Search NASA⌕ Search

SEARCH · Search NASA

Results for “genome analysis”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

Kinetic Induction of Oat Shoot Pulvinus Invertase mRNA by Gravistimulation and Partial cDNA Cloning by the Polymerase Chain Reaction

An asymmetric (top vs. bottom halves of pulvini) induction of invertase mRNA by gravistimulation was analyzed in oat shoot pulvini. Total RNA and poly(A)(+) RNA, isolated from oat pulvini, and two oli-gonucleotide primers, corresponding to two conserved amino acid sequences (NDPNG and WECPD) found in invertase from other species, were used for the polymerase chain reaction (PCR). A partial length cDNA (550 bp) was obtained and characterized. A 62% nucleotide sequence homology and 58% deduced amino acid sequence homology, as compared to beta-fructosidase of carrot cell wall, was found. Northern blot analysis showed that there was an obviously transient induction of invertase mRNA by gravistimulation in the oat pulvinus system. The mRNA was rapidly induced to a maximum level at 1 hour after gravistimulation treatment and gradually decreased afterwards. The mRNA level in the bottom half of the oat pulvinus was significantly higher than that in the top half of the pulvinus tissue. The kinetic induction of invertase mRNA was consistent with the transient accumulation of invertase activity during the graviresponse of the pulvinus. This indicates that the expression of the invertase gene(s) could be regulated by gravistimulation at the transcriptional level. Southern blot analysis showed that there were two to three genomic DNA fragments which hybridized with the partial-length invertase cDNA.

Wu, Liu-Lai↗

Variational Asymptotic Homogenization of Finitely Deformed Viscoelastic-Viscoplastic Composites

The objective of this paper is to develop a constitutive model for finitely deformed viscoelastic-viscoplastic materials and a micromechanics approach to homogenizing composites consisting of such materials. The development of the constitutive model involves establishing a thermodynamic framework based on finite strain theory, developing a viscoelasticity and a viscoplasticity model based on the thermodynamic framework, developing a radial return algorithm based on a classic framework, and deriving a closed-from incremental constitutive relation in the spatial configuration. The development of the micromechanics approach involves pulling-back the above constitutive relation to the material configuration, formulating a variational statement with the resulting constitutive relation, discretizing variational statement in a finite-dimensional space, and solving the discretized variational statement using an Euler–Newton predictor–corrector method. The constitutive model is calibrated via monotonic uniaxial compression tests on a polymer, and the calibrated model is validated by comparing its predictions with the cyclic test data. It is shown capable of characterizing viscoelasticity, viscoplasticity, and complex loading paths. The micromechanics approach’s capabilities are demonstrated through homogenizing a unidirectional fiber-reinforced composite, subjected to uniaxial, biaxial, and shear loading, at different strain rates. It is demonstrated to be capable of handling rate dependence and complex loading paths. The present framework can be further improved by implementing more sophisticated viscoelasticity and viscoplasticity models in future work.

Finite element analysis↗

Genomic and Phenotypic Characterization of Yeast Biosensor for Deep-space Radiation

The BioSentinel mission was selected to launch as a secondary payload onboard NASA Exploration Mission 1 (EM-1) in 2018. In BioSentinel, the budding yeast Saccharomyces cerevisiae will be used as a biosensor to measure the long-term impact of deep-space radiation to living organisms. In the 4U-payload, desiccated yeast cells from different strains will be stored inside microfluidic cards equipped with 3-color LED optical detection system to monitor cell growth and metabolic activity. At different times throughout the 12-month mission, these cards will be filled with liquid yeast growth media to rehydrate and grow the desiccated cells. The growth and metabolic rates of wild-type and radiation-sensitive strains in deep-space radiation environment will be compared to the rates measured in the ground- and microgravity-control units. These rates will also be correlated with measurements obtained from onboard physical dosimeters. In our preliminary long-term desiccation study, we found that air-drying yeast cells in 10% trehalose is the best method of cell preservation in order to survive the entire 18-month mission duration (6-month pre-launch plus 12-month full-mission periods). However, our study also revealed that desiccated yeast cells have decreasing viability over time when stored in payload-like environment. This suggests that the yeast biosensor will have different population of cells at different time points during the long-term mission. In this study, we are characterizing genomic and phenotypic changes in our yeast biosensor due to long-term storage and desiccation. For each yeast strain that will be part of the biosensor, several clones were reisolated after long-term storage by desiccation. These clones were compared to their respective original isolate in terms of genomic composition, desiccation tolerance and radiation sensitivity. Interestingly, clones from a radiation-sensitive mutant have better desiccation tolerance compared to their original isolate without losing radiation sensitivity. We employed Next-Generation Sequencing technology to better understand this phenotypic variation. Current effort is focusing on the analysis of high-throughput sequencing data to look for genomic changes in these reisolated clones compared to their original isolate.

yeast↗

Metagenome-assembled genomes provide insight into the metabolic potential during early production of Hydraulic Fracturing Test Site 2 in the Delaware Basin

Demand for natural gas continues to climb in the United States, having reached a record monthly high of 104.9 billion cubic feet per day (Bcf/d) in November 2023. Hydraulic fracturing, a technique used to extract natural gas and oil from deep underground reservoirs, involves injecting large volumes of fluid, proppant, and chemical additives into shale units. This is followed by a “shut-in” period, during which the fracture fluid remains pressurized in the well for several weeks. The microbial processes that occur within the reservoir during this shut-in period are not well understood; yet, these reactions may significantly impact the structural integrity and overall recovery of oil and gas from the well. To shed light on this critical phase, we conducted an analysis of both pre-shut-in material alongside production fluid collected throughout the initial production phase at the Hydraulic Fracturing Test Site 2 (HFTS 2) located in the prolific Wolfcamp formation within the Permian Delaware Basin of west Texas, USA. Specifically, we aimed to assess the microbial ecology and functional potential of the microbial community during this crucial time frame. Prior analysis of 16S rRNA sequencing data through the first 35 days of production revealed a strong selection for a Clostridia species corresponding to a significant decrease in microbial diversity. Here, we performed a metagenomic analysis of produced water sampled on Day 33 of production. This analysis yielded three high-quality metagenome-assembled genomes (MAGs), one of which was a Clostridia draft genome closely related to the recently classified Petromonas tenebris. This draft genome likely represents the dominant Clostridia species observed in our 16S rRNA profile. Annotation of the MAGs revealed the presence of genes involved in critical metabolic processes, including thiosulfate reduction, mixed acid fermentation, and biofilm formation. These findings suggest that this microbial community has the potential to contribute to well souring, biocorrosion, and biofouling within the reservoir. Our research provides unique insights into the early stages of production in one of the most prolific unconventional plays in the United States, with important implications for well management and energy recovery.

natural gas↗

Exabiome: Advancing Microbial Science through Exascale Computing

The Exabiome project seeks to improve the understanding of microbiomes through the development of methods for accelerating metagenomic science using exascale computing. This article gives an overview of scientific impact of the three components of the project: metagenome assembly, protein family detection, and comparative analysis of metagenomes. Exabiome developed MetaHipMer, the only metagenome assembler capable of scaling to full exascale systems. MetaHipMer has enabled ground-breaking assemblies on the Frontier supercomputer, with many scientific benefits, such as the discovery of rare species and viral genomes. To investigate protein families, Exabiome developed two exascale tools, PASTIS and HipMCL. Together, these can utilize exascale resources to understand the functional diversity of billions of dark matter proteins and novel protein families. For comparative analysis, Exabiome developed kmerprof, a tool that can be used to compare huge metagenomes for many different scientific purposes, for example, grouping human microbiomes according to body location.

59 BASIC BIOLOGICAL SCIENCES↗

Wetlab-2 - Quantitative PCR Tools for Spaceflight Studies of Gene Expression Aboard the International Space Station

Wetlab-2 is a research platform for conducting real-time quantitative gene expression analysis aboard the International Space Station. The system enables spaceflight genomic studies involving a wide variety of biospecimen types in the unique microgravity environment of space. Currently, gene expression analyses of space flown biospecimens must be conducted post flight after living cultures or frozen or chemically fixed samples are returned to Earth from the space station. Post-flight analysis is limited for several reasons. First, changes in gene expression can be transient, changing over a timescale of minutes. The delay between sampling on Earth can range from days to months, and RNA may degrade during this period of time, even in fixed or frozen samples. Second, living organisms that return to Earth may quickly re-adapt to terrestrial conditions. Third, forces exerted on samples during reentry and return to Earth may affect results. Lastly, follow up experiments designed in response to post-flight results must wait for a new flight opportunity to be tested.

ISS research platform↗

Phyllosticta paracitricarpa is synonymous with the EU quarantine fungus P. citricarpa based on phylogenomic analyses

Phyllosticta citricarpa is an important citrus-pathogen and a quarantine organism in the European Union. Its recently described relative, P. paracitricarpa, is very closely related and not listed as a quarantine organism. P. paracitricarpa is very difficult to distinguish from P. citricarpa, since its morphological features overlap and the barcoding gene sequences that were originally used to delimit them as distinct species have a low number of species-specific polymorphisms that have subsequently been shown to overlap between the two clades. Therefore, we performed extensive genomic analyses to determine whether the genetic variation between P. citricarpa and P. paracitricarpa strains should be considered to represent infraspecific variation within P. citricarpa, or whether it is indicative of distinct species. Using a phylogenomic analysis with 3,000 single copy ortholog genes and whole-genome comparisons, we determined that the variation between P. citricarpa and P. paracitricarpa can be considered as infraspecies variation within P. citricarpa. We also determined the level of variation in mitochondrial assemblies of several Phyllosticta species and concluded there are only minimal differences between the assemblies of P. citricarpa and P. paracitricarpa. Thus, using several orthogonal approaches, we here demonstrate that variation within the nuclear and mitochondrial genomes of other Phyllosticta species is larger than variation between genomes obtained from P. citricarpa and P. paracitricarpa strains. Thus, P. citricarpa and P. paracitricarpa should be considered as conspecific.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic reconstruction of Bacillus anthracis from complex environmental samples enables high-throughput identification and lineage assignment in Pakistan

Bacillus anthracis, the causative agent of anthrax, is a highly virulent zoonotic pathogen primarily affecting domesticated and wild herbivores. Human exposure to B. anthracis is primarily through contact with infected animals or contaminated animal products. In Pakistan, where livestock vaccines are largely unavailable and infected carcasses are often disposed of improperly, the risk to humans, wildlife and livestock is significant. Currently, the diagnosis of anthrax infections and outbreak tracing necessitates the isolation and culturing of B. anthracis, a process that requires BSL-3 facilities. In this study, we show that positive identification, genome reconstruction and lineage assignment can be accomplished using bioinformatic analysis of DNA extracted directly from environmental samples that would otherwise provide the starting material for isolation and culturing. This approach does not require laboratory target enrichment as is necessary for other pathogens, due in part to the extremely high bacterial load in the bloodstream in the deceased animals. Using these methods, we greatly expand the knowledge of endemic B. anthracis in Pakistan. We provide the first reference B. anthracis genomes from Pakistan since the 1970s and identify A.Br.014 Aust94 as a minor circulating sublineage alongside the dominant A.Br.047 Vollum. Future work will focus on the limits of detection and will determine if this bioinformatic method can be expanded more broadly for B. anthracis or other pathogens to replace typical culture-based methods.

A.Br.047 Vollum↗

Bionutrients-1: Utilizing Genomics and Transcriptomics to Assess the Reliability of Microorganisms for In Situ Nutrient Production on Long Duration Missions

The resupply of current long-duration crewed missions to the ISS relies on ground-launched supplies. As NASA looks toward Mars, ground-based resupply will no longer be an option. Critical nutrients, including vitamin C, vitamin K, folate, and thiamin, degrade during long-term storage, and regular consumption of these nutrients is essential for astronaut health. Another challenge of current food systems is the difficulty of consuming sufficient calories when subsisting on the limited flavors of freeze-dried food, which can lead to weight loss. The inclusion of microorganism-based food systems could alleviate both concerns. For example, the fermentation of rehydrated milk into yogurt with microorganisms genetically incorporating genes to produce critical vitamins would allow for both in situ production of nutrients and a fresh food product with additional flavor profiles. In comparison to plant food production, microorganisms require less flight infrastructure. The BioNutrients-1 mission is demonstrating viability of microbial fermentation food production in microgravity and testing the reliability of this approach for long-duration missions lacking resupply. While the BioNutrients-1 mission includes the collection of multiple phenotypic measurements, this status update will focus on the processing of samples for genomics and transcriptomics analyses as well as the planned analysis pipelines. First, the BioNutrients-1 mission seeks to identify microorganisms capable of surviving long-duration storage at ambient temperatures while maintaining genetic fidelity. To achieve this, nine commonly employed microbial species were stored at ambient temperatures in Stasis Packs on the ISS for five years. The viability and mutation rates will be measured at multiple time points for both flown and ground control samples. From an omics perspective, the changes in the bulk rates of point mutations and genetic rearrangements across the Stasis Pack species during the five years of storage will be determined, providing valuable insights into the potential of these microorganisms for long-duration space missions. Second, the BioNutrients-1 mission is characterizing the impact of microgravity on fermentation. Two strains of the yeast Saccharomyces cerevisiae, each encoding antioxidants (β-carotene or zeaxanthin) were flown to ISS for storage and fermentation within simplified bioreactors (Production Packs). The impact of microgravity on the expression of the antioxidant production genes and general metabolic genes will be determined using RNA sequencing. Ultimately, the transcriptome data will be compared to phenotypic measurements, such as the antioxidant yield, end-state biomass, and the production of EtOH, to determine the impacts of microgravity and long-term storage on microbial fermentation. The findings from this research will be instrumental in understanding the challenges and opportunities of microorganism-based food systems in space missions.

BioNutrients↗

Bulk segregant and QTL analysis of maltose metabolism in Saccharomyces eubayanus

This study investigates natural variation in maltose utilization among Saccharomyces eubayanus strains isolated from different tree hosts. An F2 population was generated from a cross between strain QC18 (Quercus-associated) and strain CL467.1 (Nothofagus-associated). Bulk segregant analysis (BSA) was performed on the F2 offspring, and QTL mapping was conducted by whole-genome sequencing of two pools of 30 segregants each, representing the lowest and highest growth in high maltose concentrations. For QTL analysis, the parental strains QC18 and CL467.1 were also sequenced.

evolutionary plasticity↗

NASA GeneLab Concept of Operations

NASA's GeneLab aims to greatly increase the number of scientists that are using data from space biology investigations on board ISS, emphasizing a systems biology approach to the science. When completed, GeneLab will provide the integrated software and hardware infrastructure, analytical tools and reference datasets for an assortment of model organisms. GeneLab will also provide an environment for scientists to collaborate thereby increasing the possibility for data to be reused for future experimentation. To maximize the value of data from life science experiments performed in space and to make the most advantageous use of the remaining ISS research window, GeneLab will apply an open access approach to conducting spaceflight experiments by generating, and sharing the datasets derived from these biological studies in space.Onboard the ISS, a wide variety of model organisms will be studied and returned to Earth for analysis. Laboratories on the ground will analyze these samples and provide genomic, transcriptomic, metabolomic and proteomic data. Upon receipt, NASA will conduct data quality control tasks and format raw data returned from the omics centers into standardized, annotated information sets that can be readily searched and linked to spaceflight metadata. Once prepared, the biological datasets, as well as any analysis completed, will be made public through the GeneLab Space Bioinformatics System webb as edportal. These efforts will support a collaborative research environment for spaceflight studies that will closely resemble environments created by the Department of Energy (DOE), National Center for Biotechnology Information (NCBI), and other institutions in additional areas of study, such as cancer and environmental biology. The results will allow for comparative analyses that will help scientists around the world take a major leap forward in understanding the effect of microgravity, radiation, and other aspects of the space environment on model organisms. These efforts will speed the process of scientific sharing, iteration, and discovery.

Space Life Science↗

Coassembly and binning of a twenty-year metagenomic time-series from Lake Mendota

Abstract The North Temperate Lakes Long-Term Ecological Research (NTL-LTER) program has been extensively used to improve understanding of how aquatic ecosystems respond to environmental stressors, climate fluctuations, and human activities. Here, we report on the metagenomes of samples collected between 2000 and 2019 from Lake Mendota, a freshwater eutrophic lake within the NTL-LTER site. We utilized the distributed metagenome assembler MetaHipMer to coassemble over 10 terabases (Tbp) of data from 471 individual Illumina-sequenced metagenomes. A total of 95,523,664 contigs were assembled and binned to generate 1,894 non-redundant metagenome-assembled genomes (MAGs) with ≥50% completeness and ≤10% contamination. Phylogenomic analysis revealed that the MAGs were nearly exclusively bacterial, dominated by Pseudomonadota (Proteobacteria, N = 623) and Bacteroidota (N = 321). Nine eukaryotic MAGs were identified by eukCC with six assigned to the phylum Chlorophyta. Additionally, 6,350 high-quality viral sequences were identified by geNomad with the majority classified in the phylum Uroviricota. This expansive coassembled metagenomic dataset provides an unprecedented foundation to advance understanding of microbial communities in freshwater ecosystems and explore temporal ecosystem dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

Trichococcus Patagoniensis sp. nov., a Facultative Anaerobe that grows at -5 C, Isolated from Penguin Guano in Chilean Patagonia

A novel, extremely psychrotolerant, facultative anaerobe, strain PmagGl(sup T), was isolated from guano of Magellanic penguins (Spheniscus magellanicus) collected in Chilean Patagonia. Gram-variable, motile cocci with a diameter of 1.3-2.0 micrometers were observed singularly or in pairs, short chains and irregular conglomerates. Growth occurred within the pH range 6.0-10.0, with optimum growth at pH 8.5. The temperature range for growth of the novel isolate was from -5 to 35 C, with optimum growth at 28-30 C. Strain PmagG1(sup T) did not require NaCl, as growth was observed in the presence of 0-6.5% NaCl with optimum growth at 0.5% (w/v). Strain PmagGl(sup T) was a catalase-negative chemo-organoheterotroph that used sugars and some organic acids as substrates. The metabolic end products were lactate, formate, acetate, ethanol and Con. Strain PmagG1(sup T) was sensitive to ampicillin, tetracycline, chloramphenicol, rifampicin, kanamycin and gentamicin. The G+C content of its genomic DNA was 45.8 mol%. 16S rRNA gene sequence analysis showed 100 % similarity of strain PmagG1(sup T) with Trichococcus collinsii ATCC BAA-296(sup T), but DNA-DNA hybridization between them demonstrated relatedness values of less than 45 plus or minus 1%. Another phylogenetically closely related species, Trichococcus pasteurii, showed 99.85 % similarity by 16s rRNA sequencing and DNA-DNA hybridization showed relatedness values of 47 plus or minus 1.5%. Based on genotypic and phenotypic characteristics, the novel species Trichococcus patagoniensis sp. nov. is proposed, with strain PmagG1(sup T) (=ATCC BAA-756(sup T)=JCM 12176(sup T)=CIP 108035(sup T)) as the type strain.

Pikuta, Elena V.↗

High throughput, accurate gene annotation through AI and HPC-enabled structural analysis

With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.

59 BASIC BIOLOGICAL SCIENCES↗

A single genomic region controls primocane fruiting in tetraploid blackberry

The fresh-market blackberry ( Rubus subgenus Rubus ) industry has expanded dramatically in the past 2 decades, driven in part by improved cultivars. Introgression of the primocane-fruiting (PF; annual flowering) trait into elite germplasm has enabled dual cropping in a single year, season extension, and cultivation in tropical and subtropical regions. Despite its economic performance, the genetic basis of PF is not well understood. It has been proposed that the PF trait is controlled by a major recessive locus, but its genomic location is unclear. Here, a genome-wide association study (GWAS) of 365 tetraploid blackberry genotypes identified a single genomic region on chromosome Ra03 (∼33 Mb) strongly associated with PF. Genetic linkage analysis in a biparental population confirmed that the same interval (32–35 Mb) was linked to the PF phenotype. Ten putative candidate genes were identified in this region. Allele mining using whole-genome resequencing of 17 genotypes highlighted 2 high-priority candidates: a CCCH-type zinc finger gene and an ubiquitin-specific protease gene. Use of an improved Rubus argutus “Hillquist” genome annotation (v1.2) enabled refined variant interpretation, including identification of regulatory 3′ UTR polymorphisms in the zinc finger homolog. Two diagnostic KASP markers (PF1 and PF2), designed from the most significant GWAS SNPs, predicted the PF phenotype with over 96% accuracy in a validation panel of 494 tetraploid blackberries from multiple breeding programs. Together, these results provide the first high-resolution mapping of the PF locus in blackberry, identify candidate genes for flowering regulation in Rubus , and deliver diagnostic markers that can be immediately deployed in breeding programs.

GWAS↗

Deciphering Spaceflight Medical Risks Using High-Performance Computing and Next Generation Sequencing Data From Model Organisms

Somatic mutations are acquired point mutations and other forms of genetic alteration in the DNA of somatic cells in the body. Unlike germline mutations, which can be passed on from one individual to another, somatic mutations are not heritable. Somatic mutation (also called genetic sequence variation) has been recognized for decades as an important mechanism for initiating the development of cancer. Now, with the advent of next generation sequencing (NGS), the study of somatic mutation has become much more accessible, enabling genome scientists to characterize somatic mutations in a comprehensive fashion across the entire genome. From recent studies, it is now apparent that other disease processes besides cancer may be influenced by somatic mutation as well, including degenerative processes and inflammatory diseases. Cancer, degenerative diseases and inflammatory processes are all of concern in the setting of spaceflight. Study of somatic mutation analysis, therefore, is an important new tool for examining some of the earliest changes in the genome that lead to disease. This approach has tremendous potential for NASA, for analysis of both model organisms and humans.

Somatic mutation on ISS↗