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At least 775 records · Page 43

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs. The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methylmercury quantification, is also planned.

Design↗

Developmental Research in Space: Predicting Adult Neurobehavioral Phenotypes via Metabolomic Imaging

As human habitation and eventual colonization of space becomes an inevitable reality, there is a necessity to understand how organisms develop over the life span in the space environment. Microgravity, altered CO2, radiation and psychological stress are some of the key factors that could affect mammalian reproduction and development in space, however there is a paucity of information on this topic. Here we combine early (neonatal) in vivo spectroscopic imaging with an adult emotionality assay following a common obstetric complication (prenatal asphyxia) likely to occur during gestation in space. The neural metabolome is sensitive to alteration by degenerative changes and developmental disorders, thus we hypothesized that that early neonatal neurometabolite profiles can predict adult response to novelty. Late gestation fetal rats were exposed to moderate asphyxia by occluding the blood supply feeding one of the rats pair uterine horns for 15min. Blood supply to the opposite horn was not occluded (within-litter cesarean control). Further comparisons were made with vaginal (natural) birth controls. In one-week old neonates, we measured neurometabolites in three brain areas (i.e., striatum, prefrontal cortex, and hippocampus). Adult perinatally-asphyxiated offspring exhibited greater anxiety-like behavioral phenotypes (as measured the composite neurobehavioral assay involving open field activity, responses to novel object, quantification of fecal droppings, and resident-intruder tests of social behavior). Further, early neurometabolite profiles predicted adult responses. Non-invasive MRS screening of mammalian offspring is likely to advance ground-based space analogue studies informing mammalian reproduction in space, and achieving high-priority.

rodent development spacefligh↗

Increasing the Statistical Rigor of Cross-Species Differential Expression Analysis

Microgravity inflicts substantial, but undercharacterized, pressure on organisms that induces metabolic responses such as increased microbial virulence and antibiotic resistance, altered organ weights in developing rats, and loss of bone tissue in astronauts. Numerous studies have analyzed the effects of microgravity on specific organisms, tissues, or test conditions, but these projects are necessarily limited by the small sample size of space research. Increasing the sample size of spaceflight studies is non-trivial; however, pooling data from numerous studies can greatly increase the statistical rigor of comparative analyses. The GeneLab houses datasets from 73 spaceflight studies that performed transcription profiling assays. These data encompass a diverse array of organisms ranging from Escherichia coli to Mus musculus to Homo sapiens and comprise studies analyzing ionizing radiation, mammalian pregnancy, etc. Collectively, the GeneLab database contains a large quantity of transcription assays and RNA sequence data analyzing Differential Gene Expression (DGE) between microand normogravity. Xspecies, a cross-species analysis method for DGE developed by Kristiansson, et al. in 2012, identifies homologous genes between species that are universally up- or downregulated in response to test conditions. Previous work by an intern at GeneLab applied Xspecies to 19 datasets containing seven different species and identified 14 homologous groups differentially expressed under spaceflight conditions including several heat shock proteins and cytoskeletal components. Unfortunately, these results may be biased by the disproportionate number of studies on Arabidopsis thaliana (5) and Mus musculus (6) and the results are not normalized by evolutionary distances. Here, we present modifications to the Xspecies algorithm that permits incorporation of multi-omic data and normalizes data for effect size, directionality, and evolutionary distances. We then apply this algorithm to all currently available GeneLab studies

Xspecies↗

Zoledronate Prevents Simulated Weightlessness-Induced Bone Loss in the Cancellous Compartment While Blunting the Efficacy of a Mechanical Loading Countermeasure

Astronauts using high-force resistance training while weightless show a high-turnover remodeling state within the skeletal system, with resorption and formation biomarkers being elevated. One countermeasure for the skeletal health of astronauts includes an antiresorptive of the bisphosphonate (BP) drug class. We asked, does the combination of an anti-resorptive and high-force exercise during weightlessness have negative effects on bone remodeling and strength? In this study, we developed an integrated model to mimic the mechanical strain of exercise via cyclical loading (CL) in mice treated with the BP Zoledronate (ZOL) combined with hind limb unloading (HU) to simulate weightlessness. We hypothesized that ZOL prevents structural degradation from simulated weightlessness and that CL and ZOL interact to render CL less effective. Thirty-two C57BL/6 mice (male, 16 weeks old, n=8/group) were exposed to 3 weeks of either HU or normal ambulation (NA). Cohorts of mice received one subcutaneous injection of ZOL (45μg/kg), or saline vehicle (VEH), prior to the start of HU. The right tibia was axially compressed in vivo 60x/day to 9N (+1200μstrain on the periosteal surface) and repeated 3x/week during HU. Left tibiae served as a within subject, non-compressed control. Ex vivo μCT was performed on all subjects to determine cancellous and cortical architectural parameters. Static and dynamic histomorphometry were carried out for the left and right tibiae to determine osteoclast- and osteoblast relevant surfaces. Further, micro damage was assessed in select groups by basic-fuchsin staining to test whether CL had an effect. For all assays, a multivariate (2x2x2) ANCOVA model was used to account for body weight changes. Additionally, for the tibiae, we incorporated a random effect for the subject (hence, a mixed model) to account for observations of both left and right tibiae within each subject. P < 0.05 was considered significant. In the cancellous compartment of the proximal tibial metaphysis, we observed a main effect from each independent variable, as determined by structural and histomorphometric assays. Specifically, as expected, ZOL showed an increase in the cancellous bone volume to total volume fraction (BV/TV, +32%) and trabecular number (+18%) compared to the VEH. As expected, ZOL decreased osteoclast surface (OC/BS) by -45% compared to VEH. Surprisingly, ZOL reduced mineralizing surface (MS/BS) and bone formation rate (BFR), indicators of osteoblast activity, by -40% and -54%, respectively, compared to VEH. Altogether, ZOL-treated mice displayed a low turnover state of remodeling in the metaphysis. In the context of skeletal aging, we speculate that ZOL prevented age-related cancellous strut loss during the experiment. As a main effect, as expected, HU decreased BV/TV by - 31% via reductions in both trabecular thickness (-11%) and number (-22%) compared to NA controls. Additionally, HU decreased MS/BS by -38% and bone formation rate (BFR) by -50% compared to NA controls. Altogether, these data are consistent with structural degradation resulting from imbalanced remodeling that favors resorption. As a main effect, CL increased BV/TV by +15% via increased trabecular thickness (+12%) compared to the noncompressed limb. As expected, CL increased MS/BS (+20%) and BFR (+24%), indicating osteoblast mineralization contributed to bone gains. These data show that CL provided an anabolic stimulus to the cancellous tissue. We observed unique interactions in ZOL*CL and HU*CL. First, ZOL prevented CL-induced increases in BV/TV and trabecular number, as compared to VEH. In the context of skeletal aging, these data suggest no added benefit from CL in the ZOL-treated mice. Interestingly, no microdamage was observed in mice that were unloaded and treated with ZOL (independent of CL). Secondly, HU prevented CL-induced increases in BFR, as compared to NA controls. These data suggest that either exercise is less effective or the kinetics of formation are slower during simulated weightlessness. Osteoclast surface was unchanged by either treatment. Thus, in contrast to exercising astronauts, these data do not suggest a high-turnover state in the metaphysis. To assess mechanical properties as a function of HU or ZOL, we tested the left femur in three-point bending ex vivo. As expected, HU decreased stiffness (-30%) compared to NA, and ZOL increased stiffness compared to VEH (+28%). Interestingly, HU increased the post-yield displacement, related to collagenous tensile loading, compared to NA (+20%). ZOL increased yield force (+11%) and ultimate force (+17%), which seems to explain the significant effect of ZOL increasing total energy (work-to-fracture, +15%), while not affecting the post yield displacement. Taken together, ZOL did not have detrimental affect on mechanical properties. Our integrated model simulates the combination of weightlessness, exercise-induced mechanical strain, and anti-resorptive treatment that astronauts experience during space missions. We conclude that Zoledronate was an effective countermeasure against weightlessness-induced bone loss, though zoledronate, as well as weightlessness, rendered exercise-related mechanical loading less effective.

bone↗

A UAV-Based Fog Collector Design for Fine-Scale Aerobiological Sampling

Airborne microbes are found throughout the troposphere and into the stratosphere. Knowing how the activity of airborne microorganisms can alter water, carbon, and other geochemical cycles is vital to a full understanding of local and global ecosystems. Just as on the land or in the ocean, atmospheric regions vary in habitability; the underlying geochemical, climatic, and ecological dynamics must be characterized at different scales to be effectively modeled. Most aerobiological studies have focused on a high level: 'How high are airborne microbes found?' and 'How far can they travel?' Most fog and cloud water studies collect from stationary ground stations (point) or along flight transects (1D). To complement and provide context for this data, we have designed a UAV-based modified fog and cloud water collector to retrieve 4D-resolved samples for biological and chemical analysis.Our design uses a passive impacting collector hanging from a rigid rod suspended between two multi-rotor UAVs (Unmanned Aerial Vehicles). The suspension design reduces the effect of turbulence and potential for contamination from the UAV downwash. The UAVs are currently modeled in a leader-follower configuration, taking advantage of recent advances in modular UAVs, UAV swarming, and flight planning.The collector itself is a hydrophobic mesh. Materials including Tyvek, PTFE, nylon, and polypropylene monofilament fabricated via laser cutting, CNC knife, or 3D printing were characterized for droplet collection efficiency using a benchtop atomizer and particle counter. Because the meshes can be easily and inexpensively fabricated, a set can be pre-sterilized and brought to the field for 'hot swapping' to decrease cross-contamination between flight sessions or use as negative controls.An onboard sensor and logging system records the time and location of each sample; when combined with flight tracking data, the samples can be resolved into a 4D volumetric map of the fog bank. Collected samples can be returned to the lab for a variety of analyses. Based on a review of existing flight studies, we have identified ion chromatography, metagenomic sequencing, cell staining and quantification, and ATP quantification as high-priority assays for implementation. Support for specific toxicology assays, such as methyl-mercury quantification, is also planned.

Design↗

Electrochemical Life Detection Methods for Ocean World Exploration

Ubiquitous across terrestrial life is cellular machinery that allows chemical energy flow by facilitating and regulating electron-transfer and chemical modification pathways. Key classes of energy transport molecules enable this movement of electrons for a variety of biological purposes. Additionally, biological enzymes function to add or remove functional groups such asphosphate moieties to redox biomolecules. Presumably, extraterrestrial life is likely to rely on similar energy transport mechanisms. With the search for life in our solar system focused on the icy satellites of Jupiter and Saturn, Europa and Enceladus, developing instrumentation capable of measuring electrochemical redox signatures representative of biomolecules or enzymatic activity in seawater appears a promising and novel means of life detection. Here, we report our adaptation of the Mars Phoenix Wet Chemistry Laboratory (WCL) electroanalytical voltammetry capabilities to assay life-critical redox molecules in synthetic seawater representative of a saline alkaline solution similar to what has been predicted from the Cassini mission data of Enceladus’ sub-surface ocean. In addition, we employ a well-established electrochemical assay that indicates phosphatase activity by comparing substrate and product redox signatures. Our study demonstrated a 10 nM limit of detection for biological redox molecules and a 3 aM limit of detection for alkaline phosphatase in seawater. Incorporation of these methods into next generation WCL payloads aimed at ocean world life detection will enable the search for biological redox-active species and enzymatic activity as indicators of life.

planetary instruments↗

Rapid Nucleic Acid Isolation Method and Fluid Handling Devices Overview

Sample preparation is a common bottleneck in genetic analysis. Tools that reduce time and effort are of value in a laboratory setting. There is a need for a genetic analysis/detection system that is not only mobile, ruggedized, easy-to-use but also provides an enclosed fluid handling that diminishes the risks of Ribonucleic acid (RNA) contamination and degradation during processing. NASA has developed a novel assay methodology and suite of devices to isolate nucleic acids and prepare samples for real-time (quantitative) polymerase chain reaction (PCR) analysis that solves the problem of contamination and degradation because of the advanced microfluidics which provides better fluid handling. The assay employs an aqueous-based non-alcohol method that yields robust RNA quality. The suite of ready-to-use devices provide pre-loaded reagents in liquid and lyophilized formats to enable rapid, cost effective, and portable manual operation in the laboratory or remote field environments.

Travis Boone↗

Understanding amyloids to prevent biofilm formation in space

There is a pressing need to search for novel approaches to combat biofilm formation, both in space and in medical applications. Many proteins have the ability to form ordered aggregates called amyloids. Amyloids are known to be an important part of biofilms. The use of anti-amyloid drugs is a novel venue for the development of antimicrobial agents. The ultrastructure of the amyloid aggregate shows a high packing of proteins, the second-order structure of which is dominated by β-sheets. The ability to form an amyloid aggregate is especially typical for proteins containing domains (protein fragments) with sufficient lability to arrange themselves in a tight β-sheet structure. Bioinformatics tools allow the prediction of such behavior of proteins in genomic data. We use GeneLab data of microbial populations identified aboard the International Space Station and other spacecraft to look for bacterial species that utilize amyloid aggregation in biofilm formation. We use a combined bioinformatic approach with a relatively high throughput molecular biology assay and biophysical assays to evaluate the anti-amyloid anti-biofilm approach. The significance of the research extends from understanding basic microbial community responses to spaceflight, to biofouling of the built environments in space as well as the long-term health of astronauts. Bioinformatics shows that onboard the ISS, bacterial species produce far more amyloid and prion proteins than are currently verified, hence their role in bacterial ecosystems is largely unknown. As we propose there is a link between amyloid formation in space and biofilm production, this research should lead to new paths for biofilm remediation in space.

Tomasz Zajkowski↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, the re-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA’s Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related ‘omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata ‘omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data re-use, resulting in 38 additional publications derived from the original 67 publication over the past four years. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA “Open Science Data Repositories (OSDR)” and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Fluorescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to “big data” from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology. Several other talks will cover these topics in this conference.

life sciences↗

Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery

The next era in human space exploration is rapidly approaching and will require the use of countermeasures to deep space health hazards. The development of countermeasures (or, there-purposing of existing agents) will be highly dependent on our understanding of basic biological responses to space stressors (e.g. ionizing radiation, altered gravitational fields, altered day-night cycles, confinement, isolation, hostile-closed environments, distance-duration from Earth, exposure to celestial regolith, etc.). The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, imaging, whole organism and behavior). We will discuss here several strategies that NASA's Biological and Physical Science Division has put in place to maximize the return on investment for spaceflight bioscience data. Open Science, as a scientific philosophy, is the concept that the more people who have access to the data, the more knowledge will be gained from it. This guiding principle led NASA to develop GeneLab in 2015. GeneLab houses spaceflight and relevant ground-based multi-omics data, and has grown to ~400 transcriptomatic, proteomic, metabolomic and epigenomic datasets from plant, rodent, small animal, and microbial space experiments. GeneLab provides users with various tools for data analysis and a visualization portal that allows users to interact with gene expression data from space-related 'omics experiments. Open Science is also about building scientific communities, and with this spirit in mind, GeneLab has spawned several Analysis Working Groups (AWGs), comprised of more than 200 volunteer scientists. The AWGs initially provided feedback on the processing pipeline and metadata 'omics standards for GeneLab. Over the last few years, they have become a community-driven science enterprise, engaging in large meta-analysis of GeneLab datasets, resulting in 10 publications (beyond the originally submitted research). Overall, the Open Science nature of GeneLab has resulted in a high degree of data-use, resulting in 40 enabled publications by open data. The enormous success and knowledge gained from GeneLab has led to a collection of sister NASA "Open Science Data Repositories (OSDR)" and research support groups. These include the NASA Ames Life Sciences Data Archive (ALSDA), the NASA Biological Institutional Scientific Collection (NBISC), and the Biospecimen Sharing Program (BSP). All are adopting the GeneLab data architecture system to maximize open-access, find-ability, accessibility, interoperability, and reusability (FAIR). ALSDA collects and curates phenotypic-physiological bioimaging-behavioral data from space and space-relevant non-human experiments, oftentimes coming from the same omics-associated experimental datasets found in GeneLab. Since 2021, a community of ~100 researchers have rallied around ALSDA, to provide feedback in a new ALSDA AWG focused on phenotypic-physiological investigation-sample-assay metadata standards (e.g., Micro-Computed Tomography, Light/Flourescence Microscopy, Western Blot, Flow Cytometry, Novel Object Recognition, Elevated Plus Maze, etc. of ~50 assays collected). These standards are part of a new single point-of-entry data submission portal for all non-human Space Biology and Human Research Program principal investigators, to submit, curate, and share their research data. With open-access space biological data now collected and curated together with rich metadata, and with the potential for linkage to "big data" from the international biological and medical communities (NIH, EBI, etc.), the artificial intelligence and machine learning (AI/ML) era has started for Space Biology.

omics↗

Microbial Methods for Testing a Novel Spacecraft Bioburden Reduction Method

In order to circumvent the contamination of microorganisms in both extraterrestrial and terrestrial environments, spacecraft hardware must often be sterilized. Current sterilization practices are both time-consuming and expensive. Techniques such as dry heat sterilization and scattered/localized electric field enhancements are incompatible with a variety of hardware materials as well as complex surface shapes. Our group is testing a novel femtosecond pulsed laser for the rapid sterilization of spacecraft hardware using high photon fluxes, which is both an efficient and effective technique to ensure a reduced microbial burden aboard spacecraft. This method is likely to be effective because microorganisms have not encountered high photon fluxes in their evolutionary history and thus contain no protective mechanisms against them. To assess the effectiveness of pulsed laser sterilization, we used a combination of scanning electron microscopy and elemental analysis for the examination of damaged spores on metal coupons, as well as microbiology methods for spore assays. The surfaces of metal coupons inoculated with Bacillus subtilis were illuminated with femtosecond pulses at various wavelengths below the damage threshold for the aluminum. After laser treatment, metal coupon samples were sonicated to dislodge spores, serially diluted, and finally plated and incubated. Results show that sterilization efficiency is favorable in some conditions. The NASA standards for spore assays are a preliminary demonstration in establishing the trend in ability to kill spores. The results show potential for the dual pulse illumination method as a sterilization technique for planetary protection applications.

Maha S Ulhaq↗

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↗

NASA GeneLab Multi-study Visualization Portal

NASA GeneLab has helped advance the field of Space Biology by providing a public repository where researchers can store, share, analyze and visualize the results of space flight related omics experiments. The GeneLab data visualization portal allows any user, regardless of bioinformatics knowledge or access to computational resources, to interact with the experimental data, draw their own conclusions, and gain insights about the effects of space on living systems. These tools help democratize scientific research and foster the NASA Open Science initiative. The new multi-study feature of the GeneLab visualization platform allows users to mine study metadata from RNA sequencing (RNA-seq) experiments to identify samples of interest by filtering datasets based on organism, tissue, assay technology type, and/or factor. Once samples are selected from multiple datasets, users can combine and normalize the sample data, then utilize the visualization displays, including Principal Component Analysis (PCA) plots, to assess sample distributions. Finally, users can perform differential gene expression analysis on the combined data and visualize the results through PCA plots, Volcano plots, Pair plots, Heatmap, Ideogram and Gene Set Enrichment Analysis. All user-generated results and visualizations will be available for download. Here, we present a biological study using samples from multiple GeneLab RNA-seq datasets and analyzed using the multi-study visualization platform to demonstrate inter- and intra-study variability, as well as commonly differentially expressed genes between spaceflight and ground control conditions across datasets. This new feature opens a wide range of possibilities and opportunities for further development including combining other assay technology types and integration with batch effect correction techniques and machine learning applications. Overall, this tool allows users to increase the statistical power of individual experiments, validate hypothesis, identify patterns, and opens the door to new and exciting research.

space biology↗

Open Science for Plants in Space: Improvements in NASA's Open Science Data Repository

Upcoming deep space missions will rely on plants for crew and ecosystem health. Open access space biology data enables scientists to examine the biological responses of plants to ionizing radiation, altered gravity, elevated CO2, and many other abiotic stressors. NASA has declared 2023 as the ‘Year of Open Science’ and created a 5-year Transform to Open Science (TOPS) initiative designed to rapidly transform the agency toward an inclusive culture of open science. NASA’s Open Science Data Repository (OSDR) combines two databases, GeneLab and Ames Life Sciences Data Archive (ALSDA) to maximize access to standardized ‘omics (e.g., transcriptomics, proteomics) and phenotypic data (e.g., microscopy, biomass), respectively. Current OSDR standards include the ISA (Investigation-Study-Assay) experiment model, assay metadata configurations, and standardized terminology and ontologies. In 2024 OSDR will include a new suite of features for improved FAIR compliance including downloadable plant metadata templates, data submission tools and overall improved AI-readiness of plant datasets. AI/ML methods can be helpful tools to overcome the inherent challenges of space biology research (small sample size, sparse and heterogeneous data etc.). However these methods are built on an assumption of normalized and well-curated data. OSDR’s new curation tools will improve users ability to leverage ML and AI methods to model space biology data and better understand the complex effects of spaceflight on living systems across hierarchical biological levels. We look forward to sharing our advances with the spaceflight community.

FAIR↗

T-Cell Shenanigans: The Impact of MHC Pathway & Lipid Metabolism Genes on T-Cell Differentiation in the Thymus

Astronaut health and proper immune function are key to the success and sustainability of long term missions in space. While previous studies have observed adaptive immune dysfunction such as diminished WBC counts and cytokine production during spaceflight, the underlying mechanisms behind why immune function worsens are poorly understood. Using transcriptomic data analyzed from mouse thymus tissues available from the GLDS-421 experiment on the Rodent Research-9 mission, we used the GeneLab standardized RNA-Seq pipeline and identified four genes that were largely dysregulated (p<0.05): lipid metabolic genes Hpgd and Pgr and cell cycle regulator genes Cenpe and Kif11. We analyzed how these genes regulate the MHC-TCR interaction, and used this understanding to propose a novel mechanism for alterations to T-cell differentiation. In our experimental methodology, we propose to use 36 transgenic CD4-CD8 mice and 12 wild-type mice from the Jackson Lab to create a microgravity-simulating hindlimb unloading model and test our hypothesis. By silencing the aforementioned genes using custom siRNA based primers, we will use flow cytometry and RNA-Seq to quantify Treg counts in comparison to naive CD4+ cells, Alamar Blue assay for observing the metabolic activity in T-cells, and Enzyme-Linked Immunosorbent Assay (ELISA) to observe the general immune response in terms of T-cell differentiation. We hope this methodology will improve our knowledge of MHC-TCR interaction, contribute to a better understanding of the mechanisms of autoimmune diseases such as lupus, and improve the success rate of newer cancer treatments such as CAR-T cell therapy.

GL4HS↗

Safeguards Technical Objectives for Thorium Molten Salt Reactor Fuel Cycles

China, Denmark, France, India, Indonesia, the United Kingdom, and the United States, among others, are exploring commercial thorium fuel cycles for domestic power production and/or international export. For any thorium fuel cycle facilities built and/or operated in a non-nuclear weapon State with a comprehensive safeguards agreement, those facilities and any associated nuclear material would be subject to international nuclear safeguards by the International Atomic Energy Agency (IAEA). Thorium fuel cycle facilities offered for the application of safeguards under a voluntary offer agreement by a nuclear weapon State would also be subject to safeguards, if selected by the IAEA. Compared to uranium/plutonium fuel cycle facilities, thorium fuel cycle facilities are comparatively diverse from an inspection and accounting perspective, differing greatly in material type, form, and design from uranium/plutonium fuel cycle facilities and also from each other. Of these, the most complex thorium fuel cycles – and therefore likely the most challenging to the implementation of international nuclear safeguards – are those that include thorium molten salt reactors. With thorium fuel cycles approaching near-term commercial deployment timelines, it is imperative that the international nuclear safeguards community begins to think about how to adapt existing international nuclear safeguards concepts and approaches to thorium fuel cycles, as well as mitigate any gaps that may exist. This paper focuses on the development of recommended safeguards technical objectives for efficient and effective application of international nuclear safeguards measures (e.g., containment / surveillance, non-destructive assay, destructive assay, environmental sampling) to thorium molten salt reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermostable haloarchaeal inorganic pyrophosphatase

The invention pertains to a PPA from a microorganism belonging to the family Halobacteriaceae (HPPA), for example, a PPA from Haloferax volcanii. The HPPA provided by the invention is soluble, thermostable and active at high concentrations of salt and/or organic solvent. An embodiment of the invention provides a method of increasing the rate of a reaction by adding an HPPA to the reaction mixture, wherein the reaction produces PPi, for example, an enzymatic reaction, and wherein the reaction is carried out at moderately high temperature and/or low water activity. Further embodiments of the invention provide an assay to detect the PPi released during a reaction which produces PPi by adding an HPPA to convert the PPi in to Pi and measuring the resultant Pi. The invention further pertains to an assay to monitor a reaction which produces PPi in the presence or the absence of an HPPA.

Maupin-Furlow, Julie A.↗

Model Choice Metrics to Optimize Profile-QSAR Performance

Predicting molecular activity against protein targets is difficult because of the paucity of experimental data. Approaches like multitask modeling and collaborative filtering seek to improve model accuracy by leveraging results from multiple targets, but are limited because different compounds are measured with different assays, leading to sparse data matrices. Profile-QSAR (pQSAR) 2.0 addresses this problem by fitting a series of partial least squares models for each target, using as features the predictions from single-task models on the remaining targets. Here, this method has been shown to produce better results than single task and multitask models. However, the factors determining the success of pQSAR 2.0 have as yet not been characterized. In this paper we examine the experimental conditions that lead to better pQSAR models. We limit the amount of data available to the method by retraining with decreasing amounts of data and explore the model’s ability to generalize to compounds that have never been assayed. Finally, we look at the properties of training data needed to demonstrate pQSAR improvement.

Biological and medical sciences, Computer science↗