81
|
| PHB |
Synechococcus elongatus UAM-C/S03 |
N/A |
Nitrogen limiting conditions; the biomass was washed to remove nitrogen and resuspended in 2 × BG11; experiments at pH ∼8 or uncontrolled pH were conducted at 100 μmol photons m−2 s−1, 35 ± 0.5 °C, with 0.5 g L−1 initial biomass; batch cultures lasted 7–9 days with daily sterile sampling. |
40.82 mg L−1 d−1 |
82
|
| PHA |
Cupriavidus necator H16 |
To produce P(3HB), a recombinant R. eutropha PHB-4 strain was created, carrying the plasmids pBBR1:phaCABRe or pBBR1-phaRCYB4AB with PHA synthase genes from R. eutropha and Bacillus cereus YB-4, respectively, under the control of PHA promoter. |
A 250 mL jar fermenter with continuous gas flow was used for autotrophic culture in NR medium. Using mass flow controls, a gas mix (H2 : O2 : CO2 : N2 = 3.8 : 7.3 : 13.0 : 75.9) that was created by combining 5.8% H2, 19.9% CO2, and air was delivered at 1–15 mL min−1, keeping H2 below explosive values. |
2.94 g L−1 |
83
|
| Acetic acid |
Clostridium acetobutylicum
|
Carbon monoxide dehydrogenase was overexpressed. |
A 0.6 V poised potential at the working electrode was used to operate a small-scale microbial electrochemical system (100 mL total, 75 mL working volume); strains were grown in the appropriate media and inoculated at OD 0.6 (10 v/v %), with CO2 supplied in the headspace without disturbing biofilms; the retention time was 60 h for CO2 fixation and conversion analysis. |
7.8 g L−1 |
84
|
| Reservatrol |
Cupriavidus necator H16 |
Tyrosine ammonia lyase, 4-coumaroyl CoA ligase, and stilbene synthase are heterologous genes for resveratrol production that were introduced into C. necator H16. Multiple copies of Vitis vinifera's stilbene synthase, interruption of the PHB pathway, and overexpression of acetyl-CoA carboxylase |
C. necator H16 was routinely grown in LB at 30 °C and 200 rpm. To produce heterotrophic resveratrol, strains were cultivated in 40 mL of minimal medium (MM) with 10 g L−1 fructose and 5 mM tyrosine. For lithoautotrophic fermentation, precultures in MM with fructose were washed and inoculated into MM with tyrosine in 157 mL serum bottles (20 mL volume), pressurized daily with H2 : O2 : CO2 gas (70 : 20 : 10 or 78 : 2 : 10, 150 kPa), agitated at 200 rpm and 30 °C with original OD = 1 or 5. After 24 hours, gene expression was induced with 0.2% L-arabinose, and kanamycin (200 μg mL−1) was added for plasmid maintenance. |
1.9 mg L−1 |
85
|
| Extracellular polysaccharide (EPS) |
Porphyridium purpureum CoE1 |
N/A |
A 10% inoculum size was used to cultivate P. purpureum CoE1 in a flask of 1 L capacity with 500 mL of artificial seawater (ASW). For 18 days, the flask was kept in the same illumination incubator and exposed to cool white, fluorescent light sources that emitted about 165 μmol photons m−2 s−1. A ventilation rate of 1 L min−1 was used to maintain the culture temperature at 25 °C. Different dosages of inorganic salt were used to create ASW. Throughout the cultivation process (18 days), the dosage was fixed at 30%, 50%, or 70%. |
2.89 g L−1 |
86
|
| Oxalate |
Escherichia coli
|
Genes encoding fumarate and nitrate reductase, lactate dehydrogenase, pyruvate carboxylase, oxaloacetate acetylhydrolase, and acetyl-CoA synthetase were expressed heterologously |
E. coli BL21 (DE3) was grown in LB medium aerobically and in TB medium anaerobically. |
23 μM |
87
|
| Acetone |
Clostridium autoethanogenum
|
Overexpression of secondary alcohol dehydrogenase (sAdh) variants and -CoA transferase (CtfAB) |
In 2 L CSTR reactors, continuous fermentation was carried out anaerobically at 37 °C using a condenser to reduce volatile product loss and a synthetic gas blend (50% CO, 10% H2, 30% CO2, and 10% N2) at atmospheric pressure. Pilot tests using a mixture of 50% carbon monoxide, 10% hydrogen, 20% carbon dioxide, and 20% nitrogen gases were carried out in a bespoke reactor at 1.4 bar. For gas flow rates of 200–800 SCCM for the CSTRs and 11.5–23 NLPM for the pilot reactors, the medium dilution rates varied from 1.0 to 6.5 d−1. |
3 g L−1 h−1 |
88
|
| Lactic acid |
Pichia pastoris
|
Integration of one CYB2 knockout, which codes for L-lactate cytochrome c oxidoreductase, and a bacterial lactate dehydrogenase gene |
Using 0.5% methanol and 5% CO2 in the intake gas, bioreactors were inoculated from an YPG preculture to an OD of 2 for autotrophic cultivation. Following the initial sample, the methanol content was raised to 1%. |
600 mg L−1 |
89
|
| Succinate |
Synechococcus elongatus PCC 7942 |
Blocking glycogen synthase and succinate dehydrogenase using CRISPRi |
S. elongatus strains were grown in 60 mL of BG-11 medium containing IPTG in glass tubes for production with ambient or CO2-enriched air, beginning at OD730 ≈ 0.2. After being grown to an OD730 of 0.4–0.6, the pre-culture was stimulated with IPTG, centrifuged to concentrate it, and then resuspended. The temperature was set at 30 °C, the intensity of light was kept at 200 μE s−1 m−2, and 100 mL min−1 CO2-enriched air was provided. BG-11 medium was replaced and the pH was kept at 10 with NaOH. |
8.9 g L−1 |
90
|
5.2 Integration with industrial waste streams and direct air capture (DAC) systems
A key advantage of microbial CO2 mitigation is its compatibility with industrial waste gases and direct air capture (DAC) systems. Industrial emissions from sectors like cement, steel, and power plants contain high CO2 levels that can be directly used by microbial cultures. For instance, engineered S. elongatus has been used to convert flue gas into bioethanol.91 Integrating such systems with emission treatments can reduce waste and generate valuable products. DAC, although energy-intensive,92 becomes more sustainable and cost-effective when paired with microbial fixation.93 Microalgae like Chlorella vulgaris, Spirulina sp., and Botryococcus braunii have shown carbon fixation rates of 50 g m−2 day−1 using DAC-derived CO2.94 Additionally, a chemoenzymatic system has converted captured CO2 into pyruvate and amino acids (glycine and serine) via the reductive glycine pathway, highlighting the potential of integrating biological CO2 sequestration with both industrial emissions and DAC.95
5.3 CO2 mitigation and biomass conversion
To reduce reliance on fossil resources, lignocellulosic biomass has emerged as a promising renewable carbon source for the sustainable production of chemicals and materials. Microorganisms play a central role in this transition by converting residual biomass and CO2 into fuels and value-added products through natural and engineered pathways. In industrial practice, microbial processes that transform lignocellulose into biogas mirror those naturally occurring in the environment. Heterotrophic bacteria and fungi degrade lignocellulosic and protein-rich residues into biogas (CH4 + CO2), organic acids, and nutrient-rich compost, while methanogens and acetogens re-capture part of the released CO2 to generate additional methane or acetate, thereby enhancing carbon recovery.96,97
Photosynthetic microbes such as cyanobacteria and microalgae further contribute by fixing CO2 into cellular biomass that can be harvested for biofuels, animal feed, or fertilizers. Advances in gene editing and synthetic biology have extended their utility to the sustainable biosynthesis of high-value compounds, including olefins, cinnamaldehyde, and curcumin.98 At the process scale, a 10–20 L bubble column bioreactor using Bacillus cereus SSLMC2 achieved biomass yields of 9.14–10.78 g L−1 and CO2 removal efficiencies of 56–85%. FT-IR and GC-MS analyses identified value-added products such as carboxylic acids, fatty alcohols, and hydrocarbons, while techno-economic assessment demonstrated low-cost operation ($0.167–0.187 per g C treated), underscoring the feasibility of CO2 bio-mitigation strategies.99 Integrating these microbial platforms with biomass valorization and CO2 capture provides a cornerstone for the circular bioeconomy, enabling the conversion of residual biomass and anthropogenic CO2 into renewable energy carriers and bio-based materials. Such integration offers a practical route to reduce net greenhouse gas emissions and advance toward carbon neutrality.
5.4 Challenges and future directions in industrial scalability
Microbial CO2 fixation faces persistent challenges, largely stemming from enzymatic limitations that make biological carbon assimilation slower than chemical catalysis. Low CO2 solubility and dissolution rates further restrict its bioavailability and uptake.77 Natural phototrophs demand high levels of reducing power in the form of NADPH and ATP, and their cultivation requires photobioreactors and tightly controlled environments, resulting in elevated operational costs.100 Engineered heterotrophic strains offer greater pathway flexibility, but their performance often declines over time due to genetic instability and metabolic imbalances. In addition, heterotrophs typically prioritize reduced carbon substrates over CO2, which diminishes fixation efficiency.101 Thermodynamic constraints inherent to pathways such as the WLP and rTCA cycle further complicate the optimization of carbon flux toward biomass or product formation.102
Selecting an effective CO2-fixation route requires weighing several interdependent trade-offs. One central consideration is the choice of host organism. Native autotrophs such as cyanobacteria, acetogens, and hydrogen-oxidizing bacteria provide proven CO2 assimilation pathways and exhibit physiological robustness, whereas synthetic hosts including engineered E. coli or yeast offer broader flexibility for pathway engineering and product diversification, but often demand extensive optimization to achieve stable performance.103 Another key factor concerns the balance between productivity and carbon accounting. Autotrophic processes maximize the fraction of carbon incorporated directly from CO2, strengthening their sustainability profile, yet they generally operate at slower production rates and lower overall efficiency. In comparison, mixotrophic approaches that combine CO2 with energy-rich organic substrates can achieve higher titers and productivities, although this complicates carbon balances and introduces trade-offs in life-cycle assessments.36 Finally, the mode of redox supply defines the operational boundaries of the process. Electrobiological platforms couple microbial metabolism directly to electrodes, either through direct electron uptake or redox mediators, allowing precise control over reducing power delivery. Gas-fed systems, in contrast, provide chemical reductants such as H2 (and in some cases CO or CH4), which can facilitate reactor integration at scale but impose additional challenges associated with gas liquid mass transfer limitations and safety considerations.104 Collectively, these considerations indicate that there is no universal optimum for biological CO2 fixation. Instead, the choice of strategy should be aligned with both the desired product profile and the industrial context (Table 3). For instance, formatotrophic or rGly pathway based E. coli strains may be better suited for flexible chemical production platforms, whereas hydrogenotrophic chassis are more appropriate for high-yield protein or single-cell protein applications.25,105 Biopolymer production relies on polymer-accumulating microbes like C. necator with metabolic flux redirected toward polymer pathways.
Table 3 Comparative overview of natural, synthetic, electrobiological, and cell-free CO2-fixation strategies
| Representative organisms |
Carbon & energy source(s) |
Doubling time |
Typical product yields or titers |
Key strengths |
Key limitations |
Scale maturity |
Ref. |
|
Natural microbial systems
|
|
Clostridium autoethanogenum, Clostridium ljungdahlii |
CO2/CO + H2 or syngas |
∼6–8 h under optimized conditions |
Ethanol titers >40 g L−1 in industrial plants |
Commercially proven gas fermentation, high carbon incorporation, tolerance to CO |
Gas–liquid mass transfer limitations, strict anaerobiosis, limited genetic tools |
Commercial deployment for ethanol (LanzaTech) |
107
|
|
Cupriavidus necator
|
CO2 + H2 + O2 |
∼2–4 h |
Protein yields ∼65–70% of dry weight, SCP productivity up to 20 g L−1 DCW |
High protein content, scalable SCP production, aerobic operation |
Requires H2/O2 mixing, safety hazards, limited product diversity |
Pilot scale demonstration |
108
|
| Cyanobacteria (Synechocystis sp. PCC 6803), microalgae |
CO2 + light |
6–12 h |
PHB up to 20–30% DCW; biomass productivity ∼0.5–1 g L−1 day−1 |
Renewable inputs, long research history, genetic tractability in models |
Light distribution limits, low volumetric productivity, require large reactor footprint |
Long research history, niche applications, no large-scale commodity production |
109
|
|
Synthetic microbial systems
|
| Engineered E. coli with the reductive glycine pathway |
CO2 + formate (electrosynthesized) |
<4.5 h |
3.8 g L−1 mevalonate, demonstration of isoprenol and terpenoids |
Broad metabolic engineering scope, oxygen tolerance, rapid ALE improvements |
Relies on electrochemical formate efficiency, pathway stability, scale not yet proven |
Lab-scale demonstrations |
25 and 110 |
|
Electrobiological systems (MES)
|
|
Sporomusa ovata, acetogenic consortia |
CO2 + electrons from electrodes (direct or mediated) |
Reported >12 h (biofilm-limited) |
Acetate titers 10–20 g L−1 in lab-scale systems |
Direct coupling to renewable electricity, precise redox control, avoid H2 handling |
Low areal productivity, electrode–biofilm interface resistance, high materials cost |
Lab- to bench-scale; early pilot tests |
111
|
|
Cell-free synthetic cycles
|
| CETCH cycle, THETA cycle, self-replenishing modules |
CO2 + NAD(P)H/ATP (regenerated chemically/electrochemically) |
Not applicable (enzyme systems) |
The CETCH cycle achieves CO2 fixation rates up to 5× faster than RubisCO; turnover ∼5 mmol CO2 g−1 enzyme h−1 |
High specific activity, no biomass maintenance, modular design |
Enzyme stability and cost, continuous cofactor regeneration, integration challenges |
Laboratory scale proof-of-concept |
46 and 112 |
Recent advances aim to overcome current barriers and improve industrial feasibility. ALE and continuous culture optimization are used to enhance strain robustness and long-term stability.106 Synthetic biology enables the development of more efficient carboxylases, including engineered RubisCO variants and artificial CO2-fixing enzymes, to accelerate assimilation. Electro-biotechnology is emerging as a promising route that couples microbial metabolism with renewable electricity to drive CO2 conversion. To alleviate solubility constraints, new delivery systems such as membrane-based gas transfer are under development. At process scale, cost-effective reactor designs and integration with carbon capture technologies are essential to repurpose industrial CO2 emissions into fuels, polymers, and biomaterials.
When evaluated through the framework of Green Chemistry, CO2-fixation strategies show distinct alignments with core principles. Table 3 integrates natural, synthetic, electrobiological, and cell-free systems to highlight technological progress and sustainability trade-offs. Gas-fed microbial systems achieve high atom economy but rely on low-carbon H2 or CO inputs and efficient gas transfer to maintain performance. Synthetic formatotrophy enables transparent carbon accounting and flexible pathway design, although its overall efficiency is constrained by the electricity-to-formate conversion step. Electrobiological platforms eliminate the need for molecular reductants and couple directly to renewable electricity, yet they remain limited by technological immaturity and scale. Cell-free cycles offer the prospect of superior atom economy and precise flux control, provided challenges in enzyme stability and cofactor regeneration can be addressed. Phototrophic systems operate entirely on renewable inputs, but their productivity is restricted by light distribution and reactor design. Future work should therefore prioritize comparative benchmarking of carbon yields, energy requirements, and life cycle impacts to ensure that advances in microbial CO2 fixation translate into verifiable environmental benefits consistent with the principles of Green Chemistry.
6. Conclusion
Microbial CO2 fixation has matured from reliance on native autotrophic cycles such as the CBB, reductive TCA, Wood–Ljungdahl, and archaeal HP/HB pathways to embrace engineered enhancements, wholly synthetic routes (e.g., CETCH, formolase, and SACA), electro-microbial hybrids, and non-traditional hosts like acetogens, methanotrophs, methylotrophs, and designer yeasts, forging a versatile toolkit for carbon capture and bioproduction; yet, translating these innovations into robust, industrially viable processes demands overcoming interrelated hurdles, namely, boosting enzyme turnover and thermodynamic favorability to elevate pathway flux, securing balanced ATP and redox cofactor supply through novel co-substrate or chemical strategies, expanding reliable genetic toolboxes and dynamic regulatory circuits for strict anaerobes and extremophiles, mitigating gas liquid mass transfer bottlenecks and genetic instability in high-density bioreactors, integrating predictive multi-omics and reactor modeling (potentially via AI-driven digital twins) to streamline design–build–test cycles, and anchoring development in rigorous techno-economic and life-cycle analyses; only through coordinated advances in enzyme and pathway engineering, systems biology, process intensification, computational modeling, and supportive policy frameworks can we realize scalable, cost-effective, and sustainable CO2 to chemical biorefineries. Looking forward, two research priorities stand out: (i) engineering CO2-fixing enzymes and synthetic pathways with higher catalytic efficiency and (ii) developing integrated reactor platforms that couple advanced control, multi-omics, and techno-economic assessment to ensure scalability. Guided by these directions and supported by advances in systems biology, process intensification, and policy, microbial CO2 fixation can evolve into cost-effective and sustainable CO2-to-chemical biorefineries.
Author contributions
Zeeshan Mustafa: conceptualization and writing – original draft. Naeem Auroona: conceptualization and writing – original draft. Arslan Sarwar: writing – original draft. Eun Yeol Lee: conceptualization, writing – review & editing, supervision, project administration, and funding acquisition.
Conflicts of interest
The authors declare no conflicts of interest.
Data availability
No primary research results, software or code have been included and no new data were generated or analysed as part of this review.
Acknowledgements
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (RS-2024-00466473). This research was supported by the Bio&Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT) (No. RS-2025-02214232).
References
- P. Friedlingstein, M. O'Sullivan, M. W. Jones, R. M. Andrew, J. Hauck, P. Landschützer, C. Le Quéré, H. Li, I. T. Luijkx, A. Olsen, G. P. Peters, W. Peters, J. Pongratz, C. Schwingshackl, S. Sitch, J. G. Canadell, P. Ciais, R. B. Jackson, S. R. Alin, A. Arneth, V. Arora, N. R. Bates, M. Becker, N. Bellouin, C. F. Berghoff, H. C. Bittig, L. Bopp, P. Cadule, K. Campbell, M. A. Chamberlain, N. Chandra, F. Chevallier, L. P. Chini, T. Colligan, J. Decayeux, L. Djeutchouang, X. Dou, C. Duran Rojas, K. Enyo, W. Evans, A. Fay, R. A. Feely, D. J. Ford, A. Foster, T. Gasser, M. Gehlen, T. Gkritzalis, G. Grassi, L. Gregor, N. Gruber, Ö. Gürses, I. Harris, M. Hefner, J. Heinke, G. C. Hurtt, Y. Iida, T. Ilyina, A. R. Jacobson, A. Jain, T. Jarníková, A. Jersild, F. Jiang, Z. Jin, E. Kato, R. F. Keeling, K. Klein Goldewijk, J. Knauer, J. I. Korsbakken, S. K. Lauvset, N. Lefèvre, Z. Liu, J. Liu, L. Ma, S. Maksyutov, G. Marland, N. Mayot, P. McGuire, N. Metzl, N. M. Monacci, E. J. Morgan, S. I. Nakaoka, C. Neill, Y. Niwa, T. Nützel, L. Olivier, T. Ono, P. I. Palmer, D. Pierrot, Z. Qin, L. Resplandy, A. Roobaert, T. M. Rosan, C. Rödenbeck, J. Schwinger, T. L. Smallman, S. Smith, R. Sospedra-Alfonso, T. Steinhoff, Q. Sun, A. J. Sutton, R. Séférian, S. Takao, H. Tatebe, H. Tian, B. Tilbrook, O. Torres, E. Tourigny, H. Tsujino, F. Tubiello, G. van der Werf, R. Wanninkhof, X. Wang, D. Yang, X. Yang, Z. Yu, W. Yuan, X. Yue, S. Zaehle, N. Zeng and J. Zeng, Earth Syst. Sci. Data Discuss., 2024, 2024, 1–133 Search PubMed.
- G. Hayman, Science, 2024, 383, 833–834 CrossRef PubMed.
- A. Kumar, S. Ergas, X. Yuan, A. Sahu, Q. Zhang, J. Dewulf, F. X. Malcata and H. van Langenhove, Trends Biotechnol., 2010, 28, 371–380 CrossRef PubMed.
- K. Zhang, Y. Zhou, T. Song and J. Xie, Energy Fuels, 2021, 35, 15978–15986 CrossRef.
- F. Gong, Z. Cai and Y. Li, Sci. China:Life Sci., 2016, 59, 1106–1114 CrossRef PubMed.
- L. Zhao, Z. Cai, Y. Li and Y. Zhang, Synth. Syst. Biotechnol., 2024, 9, 55–68 CrossRef PubMed.
- J. Lee, H. E. Yu and S. Y. Lee, Curr. Opin. Biotechnol., 2025, 91, 103244 CrossRef.
- C. A. Raines, New Phytol., 2022, 236, 350–356 CrossRef PubMed.
- K. R. Choi, Y.-J. Ahn and S. Y. Lee, J. CO2 Util., 2022, 58, 101929 CrossRef.
- T. Schwander, L. Schada Von Borzyskowski, S. Burgener, N. S. Cortina and T. J. Erb, Science, 2016, 354, 900–904 CrossRef PubMed.
- B. M. Mitic, C. Troyer, L. Lutz, M. Baumschabl, S. Hann and D. Mattanovich, Nat. Commun., 2023, 14, 7754 CrossRef PubMed.
- T. Cai, H. Sun, J. Qiao, L. Zhu, F. Zhang, J. Zhang, Z. Tang, X. Wei, J. Yang, Q. Yuan, W. Wang, X. Yang, H. Chu, Q. Wang, C. You, H. Ma, Y. Sun, Y. Li, C. Li, H. Jiang, Q. Wang and Y. Ma, Science, 2021, 373, 1523–1527 CrossRef PubMed.
- J. B. Siegel, A. L. Smith, S. Poust, A. J. Wargacki, A. Bar-Even, C. Louw, B. W. Shen, C. B. Eiben, H. M. Tran, E. Noor, J. L. Gallaher, J. Bale, Y. Yoshikuni, M. H. Gelb, J. D. Keasling, B. L. Stoddard, M. E. Lidstrom and D. Baker, Proc. Natl. Acad. Sci. U. S. A., 2015, 112, 3704–3709 CrossRef.
- X. Lu, Y. Liu, Y. Yang, S. Wang, Q. Wang, X. Wang, Z. Yan, J. Cheng, C. Liu, X. Yang, H. Luo, S. Yang, J. Gou, L. Ye, L. Lu, Z. Zhang, Y. Guo, Y. Nie, J. Lin, S. Li, C. Tian, T. Cai, B. Zhuo, H. Ma, W. Wang, Y. Ma, Y. Liu, Y. Li and H. Jiang, Nat. Commun., 2019, 10, 1378 CrossRef.
- D. Zhong, Q. Fang, R. Du, Y. Jin, C. Peng, D. Cheng, T. Li, T. Zhao, S. Zhang, Y. Zheng, Q. Zhao, Y. Sun and J. Li, Angew. Chem., Int. Ed., 2025, 64, e202501773 CrossRef.
- K. Li, J. Sun, S. Liu, J. Xu, C. Shen, T. Jiang, Y. Yuan, M. Chuai, Y. Xu, Z. Liu and W. Chen, ChemCatChem, 2025, 17, e202401406 CrossRef.
- E. U. Onoh, I. Stamatelos, A. A. Dubale, J. Pasel and G. A. Tiruye, J. Power Sources, 2025, 633, 236393 CrossRef.
- J. Lim, S. Y. Choi, J. W. Lee, S. Y. Lee and H. Lee, Proc. Natl. Acad. Sci. U. S. A., 2023, 120, e2221438120 CrossRef PubMed.
- H. Li, P. H. Opgenorth, D. G. Wernick, S. Rogers, T.-Y. Wu, W. Higashide, P. Malati, Y.-X. Huo, K. M. Cho and J. C. Liao, Science, 2012, 335, 1596–1596 CrossRef PubMed.
- S. Michailos, S. McCord, V. Sick, G. Stokes and P. Styring, Energy Convers. Manage., 2019, 184, 262–276 CrossRef.
- T. Nimmas, S. Wongsakulphasatch, M. Chanthanumataporn, T. Vacharanukrauh and S. Assabumrungrat, Curr. Opin. Green Sustainable Chem., 2024, 47, 100911 CrossRef.
- E. Rabei and S. A. Onaizi, J. Mater. Sci., 2025, 60, 10590–10631 CrossRef.
- M. Xu, P.-L. Tremblay, R. Ding, J. Xiao, J. Wang, Y. Kang and T. Zhang, Sci. Total Environ., 2021, 753, 142050 CrossRef PubMed.
- Q. Wang, S. Kalathil, C. Pornrungroj, C. D. Sahm and E. Reisner, Nat. Catal., 2022, 5, 633–641 CrossRef CAS.
- B. Dronsella, E. Orsi, H. Schulz-Mirbach, S. Benito-Vaquerizo, S. Yilmaz, T. Glatter, A. Bar-Even, T. J. Erb and N. J. Claassens, Nat. Microbiol., 2025, 10, 646–653 CrossRef CAS.
- M. C. Evans, B. B. Buchanan and D. I. Arnon, Proc. Natl. Acad. Sci. U. S. A., 1966, 55, 928–934 CrossRef CAS.
- L. G. Ljungdhal, Annu. Rev. Microbiol., 1986, 40, 415–450 CrossRef.
- P. M. Shih, L. M. Ward and W. W. Fischer, Proc. Natl. Acad. Sci. U. S. A., 2017, 114, 10749–10754 CrossRef CAS.
- I. A. Berg, D. Kockelkorn, W. Buckel and G. Fuchs, Science, 2007, 318, 1782–1786 CrossRef CAS PubMed.
- H. Huber, M. Gallenberger, U. Jahn, E. Eylert, I. A. Berg, D. Kockelkorn, W. Eisenreich and G. Fuchs, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 7851–7856 CrossRef.
- R. McLean, T. Schwander, C. Diehl, N. S. Cortina, N. Paczia, J. Zarzycki and T. J. Erb, Sci. Adv., 2023, 9, eadh4299 CrossRef.
- A. Satanowski, D. G. Marchal, A. Perret, J.-L. Petit, M. Bouzon, V. Döring, I. Dubois, H. He, E. N. Smith, V. Pellouin, H. M. Petri, V. Rainaldi, M. Nattermann, S. Burgener, N. Paczia, J. Zarzycki, M. Heinemann, A. Bar-Even and T. J. Erb, Nat. Commun., 2025, 16, 3134 CrossRef.
- J.-H. Peng, S.-C. Lo, Y.-N. Yu, Y.-T. Yang, Y.-C. Chen, A.-I. Tsai, D.-Y. Wu, C.-H. Huang, T.-T. Su, C.-C. Huang and E.-P. I. Chiang, J. Biol. Eng., 2025, 19, 20 CrossRef.
- D. Yao, L. Wu, D. Tan, Y. Yu, Q. Jiang, Y. Wu, H. Wang and Y. Liu, Bioresour. Technol., 2024, 408, 131176 CrossRef.
- W. Wang, S. Guo, Q. Hou, C. Zhang, Z. Gao, J. Zhou and Q. Fei, J. Agric. Food Chem., 2024, 72, 24237–24245 CrossRef.
- X. Liu, L. Li, G. Zhao and P. Xiong, Biotechnol. Adv., 2024, 73, 108364 CrossRef PubMed.
- T. Sumi and K. Harada, Commun. Chem., 2021, 4, 149 CrossRef PubMed.
- T. Zhao, Y. Li and Y. Zhang, Green Chem., 2021, 23, 7852–7864 Search PubMed.
- G. Hu, J. Zhou, X. Chen, Y. Qian, C. Gao, L. Guo, P. Xu, W. Chen, J. Chen, Y. Li and L. Liu, Metab. Eng., 2018, 47, 496–504 Search PubMed.
- Y. Wang, T. Sun, X. Gao, M. Shi, L. Wu, L. Chen and W. Zhang, Metab. Eng., 2016, 34, 60–70 Search PubMed.
- W. Tu, J. Xu, I. P. Thompson and W. E. Huang, Nat. Commun., 2023, 14, 8012 CrossRef PubMed.
- L. Castañeda-Losada, D. Adam, N. Paczia, D. Buesen, F. Steffler, V. Sieber, T. J. Erb, M. Richter and N. Plumeré, Angew. Chem., Int. Ed., 2021, 60, 21056–21061 CrossRef PubMed.
- M. Kanno, A. L. Carroll and S. Atsumi, Nat. Commun., 2017, 8, 14724 CrossRef PubMed.
- J. Bang, C. H. Hwang, J. H. Ahn, J. A. Lee and S. Y. Lee, Nat. Microbiol., 2020, 5, 1459–1463 CrossRef PubMed.
- S. Gruber, H. Schwab and P. Heidinger, J. Biotechnol., 2017, 257, 78–86 CrossRef PubMed.
- M. Scheffen, D. G. Marchal, T. Beneyton, S. K. Schuller, M. Klose, C. Diehl, J. Lehmann, P. Pfister, M. Carrillo, H. He, S. Aslan, N. S. Cortina, P. Claus, D. Bollschweiler, J.-C. Baret, J. M. Schuller, J. Zarzycki, A. Bar-Even and T. J. Erb, Nat. Catal., 2021, 4, 105–115 CrossRef.
- R. Subramaniam, Chem. Biochem. Eng. Q., 2019, 32, 451–464 CrossRef.
- K. Malairuang, M. Krajang, J. Sukna, K. Rattanapradit and S. Chamsart, Processes, 2020, 8, 1321 CrossRef.
- S.-I. Tan and I. S. Ng, Green Chem., 2021, 23, 4800–4813 RSC.
- Y. Zheng, J. J. Czajka, C. Daiek, Z. Yang, L. Sun, Y. J. Tang, Y. Liu and W. Liao, Algal Res., 2023, 72, 103103 CrossRef.
- S. Bierbaumer, M. Nattermann, L. Schulz, R. Zschoche, T. J. Erb, C. K. Winkler, M. Tinzl and S. M. Glueck, Chem. Rev., 2023, 123, 5702–5754 CrossRef PubMed.
- N. J. Claassens, I. Sánchez-Andrea, D. Z. Sousa and A. Bar-Even, Curr. Opin. Biotechnol., 2018, 50, 195–205 CrossRef CAS PubMed.
- M. E. Davin, R. A. Thompson, R. J. Giannone, L. W. Mendelson, D. L. Carper, M. Z. Martin, M. E. Martin, N. L. Engle, T. J. Tschaplinski, S. D. Brown and R. L. Hettich, Biotechnol. Biofuels Bioprod., 2024, 17, 119 CrossRef CAS.
- T. Gassler, M. Sauer, B. Gasser, M. Egermeier, C. Troyer, T. Causon, S. Hann, D. Mattanovich and M. G. Steiger, Nat. Biotechnol., 2020, 38, 210–216 CrossRef CAS.
- P. A. Davison, W. Tu, J. Xu, S. Della Valle, I. P. Thompson, C. N. Hunter and W. E. Huang, ACS Synth. Biol., 2022, 11, 3805–3816 CrossRef CAS PubMed.
- C. Xu, Y. Feng, H. Li, S. Jiang, R. Ma, Y. Yao, M. Liu, Y. Yang and Z. Xue, Sci. Total Environ., 2023, 862, 160805 CrossRef CAS.
- E. Orsi, J. M. Hernández-Sancho, M. S. Remeijer, A. J. Kruis, D. C. Volke, N. J. Claassens, C. E. Paul, F. J. Bruggeman, R. A. Weusthuis and P. I. Nikel, Curr. Opin. Biotechnol., 2024, 90, 103195 CrossRef CAS PubMed.
- I. Cengic, I. C. Cañadas, N. P. Minton and E. P. Hudson, ACS Synth. Biol., 2022, 11, 3100–3113 CrossRef CAS PubMed.
- S.-Y. Wang, X. Li, S.-G. Wang and P.-F. Xia, Metab. Eng., 2023, 75, 91–99 CrossRef CAS PubMed.
- S. Della Valle, E. Orsi, S. C. A. Creutzburg, L. F. M. Jansen, E.-N. Pentari, C. L. Beisel, H. Steel, P. I. Nikel, R. H. J. Staals, N. J. Claassens, J. Van Der Oost, W. E. Huang and C. Patinios, Trends Biotechnol., 2025, 43, 1470–1491 CrossRef.
- E. C. Holmes, A. C. Bleem, C. W. Johnson and G. T. Beckham, Metab. Eng., 2024, 86, 262–273 CrossRef.
- S. Kim, Y. J. Jang, G. Gong, S.-M. Lee, Y. Um, K. H. Kim and J. K. Ko, Microb. Cell Fact., 2022, 21, 231 CrossRef.
- M. Jahn, N. Crang, M. Janasch, A. Hober, B. Forsström, K. Kimler, A. Mattausch, Q. Chen, J. Asplund-Samuelsson and E. P. Hudson, eLife, 2021, 10, e69019 CrossRef PubMed.
- S. Roussou, M. Pan, J. O. Krömer and P. Lindblad, Metab. Eng., 2025, 88, 250–260 CrossRef.
- S. Alagesan, N. P. Minton and N. Malys, Metabolomics, 2018, 14, 9 CrossRef.
- U. J. Nwaokorie, K. Reinmets, L. A. De Lima, P. R. Pawar, K. M. Shaikh, A. Harris, M. Köpke and K. Valgepea, Front. Bioeng. Biotechnol., 2023, 11, 1167892 CrossRef.
- H. Richter, B. Molitor, H. Wei, W. Chen, L. Aristilde and L. T. Angenent, Energy Environ. Sci., 2016, 9, 2392–2399 RSC.
- A. Banerjee, C. Leang, T. Ueki, K. P. Nevin and D. R. Lovley, Appl. Environ. Microbiol., 2014, 80, 2410–2416 CrossRef PubMed.
- J. Moon and V. Müller, Environ. Microbiol., 2021, 23, 6953–6964 CrossRef PubMed.
- I. Sánchez-Andrea, I. A. Guedes, B. Hornung, S. Boeren, C. E. Lawson, D. Z. Sousa, A. Bar-Even, N. J. Claassens and A. J. M. Stams, Nat. Commun., 2020, 11, 5090 CrossRef.
- B. A. Diner, J. Fan, M. C. Scotcher, D. H. Wells and G. M. Whited, Appl. Environ. Microbiol., 2018, 84, e01723–17 CrossRef PubMed.
- O. Rasigraf, D. M. Kool, M. S. M. Jetten, J. S. Sinninghe Damsté and K. F. Ettwig, Appl. Environ. Microbiol., 2014, 80, 2451–2460 CrossRef.
- C. A. Henard, C. Wu, W. Xiong, J. M. Henard, B. Davidheiser-Kroll, F. D. Orata and M. T. Guarnieri, Appl. Environ. Microbiol., 2021, 87, e00881–21 CrossRef.
- S. Akash, B. Sivaprakash, N. Rajamohan and D.-V. N. Vo, Environ. Chem. Lett., 2023, 21, 1477–1497 CrossRef.
- H. Löwe, K. Hobmeier, M. Moos, A. Kremling and K. Pflüger-Grau, Biotechnol. Biofuels, 2017, 10, 190 CrossRef PubMed.
- I. S. Al Rowaihi, B. Kick, S. W. Grötzinger, C. Burger, R. Karan, D. Weuster-Botz, J. Eppinger and S. T. Arold, Bioresour. Technol. Rep., 2018, 1, 61–68 CrossRef.
- K.-K. Wu, P.-P. Xu, L. Zhao, N.-Q. Ren and Y.-F. Zhang, npj Mater. Sustain., 2024, 2, 4 CrossRef.
- S. Lee, Y. R. Lee, W.-H. Lee, S. Y. Lee, M. Moon, G. W. Park, K. Min, J. Lee and J.-S. Lee, Bioresour. Technol., 2022, 363, 127955 CrossRef.
- S. Park, B.-R. Park, D. Jeong, J. Park, J. K. Ko, S.-J. Kim, J.-S. Kim, Y.-S. Jin and S. R. Kim, Process Biochem., 2023, 134, 286–293 CrossRef.
- C. David, A. Schmid, L. Adrian, A. Wilde and K. Bühler, Biotechnol. Bioeng., 2018, 115, 300–311 CrossRef PubMed.
- C. Durall, P. Lindberg, J. Yu and P. Lindblad, Biotechnol. Biofuels, 2020, 13, 16 CrossRef PubMed.
- L. González-Resendiz, L. Sánchez-García, I. Hernández-Martínez, G. Vigueras-Ramírez, L. F. Jiménez-García, R. Lara-Martínez and M. Morales-Ibarría, Bioresour. Technol., 2021, 337, 125508 CrossRef.
- Y. Miyahara, C.-T. Wang, M. Ishii-Hyakutake and T. Tsuge, Bioengineering, 2022, 9, 586 CrossRef.
-
A. Tharak, G. Suresh, S. Kaveti, N. Jain and S. V. Mohan, bioRxiv, 2024, preprint, 2024.2012.2021.629878, DOI:10.1101/2024.12.21.629878.
- Y. Jang, Y. J. Lee, G. Gong, S.-M. Lee, Y. Um, K. H. Kim and J. K. Ko, Microb. Cell Fact., 2024, 23, 122 CrossRef.
- Y. Li, S. Wu, H. Chen, W. Xiao, C. Li, Z. Peng, Z. Li, J. Liu, L. Lin and X. Zeng, Bioprocess Biosyst. Eng., 2024, 47, 1017–1026 CrossRef.
- L. Xiao, G. Liu, F. Gong, H. Zhu, Y. Zhang, Z. Cai and Y. Li, ACS Catal., 2022, 12, 799–808 CrossRef.
- F. E. Liew, R. Nogle, T. Abdalla, B. J. Rasor, C. Canter, R. O. Jensen, L. Wang, J. Strutz, P. Chirania, S. De Tissera, A. P. Mueller, Z. Ruan, A. Gao, L. Tran, N. L. Engle, J. C. Bromley, J. Daniell, R. Conrado, T. J. Tschaplinski, R. J. Giannone, R. L. Hettich, A. S. Karim, S. D. Simpson, S. D. Brown, C. Leang, M. C. Jewett and M. Köpke, Nat. Biotechnol., 2022, 40, 335–344 CrossRef PubMed.
- M. Baumschabl, Ö. Ata, B. M. Mitic, L. Lutz, T. Gassler, C. Troyer, S. Hann and D. Mattanovich, Proc. Natl. Acad. Sci. U. S. A., 2022, 119, e2211827119 CrossRef.
- M. J. Lai, J. C. Tsai and E. I. Lan, Bioresour. Technol., 2022, 366, 128131 CrossRef PubMed.
- H.-H. Chou, H.-Y. Su, T.-J. Chow, T.-M. Lee, W.-H. Cheng, J.-S. Chang and H.-J. Chen, Biochem. Eng. J., 2021, 165, 107823 CrossRef.
- S. Kar, D. Kim, A. Bin Mohamad Annuar, B. B. Sarma, M. Stanton, E. Lam, S. Bhattacharjee, S. Karak, H. F. Greer and E. Reisner, Nat. Energy, 2025, 10, 448–459 CrossRef.
- P. L. Reginato, Front. Clim., 2025, 6, 1440833 CrossRef.
- E. Daneshvar, R. J. Wicker, P.-L. Show and A. Bhatnagar, Chem. Eng. J., 2022, 427, 130884 CrossRef.
- J. Liu, H. Zhang, Y. Xu, H. Meng and A.-P. Zeng, Nat. Commun., 2023, 14, 2772 CrossRef.
- D. T. Troiano and M. H. P. Studer, Nat. Commun., 2025, 16, 6712 CrossRef PubMed.
- M. L. A. Jansen, J. M. Bracher, I. Papapetridis, M. D. Verhoeven, H. De Bruijn, P. P. De Waal, A. J. A. Van Maris, P. Klaassen and J. T. Pronk, FEMS Yeast Res., 2017, 17, fox044 CrossRef.
- C. Li, L. Yin, J. Wang, H. Zheng and J. Ni, Nat. Synth., 2023, 2, 960–971 CrossRef.
- R. J. Barla, S. Raghuvanshi and S. Gupta, Sci. Rep., 2024, 14, 6354 CrossRef PubMed.
- Y. K. Dasan, M. K. Lam, Y. H. Chai, J. W. Lim, Y. C. Ho, I. S. Tan, S. Y. Lau, P. L. Show and K. T. Lee, Bioresour. Technol., 2023, 380, 129094 CrossRef PubMed.
- Z. Sun, C. Bo, S. Cao and L. Sun, Mar. Drugs, 2025, 23, 113 CrossRef PubMed.
- A. Taha, M. Patón and J. Rodríguez, mSystems, 2025, 10, e01274–e01224 CrossRef.
- S. Della Valle, W. Tu and W. E. Huang, Curr. Opin. Syst. Biol., 2024, 37, 100489 CrossRef.
- D. Zhang, J. L. Foo and M. W. Chang, Biotechnol. Notes, 2025, 6, 157–163 CrossRef.
- S. Kim, N. Giraldo, V. Rainaldi, F. Machens, F. Collas, A. Kubis, F. Kensy, A. Bar-Even and S. N. Lindner, Front. Bioeng. Biotechnol., 2023, 11, 1091899 CrossRef.
- N. Arora, H.-W. Yen and G. P. Philippidis, Sustainability, 2020, 12, 5125 CrossRef.
- H. Ingelman, K. M. Shaikh and K. Valgepea, Microb. Biotechnol., 2025, 18, e70208 CrossRef CAS PubMed.
- S. C. Angenent, J. H. Schuttinga, M. F. H. Van Efferen, B. Kuizenga, B. Van Bree, R. O. Van Der Krieken, T. J. Verhoeven and R. H. Wijffels, Open Microbiol. J., 2022, 16, e187428582207270 CrossRef CAS.
- G. Penloglou, A. Pavlou and C. Kiparissides, Processes, 2024, 12, 1104 CrossRef CAS.
- A. E. Cowan, M. Hillers, V. Rainaldi, F. Collas, H. Choudhary, B. S. Zakaria, G. G. Bieberach, D. N. Carruthers, M. Grabovac, J. W. Gin, B. Cawthon, Y. Chen, E. A. Turumtay, E. E. K. Baidoo, C. J. Petzold, A. M. Feist, S. Tejedor-Sanz, F. Kensy, B. A. Simmons, J. D. Keasling and N. J. Claassens, Nat. Commun., 2025, 16, 5908 CrossRef PubMed.
- F. Harnisch, J. S. Deutzmann, S. T. Boto and M. A. Rosenbaum, Trends Biotechnol., 2024, 42, 1035–1047 CrossRef PubMed.
- S. Luo, C. Diehl, H. He, Y. Bae, M. Klose, P. Claus, N. S. Cortina, C. A. Fernandez, H. Schulz-Mirbach, R. McLean, A. A. Ramírez Rojas, D. Schindler, N. Paczia and T. J. Erb, Nat. Catal., 2023, 6, 1228–1240 CrossRef.
Footnote |
| † These authors contributed equally to this work. |
|
| This journal is © The Royal Society of Chemistry 2026 |
Click here to see how this site uses Cookies. View our privacy policy here.