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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Evolutionary genomics suggests that CheV is an additional adaptor for accommodating specific chemoreceptors within the chemotaxis signaling complex

Escherichia coli and Salmonella enterica are models for many experiments in molecular biology including chemotaxis, and most of the results obtained with one organism have been generalized to another. While most components of the chemotaxis pathway are strongly conserved between the two species, Salmonella genomes contain some chemoreceptors and an additional protein, CheV, that are not found in E. coli. The role of CheV was examined in distantly related species Bacillus subtilis and Helicobacter pylori , but its role in bacterial chemotaxis is still not well understood. We tested a hypothesis that in enterobacteria CheV functions as an additional adaptor linking the CheA kinase to certain types of chemoreceptors that cannot be effectively accommodated by the universal adaptor CheW. Phylogenetic profiling, genomic context and comparative protein sequence analyses suggested that CheV interacts with specific domains of CheA and chemoreceptors from an orthologous group exemplified by the Salmonella McpC protein. Structural consideration of the conservation patterns suggests that CheV and CheW share the same binding spot on the chemoreceptor structure, but have some affinity bias towards chemoreceptors from different orthologous groups. Finally, published experimental results and data newly obtained via comparative genomics support the idea that CheV functions as a "phosphate sink" possibly to off-set the over-stimulation of the kinase by certain types of chemoreceptors. Altogether, our results strongly suggest that CheV is an additional adaptor for accommodating specific chemoreceptors within the chemotaxis signaling complex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Structural and Histone Binding Ability Characterizations of Human PWWP Domains

The PWWP domain was first identified as a structural motif of 100-130 amino acids in the WHSC1 protein and predicted to be a protein-protein interaction domain. It belongs to the Tudor domain 'Royal Family', which consists of Tudor, chromodomain, MBT and PWWP domains. While Tudor, chromodomain and MBT domains have long been known to bind methylated histones, PWWP was shown to exhibit histone binding ability only until recently. The PWWP domain has been shown to be a DNA binding domain, but sequence analysis and previous structural studies show that the PWWP domain exhibits significant similarity to other 'Royal Family' members, implying that the PWWP domain has the potential to bind histones. In order to further explore the function of the PWWP domain, we used the protein family approach to determine the crystal structures of the PWWP domains from seven different human proteins. Our fluorescence polarization binding studies show that PWWP domains have weak histone binding ability, which is also confirmed by our NMR titration experiments. Furthermore, we determined the crystal structures of the BRPF1 PWWP domain in complex with H3K36me3, and HDGF2 PWWP domain in complex with H3K79me3 and H4K20me3. PWWP proteins constitute a new family of methyl lysine histone binders. The PWWP domain consists of three motifs: a canonical {beta}-barrel core, an insertion motif between the second and third {beta}-strands and a C-terminal {alpha}-helix bundle. Both the canonical {beta}-barrel core and the insertion motif are directly involved in histone binding. The PWWP domain has been previously shown to be a DNA binding domain. Therefore, the PWWP domain exhibits dual functions: binding both DNA and methyllysine histones.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The functional potential of microbial communities in hydraulic fracturing source water and produced water from natural gas extraction characterized by metagenomic sequencing

Microbial activity in produced water from hydraulic fracturing operations can lead to undesired environmental impacts and increase gas production costs. However, the metabolic profile of these microbial communities is not well understood. Here, for the first time, we present results from a shotgun metagenome of microbial communities in both hydraulic fracturing source water and wastewater produced by hydraulic fracturing. Taxonomic analyses showed an increase in anaerobic/facultative anaerobic classes related to Clostridia , Gammaproteobacteria , Bacteroidia and Epsilonproteobacteria in produced water as compared to predominantly aerobic Alphaproteobacteria in the fracturing source water. Thus, the metabolic profile revealed a relative increase in genes responsible for carbohydrate metabolism, respiration, sporulation and dormancy, iron acquisition and metabolism, stress response and sulfur metabolism in the produced water samples. These results suggest that microbial communities in produced water have an increased genetic ability to handle stress, which has significant implications for produced water management, such as disinfection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Spatial distribution of an uranium-respiring betaproteobacterium at the Rifle, CO field research site

The Department of Energy’s Integrated Field-Scale Subsurface Research Challenge Site (IFRC) at Rifle, Colorado was created to address the gaps in knowledge on the mechanisms and rates of U(VI) bioreduction in alluvial sediments. Previous studies at the Rifle IFRC have linked microbial processes to uranium immobilization during acetate amendment. Several key bacteria believed to be involved in radionuclide containment have been described; however, most of the evidence implicating uranium reduction with specific microbiota has been indirect. Here, we report on the cultivation of a microorganism from the Rifle IFRC that reduces uranium and appears to utilize it as a terminal electron acceptor for respiration with acetate as electron donor. Furthermore, this bacterium constitutes a significant proportion of the subsurface sediment community prior to biostimulation based on TRFLP profiling of 16S rRNA genes. 16S rRNA gene sequence analysis indicates that the microorganism is a betaproteobacterium with a high similarity to Burkholderia fungorum . This is, to our knowledge, the first report of a betaproteobacterium capable of uranium respiration. Our results indicate that this microorganism occurs commonly in alluvial sediments located between 3-6 m below ground surface at Rifle and may play a role in the initial reduction of uranium at the site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Evaluating models of cellulose degradation by Fibrobacter succinogenes S85

Fibrobacter succinogenes S85 is an anaerobic non-cellulosome utilizing cellulolytic bacterium originally isolated from the cow rumen microbial community. Efforts to elucidate its cellulolytic machinery have resulted in the proposal of numerous models which involve a combination of cell-surface attachment via a combination of cellulose-binding fibro-slime proteins and pili, the production of cellulolytic vesicles, and the entry of cellulose fibers into the periplasmic space. Here, we used a combination of RNA-sequencing, proteomics, and transmission electron microscopy (TEM) to further elucidate the cellulolytic mechanism of F. succinogenes . Our RNA-sequence analysis shows that genes encoding Type II and III secretion systems, fibro-slime proteins, and pili are differentially expressed on cellulose, relative to glucose. A subcellular fractionation of cells grown on cellulose revealed that carbohydrate active enzymes associated with cellulose deconstruction and fibro-slime proteins were greater in the extracellular media, as compared to the periplasm and outer membrane fractions. TEMs of samples harvested at mid-exponential and stationary phases of growth on cellulose and glucose showed the presence of grooves in the cellulose between the bacterial cells and substrate, suggesting enzymes work extracellularly for cellulose degradation. Membrane vesicles were only observed in stationary phase cultures grown on cellulose. Furthermore, these results provide evidence that F. succinogenes attaches to cellulose fibers using fibro-slime and pili, produces cellulases, such as endoglucanases, that are secreted extracellularly using type II and III secretion systems, and degrades the cellulose into cellodextrins that are then imported back into the periplasm for further digestion by β-glucanases and other cellulases.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Impact of Organic Carbon Electron Donors on Microbial Community Development under Iron- and Sulfate-Reducing Conditions

Although iron- and sulfate-reducing bacteria in subsurface environments have crucial roles in biogeochemical cycling of C, Fe, and S, how specific electron donors impact the compositional structure and activity of native iron- and/or sulfate-reducing communities is largely unknown. To understand this better, we created bicarbonate-buffered batch systems in duplicate with three different electron donors (acetate, lactate, or glucose) paired with ferrihydrite and sulfate as the electron acceptors and inoculated them with subsurface sediment as the microbial inoculum. Sulfate and ferrihydrite reduction occurred simultaneously and were faster with lactate than with acetate. 16S rRNA-based sequence analysis of the communities over time revealed that Desulfotomaculum was the major driver for sulfate reduction coupled with propionate oxidation in lactate-amended incubations. The reduction of sulfate resulted in sulfide production and subsequent abiotic reduction of ferrihydrite. In contrast, glucose promoted faster reduction of ferrihydrite, but without reduction of sulfate. Interestingly, the glucose-amended incubations led to two different biogeochemical trajectories among replicate bottles that resulted in distinct coloration (white and brown). The two outcomes in geochemical evolution might be due to the stochastic evolution of the microbial communities or subtle differences in the initial composition of the fermenting microbial community and its development via the use of different glucose fermentation pathways available within the community. Synchrotron-based x-ray analysis indicated that siderite and amorphous Fe(II) were formed in the replicate bottles with glucose, while ferrous sulfide and vivianite were formed with lactate or acetate. As a result, these data sets reveal that use of different C utilization pathways projects significant changes in microbial community composition over time that uniquely impact both the geochemistry and mineralogy of subsurface environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Variations of five eIF4E genes across cassava accessions exhibiting tolerant and susceptible responses to cassava brown streak disease

Cassava (Manihot esculenta) is an important tropical subsistence crop that is severely affected by cassava brown streak disease (CBSD) in East Africa. The disease is caused by Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV). Both have a (+)-sense single-stranded RNA genome with a 5’ covalently-linked viral protein, which functionally resembles the cap structure of mRNA, binds to eukaryotic translation initiation factor 4E (eIF4E) or its analogues, and then enable the translation of viral genomic RNA in host cells. To characterize cassava eIF4Es and their potential role in CBSD tolerance and susceptibility, we cloned five eIF4E transcripts from cassava (accession TMS60444). Sequence analysis indicated that the cassava eIF4E family of proteins consisted of one eIF4E, two eIF(iso)4E, and two divergent copies of novel cap-binding proteins (nCBPs). Our data demonstrated experimentally the coding of these five genes as annotated in the published cassava genome and provided additional evidence for refined annotations. Illumina resequencing data of the five eIF4E genes were analyzed from 14 cassava lines tolerant or susceptible to CBSD. Abundant single nucleotide polymorphisms (SNP) and biallelic variations were observed in the eIF4E genes; however, most of the SNPs were located in the introns and non-coding regions of the exons. Association studies of non-synonymous SNPs revealed no significant association between any SNP of the five eIF4E genes and the tolerance or susceptibility to CBSD. However, two SNPs in two genes were weakly associated with the CBSD responses but had no direct causal-effect relationship. SNPs in an intergenic region upstream of eIF4E_me showed a surprising strong association with CBSD responses. Digital expression profile analysis showed differential expression of different eIF4E genes but no significant difference in gene expression was found between susceptible and tolerant cassava accessions despite the association of the intergenic SNPs with CBSD responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Draft genome sequence of Actinotignum schaalii DSM 15541 T : Genetic insights into the lifestyle, cell fitness and virulence

The permanent draft genome sequence of Actinotignum schaalii DSM 15541 T is presented. The annotated genome includes 2,130,987 bp, with 1777 protein-coding and 58 rRNA-coding genes. Genome sequence analysis revealed absence of genes encoding for: components of the PTS systems, enzymes of the TCA cycle, glyoxylate shunt and gluconeogensis. Genomic data revealed that A. schaalii is able to oxidize carbohydrates via glycolysis, the nonoxidative pentose phosphate and the Entner-Doudoroff pathways. Besides, the genome harbors genes encoding for enzymes involved in the conversion of pyruvate to lactate, acetate and ethanol, which are found to be the end products of carbohydrate fermentation. The genome contained the gene encoding Type I fatty acid synthase required for de novo FAS biosynthesis. The plsY and plsX genes encoding the acyltransferases necessary for phosphatidic acid biosynthesis were absent from the genome. The genome harbors genes encoding enzymes responsible for isoprene biosynthesis via the mevalonate (MVA) pathway. Genes encoding enzymes that confer resistance to reactive oxygen species (ROS) were identified. In addition, A. schaalii harbors genes that protect the genome against viral infections. These include restriction-modification (RM) systems, type II toxin-antitoxin (TA), CRISPR-Cas and abortive infection system. A. schaalii genome also encodes several virulence factors that contribute to adhesion and internalization of this pathogen such as the tad genes encoding proteins required for pili assembly, the nanI gene encoding exo-alpha-sialidase, genes encoding heat shock proteins and genes encoding type VII secretion system. These features are consistent with anaerobic and pathogenic lifestyles. Finally, resistance to ciprofloxacin occurs by mutation in chromosomal genes that encode the subunits of DNA-gyrase (GyrA) and topisomerase IV (ParC) enzymes, while resistant to metronidazole was due to the frxA gene, which encodes NADPH-flavin oxidoreductase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Antimicrobial resistance and genomic characterization of Salmonella Dublin isolates in cattle from the United States

Salmonella enterica subspecies enterica serotype Dublin is a host-adapted serotype in cattle, associated with enteritis and systemic disease. The primary clinical manifestation of Salmonella Dublin infection in cattle, especially calves, is respiratory disease. While rare in humans, it can cause severe illness, including bacteremia, with hospitalization and death. In the United States, S . Dublin has become one of the most multidrug-resistant serotypes. The objective of this study was to characterize S . Dublin isolates from sick cattle by analyzing phenotypic and genotypic antimicrobial resistance (AMR) profiles, the presence of plasmids, and phylogenetic relationships. S . Dublin isolates (n = 140) were selected from submissions to the NVSL for Salmonella serotyping (2014–2017) from 21 states. Isolates were tested for susceptibility against 14 class-representative antimicrobial drugs. Resistance profiles were determined using the ABRicate with Resfinder and NCBI databases, AMRFinder and PointFinder. Plasmids were detected using ABRicate with PlasmidFinder. Phylogeny was determined using vSNP. We found 98% of the isolates were resistant to more than 4 antimicrobials. Only 1 isolate was pan-susceptible and had no predicted AMR genes. All S . Dublin isolates were susceptible to azithromycin and meropenem. They showed 96% resistance to sulfonamides, 97% to tetracyclines, 95% to aminoglycosides and 85% to beta-lactams. The most common AMR genes were: sulf2 and tetA (98.6%), aph(6)-Id (97.9%), aph(3’’)-Ib, (97.1%), floR (94.3%), and blaCMY-2 (85.7%). All quinolone resistant isolates presented mutations in gyr A. Ten plasmid types were identified among all isolates with IncA/C2, IncX1, and IncFII(S) being the most frequent. The S . Dublin isolates show low genomic genetic diversity. This study provided antimicrobial susceptibility and genomic insight into S . Dublin clinical isolates from cattle in the U.S. Further sequence analysis integrating food and human origin S . Dublin isolates may provide valuable insight on increased virulence observed in humans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Evaluation of co-circulating pathogens and microbiome from COVID-19 infections

Co-infections or secondary infections with SARS-CoV-2 have the potential to affect disease severity and morbidity. Additionally, the potential influence of the nasal microbiome on COVID-19 illness is not well understood. In this study, we analyzed 203 residual samples, originally submitted for SARS-CoV-2 testing, for the presence of viral, bacterial, and fungal pathogens and non-pathogens using a comprehensive microarray technology, the Lawrence Livermore Microbial Detection Array (LLMDA). Eighty-seven percent of the samples were nasopharyngeal samples, and 23% of the samples were oral, nasal and oral pharyngeal swabs. We conducted bioinformatics analyses to examine differences in microbial populations of these samples, as a proxy for the nasal and oral microbiome, from SARS-CoV-2 positive and negative specimens. We found 91% concordance with the LLMDA relative to a diagnostic RT-qPCR assay for detection of SARS-CoV-2. Sixteen percent of all the samples (32/203) revealed the presence of an opportunistic bacterial or frank viral pathogen with the potential to cause co-infections. The two most detected bacteria, Streptococcus pyogenes and Streptococcus pneumoniae , were present in both SARS-CoV-2 positive and negative samples. Human metapneumovirus was the most prevalent viral pathogen in the SARS-CoV-2 negative samples. Sequence analysis of 16S rRNA was also conducted to evaluate bacterial diversity and confirm LLMDA results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MAVS mediates a protective immune response in the brain to Rift Valley fever virus

Rift Valley fever virus (RVFV) is a highly pathogenic mosquito-borne virus capable of causing hepatitis, encephalitis, blindness, hemorrhagic syndrome, and death in humans and livestock. Upon aerosol infection with RVFV, the brain is a major site of viral replication and tissue damage, yet pathogenesis in this organ has been understudied. Here, we investigated the immune response in the brain of RVFV infected mice. In response to infection, microglia initiated robust transcriptional upregulation of antiviral immune genes, as well as increased levels of activation markers and cytokine secretion that is dependent on mitochondrial antiviral-signaling protein (MAVS) and independent of toll-like receptors 3 and 7. In vivo , Mavs -/- mice displayed enhanced susceptibility to RVFV as determined by increased brain viral burden and higher mortality. Single-cell RNA sequence analysis identified defects in type I interferon and interferon responsive gene expression within microglia in Mavs -/- mice, as well as dysregulated lymphocyte infiltration. The results of this study provide a crucial step towards understanding the precise molecular mechanisms by which RVFV infection is controlled in the brain and will help inform the development of vaccines and antiviral therapies that are effective in preventing encephalitis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Depth-resolved sagebrush root metabolomics, rhizosphere microbial communities, and geochemistry at the East River Watershed

This data set consists of results from soil nutrient profile, untargeted metabolomics, mass spec imaging, and amplicon sequencing. Data for soil nutrient profile includes common cations (Ca, Mg, Na, and K etc.) extracted from 3 digesting steps – ammonia acetate (for exchangeable cations), nitric acid (for acid dissolved fraction), and hydrofluoric acid/perchloric acid (HF/HClO4) for whole soil digestion. It also includes concentration of organic carbon, inorganic nitrogen (ammonia and nitrate) and phosphorus (Bray-1 P and nitric acid extract), and total nitrogen and phosphorus. Data for untargeted metabolomics includes metabolomic profile for root exudate/tissues and soil extracts from depths at surface soil to saprolite, that were measured using gas chromatography – mass spectrometry (GC-MS), and liquid chromatography – tandem mass spectrometry (LC-MS/MS). Data for mass spec imaging includes spatial distribution of metabolites that were detected and annotated with Fourier transformation ion cyclotron resonance mass spectrometer (FTICR-MS). Data for amplicon sequencing includes the base paired 16S and ITS ribosomal RNA sequences from Miseq Illumina sequencing. All samples were collected from 2 sampling campaign October 2022 and June 2023. Collectively, these datasets enable a mechanistic evaluation of how nutrient acquisition, especially nitrogen and phosphorus, differs between shallow roots operating in soil and deep roots functioning within the fractured bedrock zone. All files are provided as comma-separated values (CSV) fies (.csv) and (GZIP) file (.gz). The compressed .gz FASTQ files can be read directly in R using the dada2 package as part of the amplicon sequence analysis workflow. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. This research was performed on a project award 60563 (https://dx.doi.org/10.46936/expl.proj.2022.60563/60008727) from the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830.

EARTH SCIENCE > AGRICULTURE > SOILS > CARBON↗
DOE OSTI2016

Global Gene Expression Differences in Joints of Mice with Divergent Post Traumatic Osteoarthritis Phenotypes

Osteoarthritis (OA) is a debilitating joint disease characterized by cartilage degradation which prompts pain, stiffness and swelling. Contributing factors include age, genetics, obesity, injury and overuse of joints. OA is defined by an acute phase and a chronic phase whereby inflammation and degeneration of articular cartilage and other tissues is followed by joint pain and limited mobility. Patients remain asymptomatic until substantial joint damage has occurred and therefore rely on long term surgical joint replacement and pain management as their sole treatment options. For this reason, there is an increasing need to identify early stage osteoarthritis biomarkers. Our study aimed to identify and characterize gene expression variances in 3 different mouse strains (STR/ort, C57BL/6 and MRL/MpJ) with different susceptibility to post traumatic osteoarthritis (PTOA). Through RNA sequence analysis of whole knee joint RNA, we identified differentially expressed genes associated with the initial stages of PTOA in relation to mice with divergent phenotypes. These results will help elucidate potential mechanisms responsible for PTOA outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Proposal to support the 4th international conference on nitrification and related processes (ICoN4)

The 4th International Conference on Nitrification and Related Processes (ICoN4) commencing between June 27 and July 1, 2015, at the University of Alberta in Edmonton, Alberta, Canada brings together an international collection of academic, government, and private sector researchers of the global biogeochemical nitrogen cycle to share their scientific discoveries, innovations and pertinent societal impacts. The classical understanding of “nitrification” describes the two-step transformation of ammonium to nitrite and nitrite to nitrate; however, we now know from the analysis genome sequences, the application of ‘omics technologies, microbial ecology, biogeochemistry, and microbial physiology that the transformation of ammonium is not performed by a few particular groups of microorganisms nor is it confined to oxic environments. Past ICoN meetings have explored the interconnections between ammonium- and nitrite-consuming processes in all ecosystems, the emission of greenhouse gases by these processes and their control, and the intersection between intermediates of the nitrification process and other elemental cycles; this has generated tremendous progress in our understanding of the global nitrogen cycle and it has generated excitement in the next generation of N cycle researchers. Nitrification research has a long-standing connection to the Community Science Program of the DOE. Between 1999 and 2001, the JGI generated the first genome sequence of an ammonia-oxidizing bacterium, Nitrosomonas europaea ATCC 19718, and it has subsequently sequenced, or is in the process of sequencing over 50 additional genomes from ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and ammonia-oxidizing archaea. Autotrophic ammonia- and nitrite-transforming microorganisms play also a critical role in carbon cycling and sequestration in nearly all ecosystems. Not only do they control the concentration and speciation of biologically available N to plants and other microorganisms, nitrification is also the source of the various forms of nitrogen pollution. Nitrate pollution from over-fertilization of managed soils causes eutrophication and the reduction of nitrate and nitrate also results in emission of N2O, a denitrification process that leads to the accumulation of this major greenhouse gas in the atmosphere. Anaerobic ammonia oxidation (anammox) and nitrite-driven anaerobic methane oxidation (n-DAMO) are involved in the transformation of ammonium, nitrite, and nitrate to dinitrogen without N2O as an intermediate, acting as mitigating processes to nitrification. Along with the vast international participation in the ICoN conferences, encouragement and inclusion of early career investigators and graduate students is viewed as critical to the continued success of our discipline.

42 ENGINEERING↗
DOE OSTI2017

Temporal Cyber Attack Detection.

Rigorous characterization of the performance and generalization ability of cyber defense systems is extremely difficult, making it hard to gauge uncertainty, and thus, confidence. This difficulty largely stems from a lack of labeled attack data that fully explores the potential adversarial space. Currently, performance of cyber defense systems is typically evaluated in a qualitative manner by manually inspecting the results of the system on live data and adjusting as needed. Additionally, machine learning has shown promise in deriving models that automatically learn indicators of compromise that are more robust than analyst-derived detectors. However, to generate these models, most algorithms require large amounts of labeled data (i.e., examples of attacks). Algorithms that do not require annotated data to derive models are similarly at a disadvantage, because labeled data is still necessary when evaluating performance. In this work, we explore the use of temporal generative models to learn cyber attack graph representations and automatically generate data for experimentation and evaluation. Training and evaluating cyber systems and machine learning models requires significant, annotated data, which is typically collected and labeled by hand for one-off experiments. Automatically generating such data helps derive/evaluate detection models and ensures reproducibility of results. Experimentally, we demonstrate the efficacy of generative sequence analysis techniques on learning the structure of attack graphs, based on a realistic example. These derived models can then be used to generate more data. Additionally, we provide a roadmap for future research efforts in this area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Investigating the role of innate immunity in viral encephalitis caused by Rift Valley fever virus

Rift Valley Fever Virus (RVFV) is a category A biodefense pathogen due to its potential for intentional spread by aerosols and the lack of a licensed vaccine or antiviral therapeutic. Although the brain is a major target of viral replication and tissue damage following aerosol infection, little is known about innate immune responses to RVFV in the brain. We are investigating the responses of resident innate immune cells of the brain (microglia and astrocytes) during RVFV infection, in order to identify how these cells are capable of controlling RVFV replication. Microglia mount a robust response to RVFV that is dependent upon mitochondrial antiviral-signaling protein (MAVS) and independent of toll-like receptors 3 and 7. Mice genetically modified to have nonfunctional MAVS (MAVS "knock out" or KO mice) have significantly higher viral loads in the brain following intranasal infection, but surprisingly, many markers of immune activity were similarly upregulated in the brains of MAVS KO and wild type (WT, or “normal”) mice. This is in contrast to the in vitro response, where microglia and astrocytes derived from MAVS KO mice were unresponsive to RVFV infection. RNA-sequencing analysis of infected brain tissue revealed that key antiviral genes are not activated in the MAVS KO animals. These results are an important step towards understanding the molecular pathways responsible for controlling RVFV infection in the brain and lay the groundwork for the development of targeted therapies for the prevention of RVFV encephalitis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

NEAMS Workbench MOOSE Integration Update

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench is a graphical user interface (GUI) that provides a common analysis environment for the accelerated use of the NEAMS toolkit. To improve design and analysis of current and future nuclear energy systems, the NEAMS Workbench provides an integrated development environment for model creation, review, execution, output review, and visualization for integrated tools. In addition to a GUI, the NEAMS Workbench provides the Workbench Analysis Sequence Processor, an open-source tool set that facilitates input-content assistance for supported domain-specific input languages and user-friendly syntaxes. These supported syntaxes enable accelerated development and deployment of enhanced user inputs and workflows. The Multiphysics Object-Oriented Simulation Environment (MOOSE) has been supported in the NEAMS Workbench since 2016 and receives continuous updates. Efforts to improve MOOSE-based tool integration in the NEAMS Workbench are ongoing. This document details the current and planned enhancements of the NEAMS Workbench and the MOOSE framework to improve integration and usability of MOOSE-based applications within the NEAMS Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Linking Spatiotemporal Biological Data to Predict Harmful Algal Blooms

Cyanobacterial Harmful Algal Blooms (cHABs) have significant impacts on an affected region’s economy, ecology, and human health. The blooms can release toxins that kill fish and poison water for people and animals. The global adverse effects of cHABs are exacerbated by the consequences of climate change and increased pollution. Though the phenomena are well documented, scientists’ efforts to mitigate the damage are hampered by insufficient predictive models and incomplete granular knowledge of cHAB community structure. With a goal of leveraging bioinformatics and machine learning tools to better understand and predict cHABs, we are first exploring water sample data sets. Using nearly four thousand samples from the National Center for Biotechnology Information Sequence Read Archive (NCBI-SRA) across 16 years with latitude and longitude embedded in the metadata, we mapped the location of the samples onto a Lake Erie shape file. We combined information about location, date, and community taxa in the NCBI samples to discover factors that determine cHAB features. The data are separated into three distinct zones, with the majority pooled at the southwest end of the lake and occurring in 2017. The samples are rich in biological data; our next steps are to carry out whole genome sequence analysis and use the community profiles as part of our predictive machine learning model.

59 BASIC BIOLOGICAL SCIENCES↗