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Data for "Photoinduced Chemomimetic Biocatalysis for Enantioselective Intermolecular Radical Conjugate Addition"

Exploiting nature’s catalysts for non-natural transformations that are inaccessible to chemocatalysis is highly desirable but challenging. On the one hand, the widespread nicotinamide-dependent oxidoreductases have not been utilized for single-electron-transfer-induced bimolecular cross-couplings; on the other, the addition of catalytic asymmetric radical conjugate to terminal alkenes remains a challenge owing to strong racemic background reaction and unselective termination of prochiral radical species. Here we report a chemomimetic biocatalysitic approach for construction of alpha-carbonyl stereocentres via an unnatural intermolecular conjugate addition of N-(acyloxy)phthalimides-derived radicals with acceptor-substituted terminal alkenes, by combination of visible-light excitation and nicotinamide-dependent ketoreductases (KREDs). Based on protein crystal structure, we engineered KREDs via a semi-rational mutagenesis strategy to improve reaction outcomes with a small and high-quality variants library. Mechanistic investigations combining wet experiments, crystallographic studies and computational simulations demonstrate that the repurposed biocatalyst can suppress racemic background reaction and unselected side reactions, yielding enantioselectivity that is challenging to achieve by chemocatalysis.

Catalysis

Engineering a photoenzyme to use red light

Photoenzymatic reactions involving flavin-dependent “ene”-reductases (EREDs) rely on protein-templated charge transfer (CT) complexes between the cofactor and substrate for radical initiation. These complexes typically absorb in the blue region of the electromagnetic spectrum. Here, we engineered an ERED to form CT complexes that absorb red light. Mechanistic studies indicate that red-light activity is due to the growth of a red-absorbing shoulder off the previously identified cyan absorption feature. Molecular dynamics simulations, docking, and excited-state calculations suggest that the cyan feature involves a π→π* transition on flavin, whereas the red-light absorption is a π→π* transition between flavin and the substrate. Furthermore, differences in the electronic transition are due to changes in the substrate-binding conformation and allosteric tuning of the electronic structure of the cofactor-substrate complex. Microenvironment tuning of the CT complex for red-light activity is observed with other engineered photoenzymatic reactions, highlighting this effect’s generality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Towards chloroplastic nanofactories: formation of proteinaceous scaffolds for metabolic engineering

The evolution of eukaryotic lipid-bound organelles allows for specialized metabolism to occur within spatially distinct metabolic landscapes within the same cell. However, this strategy of compartmentalization is not unique to eukaryotic organisms. Many bacteria, spread across 45 different phyla, contain loci that encode for specialized bacterial microcompartments (BMCs) (Sutter et al., 2021). The formation of a BMC involves self-assembly from three families of shell proteins to form the outer shell membrane, in addition to the encapsulation of an enzymatic core packaged within the lumen of a BMC (Kerfeld et al., 2018). These proteinaceous organelles provide a competitive growth advantage by enabling organisms to process inaccessible substrates by sequestering metabolic intermediates (i.e. aldehydes) that would otherwise be toxic within the cytoplasm. While BMCs perform specific metabolic functions in their native organism, synthetic, empty BMC shells can form without the requirement of native cargo inside (Doron and Kerfeld, 2024). This provides a transferable and tunable platform of protein scaffolding for guiding metabolic engineering within a host organism of choice (Raba and Kerfeld, 2022).

59 BASIC BIOLOGICAL SCIENCES

Systematic Mapping of Bacterial CRISPRa Systems for Synergistic Gene Activation Reveals Antagonistic Effects

CRISPR gene activation (CRISPRa) tools have shown great promise for bacterial strain engineering but often require customization for each intended application. Our goal is to create generalizable CRISPRa tools that can overcome previous limitations of gene activation in bacteria. In eukaryotic cells, multiple activators can be combined for synergistic gene activation. To identify potential effectors for synergistic activation in bacteria, we systematically characterized bacterial activator proteins with a set of engineered synthetic promoters. We found that optimal target sites for different activators could vary by up to 200 bases in the region upstream of the transcription start site (TSS). These optimal target sites qualitatively matched previous reports for each activator, but the precise targeting rules varied between different promoters. By characterizing targeting rules in the same promoter context, we were able to test activator combinations with each effector positioned at its optimal target site. We did not find any activator combinations that produced synergistic activation, and we found that many combinations were antagonistic. Furthermore, this systematic investigation highlights fundamental mechanistic differences between bacterial and eukaryotic transcriptional activation systems and suggests that alternative strategies will be necessary for strong bacterial gene activation at arbitrary endogenous targets.

CRISPR activation

Thermophilic Chassis-Enabled High-Throughput Selection of a Thermostable Fluorogenic Reporter

Thermostable proteins show increased shelf life and performance at elevated temperatures and under harsh conditions, resulting in lower costs for various industrial and biotechnological applications. However, due to a limited understanding of the relationship between stability and function, protein stabilization remains primarily a trial-and-error approach. Therefore, building a combinatorial library of mutations predicted to improve stability, followed by experimental testing, represents a markedly improved methodology. However, the lack of high-throughput approaches to screen even a moderately sized library presents a major bottleneck in the field. Here, in this study, we use a thermophile, Parageobacillus thermoglucosidasius (Ptherm) to rapidly screen combinatorial libraries consisting of rationally designed thermostabilizing mutations (∼10 3 –10 4 ) of a mesophilic fluorescent reporter, Y-FAST. On a Petri dish, microbial growth at an elevated temperature and exposure to fluorogen yielded several colonies of Ptherm that showed distinct fluorescence at 55 and 68 °C in our two sequentially generated libraries using Rosetta and ProteinMPNN, respectively. The Y-FAST variants isolated from fluorescent colonies were brighter than Y-FAST and showed higher resistance to thermal and chemical denaturation. AlphaFold-predicted structures and MD simulations revealed stability-enhancing salt bridges and hydrogen bond networks in the isolated FAST variants. The moderately thermostable FAST (tsFAST) and hyperstable FAST (hsFAST) were then demonstrated as translation reporters for protein expression and folding at elevated temperatures, such as 55 and 68 °C. Our approach of combinatorial library generation and high-throughput screening in a thermophilic chassis could, in principle, be extended to other proteins fused to these translation reporters. Furthermore, the hsFAST protein is small─half the size of the green fluorescent protein─and does not require oxygen for maturation, making it ideal for engineering extremophilic anaerobes for biosensing and bioconversion.

59 BASIC BIOLOGICAL SCIENCES

Molecular Design Principles for Photosystem I-Based Biohybrid Solar Fuel Catalysts

Direct solar-to-chemical conversion offers a compelling route to clean, dispatchable energy. Photosystem I (PSI), an evolutionarily optimized light-driven oxidoreductase, can be repurposed for solar-fuel production by coupling its photochemistry to catalytic interfaces. However, the molecular determinants that govern productive electron transfer to abiotic catalysts remain poorly understood. Here, we present molecular structures of active PSI-Pt nanoparticle (PtNP) biohybrids that reveal how protein architecture controls catalyst access, binding geometry, and photocatalytic efficiency. Removal of stromal subunits exposes the electron transfer chain and enables PtNP binding proximal to the F X cluster, demonstrating that steric occlusion limits access to native acceptor regions in PSI. In contrast, in trimeric PSI, PtNPs bind at multiple sites per monomer, but only a subset are positioned within electron transfer distance of terminal cofactors, resulting in a heterogeneous population of productive and nonproductive configurations. Structural analyses and molecular dynamics simulations define the interface topology, electrostatics, and cofactor-to-nanoparticle distances that govern catalyst binding and electron transfer. These results establish that catalytic inefficiency arises not only from intrinsic electron transfer constraints but also from the distribution of binding geometries imposed by the protein scaffold. Together, these findings provide a molecular framework linking protein structure to biohybrid function and define design principles for engineering PSI-based solar fuel systems and protein-nanomaterial interfaces for light-driven catalysis.

biohybrid

Transforming an ATP-dependent enzyme into a dissipative, self-assembling system

Nucleoside triphosphate (NTP)-dependent protein assemblies such as microtubules and actin filaments have inspired the development of diverse chemically fueled molecular machines and active materials but their functional sophistication has yet to be matched by design. Given this challenge, we asked whether it is possible to transform a natural adenosine 5'-triphosphate (ATP)-dependent enzyme into a dissipative self-assembling system, thereby altering the structural and functional mode in which chemical energy is used. Furthermore we report that FtsH (filamentous temperature-sensitive protease H), a hexameric ATPase involved in membrane protein degradation, can be readily engineered to form one-dimensional helical nanotubes. FtsH nanotubes require constant energy input to maintain their integrity and degrade over time with the concomitant hydrolysis of ATP, analogous to natural NTP-dependent cytoskeletal assemblies. Yet, in contrast to natural dissipative systems, ATP hydrolysis is catalyzed by free FtsH protomers and FtsH nanotubes serve to conserve ATP, leading to transient assemblies whose lifetimes can be tuned from days to minutes through the inclusion of external ATPases in solution.

59 BASIC BIOLOGICAL SCIENCES

Engineering and Application of a Thermostable MHETase for PET Depolymerization

Enzymatic hydrolysis of poly(ethylene terephthalate) (PET) releases mono(2-hydroxyethyl) terephthalate (MHET) as a major product, the accumulation of which can prolong reactor residence times and complicate downstream monomer separations. The use of a MHETase enzyme can enable MHET hydrolysis to the monomers, terephthalic acid and ethylene glycol, but industrial PETases typically operate at thermophilic temperatures and the well-known MHETase from Ideonella sakaiensis is a mesophilic enzyme, thus warranting the development of thermophilic MHETases. Here, we characterize thermostable MHET-active enzymes from a natural diversity screen by applying a hidden Markov model based on the previously reported, archaeal ferulic acid esterase, PET46. We identified enzymes with higher thermostability than PET46 and quantified their MHETase activity in reactions at 70 °C. The crystal structure of MHT077, the homologue with the highest MHETase activity and an apparent melting temperature (T m,app ) of 94.6 °C, informed site saturation mutagenesis in the active site and lid-domain interface. MHT077 exhibited a ∼100-fold slower unfolding rate at 65 °C than PET46, indicating substantially greater kinetic stability. In parallel, we applied evolution-informed design, a probabilistic model that leverages coevolutionary patterns in large multiple sequence alignments, to improve the activity and thermostability of five ferulic acid esterases. One design, EV-MHT043–5 was identified with a comparable thermostability (T m,app = 96.1 °C) and a 3-fold improvement in its MHETase activity relative to the wildtype enzyme, MHT043. Combination variants of beneficial mutations were screened and afforded a variant, MHT077 LFK , which reduced MHET accumulation in bioreactor experiments with postconsumer PET waste. Overall, this study expands the known MHET-hydrolyzing protein scaffolds available for enzymatic PET recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Bacterial microcompartment architectures as biomaterials for conversion of gaseous substrates

Bacterial microcompartments (BMCs) are protein shells encapsulating multiple enzymes of a metabolic pathway. Interpretations of early experiments on carboxysomes led to the narrative that transport of small gases (CO 2 , O 2 ) across the shell membrane is restricted. Since then, this notion has been largely contradicted by studies of engineered shells, although these shell constructs lack important proteins present in the native BMCs, altering the synthetic shells’ topology, surface and mechanical properties. Here, we discuss here an updated model of gas permeability that informs the design of engineered shells for catalysis on gas substrates and outline how nonshell suprastructures of BMC shell proteins could be used in formulating sustainable biomaterials for hydrogen generation via methane pyrolysis and for other greenhouse gas mitigations.

Bacterial microcompartment

Improving the Transformation Efficiency of Synechococcus sp. PCC 7002 via Methylome-Guided Premethylation of DNA

Cyanobacteria are promising microbial platforms for a diverse set of biotechnology applications, from living materials to photosynthetic chemical production, but are less well characterized than commonly engineered microbes such as Escherichia coli. This study facilitates genetic engineering in Synechococcus sp. PCC 7002, a fast-growing, halotolerant, and naturally competent strain, by identifying ten native methylation motifs and designing shuttle strains that mimic the native methylation state by expressing a subset of heterologous methyltransferases. DNA methylation in E. coli with as few as two active methyltransferases increased transformation efficiency up to 30-fold across four distinct integration sites in PCC 7002. This work provides an experimental framework to bypass native restriction-modification systems for efficient genome editing and metabolic engineering in nonmodel bacteria.

59 BASIC BIOLOGICAL SCIENCES

Rapid discovery and evolution of nanosensors containing fluorogenic amino acids

Binding-activated optical sensors are powerful tools for imaging, diagnostics, and biomolecular sensing. However, biosensor discovery is slow and requires tedious steps in rational design, screening, and characterization. Here we report on a platform that streamlines biosensor discovery and unlocks directed nanosensor evolution through genetically encodable fluorogenic amino acids (FgAAs). Building on the classical knowledge-based semisynthetic approach, we engineer ~15 kDa nanosensors that recognize specific proteins, peptides, and small molecules with up to 100-fold fluorescence increases and subsecond kinetics, allowing real-time and wash-free target sensing and live-cell bioimaging. An optimized genetic code expansion chemistry with FgAAs further enables rapid (~3 h) ribosomal nanosensor discovery via the cell-free translation of hundreds of candidates in parallel and directed nanosensor evolution with improved variant-specific sensitivities (up to ~250-fold) for SARS-CoV-2 antigens. Altogether, this platform could accelerate the discovery of fluorogenic nanosensors and pave the way to modify proteins with other non-standard functionalities for diverse applications.

Biosensors

Evolutionary trajectory of transcription factors and selection of targets for metabolic engineering

Transcription factors (TFs) provide potentially powerful tools for plant metabolic engineering as they often control multiple genes in a metabolic pathway. However, selecting the best TF for a particular pathway has been challenging, and the selection often relies significantly on phylogenetic relationships. Here, we offer examples where evolutionary relationships have facilitated the selection of the suitable TFs, alongside situations where such relationships are misleading from the perspective of metabolic engineering. We argue that the evolutionary trajectory of a particular TF might be a better indicator than protein sequence homology alone in helping decide the best targets for plant metabolic engineering efforts. This article is part of the theme issue ‘The evolution of plant metabolism’.

Life Sciences & Biomedicine - Other Topics

Predicting compatibility between ferredoxins and the Fe protein of nitrogenase using in silico protein modeling

Biological nitrogen fixation is the process by which certain bacteria and archaea use the enzyme nitrogenase to reduce atmospheric nitrogen into bioavailable ammonium. Engineering non‐nitrogen‐fixing organisms, like plants, to use nitrogenase could reduce dependency on synthetic fertilizer and mitigate the environmental impacts of industrial fertilizer production. However, nitrogenase activity requires delivery of reducing power by small electron carrying proteins known as ferredoxins and flavodoxins, and successfully engineering nitrogenase into new systems will require a mechanistic understanding of electron delivery by these proteins. Most organisms often have multiple ferredoxins, raising the question of which ferredoxin can support nitrogenase activity. The purpose of this study is to gain insight into how we can predict which ferredoxin is compatible with the Fe protein, the component of nitrogenase that interacts with ferredoxin or flavodoxin. Our in silico protein–protein docking simulations reveal that most ferredoxins and flavodoxins involved in nitrogen fixation have the shortest distance (≤10 Å) between their redox cofactor and the [4Fe‐4S] cluster of the Fe protein. We found shorter cofactor distance contributes to faster intermolecular electron tunneling rates. Bacterial ferredoxins that play a role in nitrogen fixation also exhibit more complementary interactions with the Fe protein than bacterial and plant ferredoxins not involved in this process. Heterologous expression of a set of ferredoxins from both nitrogen‐fixing and non‐nitrogen‐fixing bacteria in the diazotroph Rhodopseudomonas palustris supports our model‐derived prediction that shorter distances between the electron‐carrying cofactors favor nitrogenase compatibility. These findings offer a framework to predict and potentially enhance ferredoxin–nitrogenase compatibility, which will help to improve our ability to engineer nitrogen fixation into non‐nitrogen‐fixing organisms like plants.

59 BASIC BIOLOGICAL SCIENCES

LDBT instead of DBTL: combining machine learning and rapid cell-free testing

Synthetic biology is defined by Design-Build-Test-Learn cycles. Machine learning has yielded significant improvements in protein design; thus, we propose that “Learning” can precede “Design” to optimize engineering workflows. Additionally, shifting to cell-free platforms will further accelerate “Build” and “Test” capabilities by allowing the rapid expression of proteins and functional testing without the need for cellular transformation or isolation.

59 BASIC BIOLOGICAL SCIENCES

Carbon Negative Synthesis of Amino Acids Using a Cell-Free-Based Biocatalyst

Biological systems can directly upgrade carbon dioxide (CO 2 ) into chemicals. The CO 2 fixation rate of autotrophic organisms, however, is too slow for industrial utility, and the breadth of engineered metabolic pathways for the synthesis of value-added chemicals is too limited. Biotechnology workhorse organisms with extensively engineered metabolic pathways have recently been engineered for CO 2 fixation. Yet, their low carbon fixation rate, compounded by the fact that living organisms split their carbon between cell growth and chemical synthesis, has led to only cell growth with no chemical synthesis achieved to date. Here, we engineer a lysate-based cell-free expression (CFE)-based multienzyme biocatalyst for the carbon negative synthesis of the industrially relevant amino acids glycine and serine from CO 2 equivalents–formate and bicarbonate–and ammonia. The formate-to-serine biocatalyst leverages tetrahydrofolate (THF)-dependent formate fixation, reductive glycine synthesis, serine synthesis, and phosphite dehydrogenase-dependent NAD(P)H regeneration to convert 30% of formate into serine and glycine, surpassing the previous 22% conversion using a purified enzyme system. We find that (1) the CFE-based biocatalyst is active even after 200-fold dilution, enabling higher substrate loading and product synthesis without incurring additional cell lysate cost, (2) NAD(P)H regeneration is pivotal to driving forward reactions close to thermodynamic equilibrium, (3) balancing the ratio of the formate-to-serine pathway genes added to the CFE is key to improving amino acid synthesis, and (4) efficient THF recycling enables lowering the loading of this cofactor, reducing the cost of the CFE-based biocatalyst. To our knowledge, this is the first synthesis of amino acids that can capture CO 2 equivalents for the carbon negative synthesis of amino acids using a CFE-based biocatalyst. Looking ahead, the CFE-based biocatalyst process could be extended beyond serine to pyruvate, a key intermediate, to access a variety of chemicals from aromatics and terpenes to alcohols and polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Cell-Free-Based Thermophilic Biocatalyst for the Synthesis of Amino Acids from One-Carbon Feedstocks

Bioproduction from one-carbon compounds, such as formate, is an attractive prospect due to reduced energy requirements and the possibility for using CO 2 as a sustainable feedstock. Formate-fixing pathways engineered using Escherichia coli lysate-based cell-free expression (CFE) biocatalysts have the potential to route 100% of feedstock carbon toward chemical synthesis but are undermined by siphoning of in-pathway metabolites and cofactors by the CFE background metabolism. To address this limitation, we engineer a CFE-based thermophilic multienzyme biocatalyst for the synthesis of serine and glycine from formate, bicarbonate, and ammonia. After expression of the thermophilic formate-to-serine pathway in a one-pot reaction, the mesophilic E. coli CFE background machinery is removed by simple heat denaturation, eliminating the siphoning of cofactors, inpathway metabolites, and products. After bioprocess optimization, including pathway gene expression duration and chemical synthesis temperature, we achieve near stoichiometric conversion of formate and bicarbonate to serine and glycine, reaching 97% of stoichiometric yield. The use of a moderately thermophilic biocatalyst allowed chemical synthesis to take place at mesophilic temperatures, enabling the balance of optimal enzyme activity with minimal metabolite/cofactor thermal degradation. In a fed-batch experiment, the biocatalyst shows sustained chemical synthesis rates for 8 h, paving the way toward a continuous bioprocess. Finally, a sensitivity analysis of cofactor usage revealed that the most expensive cofactors, THF and NADPH, can be reduced by 5-fold without significantly lowering product yields. To the best of our knowledge, this is the first instance of expressing a thermophilic pathway in an E. coli lysate-based CFE system to generate a thermophilic biocatalyst for use at mesophilic temperatures. The CFEbased thermophilic formate-to-serine biocatalyst triples the combined serine and glycine yield previously obtained by a CFE-based mesophilic formate-to-serine biocatalyst (30%), and quadruple the yield obtained by a purified enzyme system (22%). Ultimately, this work opens the door to using E. coli lysate-based CFE for thermophilic biocatalyst generation to achieve high chemical synthesis yields.

bacteria

Comparative Performance Evaluation of Large Language Models for Extracting Molecular Interactions and Pathway Knowledge

Understanding the interactions and regulatory relationships among biomolecules is essential for deciphering complex biological systems and elucidating the mechanisms behind diverse biological functions. Traditionally, the collection of such molecular interaction data has relied on expert curation, a process that is both time-consuming and labor-intensive. To address these limitations, this study explores the use of large language models (LLMs) to automate the genome-scale extraction of molecular interaction knowledge. Here, we evaluate the performance of various LLMs on key biological tasks, including the identification of protein-protein interactions, detection of genes associated with pathways influenced by low-dose radiation, and inference of gene regulatory relationships. Our findings demonstrate that larger LLMs tend to perform better, particularly in extracting intricate gene and protein interactions. Despite their strengths, these models face challenges in recognizing functionally diverse gene groups and highly correlated regulatory relationships. Through a comprehensive analysis using established molecular interaction and pathway databases, we show that LLMs possess the potential to identify relevant biomolecules and predict their interactions, offering valuable insights and marking a significant step toward AI-driven biological knowledge discovery.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN