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NASA Omics Archive Project

The space environment consists of a complex set of hazards including altered gravity, radiation, psychological/physiological stress, isolation, and confinement leading to complex biological responses. Advances in biotechnology capabilities offer considerable potential to provide novel insight into those responses as well as innovative diagnostic, treatment, and countermeasure solutions for astronauts as NASA begins to travel beyond low Earth orbit. Omics data (genomics, transcriptomics, proteomics, etc.) is one example that can provide NASA with critical knowledge of how a crewmember’s genetics, environment, and lifestyle can be used to develop individualized approaches for disease prevention, advance diagnostics, and improve treatment strategies. NASA ventured into the field of omics on human subjects with the successful completion of the NASA Twins Study which was the first step in mapping the multi-omic profile of astronauts to understand and mitigate the health consequences of spaceflight. The Human Research Program aims to build upon the success of the Twins Study with the NASA Omics Archive flight study, establishing a longitudinal biospecimen archive and efficiently generating a comprehensive high-quality multi-omic dataset from astronauts for the purpose of studying molecular, metabolic, and microbial changes associated with longduration spaceflight missions. The goal is to facilitate scientific and medical research community efforts to characterize and mitigate spaceflight health and performance risks. In this presentation, we will review details regarding the biospecimen and data archive to be generated by the NASA Omics Archive flight study. Data generated as part of this project will be archived in the NASA Life Sciences Portal (NLSP) and be made available for future hypothesis-driven research efforts or occupational surveillance through Institutional Review Board-approved data sharing and retrospective data requests submitted to the Life Sciences Data Archive (LSDA) team. We will also present results of a ground study performed to evaluate in-house procedures, new sample collection hardware, and vendor capabilities. The data repository generated and the samples to be archived by this study will enable future research efforts to assess an astronauts’ unique molecular and genetic profile with respect to individual spaceflight responses. Results of which will be instrumental in enabling precision health capabilities to better assess and mitigate spaceflight risks, detect disease states earlier, and actively monitor countermeasure treatments, ultimately improving clinical outcomes during future exploration class missions.

C. A. Theriot↗

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗

Spaceflight Environmental-Telemetry Data for Biological Science

There is a critical need for better access and visualization of spaceflight environmental telemetry and mission hardware data from sensors including relative humidity, carbon dioxide, oxygen, radiation, airflow, temperature, acceleration, and acoustics. Under the stewardship of the Ames Life Sciences Data Archive (ALSDA) and GeneLab, an effort is underway to consolidate, normalize and provide accessibility of archived mission environmental data and hardware information, with the purpose of providing important context to biological data. This effort is necessary to provide scientific context of its impact upon biological and biomedical data from spaceflight missions and experiments (genomic, metagenomic, gene expression, proteomic, metabolomic, physiological, phenomics, behavioral; tabular, imaging, video). Environmental spaceflight data is derived from dozens of sources, with various formats, and in the past year a pipeline is in development to collect, curate and present this data efficiently. In the upcoming year, a new Data Visualization Portal will utilize the standardized pipeline data to provide easy user access to compare parameters and environmental conditions between missions, locations, subjects, and durations. Environmental and hardware data enables broad accessibility and analytics, without the need for advanced data informatic expertise. Familiarity with the capabilities and limitations of a variety of existing hardware/tools is a strength that could be applied to creation of improved hardware for future ecosystems on the Moon and Mars. The intention is to make biological and environmental telemetry data maximally open-access and FAIR (findable, accessible, interoperable, reusable) for data mining-informatic approaches to support knowledge discovery necessary for low Earth orbit, cis-Lunar, Mars transit, and Mars surface missions.

Danielle K. Lopez↗

Murine Host-gut Microbiota Interactions are Modulated During Spaceflight

The rodent habitat on the International Space Station has provided critical insight into the impact of spaceflight on mammalian physiology. These effects include dysfunction of carbohydrate, steroid and lipid metabolism, and immune response, as well as induction of symptoms characteristic of liver disease, insulin resistance, osteopenia and myopathy, which are anticipated to intensify over long-duration spaceflight. Although these physiological responses can involve the microbiome, the host-microorganism interactions during spaceflight are still largely unknown. NASA GeneLab curates a wide range of space research data and the current work harnesses GeneLab multi’omic data from recent Rodent Research studies to explore changes to gut microbiota during spaceflight and their associations with host physiology when compared to ground controls. Using a hybrid analysis of DNA barcoding and whole genome shotgun data, an array of bacteria, fungi and nematodes could be identified at species level, and significant differences in relative abundances associated with spaceflight. Functional prediction based on differential abundance of species and metagenome gene inventories as well as metatranscriptomic gene expression at the host-gut microbiome interface implicate microbiota interactions could contribute to spaceflight pathology. Harnessing carefully curated publicly available data, such as from Genelab, to generate multi‘omic space science discoveries can help decipher the complex host-microbiome interactions that influence both health on Earth and the feasibility of long-duration spaceflight.

Microbiome↗

An Integrated Design Tool for Tow-Steered Laminates of Composites in Abaqus and MSC.Patran/Nastran

Tow-steered composites can be tailored for optimal mechanical performance of lightweight structures. However, there are no commercial-grade design tools for tow-steered composite structures, which hinders the design innovation of tow-steered composites in realistic structures. The novelty of this paper is to develop an integrated design framework along with the development of graphical user interface (GUI) plug-ins in commercial finite element (FE) software Abaqus and MSC.Patran/Nastran. The GUI plug-ins take all the design setups and communicate with external codes for the material modeling and optimization, and hence provide a unified design environment within the FE codes. The mechanics of structure genome (MSG) plate model computes shell element properties based on user-defined fiber paths and layup, which are defined via the GUI plug-ins. The optimization is performed by an open-source code, Dakota, from Sandia National Laboratories (Sandia), which also coordinates the structural analysis, material modeling, and optimization in design iterations. Two examples are presented to demonstrate the user-friendliness and versatility of the developed GUI plug-ins. The developed tools will ease the design process and facilitate the application of tow-steered composites in realistic aerospace structures.

Xin Liu↗

An Integrated Design Tool for Tow-Steered Laminates of Composites in Abaqus and MSC.Patran/Nastran

Tow-steered composites can be tailored for optimal mechanical performance of lightweight structures. However, there are no commercial-grade design tools for tow-steered composite structures, which hinders the design innovation of tow-steered composites in realistic structures. The novelty of this paper is to develop an integrated design framework along with the development of graphical user interface (GUI) plug-ins in commercial finite element (FE) software Abaqus and MSC.Patran/Nastran. The GUI plug-ins take all the design setups and communicate with external codes for the material modeling and optimization, and hence provide a unified design environment within the FE codes. The mechanics of structure genome (MSG) plate model computes shell element properties based on user-defined fiber paths and layup, which are defined via the GUI plug-ins. The optimization is performed by an open-source code, Dakota, from Sandia National Laboratories (Sandia), which also coordinates the structural analysis, material modeling, and optimization in design iterations. Two examples are presented to demonstrate the user-friendliness and versatility of the developed GUI plug-ins. The developed tools will ease the design process and facilitate the application of tow-steered composites in realistic aerospace structures.

Xin Liu↗

The NASA Twins Study: The Effect of One Year in Space on Long-Chain Fatty Acid Desaturases and Elongases

Background: To date, there is no clear understanding of the effect of long-duration spaceflight on the major enzymes that govern the metabolism of omega-6 and omega-3 fatty acids. To address this gap in knowledge, we used data from the NASA Twins Study, which includes a multi-scale omic investigation of the changes that occurred during a year-long (340 days) human spaceflight. Embedded within the NASA Twins data are specific analytes associated with fatty acid metabolism. Objectives: To examine the long-chain fatty acid desaturases and elongases in a single human during one year in space. Method: One male twin was on board the International Space Station (ISS) for one year, while his monozygotic twin served as a genetically matched ground control. Longitudinal assessments included the genome, epigenome, transcriptome, proteome, metabolome, microbiome, and immunome during the mission, as well as six months before and after. The gene-specific fatty acid desaturase and elongase transcriptome data (FADS1, FADS2, ELOVL2 and ELOVL5) were extracted from untargeted RNA-seq measurements derived from white blood cell fractions. Results: Most data from the elongases and desaturases exhibited relatively similar expression profiles (R2>0.6) over time for the CD8, CD19, and LD cell fractions, indicating overall conservation of function within and between the subjects. Both cell-type and temporal specificity was observed in some cases, and some differences were also apparent between the poly-adenylated fraction (polyA) of processed RNAs vs. the ribo-depleted (ribo-) fraction. The flight subject showed a stronger enrichment of the Fatty Acid Metabolic processes pathway across almost all cell types (columns, CD4, CD8, CPT, LD), most especially in the ribodepleted fraction of RNA, but also with the polyA+ fraction of RNA. GSEA enrichment measures across three related Fatty Acid Metabolism pathways showed a differential between the ground and flight subject. Conclusions: There appears to be no persistent alteration of desaturase and elongase gene expression associated with one year in space. However, these data provide evidence that cellular lipid metabolism can be responsive and dynamic to spaceflight, even though it appears cell-type- and context-specific, most notably in terms of the fraction of RNA measured and the collection protocols. These results also provide new evidence of mid-flight spikes in expression of selected genes, which may indicate transient responses to specific insults during spaceflight.

Elongase↗

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↗

Biological Data for Deep Space Mission Support

Increased biomedical risks and challenges associated with deep space missions (cis-Lunar, Mars transit, Mars surface) require new knowledge discovery and development of novel ecosystem and biomedical support capabilities. This paradigm shift supporting distant and long-duration missions requires biological data to be findable, accessible, interoperable, reusable (FAIR), and maximally open-access (i.e., there is a data governance continuum from closed to mediated to embargoed to open). The NASA “Open Science Data Repositories” (OSDR) aims to meet scientific, technical, and operational spaceflight needs, and offers the ability to upload, download, search, share, analyze, and visualize data across physiological, behavioral, ‘omics, and environmental monitoring telemetry datasets. OSDR includes NASA GeneLab, NASA Ames Life Sciences Data Archive (ALSDA), and NASA Biological Institutional Scientific Collection (NBISC). In the past year, ALSDA has undergone a transformation in its data collection, curation, and architecture methods. Standardizing non-genomic (phenotypic) datasets was, and will continue to be, a challenge because of their diverse nature (e.g., molecular, cellular, tissue, whole organism, behavior; micro-computed tomography, intraocular pressure, fluorescence microscopy, western blot, ultrasonography; tabular, images, video). This year ALSDA, alongside GeneLab, introduced the Biological Data Management Environment (BDME) with the purpose to accept submission of data from space relevant experiments including spaceflight, radiation, simulated gravity, gravitropism, isolation and confinement, hostile closed environments and/or distance from Earth. In addition to bringing together omics, phenotypic, physiological, bioimaging, and behavioral data into one repository. By integrating with GeneLab a multi-project submission portal aims to reduce the burden on PIs submitting data and enabling the discovery of both omics and phenotypic data. The purpose of ALSDA is to collect, curate, and make all non-human space-relevant biological data maximally findable, accessible, interoperable, and reusable (FAIR). These scope of ALSDA data collected and submitted by PIs include study design metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). In 2021, a community of researchers rallied to form the ALSDA Analysis Working Group (AWG) and provided scientific consensus on dataset sample and assay metadata. The community and excitement around the ALSDA/OSDR system has already led to several data reuse studies, demonstrating value using machine learning (ML), knowledge graphs, and meta-analysis approaches.

space biology↗

Molecular Identification of Microbial Contaminants

Microorganisms can have significant impacts on the success of NASA’s missions, including the integrity of materials, the reliability of scientific results, and maintenance of crew health. Robust cleaning and sterilization protocols are currently in place in NASA facilities, but agency experts agree that microbial contamination is unavoidable and its impact on NASA’s missions and science must be minimized. Therefore, it is critical to understand: 1) what specific microorganisms are present, 2) how they may impact scientific objectives, and 3) how to select appropriate mitigation strategies. The Marshall Space Flight Center (MSFC) Planetary Protection (PP) microbiology lab historically relied solely upon enumeration of culturable microbial contamination associated with spacecraft materials or cleanrooms. However, this process is time consuming, many microbes cannot be cultured, and very few can be identified with any fidelity using NASA standard microbiological methods. The work described in this white paper includes the establishment of molecular identification capabilities at MSFC, including DNA isolation, amplification, purification, and Sanger sequencing. This capability will not only improve planetary protection efforts at MSFC (i.e. by identifying contaminating microorganisms in cleanrooms or on spacecraft) but also offers a service center-wide for the identification of contaminants that arise in other projects, processing locations, or during set up and roll out of spacecraft. This work also lays the foundation for higher throughput efforts to identify large populations of microbes across the lifetime of a project and serves as the starting point for future work into whole genome sequencing, non-culture based methods, or additional characterization studies. Ultimately, accurate identification informs appropriate mitigation strategies, increasing the chances of success for NASA’s missions and objectives.

C. D. Cassilly↗

Prochlorococcus phage ferredoxin: structural characterization and electron transfer to cyanobacterial sulfite reductases

Marine cyanobacteria are infected by phages whose genomes encode ferredoxin (Fd) electron carriers. These Fds are thought to redirect the energy harvested from light to phage-encoded oxidoreductases that enhance viral fitness, but it is unclear how the biophysical properties and partner specificities of phage Fds relate to those of photosynthetic organisms. Here, results of a bioinformatics analysis using a sequence similarity network revealed that phage Fds are most closely related to cyanobacterial Fds that transfer electrons from photosystems to oxidoreductases involved in nutrient assimilation. Structural analysis of myovirus P-SSM2 Fd (pssm2-Fd), which infects the cyanobacterium Prochlorococcus marinus, revealed high levels of similarity to cyanobacterial Fds (root mean square deviations of ≤0.5 Å). Additionally, pssm2-Fd exhibited a low midpoint reduction potential (–336 mV versus a standard hydrogen electrode), similar to other photosynthetic Fds, although it had lower thermostability (Tm = 28 °C) than did many other Fds. When expressed in an Escherichia coli strain deficient in sulfite assimilation, pssm2-Fd complemented bacterial growth when coexpressed with a P. marinus sulfite reductase, revealing that pssm2-Fd can transfer electrons to a host protein involved in nutrient assimilation. The high levels of structural similarity with cyanobacterial Fds and reactivity with a host sulfite reductase suggest that phage Fds evolved to transfer electrons to cyanobacterially encoded oxidoreductases.

cyanobacteria↗

Space Algae-2: Preflight Testing for A Long-Duration, Multi-Omics Analysis of Arthrospira Platensis

The cyanobacteria Arthrospira platensis NIES-39, commonly known as spirulina, could provide a fresh supply of nutrients for crew on long-duration spaceflight missions. Spirulina is a readily digestible food that is high in protein with all essential amino acids as well as significant levels of B vitamins, antioxidants, and anti-inflammatory metabolites. Spaceflight has multiple abiotic stressors such as increased ionizing radiation and microgravity, which causes a lack of convective mixing. These environmental conditions may impact productivity, nutritional composition, and in long-duration propagation, spaceflight stress may impact the genetic stability of spirulina cultures. We are developing an International Space Station experiment to continuously culture A. platensis for six months. Multi-omics profiling will be used to monitor for changes in the genome, transcriptome, proteome, and metabolome to determine if A. platensis is a suitable nutritional supplement on long-duration missions. During preflight testing we developed a protocol for inoculated liquid cultures to survive a 10-week storage period prior to photo-incubation. The bioreactor bag, temperature, and lighting conditions that support a 14-day growth cycle between passages were also determined. Media testing identified minimal salts supporting robust growth that can be stored in liquid or dry form. A simple filtration method was developed to dewater cultures and harvest biomass for frozen sample return. We optimized a cryopreservation method to enable return of live cells for isolation of individual A. platensis clones. The concept of operations for Space Algae-2 developed from these test results as well as progress on multi-omics analysis methods will be presented.

Algae↗

Elevating the Quality of Space Omics Sequencing Data: Innovations and Methodologies from NASA GeneLab Sample Processing Laboratory

NASA’s GeneLab, part of the NASA Open Science Data Repository, is a space-related database that hosts a diverse range of transcriptomics, proteomics, epigenomics and genomics data. The NASA GeneLab Sample Processing Laboratory (SPL) generates omics data from biological experiments conducted aboard the International Space Station, Space Shuttle and space related ground experiments, this omics data then hosted on the GeneLab repository. Samples generated such experiments pose numerous technical challenges such as small experimental sample size, variance in dissection times, limited tissue preservation methods, prolonged storage time, and more. GeneLab SPL team had developed specialized expertise in nucleic acid extraction, library preparation and sequencing of such biological samples via extensive training and years of experience. In order to ensure data accuracy and consistency across experiments, SPL has developed standardized protocols for each species and tissue type. These protocols in conjunction with quality control metrics and data standards are crucial in generating of high-quality data. SPL protocols and standards have been developed in collaboration with the scientific community and had been made publicly available on the GeneLab portal, guaranteeing comparability of datasets across spaceflight experiments. To ensure reliability of data generation, SPL leverages cutting-edge innovations in laboratory automation for sample processing. By leveraging these state-of-the-art platforms, SPL achieves high levels of data reproducibility while significantly minimizing sources of bias and variability, especially across experiments with large numbers of samples. Over the past few years, the space biology investigator community has accessed SPL-generated data from the Open Science Data Repository for a myriad of data re-analysis and re-use studies. We observe a trend that in-house SPL-generated data consistently outperforms outsourced sequencing data in terms of technical standards, quality control metrics, timeliness of data delivery, and sequencing and reagent efficiency. Superior data generation has and will continue to enable discoveries in disease, diagnostic tools, and the biological effects of long duration spaceflight.

GeneLab↗

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗

ICME for NASA Aerospace Applications: Batteries for Electric Aviation

NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.

John Lawson↗

HRP Data Management Plan

The purpose of Human Research Program Data Management Plan (DMP) is to define the processes and activities required for the overall management of the research data collected and managed by HRP throughout their life cycle. New updates to the Data Management Plan in 2023 include 1. CAPABILITIES AND SERVICES Data Repositories. Principal Investigators (PIs) funded by HRP may be asked to submit data to one of several NASA data repositories. HRP archives data in the NASA Life Sciences Portal (NLSP) that it considers to be unique and high value. This includes data from human subjects in space flight (ISS and commercial flights) and ground analogs to spaceflight; spaceflight tech demos involving humans; human omics data including the microbiome; parabolic flight studies; and the NASA Space Radiation Laboratory (NSRL). The Open Science Data Repository (OSDR) includes The Ames Life Sciences Data Archive (ALSDA), used to archive non-human biological data (e.g., animal) generated by the Human Research program, and GeneLab, available to HRP PIs to archive non-human omics data. Catalog for search and retrieval. A catalog of non-human HRP life science experiments, with all associated descriptions (mission, payload, hardware, and personnel related information), and biospecimens is provided on the NLSP public web site for search and retrieval. 2. IRB ROLE IN RETURN OF INDIVIDUAL RESEARCH RESULTS The NASA IRB manages the process for incidental findings and for returning results to subjects for studies for which NASA IRB is the IRB of record. Omics data, especially genomics data, may generate information significant to the health of or risk to a research subject. These data potentially hold the keys to understand lifetime risks of chronic diseases, such as cancer, as well as risks associated with exposures common in space flight. 3. UPDATE OF TERMS – IDENTIFIABLE AND ATTRIBUTABLE DATA HRP now follows Federal and NASA policy by using “identifiable” instead of “attributable” for Personally Identifiable Information (PII). 4. POLICY ABOUT INTERNAL NON-RESEARCH USE OF DATA The HRP Chief Scientist grants access to data from HRP-funded research for non-research internal use that includes program management, customer facilitation, strategic planning, and risk research planning. Typical HRP personnel granted access to HRP research data for internal use include the Element Scientist, Subject Matter Experts (SME), and Data/bioinformatics Scientists. If data accessed for Internal Use is provided to an intramural or extramural scientist for hypothesis driven research, all Federal and NASA regulations (e.g., IRB review) regarding human subject research apply.

Data Management Plan↗

Microbial Adaptation to Spaceflight Is Correlated With Bacteriophage-Encoded Functions

Evidence from the International Space Station suggests microbial populations are rapidly adapting to the spacecraft environment; however, the mechanism of this adaptation is not understood. Bacteriophages are prolific mediators of bacterial adaptation on Earth. Here we survey 245 genomes sequenced from bacterial strains isolated on the International Space Station for dormant (lysogenic) bacteriophages. Our analysis indicates phage-associated genes are significantly different between spaceflight strains and their terrestrial counterparts. Additionally, we identify 283 complete prophages, those that could initiate bacterial lysis and infect additional hosts, of which 21% are novel. These prophage regions encode functions that correlate with increased persistence in extreme environments, such as spaceflight, to include antimicrobial resistance and virulence, DNA damage repair, and dormancy. Our results correlate microbial adaptation in spaceflight to bacteriophage-encoded functions that may impact human health in spaceflight.

Space Biology↗

Space Algae-2: Preflight Testing for A Long-Duration, Multi-Omics Analysis of Arthrospira Platensis

The cyanobacteria Arthrospira platensis NIES-39, commonly known as spirulina, could provide a fresh supply of nutrients for crew on long-duration spaceflight missions. Spirulina is a readily digestible food that is high in protein with all essential amino acids as well as significant levels of B vitamins, antioxidants, and anti-inflammatory metabolites. Spaceflight has multiple abiotic stressors such as increased ionizing radiation and microgravity, which causes a lack of convective mixing. These environmental conditions may impact productivity, nutritional composition, and in long-duration propagation, spaceflight stress may impact the genetic stability of spirulina cultures. We are developing an International Space Station experiment to continuously culture A. platensis for six months. Multi-omics profiling will be used to monitor for changes in the genome, transcriptome, proteome, and metabolome to determine if A. platensis is a suitable nutritional supplement on long-duration missions. During preflight testing we developed a protocol for inoculated liquid cultures to survive a 10-week storage period prior to photo-incubation. The bioreactor bag, temperature, and lighting conditions that support a 14-day growth cycle between passages were also determined. Media testing identified minimal salts supporting robust growth that can be stored in liquid or dry form. A simple filtration method was developed to dewater cultures and harvest biomass for frozen sample return. We optimized a cryopreservation method to enable return of live cells for isolation of individual A. platensis clones. The concept of operations for Space Algae-2 developed from these test results as well as progress on multi-omics analysis methods will be presented.

Algae↗