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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The eco-evolutionary role of fire in shaping terrestrial ecosystems

Fire is an inherently evolutionary process, even though much more emphasis has been given to ecological responses of plants and their associated communities to fire. Here, in this work, we synthesize contributions to a Special Feature entitled ‘Fire as a dynamic ecological and evolutionary force’ and place them in a broader context of fire research. Topics covered in this Special Feature include a perspective on the impacts of novel fire regimes on differential forest mortality, discussions on new approaches to investigate vegetation-fire feedbacks and resulting plant syndromes, synthesis of fire impacts on plant–fungal interactions, and a meta-analysis of arthropod community responses to fire. We conclude by suggesting pathways forward to better understand the ecological and evolutionary consequences of fire. These include developing ecological and evolutionary databases for fire ecology, integrating hierarchical genetic structure or phylogenetic structure, and developing new experimental frameworks that limit context-dependent outcomes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Software Helps Retrieve Information Relevant to the User

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Mathe, Natalie↗
DOE OSTI2024

VISTA Enhancer browser: an updated database of tissue-specific developmental enhancers

Regulatory elements (enhancers) are major drivers of gene expression in mammals and harbor many genetic variants associated with human diseases. Here, we present an updated VISTA Enhancer Browser (https://enhancer.lbl.gov), a database of transgenic enhancer assays conducted in developing mouse embryos in vivo. Since the original publication in 2007, the database grew nearly 20-fold from 250 to over 4500 experiments and currently harbors over 23 500 images. The updated database provides structured information on experiments conducted at different stages of embryonic development, including enhancer activities of human pathogenic and synthetic variants and sequences derived from a variety of species. In addition to manually curated results of thousands of individual experiments, the new database also features hundreds of manually curated comparisons between alleles. The VISTA Enhancer Browser provides a crucial resource for study of human genetic variation, gene regulation and developmental biology.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Methods for determining the genetic affinity of microorganisms and viruses

Selecting which sub-sequences in a database of nucleic acid such as 16S rRNA are highly characteristic of particular groupings of bacteria, microorganisms, fungi, etc. on a substantially phylogenetic tree. Also applicable to viruses comprising viral genomic RNA or DNA. A catalogue of highly characteristic sequences identified by this method is assembled to establish the genetic identity of an unknown organism. The characteristic sequences are used to design nucleic acid hybridization probes that include the characteristic sequence or its complement, or are derived from one or more characteristic sequences. A plurality of these characteristic sequences is used in hybridization to determine the phylogenetic tree position of the organism(s) in a sample. Those target organisms represented in the original sequence database and sufficient characteristic sequences can identify to the species or subspecies level. Oligonucleotide arrays of many probes are especially preferred. A hybridization signal can comprise fluorescence, chemiluminescence, or isotopic labeling, etc.; or sequences in a sample can be detected by direct means, e.g. mass spectrometry. The method's characteristic sequences can also be used to design specific PCR primers. The method uniquely identifies the phylogenetic affinity of an unknown organism without requiring prior knowledge of what is present in the sample. Even if the organism has not been previously encountered, the method still provides useful information about which phylogenetic tree bifurcation nodes encompass the organism.

Fox, George E.↗
NASA NTRS2002

Genes encoding calmodulin-binding proteins in the Arabidopsis genome

Analysis of the recently completed Arabidopsis genome sequence indicates that approximately 31% of the predicted genes could not be assigned to functional categories, as they do not show any sequence similarity with proteins of known function from other organisms. Calmodulin (CaM), a ubiquitous and multifunctional Ca(2+) sensor, interacts with a wide variety of cellular proteins and modulates their activity/function in regulating diverse cellular processes. However, the primary amino acid sequence of the CaM-binding domain in different CaM-binding proteins (CBPs) is not conserved. One way to identify most of the CBPs in the Arabidopsis genome is by protein-protein interaction-based screening of expression libraries with CaM. Here, using a mixture of radiolabeled CaM isoforms from Arabidopsis, we screened several expression libraries prepared from flower meristem, seedlings, or tissues treated with hormones, an elicitor, or a pathogen. Sequence analysis of 77 positive clones that interact with CaM in a Ca(2+)-dependent manner revealed 20 CBPs, including 14 previously unknown CBPs. In addition, by searching the Arabidopsis genome sequence with the newly identified and known plant or animal CBPs, we identified a total of 27 CBPs. Among these, 16 CBPs are represented by families with 2-20 members in each family. Gene expression analysis revealed that CBPs and CBP paralogs are expressed differentially. Our data suggest that Arabidopsis has a large number of CBPs including several plant-specific ones. Although CaM is highly conserved between plants and animals, only a few CBPs are common to both plants and animals. Analysis of Arabidopsis CBPs revealed the presence of a variety of interesting domains. Our analyses identified several hypothetical proteins in the Arabidopsis genome as CaM targets, suggesting their involvement in Ca(2+)-mediated signaling networks.

NASA Discipline Plant Biology↗
NASA NTRS2004

NASA Technology Takes Center Stage

In today's fast-paced business world, there is often more information available to researchers than there is time to search through it. Data mining has become the answer to finding the proverbial "needle in a haystack," as companies must be able to quickly locate specific pieces of information from large collections of data. Perilog, a suite of data-mining tools, searches for hidden patterns in large databases to determine previously unrecognized relationships. By retrieving and organizing contextually relevant data from any sequence of terms - from genetic data to musical notes - the software can intelligently compile information about desired topics from databases.

Source record↗
DOE OSTI2023

IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata

Plasmids are mobile genetic elements found in many clades of Archaea and Bacteria. They drive horizontal gene transfer, impacting ecological and evolutionary processes within microbial communities, and hold substantial importance in human health and biotechnology. To support plasmid research and provide scientists with data of an unprecedented diversity of plasmid sequences, we introduce the IMG/PR database, a new resource encompassing 699 973 plasmid sequences derived from genomes, metagenomes and metatranscriptomes. IMG/PR is the first database to provide data of plasmid that were systematically identified from diverse microbiome samples. IMG/PR plasmids are associated with rich metadata that includes geographical and ecosystem information, host taxonomy, similarity to other plasmids, functional annotation, presence of genes involved in conjugation and antibiotic resistance. The database offers diverse methods for exploring its extensive plasmid collection, enabling users to navigate plasmids through metadata-centric queries, plasmid comparisons and BLAST searches. The web interface for IMG/PR is accessible at https://img.jgi.doe.gov/pr. Plasmid metadata and sequences can be downloaded from https://genome.jgi.doe.gov/portal/IMG_PR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Relationship and distribution of Salmonella enterica serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database

Background: Of the > 2600 Salmonella serovars, Salmonella enterica serovar I 4,[5],12:i:- (serovar I 4,[5],12:i:-) has emerged as one of the most common causes of human salmonellosis and the most frequent multidrug-resistant (MDR; resistance to ≥3 antimicrobial classes) nontyphoidal Salmonella serovar in the U.S. Serovar I 4,[5],12:i:- isolates have been described globally with resistance to ampicillin, streptomycin, sulfisoxazole, and tetracycline (R-type ASSuT) and an integrative and conjugative element with multi-metal tolerance named Salmonella Genomic Island 4 (SGI-4). Results: We analyzed 13,612 serovar I 4,[5],12:i:- strain sequences available in the NCBI Pathogen Detection database to determine global distribution, animal sources, presence of SGI-4, occurrence of R-type ASSuT, frequency of antimicrobial resistance (AMR), and potential transmission clusters. Genome sequences for serovar I 4,[5],12:i:- strains represented 30 countries from 5 continents (North America, Europe, Asia, Oceania, and South America), but sequences from the United States (59%) and the United Kingdom (28%) were dominant. The metal tolerance island SGI-4 and the R-type ASSuT were present in 71 and 55% of serovar I 4,[5],12:i:- strain sequences, respectively. Sixty-five percent of strain sequences were MDR which correlates to serovar I 4,[5],12:i:- being the most frequent MDR serovar. The distribution of serovar I 4,[5],12:i:- strain sequences in the NCBI Pathogen Detection database suggests that swine-associated strain sequences were the most frequent food-animal source and were significantly more likely to contain the metal tolerance island SGI-4 and genes for MDR compared to all other animal-associated isolate sequences. Conclusions: Our study illustrates how analysis of genomic sequences from the NCBI Pathogen Detection database can be utilized to identify the prevalence of genetic features such as antimicrobial resistance, metal tolerance, and virulence genes that may be responsible for the successful emergence of bacterial foodborne pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multimodal Approaches for Leveraging Domain Knowledge with State-of-the-Art Machine Learning to Engineer Biocatalysts

This grant aimed to accelerate the development of specialized enzymes—biological catalysts essential for sustainable manufacturing and medicine—by integrating traditional laboratory evolution with cutting-edge artificial intelligence. To achieve this, we developed a suite of high-throughput sequencing tools and a centralized database to bridge the gap between a protein’s genetic "code" and its physical function. By training machine learning models on large datasets, we also demonstrated the ability to move beyond slow, trial-and-error testing to a "generative" approach, where AI can independently design new, versatile enzymes like tryptophan synthases. Ultimately, these findings demonstrate that combining laboratory data with computer-guided design enables the engineering of highly efficient biological tools with unprecedented speed and precision.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1992

The Vredefort Dome: Review of geology and deformation phenomena and status report on current knowledge and remaining problematics (five years after the cryptoexplosion workshop)

The Vredefort structure located in the center of the Witwatersrand basin in South Africa and the Sudbury structure in Canada are widely considered the two oldest and largest impact structures still evident on Earth. Both structures are very similar in a number of geological aspects (e.g., association with major economic ore deposits, similar ages of ca. 2 Ga, abundant pseudotachylite as well as shatter cone occurrences, overturned collar). However, whereas the geological community generally accepts an impact origin for the Sudbury structure, a number of researchers are still reluctant to accept this for the Vredefort Dome. Therefore, the aim of this review is to present new data, highlight the most obvious shortcomings in the current database, and to summarize the major arguments in the genetic controversy.

Reimold, W. U.↗
DOE OSTI2022

Plant carbohydrate storage: intra- and inter-specific trade-offs reveal a major life history trait

Trade-offs among carbon sinks constrain how trees physiologically, ecologically, and evolutionarily respond to their environments. These trade-offs typically fall along a productive growth to conservative, bet-hedging continuum. How nonstructural carbohydrates (NSCs) stored in living tree cells (known as carbon stores) fit in this trade-off framework is not well understood. Here, we examined relationships between growth and storage using both within species genetic variation from a common garden, and across species phenotypic variation from a global database. We demonstrate that storage is actively accumulated, as part of a conservative, bet-hedging life history strategy. Storage accumulates at the expense of growth both within and across species. Within the species Populus trichocarpa, genetic trade-offs show that for each additional unit of wood area growth (in cm 2 yr –1 ) that genotypes invest in, they lose 1.2 to 1.7 units (mg g –1 NSC) of storage. Across species, for each additional unit of area growth (in cm 2 yr –1 ), trees, on average, reduce their storage by 9.5% in stems and 10.4% in roots. Our findings impact our understanding of basic plant biology, fit storage into a widely used growth-survival trade-off spectrum describing life history strategy, and challenges the assumptions of passive storage made in ecosystem models today.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

pnnl-predictive-phenomics/csc031cyc

Organism-specific Pathway/Genome databases enable the analysis, visualization and interrogation of metabolism, regulation, and genetics. Licensed under the CC-BY-4.0 license

Zucker, Jeremy [Pacific Northwest National Laborat↗
DOE OSTI2025

pnnl-predictive-phenomics/csc043cyc

Organism-specific Pathway/Genome databases enable the analysis, visualization and interrogation of metabolism, regulation, and genetics. Licensed under the CC-BY-4.0 license

Zucker, Jeremy [Pacific Northwest National Laborat↗
DOE OSTI2025

Integrase-on-Demand

SAND2025-07449O Integrase-on-Demand is a software tool that allows users to identify regions in genomic sequences where genetic material can be integrated with high probability. It uses a database of integrases and their DNA attachment sites to search against any genomic sequence, producing a list of open sites, the integrase sequence, and the source of the genomic island. The program requires MASH software to be available on the system. It consists of a main script and a precomputed input file, with a taxonomy mode that searches closely related genomes and a search mode that looks for identical attachment site matches in the integrase/attachment input file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Williams, Kelly [Sandia National Lab. (SNL-CA), Li↗
DOE OSTI2025

hashin_shtrikman_mp: a package for the optimal design and discovery of multi-phase composite materials

hashin_shtrikman_mp is a tool for composites designers who have desired composite properties in mind, but who do not yet have an underlying formulation. The library utilizes the tightest theoretical bounds on the effective properties of composite materials with unspecified microstructure – the Hashin-Shtrikman bounds – to identify candidate theoretical materials, find real materials that are close to the candidates, and determine the optimal volume fractions for each of the constituents in the resulting composite. Its features include (i) leveraging of materials in the Materials Project database, (ii) integration with the Materials Project API, (iii) use of genetic machine-learning, (iv) agnosticism to underlying microstructure, and (v) ultimate engineering application, make it a tool with much broader applications than its predecessors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Modeling and Optimization of Zeolites for Contaminant Removal from Coal Combustion Impoundment Leachates

Coal Combustion Residual (CCR) landfills in the U.S. can lead to elevated contaminant concentrations in groundwater and runoff, particularly of arsenic, boron, and selenium. Zeolites can be readily synthesized from materials contained within the coal combustion ash impoundments and can be cation-exchanged to enhance adsorption capacity, selectivity, and reactivity. However, the optimization of zeolites becomes a daunting task when accounting for the variety of Si:Al ratios, the species of extra-framework cations present, and the zeolite pore structure. Molecular simulations provide methods to study and guide the design of zeolites for the sorption of contaminants from aqueous solution. In this work, models that predict the sorption of arsenic, boron, and selenium from water using cation-exchanged zeolites. Because of the lack of experimental adsorption data for these species of contaminants, models were parametrized to reproduce the results of first-principles calculations and then used to predict sorption for zeolites for a dataset containing 6000 combinations of zeolites and sorption conditions. Machine learning was used to train a model to predict sorption for materials in this database based on the results of the molecular simulations. Next, a genetic algorithm was used to optimize zeolites for the removal of each contaminant from aqueous solution for individual impoundment sites based on contaminant concentrations reported by the Electric Power Research Institute.

Findley, John↗