Metabolic Engineering

While in vivo synthesis of biologic therapeutics has been broadly successful, it is limited by biological constraints of the cells and by the complexity, time, and cost of implementing the pipeline from discovery through manufacturing. Cell-free expression systems (CFES), which use cellular transcription and translation machinery to express proteins in vitro, offer a promising alternative approach that could improve robustness and modularity in that pipeline. However, current benchmark CFES productivity is well below the theoretical capacity of the input nucleotides and amino acids. Efforts to address this issue are hindered by limited understanding of the extent of enzymatic activity in CFES beyond gene expression, as previous work has shown that metabolic enzymes in cell-free lysates cause substantial background metabolic activity that influences protein expression. Here, we hypothesized that the inflection point of protein expression is a critical timescale for CFES metabolism. We performed metabolomics characterization of CFES reactions, finding significant metabolic changes at the inflection point. Driven by these findings, we sought to identify supplements that could be added to the cell-free reaction to avoid metabolic limitations. We found that amino acid supplementation increased expression productivity and lifetime only when added after the inflection point, and actually hurt expression when added before the inflection point. We found similar supplementation timing impacts for some other metabolites as well. These findings show that endogenous metabolism and supplementation timing are deeply interconnected and are critical considerations in CFES optimization, and that metabolomics-informed fed-batch supplementation is a potentially valuable strategy to improve reaction productivity.

Fed-batch production in Chinese hamster ovary cells is usually optimised empirically, yet the intracellular mechanisms that determine whether cells sustain productivity or enter terminal decline remain poorly resolved. Here, we combine longitudinal proteomics and intracellular metabolomics across differential ambr250 fed-batch processes to define the metabolic programmes associated with CHO cell viability and antibody production. Across media/feed combinations and an intensified seeding regime, culture progression followed a conserved trajectory from proliferation to metabolic transition and terminal stress. The high-stress state was characterised by a switch toward mitochondrial and peroxisomal fatty acid {beta}-oxidation, lipid remodelling, oxidative burden and activation of ferroptosis-associated pathways. Enriched feed conditions delayed this transition through enhanced redox and glutathione-linked defence, but did not proportionally increase antibody titre, revealing a trade-off in which cellular resources are diverted from recombinant protein production toward survival. These data identify fatty acid metabolism and ferroptosis as key constraints on late-stage CHO fed-batch performance and provide a mechanistic framework for rational feed design and host-cell engineering.

Methylglyoxal (MGO) is a metabolic byproduct of sugar metabolism involved in the formation of advanced glycation end products (AGEs) and its accumulation disrupts protein function, redox balance and cellular viability. Yet the metabolic rewiring required to divert MGO overflow and prevent these cytotoxic effects remains largely unknown. To address these gaps, we used flux sampling and flux balance analysis in genome scale metabolic model iJO1366 of E. coli. High glucose increased MGO flux from 0.16 mmol/gDCW/h to 1.87 mmol/gDCW/h in simulation. Large scale in silico screening of metabolic reactions identified that increasing threonine uptake, thereby increasing ethanol flux, reduced glucose induced increase in MGO flux from 1.87 mmol/gDCW/h to 0.405 mmol/gDCW/h. In silico inhibition of ethanol production (NAD+ regeneration) inhibited the MGO lowering potential of threonine. Threonine supplementation actively drives the acetaldehyde to ethanol flux to provide localized NAD+ relief, which subsequently enhances the flux of payoff phase in glycolysis (glyceraldehyde 3-phosphate), thereby efficiently draining the stagnated DHAP pool and shutting down the overflow towards MGO production. Unexpectedly, under reduced oxygen conditions, high glucose caused only a minimal increase in MGO flux, which was not reduced by threonine supplementation. Our study also decoded the mechanistic details behind this paradox. Though this model driven hypothesis requires further validation in vivo, these stoichiometric predictions have applications in metabolic engineering, for commercial MGO production. Furthermore, in vivo studies focused on bacterial stress, gut microbiome imbalances and AGE related diseases might benefit from these simulations

Improving carbon recovery during sugar fermentation remains a major challenge because a substantial fraction of substrate carbon is lost as CO2 during central metabolism. To overcome this limitation, Clostridium sp. JS66 (JS66), an acetogen producing hexanoic acid from glucose, was subjected to adaptive laboratory evolution under CO2/H2 conditions to enhance H2-assisted CO2 reassimilation during glucose fermentation. The evolved strain, ALECO2, exhibited CO2 consumption without a lag phase under autotrophic conditions and reached a 9.5-fold higher CO2 uptake rate than JS66. Under fed-batch conditions, glucose-only fermentation yielded a carbon molar yield (Cmetabolite/Csugar, CM/CS) of 0.60, whereas H2 supplementation increased CM/CS to 0.91 and redirected carbon flux toward C6 products (hexanoic acid and hexanol), which accounted for 49% of total C_output. With additional CO2 supplementation, ALECO2 further assimilated externally supplied CO2, increasing the CM/CS to 1.10 and demonstrating carbon-negative fermentation. Assimilation of externally supplied CO2 further redirected carbon flux toward chain elongation, producing 7.14 g/L hexanoic acid and increasing the C6 carbon fraction to 57% of total C_output. Constraint-based flux analysis supported increased acetyl-CoA formation through the Wood-Ljungdahl pathway and enhanced flux toward reverse {beta}-oxidation under H2- and CO2/H2-supplemented conditions. Genome analysis identified mutations including genes encoding a putative HytB homolog and a LysR-type transcriptional regulator. These results establish ALECO2 as a promising evolved anaerobic non-photosynthetic (ANP) mixotrophy platform that links CO2 reassimilation and external CO2 assimilation with chain elongation, enabling carbon-neutral and carbon-negative production of value-added C6 products from glucose.

Synthetic microbial consortia have the potential to bring novel architectures to biotechnological processes. They enable more flexible and efficient bioprocesses by reducing metabolic burden and supporting division of labour. Obligately mutualistic cross-feeding has been used to stabilise the population composition of artificially assembled consortia. However, many current strategies rely on the cross-feeding of metabolites with limited exchange rates, and this imposes a growth burden on the consortium members. Here, we used adaptive laboratory evolution (ALE) to address this growth bottleneck and create an optimised co-culture chassis to host bioproduction functions. Transcriptome analysis revealed how ALE alleviated stress responses associated with nutritional restrictions in the non-evolved cross-feeding system. Using a case-study split bioproduction pathway, we demonstrated that improvements in the chassis growth performance resulted in production improvements, surpassing the performance of a monoculture implementation by 1.5-fold. Our results show the potential of ALE to optimise the cross-feeding layer of yeast co-cultures, and how this enables the efficient implementation of a bioproduction process.

Synthetic genetic circuits enable microbial differentiation from growth to production, yet metabolic burden, imbalance and toxicity frequently drive strain degeneration. Yeast strains engineered to produce different terpene products exhibited divergent genetic responses to metabolic stresses, but commonly underwent progressive loss of induction of synthetic GAL regulatory circuits, either across the entire population or within subpopulations. Using di- and tri-input biocomputing circuits, the essential glutamine synthetase gene GLN1 was coupled to GAL induction, thereby enabling stabilisation and evolutionary adaptation of the synthetic genetic circuits and stressful heterologous terpene synthetic pathways. The integrated biocomputing and metabolic coupling circuit systems not only prevent strain degeneration but also enable interrogation of non-degenerative evolutionary shifts, providing a platform for metabolic engineering optimisation.

Building high-performance microbial cell factories requires dynamic coordination of resource allocation among cellular growth, target-product biosynthesis, and endogenous host metabolism. However, existing polyploid engineering strategies rely primarily on static manipulation of chromosome copy number. Although increasing gene dosage can enhance biosynthetic capacity, static designs cannot readily accommodate the changing metabolic demands encountered during fermentation. Here, we developed a metabolite-responsive dynamic polyploid engineering strategy that couples chromosome ploidy to the cellular metabolic state. We first constructed a high-performance L-threonine biosensor and used it to sense intracellular L-threonine levels and regulate ftsZ expression, a key cell-division gene, thereby establishing a dynamic polyploid system that requires neither exogenous inducers nor antibiotics. This system enabled engineered cells to progressively transition from polyploid to haploid during fermentation, accompanied by stage-specific remodeling of cellular physiology and metabolism. Physiological characterization revealed a marked increase in cell size and alterations in cell-envelope properties during the polyploid phase, followed by a gradual decrease in chromosome copy number as fermentation progressed. Transcriptomic and metabolomic analyses further demonstrated that dynamic ploidy transitions induced global metabolic network rewiring, remodeling the tricarboxylic acid cycle and amino acid metabolism while redirecting carbon flux toward the biosynthesis of aspartate-family amino acids. Ultimately, dynamic polyploid engineering substantially enhanced L-threonine production, enabling the engineered strain to achieve an L-threonine titer of 183.1 g/L and a yield of 0.67 g/g glucose in 5-L fed-batch fermentation without antibiotics or exogenous inducers. These findings show that dynamic regulation of chromosome ploidy can couple gene-dosage control with remodeling of cellular physiology and metabolic networks, providing a new engineering strategy to overcome the limitations of static polyploid designs and build high-performance microbial cell factories.

Cyanobacterium aponinum UTEX 3222 is a fast-growing marine cyanobacterium that reaches high cell densities, making it an attractive chassis strain for low-cost biomanufacturing. However, past efforts to genetically engineer UTEX 3222 have been unsuccessful. We hypothesized that the complex restriction modification systems in the UTEX 3222 genome constitute a major barrier to genetic transformation. Using a combined methylation avoidance and methylation mimicking approach, we overcame this barrier and successfully transformed UTEX 3222 by natural transformation, generating a large panel of fully segregated axenic strains. Transformation method was also established for a novel shuttle vector that replicates in UTEX 3222. A large-scale promoter screen identified promoters which exhibited strong expression at high cell density. These advances establish the foundation for developing UTEX 3222 as a scalable platform for photosynthetic biomanufacturing.

Electromicrobial production (EMP) technologies aim to combine renewable electricity, CO2, and engineered microbes to make energy-dense molecules at efficiencies exceeding photosynthesis. CO2 can be electrochemically reduced to formate, which is far easier to handle at the bench than H2 or an electrode, but formate carries only two electrons per carbon against the six in a biofuel. The remaining electrons must come from oxidizing additional formate, from H2 oxidation, or from extracellular electron uptake (EEU), and no rigorous comparison of these options coupled to the choice of carbon assimilation pathway currently exists. We calculate upper-limit efficiencies for butanol production by six carbon assimilation pathways, each paired with all three electron delivery mechanisms, using electrochemical parameters drawn from a survey of the recent literature. Electrical to butanol energy conversion efficiencies range from 35.5 to 51.7%, corresponding to solar-to-fuel efficiencies of 11.7 to 17%, so even the least efficient route exceeds the 8% theoretical ceiling of algal photosynthesis. The serine variant of the reductive glycine pathway reaches an electrical energy conversion efficiency of when using H2 oxidation, within 1.9 points of the most efficient pathway, and is the only high-efficiency option that tolerates O2. This makes an EMP system that combines electron delivery by formate coupled with the serine variant of reductive glycine pathway highly attractive, as it presents few barriers to rapid, iterative engineering in the lab, and a high theoretical ceiling. Drawing both carbon and electrons from formate costs 6.2 points against H2 at a state-of-the-art whole-cell voltage (2.2 V). However, this small penalty is amplified three-fold by any rise in the CO2-to-formate cell voltage, and reaches 13.5 points at the highest whole-cell voltages reported for scaled-up CO2-to-formate electrolyzers, where formate-only operation falls to 11.2 electrical-to-fuel and 3.7% solar-to-fuel efficiency, below the ceiling of photosynthesis, against 24.7 and 8.1% for H2 (only just above algal photosynthesis). Our choice between a formate-only system and one coupled to H2 oxidation or EEU therefore depends on our belief about the trajectory of CO2 reduction technology. If whole-cell voltages continue to fall at the rate of the past decade, formate alone is the right target, and the simplicity of its workflow is bought at low cost. However, if that improvement plateaus, the electron delivery mechanism must be swappable, and a system should be designed from the outset so that it can be. At the US Department of Energy SunShot target of 2 cents per kilowatt hour, the electricity to make a US gallon of butanol costs $1.40 for a formate-only system at the state of the art, rising to $5.45 at the highest scaled-up electrolyzer voltage reported, against $1.23 and $2.47 for formate and H2 system.

Multi-stage continuous bioprocessing can increase volumetric productivity, operational consistency, and process throughput, but its design is complicated by coupling among dilution rate, reactor volume, feed allocation, and cellular physiology. Here, we present ContiDesigner, available at https://chemnettools.anc.univie.ac.at/ContiDesigner/, a mechanistic steady-state framework and interactive web tool for the system-level design of continuous fermentation cascades. Comparing one- and two-stage configurations at equal total reactor volume and outlet flow, ContiDesigner reveals how internal flow and reactor volume allocation shape space-time yield and identifies productivity-maximizing operating conditions. Compared with one-stage processes, two-stage cascades favor lower over-all dilution rates, thereby preserving residence time in the production stage. The first-stage dilution rate approaches the corresponding one-stage productivity optimum, but the cascade optimum occurs earlier, reflecting a system-level compromise between biomass generation and production-stage residence time. However, two-stage operation outperforms optimized one-stage operation only when non-growth-associated production in the second stage is sufficiently strong, whereas increasing growth coupling favors one-stage operation. Two case studies demonstrate both the potential and limits of process intensification. An optimized two-stage design is predicted to achieve a more than 1.5 fold increase in space-time yield for poly-R-3-hydroxybutyrate (PHB) production compared with a published experimental five-stage cascade, whereas the lactic acid case study identifies conditions under which staging offers no advantage. ContiDesigner translates these design principles into an accessible workflow to explore feasible operating regions and prioritize cascade designs for experimental evaluation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/743657v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@ef58faorg.highwire.dtl.DTLVardef@1ba88a4org.highwire.dtl.DTLVardef@160edd3org.highwire.dtl.DTLVardef@9dda34_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIContiDesigner enables system-level design of continuous fermentation cascades C_LIO_LIHigh stage-one dilution supports biomass generation C_LIO_LILow stage-two dilution preserves productive residence time C_LIO_LIYet two-stage cascades favor lower overall dilution than one-stage systems C_LIO_LITwo-stage advantage requires strong non-growth-associated production in stage two C_LI

Biomanufacturing offers sustainable alternatives to chemical synthesis under lower temperatures and pressures than traditional catalytic methods. However, the slow pace and iterative engineering bottlenecks of cell strain development restrict the feasible biological design space. Cell-free systems circumvent these constraints, providing a flexible and high-throughput screening approach to accelerate pathway prototyping and enzyme optimization but are not typically used for manufacturing scale-up. To understand the scalability of cell-free biosynthesis, we establish an end-to-end fully cell-free architecture to discover, develop, and scale the biosynthesis of 1,2,4-butanetriol (BT), a high-value industrial platform chemical. First, we systematically screened ~150 enzymes across the 4-step pathway from xylose to BT to identify highly active homologs for each reaction. Next, we applied statistical Design of Experiments to optimize reaction formulations for cost and titer. Finally, the maximum-titer and minimum-cost formulations were scaled up across five orders of magnitude, from 10-{micro}L to 1-L reactions. This resulted in peak volumetric productivities of ~1 g/L/h and yields over 13 g of BT in a single 1-L reaction, with raw substrate costs totaling just $3.00 per liter. This work expands the diversity of enzymes tested for BT synthesis and establishes a blueprint for advancing industrial biochemical manufacturing fully in vitro.

The trend towards concentrated animal feeding operations (CAFOs) has served to concentrate not only livestock animals but the waste they produce to comparatively smaller areas. The point-source nature of this waste is an opportunity for the recovery and valorization of the nitrogen therein. Such a process would be viable on small to intermediate scales and require minimal inputs at the CAFO. In this study, we demonstrate the potential of the biopolymer cyanophycin to serve as a medium for manure-nitrogen recovery. In the first step, genetically modified strains of Escherichia coli produce intracellular cyanophycin from mock manure hydrolysates. Next, cyanophycin is recovered from microbial biomass via acid solubilization and base precipitation using electrochemically generated acids and bases. Finally, to improve both the yield and recoverable fraction of cyanophycin produced, we leverage the tunability of our genetically engineered system to probe the impacts of cyanophycin synthetase solubility, N-domain activity, and cyanophycin molecular weight on cyanophycin recoverability. Collectively, this work serves as a proof of concept for nitrogen recovery from agricultural waste, aligning with global sustainability initiatives.

Acetate is an attractive renewable two-carbon substrate for microbial biotechnology, but its toxicity limits growth and carbon-use efficiency at process-relevant concentrations. Here, we used adaptive laboratory evolution to improve acetate tolerance in a genome-reduced strain of Pseudomonas putida and combined whole-genome sequencing, reverse engineering, transcriptomics, proteomics, and 13C-acetate fluxomics to resolve the underlying adaptation mechanisms. Evolution under increasing acetate concentrations selected recurrent mutations in gacA and fabB, which encode a global response regulator and a fatty acid biosynthesis enzyme, respectively. Reverse engineering of these mutations recovered most of the evolved phenotype, including shorter lag phase and substantially higher biomass yield from acetate. Multi-omic analyses showed repression of type VI secretion systems, carbohydrate storage functions, fatty acid metabolism, and oxidative stress-associated proteins, indicating resource reallocation away from costly stress and non-essential programs. Fluxomics further revealed reduced EDEMP cycling and increased glyoxylate shunt flux, consistent with improved acetate-carbon retention in biomass. These results establish acetate tolerance in P. putida as a resource-efficiency phenotype and identify gacA and fabB as actionable targets for acetate-based bioproduction.

Optimizing microbial biomanufacturing is required if renewable and waste carbon are to replace petrochemical routes at competitive titers, rates, and yields. Growth-coupled (GC) production supports that goal by linking target synthesis to biomass formation, so product formation is required for growth. Constructing knockout strains yielding GC production from a list of candidate genes is labor and time demanding. This results in few in vivo tested designs, which hampers standard machine-learning methods to learn GC patterns for specific bioprocesses. We therefore developed ML4SD, an active-learning Design-Build-Test-Learn (DBTL) cycle that trains ensembles on genome-scale metabolic model (GEM) scores of knockout designs, sampling the next designs from predicted model performance and error. That cycle generalizes only if the initial library is large and diverse, including suboptimal and non-viable designs; libraries restricted to minimal designs or Pareto-optimal knockouts were found to generate models overfitting. To meet those specific demands a novel strain design algorithm, gcSwarms, was developed and tested for a diverse set of bioprocesses within Pseudomonas putida iJN1462. ML4SD was tested with an in silico case study converting lignin-derived 4-hydroxybenzoate to 6-caprolactam, the nylon-6 monomer. ML4SD results showed improvements of up to 164% on carbon yield, recovering a shared SHAP motif that redirects TCA flux through acetyl-CoA. Importantly it reaches that result using 2.5- to 7.1-fold fewer designs than a gcSwarms-only search, demonstrating the data efficiency of this method.

Glucoamylase is essential for industrial starch saccharification, but the limited thermostability and near-neutral pH tolerance of fungal glucoamylases necessitate cooling and acidification of liquefied starch. Here, we developed an artificial intelligence-guided strategy to simultaneously improve the thermostability, pH tolerance, and catalytic activity of glucoamylase from Penicillium oxalicum (PoGA). Two property-specific machine-learning models, CASPE-T and CASPE-A, identified substitutions associated with thermostability and pH tolerance, respectively. Experimental screening identified beneficial substitutions in 11 of 21 CASPE-T and 12 of 22 CASPE-A candidates. Folding-energy-guided recombination integrated the two traits while maintaining structural compatibility. The optimal variant, PoGA T513E/Q305N, exhibited 2.21-fold higher specific activity than the wild type, with half-life extended from 22.3 to 57.9 min at 60 degrees C and from 16.6 to 64.7 min at pH 8.0. Molecular dynamics simulations attributed these improvements to reinforcement of high-occupancy hydrogen-bonding networks, suppression of conformational fluctuations in the linker and carbohydrate-binding module, enhanced long-range dynamic coordination, and preservation of a compact catalytic architecture. At 60 degrees C and pH 6.5 without acidification, PoGA T513E/Q305N produced 219.9 g/L glucose and achieved 89.1% starch conversion, 31.4% higher than the wild type. This work provides an efficient framework for multi-objective enzyme engineering and sustainable starch biorefining.

Chinese hamster ovary (CHO) cells are the dominant platform for recombinant biotherapeutics, yet the impact of producer cell line selection on mammalian cell metabolism remains poorly understood. Here, we performed 41 independent 13C-tracer experiments using uniformly labeled glucose or individual amino acids to comprehensively map carbon utilization in the two principal CHO production platforms: methotrexate-selected CHO-K1 and glutamine synthetase-selected CHO-GS cells. Time-resolved GC-MS analysis revealed distinct metabolic phenotypes spanning central carbon metabolism, amino acid interconversion, lipid biosynthesis, and one-carbon metabolism. CHO-K1 cells exhibited extensive reductive carboxylation and pyruvate carboxylase-mediated anaplerosis, whereas CHO-GS cells redirected glutamate toward glutamine synthesis and relied on asparagine and aspartate to support TCA cycle activity. Isotopomer analysis uncovered substantial intracellular-extracellular cycling of alanine, glycine, glutamate, and serine despite contrasting uptake profiles and quantified differential amino acid contributions to fatty acids and cholesterol. Serine, glycine, and methionine labeling revealed active folate-cycle interconversion in CHO-K1 and enhanced methionine-cycle activity in CHO-GS. Aspartate is identified as a key redox exchange factor and uniquely informative tracer for pathway characterization following glutamine depletion. Together, this exhaustive isotope-tracing framework establishes how producer cell line selection rewires mammalian metabolism and provides a foundation for cell engineering, media optimization, metabolic modeling, and next-generation biomanufacturing.

The tricarboxylic acid (TCA) cycle is central to cellular metabolism, yet its disruption offers an attractive opportunity to redirect carbon toward biotechnological products. A key challenge is that severe TCA cycle interruption often results in auxotrophic phenotypes, limiting their practical application. Here, we used adaptive laboratory evolution to restore growth of the strictly aerobic bacterium Acinetobacter baylyi ADP1 following major disruption of the TCA cycle during growth on glucose minimal medium. Evolved strains recovered rapid growth through extensive reorganization of central metabolism, including reduced flux through the oxidative branch of the TCA cycle, enhanced anaplerotic cycling, increased acetate overflow, and remodeling of oxidative phosphorylation. Adaptation involved coordinated changes in quinone-linked electron transport and intracellular redox balancing, enabling continued growth despite reduced respiratory efficiency. These results demonstrate that adaptive evolution can overcome fundamental physiological constraints imposed by TCA cycle disruption and establish a framework for engineering carbon-partitioning phenotypes in aerobic production hosts.

Mesoplasma florum is a fast-growing, near-minimal bacterium and an emerging model for systems and synthetic biology. However, its dependence on complex serum-containing media limits experimental control and complicates the interpretation of cellular phenotypes. Here, we developed CMRL-AT, a serum-free, quasi-defined medium that supports rapid growth comparable to the commonly used ATCC 1161 medium. Despite supporting similar biomass, CMRL-AT profoundly reshaped the M. florum transcriptome, with approximately one-third of the annotated protein-encoding genes being differentially expressed relative to ATCC 1161. These changes revealed distinct physiological programs associated with rapid growth in complex medium and higher nutrient acquisition in CMRL-AT, illustrating how medium composition alters the functional priorities of a near-minimal cell. Transcriptome profiling across six energy sources further uncovered distinct sugar-responsive expression programs. Combining these responses with transcription-unit organization, protein-domain predictions, and metabolic context resolved fructose- and sucrose-responsive modules, and allowed the assignment of previously ambiguous phosphotransferase system components to specific sugar-utilization pathways. CMRL-AT provides an experimental framework to help resolving gene functions, refining metabolic models, and designing reduced genomes adapted to defined environments.

mRNA therapeutics have demonstrated transformative potential in infectious disease, oncology and genetic disorders. Parallel to the rapid clinical advancement of mRNA therapies, research into in vitro transcription (IVT), the pivotal process of mRNA manufacturing, has intensified significantly. However, the majority of these studies omitted cap analog, an essential substrate for co-transcriptional capped IVT (co-IVT), likely to simplify experimental systems. Nevertheless, co-IVT remains the dominant industrial standard for the production of mRNA therapeutics. Here, we report an optimized co-IVT process that achieves a yield of more than 26 g/L while maintaining capping efficiency of over 99.5%, and achieving a 30-fold reduction in double-stranded RNA (dsRNA), the most critical process-related impurity. These performance gains substantially improve mRNA production efficiency and enhance mRNA quality, thereby accelerating the transition to commercial-scale manufacturing of mRNA therapeutics. Moreover, the performance was attained using either of two mechanistically distinct engineered T7 RNA polymerase (RNAP) mutants. Both mutants enabled robust mRNA synthesis under process conditions that have not been previously reported. These observations provide mechanistic insights into IVT and advance our fundamental understanding of this critical bio-manufacturing step.

Methyl 12-aminododecanoate (ADAME) is a key precursor for Nylon 12 synthesis and an attractive target for sustainable microbial production. However, efficient biosynthesis of ADAME requires the coordinated oxidation and transamination of methyl dodecanoate (DAME), and identifying compatible enzymes for this multistep pathway remains challenging. In this study, we applied a machine learning-based bioinformatic screening approach to identify alternative enzymes for DAME-to-ADAME bioconversion. Among 18 selected distantly related AlkB homologs, AlkBGp01 from Alcanivorax sp. P2S70 showed activity toward DAME, producing 12-hydroxydodecanoic acid methyl ester (HDAME) and 12-oxododecanoic acid methyl ester (ODAME) despite low sequence identity to Pseudomonas putida AlkB. Further screening identified compatible redox partners, AlkG60 from the same species as AlkBGp01 and AlkTp04, whose combination with AlkBGp01 resulted in almost sixfold higher ODAME production than that achieved with P. putida AlkBFGJLT. ODAME production was further increased by more than threefold by conjugating these three newly identified proteins. The optimized single-plasmid system comprising conjugated AlkBGp01, AlkG60, and AlkTp04, together with AlaD and newly identified omega-transaminases EAV41574 produced 0.28 mM gDCW-1 ADAME, representing a 5.6-fold improvement over the previously reported P. putida AlkBFGJLT-based system with AlaD-CV2025. These results demonstrate that machine learning-guided enzyme discovery can identify functional distantly related homologs and compatible enzyme combinations for constructing efficient synthetic pathways. This study also highlights the importance of optimizing pathway architecture, including enzyme conjugation and plasmid configuration, for improving microbial production of bio-based monomer precursors.