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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases

Model organisms are essential experimental platforms for discovering gene functions, defining protein and genetic networks, uncovering functional consequences of human genome variation, and for modeling human disease. For decades, researchers who use model organisms have relied on Model Organism Databases (MODs) and the Gene Ontology Consortium (GOC) for expertly curated annotations, and for access to integrated genomic and biological information obtained from the scientific literature and public data archives. Through the development and enforcement of data and semantic standards, these genome resources provide rapid access to the collected knowledge of model organisms in human readable and computation-ready formats that would otherwise require countless hours for individual researchers to assemble on their own. Since their inception, the MODs for the predominant biomedical model organisms [Mus sp (laboratory mouse), Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, Danio rerio, and Rattus norvegicus] along with the GOC have operated as a network of independent, highly collaborative genome resources. In 2016, these six MODs and the GOC joined forces as the Alliance of Genome Resources (the Alliance). By implementing shared programmatic access methods and data-specific web pages with a unified "look and feel," the Alliance is tackling barriers that have limited the ability of researchers to easily compare common data types and annotations across model organisms. To adapt to the rapidly changing landscape for evaluating and funding core data resources, the Alliance is building a modern, extensible, and operationally efficient "knowledge commons" for model organisms using shared, modular infrastructure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Diverse data supports the transition of filamentous fungal model organisms into the post-genomics era

As model organisms filamentous fungi have been important since the beginning of modern biological inquiry and have benefitted from open data since the earliest genetic maps were shared. From early origins in simple Mendelian genetics of mating types, parasexual genetics of colony colour, and the foundational demonstration of the segregation of a nutritional requirement, the contribution of research systems utilising filamentous fungi has spanned the biochemical genetics era, through the molecular genetics era, and now are at the very foundation of diverse omics approaches to research and development. Fungal model organisms have come from most major taxonomic groups although Ascomycete filamentous fungi have seen the most major sustained effort. In addition to the published material about filamentous fungi, shared molecular tools have found application in every area of fungal biology. Likewise, shared data has contributed to the success of model systems. Furthermore, the scale of data supporting research with filamentous fungi has grown by 10 to 12 orders of magnitude. From genetic to molecular maps, expression databases, and finally genome resources, the open and collaborative nature of the research communities has assured that the rising tide of data has lifted all of the research systems together.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Superplasticizer to layered calcium aluminate hydrate interface characterized using model organic molecules

Ten organic molecule models simulating the chemical functions of commercial superplasticizers used in the cement/concrete industry were intercalated into lamellar calcium aluminate hydrates to synthesize hybrid AFm phases. AFm phases, encountered in cement hydration chemistry, belong to the large Layered Double Hydroxide (LDH) family. The intercalation process was performed using the anion exchange method. The affinities of the model molecules toward the AFm mineral layers, [Ca{sub 2}Al(OH){sub 6}]{sup +}, were compared using several complementary techniques. They display the following tendencies: –PO{sub 3}{sup 2-} > –SO{sub 3}{sup -} > –CO{sub 2}{sup -} for the hydrophilic parts and heptyl-R > phenyl-R > pentyl-R > ethyl-R for the hydrophobic parts. The organic-inorganic interface of the hybrid AFm phases was achieved. The organic molecule arrangement is either perpendicular or parallel to the inorganic main layer, resulting in various connection modes, from intercalation to grafting. The results enable a better understanding of the chemical reactivity of the utilized superplasticizers during the concrete setting process.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The influence of disease categories on gene candidate predictions from model organism phenotypes

The molecular etiology is still to be identified for about half of the currently described Mendelian diseases in humans, thereby hindering efforts to find treatments or preventive measures. Advances, such as new sequencing technologies, have led to increasing amounts of data becoming available with which to address the problem of identifying disease genes. Therefore, automated methods are needed that reliably predict disease gene candidates based on available data. We have recently developed Exomiser as a tool for identifying causative variants from exome analysis results by filtering and prioritising using a number of criteria including the phenotype similarity between the disease and mouse mutants involving the gene candidates. Initial investigations revealed a variation in performance for different medical categories of disease, due in part to a varying contribution of the phenotype scoring component. In this study, we further analyse the performance of our cross-species phenotype matching algorithm, and examine in more detail the reasons why disease gene filtering based on phenotype data works better for certain disease categories than others. We found that in addition to misleading phenotype alignments between species, some disease categories are still more amenable to automated predictions than others, and that this often ties in with community perceptions on how well the organism works as model. In conclusion, our automated disease gene candidate predictions are highly dependent on the organism used for the predictions and the disease category being studied. Future work on computational disease gene prediction using phenotype data would benefit from methods that take into account the disease category and the source of model organism data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

3′ RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism

The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

3’ RNA-seq↗
DOE OSTI2019

Crystal structure of the 65-kilodalton amino-terminal fragment of DNA topoisomerase I from the gram-positive model organism Streptococcus mutans

Here, we report the first structure of topoisomerase I determined from the gram-positive bacterium, S. mutans. Bacterial topoisomerase I is an ATP-independent type 1A topoisomerase that uses the inherent torsional strain within hyper-negatively supercoiled DNA as an energy source for its critical function of DNA relaxation. Interest in the enzyme has gained momentum as it has proven to be essential in various bacterial organisms. In order to aid in further biochemical characterization, the apo 65-kDa amino-terminal fragment of DNA topoisomerase I from the gram-positive model organism Streptococcus mutans was crystalized and a three-dimensional structure was determined to 2.06 Å resolution via x-ray crystallography. The overall structure illustrates the four classic major domains that create the traditional topoisomerase I “lock” formation comprised of a sizable toroidal aperture atop what is considered to be a highly dynamic body. A catalytic tyrosine residue resides at the interface between two domains and is known to form a 5’ phosphotyrosine DNA-enzyme intermediate during transient single-stranded cleavage required for enzymatic relaxation of hyper negative DNA supercoils. Surrounding the catalytic tyrosine residue is the remainder of the highly conserved active site. Within 5 Å from the catalytic center, only one dissimilar residue is observed between topoisomerase I from S. mutans and the gram-negative model organism E. coli. Immediately adjacent to the conserved active site, however, S. mutans topoisomerase I displays a somewhat unique nine residue loop extension not present in any bacterial topoisomerase I structures previously determined other than that of an extremophile.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Rapidly moving new bacteria to model-organism status

The paradigm of large research communities collectively working on a small number of model bacteria such as Escherichia coli and Bacillus subtilis is changing. While these classic model bacteria will continue to be important for advanced systems biology and new technology development, we envision that increasingly small research teams will be deeply investigating their own favorite strains, for example as new hosts for metabolic engineering or as key members of a complex microbiome. Given the lack of a research community and the sheer number of possible bacteria to interrogate, the development and application of technologies to rapidly and inexpensively advance these unstudied strains to ‘model-organism’ status is imperative. Here, we discuss the minimal information and tools necessary to develop a new model bacterium and how existing approaches can bring this power into the hands of a single investigator.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Model Organisms To Study Methanogenesis, a Uniquely Archaeal Metabolism

Methanogenic archaea are the only organisms that produce CH 4 as part of their energy-generating metabolism. They are ubiquitous in oxidant-depleted, anoxic environments such as aquatic sediments, anaerobic digesters, inundated agricultural fields, the rumen of cattle, and the hindgut of termites, where they catalyze the terminal reactions in the degradation of organic matter. Methanogenesis is the only metabolism that is restricted to members of the domain Archaea. Here, we discuss the importance of model organisms in the history of methanogen research, including their role in the discovery of the archaea and in the biochemical and genetic characterization of methanogenesis. Finally, we also discuss outstanding questions in the field and newly emerging model systems that will expand our understanding of this uniquely archaeal metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Status of genome function annotation in model organisms and crops

Abstract Since the entry into genome‐enabled biology several decades ago, much progress has been made in determining, describing, and disseminating the functions of genes and their products. Yet, this information is still difficult to access for many scientists and for most genomes. To provide easy access and a graphical summary of the status of genome function annotation for model organisms and bioenergy and food crop species, we created a web application ( https://genomeannotation.rheelab.org ) to visualize, search, and download genome annotation data for 28 species. The summary graphics and data tables will be updated semi‐annually, and snapshots will be archived to provide a historical record of the progress of genome function annotation efforts. Clear and simple visualization of up‐to‐date genome function annotation status, including the extent of what is unknown, will help address the grand challenge of elucidating the functions of all genes in organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A synthetic ecology perspective: How well does behavior of model organisms in the laboratory predict microbial activities in natural habitats?

In this perspective article, we question how well model organisms, the ones that are easy to cultivate in the laboratory and that show robust growth and biomass accumulation, reflect the dynamics and interactions of microbial communities observed in nature. Today's -omics toolbox allows assessing the genomic potential of microbes in natural environments in a high-throughput fashion and at a strain-level resolution. However, understanding of the details of microbial activities and of the mechanistic bases of community function still requires experimental validation in simplified and fully controlled systems such as synthetic communities. We have studied methane utilization in Lake Washington sediment for a few decades and have identified a number of species genetically equipped for this activity. We have also identified cooccurring satellite species that appear to form functional communities together with the methanotrophs. Here, we compare experimental findings from manipulation of natural communities involved in metabolism of methane in this niche with findings from manipulation of synthetic communities assembled in the laboratory of species originating from the same study site, from very simple (two-species) to rather complex (50-species) synthetic communities. We observe some common trends in community dynamics between the two types of communities, toward representation of specific functional guilds. However, we also identify strong discrepancies between the dominant methane oxidizers in synthetic communities compared to natural communities, under similar incubation conditions. Furthermore, these findings highlight the challenges that exist in using the synthetic community approach to modeling dynamics and species interactions in natural communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Integration of evidence across human and model organism studies: A meeting report

The National Institute on Drug Abuse and Joint Institute for Biological Sciences at the Oak Ridge National Laboratory hosted a meeting attended by a diverse group of scientists with expertise in substance use disorders (SUDs), computational biology, and FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing. The meeting's objective was to discuss and evaluate better strategies to integrate genetic, epigenetic, and 'omics data across human and model organisms to achieve deeper mechanistic insight into SUDs. Specific topics were to (a) evaluate the current state of substance use genetics and genomics research and fundamental gaps, (b) identify opportunities and challenges of integration and sharing across species and data types, (c) identify current tools and resources for integration of genetic, epigenetic, and phenotypic data, (d) discuss steps and impediment related to data integration, and (e) outline future steps to support more effective collaboration—particularly between animal model research communities and human genetics and clinical research teams. This review summarizes key facets of this catalytic discussion with a focus on new opportunities and gaps in resources and knowledge on SUDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency

Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein– protein association neighbors. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders.

semantic comparison↗
DOE OSTI2014

Inference of Expanded Lrp-Like Feast/Famine Transcription Factor Targets in a Non-Model Organism Using Protein Structure-Based Prediction

Widespread microbial genome sequencing presents an opportunity to understand the gene regulatory networks of non-model organisms. This requires knowledge of the binding sites for transcription factors whose DNA-binding properties are unknown or difficult to infer. We adapted a protein structure-based method to predict the specificities and putative regulons of homologous transcription factors across diverse species. As a proof-of-concept we predicted the specificities and transcriptional target genes of divergent archaeal feast/famine regulatory proteins, several of which are encoded in the genome of Halobacterium salinarum. This was validated by comparison to experimentally determined specificities for transcription factors in distantly related extremophiles, chromatin immunoprecipitation experiments, and cis-regulatory sequence conservation across eighteen related species of halobacteria. Through this analysis we were able to infer that Halobacterium salinarum employs a divergent local trans-regulatory strategy to regulate genes (carA and carB) involved in arginine and pyrimidine metabolism, whereas Escherichia coli employs an operon. The prediction of gene regulatory binding sites using structure-based methods is useful for the inference of gene regulatory relationships in new species that are otherwise difficult to infer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Validation of the plasma-wall self-organization model for density limit in ECRH-assisted start-up of Ohmic discharges on J-TEXT

Abstract A recently developed plasma-wall self-organization model (Escande et al 2022 Nucl. Fusion 62 026001) predicts a significantly enhanced density limit, which may be attainable in tokamaks with ECRH-assisted Ohmic start-up and sufficiently high initial neutral density. Experiments have been conducted on J-TEXT to validate such a density limit scenario based on this model. Experimental results demonstrate that increasing the pre-filled gas pressure or ECRH power during the start-up phase can help effectively enhance plasma purity and raise the density limit at the flat-top phase. The experimental data shows that density limit increases by a ratio 0.76 / 0.6 ≈ 1.27 for a decrease by a factor 0.13 / 0.33 ≈ 0.4 in C III radiation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Commentary: Duckweeds as model organisms for metabolic studies

Duckweeds have many practical applications, for example in human nutrition, as animal feed, in the production of bioplastics or vaccines, and phytoremediation (Acosta et al., 2021). Under most conditions, they reproduce asexually which provides genetically uniform material with predictable patterns of growth that make them ideal as sentinel organisms for phytotoxicity testing (Park et al., 2021). Asexual growth also results in high biomass production which makes duckweeds promising candidates as biofuel feedstocks (Acosta et al., 2021; Liang et al., 2023). In addition, duckweed species like Lemna minor and Spirodela polyrhiza are also reemerging as model organisms in plant biology as high-quality full genome assemblies and other genomic resources become available (Chang et al., 2016; Acosta et al., 2021). We argue that duckweed species are particularly of interest for the study of primary plant metabolism. Primary metabolism concerns the part of metabolism that is directly involved in the growth and development of plants, and which tends to be highly conserved among plant species. What makes duckweeds particularly attractive is that when grown on liquid media more precise control of physiological conditions can be attained relative to growth of plants in soil. Also, due to their relatively simple anatomical structure and asexual reproduction of fronds by budding, precise characterization of the physiological state under study is possible through one simple metric, i.e., the specific growth rate (rate of dry weight increase per existing dry weight), which can be incorporated relatively easily into metabolic models. This is not possible for land plants, such as Arabidopsis, because over the course of their life cycle, they go through multiple growth stages and phases of anatomical differentiation, which are much more complex to quantify. Furthermore, duckweeds can grow on organic substrates under heterotrophic or photomixotrophic conditions that facilitate isotope tracer studies. For example, in a previous study on duckweed by one of the authors, Lemna gibba (L). was grown on glucose with a position-specific 13 C-label that can be detected and resolved by Mass Spectrometry or Nuclear Magnetic Resonance spectrometry. Using this approach, the 13 C-label was traced into biomass compounds formed from glucose, particularly isoprenoid compounds. Some of the resulting labeling patterns were in apparent disagreement with predictions based on known metabolic pathways for the biosynthesis of isopentenyl pyrophosphate, the universal building block for isoprenoids, (Lichtenthaler et al., 1997). From this data it was deduced that isoprenoid compounds such as carotenoids and isoprenoid chains of phytol and plastoquinone, synthesized in the chloroplast, are produced via a previously unreported plant metabolic pathway, now known as the methylerythitol/deoxyxylulose-5-phosphate pathway (Lichtenthaler et al., 1997).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Synergistic Effect of High Charge and Energy Particle Radiation and Chronological Age on Biomarkers of Oxidative Stress and Tissue Degeneration: A Ground-Based Study Using the Vertebrate Laboratory Model Organism Oryzias latipes

High charge and energy (HZE) particles are a main hazard of the space radiation environment. Uncertainty regarding their health effects is a limiting factor in the design of human exploration-class space missions, that is, missions beyond low earth orbit. Previous work has shown that HZE exposure increases cancer risk and elicits other aging-like phenomena in animal models. In this work, we investigate how a single exposure to HZE particle radiation, early in life, influences the subsequent age-dependent evolution of oxidative stress and appearance of degenerative tissue changes. Embryos of the laboratory model organism, Oryzias latipes (Japanese medaka fish), were exposed to HZE particle radiation at doses overlapping the range of anticipated human exposure. A separate cohort was exposed to reference γ-radiation. Survival was monitored for 750 days, well beyond the median lifespan. The population was also sampled at intervals and liver tissue was subjected to histological and molecular analysis. HZE particle radiation dose and aging contributed synergistically to accumulation of lipid peroxidation products, which are a marker of chronic oxidative stress. This was mirrored by a decline in PPARGC1A mRNA, which encodes a transcriptional co-activator required for expression of oxidative stress defense genes and for mitochondrial maintenance. Consistent with chronic oxidative stress, mitochondria had an elongated and enlarged ultrastructure. Livers also had distinctive, cystic lesions. Depending on the endpoint, effects of γ-rays in the same dose range were either lesser or not detected. Results provide a quantitative and qualitative framework for understanding relative contributions of HZE particle radiation exposure and aging to chronic oxidative stress and tissue degeneration.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

A Decentralized Approach for Modeling Organized Convection Based on Thermal Populations on Microgrids

Abstract In this study, a spectral model for convective transport is coupled to a thermal population model on a two‐dimensional horizontal “microgrid,” covering the typical gridbox size of general circulation models. The goal is to explore new ways of representing impacts of spatial organization in cumulus cloud fields. The thermals are considered the smallest building block of convection, with thermal life cycle and movement represented through binomial functions. Thermals interact through two simple rules, reflecting pulsating growth and environmental deformation. Long‐lived thermal clusters thus form on the microgrid, exhibiting scale growth and spacing that represent simple forms of spatial organization and memory. Size distributions of cluster number are diagnosed from the microgrid through an online clustering algorithm, and provided as input to a spectral multiplume eddy‐diffusivity mass flux scheme. This yields a decentralized transport system, in that the thermal clusters acting as independent but interacting nodes that carry information about spatial structure. The main objectives of this study are (a) to seek proof of concept of this approach, and (b) to gain insight into impacts of spatial organization on convective transport. Single‐column model experiments demonstrate satisfactory skill in reproducing two observed cases of continental shallow convection. Metrics expressing self‐organization and spatial organization match well with large‐eddy simulation results. We find that in this coupled system, spatial organization impacts convective transport primarily through the scale break in the size distribution of cluster number. The rooting of saturated plumes in the subcloud mixed layer plays a key role in this process.

54 ENVIRONMENTAL SCIENCES↗