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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Image-Based Methods to Score Fungal Pathogen Symptom Progression and Severity in Excised Arabidopsis Leaves

Image-based symptom scoring of plant diseases is a powerful tool for associating disease resistance with plant genotypes. Advancements in technology have enabled new imaging and image processing strategies for statistical analysis of time-course experiments. There are several tools available for analyzing symptoms on leaves and fruits of crop plants, but only a few are available for the model plant Arabidopsis thaliana (Arabidopsis). Arabidopsis and the model fungus Botrytis cinerea (Botrytis) comprise a potent model pathosystem for the identification of signaling pathways conferring immunity against this broad host-range necrotrophic fungus. Here, we present two strategies to assess severity and symptom progression of Botrytis infection over time in Arabidopsis leaves. Thus, a pixel classification strategy using color hue values from red-green-blue (RGB) images and a random forest algorithm was used to establish necrotic, chlorotic, and healthy leaf areas. Secondly, using chlorophyll fluorescence (ChlFl) imaging, the maximum quantum yield of photosystem II (Fv/Fm) was determined to define diseased areas and their proportion per total leaf area. Both RGB and ChlFl imaging strategies were employed to track disease progression over time. This has provided a robust and sensitive method for detecting sensitive or resistant genetic backgrounds. A full methodological workflow, from plant culture to data analysis, is described.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Herbaspirillum rubrisubalbicans as a Phytopathogenic Model to Study the Immune System of Sorghum bicolor

Herbaspirillum rubrisubalbicans is the causal agent of red stripe disease (RSD) and mottle stripe disease of sorghum and sugarcane, respectively. In all, 63 genotypes of Sorghum bicolor were inoculated with H. rubrisubalbicans, with 59 showing RSD symptoms. Quantitative trait loci (QTL) analysis in a recombinant inbred line (RIL) population identified several QTL associated with variation in resistance to RSD. RNA sequencing analysis identified a number of genes whose transcript levels were differentially regulated during H. rubrisubalbicans infection. Among those genes that responded to H. rubrisubalbicans inoculation were many involved in plant–pathogen interactions such as leucine-rich repeat receptors, mitogen-activated protein kinase 1, calcium-binding proteins, transcriptional factors (ethylene-responsive element binding factor), and callose synthase. Pretreatment of sorghum leaves with the pathogen-associated molecular pattern (PAMP) molecules flg22 and chitooctaose provided protection against subsequent challenge with the pathogen, suggesting that PAMP-triggered immunity plays an important role in the sorghum immunity response. These data present baseline information for the use of the genetically tractable H. rubrisubalbicans–sorghum pathosystem for the study of innate immunity and disease resistance in this important grain and bioenergy crop. Information gained from the use of this system is likely to be informative for other monocots, including those more intractable for experimental study (e.g., sugarcane).

Biochemistry & Molecular Biology↗
DOE OSTI2020

Modeled economic potential for Eucalyptus spp. production for jet fuel additives in the United States

Feedstock price and availability remain a barrier to adoption of cellulosic biofuels. Eucalyptus spp., can produce an energy-dense terpene suitable for high-density synthetic hydrocarbon-type fuel (grade JP-10) production in addition to cellulosic-based feedstock for traditional jet fuels (e.g., grade Jet A) and gasoline. This study modeled economic potential for Eucalyptus to fulfill US fuel markets. Cold-tolerant Eucalyptus was simulated in an annual coppice system for maximized leaf production. Results of the lowest simulated price ($110 t -1 ) show that within 10 years, there is potential to produce 204 million L yr -1 of fuel, including 51 million L yr -1 of JP-10-type fuel, 75 million L yr -1 of Jet A type fuel, and 77 million L yr -1 of gasoline. These quantities of fuel could be valued at approximately $500 million (USD), with feedstock costs totaling approximately $100 million (USD). Longer-term markets (to 20 years) or higher priced (to $220 t -1 ) scenarios show potential for more production. Furthermore, research to determine potential for genetic improvement, delivered fuel costs, and biorefinery siting near existing infrastructure is recommended.

09 BIOMASS FUELS↗
DOE OSTI2023

Ontologizing health systems data at scale: making translational discovery a reality

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68–99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Convergent evolution of aerobic fermentation through divergent mechanisms acting on key shared glycolytic genes

As the tree of life becomes increasingly accessible to molecular investigations, describing mechanisms underlying evolutionary convergence and constraint will be crucial to understanding diversification. The lineage including the model yeast Saccharomyces cerevisiae evolved aerobic fermentation in part through an ancient whole genome duplication and retention of glycolytic genes. To evaluate glycolytic rates across diverse yeasts, we developed and deployed an extracellular acidification rates (ECAR) assay on 299 species that span more than 400 million years of evolution and identified a clade in the genus Saturnispora that convergently evolved aerobic fermentation. Through comparative genomics and transcriptomics, we found that several glycolytic genes had higher expression and novel cis-regulatory elements in aerobically fermenting Saturnispora species. When the transcription factor required for their activation was deleted in Saturnispora dispora, the mutants had reduced glycolytic rates and increased respiration. Intriguingly, many of the upregulated genes are orthologous to duplicated glycolytic genes in S. cerevisiae. These divergent genetic mechanisms affecting the same set of genes suggest that there are strong evolutionary constraints on how aerobic fermentation can arise.

Horianopoulos, Linda C. [Great Lakes Bioenergy Res↗
DOE OSTI2023

Hydrophobic interactions dominate the recognition of a KRAS G12V neoantigen

Specificity remains a major challenge to current therapeutic strategies for cancer. Mutation associated neoantigens (MANAs) are products of genetic alterations, making them highly specific therapeutic targets. MANAs are HLA-presented (pHLA) peptides derived from intracellular mutant proteins that are otherwise inaccessible to antibody-based therapeutics. Here, we describe the cryo-EM structure of an antibody-MANA pHLA complex. Specifically, we determine a TCR mimic (TCRm) antibody bound to its MANA target, the KRAS G12V peptide presented by HLA-A*03:01. Hydrophobic residues appear to account for the specificity of the mutant G12V residue. We also determine the structure of the wild-type G12 peptide bound to HLA-A*03:01, using X-ray crystallography. Based on these structures, we perform screens to validate the key residues required for peptide specificity. These experiments led us to a model for discrimination between the mutant and the wild-type peptides presented on HLA-A*03:01 based exclusively on hydrophobic interactions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Structural studies of the IFNλ4 receptor complex using cryoEM enabled by protein engineering

Abstract IFNλ4 has posed a conundrum in human immunology since its discovery in 2013, with its expression linked to complications with viral clearance. While genetic and cellular studies revealed the detrimental effects of IFNλ4 expression, extensive structural and functional characterization has been limited by the inability to express and purify the protein, complicating explanations of its paradoxical behavior. In this work, we report a method for robust production of IFNλ4. We then use yeast surface display to affinity-mature IL10Rβ and solve the 72 kilodalton structures of IFNλ4 (3.26 Å) and IFNλ3 (3.00 Å) in complex with their receptors IFNλR1 and IL10Rβ using cryogenic electron microscopy. Comparison of the structures highlights differences in receptor engagement and reveals a distinct 12-degree rotation in overall receptor geometry, providing a potential mechanistic explanation for differences in cell signaling, downstream gene induction, and antiviral activities. Further, we perform a structural analysis using molecular modeling and simulation to identify a unique region of IFNλ4 that, when replaced, enables secretion of the protein from cells. These findings provide a structural and functional understanding of the IFNλ4 protein and enable future comprehensive studies towards correcting IFNλ4 dysfunction in large populations of affected patients.

Science & Technology - Other Topics↗
DOE OSTI2021

RNA-Seq Reveals that Light and Darkness Are Different Stimuli in Freshwater Heterotrophic Actinobacteria

Light is a ubiquitous source of both energy and information in surface environments, and regulates gene expression not only in photosynthetic microorganisms, but in a broad range of photoheterotrophic and heterotrophic microbes as well. Actinobacteria are keystone species in surface freshwater environments, where the ability to sense light could allow them to coordinate periods of nutrient uptake and metabolic activity with primary production. The model freshwater Actinobacteria Rhodoluna (R.) lacicola strain MWH-Ta8 and Aurantimicrobium(A.) photophilum strain MWH-Mo1 grow faster in the light than in the dark, but do not use light energy to support growth. Here, we characterize transcription throughout a light-dark cycle in R. lacicola and A. photophilum. In both species, some genes encoding carbohydrate metabolism and storage are upregulated in the light. However, expression of genes of the TCA cycle is only coordinated with light availability in R. lacicola. In fact, the majority of genes that respond to light and darkness in these two species are different, even though their light-responsive phenotypes are similar. The ability to respond to light and darkness may be widespread in freshwater Actinobacteria, but the genetic networks controlled by these two stimuli may vary significantly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A novel machine learning-based optimization algorithm (ActivO) for accelerating simulation-driven engine design

A novel design optimization approach (ActivO) that employs an ensemble of machine learning algorithms is presented. The proposed approach is a surrogate-based scheme, where the predictions of a weak leaner and a strong learner are utilized within an active learning loop. The weak learner is used to identify promising regions within the design space to explore, while the strong learner is used to determine the exact location of the optimum within promising regions. For each design iteration, exploration is done by randomly selecting evaluation points within regions where the weak learner-predicted fitness is high. The global optimum obtained by using the strong learner as a surrogate is also evaluated to enable rapid convergence once the most promising region has been identified. First, the performance of ActivO was compared against five other optimizers on a cosine mixture function with 25 local optima and one global optimum. In the second problem, the objective was to minimize indicated specific fuel consumption of a compression-ignition internal combustion (IC) engine while adhering to desired constraints associated with in-cylinder pressure and emissions. In this work, the efficacy of the proposed approach is compared to that of a genetic algorithm, which is widely used within the internal combustion engine community for engine optimization, showing that ActivO reduces the number of function evaluations needed to reach the global optimum, and thereby time-to-design by 80%. Furthermore, the optimization of engine design parameters leads to savings of around 1.9% in energy consumption, while maintaining operability and acceptable pollutant emissions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Generating Co-expression Networks for Three Cyanobacteria: Synechococcus sp. PCC 7942, Synechococcus sp. PCC 7002, Synechocystis sp. PCC 6803

Cyanobacteria are photosynthetic organisms capable of high growth rate and represent a promising bioplatform for harnessing the sun’s energy to make biofuel. Additionally, the process of photosynthesis absorbs CO2 from the environment. Understanding the metabolic processes involved in photosynthesis could lead to solutions to the recent rise of CO2 concentration in Earth’s atmosphere and the associated climate change. More research on the transcriptional regulation of these cells is needed to learn how to harness the untapped potential of cyanobacteria for these applications. Transcriptional analysis via RNA-seq provides an understanding of how gene expression changes at the mRNA level under diverse growing conditions. I systematically collected and analyzed RNA-Seq data obtained under a variety of conditions and available on the NCBI database for three cyanobacteria model organisms: Synechococcus elongatus sp. PCC 7942, Synechococcus sp. PCC 7002, and Synechocystis sp. PCC 6803. For each organism, the data was mapped to a reference genome to characterize the RNA expression profile. Samples were checked for quality based on the number of reads and the correlation of the expression profile between labeled replicates. All samples were transformed into transcripts per million reads, followed by a log transformation to account for the wide range of sample sizes. Gene co-expression networks were generated and analyzed for each species using Cytoscape. These networks provide a base level of gene expression for each species. The network topology and high-betweeness nodes of these networks need to be analyzed further to provide insight on potential ways to harness cyanobacteria genetics. Additionally, these datasets can be used together to form a core genome network analysis- one that includes only the genes that are homologous between the three species. This project has prepared the way for a more in-depth study on photosynthetic microbes on a genetic level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The role of CenKR in the coordination of Rhodobacter sphaeroides cell elongation and division

ABSTRACT Cell elongation and division are essential aspects of the bacterial life cycle that must be coordinated for viability and replication. The impact of misregulation of these processes is not well understood as these systems are often not amenable to traditional genetic manipulation. Recently, we reported on the CenKR two-component system (TCS) in the Gram-negative bacterium Rhodobacter sphaeroides that is genetically tractable, widely conserved in α-proteobacteria, and directly regulates the expression of components crucial for cell elongation and division, including genes encoding subunit of the Tol-Pal complex. In this work, we show that overexpression of cenK results in cell filamentation and chaining. Using cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET), we generated high-resolution two-dimensional (2D) images and three-dimensional (3D) volumes of the cell envelope and division septum of wild-type cells and a cenK overexpression strain finding that these morphological changes stem from defects in outer membrane (OM) and peptidoglycan (PG) constriction. By monitoring the localization of Pal, PG biosynthesis, and the bacterial cytoskeletal proteins MreB and FtsZ, we developed a model for how increased CenKR activity leads to changes in cell elongation and division. This model predicts that increased CenKR activity decreases the mobility of Pal, delaying OM constriction, and ultimately disrupting the midcell positioning of MreB and FtsZ and interfering with the spatial regulation of PG synthesis and remodeling. IMPORTANCE By coordinating cell elongation and division, bacteria maintain their shape, support critical envelope functions, and orchestrate division. Regulatory and assembly systems have been implicated in these processes in some well-studied Gram-negative bacteria. However, we lack information on these processes and their conservation across the bacterial phylogeny. In R. sphaeroides and other α-proteobacteria, CenKR is an essential two-component system (TCS) that regulates the expression of genes known or predicted to function in cell envelope biosynthesis, elongation, and/or division. Here, we leverage unique features of CenKR to understand how increasing its activity impacts cell elongation/division and use antibiotics to identify how modulating the activity of this TCS leads to changes in cell morphology. Our results provide new insight into how CenKR activity controls the structure and function of the bacterial envelope, the localization of cell elongation and division machinery, and cellular processes in organisms with importance in health, host-microbe interactions, and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Growth-associated polyhydroxybutyrate accumulation in Azospira suillum PS during aerobic and perchlorate respiration

Polyhydroxyalkanoates (PHAs) are widespread microbial storage polymers increasingly recognized for roles beyond carbon and energy storage, including redox homeostasis and stress physiology. While PHA accumulation is classically associated with stationary-phase metabolism under severe nutrient imbalance, comparatively little is known about growth-associated PHA synthesis in facultative anaerobes with unusual respiratory strategies. Here, we investigated polyhydroxybutyrate (PHB) metabolism in Azospira suillum PS, a genetically tractable perchlorate-reducing bacterium capable of both aerobic and anaerobic respiration. Using physiological growth experiments, targeted gene deletions, PHB extractions, and intracellular redox measurements, we examined PHB accumulation under varying respiratory and nutrient conditions. We demonstrate that PHB accumulates during exponential growth under moderately nitrogen-limited conditions, both aerobically and during perchlorate respiration, representing a rare example of growth-associated PHB synthesis under anaerobic conditions. Genomic analysis revealed four phaC homologs, one of which could not be deleted under the experimental conditions tested and co-localized with phaB and phaR. Redox profiling further revealed a strong positive correlation between PHB accumulation and intracellular NADPH/NADP+ ratios. Together, these findings expand the physiological contexts in which PHB synthesis is known to occur and highlight perchlorate-respiring bacteria as underexplored model systems for studying growth-integrated carbon and redox storage strategies.

Meier, David A O↗
DOE OSTI2023

tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking

A critical step in structure-based drug discovery is predicting whether and how a candidate molecule binds to a model of a therapeutic target. However, substantial protein side chain movements prevent current screening methods, such as docking, from accurately predicting the ligand conformations and require expensive refinements to produce viable candidates. Here, we present the development of a high-throughput and flexible ligand pose refinement workflow, called “tinyIFD”. The main features of the workflow include the use of specialized high-throughput, small-system MD simulation code mdgx.cuda and an actively learning model zoo approach. We show the application of this workflow on a large test set of diverse protein targets, achieving 66% and 76% success rates for finding a crystal-like pose within the top-2 and top-5 poses, respectively. We also applied this workflow to the SARS-CoV-2 main protease (M pro ) inhibitors, where we demonstrate the benefit of the active learning aspect in this workflow.

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

Dynamic basis of supercoiling-dependent DNA interrogation by Cas12a via R-loop intermediates

The sequence specificity and programmability of DNA binding and cleavage have enabled widespread applications of CRISPR-Cas12a in genetic engineering. As an RNA-guided CRISPR endonuclease, Cas12a engages a 20-base pair (bp) DNA segment by forming a three-stranded R-loop structure in which the guide RNA hybridizes to the DNA target. Here we use single-molecule torque spectroscopy to investigate the dynamics and mechanics of R-loop formation of two widely used Cas12a orthologs at base-pair resolution. We directly observe kinetic intermediates corresponding to a ~5 bp initial RNA-DNA hybridization and a ~17 bp intermediate preceding R-loop completion, followed by transient DNA unwinding that extends beyond the 20 bp R-loop. The complex multistate landscape of R-loop formation is ortholog-dependent and shaped by target sequence, mismatches, and DNA supercoiling. A four-state kinetic model captures essential features of Cas12a R-loop dynamics and provides a biophysical framework for understanding Cas12a activity and specificity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhancing chemical bioproduction with rational control of bacterial post-translational modifications

Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Metagenome-assembled genome extraction and analysis from microbiomes using KBase

Uncultivated Bacteria and Archaea account for the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only become possible recently. In order to realize the hope of capturing Earth’s microbial genetic complement and to facilitate the investigation of the functional roles of specific lineages in a given ecosystem, technologies that accelerate the recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high-quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). Overall, these steps take about a day to obtain extracted genomes when starting from smaller environmental shotgun read libraries, or up to about a week from larger libraries. In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAGs, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq and others. While portions of such capabilities are available individually from other resources, the combination of the intuitive usability, data interoperability and integration of tools in a freely available computational resource makes KBase a powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended with additional MAG recovery and analysis tools, via the KBase software development kit (SDK).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A prognostic risk model for glioma patients by systematic evaluation of genomic variations

The overall survival rate of gliomas has not significantly improved despite new effective treatments, mainly due to tumor heterogeneity and drug delivery. Here, we perform an integrated clinic-genomic analysis of 1, 477 glioma patients from a Chinese cohort and a TCGA cohort and propose a potential prognostic model for gliomas. We identify that SBS11 and SBS23 mutational signatures are associated with glioma recurrence and indicate worse prognosis only in low-grade type of gliomas and IDH-Mut subtype. We also identify 42 genomic features associated with distinct clinical outcome and successfully used ten of these to develop a prognostic risk model of gliomas. The high-risk glioma patients with shortened survival were characterized by high level of frequent copy number alterations including PTEN, CDKN2A/B deletion, EGFR amplification, less IDH1 or CIC gene mutations, high infiltration levels of immunosuppressive cells and activation of G2M checkpoint and Oxidative phosphorylation oncogenic pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Transposition of HOPPLA in siRNA-deficient plants suggests a limited effect of the environment on retrotransposon mobility in Brachypodium distachyon

Long terminal repeat retrotransposons (LTR-RTs) are powerful mutagens regarded as a major source of genetic novelty and important drivers of evolution. Yet, the uncontrolled and potentially selfish proliferation of LTR-RTs can lead to deleterious mutations and genome instability, with large fitness costs for their host. While population genomics data suggest that an ongoing LTR-RT mobility is common in many species, the understanding of their dual role in evolution is limited. Here, we harness the genetic diversity of 320 sequenced natural accessions of the Mediterranean grass Brachypodium distachyon to characterize how genetic and environmental factors influence plant LTR-RT dynamics in the wild. When combining a coverage-based approach to estimate global LTR-RT copy number variations with mobilome-sequencing of nine accessions exposed to eight different stresses, we find little evidence for a major role of environmental factors in LTR-RT accumulations in B. distachyon natural accessions. Instead, we show that loss of RNA polymerase IV (Pol IV), which mediates RNA-directed DNA methylation in plants, results in high transcriptional and transpositional activities of RLC_BdisC024 (HOPPLA) LTR-RT family elements, and that these effects are not stress-specific. This work supports findings indicating an ongoing mobility in B. distachyon and reveals that host RNA-directed DNA methylation rather than environmental factors controls their mobility in this wild grass model.

59 BASIC BIOLOGICAL SCIENCES↗