ACS Synthetic Biology

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

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.

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.

Cancer therapeutics are increasingly incorporating engineered receptors due to their ability to detect extracellular ligands and initiate intracellular responses that regulate gene expression. By redesigning these natural signaling systems, synthetic receptors hold great potential for use in novel cell-based therapies. One particularly promising direction is modifying the Notch receptor, a transmembrane protein that naturally mediates ligand-dependent signaling at the cell surface to regulate cell proliferation and differentiation in neurogenesis. Both the intracellular and extracellular domains of Notch can be replaced with alternative domains, creating the family of modified Notch receptors known as synthetic Notch (synNotch). In existing synNotch-activated chimeric antigen receptor (CAR) T-cells, the extracellular domain can be engineered to adjust binding affinity for a specific cancer antigen, enabling precise tuning of therapeutic activity while minimizing off-target effects. To quantify and inform such tuning, we develop differential equations models of synNotch receptor signaling and subsequent gene expression. The mathematical models couple activation dynamics on fast timescales (characteristic of receptor-ligand interactions) and on slow timescales (characteristic of downstream gene expression dynamics). Global Sobol sensitivity analysis of the proposed models highlights parameters that yield the greatest variability in synNotch signal transduction and gene expression, indicating their potential to be engineered for different functions in future cancer therapeutics. For the receptor-ligand interactions in the synNotch model, we find that ligand association and ligand-independent activation are the most sensitive parameters. In the downstream gene expression model, promoter strength and degradation rates of mRNA and gene product are found to be most amenable to engineering.

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

Cell-free expression systems (CFES) are increasingly used alongside conventional biotechnological approaches to accelerate early-stage prototyping and are particularly valuable in point-of-use settings. However, their broader adoption remains limited by time- and cost-intensive preparation, as well as stringent cryogenic storage requirements. To address this, several studies have explored lyophilization with protective additives to generate stable, solid-state CFES. These approaches had to balance the protection gained with a loss of activity due to the additives. In this study, we present a CFES that contains a tardigrade-derived Cytosolic-Abundant Heat-Soluble (CAHS) protein to protect the biosynthetic machinery in lysates from damages during drying. We show that the CAHS protein, without any other additives, preserves protein synthesis activity during low-cost room temperature desiccation, while unprotected lysates are affected in mRNA synthesis kinetics and translation yields. The diversity of tardigrade-derived protective proteins is a treasure trove for cell-free synthetic biology, in particular for making CFES more accessible and portable. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/715078v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@8ecc2eorg.highwire.dtl.DTLVardef@ff0432org.highwire.dtl.DTLVardef@6c940eorg.highwire.dtl.DTLVardef@6c5390_HPS_FORMAT_FIGEXP M_FIG C_FIG

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.

Biocompatible fluorosurfactants are essential for many droplet microfluidic workflows but are often obtained from commercial sources because published syntheses of perfluoropolyether (PFPE)-based surfactants typically require acid chloride intermediates and chemistry-oriented purification methods. These requirements can limit access for biology and clinical laboratories seeking low-cost or customizable surfactant systems. Here we describe a practical method for preparing functional PFPE-based fluorosurfactant materials by direct carbodiimide coupling of functionalized PFPE carboxylic acids(Krytox 157 FSH) to amine-containing head groups under laboratory-accessible conditions. Using this approach, we prepared a PFPE-polyethylene-glycol (PFPE-PEG) material from Jeffamine ED900 and a PFPE-Tris material from Tris base. Because these products were not fully structurally characterized, we present them as functional reaction products and evaluate them by use in biomicrofluidic workflows rather than by definitive compositional assignment. PFPE-Tris was useful for generating relatively uniform small droplets, whereas the PFPE-PEG preparation supported a broader range of biological applications. These materials were used in genomic library screening for {beta}-glucosidase activity, thermocycling-associated droplet workflows, and protein crystallization experiments. In addition, the PFPE-PEG preparation improved emulsion behavior in many protein crystallization screens that were unstable with a commercial droplet oil used in our laboratory. This method reduces the practical barrier to in-house fluorosurfactant preparation and allows biology-focused laboratories to explore head-group chemistry, oil composition, and operating conditions without complete reliance on commercial reagents. The results support this workflow as a useful entry point for biomicrofluidics laboratories, while also highlighting the need for careful interpretation of thermocycled droplet assays and for future analytical characterization of the resulting materials. Significance statementDroplet microfluidics relies on fluorosurfactants that are often costly and difficult to synthesize outside of chemistry-focused settings. We describe a simple, biology-laboratory-compatible approach for generating functional perfluoropolyether-based fluorosurfactant materials using direct carbodiimide coupling and straightforward cleanup. The resulting materials supported multiple biomicrofluidic workflows in our laboratory, including enzymatic screening and protein crystallization, and provide a practical route for groups seeking lower-cost and more customizable surfactant systems.

Combinatorial mutagenesis is essential for exploring protein sequence-function landscapes in engineering applications. However, while large-scale machine learning benchmarks exist for protein function prediction, they are primarily limited to single-mutant libraries, leaving a critical gap for combinatorial mutagenesis. Here we introduce CombinGym, a benchmarking platform featuring 14 curated combinatorial mutagenesis datasets spanning 9 proteins with diverse functional properties including binding affinity, fluorescence, and enzymatic activities. We evaluated nine machine learning algorithms from five methodological categories (alignment-based, protein language, structure-based, sequence-label, and substitution-based) across multiple prediction tasks, assessing both zero-shot and supervised learning performance using Spearmans {rho} and Normalized Discounted Cumulative Gain metrics. Our analysis reveals the substantial impact of measurement noise and data processing strategies on model performance. By implementing hierarchical dataset splits (0-vs-rest, 1-vs-rest, 2-vs-rest, and 3-vs-rest scenarios), we demonstrate the value of lower-order mutation data for empowering machine learning models to predict higher-order mutant properties. We validated this capacity through both in silico simulation (improving fluorescence brightness of an oxygen-independent fluorescent protein) and experimental validation (engineering enzyme substrate specificity), achieving a substantial increase in specific activity. All datasets, benchmarks, and metrics are available through an interactive website (https://www.combingym.org), facilitating collaborative dataset expansion and model development through integration with automated biofoundry platforms.

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

Protein synthesis using recombinant elements (PURE) system has been widely applied in various biological research fields and synthetic cell construction. Optimization efforts to enhance the PURE system performance by adjusting its individual components have remained limited to the expression of single genes with a small number of molecular compositions tested, making it difficult to link component composition to system-level performance across different DNA contexts. Here, we combine automated acoustic liquid handling with an active learning framework to explore broadly the compositional landscape of PURE system. By grouping the 69 individual components (including proteins and tRNAs) into 21 functional sets and iteratively guiding experiments with active learning, we rapidly identify improved compositions and demonstrated up to 3-fold enhancement in protein yield and translation rate for a single reporter gene. We further show that optimization drivers differ between low and high DNA concentrations, revealing that optimal PURE compositions are DNA concentration-dependent. We then apply this optimization strategy to enhance the expression of a 41-kb synthetic chromosome containing 15 genes by maximizing the fluorescence intensities of two reporter proteins. While a 3-fold improvement could be reached on the two gene products guiding learning, a full proteomic analysis revealed that optimization is gene-specific, i.e., changes in PURE system compositions differently impact the amounts of synthesized proteins encoded on the same DNA template. Together, this work establishes active learning as an efficient strategy to navigate the high-dimensional PURE compositional space and provides mechanistic insight into DNA context-dependence of gene expression optimization.

Engineering bacterial promoters to integrate multiple regulatory signals remains a formidable challenge. Juxtaposing operator sites frequently increases basal leakiness, compresses the fully induced state, and introduces severe sequence-context dependencies. Here, we systematically engineered two-input combinatorial promoters in Escherichia coli that integrate signals from multiple transcription factors. To achieve precise operational control over these regulators, we drove the promoters using highly optimised, small-molecule-responsive sensors from the Marionette transcription-factor cassette, allowing us to assemble 19 reporter-specific, four-state truth tables across 12 distinct promoter architectures. We evaluated each design against a stringent statistical criterion for inducer-conditioned coincidence responses. Nine architectures satisfied this criterion, yielding a robust set of operational AND switches. By comparing successful and unsuccessful designs, we reveal that performance hinges primarily on suppressing partially induced states, ensuring structural compatibility between the promoter scaffold and the inserted operator, and precisely managing the orientation of long operators to avoid recreating unintended promoter-like motifs. Furthermore, reciprocal architectures and alternate downstream reporters frequently display divergent behaviours, underscoring profound asymmetries and local genetic-context dependencies. Ultimately, these findings deliver versatile combinatorial switches alongside practical, sequence-aware design rules for engineering multi-input bacterial promoters.

Efficient production of human proteins for the development of tool compounds and biologics depends on a detailed understanding of the protein expression machinery in mammalian cells. Codon optimization is widely believed to enhance protein yield, yet its impact in homologous mammalian systems remains poorly defined. Here, we systematically compare five codon usage strategies reflecting common assumptions about rare codons, RNA stability, and synthesis efficiency. We developed pTipi, an efficient open-source mammalian expression vector, and evaluated its performance in antibody production. We generated plasmids for common epitope tag antibodies such as V5, anti-biotin and anti-His for distribution by Addgene. To compare codon usage schemes, we performed a bake-off of 18 human and murine Wnt pathway glycoproteins in mammalian cells. Small-scale expression screens revealed that codon optimization did not provide a general advantage over native coding sequences, while strategies prioritizing RNA stability consistently reduced expression. Interestingly, a skewed codon scheme using the most abundant codons produced yields comparable to native sequences and occasionally enhanced protein output. To enable flexible evaluation of codon strategies, we implemented a Golden Gate-compatible pTipi platform for efficient synthetic gene incorporation. We conclude that native codons are sufficient for robust homologous mammalian expression of glycoproteins, while selective codon skewing can be beneficial for some targets.

The design of maximally divergent DNA sequences translating into the same protein is a critical problem in synthetic biology. Current design tools that rely on heuristics or machine learning often fail to effectively minimize the length of shared subsequences between the gene copies, compromising strain stability. Here, we introduce SIRIUS, a combinatorial optimization algorithm designed to generate maximally divergent coding sequences for a given protein of interest. Leveraging integer linear programming enforcing host-specific codon usage thresholds, SIRIUS stabilizes synthetic constructs and broadens the accessible design space for robust and scalable synethtic biology. Experimental results show that SIRIUS produces diverse sequences with fewer shared subsequences than existing methods. SIRIUS is freely available on GitHub at https://github.com/ucrbioinfo/sirius.

Despite >50 years of methods development, specific antibodies are still generated at low throughput and remain in high demand across biotechnology. Most biologics and immunoprobes are monoclonal antibodies, developed using a combination of inoculating animals with a target antigen, engineered candidate libraries, and multiple rounds of selection using phage or yeast display. Here we introduce a synthetic biology scheme to eliminate the need for nearly all of these steps, by combining Surface display on E. coli and Phage display with the microvirus {Phi}X174, Assisting Continuous Evolution (SurPhACE). Instead of building libraries for screening, SurPhACE runs a closed evolutionary program. A typical experiment can have 1011 mutant candidates under active selection, with complete turnover of the mutant population every 30min, or >5x1012 unique mutants per day, using less than 100mL of bacterial culture media. We demonstrate SurPhACE for optimizing a nanobody to a related epitope, and develop novel nanobodies for an arbitrary target using a minimal starting library to establish a proof of concept and identify best practices for this scalable method for generating protein binders.

The bottom-up construction of synthetic cells based on giant unilamellar vesicles (GUVs) is a central goal in synthetic biology. Achieving targeted changes in membrane and cytoplasmic composition with temporal control remains challenging however. DNA-mediated fusion with small vesicles ([~]100 nm large unilamellar vesicles; LUVs) has been proposed as a strategy to deliver lipids and cytosolic contents in a programmable manner. However, in vitro, membrane fusion is generally found to be inefficient and poorly controllable for reasons that are poorly understood. Here, we present an approach based on lipid-conjugated DNA (LiNA) to mediate programmable fusion between LUVs and micron-sized GUVs, which we quantitatively monitor with confocal microscopy at the single-GUV level. We show that lipid and content mixing both occur with high efficiency over a wide range of LiNA concentrations, demonstrating that LiNAs indeed induce robust membrane fusion. Furthermore, we show that LiNA-mediated fusion provides a powerful tool to deliver cytosolic biomolecules, enabling control over internal activities. Our findings establish a quantitative framework for studying fusion-driven processes in synthetic cells and provide a versatile platform for the programmable delivery of lipids and cytosolic cargoes - thus advancing the development of synthetic cells that can grow and adapt through fusion-based uptake of molecular building blocks.

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.

Optogenetics enables researchers to control protein localization, interactions, and activity using photosensitive domains. The key desired properties for optogenetic tools include broad applicability, tight light-regulated control with high dynamic range, and tunability. Previously, we described an engineered light-sensitive switch, LightR, composed of two VVD domains connected by a flexible linker, enabling light-dependent allosteric control of protein activity through site-specific insertion. Here, we introduce enhanced LightR variants with improved dynamic range and faster activation kinetics. Through targeted modifications to the VVD domains and linker region, we optimized a LightR-regulated Src kinase (LightR-Src) activity and generated two LightR-Src variants: one supporting sustained Src activation comparable to constitutively active Src, and another enabling rapid, reversible control, ideal for modeling transient signaling events suitable to mimic Src signaling in living cells. These modifications expand the versatility of LightR-based tools, facilitating their use in diverse optogenetic applications requiring high dynamic range of regulation and fast control of targeted proteins.

Bacterial microcompartments (BMCs) are proteinaceous organelles that spatially organize metabolic reactions in bacteria and represent an attractive scaffold for pathway engineering. Here, we present a proof-of-concept in vitro study demonstrating a simple, scalable, and modular BMC shell-based platform for enzyme encapsulation using the SpyCatcher-SpyTag (SC-ST) covalent conjugation system. To evaluate the generality of this approach, 16 dehydrogenases were selected, of which 13 were successfully expressed and purified as SC-tagged enzymes in E. coli by five research groups working in parallel. Twelve of these efficiently conjugated to ST-fused BMC-T1 proteins, and addition of urea-solubilized BMC-H triggered rapid self-assembly of HT1 shells, resulting in successful encapsulation of all conjugated enzymes. The only enzyme lacking detectable activity after encapsulation was also inactive in its free SC-fused form, indicating that encapsulation retained enzymatic activity for all tested enzymes. Encapsulation modulated enzymatic activity and kinetic parameters in an enzyme-dependent manner, likely arising from variations in catalytic mechanism, structural flexibility affected by immobilization, and sensitivity to the local microenvironment created by encapsulation. Functional characterization of a subset of encapsulated enzymes revealed enhanced thermal stability up to [~]50 {degrees}C and improved storage stability relative to free SC-fused enzymes. Enzyme-loaded shells could be lyophilized and reconstituted without loss of structural integrity or activity. Finally, we demonstrate co-encapsulation of two enzymes within a single shell and their cooperative function through cofactor recycling. Together, these results establish engineered BMCs as a robust and modular platform for organizing multi-enzyme pathways, enabling rapid assembly, stabilization, and functional integration of enzymes for diverse metabolic engineering applications. HighlightsA single strategy enables encapsulation of 12 diverse dehydrogenases in BMCs. SpyCatcher-SpyTag interactions drive rapid enzyme assembly in BMCs. Encapsulated enzymes are active and show improved thermal stability. The platform enables scalable construction of synthetic metabolic modules. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/712704v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1e56ffborg.highwire.dtl.DTLVardef@1ac8b5org.highwire.dtl.DTLVardef@6f23c1org.highwire.dtl.DTLVardef@945c54_HPS_FORMAT_FIGEXP M_FIG C_FIG

Efficient protein synthesis in eukaryotic cells typically requires a 5' cap structure on messenger RNAs (mRNAs). However, under stress conditions or in viral infection, translation can also occur independently of the cap via internal ribosomal entry sites (IRES). IRES elements are therefore key regulators of protein expression in both viral and cellular contexts. Here we describe a cell-free protocol to quantitatively assess IRES-mediated translation using wheat germ extract (WGE) and a firefly luciferase (FLuc) reporter. The protocol includes template preparation, RNA synthesis and luminescence measurement following in vitro translation in WGE. This method enables rapid and robust comparison of IRES activity under controlled conditions and can additionally be applied to evaluate mRNA modifications designed to enhance translation efficiency. Key featuresO_LIStringent in vitro workflow from DNA template preparation through RNA synthesis and protein synthesis to reporter readout, including quality controls. C_LIO_LIEvaluation of IRES-driven translation suitable for testing combinations of IRES and CDS. C_LIO_LItranslation analysis without radioactive labeling. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/716985v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@417649org.highwire.dtl.DTLVardef@1bcd186org.highwire.dtl.DTLVardef@15fecb3org.highwire.dtl.DTLVardef@acdf8d_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractPipeline for the production and evaluation of IRES-firefly luciferase constructs using wheat germ extract. (1-4) Preparation: IRES-firefly luciferase constructs are amplified in E. coli and isolated from bacterial cells. Plasmids are linearized to prepare for in vitro transcription. (5-6) Transcript synthesis and verification: In vitro transcription is followed by electrophoretic validation to confirm integrity and correct molecular weight. (7-8) Translation and detection: Translation is executed in wheat germ extract and quantified by measuring reporter activity in a luminometer.