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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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88 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The International Space Station Environment Triggers Molecular Responses in Aspergillus niger

Due to immense phenotypic plasticity and adaptability, Aspergillus niger is a cosmopolitan fungus that thrives in versatile environments, including the International Space Station (ISS). This is the first report of genomic, proteomic, and metabolomic alterations observed in A. niger strain JSC-093350089 grown in a controlled experiment aboard the ISS. Whole-genome sequencing (WGS) revealed that ISS conditions, including microgravity and enhanced irradiation, triggered non-synonymous point mutations in specific regions, chromosomes VIII and XII of the JSC-093350089 genome when compared to the ground-grown control. Proteome analysis showed altered abundance of proteins involved in carbohydrate metabolism, stress response, and cellular amino acid and protein catabolic processes following growth aboard the ISS. Metabolome analysis further confirmed that space conditions altered molecular suite of ISS-grown A. niger JSC-093350089. After regrowing both strains on Earth, production of antioxidant—Pyranonigrin A was significantly induced in the ISS-flown, but not the ground control strain. In summary, the microgravity and enhanced irradiation triggered unique molecular responses in the A. niger JSC-093350089 suggesting adaptive responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [ Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height ( Dw1 and Dw2 ) and the YELLOW SEED1 locus ( Y1 ) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.

bioenergy association panel↗
DOE OSTI2021

Whole-Genome SNP Analysis Identifies Putative Mycobacterium bovis Transmission Clusters in Livestock and Wildlife in Catalonia, Spain

The high-resolution WGS analyses of MTBC strains have provided useful insight for determining sources of infection for animal tuberculosis. In Spain, tuberculosis in livestock is caused by Mycobacterium bovis and Mycobacterium caprae, where wildlife reservoirs play an important role. We analyzed a set of 125 M. bovis isolates obtained from livestock and wildlife from Catalonia to investigate strain diversity and identify possible sources and/or causes of infection. Whole-genome SNP profiles were used for phylogenetic reconstruction and pairwise SNP distance analysis. Additionally, SNPs were investigated to identify virulence and antimicrobial resistance factors to investigate clade-specific associations. Putative transmission clusters (≤12 SNPs) were identified, and associated epidemiological metadata were used to determine possible explanatory factors for transmission. M. bovis distribution was heterogeneous, with 7 major clades and 21 putative transmission clusters. In order of importance, the explanatory factors associated were proximity and neighborhood, residual infection, livestock-wildlife interaction, shared pasture, and movement. Genes related to lipid transport and metabolism showed the highest number of SNPs. All isolates were pyrazinamide resistant, and five were additionally resistant to isoniazid, but no clade-specific associations could be determined. Our findings highlight the importance of high-resolution molecular surveillance to monitor bovine tuberculosis dynamics in a low-prevalence setting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Phylodynamics of SARS-CoV-2 Lineages B.1.1.7, B.1.1.529 and B.1.617.2 in Nigeria Suggests Divergent Evolutionary Trajectories

Background: The early months of the COVID-19 pandemic were characterized by high transmission rates and mortality, compounded by the emergence of multiple SARS-CoV-2 lineages, including Variants of Concern (VOCs). This study investigates the phylodynamic and spatio-temporal trends of VOCs during the peak of the pandemic in Nigeria. Methods: Whole-genome sequencing (WGS) data from three major VOCs circulating in Nigeria, B.1.1.7 (Alpha), B.1.617.2 (Delta), and B.1.1.529 (Omicron), were analyzed using tools such as Nextclade, R Studio v 4.2.3, and BEAST X v 10.5.0. The spatial distribution, evolutionary history, viral ancestral introductions, and geographic dispersal patterns were characterized. Results: Three major lineages following WHO nomenclature were identified: Alpha, Delta, and Omicron. The Delta variant exhibited the widest geographic spread, detected in 14 states, while the Alpha variant was the least distributed, identified in only eight states but present across most epidemiological weeks studied. Evolutionary rates varied slightly, with Alpha exhibiting the slowest rate (2.66 × 10 −4 substitutions/site/year). Viral population analyses showed distinct patterns: Omicron sustained elevated population growth over time, while Delta declined after initial expansion. The earliest Times to Most Recent Common Ancestor (TMRCA) were consistent with the earliest outbreaks of SARS-CoV-2 globally. Geographic transmission analysis indicated a predominant coastal-to-inland spread for all variants, with Omicron showing the most diffuse dispersal, highlighting commercial routes as significant drivers of viral diffusion. Conclusion: The SARS-CoV-2 epidemic in Nigeria was characterized by multiple variant introductions and a dominant coastal-to-inland spread, emphasizing that despite lockdown measures, commercial trade routes played a critical role in viral dissemination. These findings provide insights into pandemic control strategies and future outbreak preparedness.

Nigeria↗
DOE OSTI2026

LandScan Mosaic Time Series Version 1.0: 1975-2024

The LandScan Mosaic Annual Global Ambient Population Time Series, Version 1.0, provides annual high-resolution global ambient population estimates from 1975 to 2024. The dataset is distributed as one Cloud-Optimized GeoTIFF per year on a globally aligned 3 arc-second WGS 84 grid. The 2024 layer is the LandScan Mosaic benchmark reference year, while the 1975–2023 layers are historical estimates generated using the LandCast backcasting framework.

Zimmer, Andrew [ORNL] (ORCID:0000000176838713)↗
NASA NTRS2002

Comparing IKONOS and Landsat 7 Images

This work is a continuation of the simulations presented at the previous workshop.INformation is presented on the following: 20 IKONOS images compared with 10 Landsat 7 ETM+VNIR images acquired on the same days. Comparisons are based on simulations of the Landsat 7 images from the IKONOS data. IKONOS and Landsat 7 images used in simulations are on a similar processing level with radiometric correction, georeferenced with cubic-convolution resampling, and UTM projection with WGS-84 datum.

Blonski, Slawomir↗
NASA NTRS2004

Evaluation of Experimental Data from the GAINS Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in September 2001. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the 48-hour flight over the Northwest US, the instrument will measure surface reflections that can be detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and results of the science data analyses for the 48-hour mission.

Gance, George G.↗
NASA NTRS2002

Evaluation of Experimental Data from the Gains Balloon GPS Surface Reflection Instrument

The GPS Surface Reflection Instrument was integrated as an experiment on the GAINS (Global Airocean IN-situ System) 48-hour balloon mission flown in June 2002. The data collected by similar instruments in the past has been used to measure sea state from which ocean surface winds can be accurately estimated. The GPS signal has also been shown to be reflected from wetland areas and even from subsurface moisture. The current version of the instrument has been redesigned to be more compact, use less power, and withstand a greater variation in environmental conditions than previous versions. This instrument has also incorporated a new data collection mode to track 5 direct satellites (providing a continuous navigation solution) and multiplex the remaining 7 channels to track the reflected signal of the satellite tracked in channel 0. The new software mode has been shown to increase the signal to noise ratio of the collected data and enhance the science return of the instrument. During the GAINS balloon flight over the Northwest US, the instrument measured surface reflections as they were detected over the balloon's ground track. Since ground surface elevations in this area vary widely from the WGS-84 ellipsoid altitude, the instrument software has been modified to incorporate a surface altitude correction based on USGS 30-minute Digital Elevation Models. Information presented will include facts about instrument design goals, data collection methodologies and algorithms, and will focus on results of the science data analyses for the mission.

Ganoe, George G.↗
NASA NTRS2018

ICESat-2 Photon Classification: Finding Signal Photons in the ATL03 Geolocated Photon Data Product

ICESat-2 carries NASA's next-generation laser altimeter, ATLAS, (Advanced Topographic Laser Altimeter System), designed to measure changes in ice sheet height, sea ice freeboard, and vegetation canopy height. ATLAS contains a photon-counting lidar which transmits green (532-nm) pulses at 10kHz. Each pulse is split into 3 pairs of beams (one strong and one weak). Approximately 1014 photons per pulse travel from ATLAS through the atmosphere to reflect off the Earth's surface. Some return back into the ATLAS telescope where they are recorded. Photons from sunlight and instrument noise at the same wavelength are also recorded. The flight software time tags all photons within a 500m to 6 km range window and generates histograms. Using the histograms, it selects a telemetry window which varies from 20m over flat surfaces to hundreds of meters over rougher terrain. ATL03 contains the time, height (relative to the WGS-84 ellipsoid), latitude and longitude of every photon within the telemetry window. The basic challenge is to determine which of these photons were reflected off the surface. We have developed an algorithm that identifies these signal photons and assigns a confidence level (low, medium, or high) to each signal photon based on the signal to noise ratio. We present an overview of the signal identification algorithm and show the results on actual ICESat-2 data over ice sheet, sea ice, vegetated, and water surfaces. Higher level ATLAS products work with aggregations of the photons in order to determine the ellipsoidal height of the Earth, canopy height and structure, and other quantities of geophysical interest.

Remote Sensing↗
NASA NTRS2018

Detection of Antimicrobial Resistance Genes Associated With the International Space Station Environmental Surfaces

Antimicrobial resistance (AMR) is a global health issue. In an effort to minimize this threat to astronauts, who may be immunocompromised and thus at a greater risk of infection from antimicrobial resistant pathogens, a comprehensive study of the ISS “resistome’ was conducted. Using whole genome sequencing (WGS) and disc diffusion antibiotic resistance assays, 9 biosafety level 2 organisms isolated from the ISS were assessed for their antibiotic resistance. Molecular analysis of AMR genes from 24 surface samples collected from the ISS during 3 different sampling events over a span of a year were analyzed with Ion AmpliSeq™ and metagenomics. Disc diffusion assays showed that Enterobacter bugandensis strains were resistant to all 9 antibiotics tested and Staphylococcus haemolyticus being resistant to none. Ion AmpliSeq™ revealed that 123 AMR genes were found, with those responsible for beta-lactam and trimethoprim resistance being the most abundant and widespread. Using a variety of methods, the genes involved in antimicrobial resistance have been examined for the first time from the ISS. This information could lead to mitigation strategies to maintain astronaut health during long duration space missions when return to Earth for treatment is not possible.

Antimicrobial resistance↗
DOE OSTI2026

Summertime methane and carbon dioxide emission rates and associated variables from a national‐scale survey of 146 reservoirs in the United States

Reservoirs are globally important sources of greenhouse gases, but the magnitude of their emissions is highly uncertain. Here, we present data for 146 reservoirs from two surveys of reservoir methane and carbon dioxide emissions, one at the regional scale in the midwestern United States and one at the national scale in the United States, plus data from two hand‐picked sites in Washington and Puerto Rico. At all reservoirs, ebullitive and diffusive emissions and basic physicochemistry were measured at 15–55 locations during one 22 to 64‐h period during the summers of 2016–2023, with four reservoirs revisited a second time. Contemporaneous water chemistry measurements were made at one or two locations in each reservoir. The dataset consists of two geospatial files and seven CSV files containing greenhouse gas emissions, water chemistry, morphology, and other relevant data. To date, these data comprise the largest multi‐reservoir emissions dataset assembled using consistent measurement methods.

Beaulieu, Jake J. [US Environmental Protection Age↗
DOE OSTI2020

Whole-Genome Sequencing and Bioinformatic Analysis of Environmental, Agricultural, and Human Campylobacter jejuni Isolates From East Tennessee

As a leading cause of bacterial-derived gastroenteritis worldwide, Campylobacter jejuni has a significant impact on human health in both the developed and developing worlds. Despite its prevalence as a human pathogen, the source of these infections remains poorly understood due to the mutation frequency of the organism and past limitations of whole genome analysis. Recent advances in both whole genome sequencing and computational methods have allowed for the high-resolution analysis of intraspecies diversity, leading multiple groups to postulate that these approaches may be used to identify the sources of Campylobacter jejuni infection. To address this hypothesis, our group conducted a regionally and temporally restricted sampling of agricultural and environmental Campylobacter sources and compared isolated C. jejuni genomes to those that caused human infections in the same region during the same time period. Through a network analysis comparing genomes from various sources, we found that human C. jejuni isolates clustered with those isolated from cattle and chickens, indicating these as potential sources of human infection in the region.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Benchmark datasets for SARS-CoV-2 surveillance bioinformatics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has spread globally and is being surveilled with an international genome sequencing effort. Surveillance consists of sample acquisition, library preparation, and whole genome sequencing. This has necessitated a classification scheme detailing Variants of Concern (VOC) and Variants of Interest (VOI), and the rapid expansion of bioinformatics tools for sequence analysis. These bioinformatic tools are means for major actionable results: maintaining quality assurance and checks, defining population structure, performing genomic epidemiology, and inferring lineage to allow reliable and actionable identification and classification. Additionally, the pandemic has required public health laboratories to reach high throughput proficiency in sequencing library preparation and downstream data analysis rapidly. However, both processes can be limited by a lack of a standardized sequence dataset. We identified six SARS-CoV-2 sequence datasets from recent publications, public databases and internal resources. In addition, we created a method to mine public databases to identify representative genomes for these datasets. Using this novel method, we identified several genomes as either VOI/VOC representatives or non-VOI/VOC representatives. To describe each dataset, we utilized a previously published datasets format, which describes accession information and whole dataset information. Additionally, a script from the same publication has been enhanced to download and verify all data from this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Population genomics identify the requirement of BAP2 in the sufficiency of IRE1 in the UPR

Sequencing reads archived here are part of a project studying natural variation in ER stress responses in Arabidopsis reported in Pastor-Cantizano et al. 2024. The project focused on contrasting alleles derived from Na-1 (tolerant) and Est-0 (susceptible) accessions when exposed to a ER stress inducer. These accession were crossed, F3 progeny were phenotyped, and the top and bottom 10% of relative performance under ER stress (42 individuals from each tail) were pooled and sequenced. Candidate genomic regions were identified by looking for allele frequency differences among the two pools in a standard QTL-seq approach

programmed cell death↗