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.

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.

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.

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

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.

Given the current global environmental challenges, waste biomass is an attractive renewable resource for circular economies. Gasification of biomass yields syngas (CO, CO2, and H2) that is a suitable feedstock for gas fermentation in biomanufacturing of fuels and chemicals using acetogen microbes. While it is generally known that syngas composition influences both acetogen growth and process performance, we are lacking a consistent dataset quantifying these effects under controlled fermentation conditions. Here, we mapped the metabolic response of the model-acetogen Clostridium autoethanogenum to seven synthetic syngas mixtures during exponential batch growth in bioreactor fermentations. Notably, distinct gas compositions resulted in different fermentation profiles, affecting both growth and metabolite production. Maximum specific growth rates ranged within 0.05 0.13 h-1, with slower growth for low-CO mixtures. While acetate and ethanol production yields varied between 20-133 and 76-353 mmol per gram dry cell weight, respectively, minor production of 2,3-butanediol was detected. All syngas mixtures supported co-utilization of CO and H2, though gas uptake stoichiometry only moderately correlated with syngas content. Importantly, gas uptake stoichiometry strongly influenced carbon partitioning, with higher relative H2 uptake reducing CO2 loss or even realizing CO2 fixation together with increasing carbon flow towards metabolites. Interestingly, higher syngas H2 content favored ethanol and 2,3-butanediol production, while higher H2:CO uptake ratios increased total flux through the Wood-Ljungdahl pathway rather than selectively favoring reduced by-products. Our results are valuable for a better understanding of syngas composition effects on the acetogen biocatalyst and for process engineering towards optimizing gas fermentation performance. HighlightsO_LISyngas composition affects acetogen growth, gas uptake, and carbon distribution C_LIO_LIHigher H2:CO uptake ratios increase carbon flow through the Wood-Ljungdahl pathway C_LIO_LIHigher relative H2 uptake reduces CO2 loss and increases metabolite production C_LI

The domestication of Streptomyces species for antibiotic production involves long-term, iterative mutagenesis and selection, yet the genomic changes driving enhanced production remain unclear. Analysis of five strains from an industrial lineage of Streptomyces clavuligerus using comparative genomics, transcriptomics and phenotypic profiling for dynamic genome architectures with plasmid integration events and chromosomal rearrangements, alongside the accumulation of mutations affecting metabolic pathways and global gene regulation. These changes increased precursor supply and reprogrammed transcription leading to enhanced clavulanic acid production but reduced catabolic flexibility. Complementation experiments confirmed the functional impacts of specific mutations. These findings reveal that artificial selection shapes genome evolution in industrial strains, balancing production gains with metabolic trade-offs. This work will likely inform rational design of Streptomyces strains for improved natural product production in industry while highlighting the constraints imposed by domestication on metabolic versatility. More broadly it shows that many of the evolutionary processes in industrial strain improvement programmes mirror those at play during natural selection.

Acetate is a promising carbon source for microbial biotechnology as it can be produced sustainably from lignocellulosic biomass or C1 gases. Since acetate is directly activated to acetyl-CoA, it is especially suitable for producing acetyl-CoA-derived products, showcased here with the production of 3-(3-hydroxyalkanoyloxy) alkanoic acids (HAAs). P. putida KT2440 can natively metabolize acetate, but the weak acid has also inhibitory effects on microbial growth. We present an in-depth study on the physiology of P. putida KT2440 using acetate as carbon and energy source and evaluate acetate as feedstock for the biosynthesis of HAAs. Initially, a rational engineering approach to overexpress acetyl-CoA synthetase for acetate activation resulted in an improved growth rate of 16% and reduced lag phase by six hours. To further increase the performance of P. putida KT2440 on acetate, adaptive laboratory evolution was performed. This resulted in an improvement in the growth rate from 0.4 h-1 to 0.6 h-1 and enabled growth on up to 12.5 g L-1 acetate with a shortened lag phase compared to the wild type. Whole-genome sequencing revealed mutations in proteins involved in gene expression regulation and signal transduction. This evolutionary engineering approach informed the deletions of gacS and crc, which resulted in a reduction in the lag phase from seven hours to one hour and an improvement of the growth rate by 25 %, matching the growth properties of the evolved clones. Using the evolved strains for the production of HAAs resulted in faster biomass and product formation with product titers reaching up to 94 % of that of the wild type. In conclusion, we identified mechanisms in the acetate metabolism of P. putida KT2440 and improved the growth performance of the strain by rational and evolutionary engineering, demonstrating the potential of the promising, but challenging 3rd generation feedstock acetate.

The pulp and paper industry produces large volumes of condensed kraft lignin, which is challenging to convert to single chemical products. For this purpose, tandem chemical depolymerization and bioconversion to a single atom-efficient product is a potentially promising strategy. In this study, we conducted copper-catalyzed oxidative depolymerization using pine-derived kraft lignin to generate multiple bioavailable aromatic monomers at a yield of 4.5 weight% (wt%; g monomers per g lignin) from both C--O and C--C bond cleavage, followed by counter-current extraction with a 52 wt% monomer recovery. This resulted in an oxidized lignin product containing vanillin, vanillate, 4-hydroxybenzaldehyde, 4-hydroxybenzoate, 5-formylvanillin, 5-carboxyvanillin, 5-carboxyvanillate, acetovanillone, and vanillyl glyoxylate. Based on this stream composition, we engineered the industrially relevant soil bacterium Pseudomonas putida KT2440 to catabolize the latter five compounds via overexpression of ten heterologous genes (acvABCDEFSYK-6, vceABSYK-6, ligW2SYK-6, and mdlCPP). We combined these engineered pathways with previously reported strategies for muconate production from G- and H-type monomers to generate P. putida KMM428, which utilized 93.6 {+/-} 0.2 mol% of the quantified aromatic monomers in a depolymerized kraft lignin mixture, and produced muconate at a yield of 99 {+/-} 3 mol%, on a quantified monomer basis. Together, this work increases the theoretical carbon conversion efficiency of this process by 37.6 {+/-} 0.1 mol% through incorporation of three {beta}-5 cleavage products, in addition to traditional G-type monomers.

Microbial fuel cells (MFCs) have been widely investigated as decentralized bioelectrochemical systems capable of converting organic substrates into electricity. However, their long-term autonomous operation is constrained by substrate depletion in the anode compartment, leading to metabolic starvation of electroactive biofilms and a decline in power output. Conventional MFC design treats substrate crossover through the membrane separator as a parasitic loss that reduces coulombic efficiency. In this work, we propose a conceptual inversion of this paradigm by considering controlled cathodic-to-anodic substrate crossover as a passive mechanism to sustain basal microbial metabolism during periods of substrate scarcity. A transport-reaction framework is developed to quantify the balance between membrane-mediated substrate flux and microbial maintenance demand within the anode biofilm. Based on this balance, a dimensionless maintenance crossover Damkohler number (Dam) is introduced to define three operational regimes: starvation-dominated (Dam >> 1), balanced autonomous (Dam {approx} 1), and crossover-dominated (Dam << 1). The framework integrates membrane transport theory with biofilm kinetics to evaluate the effects of separator properties, substrate gradients, and current-dependent electro-osmotic transport on system stability. Order-of-magnitude analysis indicates that achievable crossover fluxes span several orders of magnitude depending on separator characteristics, suggesting that membrane properties critically influence system behavior. This perspective reframes substrate crossover from a loss mechanism to a potential design variable, offering a conceptual tool for enhancing resilience and guiding separator selection in MFCs intended for long-duration, and low-maintenance operation. HighlightsO_LIControlled crossover can sustain microbial metabolism in MFCs C_LIO_LIIntroduces maintenance crossover Damkohler number (Dam) C_LIO_LIIdentifies regimes for autonomous and starvation operation C_LIO_LILinks membrane properties to long-term system stability C_LIO_LIReframes crossover as a design variable, not only a loss C_LI

Isotopic Metabolic Flux Analysis (I-MFA) is a standard approach for estimating intracellular metabolic fluxes. I-MFA infers fluxes by comparing simulated and measured metabolite isotopologue distributions (MIDs) of metabolites from isotope labeling experiments. MIDs represent fractional abundances that strictly sum to one for any given metabolite, thus they are inherently compositional data. However, state-of-the-art estimation approaches rely on calculating standard Euclidean distances between MIDs in a non-compositional paradigm, introducing a systemic bias. To resolve this, our study proposes compositional I-MFA. We demonstrate how to construct a meaningful orthonormal basis for MIDs via ordered sequential binary partitioning, which can be used to perform isometric log-ratio (ILR) transformation. As a minimal change to existing I-MFA workflows, we suggest estimating fluxes by minimizing Euclidean distances between ILR-transformed MIDs. We validated this framework against traditional methods using both a toy model and a biologically realistic model, evaluating point estimates, sensitivity across varied true fluxes, and confidence intervals. In the two examples, compositional I-MFA consistently outperformed traditional approaches, reducing mean squared error of flux point estimates by an average of 42.6% and substantially narrowing confidence intervals. We conclude that compositional data analysis significantly improves I-MFA and can be implemented as a simple drop-in replacement for current pipelines. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/742769v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1a53aa4org.highwire.dtl.DTLVardef@ad225aorg.highwire.dtl.DTLVardef@aa430eorg.highwire.dtl.DTLVardef@1880ca_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LINew compositional data approach improves metabolic flux estimation. C_LIO_LIThis data transformation requires minimal changes to existing workflows. C_LIO_LIThe new method reduced MSE of flux estimates by 42.6% in two examples tested. C_LIO_LIThe confidence intervals of the estimated fluxes were substantially narrowed. C_LIO_LIEstimation accuracy remained robust across a wide range of metabolic fluxes. C_LI

O_LIVitamin B12, an essential micronutrient for many microalgae and humans, is synthesised only by certain prokaryotes. B12 is a complex tetrapyrrole that can exist in many forms (vitamers), some more bioavailable than others. Some microalgae are able to interconvert, or remodel, different B12 vitamers. As microalgae are important primary producers, it is crucial to understand how diverse microalgae acquire, utilise, and remodel this micronutrient. C_LIO_LIThrough the development of a novel algal bioassay for B12 quantification that distinguishes between B12 vitamers with different lower axial ligands, and the generation of targeted knock-out lines, we characterised the role of proteins involved in algal B12 uptake and remodelling. C_LIO_LIWe found that the previously characterised protein CoBalamin-Acquisition protein 1 (CBA1) is also necessary for the acquisition of pseudocobalamin, a less bioavailable form of B12. In addition, we provide the first experimental evidence that COBT is required for Chlamydomonas reinhardtii to remodel B12. C_LIO_LIWe apply the algal B12 bioassay to show that the edible alga Chlorella vulgaris can accumulate pseudocobalamin but is unable to remodel it, highlighting the need for thorough investigation of the metabolic requirements and capabilities of microalgae, especially given the growing interest in microalgae-based food additives. C_LI

Although metabolomics has shown considerable promise for biomarker discovery, and the development of diagnostic and prognostic applications, its translation into routine clinical practice remains limited by analytical complexity, cost, throughput, and standardization challenges. These limitations underscore the need for complementary tools, particularly in resource-limited settings. In this study, we developed a workflow for the engineering and characterization of growth-coupled metabolic sensors capable of disease detection (healthy vs. infected) and outcome prediction (mild vs. severe), which we illustrated using COVID-19 as a proof-of-concept application. We first generated a biomarker-guided library of 34 candidate sensors leveraging both auxotrophic phenotypes and less stringent metabolic dependencies. We then screened the library against patient plasma pools, identifying 19 sensor candidates with diagnostic and/or prognostic potential, including 14 with prognostic potential. Lastly, a selected subset of candidates was further evaluated on a patient cohort using two newly developed analytical frameworks designed to extract additional information from bacterial growth curves. The best-performing sensors achieved a balanced accuracy of 0.88{+/-} 0.06 for prognostic prediction (outer-test AUC = 0.89, 5-fold cross-validation, n = 37) and 1.00 for diagnostic classification (outer-test AUC = 1.00, 5-fold cross-validation, n = 56). Collectively, these findings establish a proof of concept for translating disease-associated plasmatic metabolic signatures into low-cost, growth-coupled biosensors with diagnostic and prognostic capabilities.

Pancreatic beta cells exhibit marked resistance to proliferation, posing a barrier to therapeutic strategies aimed at restoring beta-cell mass in diabetes. Here, we present a transient, non-integrative approach to stimulate beta-cell proliferation using in vitro transcribed (IVT) mRNAs encoding cell cycle regulators. In rodent beta cells and human-beta cell derived EndoC-BH5 cells, chemically modified IVT mRNAs activated cell cycle entry and subsequent mitosis. A single dose of cyclin D1 and CDK4 IVT mRNAs nearly doubled the number of rat beta cells. However, achieving cell division in human beta cells required co-delivery of MYC IVT mRNA. The mitogenic response of beta cells peaked within 36-60 hours, and declined thereafter, reflecting the transient nature of IVT mRNA. Transcriptomic profiling revealed temporary activation of proliferative pathways and reversible downregulation of beta-cell maturation markers. Importantly, we detected no evidence of sustained proliferation. Our findings demonstrate that mRNA-based delivery of cell cycle regulators can overcome the intrinsic cell cycle block in beta cells and may provide a controllable approach for beta-cell regeneration.

The budding yeast Saccharomyces cerevisiae is a well-established model organism to study cellular stress response and underlying mechanistic regulation. Although glucose starvation fundamentally alters gene regulation and cell behaviour, inconsistent deprivation protocols often trigger gross morphological artefacts. These non-specific changes confound findings by activating pathways independently of true glucose-signalling mechanisms. Furthermore, a thorough transcriptomic profile of glucose starvation using non-confounding conditions remains lacking. Consequently, the precise transcriptional impact of losing key metabolic regulators that mediate adaptation to glucose starvation remains undefined. Here we have employed a refined glucose starvation protocol, utilising raffinose exchange, which shows induction of vast transcriptional stress response with minimal impact on cellular morphology confirmed by label-free imaging. Transcriptomic profiling revealed shifts in metabolic regulation, ATP turnover, and cell-to-cell communication as acute glucose deprivation driving cells towards oxidation-driven metabolism. Additionally, we characterise transcriptional alterations seen in deletion mutants of SNF12 and SPT20, known regulators of cellular metabolism, showing previously unappreciated transcriptional conservation, in part mimicking glucose starvation response. Finally, we identified cargo and stress-specific expression related to both eisosome components and surface transporters that are critical for metabolic adaptation. Overall, this dataset provides a comprehensive transcriptomic resource for dissecting stress signalling and driving novel hypothesis generation.

Fluorescent proteins are fundamental tools for cellular imaging. Most fluorescent proteins in routine use, including GFP, are derived from the jellyfish Aequorea victoria and emit blue-green light, which is strongly absorbed and scattered by tissue, limiting imaging depth. Far-red and near-infrared fluorescent proteins, engineered from bacteriophytochromes, address this limitation because far-red light penetrates tissue considerably further. However, these proteins are typically much dimmer than their A. victoria -derived counterparts. Improving brightness by conventional directed evolution requires screening large random mutant libraries, a process that is slow, labor-intensive, and often impractical outside specialized laboratories. We utilized an active-learning-guided directed evolution workflow that identified improved variants from substantially less data than conventional screening. Each round coupled automated, miniaturized cell-free protein expression directly from a DNA template without cloning or cell culture, with a machine-learning model retrained on cumulative sequence-function data to nominate the most informative variants for the next round. Applied to miRFP670nano3, this workflow screened 120 variants across successive rounds and identified twelve with improved brightness, the best four-fold brighter in bacterial systems. However, these gains did not translate when the variants were evaluated in mammalian cells, indicating that performance can be strongly dependent on cellular context. Retrospective simulation across benchmark datasets from ProteinGym showed that performing more experimental batches with fewer samples per batch consistently accelerated convergence to high-fitness sequences. Incorporating protein-language-model derived zero-shot fitness priors also accelerated convergence, but only in proportion to how well each prior score correlated with the true fitness landscape. Together, these findings established generalizable design rules, favoring smaller acquisition batches and confidence-weighted priors, for engineering proteins from minimal experimental data. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=55 SRC="FIGDIR/small/744534v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@14992f7org.highwire.dtl.DTLVardef@14fad5borg.highwire.dtl.DTLVardef@1fe4ec2org.highwire.dtl.DTLVardef@e4b1f0_HPS_FORMAT_FIGEXP M_FIG C_FIG

The declining cost of green hydrogen--projected below 1.5 USD/kg by 2030--opens new avenues for its use beyond fuel cells and industrial heating. Here we demonstrate that H2 can serve as a stoichiometric electron donor for cell-free enzymatic cofactor regeneration, coupling H2 oxidation to NADPH production and driving the complete bioconversion of pyruvate to lactate. A partially purified enzyme ensemble from Escherichia coli overexpressing Clostridium pasteurianum ferredoxin, augmented with [FeFe]-hydrogenase CpII, delivers NADP+ reduction rates of 103 M min-1 (27-fold enhancement) with superlinear dependence on H2 partial pressure. Reconstitution from purified components (CpI or CpII, CpFd, AnFNR, LDH) uncovers a redox-potential-dependent lag phase: the NADPH/NADP+ ratio must exceed 0.85 before pyruvate reduction becomes thermodynamically spontaneous, after which the rate accelerates exponentially. These results position hydrogen-driven cofactor regeneration as a scalable, byproduct-free platform for reductive biotransformations powered by renewable H2.

The gastrointestinal tract is rich in metabolic, immune, and microbiome-derived signals that can inform the design of live biotherapeutics and diagnosis of intestinal disorders. Engineered cell-based biosensors can tap into this molecular information and report on their environment, yet their development in gut-resident symbionts has been limited by a lack of validated sensor systems. Here, we present a generalizable pipeline that leverages bacterial transcriptional profiling to identify environment-responsive systems for biosensor engineering. Candidate Sensors Systems (CSSs) mined from healthy, disease, and in vitro transcriptomes were assembled into a barcoded library in Bacteroidaceae chassis and screened in high-throughput in vivo to identify responsive promoters. A unique Bacteroidales ECF-type sigma factor operon with ties to sphingolipid metabolism and flux was highly responsive in chemically-induced colitis models. The biosensor responded robustly to disease and returned to baseline upon recovery, establishing an in vivo-driven strategy for discovering functional biosensors in non-model gut-resident bacteria.

Cell confluency is a major determinant of cell-cell communication, protein interactions, access to nutrients, and signalling dynamics, thereby significantly impacting biological outcomes. Lung cancer cells like A549 are widely used as screening models for scientific studies wherein their growth in vitro progress from non-confluent to confluent growth. In this study, we investigated the transcriptomic adaptations associated with the transition of A549 cells from baseline non-confluent to confluent growth. Comparative transcriptomic analysis between confluent and cells at baseline identified 815 upregulated and 671 downregulated transcripts. Pathway enrichment analysis of deregulated transcripts in confluent cells revealed enhanced cholesterol and sterol biosynthetic pathways, along with suppression of chromosomal segregation and mitotic pathways. At confluency, an increased expression of glucose transporters (SLC2, SLC60, and SL37 families) and glycolytic pathways, and a decrease in amino acid transporters (SLC1, SLC7, SLC38, and SLC36) and amino acid metabolic pathways is observed. A reduced one-carbon metabolic signature (SHMT2, DHFR, and MTHFD2) and enhanced fatty acid precursor synthesis (HMGCLL1, ALDH6A1, and AASS) were also observed at confluency. 1H NMR profiling of culture media revealed higher glucose and glutamine utilisation with lactate accumulation during culture maturation. Collectively, the data suggest transcriptome-level rewiring in A549 cells with preferential biosynthesis of lipids and sterols at confluency and underscore the importance of considering culture maturity in cancer biology, metabolism, and therapeutic studies.