Metabolic Engineering Communications

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.

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.

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

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 efficient production of food and biochemicals using microorganisms that utilize single-carbon feedstocks presents a promising approach for advancing a circular bioeconomy. Komagataella phaffii (formerly Pichia pastoris) is a methylotrophic yeast already widely used in industry, making it an attractive host for such applications. Recently, K. phaffii was converted into an autotrophic strain capable of assimilating CO2 into both biomass and secreted organic acids, using energy derived from dissimilation of methanol to CO2. In these strains, methanol oxidation is catalysed by an alcohol oxidase (Aox2), which transfers electrons to oxygen without conserving reducing equivalents. To address this limitation, in this study we explored redirecting methanol dissimilation through the native alcohol dehydrogenase (Adh2), coupling methanol oxidation with NADH generation to improve carbon efficiency. By deleting AOX2 and overexpressing ADH2, we generated Adh2-based autotrophic strains that exhibited growth rates comparable to the parental strain (0.007 h-{superscript 1}), while reducing specific CO2 production by 53% and increasing biomass yield (YX/MeOH) by 59%. We further applied this strategy to convert previously developed autotrophic strains producing itaconic acid and lactic acid into Adh2-dependent strains. Optimizing ADH2 expression through multicopy integration resulted in strains with approximately two-fold higher molar carbon efficiency (Y(X+P)/CO2) while achieving elevated product titers--2.2-fold for itaconic acid and 3.8-fold for lactic acid--relative to the parental strains. Our findings demonstrate that alcohol dehydrogenase-mediated methanol dissimilation can significantly improve yield and productivity of autotrophic K. phaffii strains, with broad implications for sustainable bioproduction from one-carbon substrates.

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

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.

The transcription factor Pho4 is crucial for the response to phosphate starvation in many fungi, and it has been linked to tolerance to alkalinization of the medium and to pathogenicity. It is widely accepted that it is encoded by a single gene. However, the industrially relevant yeast Komagataella phaffii might contain two Pho4-encoding genes (PAS_chr1-1_0265 and PAS_chr2-1_0177, designated here PHO4(A) and PHO4(B), respectively), which have never been functionally characterized. The phenotypic analysis of single and double mutants suggests that Pho4(B) plays a major role in the adaptation to Pi scarcity. While single mutants exhibited limited and non-overlapping phenotypic defects, the pho4(A) pho4(B) strain was sensitive to multiple types of stress, including phosphate starvation and alkaline pH. Transcriptomic analysis confirms that Pho4(B) is crucial for the transcriptional response to phosphate starvation, including induction of typical gene markers (PHO5, PHO89, VTC1, etc.). However, by using a GFP reporter we found that PHO4(A) also participates in the induction of PHO89 under high pH stress. Expression of both PHO4(A) and PHO4(B) in S. cerevisiae complemented the pho4 mutation under phosphate limitation by restoring growth, expression of the Pho84 transporter and secreted phosphatase activity. These results indicate that both transcription factors display partially overlapping functions, responding differently to diverse stimuli, and that together they constitute a key component in the adaptation to a variety of stresses. Therefore, K. phaffii is an exceptional example among fungi that encodes two Pho4 functional transcription factors.

Biological carbon fixation is currently limited to seven naturally occurring pathways, each with its own limitations and constraints. In recent years, computational analyses of known biochemical reaction networks have identified dozens of theoretical carbon fixation pathways, some of which may have the potential to outperform their natural counterparts. This mix-and-match approach, however, cannot account for those reactions that have not been reported to occur in nature, which heavily limits the possible solution space. Here, we use a bioretrosynthetic approach coupled with expert biochemical knowledge to identify several novel pathways that leverage enzyme promiscuity and the latent biochemical reaction space. We analyze the thermodynamic, stoichiometric, and kinetic parameters of these pathways and compare them to the ubiquitous Calvin-Benson-Bassham cycle and previously proposed synthetic CO2 fixation cycles, highlighting advantages and disadvantages. We identify several promising pathways that could potentially outcompete the Calvin cycle and other previously proposed synthetic CO2 fixation pathways in predicted biomass yield and/or overall pathway activity. In addition, unlike most of the previously proposed efficient mix-and-match pathways, the pathways proposed in this work do not require vitamin B12, which is an advantage for future implementation in plants or microalgae that typically lack B12 biosynthesis. This work highlights the need for enzyme engineering and design in the quest for efficient biological carbon fixation.

The hydrolytic breakdown of cellobiose into glucose, catalysed by {beta}-glucosidases, is the last and rate-limiting step in cellulose saccharification for producing fermentable glucose in the bioethanol industry. This limitation arises because {beta}-glucosidase activity is inhibited by factors such as temperature, pH, and glucose accumulation in reactors. Enzyme inactivation leads to the buildup of cello-oligosaccharides, which, in turn, inhibit upstream cellulases. Therefore, glucose-tolerant {beta}-glucosidases are preferred for the formulation of industrial cellulase cocktails. In this study, we have recombinantly expressed, purified, and biochemically characterised a {beta}-glucosidase from the cellulolytic fungus Fusarium odoratissimum (FoBgl-WT). FoBgl-WT exhibits optimal cellobiose hydrolysis over a broad pH range (4.5-7.5), an important and industrially desirable property for its application in bioreactors. However, the glucose tolerance of FoBgl-WT was [~]0.56 M. Structure-based analyses were carried out to map the residues lining the active site of FoBgl, and their roles in stabilising the product glucose (or even the substrate, cellobiose) were elucidated through a series of site-specific mutations, followed by biochemical characterisation of the resulting FoBgl mutants. Among all the mutants generated, FoBgl-K256I-Y325F exhibits >2.5-fold greater glucose tolerance ([~]1.4 M) than FoBgl-WT. Further, we have observed that the FoBgl-K256W and FoBgl-K256I mutants exhibit improved kinetic properties, such as catalytic efficiencies. The structure-based rational engineering efforts improve glucose tolerance and the kinetic properties of FoBgl mutants, making it a useful and promising candidate enzyme for industrial cellulase cocktails.

Design-Build-Test-Learn (DBTL) cycles are a widely employed engineering framework in metabolic engineering. Nonetheless, their performance depends on a wide range of experimental and algorithmic design choices, whose combined effects on the successful optimization of microbial strains remain an open question. In this study, we performed in-silico DBTL cycles based on metabolic kinetic models to quantitatively assess how key process parameters affect strain optimization outcomes across four distinct metabolic pathway models. This includes parameters governing DNA library design, experimental budget limitations, and machine learning configuration. The results show that screening capacity is a dominant driver of optimization success, whereas DNA sequencing capacity has surprisingly little impact, despite its importance for model training. Selecting top-producing strains for sequencing consistently outperforms stratified sampling, highlighting a trade-off between predictive accuracy and optimization efficiency. DNA library structure strongly affects performance: increasing the number of editable positions generally improves outcomes, while expanding the set of gene targets can hinder optimization due to increased dimensionality or sparse sampling. Together, these findings offer actionable guidance for designing more effective DBTL workflows and underscore the value of simulation frameworks for exploring metabolic engineering strategies prior to experimental implementation.

Combinatorial DNA design and assembly is an efficient and pragmatic way to obtain high-performing metabolic pathway designs quickly. However, implementation may require organism-specific technical barriers to be overcome. Firstly, suitable expression control parts such as promoters and ribosome-binding sites (RBSs) which provide a suitable range of expression levels need to be identified or developed. Secondly, these need to be assembled into pathway-encoding combinatorial libraries of sufficient size, quality and diversity. For organisms with transformation frequencies too low to allow direct transformation of library assembly reactions, such as many Clostridium spp., assembly and amplification is typically carried out using Escherichia coli. However, if constructs are deleterious (or burdensome) to E. coli, which is often the case when using Clostridium genetic parts, poor libraries may be obtained. Here we develop a new approach called integration-coupled activation of promoterless sequences (ICAPS) to overcome this barrier and therefore enable combinatorial assembly in Clostridium. Libraries were designed and assembled as promoterless synthetic operons, preventing expression during DNA assembly, and expression was only activated later, when constructs were integrated into the host genome downstream of a promoter. Variation of expression levels was achieved using a range of context-resistant RBS sequences. This approach was used to produce a Clostridium acetobutylicum library with combinatorial expression variants of an introduced hexanol pathway. This proof of concept provides a generally-applicable approach to implement combinatorial metabolic pathway-encoding libraries in Clostridium spp., circumventing the excessive strength of Clostridium expression control parts in E. coli, and is applicable to other organisms.

This study explores computational design predictions related to experimental enzyme behavior by analyzing seven single-point mutants of {beta}-glucosidase B (BglB) from Paenibacillus polymyxa: Y333F, A88E, L219Q, A408H, Y173L, E340S, and Y422F. Each mutation was modeled using Foldit Standalone, and mutant selections were based on predicted thermodynamic stability changes of interest. Six of the seven mutants in this set yielded soluble, expressed protein. Most variants had similar catalytic efficiency compared to the wild type with one exception. The melting temperatures for most variants were also similar to the wild type. Correlation analysis revealed weak but potentially informative relationships between predicted {Delta}TSE and (a) thermal stability and (b) catalytic efficiency. These results further support known limitations of TSE score as a tool for single point mutation design and add to a growing dataset being generated to build the next generation of functionally predictive protein models.

Poly({varepsilon}-caprolactone) (PCL) is a well-known biodegradable polyester and is among the few polyesters susceptible to degradation in marine environments; however, marine-derived PCL-degrading enzymes remain poorly characterized. Here, we searched for PCL-degrading enzymes from the marine bacterium Alloacanivorax gelatiniphagus JCM 18425 using a genome-based approach. Five candidate genes were predicted, and one encoded protein, designated Ag0826, was identified as a PCL depolymerase. Recombinant Ag0826 was expressed, purified, and biochemically characterized. The enzyme exhibited optimal activity at 35-40{degrees}C and pH 8.0, although it showed limited thermal stability. Substrate specificity was compared with that of leaf-branch compost cutinase (LCC), a well-characterized poly(ethylene terephthalate) (PET) hydrolase, using various polyesters. Both enzymes exhibited largely overlapping substrate ranges with respect to the presence or absence of monomer conversion activity across the tested substrates. Ag0826 slightly degraded PET to terephthalic acid, indicating potential PET-hydrolyzing activity; its conversion rate, however, was substantially lower than that of LCC, suggesting that Ag0826 exhibits a substrate preference differing from LCC. Phylogenetic analysis based on amino acid sequences revealed that Ag0826 formed a separate clade from LCC and IsPETase (from Ideonella sakaiensis). At a broader level, Ag0826 was positioned near HaloPETase1 (from Halopseudomonas pachastrellae), which has been proposed as a Type III PET hydrolase; in contrast, residues corresponding to the substrate-binding subsites were similar but not identical between the two enzymes. These results suggest that Ag0826 broadly belongs to the group of known PET hydrolases, yet it exhibits a partially distinct sequence profile even within this enzyme family.

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.

CO dehydrogenases (CODH) are metalloenzymes that reversibly oxidize CO to CO2, at a buried NiFe4S4 active site. The substrates, CO and CO2, need therefore to be transported through the protein matrix to reach the active site. The most likely pathway for intra-protein diffusion is the hydrophobic channel identified in the crystal structures. Here, we use site-directed mutagenesis to study the highly conserved isoleucine 563 of Thermococcus sp. AM4 CODH2. Mutations at this position change the biochemical properties (KM for CO, product inhibition constant, catalytic bias...), and increase the resistance of the enzyme to the inhibitor O2, showing that isoleucine 563 indeed lines the gas channel. The I563F mutation decreases the bimolecular rate constant of inhibition by O2 15-fold, and increases the IC50 20-fold, which is the strongest improvement in O2 resistance reported so far. We show that the size of the introduced amino acids is less important than their flexibility - along with the size of the cavity formed near the active site in the channel. We also conclude that O2 access to the active site cannot be slowed down without also affecting CO diffusion. This tradeoff will have to be considered in further attempts to use site-directed mutagenesis to make CODHs more O2 tolerant.

Acetogens are promising microbes for sustainable biomanufacturing but improving acetogen gas fermentation requires efficient conversion of CO and CO2 into fuels and chemicals. Carbon monoxide dehydrogenase (CODH) enzymes couple carbon fixation to energy conservation in acetogens and serve as potential regulatory modules for tuning autotrophic metabolism. Intriguingly, the model-acetogen Clostridium autoethanogenum lost its unique truncation in the bifunctional CODH (acsA), essential for autotrophy, during autotrophic adaptive laboratory evolution while obtaining superior phenotypes. Additionally, protein expression of the monofunctional CODH cooS1 is high and conditionally-regulated in C. autoethanogenum. Here, we genetically engineered CODHs in C. autoethanogenum by replacing the stop codon in acsA with leucine (strain Leu_SNP) or serine (Ser_SNP), and deleting cooS1 ({Delta}cooS1). Phenotyping in autotrophic batch and chemostat cultures revealed altered growth profiles and significant redistribution of carbon and redox flows in SNP strains, whereas {Delta}cooS1 showed moderate and condition-dependent effects. Surprisingly, structural modelling identified no conformational differences between wild-type and mutant AcsA proteins. While transcriptomics showed limited transcriptional changes in {Delta}cooS1, it suggested potential transcriptional adjustments linked to reduced robustness and altered product profile of Leu_SNP. Our results demonstrate the impact of CODHs on autotrophy and offer targets for rational engineering of acetogen cell factories.

Rhamnolipids (RLs) are versatile biosurfactants produced by Pseudomonas aeruginosa with significant industrial potential. However, high production costs remain a barrier to large-scale use, necessitating genetic strategies to improve yields. While many genes are reported to influence RL production, studies often rely on qualitative phenotypic assays of questionable reliability. We systematically evaluated 29 P. aeruginosa PA14 mutants using traditional assays (Siegmund-Wagner blue plates, swarming motility) and validated the findings using Liquid Chromatography-Mass Spectrometry (LC/MS). We found that traditional phenotypic assays have a high misprediction rate ([~]35-38%), primarily due to confounding factors like variable flagellar function, colony spreading, and growth rates. Specifically, LC/MS quantification revealed that rpoN and pvdQ knockouts significantly increased total rhamnolipid titers, whereas crc, dksA, and dspI knockouts decreased production. Notably, the increased titers in rpoN and pvdQ mutants were linked to enhanced biomass accumulation rather than higher per-cell biosynthetic rates. These findings highlight the critical necessity of using quantitative analytical methods for accurate strain screening and provide a clarified set of genetic targets for metabolic engineering aimed at optimizing rhamnolipid production. ImportanceThis study addresses a critical methodological flaw in biosurfactant research: the over-reliance on qualitative phenotypic assays that too often lead to inaccurate conclusions. By systematically comparing traditional screening methods with LC/MS quantification across a collection of Pseudomonas aeruginosa mutants, we demonstrate that common assays like swarming motility and blue plates fail to accurately predict rhamnolipid production in over one-third of cases. These inaccuracies lead to the misidentification of genetic targets and may waste resources in metabolic engineering efforts. Our work provides a reliable framework for strain screening, identifies specific genes that influence rhamnolipid yields, and clarifies the biological factors--such as flagellar motility and growth dynamics--that bias traditional results. These findings are essential to optimize biosurfactant production and ensure data reproducibility.

Biomass separation represents a critical bottleneck in Komagataella phaffii-based biopharmaceutical processes, as typically high cell densities of 40 - 50 % create significant operational, technical and economic challenges for harvest operations. Yeast cell aggregation (flocculation) provides a solution to accelerate cell sedimentation by increasing particle size, thus allowing to improve biomass-supernatant separation efficiency during both natural gravity settling and (continuous) centrifugation operations. This study demonstrates successful engineering of K. phaffii strains with an inducible flocculation phenotype using CRISPR/Cas9-based genome editing to integrate the Saccharomyces cerevisiae FLO1 (ScFLO1) gene under control of various regulatory elements, including methanol-inducible and derepressible promoters. Flocculation strength could be enhanced by implementing transcriptional positive feedback circuits based on the methanol-inducible AOX1 promoter. To address methanol-free production requirements, we developed alternative systems to retrofit PAOX1-based ScFLO1 expression and exploited the derepressible PDF promoter, offering broader compatibility with biopharmaceutical manufacturing facilities. Flocculating cells cultivated in a bioreactor demonstrated significantly improved sedimentation behavior, with considerably lower supernatant turbidity after short low-speed centrifugation compared to non-flocculating controls. Crucially, cell flocculation had no negative impact on product amount and quality when expressing a multivalent NANOBODY(R) VHH molecule with pharmaceutical relevance. Thus, this work establishes the first genetically engineered flocculation system in K. phaffii compatible with recombinant protein production, providing the basis for an innovative approach to streamline harvest operations in biopharmaceutical processes.

Prokaryotic transcription factors (TFs) are used as small molecule biosensors with broad applications in biotechnology, yet only a small fraction from microbial genomes have been characterized. To address this gap, we recently described the bioinformatic method Ligify, which leverages information from genome context and enzyme reaction databases to predict a TFs cognate effector molecule. Here we report Ligify 2.0, a modern web server for Ligify predictions. We systematically evaluate 10,965 small molecules within the Rhea enzyme reaction database for associations to TFs, ultimately generating 13,435 hypothetical interactions between 1,362 small molecules and 3,164 TFs. We then develop an interactive web server (https://ligify.groov.bio) to search and visualize prediction data. Each TF sensor page includes visualizations for chemical ligand structures, interactive TF protein structures, and genome context. Pages also include metadata links, predicted promoter sequences, prediction confidence metrics, and references to relevant literature. A plasmid builder tool enables users to generate custom biosensor circuit designs. Finally, we provide case studies using Ligify 2.0 to identify two TFs from the pathogens Escherichia coli O157:H7 and Mycobacterium abscessus responsive to 4-hydroxybenzoate and Pseudomonas Quinolone Signal, respectively. The Ligify web server aims to facilitate the systematic characterization of biosensors for chemical-control of biological systems. Key pointsO_LILigify 2.0 contains >13,000 predicted transcription factor-small molecule interactions C_LIO_LIA rich web interface provides interactive visualizations and a plasmid design tool C_LIO_LIPredicted ligands for regulators from pathogenic bacteria are experimentally validated C_LI Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/683484v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1afa575org.highwire.dtl.DTLVardef@97c811org.highwire.dtl.DTLVardef@cfdb93org.highwire.dtl.DTLVardef@58977d_HPS_FORMAT_FIGEXP M_FIG C_FIG