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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Fitness Landscape-Guided Engineering of Locally Supercharged Virus-like Particles with Enhanced Cell Uptake Properties

Protein-based nanoparticles are useful models for the study of self-assembly and attractive candidates for drug delivery. Virus-like particles (VLPs) are especially promising platforms for expanding the repertoire of therapeutics that can be delivered effectively as they can deliver many copies of a molecule per particle for each delivery event. However, their use is often limited due to poor uptake of VLPs into mammalian cells. In this study, we use the fitness landscape of the bacteriophage MS2 VLP as a guide to engineer capsid variants with positively charged surface residues to enhance their uptake into mammalian cells. By combining mutations with positive fitness scores that were likely to produce assembled capsids, we identified two key double mutants with internalization efficiencies as much as 67-fold higher than that of wtMS2. Internalization of these variants with positively charged surface residues depends on interactions with cell surface sulfated proteoglycans, and yet, they are biophysically similar to wtMS2 with low cytotoxicity and an overall negative charge. Additionally, the best-performing engineered MS2 capsids can deliver a potent anticancer small-molecule therapeutic with efficacy levels similar to antibody-drug conjugates. Through this work, we were able to establish fitness landscape-based engineering as a successful method for designing VLPs with improved cell penetration. These findings suggest that VLPs with positive surface charge could be useful in improving the delivery of small-molecule- and nucleic acid-based therapeutics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Enzymatic Activity of Inosine 5'-Monophosphate Dehydrogenase May Not Be a Vulnerable Target for Staphylococcus aureus Infections

Many bacterial pathogens, including Staphylococcus aureus, require inosine 5'-monophosphate dehydrogenase (IMPDH) for infection, making this enzyme a promising new target for antibiotics. Although potent selective inhibitors of bacterial IMPDHs have been reported, relatively few have displayed antibacterial activity. Here we use structure-informed design to obtain inhibitors of S. aureus IMPDH (SaIMPDH) that have potent antibacterial activity (minimal inhibitory concentrations less than 2 μM) and low cytotoxicity in mammalian cells. The physicochemical properties of the most active compounds were within typical Lipinski/Veber space, suggesting that polarity is not a general requirement for achieving antibacterial activity. In this work, five compounds failed to display activity in mouse models of septicemia and abscess infection. Inhibitor-resistant S. aureus strains readily emerged in vitro. Resistance resulted from substitutions in the cofactor/inhibitor binding site of SaIMPDH, confirming on-target antibacterial activity. These mutations decreased the binding of all inhibitors tested, but also decreased catalytic activity. Nonetheless, the resistant strains had comparable virulence to wild-type bacteria. Surprisingly, strains expressing catalytically inactive SaIMPDH displayed only a mild virulence defect. Collectively these observations question the vulnerability of the enzymatic activity of SaIMPDH as a target for the treatment of S. aureus infections, suggesting other functions of this protein may be responsible for its role in infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Tre-DST: A Drug Susceptibility Test for Mycobacterium tuberculosis Using Solvatochromic Trehalose Probes

In 2024, an estimated 10 million people developed Tuberculosis (TB), nearly half a million of whom were infected with drug-resistant tuberculosis (DR-TB). Early detection of infection and drug resistance enables rapid engagement in effective care. Bacterial culture and nucleic acid testing remain the primary diagnostic methods, with smear microscopy being phased out. However, these methods present significant limitations for diagnosing drug resistance, such as lengthy time-to-result for phenotypic tests, as well as the need for prior knowledge of resistance mutations and prohibitive cost for molecular tests. To address this, we developed a rapid phenotypic TB drug susceptibility test, termed Tre-DST, based on novel metabolically incorporated trehalose probes, which specifically detect live mycobacteria. We used the nonpathogenic Mycobacterium smegmatis and the virulence-attenuated Mycobacterium tuberculosis (Mtb) H37Ra or auxotrophic Mtb to demonstrate a strong correlation between cost-effective plate reader results and flow cytometry data, suggesting that the plate reader is a suitable fluorescence detector for Tre-DST. We determined that adding a 1-week incubation step allowed Mtb samples originally seeded at 10 4 CFU/mL to become detectable, over 2 weeks earlier than colony-forming unit analysis. We found that Tre-DST reports on drug susceptibility in a drug-agnostic manner, demonstrating loss of fluorescence with frontline TB drugs as well as the newer drug bedaquiline. Tre-DST distinguished RIF- and INH-resistant auxotrophs from susceptible controls and accurately reported the resistance activity. Ultimately, because Tre-DST is agnostic to mechanisms of drug resistance, this assay is likely compatible with all WHO-recommended and future DR-TB drugs as a diagnostic in reference laboratories.

diagnostics↗
DOE OSTI2020

Enhanced Binding of SARS-CoV-2 Spike Protein to Receptor by Distal Polybasic Cleavage Sites

The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein plays a crucial role in binding the human cell receptor ACE2 that is required for viral entry. Many studies have been conducted to target the structures of RBD–ACE2 binding and to design RBD-targeting vaccines and drugs. Nevertheless, mutations distal from the SARS-CoV-2 RBD also impact its transmissibility and antibody can target non-RBD regions, suggesting the incomplete role of the RBD region in the spike protein–ACE2 binding. Here, in order to elucidate distant binding mechanisms, we analyze complexes of ACE2 with the wild-type spike protein and with key mutants via large-scale all-atom explicit solvent molecular dynamics simulations. We find that though distributed approximately 10 nm away from the RBD, the SARS-CoV-2 polybasic cleavage sites enhance, via electrostatic interactions and hydration, the RBD–ACE2 binding affinity. A negatively charged tetrapeptide (GluGluLeuGlu) is then designed to neutralize the positively charged arginine on the polybasic cleavage sites. We find that the tetrapeptide GluGluLeuGlu binds to one of the three polybasic cleavage sites of the SARS-CoV-2 spike protein lessening by 34% the RBD–ACE2 binding strength. This significant binding energy reduction demonstrates the feasibility to neutralize RBD–ACE2 binding by targeting this specific polybasic cleavage site. Our work enhances understanding of the binding mechanism of SARS-CoV-2 to ACE2, which may aid the design of therapeutics for COVID-19 infection.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Self-Assembly of Accumulated Sphingolipids into Cytotoxic Fibrils in Globoid Cell Leukodystrophy and Their Inhibition by Small Molecules In Vitro

Globoid cell leukodystrophy (GLD) is a rare hereditary inborn error of metabolism due to recessive mutations that cause loss of function of the enzyme galactosylceramidase (GALC). This results in the accumulation of the sphingolipids galactosylceramide (GalCer) and galactosylsphingosine (GalSph) in the lysosomes of neuronal cells. The accumulated GalCer and GalSph in cerebral macrophages of GLD patients are neurotoxic to oligodendrocytes and Schwann cells, leading to demyelination in the nervous system. The disease typically presents with infantile onset in the first six months of life and death by age 2. Here, we identified a supramolecular structure of GalCer and GalSph that may contribute to GLD pathology. Using biophysical assays commonly used for studying proteinaceous amyloids, e.g., amyloidspecific dyes, microscopical imaging, and a series of analytical methods (FTIR, PXRD, and SAXS), we demonstrate that both GalCer and GalSph can self-assemble in vitro into highly organized fibrils reminiscent of fibrils of amyloidogenic proteins. These fibrils exhibit significant cytotoxicity to both neuronal and oligodendroglial cells. Using an inhibitor of the GALC enzyme in cell culture to mimic the GLD pathophysiology, we could detect the accumulation of these fibrils in cells. We also observed that small molecules, which are bona fide inhibitors of proteinaceous amyloids, effectively mitigated the formation of the GalCer and GalSph fibrillar structures in vitro. Finally, the small molecule ameliorated the cytotoxic effects of the sphingolipid fibrils in SH-SY5Y cells, suggesting a potential avenue for therapeutic intervention in GLD orphan disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

High-Sensitivity DNA Aptasensors for Detecting Salivary Biomarker S100A7 in Heart Failure

Early detection of heart failure (HF) is vital for improving patient outcomes, lowering hospital readmission rates, and enabling prompt treatment. We present the first high-affinity DNA aptamer for the salivary HF biomarker S100A7 and its application in highly sensitive, noninvasive diagnostic tests. Iterative truncation of the initial 82-nt aptamer (17–82) produced a 43-nt core (17–43) with a binding affinity of 27 nM, which was further enhanced to 5.5 nM through dimerization. Biochemical and mutational studies confirmed that 17–43 adopts a G-quadruplex structure, which is essential for S100A7 recognition and resistance to enzymatic degradation in human saliva. Incorporating 17–43 into sandwich aptamer-ELISA and hybrid aptamer–antibody ELISA assays allowed detection of recombinant S100A7 in human saliva with limits of detection (LOD) of 7.4 ng mL–1 (0.6 nM) and 29 pg/mL (2.2 pM), respectively-outperforming commercial immunoassays in both sensitivity and dynamic range. The hybrid assay maintained its full performance after 2.5 months of room temperature storage. Additionally, a biolayer interferometry (BLI) sensor with 17–43 quantified S100A7 in patient saliva (n = 3), achieving a LOD of 3.2 ng mL–1 (0.3 nM) with a total assay time of less than 20 min. The aptamer’s stability, high specificity, and versatility across biosensing platforms establish it as a promising tool for noninvasive heart failure diagnostics, laying the groundwork for portable aptamer-based biosensors for multiplexed monitoring of HF biomarkers.

DNA aptamer↗
DOE OSTI2026

Evaluating Limits of Machine Learning-Assisted Raman Spectroscopy in Classification of Biological Samples

Machine learning (ML)-assisted Raman spectroscopy has become a powerful analytical tool for the classification and identification of analytes; however, technical challenges impacting its detection accuracy have not been thoroughly investigated. This study explores experimental factors affecting classification performance. Among the evaluated ML models, ML algorithms show minimal impact on classification accuracy. Instead, experimental factors, including spectral similarity between tested samples and data quality, dominate detection performance. Increases in spectral noise and spectral similarity significantly reduce classification accuracy. In well-controlled samples with low experimental noise, ML-assisted Raman spectroscopy can discriminate lipid mixtures with a composition difference of 1.85 mol %. To assess the effect of biological heterogeneity, we analyzed single-cell Raman spectra from Saccharomyces cerevisiae strains carrying single, double, or triple gene mutations. Intrinsic cell-to-cell variability introduced substantial spectral differences, severely reducing the accuracy of multiclass classification of these genetically similar strains at the single-cell level. Averaging Raman spectra across multiple cells improved classification accuracy by reducing this spectral variability. We also assess the effectiveness of transfer learning across different Raman spectrometers, specifically by applying an ML model trained on one instrument to another Raman spectrometer. Transfer learning can be improved with proper instrument calibration, highlighting the importance of instrument standardization. Overall, our results demonstrate that data quality and spectral similarity are the primary bottlenecks in ML-assisted Raman spectroscopy. Careful attention to sample preparation, data acquisition, measurement conditions, and instrument calibration is critical to achieving robust and reliable classification performance.

Fungi↗
DOE OSTI2026

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↗
DOE OSTI2022

Comparison of Kill Switch Toxins in Plant-Beneficial Pseudomonas fluorescens Reveals Drivers of Lethality, Stability, and Escape

Kill switches provide a biocontainment strategy in which unwanted growth of an engineered microorganism is prevented by expression of a toxin gene. A major challenge in kill switch engineering is balancing evolutionary stability with robust cell killing activity in application relevant host strains. Understanding host-specific containment dynamics and modes of failure helps to develop potent yet stable kill switches. To guide the design of robust kill switches in the agriculturally relevant strain Pseudomonas fluorescens SBW25, we present a comparison of lethality, stability, and genetic escape of eight different toxic effectors in the presence of their cognate inactivators (i.e., toxin–antitoxin modules, polymorphic exotoxin–immunity systems, restriction endonuclease–methyltransferase pair). We find that cell killing capacity and evolutionary stability are inversely correlated and dependent on the level of protection provided by the inactivator gene. Decreasing the proteolytic stability of the inactivator protein can increase cell killing capacity, but at the cost of long-term circuit stability. By comparing toxins within the same genetic context, we determine that modes of genetic escape increase with circuit complexity and are driven by toxin activity, the protective capacity of the inactivator, and the presence of mutation-prone sequences within the circuit. Here, the results of our study reveal that circuit complexity, toxin choice, inactivator stability, and DNA sequence design are powerful drivers of kill switch stability and valuable targets for optimization of biocontainment systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Characterization and Diversification of AraC/XylS Family Regulators Guided by Transposon Sequencing

In this study, we explored the development of engineered inducible systems. Publicly available data from previous transposon sequencing assays were used to identify regulators of metabolism in Pseudomonas putida KT2440. For AraC family regulators (AFRs) represented in these data, we posited AFR/promoter/inducer groupings. Twelve promoters were characterized for a response to their proposed inducers in P. putida, and the resultant data were used to create and test nine two-plasmid sensor systems in Escherichia coli. Several of these were further developed into a palette of single-plasmid inducible systems. From these experiments, we observed an unreported inducer response from a previously characterized AFR, demonstrated that the addition of a P. putida transporter improved the sensor dynamics of an AFR in E. coli, and identified an uncharacterized AFR with a novel potential inducer specificity. Finally, targeted mutations in an AFR, informed by structural predictions, enabled the further diversification of these inducible plasmids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Robust Synthetic Biology Toolkit to Advance Carboxysome Study and Redesign

Carboxysomes are polyhedral protein organelles that microorganisms use to facilitate carbon dioxide assimilation. They are composed of a modular protein shell that envelops an enzymatic core mainly composed of physically coupled Rubisco and carbonic anhydrase. While the modular construction principles of carboxysomes make them attractive targets as customizable metabolic platforms, their size and complexity can be a hindrance. In this work, we design and validate a plasmid set, the pXpressome toolkit, in which α-carboxysomes are robustly expressed and remain intact and functional after purification. We tested this toolkit by introducing mutations that influence carboxysome structure and performance. We find that deletion of vertex-capping genes results in formation of larger carboxysomes, while deletion of facet forming genes produces smaller particles, suggesting that adjusting the ratio of these proteins can rationally affect morphology. Through a series of fluorescently labeled constructs, we observe that this toolkit leads to more uniform expression and better cell health than previously published carboxysome expression systems. Overall, the pXpressome toolkit facilitates the study and redesign of carboxysomes with robust performance and improved phenotype uniformity. The pXpressome toolkit will support efforts to remodel carboxysomes for enhanced carbon fixation or serve as a platform for other nanoencapsulation goals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Continuous Directed Evolution of a Short-Lived Plant Histidinol Dehydrogenase

Enzyme protein turnover accounts for about half the maintenance energy budget in plants. Slowing turnover i.e., extending the effective working life (Catalytic Cycles till Replacement, CCR) of short-lived enzymes is thus a rational strategy to conserve energy and carbon and raise crop productivity. Arabidopsis histidinol dehydrogenase (HDH) is a short-lived enzyme that can sustain lifeshortening damage from its aminoaldehyde reaction intermediate. We used the yeast OrthoRep continuous directed evolution system in a his4 Δ strain to raise cumulative HDH function and, by proxy, lifespan as functional enzymes, by selecting for growth rate while tapering histidinol concentration and escalating that of the inhibitor histamine. Improved HDH variants carried diverse nonsynonymous mutations and ranged 20-fold in level. Improved HDH performance was associated with higher HDH abundance in some cases and with greater catalytic efficiency or histamine resistance in others. These findings indicate that OrthoRep-based directed evolution can extend enzyme working life in vivo in addition to, as expected, altering kinetic properties.

directed evolution↗
DOE OSTI2026

Using Domain Insertion to Create Sulfite Reductases That Present Chemical-Dependent Activities

Domain insertion can be used to create oxidoreductases whose activities are dependent upon analyte binding. To date, most domain insertion studies have targeted relatively small oxidoreductases of known structure, so it remains unclear how to apply this protein engineering approach to large hetero-oligomeric proteins that require dynamic conformational changes for catalysis. To address this question, we studied the effects of peptide and domain insertions on the activity of NADPH-dependent sulfite reductase (SiR) from Escherichia coli, a dodecameric oxidoreductase containing four hemoprotein and eight flavoprotein subunits. SiR mutational tolerance was first evaluated using systematic octapeptide insertion and a cellular selection, which identified regions across the hemoprotein structure that retain parent-like activity following insertion. When a ligand-binding domain was inserted at backbone locations tolerant to peptide insertion, including sites proximal and distal from the intersubunit interfaces, ∼90% retained catalytic activity, and >50% presented activity that is regulated by an endocrine disruptor. With one domain insertion variant, the conditional production of sulfide could be monitored electrochemically from cells using a bioelectrochemical reactor. These results show how systematic peptide insertion can be used to inform domain insertion in a large heterooligomeric protein complex, and they illustrate how SiR can be engineered to convert chemical information in the environment into a redox-active metabolite that diffuses across the cell membrane.

bacteria↗
DOE OSTI2022

Energetic Basis and Design of Enzyme Function Demonstrated Using GFP, an Excited-State Enzyme

We report the past decades have witnessed an explosion of de novo protein designs with a remarkable range of scaffolds. It remains challenging, however, to design catalytic functions that are competitive with naturally occurring counterparts as well as biomimetic or nonbiological catalysts. Although directed evolution often offers efficient solutions, the fitness landscape remains opaque. Green fluorescent protein (GFP), which has revolutionized biological imaging and assays, is one of the most redesigned proteins. While not an enzyme in the conventional sense, GFPs feature competing excited-state decay pathways with the same steric and electrostatic origins as conventional ground-state catalysts, and they exert exquisite control over multiple reaction outcomes through the same principles. Thus, GFP is an “excited-state enzyme”. Herein we show that rationally designed mutants and hybrids that contain environmental mutations and substituted chromophores provide the basis for a quantitative model and prediction that describes the influence of sterics and electrostatics on excited-state catalysis of GFPs. As both perturbations can selectively bias photoisomerization pathways, GFPs with fluorescence quantum yields (FQYs) and photoswitching characteristics tailored for specific applications could be predicted and then demonstrated. The underlying energetic landscape, readily accessible via spectroscopy for GFPs, offers an important missing link in the design of protein function that is generalizable to catalyst design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Shaping the Water-Harvesting Behavior of Metal–Organic Frameworks Aided by Fine-Tuned GPT Models

Here, we construct a data set of metal–organic framework (MOF) linkers and employ a fine-tuned GPT assistant to propose MOF linker designs by mutating and modifying the existing linker structures. This strategy allows the GPT model to learn the intricate language of chemistry in molecular representations, thereby achieving an enhanced accuracy in generating linker structures compared with its base models. Aiming to highlight the significance of linker design strategies in advancing the discovery of water-harvesting MOFs, we conducted a systematic MOF variant expansion upon state-of-the-art MOF-303 utilizing a multidimensional approach that integrates linker extension with multivariate tuning strategies. We synthesized a series of isoreticular aluminum MOFs, termed Long-Arm MOFs (LAMOF-1 to LAMOF-10), featuring linkers that bear various combinations of heteroatoms in their five-membered ring moiety, replacing pyrazole with either thiophene, furan, or thiazole rings or a combination of two. Beyond their consistent and robust architecture, as demonstrated by permanent porosity and thermal stability, the LAMOF series offers a generalizable synthesis strategy. Importantly, these 10 LAMOFs establish new benchmarks for water uptake (up to 0.64 g g –1 ) and operational humidity ranges (between 13 and 53%), thereby expanding the diversity of water-harvesting MOFs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Conical Intersection Accessibility Dictates Brightness in Red Fluorescent Proteins

Red fluorescent protein (RFP) variants are highly sought after for in-vivo imaging since longer wavelengths improve depth and contrast in fluorescence imaging. However, the lower energy emission wavelength usually correlates with a lower fluorescent quantum yield compared to their green emitting counterparts. To guide the rational design of bright variants, we have theoretically assessed two variants (mScarlet and mRouge) which are reported to have very different brightness. Using an α-CASSCF QM/MM framework (chromophore and all protein residues within 6 Å of it in the QM region, for a total of more than 450 QM atoms), we identify key points on the ground and first excited state potential energy surfaces. The brighter variant mScarlet has a rigid scaffold, and the chromophore stays largely planar on the ground state. The dimmer variant mRouge shows more flexibility and can accommodate a pre-twisted chromophore conformation which provides easier access to conical intersections. Notably, the main difference between the variants lies in the intersection seam regions, which appear largely inaccessible in mScarlet but partially accessible in mRouge. This observation is mainly related with changes in the cavity charge distribution, the hydrogen-bonding network involving the chromophore and a key ARG/THR mutation (which changes both charge and steric hindrance).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Engineering Polyketide Stereocenters with Ketoreductase Domain Exchanges

Polyketide synthases (PKSs) are versatile biosynthetic megasynthases capable of producing a diverse range of natural products with many applications, including in pharmaceuticals. The stereochemical precision of PKSs makes them a powerful tool for engineering tailored, unnatural polyketides; however, modifying the stereocenters of a PKS product while maintaining production levels remains a significant challenge. In this study, we systematically tested and evaluated strategies for ketoreductase (KR) domain exchanges, the domain responsible for setting stereocenters of polyketide products. After first optimizing the method for KR exchanges, we then performed 44 KR domain exchanges on three different PKSs to obtain high production of all four stereoisomers in vivo. By testing both one- and two-module PKS systems, we investigated how downstream modules process intermediates with altered stereochemistry and found that the configuration of the α-substituents was critical for gatekeeping by the ketosynthase (KS). To overcome this constraint, we investigated two different strategies for altering the KS domain, including introducing targeted mutations in the downstream KS, and exploring boundaries in exchanging the entire functional unit from the donor PKS. Both strategies successfully modified the KS stereocontrol with distinct trade-offs; the functional unit exchange resulted in higher titer improvements, though it was more likely to break the entire PKS. This study demonstrates a comprehensive approach to successfully engineering all four stereochemical configurations in multiple PKS systems, advancing our understanding of and ability to rationally modify polyketide stereochemistry through multiple engineering strategies.

Keiser, Leah S. [Joint BioEnergy Institute (JBEI),↗