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.

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.

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.

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

Cyanobacteria have garnered interest as promising biological platforms for producing renewable biofuel, chemical feedstock, and bioactive molecules. For biotechnology applications, robust well-characterized genetic tools are required for genetically modifying cyanobacteria, but these tools are often developed for specific model strains. Here, we used broad host-range RSF1010-based plasmids to characterize a set of orthogonal constitutive promoters in diverse cyanobacterial strains. The promoters are random variants of the synthetic Escherichia coli PconII promoter. A library of PconII promoters driving a fluorescent reporter gene was first evaluated in Synechococcus elongatus and found to have a wide range of gene expression levels. A set of 25 promoter variants with graded strengths was selected after characterization in S. elongatus and three additional model cyanobacterial strains. To demonstrate the utility of these promoters, we isolated new genetically tractable cyanobacterial strains with high salt and alkalinity tolerance and transferred the subset of promoters into one of these newly isolated strains. Similar to the results with model strains, the subset of promoters had a wide range of expression levels in the non-model strain. These characterized promoters expand the genetic tools available for genetic engineering of model and non-model cyanobacterial strains. ImportanceThe use of cyanobacteria to produce renewable products will require engineered expression of many genes that affect cell growth, metabolism, and agronomic properties, leading to efficient production of biomass and desired products. Engineering the strength of gene transcription is an important element of overall gene expression levels. The set of constitutive promoters described here, with a wide range of expression strengths characterized in several diverse cyanobacterial strains, provides an important resource for genetic engineering required for biotechnology applications. Research AreasMicrobial genetics, plasmids and other genetic constructs, biotechnology Journal SecctionBiotechnology

Current mechanical and chemical recycling strategies address less than 10% of global plastic waste, necessitating alternative valorization routes. Biological upcycling via enzymatic depolymerization combined with microbial conversion of the resulting monomers offers a promising pathway to transform mixed plastic waste into valuable alternatives. Here, we employed a single engineered Pseudomonas putida KT2440 for simultaneous co-utilization of five plastic monomers including ethylene glycol, terephthalic acid, adipic acid, 1,4-butanediol, and L-lactic acid, which can be derived from enzymatic hydrolysis of polyethylene terephthalate (PET), polybutylene adipate-co-terephthalate (PBAT), polyester-polyurethanes (PUs), and polylactic acid (PLA). Continuous fermentation over 21 days with alternating mixed-monomer feeds achieved steady state growth and complete substrate depletion, yielding adaptive mutations that informed iterative strain improvement. Further engineering enabled the biosynthesis of (R)-3-hydroxybutyrate (R-3HB), and 0.70 g L-1 R-3HB was produced directly from enzymatic hydrolysates of blended PET, PBAT, and TPU. These results establish a viable bio-based approach for upcycling realistic mixed plastics into value-added bioproducts.

Pseudomonas putida strain KT2440 is a crucial model organism for synthetic biology and bioengineering applications, yet there currently exists no comprehensive metabolomics database comparable to those available for other model organisms. This gap hinders the use of untargeted metabolomics for exploratory analyses in this system. We developed the P. putida metabolome reference database (PPMDB v1) to address this limitation by consolidating metabolite information from multiple sources and expanding coverage through computational predictions. The database was constructed by curating metabolites from BioCyc, BiGG, and other literature sources, then computationally expanding this collection using BioTransformer environmental transformation predictions to generate additional predicted metabolites. We enhanced the databases utility for molecular annotation in metabolomics studies by incorporating analytical properties including collision cross-sections, tandem mass spectra, and gas-phase infrared spectra. These analytical properties were gathered from existing measurement data or predicted using computational tools. We further augmented the database through inclusion of reaction information and pathway annotations, facilitating biological interpretation of metabolomics data. This publicly available resource fills a critical gap in P. putida research infrastructure, supporting metabolite annotation and biological interpretation in untargeted metabolomics studies and enabling in-depth exploratory analyses of this important synthetic biology platform at the molecular level. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/713193v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@c8828forg.highwire.dtl.DTLVardef@1f3a5c5org.highwire.dtl.DTLVardef@1084535org.highwire.dtl.DTLVardef@1f7ca4a_HPS_FORMAT_FIGEXP M_FIG C_FIG

Metabolic engineering to produce molecules not naturally synthesized by the host often requires directed evolution to improve pathway enzyme performance. Growth-coupled selection can dramatically increase directed-evolution throughput, and manipulation of redox balance has proven effective for tying reductase fitness to microbial growth. However, most redox-balance selections require feeding the reductase substrate because of stoichiometric constraints. This is impractical for many biosynthetic pathways either due to practical limitations on cost or complexity of bulk substrate synthesis, or the lack of an ability to transport substrate into cells, for example intracellular acyl-CoA/ACP intermediates. Here we define stoichiometric constraints that make substrate feeding necessary for many acetyl-CoA-derived reduction pathways in NADPH-imbalanced hosts. We overcome these constraints with a dual-feedstock strategy in which glucose provides reducing power while acetate supplies additional acetyl-CoA without directly perturbing redox balance. In an engineered E. coli selection strain, acetate co-feeding enabled growth coupling of acetaldehyde, 3-hydroxybutyrate, and mevalonate production and produced a linear correlation between product formation and growth. We then used this selection to evolve a class II HMG-CoA reductase (HMGR) from Delftia acidovorans toward NADPH utilization, enriching variants with improved NADPH-dependent activity. Finally, propionate co-feeding enabled growth coupling of propionyl-CoA reduction, supporting the generality of carbon co-feeding for selecting enzymes in pathways involving acyl-chain elongation and reduction. HighlightsO_LIStoichiometric limits of redox-balance growth coupling are defined C_LIO_LIAcetate co-feeding supplies acetyl-CoA without perturbing redox balance C_LIO_LICo-feeding enables growth coupling of acetaldehyde, 3-HB, and mevalonate C_LIO_LIGrowth coupling enables evolution of HMGR toward NADPH specificity C_LIO_LIPropionate co-feeding extends growth coupling to additional acyl-CoA substrates C_LI

Zymomonas mobilis is an ethanologenic Alphaproteobacterium with many interesting characteristics for fundamental research and applied microbial engineering. Although genetic engineering has been established for Z. mobilis since the 1980s, a rich set of inducible transcriptional regulators is still unavailable. In this work, seven different chemically inducible promoters have been systematically tested for their functionality in Z. mobilis. In particular, for the first time, NahR-PsalTTC, VanRAM-PvanCC, CinRAM-Pcin and LuxR-PluxB have been characterized in Z. mobilis, alongside the commonly used regulator-promoter pairs TetR-Ptet and LacI-PlacT7A1_O3O4, and the less commonly used XylS-Pm. All promoters investigated in this work are compatible with the Golden Gate modular cloning framework Zymo-Parts. Characterization was carried out with a shuttle vector backbone based on pZMO7, which has so far been rarely used for applications in Z. mobilis but seems to be completely stable without selection and generates high and uniform levels of expression. From the experimental results presented, it can be concluded that VanRAM-PvanCC and CinRAM-Pcin are particularly promising for broad use in the Z. mobilis community. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/712268v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@16579e6org.highwire.dtl.DTLVardef@1262533org.highwire.dtl.DTLVardef@15456a2org.highwire.dtl.DTLVardef@3af98_HPS_FORMAT_FIGEXP M_FIG C_FIG

The unicellular green alga Chlamydomonas reinhardtii provides a tractable model for investigating how carbon availability influences metabolic organization and cell-cycle control in photosynthetic eukaryotes. Its capacity for autotrophic (light, CO2), mixotrophic (light, CO2, acetate), and heterotrophic (acetate, dark) growth enables systematic analysis of trophic-state-dependent regulation. We performed comparative transcriptomic analyses of strain 21gr grown under these three regimes at 30 {degrees}C. Mixotrophy resulted in the highest biomass accumulation and was associated with earlier cell-cycle commitment compared with autotrophy, whereas heterotrophy displayed delayed commitment and reduced growth. Transcriptomic profiling revealed coordinated upregulation of central carbon metabolic pathways under mixotrophy, including photorespiration, glycolysis, the oxidative pentose phosphate pathway, and tricarboxylic acid cycle functions, consistent with enhanced carbon flux and biosynthetic capacity. In contrast, heterotrophy preferentially induced acetate assimilation and glyoxylate cycle genes and was accompanied by elevated expression of cell-cycle regulators, including the CDK-inhibitory kinase WEE1. Together, these findings indicate that trophic mode modulates the coupling between carbon metabolism and cell-cycle progression, with mixotrophy supporting integrated metabolic and proliferative activity, whereas heterotrophy is associated with delayed cell-cycle timing and transcriptional signatures of metabolic adjustment.

Cells have the potential to utilize biological pathways to synthesize semiconductor nanomaterials, such as CdS quantum dots. As in chemical reaction schemes, biogenic synthesis requires control of the concentration and redox state of starting materials during the nucleation and growth of nanoparticles. Biological pathways regulate these key processes of particle synthesis, and manipulation of such pathways enables biological control of multiple aspects of nanoparticle synthesis. Here, strains of Escherichia coli were engineered to biosynthesize cadmium sulfide (CdS) quantum dots through the coordinated action of three pathways controlling sulfide generation, cadmium uptake, and nanoparticle nucleation. When exposed to low, micromolar concentrations of external cadmium, strains combining all three pathways produced CdS quantum dots. The synthesis of nanoparticles, nanoparticle yield, and nanoparticle size depended on the combination of pathways found in each strain. Cells lacking all three pathways produced no detectable nanomaterials, cells with specific combinations of one or two pathways produced small particles in the range of 1.95 to 7.9 nm, and cells with all three pathways produced the largest particles with average diameters of 11.78 nm. These results demonstrate that cells can be engineered to control multiple aspects of biogenic nanoparticle synthesis and that these pathways act together to tune the biosynthesis of semiconductor nanomaterials within cells. ImportanceMicrobes synthesize materials, including metallic and semiconductor nanomaterials. This capability stems from the natural ability of microbes to interact with and precisely manipulate metal atoms. Here, multiple biological pathways were combined within a single strain of Escherichia coli, creating a cell capable of producing CdS nanoparticles. This engineered cell controls multiple steps of particle synthesis, including metal uptake, reduction of starting materials, and binding cadmium and sulfide ions to initiate particle formation. Metal uptake by the cells was improved through the modification of a metal ion transport protein, improving cadmium uptake across the outer membrane and creating higher concentrations of cadmium within the cell. Cells with all three pathways were able to produce CdS nanoparticles, called quantum dots, even when exposed to low concentrations of external cadmium. This biotechnology enables nanomaterial synthesis under environmentally friendly conditions and may improve technologies using bacteria to clean up toxic metals.

The contemporary shift toward multispecific antibodies, antibody-drug conjugates (ADCs), and bespoke glycoengineered therapeutics have exposed the limitations of standard genomic engineering tools. This paper presents a novel iterative engineering paradigm utilizing the Leap-In Transposase(R) platform. By leveraging a suite of three mutually orthogonal transposase-transposon systems, we demonstrate the sequential modification of the Chinese Hamster Ovary (CHO) genome to achieve three distinct functional outcomes: (i) First, the creation of a glutamine synthetase (GS)-deficient host (CHO-K1-GS) via targeted knockdown, (ii) Second, the integration of multiple copies of a model therapeutic IgG1 for expression, and (iii) Third, the subsequent knockdown of the fucosylation pathway to modulate the glycan profile of the expressed IgG1. Genetic stability (copy number & sequence) of each integration event was confirmed using Targeted Locus Amplification (TLA) and Next-Generation Sequencing (NGS). Functional stability (expression levels, metabolic phenotype, and glycan phenotypes) was confirmed using standard cell culture and analytical techniques. Crucially, the truly orthogonal nature of the transposase-transposon pairs prevents cross-mobilization and ensures the structural and functional integrity of previously integrated cargo. This study establishes a "What You See Is What You Get" (WYSIWYG) methodology that provides a robust, scalable, and predictable framework for developing next-generation complex biopharmaceutical manufacturing cell lines.

Precise regulation of gene expression in batch bacterial cultures is challenging because the underlying dynamics vary with cellular physiological state over time. Although cell-silicon systems enable rapid, real-time optogenetic control, disturbance rejection remains difficult in batch culture because the plant dynamics shift across growth phases, limiting the effectiveness of fixed-gain controllers designed under constant-growth assumptions. Here, we present a multiscale model-guided feedback control framework for disturbance rejection in batch E. coli cultures. Frequency-response analysis shows that the input-output dynamics of gene expression depend strongly on growth phase, revealing operating-point-dependent limits on the disturbance rejection performance of a fixed-gain PID controller. To address this limitation, we develop two growth-aware control strategies: a gain-scheduled PID (PID-GS) controller that adapts to cellular physiological state, and a gain-scheduled feedback-feedforward controller (PID-GS-FF) that further compensates for growth perturbations. We also introduce a controller evaluation framework that identifies three distinct operating regimes for targeted experimental validation. Together, these results show that accounting for growth-state-dependent dynamics is necessary for robust disturbance rejection in batch culture and provide a control-oriented framework for regulating living systems with shifting operating conditions.

Course-based Undergraduate Research Experiences (CUREs) have emerged as a transformative approach to science education, expanding access to authentic research opportunities beyond the traditional undergraduate research assistant (URA) training. By embedding research into a curriculum, CUREs engage a broad and diverse population of students in a classroom environment that emphasizes experimental design, data analysis, and scientific communication. However, this has been difficult to develop for fields such as plant synthetic biology due to the long timescales of plant transformation. One avenue around this problem is to utilize a recent innovation that enables high throughput and rapid screening of gRNA efficacy by leveraging viral-based delivery of guide RNAs (gRNAs). In this work, we develop and validate a CURE with undergraduate students at Colorado State University (CSU). Students worked in teams to design and test efficacy of gRNAs targeting a Cas9-based transcriptional repressor to different regions of the promoters of the three GIBBERELLIN INSENSITIVE 1 genes (GID1a, GID1b, and GID1c) in Arabidopsis thaliana. Over the semester, students generated and analyzed gene expression data to understand the efficiency of twelve new gRNAs. We further validated CURE student-identified gRNAs with an undergraduate research assistant (URA) that assessed target gene expression and phenotypic outcomes in stable transgenic lines expressing SynTF constructs with the strongest gRNAs from the class. We further describe the curriculum structure to facilitate adoption at other institutions and present student-generated datasets demonstrating the utility of ViN-based screening for identifying effective SynTF gRNAs for plant functional genomics and engineering. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/715601v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@13869f5org.highwire.dtl.DTLVardef@b469feorg.highwire.dtl.DTLVardef@9aa51borg.highwire.dtl.DTLVardef@cdc129_HPS_FORMAT_FIGEXP M_FIG C_FIG

Source-separated organics (SSO) are widely processed via anaerobic digestion to produce biogas, yet alternative conversion pathways could generate higher-value products. Here, we demonstrate long-term continuous production and recovery of medium-chain carboxylic acids (MCCAs) from SSO via microbial chain elongation using a bench-scale anaerobic bioreactor operated for 911 days. The reactor was fed with SSO samples collected from two full-scale municipal organics processing facilities in Toronto, Canada, capturing facility-specific and seasonal variability in SSO composition. MCCA production depended strongly on the availability of lactate as an electron donor, which varied with SSO preprocessing operations and outdoor collection temperatures. To mitigate product inhibition, an in-line extraction system using hollow-fiber polydimethylsiloxane (PDMS, also known as silicone) membranes was integrated with the anaerobic membrane bioreactor, providing a robust and solvent-free alternative to solvent-based extraction methods. Maximum MCCA yields reached 0.31 g MCCA/ g VSfeed, with notable octanoic acid production (up to 20% of total MCCA), and production rates up to 0.84 g L-1 d-1. Acidification of the alkaline extract produced a phase-separated MCCA-rich oil ([~]95% purity) without addition of downstream separation steps. Microbial community analysis of the reactor revealed enrichment of putative chain-elongating bacteria, including Eubacterium and Pseudoramibacter species, while shifts in SSO feedstock microbiomes influenced substrate availability and product spectra. These results demonstrate the feasibility of sustained MCCA production from municipal organic waste streams and highlight opportunities to integrate chain elongation with existing anaerobic digestion infrastructure.

Probiotic-based encapsulation offers unique advantages over purified enzymes, such as increased protection from thermal-, pH-, and protease-mediated degradation, for oral therapeutic delivery applications. However, one of the major disadvantages of whole-cell systems is lower reaction rate due to substrate-product transport limitations imposed by the cell membrane and/or wall. In this work, we explore the potential of different lactic acid bacteria (LAB) - Lacticaseibacillus rhamnosus GG (LGG), Lactococcus lactis (Ll), and Lactiplantibacillus plantarum (Lp) - as expression hosts for recombinant Anabaena variabilis phenylalanine ammonia-lyase (AvPAL*). AvPAL* is used as a therapeutic to treat Phenylketonuria (PKU), a rare autosomal recessive metabolic disorder. Among the three species tested, LGG showed the highest PAL activity followed by L. lactis. Next, we attempted to overcome mass transfer limitation in whole-cell biocatalysts in two ways - expression of heterologous transporters and treatment with different chemical surfactants. Engineered strains expressing heterologous transporters exhibited approximately 3-4-fold increased PAL activity, while chemical treatment did not improve reaction rates. This work highlights the challenges and advances in realizing the potential of LAB as biotherapeutics. Impact StatementOral delivery of phenylalanine ammonia-lyase (PAL) using engineered probiotics is a promising therapeutic strategy to treat Phenylketonuria (PKU). Although PAL expression has been reported in probiotic strains of Limosilactobacillus reuteri, Lactococcus lactis, and E. coli, a systematic comparison of lactic acid bacteria (LAB) is underexplored. This study explores the potential of multiple LAB as hosts for PAL expression and investigates strategies to improve whole cell enzymatic activity. The findings from this study provide a foundation for implementing LAB-based delivery of PAL and indicate an important step towards development of probiotic platform for PKU management.

Knock-out mutants are often used to study gene function by disrupting a specific gene and comparing the mutant to a wild-type strain. Reliable interpretation, however, requires that the two strains differ only by the intended mutation and that the observed phenotype is caused specifically by the deleted gene. In the highly polyploid cyanobacterium Synechocystis sp. PCC 6803, this is particularly challenging because incomplete segregation can mask genetic heterogeneity or secondary suppressor mutations. The genetic variation among laboratory wild-type lines can further confound phenotypic analyses. We show that these challenges can be addressed by routine strain validation via whole-genome sequencing (WGS). To this end, we developed and tested user friendly workflows for short-read (Illumina), long-read (Oxford Nanopore Technologies; ONT), and hybrid data, providing standardized quality control, variant calling, and structural variant detection. We benchmarked their performance in detecting single-nucleotide polymorphisms (SNPs), small indels, and structural variants using simulated datasets across different coverages and mixed populations. Applying the workflows to three Synechocystis sp. PCC 6803 wild-type lines revealed multiple sequence and structural differences relative to the reference genome, including previously undescribed genetic variants, underscoring the importance of documenting the strain background and the value of long-read sequencing. Characterization of two independent 6-phosphogluconate dehydrogenase (gnd) knock-out mutants and their complemented strains highlighted how a failed rescue can reveal a phenotype unrelated to the intended knock-out. An automated literature analysis revealed that only a minority of the investigated Synechocystis studies that used knock-out mutants included complementation as a control (39%), whereas this practice is more common in studies involving Escherichia coli (63%) and Saccharomyces cerevisiae (55%). Based on these results, we propose a practical guide for standardizing knock-out phenotyping in Synechocystis PCC 6803. Combined with accessible workflows for routine whole-genome validation, this framework aims to support more robust and reproducible knock-out studies in the future.

Xylella fastidiosa is a xylem-limited phytopathogen bacterium responsible for severe diseases in numerous plant species of major agricultural importance. Despite its economic impact, its metabolism remains poorly characterized due to the bacteriums fastidious growth and the limited availability of defined culture media. In this work, we reconstructed the first pangenome-based genome-scale metabolic model for X. fastidiosa, integrating the conserved metabolic capabilities of 18 strains representing five described subspecies. The resulting core metabolic model, Xfcore, was manually curated and used to investigate the metabolic potential of the species. Model simulations predict minimal nutritional requirements that guide the formulation of defined media capable of supporting biofilm formation in vitro. Analysis of the metabolic network also suggests an undescribed metabolic pathway that enables growth on acetate as a sole carbon source. Furthermore, the model predicts that X. fastidiosa could overproduce polyamines, compounds previously associated with virulence in other phytopathogens. Experimental analyses confirm the production and secretion of polyamines in several X. fastidiosa strains, providing the first in vitro evidence of polyamine production in this pathogen. These findings suggest that polyamine biosynthesis may represent an uncharacterized virulence factor in X. fastidiosa, potentially contributing to bacterial protection against host-induced oxidative stress. Overall, the Xfcore model provides a systems-level framework to explore the metabolism of X. fastidiosa, generate testable hypotheses about its physiology and virulence, and establish a basis for future strain-specific reconstructions and host-pathogen metabolic interaction studies.