Metabolic Engineering

13C-metabolic flux analysis (13C-MFA) is a crucial technique that experimentally determines metabolic flux distribution. Although precision of each flux strongly depends on tracer labeling pattern, its optimization remains challenging. We developed an integrated platform, OpenMebius2, a graphical user interface (GUI)-based software for 13C-MFA that includes a tracer labeling pattern suggestion function to support subsequent experiments. The proposed function leverages metabolic flux distributions and their 95 % confidence intervals obtained using low-cost 13C-labeled substrates to evaluate hypothetical parallel labeling scenarios and predict improvements in flux estimation precision. Availability and implementationThis software runs on Linux, macOS, and Windows. The source code and binary files are available at https://github.com/metabolic-engineering/OpenMebius2 under the PolyForm Noncommercial License 1.0.0.

Photosynthetic cyanobacteria are promising platforms for sustainable chemical production, as they can convert light and CO2 into valuable compounds. Achieving this often requires engineering cyanobacteria with non-native enzymes with strong promoters to maximize enzyme accumulation. However, despite extensive engineering efforts, the extent to which heterologous proteins misfold and undergo degradation in cyanobacteria remains unknown. Here, we systematically investigate the fate of recombinant proteins in Synechocystis sp. PCC 6803 by quantifying metabolic enzyme degradation. To do this, we developed a quantitative approach that combines split-GFP protein reporting with inducible CRISPRi knockdown of Clp protease system, enabling detection of proteins that would otherwise be degraded. Applying this method to 103 heterologous proteins previously used in cyanobacterial metabolic engineering studies, we find that nearly half undergo significant degradation, with some losing over 95% of their potential expression. Furthermore, we demonstrate that replacing enzymes with homologs is often a more effective strategy to address expression issues than optimizing genetic elements. These findings provide the first quantitative overview of heterologous protein expression in cyanobacteria and identify enzymes that are poorly expressed and suboptimal for their respective pathways, information usable to increase production titers in photosynthetic cell factories.

Budding yeast Saccharomyces cerevisiae is a workhorse chassis for producing added food and agricultural compounds. However, building multi-enzymatic pathways for these chemicals often requires iterative genomic integration, underscoring the need for efficient, rapid genome-editing tools that can reliably target transcriptionally active chromosomal regions. In this study, to accelerate strain construction, we established a genome-editing toolkit to rapidly engineer eight loci, highly expressed hot-spots, but nonessential genomic sites suitable for stable pathway assembly. Our approach integrates three key design features: (i) selectable markers to enable rapid screening of edited cells, (ii) extended homology arms that leverage the yeast homology-directed repair machinery for robust genomic integration, and (iii) co-delivery of Cas9 and guide RNAs to promote efficient double-stranded DNA breaks at specific integration sites. The sequence independence of FASTOP relies on the release of integration cassettes from integrative vectors, mediated by restriction digestion at two flanking multiple-cutting sites in the integration module to minimize the risk of introducing sequence errors during PCR amplification of the integration cassettes. Following the introduction of a fluorescent reporter cassette, we observed high integration efficiencies across the target sites. We then integrated the biosynthetic pathway of plant-derived flavonoid naringenin into the hot-spots of the yeast genome using the FASTOP toolkit. Our results demonstrated that upon expressing the five essential genes in simple shake flask culture, naringenin production reached 505.7 mg/L, representing a significant (69-fold) increase over previously reported titers for comparable minimal heterologous pathways in S. cerevisiae. Together, the FATSOP toolkit provides a user-friendly platform for reliably modifying hot-spot loci to rapidly construct multi-enzymatic metabolic pathways in S. cerevisiae, while achieving high production levels for high-value food-relevant metabolites.

Lignin-derived aromatics are abundant in depolymerized lignin but remain remain untilized as carbon sources for commercial production of bulk chemicals. Among these aromatics, p-coumaric acid can be funnelled through the {beta}-ketoadipate pathway toward cis,cis-muconic acid (ccMA), a precursor of bio-based adipic and terephthalic acids. However, efficient ccMA production by Acinetobacter baylyi ADP1 is constrained by toxicity of catechol (the immediate precursor of ccMA), inefficient channelling of protocatechuate (PCA) metabolism towards ccMA production, and absence of PCA decarboxylase for converting PCA to catechol. Therefore, in this study, we engineered a modular co-culture system, combining engineered strains of A. baylyi and E. coli, for ccMA production from synthetic p-coumaric acid. Deletion of catB and catC genes and overexpression of catA in A. baylyi GJS_catA strain enabled near-stoichiometric conversion of catechol to ccMA ([~]90% carbon yield) with titres up to 56.4 mM ([~] 8 g/L) under controlled fed-batch feeding. The strain was further engineered (A. baylyi GJS2_catA) to convert p-coumaric acid to PCA. Due to the inactivity of heterologous PCA decarboxylase (aroY gene) in A. baylyi, this gene was incorporated in E. coli where it exhibited activity through PCA to catechol conversion. Upon its production by E.coli_aroY in the co-culture, catechol is instantaneously converted to ccMA by A. baylyi GJS2_catA strain. In a two-step process, 22 mM p-coumaric acid was initially converted to 20.6 mM PCA (A. baylyi GJS2_catA), which was further converted to catechol (E.coli_aroY) and finally to 18.55 mM ccMA (2.63 g L-{superscript 1}) by A. baylyi GJS2_catA. This process was validated by the valorization of lignin-derived p-coumaric acid to ccMA. While the modular strategy developed in this study substantially improves ccMA titres, it also highlights the bottlenecks in A. baylyi metabolic pathway engineering for lignin valorization. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/709578v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@a83daborg.highwire.dtl.DTLVardef@168c6b6org.highwire.dtl.DTLVardef@1ce0abdorg.highwire.dtl.DTLVardef@23200b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Malic acid is a C4 dicarboxylic acid traditionally produced from petroleum and widely used in the food industry. As a sustainable alternative, it can also be produced as a value-added platform chemical from biomass. Previously, the Escherichia coli strain XZ658 was engineered to produce L-malate via the carbon-fixation reductive branch of the TCA cycle. In this study, we further improved this system by relieving allosteric regulation of citrate synthase, addressing redox imbalance, and enhancing malate export. These modifications approximately doubled the L-malate titer in the final strain MO128 compared to XZ658 under simple batch fermentation conditions. The process achieved a high mass yield of 1.2 g malate g-{superscript 1} glucose, highlighting the carbon-fixation capacity of the reductive TCA pathway for fermentative malate production.

In this study, we employ a two-stage dynamic metabolic control strategy to enhance the NADPH dependent biosynthesis of ethylene glycol from xylose in engineered E. coli. We evaluated the use of metabolic valves to dynamically reduce the enzymes involved in competitive pathways which compete for substrates with ethylene glycol biosynthesis, as well as regulatory pathways aimed at increasing NADPH fluxes. The performance of our initial strains with limits in pathway expression levels was improved by the addition of competitive valves, but not by increases in NADPH flux. In contrast, improving pathway expression levels, led to strains improved significantly by our regulatory valves which improved NADPH flux, but not by the competitive valves. This is consistent with a central hypothesis that faster pathways in and of themselves can compete with other metabolic fluxes by being faster and are better aided by regulatory changes capable of change rates elsewhere in metabolism. In this case in NADPH flux. Lastly, upon scale up to fed-batch bioreactors, our optimized strain, featuring dynamic control of two regulatory valves produced 140 g/L of EG in 70 hours at 92% of the theoretical yield.

The optimization and control of bioprocesses require robust in silico models that can accurately capture the complex and dynamic behavior of living cells. While hybrid models that combine machine learning with mechanistic equations have emerged as a powerful tools, they often require relatively large datasets and might yield inconsistent predictions that violate the stoichiometry of metabolism. In this study, we introduce FBA-Hyb, a multi-scale hybrid modeling framework that tightly integrates genome-scale metabolic networks via flux balance analysis (FBA) into its architecture. In our FBA-Hyb framework, artificial neural networks predict key FBA inputs (substrate uptake rates and cellular objectives) while a surrogate FBA module translates them into the metabolic fluxes that govern the bioprocess. A key novelty is that the FBA optimization step is replaced by a surrogate generated with symbolic regression, which encapsulates the FBA model into a compact analytical expression. This allows easy backpropagation through the integration of the neural controlled differential equationbased FBA-Hyb bioprocess model. We validated FBA-Hyb against a standard hybrid model (Std-Hyb) using two Escherichia coli fedbatch case studies. In the first study, FBA-Hyb achieved a 42 % average improvement in predictive accuracy (R2) during a leave-one-process-out cross validation. Crucially, FBA-Hyb maintains strict stoichiometric feasibility even during extrapolation. Meanwhile, an alternative approach based on standard architectures leads to stoichiometrically inconsistent solutions in 22 % of the cases analyzed. In the second case study, we demonstrate how FBA-Hyb effectively simulates unmeasured chemical species and discovers a metabolic shift in sulfate-limited regimes during bioprocessing. By providing a modular, biologically consistent, and computationally efficient architecture, FBA-Hyb offers a robust foundation for the next generation of bioprocess models and sustainable process optimization. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/720062v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@16f011eorg.highwire.dtl.DTLVardef@b25b5borg.highwire.dtl.DTLVardef@18bd178org.highwire.dtl.DTLVardef@65274e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIFBA-Hyb integrates flux balance analysis (FBA) into hybrid bioprocess models. C_LIO_LISymbolic regression discovers a simple closed-form FBA surrogate model. C_LIO_LIThe FBA surrogate ensures accurate reaction stoichiometry. C_LIO_LIA neural network predicting the FBA objective keeps the model flexible. C_LIO_LIFBA-Hyb has superior capabilities and accuracy compared to the current standard. C_LI

Non-model bacteria offer unique metabolic capabilities for sustainable bioproduction, yet their limited genetic accessibility hinders systematic strain development. Here we present conjugation-based serine recombinase-assisted genome engineering (cSAGE), a broad-host-range platform that enables predictable, iterative genomic integration in transformation-resistant bacteria. cSAGE combines conjugative DNA delivery, standardized low-copy vectors, orthogonal recombinases, and modular genetic parts to support rapid pathway assembly and cross-host benchmarking. Using purple nonsulfur bacteria as a testbed, we integrate promoter engineering, multi-payload genome modification, and genome-scale metabolic modeling to empirically evaluate host-dependent pathway performance. Applying this workflow, we identify strain-specific differences in photosynthetic conversion of lignin-derived p-coumarate to the thermoplastic precursor p-vinylphenol. By enabling genome engineering and functional comparison across diverse bacteria using a single plasmid system, cSAGE provides a general framework for non-model strain prototyping and biotransformation discovery.

The fast-growing cyanobacterium Synechococcus sp. PCC 11901 is emerging as a promising chassis for photosynthetic biomanufacturing. Here we report recombinant protein production in PCC 11901 via signal peptide-mediated secretion, enabling direct recovery of target proteins from the culture medium without cell disruption. Seven signal peptides spanning both Sec and Tat pathways are screened using eYFP as a reporter, with secretion quantified daily over seven days by fluorescence measurements. FutA, belonging to the Tat pathway from Synechocystis sp. PCC 6803, achieves 92.2% extracellular export by day 7, substantially outperforming all Sec candidates, including the best Sec signal peptide thermitase from Cyanobacterium aponinum PCC 10605 (55.7%). Signal peptide-bearing strains exhibit growth reductions of up to 26% relative to the wild-type, with FutA most affected, indicating a general metabolic cost correlated with secretion efficiency. The best-performing signal peptides from both pathways, FutA and thermitase, are validated with secretion of lichenase. Notably, the rank order of signal peptide performance is reversed for lichenase: thermitase demonstrates 2.6-fold higher extracellular activity than FutA, indicating that optimal signal peptide selection is cargo-dependent. These results establish PCC 11901 as a secretion-competent chassis and provide a rational framework for matching signal peptide pathways to target protein properties.

Despite its industrial importance, microbial L-lysine production has largely been confined to classical producer strains, leaving the fast-growing, non-pathogenic marine microorganism V. natriegens largely untapped as an unconventional biosynthetic platform. In this work, we established an L-lysine-overproducing V. natriegens DSM759 strain through a step-wise, systematic rational engineering strategy targeting the native biosynthetic pathway. Guided by our prior systems-level analysis of the strains genetic and regulatory architecture, we identified key metabolic bottlenecks and implemented knowledge-driven interventions to relieve pathway constraints. Central to production was alleviation of feedback inhibition in the native key regulatory enzymes, aspartate kinase (AK, lysC) and dihydrodipicolinate synthase (DHDPS, dapA). Site-directed amino-acid substitutions, replicating established E. coli feedback-resistance mechanisms, were introduced into conserved regions of the V. natriegens DSM759 enzymes, producing L-lysine-insensitive variants with kinetic parameters comparable to that of corresponding wild type enzymes. Among the tested configurations, the strain co-expressing Vn.lysC2 and Vn.dapA1:E84T reached the highest L-lysine titer (9.0{+/-}0.6 mM) and yield (0.11{+/-}0.01 molLys molGlc-1), whereas overexpression of additional L-lysine pathway genes provided no further benefit. Leveraging the hosts metabolic versatility, L-lysine synthesis was also demonstrated from the chitin-derived amino-sugar N-acetylglucosamine (0.09{+/-}0.00 molLys molGlcNAc-1), highlighting the potential to valorize chitin-rich waste streams from the seafood industry. This work establishes a minimal, rational strategy for L-lysine biosynthesis in V. natriegens DSM759 and positions it as a promising platform for sustainable amino acid production.

Cyanobacterial natural products are a rich source of bioactive compounds, yet their heterologous production remains challenging. This study investigates the feasibility of expressing the lyngbyatoxin A (LTXA) biosynthetic gene cluster in a fungal host. The lyngbyatoxin biosynthetic genes (ltxA, ltxB, ltxC) were individually cloned and expressed in Aspergillus oryzae NSAR1 under the control of an inducible promoter. Metabolite production was assessed using LC- MS, and transcriptional analysis was performed by RT-PCR. Codon-optimized constructs and precursor feeding experiments were employed to evaluate pathway functionality. No production of LTXA or pathway intermediates was detected upon co-expression of ltxA-C despite confirmed transcription of ltxB and ltxC. RT-PCR analysis revealed truncation of the ltxA transcript, suggesting incompatibility with fungal transcriptional or splicing machinery. In contrast, expression of a codon-optimized ltxC enabled biotransformation of indolactam V to LTXA in A. oryzae, confirming functional expression of the prenyltransferase. These results highlight transcriptional limitations as a key barrier to heterologous expression of cyanobacterial NRPS pathways in fungal hosts, while demonstrating that downstream tailoring enzymes can remain functional. This work provides insights for future engineering of fungal platforms for cyanobacterial natural product biosynthesis.

Improving the reconstituted translation system is a key requirement for bottom-up synthetic biology. Here, we developed a two-step in vitro evolutionary method that can be used for improving translational proteins. In this method, two distinct conditions were sequentially applied while maintaining genotype-phenotype linkage in water-in-oil droplets. Using this method, we performed in vitro evolution of four translation factors, IleRS, PheRS, EF-G, and EF-Tu, and identified mutations that modestly enhanced translation activity in in vitro expression assays. One of the EF-G mutations (P610S) increased activity per protein approximately 2-fold for the recombinant protein purified from E. coli. This selection method is useful for improving translational proteins for bottom-up synthetic biology.

Human N-glycoproteins constitute a market worth hundreds of billions of dollars. However, their production in yeast is often limited by misfolding and subsequent degradation, largely due to differences in N-glycan-dependent protein quality control (QC) systems between humans and yeast. Notably, yeast lacks the UGGT-mediated reglucosylation-refolding cycle that rescues misfolded glycoproteins, and its degradation pathway involves fewer rate-limiting steps. To address this, we engineer the glycoprotein QC system in Kluyveromyces marxianus, a promising host for protein production, by introducing key human components and modifying native pathways. Expression of human UGGT1 or UGGT2 enhances the soluble and secretory production of glycoproteins in an activity-dependent manner. This effect is further improved by co-expression of the UGGT cochaperone SEP15 and by reducing native glucosidase II trimming activity. In addition, introduction of human EDEM2, a rate-limiting enzyme in glycoprotein degradation, delays ER-associated degradation and increases secretion. Integration of these engineering strategies substantially enhances the production of several high-value human-derived glycoprotein therapeutics, including etanercept, dulaglutide, and abatacept, with up to a [~]12-fold increase. These findings demonstrate that engineering a human-like glycoprotein QC network in yeast is an effective strategy to improve glycoprotein folding and secretion.

Adaptive laboratory evolution is used to improve the phenotypes of microorganisms and to characterise the mechanisms underlying resistance against complex growth inhibition. Here we focused on lactic acid bacteria (LAB) as starter cultures for food fermentations. Production of LAB starter cultures is challenging due to growth inhibition by organic acids, mainly lactate, produced during fermentation. By utilising stressostat cultivation we generated Lactococcus lactis isolates with enhanced lactate resistance. Using a combination of (meta)genomics, proteomics and pH-controlled batch fermentations, we deciphered the lactate resistance mechanisms of these L. lactis isolates. Proteome responses of L. lactis, combined with similar growth inhibition at high salt, suggest that high lactate mainly causes osmotic stress. We identified RNA polymerase (RNAP) mutations in subunits {beta} (rpoB) and {beta} (rpoC) as key mutations, causing pleiotropic effects in the proteome. These proteome adaptations are linked to enhanced lactate resistance, particularly the resistance to hyperosmotic stress without glycine-betaine supplementation, likely by altering cross-linking of the peptidoglycan in the cell envelope via downregulation of MurE. The proteome changes indicate that lactate might (indirectly) cause oxidative stress. Combined, our study shows that RNAP mutations enhanced lactate resistance through pleotropic effects in the proteome that changed L. lactis responses against multiple stresses. HighlightsO_LILactate resistant variants were isolated from stressostat cultivations C_LIO_LIMetagenomics revealed evolutionary trajectory during stressostat cultivation C_LIO_LIRNAP mutations were identified as key drivers for improved lactate resistance C_LIO_LIRNAP mutations altered the proteome, enhancing the osmotic stress resistance C_LI

The disparity between the production and demand of recombinant proteins (r-proteins) has significantly hindered their commercial viability. Leveraging genomic resources offers substantial promise in enhancing our comprehension of metabolic and regulatory networks, thus facilitating the development of highly productive protein cell factories. However, the considerable gap between high-throughput strategies for monitoring r-protein secretion and genome perturbation in P. pastoris continues to obstruct the systematic linkage of genotype and phenotype, thereby limiting the optimization of production. Here, we developed a novel strategy combining dual-base editor-mediated in-situ genome engineering with nanobody-regulated biosensor-assisted droplet sorting to enhance r-protein secretion (BINDER) in P. pastoris. We successfully employed BINDER to screen recombinant human serum albumin (rHSA) hyper-producers and identified two critical SNVs conferring up to a 1.78-fold improved secretion titer from 113,632 mutants, providing valuable insights into the secretion mechanism. Fed-batch cultivation of the engineered strain resulted in the highest reported rHSA titer, 23.43g/L, in P. pastoris, demonstrating its substantial potential for industrial applications. Given the high transferability of base editors and the novel biosensors independence from the properties of the target protein, the strategy developed here might be expanded to a variety of microbial species and r-proteins.

Hydrogenophilus thermoluteolus TH-1 is a thermophilic hydrogen-oxidizing bacterium capable of producing poly(3-hydroxybutyrate) (PHB) from CO2. To redirect carbon flux for producing other useful biomaterials, we disrupted the acetoacetyl-CoA reductase genes (phaB1 and phaB2), which are central to the primary PHB synthesis pathway. Unexpectedly, the resulting {Delta}phaB1B2 mutant still accumulated PHB under autotrophic conditions, reaching approximately 25-35 % of the wild-type level. Furthermore, PHB accumulation in the mutant was significantly restored when fatty acids (butyrate and oleate) were used as carbon sources, whereas acetate and malate resulted in reduced accumulation. These results suggest the existence of a PhaB-independent PHB synthesis pathway. We propose that intermediates from the {beta}-oxidation of fatty acids are converted to (R)-3-hydroxybutyryl-CoA, bypassing the disrupted PhaB enzymes. Additionally, the basal PHB production from non-fatty acid sources implies the involvement of a reverse {beta}-oxidation pathway. This study highlights the metabolic versatility of strain TH-1 for future metabolic engineering.

Stachys affinis (Chinese artichoke) tubers contain 50-80% stachyose by dry weight, the most concentrated dietary source of raffinose-family oligosaccharides (RFOs) known. Because humans lack sufficient -galactosidase activity, stachyose transits intact to the colon where microbial fermentation yields short-chain fatty acids (SCFAs). However, the quantitative impact of stachyose-derived SCFAs on host hepatic energy metabolism has not been systematically explored using genome-scale metabolic models. Three stachyose dose scenarios (Low/Mid/High: [~]25, 50, 100 g fresh tubers) were translated to SCFA availability vectors. Hepatic metabolic responses were simulated using Recon3D (10,600 reactions) and Human-GEM (13,417 reactions) under strict hepatocyte-like media, maximizing ATP maintenance flux (ATPM). FVA across multiple optimality thresholds (90-100%) and pFBA confirmed solution robustness. One-at-a-time sensitivity analysis characterized ATPM responses to individual parameter perturbations, and a ratio sensitivity sweep across six alternative SCFA profiles assessed dependence on assumed fermentation ratios. A targeted rescue experiment addressed model-specific propionate catabolism gaps. Both models showed dose-dependent ATPM increases (Recon3D: +71 to +286%; Human-GEM: +103 to +413% above baseline), with the 19-33% inter-model gap attributable entirely to Human-GEMs functional propionate catabolism pathway. FVA confirmed near-unique optimal solutions (ATPM ranges [~]1% at 99% optimality, widening to [~]10% at 90%). Parsimonious FBA preserved identical ATPM values while reducing total flux by [~]4-14%, confirming objective robustness. SCFA ratio sensitivity across six alternative profiles showed 27- 28% ATPM variation, indicating qualitative robustness. Butyrate yielded the highest ATP per mole ([~]22) in both models; propionate sensitivity was zero in Recon3D but [~]15.25 mmol ATPM/mmol propionate in Human-GEM. Reopening propionyl-CoA carboxylase (PPCOACm) in Recon3D under strict constraints converged ATPM to within 0.3-0.7% of Human-GEM, cross-validating both reconstructions. This reproducible dual-model pipeline identifies model-specific pathway gaps and provides cross-validated predictions to guide future experimental studies of how dietary SCFAs influence hepatic ATP metabolism.

This article presents the development of an advanced modeling and simulation platform for carbon capture systems, with a focus on integrated process analysis from upstream CO2 capture through to bioethanol production. The platform supports the evaluation of CO2 mitigation technology by coupling mathematical bioprocess models with an interactive desktop application. The biological system employs Chlorella vulgaris microalgae to fix CO2 through photosynthesis and generate carbohydrate substrates, which are subsequently converted to bioethanol by Saccharomyces cerevisiae yeast via fermentation. The simulation integrates three established kinetic models--the Monod, Logistic, and Luedeking-Piret models--to predict biomass growth, substrate consumption, and ethanol yield under varying operational conditions. A closed-loop CO2 recycling subsystem captures fermentation off-gases and reintroduces them into the bioreactor, enhancing overall carbon utilization efficiency. Three representative simulation scenarios demonstrated process efficiencies ranging from 1.09% to 93.78% of the theoretical maximum CO2-to-ethanol conversion efficiency, confirming the platforms capacity to evaluate a wide operational envelope. The Electron/React-based desktop application provides real-time visualization, interactive 3D bioreactor models, and a simulation history module, making it accessible to researchers, engineers, and students. The platform serves as a digital twin that bridges rigorous bioprocess mathematics with intuitive user interaction, providing a cost-effective tool for designing and optimizing sustainable carbon capture and biofuel production systems.

Industrial defossilisation requires carbon-negative routes for sustainable chemical production. Bioprocesses based on renewable feedstocks are often constrained by biogenic CO2 emissions, reducing yields and undermining environmental performance. Here, we report a mixotrophic gas fermentation strategy using the chemolithoautotroph Cupriavidus necator H16 that simultaneously assimilates CO2 for cell growth and biocatalyst generation while converting the PET monomer terephthalic acid (TPA) into value-added biopolymer precursors. This process achieved complete conversion of TPA to 2-pyrone-4,6-dicarboxylic acid (PDC) with titres of 24.5 g/L and a productivity of 0.47 g/L{middle dot}h. Conversion to pyridine dicarboxylic acids (2,4- and 2,5-PDCA) was less efficient ([~]22% and [~]4% respectively) due to metabolic limitations such as intermediate toxicity, pH and ammonia-dependent spontaneous cyclisation. Our results establish the first carbon-negative route coupling simultaneous CO2 assimilation with plastic monomer valorisation, providing a blueprint for sustainable biomanufacturing aligned with global climate and circular economy goals.

Crude glycerol is an underutilized waste stream. Viable routes for converting it to 1,3-propanediol (1,3-PDO) can conserve important resources and add value to its supply chain. Biological methods are appealing because they can circumvent expensive preprocessing steps while operating under mild conditions. Here, we show that the propanediol utilization pathway of Salmonella enterica serovar Typhimurium LT2 can be used to convert glycerol, including unprocessed crude glycerol, into 1,3-PDO under aerobic conditions in minimal media. Additionally, we demonstrate that high concentrations of expensive cofactors are not necessary to achieve optimal production titers. This study lays the groundwork for continual iteration on this pathway for bioprocess development. Key pointsO_LIS. enterica can produce 1,3-propanediol from crude glycerol alone C_LIO_LIGlycerol-to-1,3-propanediol conversion is dependent on expression of the propanediol utilization (Pdu) pathway C_LIO_LISub-saturating concentrations of exogenous vitamin B12 can boost cell growth and 1,3-propanediol yield C_LI