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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structural and functional analysis of two SHMT8 variants associated with soybean cyst nematode resistance

Two amino acid variants in soybean serine hydroxymethyltransferase 8 (SHMT8) are associated with resistance to the soybean cyst nematode (SCN), a devastating agricultural pathogen with worldwide economic impacts on soybean production. SHMT8 is a cytoplasmic enzyme that catalyzes the pyridoxal 5‐phosphate‐dependent conversion of serine and tetrahydrofolate (THF) to glycine and 5,10‐methylenetetrahydrofolate. A previous study of the P130R/N358Y double variant of SHMT8, identified in the SCN‐resistant soybean cultivar (cv.) Forrest, showed profound impairment of folate binding affinity and reduced THF‐dependent enzyme activity, relative to the highly active SHMT8 in cv. Essex, which is susceptible to SCN. Given the importance of SCN‐resistance in soybean agriculture, we report here the biochemical and structural characterization of the P130R and N358Y single variants to elucidate their individual effects on soybean SHMT8. We find that both single variants have reduced THF‐dependent catalytic activity relative to Essex SHMT8 (10‐ to 50‐fold decrease ink cat /K m ) but are significantly more active than the P130R/N368Y double variant. The kinetic data also show that the single variants lack THF‐substrate inhibition as found in Essex SHMT8, an observation with implications for regulation of the folate cycle. Five crystal structures of the P130R and N358Y variants in complex with various ligands (resolutions from 1.49 to 2.30 Å) reveal distinct structural impacts of the mutations and provide new insights into allosterism. Our results support the notion that the P130R/N358Y double variant in Forrest SHMT8 produces unique and unexpected effects on the enzyme, which cannot be easily predicted from the behavior of the individual variants.

Biochemistry & Molecular Biology↗
DOE OSTI2023

Human cytochrome P450 17A1 structures with metabolites of prostate cancer drug abiraterone reveal substrate-binding plasticity and a second binding site

Abiraterone acetate is a first-line therapy for castration-resistant prostate cancer. This prodrug is deacetylated in vivo to abiraterone, which is a potent and specific inhibitor of cytochrome P450 17A1 (CYP17A1). CYP17A1 performs two sequential steps that are required for the biosynthesis of androgens that drive prostate cancer proliferation, analogous to estrogens in breast cancer. Abiraterone can be further metabolized in vivo on the steroid A ring to multiple metabolites that also inhibit CYP17A1. Despite its design as an active-site-directed substrate analog, abiraterone and its metabolites demonstrate mixed competitive/noncompetitive inhibition. To understand their binding, we solved the X-ray structures of CYP17A1 with three primary abiraterone metabolites. Despite different conformations of the steroid A ring and substituents, all three bound in the CYP17A1 active site with the steroid core packed against the I helix and the A ring C3 keto or hydroxyl oxygen forming a hydrogen bond with N202 similar to abiraterone itself. The structure of CYP17A1 with 3-keto, 5α-abiraterone was solved to 2.0 Å, the highest resolution to date for a CYP17A1 complex. This structure had additional electron density near the F/G loop, which is likely a second molecule of the inhibitor and which may explain the noncompetitive inhibition. Mutation of the adjacent Asn52 to Tyr positions its side chain in this space, maintains enzyme activity, and prevents binding of the peripheral ligand. Collectively, our findings provide further insight into abiraterone metabolite binding and CYP17A1 function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Harnessing plant‐based platform for low‐cost cellulosic sugar recovery from bioenergy crops

The price of pure cellulase enzyme for the recovery of fermentable cellulosic sugars is one of the major challenges that limit the commercialization of second-generation biofuels and bio-based products. This work shows a means to greatly reduce the cost of cellulases. The abundant capacity of plants to synthesize and hyperaccumulate transgenic proteins in their plastids has been demonstrated for two gene constructs using either NPT II or Tet C to regulate the expression of bacterial cellulase Cel6A. Previously, the expression of Cel6A to 20–35% of total soluble leaf protein in tobacco was shown in two consecutive field trials. Moving forward, the key challenge was the extraction of active enzymes from the transgenic tobacco leaves hyperaccumulating bacterial cellulases in a cost-effective manner. The study showed that unpurified crude extracts of NPT II and Tet C transgenic tobacco leaves recovered ~23% and ~29% w/w cellulosic sugars from energycane bagasse, respectively. A supplementation of as low as 25% of purified commercial cellulase improved the glucose recovery by 2.9 times (~85% w/w) compared to 100% crude extract, which is comparable to the glucose recovery obtained by commercial cellulases, thereby suggesting a reduced requirement of commercial cellulases leading to a cost reduction of 75% for biorefineries. Assuming a stable 40% cellulase yield in total soluble protein under field conditions and multiple harvests (one to three) a year, the study estimates that the potential cost for saccharification of 1 t of lignocellulosic biomass can be reduced to 67–200 USD by using crude leaf extracts of transgenic tobacco.

biofuel↗
DOE OSTI2024

Separation of life stages within anaerobic fungi (Neocallimastigomycota) highlights differences in global transcription and metabolism

Anaerobic gut fungi of the phylum Neocallimastigomycota are microbes proficient in valorizing low-cost but difficult-to-breakdown lignocellulosic plant biomass. Characterization of different fungal life stages and how they contribute to biomass breakdown are critical for biotechnological applications, yet we lack foundational knowledge about the transcriptional, metabolic, and enzyme secretion behavior of different life stages of anaerobic gut fungi: zoospores, germlings, immature thalli, and mature zoosporangia. A Miracloth-based technique was developed to enrich cell pellets with zoospores - the free-swimming, flagellated, young life stage of anaerobic gut fungi. By contrast, fungal mats contained relatively more vegetative, encysted, mature sporangia that form films. Global gene expression profiles were compared from two sample types (zoospore-enriched cell pellets vs. mature mats) harvested from the anaerobic gut fungal strain Neocallimastix californiae G1. Despite cultures being grown on glucose, the fungal zoospore-enriched samples were transcriptionally primed to encounter plant matter substrate, as evidenced by upregulation of catabolic carbohydrate-active enzymes and putative carbohydrate transporters. Furthermore, we report significant differential gene expression for gene annotation groups, including putative secondary metabolites and transcription factors. Understanding global gene expression differences between the fungal zoospore-enriched cells and mature fungi aid in characterizing fungal development, unmasking gene function, and guiding cultivation conditions and engineering targets to promote enzyme secretion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

First comprehensive identification of cardiac proteins with putative increased O-GlcNAc levels during pressure overload hypertrophy

Protein posttranslational modifications (PTMs) by O-GlcNAc globally rise during pressure-overload hypertrophy (POH). However, a major knowledge gap exists on the specific proteins undergoing changes in O-GlcNAc levels during POH primarily because this PTM is low abundance and easily lost during standard mass spectrometry (MS) conditions used for protein identification. Methodologies have emerged to enrich samples for O-GlcNAcylated proteins prior to MS analysis. Accordingly, our goal was to identify the specific proteins undergoing changes in O-GlcNAc levels during POH. We used C57/Bl6 mice subjected to Sham or transverse aortic constriction (TAC) to create POH. From the hearts, we labelled the O-GlcNAc moiety with tetramethylrhodamine azide (TAMRA) before sample enrichment by TAMRA immunoprecipitation (IP). We used LC-MS/MS to identify and quantify the captured putative O-GlcNAcylated proteins. We identified a total of 700 putative O-GlcNAcylated proteins in Sham and POH. Two hundred thirty-three of these proteins had significantly increased enrichment in POH over Sham suggesting higher O-GlcNAc levels whereas no proteins were significantly decreased by POH. We examined two MS identified metabolic enzymes, CPT1B and the PDH complex, to validate by immunoprecipitation. We corroborated increased O-GlcNAc levels during POH for CPT1B and the PDH complex. Enzyme activity assays suggests higher O-GlcNAcylation increases CPT1 activity and decreases PDH activity during POH. In summary, we generated the first comprehensive list of proteins with putative changes in O-GlcNAc levels during POH. Our results demonstrate the large number of potential proteins and cellular processes affected by O-GlcNAc and serve as a guide for testing specific O-GlcNAc-regulated mechanisms during POH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

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↗
DOE OSTI2025

Modification and analysis of context-specific genome-scale metabolic models: methane-utilizing microbial chassis as a case study

ABSTRACT Context-specific genome-scale model (CS-GSM) reconstruction is becoming an efficient strategy for integrating and cross-comparing experimental multi-scale data to explore the relationship between cellular genotypes, facilitating fundamental or applied research discoveries. However, the application of CS modeling for non-conventional microbes is still challenging. Here, we present a graphical user interface that integrates COBRApy, EscherPy, and RIPTiDe, Python-based tools within the BioUML platform, and streamlines the reconstruction and interrogation of the CS genome-scale metabolic frameworks via Jupyter Notebook. The approach was tested using -omics data collected for Methylotuvimicrobium alcaliphilum 20Z R , a prominent microbial chassis for methane capturing and valorization. We optimized the previously reconstructed whole genome-scale metabolic network by adjusting the flux distribution using gene expression data. The outputs of the automatically reconstructed CS metabolic network were comparable to manually optimized i IA409 models for Ca-growth conditions. However, the CS model questions the reversibility of the phosphoketolase pathway and suggests higher flux via primary oxidation pathways. The model also highlighted unresolved carbon partitioning between assimilatory and catabolic pathways at the formaldehyde-formate node. Only a very few genes and only one enzyme with a predicted function in C1 metabolism, a homolog of the formaldehyde oxidation enzyme ( fae1-2 ), showed a significant change in expression in La-growth conditions. The CS-GSM predictions agreed with the experimental measurements under the assumption that the Fae1-2 is a part of the tetrahydrofolate-linked pathway. The cellular roles of the tungsten (W)-dependent formate dehydrogenase ( fdhAB ) and fae homologs ( fae1-2 and fae3 ) were investigated via mutagenesis. The phenotype of the f dhAB mutant followed the model prediction. Furthermore, a more significant reduction of the biomass yield was observed during growth in La-supplemented media, confirming a higher flux through formate. M. alcaliphilum 20Z R mutants lacking fae1-2 did not display any significant defects in methane or methanol-dependent growth. However, contrary to fae1, the fae1-2 homolog failed to restore the formaldehyde-activating enzyme function in complementation tests. Overall, the presented data suggest that the developed computational workflow supports the reconstruction and validation of CS-GSM networks of non-model microbes. IMPORTANCE The interrogation of various types of data is a routine strategy to explore the relationship between genotype and phenotype. An efficient approach for integrating and cross-comparing experimental multi-scale data in the context of whole-genome-based metabolic network reconstruction becomes a powerful tool that facilitates fundamental and applied research discoveries. The present study describes the reconstruction of a context-specific (CS) model for the methane-utilizing bacterium, Methylotuvimicrobium alcaliphilum 20Z R . M. alcaliphilum 20Z R is becoming an attractive microbial platform for the production of biofuels, chemicals, pharmaceuticals, and bio-sorbents for capturing atmospheric methane. We demonstrate that this pipeline can help reconstruct metabolic models that are similar to manually curated networks. Furthermore, the model is able to highlight previously overlooked pathways, thus advancing fundamental knowledge of non-model microbial systems or promoting their development toward biotechnological or environmental implementations.

Kulyashov, M. A.↗
DOE OSTI2023

Large-scale genomic analyses with machine learning uncover predictive patterns associated with fungal phytopathogenic lifestyles and traits

Abstract Invasive plant pathogenic fungi have a global impact, with devastating economic and environmental effects on crops and forests. Biosurveillance, a critical component of threat mitigation, requires risk prediction based on fungal lifestyles and traits. Recent studies have revealed distinct genomic patterns associated with specific groups of plant pathogenic fungi. We sought to establish whether these phytopathogenic genomic patterns hold across diverse taxonomic and ecological groups from the Ascomycota and Basidiomycota, and furthermore, if those patterns can be used in a predictive capacity for biosurveillance. Using a supervised machine learning approach that integrates phylogenetic and genomic data, we analyzed 387 fungal genomes to test a proof-of-concept for the use of genomic signatures in predicting fungal phytopathogenic lifestyles and traits during biosurveillance activities. Our machine learning feature sets were derived from genome annotation data of carbohydrate-active enzymes (CAZymes), peptidases, secondary metabolite clusters (SMCs), transporters, and transcription factors. We found that machine learning could successfully predict fungal lifestyles and traits across taxonomic groups, with the best predictive performance coming from feature sets comprising CAZyme, peptidase, and SMC data. While phylogeny was an important component in most predictions, the inclusion of genomic data improved prediction performance for every lifestyle and trait tested. Plant pathogenicity was one of the best-predicted traits, showing the promise of predictive genomics for biosurveillance applications. Furthermore, our machine learning approach revealed expansions in the number of genes from specific CAZyme and peptidase families in the genomes of plant pathogens compared to non-phytopathogenic genomes (saprotrophs, endo- and ectomycorrhizal fungi). Such genomic feature profiles give insight into the evolution of fungal phytopathogenicity and could be useful to predict the risks of unknown fungi in future biosurveillance activities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

High-quality RNA extraction and the regulation of genes encoding cellulosomes are correlated with growth stage in anaerobic fungi

Anaerobic fungi produce biomass-degrading enzymes and natural products that are important to harness for several biotechnology applications. Although progress has been made in the development of methods for extracting nucleic acids for genomic and transcriptomic sequencing of these fungi, most studies are limited in that they do not sample multiple fungal growth phases in batch culture. In this study, we establish a method to harvest RNA from fungal monocultures and fungal–methanogen co-cultures, and also determine an optimal time frame for high-quality RNA extraction from anaerobic fungi. Based on RNA quality and quantity targets, the optimal time frame in which to harvest anaerobic fungal monocultures and fungal-methanogen co-cultures for RNA extraction was 2-5 days of growth post-inoculation. When grown on cellulose, the fungal strain Anaeromyces robustus cocultivated with the methanogen Methanobacterium bryantii upregulated genes encoding fungal carbohydrate-active enzymes and other cellulosome components relative to fungal monocultures during this time frame, but expression patterns changed at 24-hour intervals throughout the fungal growth phase. These results demonstrate the importance of establishing methods to extract high-quality RNA from anaerobic fungi at multiple time points during batch cultivation.

Brown, Jennifer L.↗
DOE OSTI2023

Structural basis for heparan sulfate co-polymerase action by the EXT1–2 complex

Heparan sulfate (HS) proteoglycans are extended (-GlcAβ1,4GlcNAcα1,4-)n co-polymers containing decorations of sulfation and epimerization that are linked to cell surface and extracellular matrix proteins. In mammals, HS repeat units are extended by an obligate heterocomplex of two exostosin family members, EXT1 and EXT2, where each protein monomer contains distinct GT47 (GT-B fold) and GT64 (GT-A fold) glycosyltransferase domains. In this study, we generated human EXT1–EXT2 (EXT1–2) as a functional heterocomplex and determined its structure in the presence of bound donor and acceptor substrates. Structural data and enzyme activity of catalytic site mutants demonstrate that only two of the four glycosyltransferase domains are major contributors to co-polymer syntheses: the EXT1 GT-B fold β1,4GlcA transferase domain and the EXT2 GT-A fold α1,4GlcNAc transferase domain. Furthermore, the two catalytic sites are over 90 Å apart, indicating that HS is synthesized by a dissociative process that involves a single catalytic site on each monomer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effects of experimental nitrogen deposition on soil organic carbon storage in Southern California drylands

Atmospheric nitrogen (N) deposition is enriching soils with N across biomes. Soil N enrichment can increase plant productivity and affect microbial activity, thereby increasing soil organic carbon (SOC), but such responses vary across biomes. Drylands cover ~45% of Earth's land area and store ~33% of global SOC contained in the top 1 m of soil. Nitrogen fertilization could, therefore, disproportionately impact carbon (C) cycling, yet whether dryland SOC storage increases with N remains unclear. To understand how N enrichment may change SOC storage, we separated SOC into plant–derived, particulate organic C (POC), and largely microbially derived, mineral–associated organic C (MAOC) at four N deposition experimental sites in Southern California. Theory suggests that N enrichment increases the efficiency by which microbes build MAOC (C stabilization efficiency) if soil pH stays constant. But if soils acidify, a common response to N enrichment, then microbial biomass and enzymatic organic matter decay may decrease, increasing POC but not MAOC. We found that N enrichment had no effect on C fractions except for a decrease in MAOC at one site. Specifically, despite reported increases in plant biomass in three sites and decreases in microbial biomass and extracellular enzyme activities in two sites that acidified, POC did not increase. Furthermore, microbial C use and stabilization efficiency increased in a non–acidified site, but without increasing MAOC. Instead, MAOC decreased by 16% at one of the sites that acidified, likely because it lost 47% of the exchangeable calcium (Ca) relative to controls. Indeed, MAOC was strongly and positively affected by Ca, which directly and, through its positive effect on microbial biomass, explained 58% of variation in MAOC. Finally, long–term effects of N fertilization on dryland SOC storage appear abiotic in nature, such that drylands where Ca–stabilization of SOC is prevalent and soils acidify, are most at risk for significant C loss.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Data for Zheng et al. (2025), "AquaMEND: Reconciling multiple impacts of salinization on soil carbon biogeochemistry"

Soil salinization, exacerbated by climate change, poses a global threat to coastal ecosystems and soil function. Salinity affects soil carbon cycling by directly impacting microbial activity and indirectly altering soil physicochemical properties, but current models inadequately represent these complexities. This dataset contains the observational and modeling data from Zheng et al. (2025), which described a process-based modeling framework that couples soil solution chemistry with microbial carbon cycling reactions to study the impacts of soil salinization. This conceptual model is implemented numerically into the open-source geochemical program PHREEQC 3.0 (Parkhurst and Appelo, 2013). This dataset consists of: - Figure2_AquaMEND_salinity_buffer: Contains model simulation outputs to assess the impact of three different cation exchange and surface complexation processes on salinity buffering (Fig. 2 from Zheng et al. 2025). - Figure3_Salinity_function: Contains salinity function fitting for literature data (Fig. 3 from Zheng et al. 2025). - Figure4_AquaMEND_microbial_mechanisms: Contains model simulation outputs for testing various microbial process-based hypotheses related to soil salinization, including microbial mortality, carbon use efficiency (CUE), extracellular enzyme activity, and other microbial mechanisms (Fig. 4 from Zheng et al. 2025). - Figure5_AquaMEND_Redox: Contains on model simulation outputs to evaluate shifts among key redox processes, such as aerobic respiration, sulfate reduction, and methanogenesis (Fig.5 from Zheng et al. 2025). - Figure6_AquaMEND_sorption: Contains on model simulation outputs for investigating the effects of salinity on dissolved organic matter (DOM) sorption and desorption processes (Fig. 6 from Zheng et al. 2025). - Figure7_AquaMEND_process_couple: Contains on model simulation outputs for exploring coupled biotic-abiotic processes and their interactions (Fig. 7 from Zheng et al. 2025). - data: Includes datasets used to develop salinity response functions and evaluate salinity buffering capacity. Datasets for MEND model calibration. - database: Contains the `.dat` file required by PHREEQC for model execution. - README.md: A Markdown plain text file describing the computational tools and directories. Files are a mixture of plain text CSV (comma-separated value) and plain text *.dat files written by the model; no special software is required to read them.

EARTH SCIENCE > AGRICULTURE > SOILS > SOIL SALINIT↗
NASA NTRS1989

Characteristics and Preliminary Observations of the Influence of Electromyostimulation on the Size and Function of Human Skeletal Muscle During 30 Days of Simulated Microgravity

During 30 days (d) of bedrest, the practicality of using Elec- troMyoStimulation (EMS) as a deterrent to atrophy and strength loss of lower limb musculature was examined. An EMS system was developed that provided variable but quantifiable levels of EMS, and measured torque. The dominant log of three male subjects was stimulated twice daily in a 3-d on/1-d off cycle during bedrest. The non-dominant leg of each subject acted as a control. A stimulator, using a 0.3 ms monophasic 60 Hz pulse waveform, activated muscle tissue for 4 s. The output waveform from the stimulator was sequenced to the Knee Extensors (KE), Knee Flex- ors (KF), Ankle Extensors (AE), and Ankle Flexors (AF), and caused three isometric contractions of each muscle group per minute. Subject tolerance determined EMS Intensity. Each muscle group received four 5-min bouts of EMS each session with a 10 -min rest between bouts. EMS and torque levels for each muscle action were recorded directly an a computer. Overall average EMS Intensity was 197, 197, 195, and 188 mA for the KE, KF, AF, and AE, respectively. Overall average torque development for these muscle groups was 70, 16, 12, and 27 Nm, respectively. EMS intensity doubled during the study, and average torque increased 2.5 times. Average maximum torque throughout a session reached 54% of maximal voluntary for the KE and 29% for the KF. Reductions in leg volume, muscle compartment size, cross-sectional area of slow and fast-twitch fibers, strength, and aerobic enzyme activities, and increased log compliance were attenuated in the legs which received EMS during bedrest. These results indicate that similar EMS levels induce different torques among different muscle groups and that repeated exposure to EMS increases tolerance and torque development. Longer orien- tation periods, therefore, may enhance its effectiveness. Our preliminary data suggest that the efficacy of EMS as an effective countermeasure for muscle atrophy and strength loss during long duration space travel warrants further investigation.

Duvoisin, Marc R.↗
DOE OSTI2020

Genome-based analysis for the bioactive potential of Streptomyces yeochonensis CN732, an acidophilic filamentous soil actinobacterium

Background: Acidophilic members of the genus Streptomyces can be a good source for novel secondary metabolites and degradative enzymes of biopolymers. In this study, a genome-based approach on Streptomyces yeochonensis CN732, a representative neutrotolerant acidophilic streptomycete, was employed to examine the biosynthetic as well as enzymatic potential, and also presence of any genetic tools for adaptation in acidic environment. Results: A high quality draft genome (7.8Mb) of S. yeochonensis CN732 was obtained with a G+C content of 73.53% and 6549 protein coding genes. The in silico analysis predicted presence of multiple biosynthetic gene clusters (BGCs), which showed similarity with those for antimicrobial, anticancer or antiparasitic compounds. However, the low levels of similarity with known BGCs for most cases suggested novelty of the metabolites from those predicted gene clusters. The production of various novel metabolites was also confirmed from the combined high performance liquid chromatography-mass spectrometry analysis. Through comparative genome analysis with related Streptomyces species, genes specific to strain CN732 and also those specific to neutrotolerant acidophilic species could be identified, which showed that genes for metabolism in diverse environment were enriched among acidophilic species. In addition, the presence of strain specific genes for carbohydrate active enzymes (CAZyme) along with many other singletons indicated uniqueness of the genetic makeup of strain CN732. The presence of cysteine transpeptidases (sortases) among the BGCs was also observed from this study, which implies their putative roles in the biosynthesis of secondary metabolites. Conclusions: This study highlights the bioactive potential of strain CN732, an acidophilic streptomycete with regard to secondary metabolite production and biodegradation potential using genomics based approach. The comparative genome analysis revealed genes specific to CN732 and also those among acidophilic species, which could give some insights into the adaptation of microbial life in acidic environment.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2000

Development and Application of Computational/In Vitro Toxicological Methods for Chemical Hazard Risk Reduction of New Materials for Advanced Weapon Systems

The development of quantitative structure-activity relationship (QSAR) is essential for reducing the chemical hazards of new weapon systems. The current collaboration between HEST (toxicology research and testing), MLPJ (computational chemistry) and PRS (computational chemistry, new propellant synthesis) is focusing R&D efforts on basic research goals that will rapidly transition to useful products for propellant development. Computational methods are being investigated that will assist in forecasting cellular toxicological end-points. Models developed from these chemical structure-toxicity relationships are useful for the prediction of the toxicological endpoints of new related compounds. Research is focusing on the evaluation tools to be used for the discovery of such relationships and the development of models of the mechanisms of action. Combinations of computational chemistry techniques, in vitro toxicity methods, and statistical correlations, will be employed to develop and explore potential predictive relationships; results for series of molecular systems that demonstrate the viability of this approach are reported. A number of hydrazine salts have been synthesized for evaluation. Computational chemistry methods are being used to elucidate the mechanism of action of these salts. Toxicity endpoints such as viability (LDH) and changes in enzyme activity (glutahoione peroxidase and catalase) are being experimentally measured as indicators of cellular damage. Extrapolation from computational/in vitro studies to human toxicity, is the ultimate goal. The product of this program will be a predictive tool to assist in the development of new, less toxic propellants.

Frazier, John M.↗
DOE OSTI2020

Soil aggregate-mediated microbial responses to long-term warming

Soil microbial carbon use efficiency (CUE) is a combination of growth and respiration, which may respond differently to climate change depending on physical protection of soil carbon (C) and its availability to microbes. In a mid-latitude hardwood forest in central Massachusetts, 27 years of soil warming (+5 °C) has resulted in C loss and altered soil organic matter (SOM) quality, yet the underlying mechanisms remain unclear. In this work, we hypothesized that long-term warming reduces physical aggregate protection of SOM, microbial CUE, and its temperature sensitivity. Soil was separated into macroaggregate (250–2000 μm) and microaggregate (<250 μm) fractions, and CUE was measured with 18 O enriched water (H 2 18 O) in samples incubated at 15 and 25 °C for 24 h. We found that long-term warming reduced soil C and nitrogen concentrations and extracellular enzyme activity in macroaggregates, but did not affect physical protection of SOM. Long-term warming showed little effect on CUE or microbial biomass turnover time because it reduced both growth and respiration. However, CUE was less temperature sensitive in macroaggregates from the warmed compared to the control plots. Our findings suggest that microbial thermal responses to long-term warming occur mostly in soil compartments where SOM is less physically protected and thus more vulnerable to microbial degradation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Enhanced active-site electric field accelerates enzyme catalysis

In this study, the design and improvement of enzymes based on physical principles remain challenging. Here we demonstrate that the principle of electrostatic catalysis can be leveraged to substantially improve a natural enzyme’s activity. We enhanced the active-site electric field in horse liver alcohol dehydrogenase by replacing the serine hydrogen-bond donor with threonine and replacing the catalytic Zn 2+ with Co 2+ . Based on the electric field enhancement, we make a quantitative prediction of rate acceleration—50-fold faster than the wild-type enzyme—which was in close agreement with experimental measurements. The effects of the hydrogen bonding and metal coordination, two distinct chemical forces, are described by a unified physical quantity—electric field, which is quantitative, and shown here to be additive and predictive. These results suggest a new design paradigm for both biological and non-biological catalysts.

59 BASIC BIOLOGICAL SCIENCES↗