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Brain probes, multichannel telemetry devices, and telemetric brain temperature sensors for space biology studies
Transcriptomics holds significant value in elucidating the relationship between gene expression, experimental factors, biological factors, and various types of omics data. Enhancing our understanding of these connections is paramount for foundational biology, which plays a pivotal role in devising solutions for challenges pertinent to both space travel and terrestrial life. The NASA GeneLab project, part of the Open Science Data Repository (OSDR.nasa.gov), seeks to accelerate space biology research through cataloging and democratizing ‘omics data, including transcriptomics. Since raw omics data are largely inaccessible to non-bioinformaticians, GeneLab works with the scientific community via the Open Science Analysis Working Groups (AWGs) to develop standard processing pipelines to generate and publish processed data. Unlike raw data, processed data have greater immediate value to diverse users with varying technical backgrounds and computational capabilities. Standardizing processing workflows is essential to match the pace of raw data generation, ensure reproducibility, and enable standardized processed data for comparison across datasets. As of June 2023, transcriptomics studies comprise over half of GeneLab datasets hosted on the OSDR, including data from bulk RNA-seq and Affymetrix or Agilent 1-Channel DNA microarray assays. In collaboration with the AWGs, GeneLab developed consensus processing pipelines for these transcriptomics data types that includes quality control, background correction (microarray only), data normalization and quantification, culminating in the detection and annotation of differentially expressed genes. The work presented here describes Nextflow implementations of GeneLab’s consensus transcriptomics pipelines that automates and accelerates processing of these datasets. In addition to the core data processing, these workflows also include raw data staging and a robust verification and validation program to identify errors in real-time, stop additional downstream computation, and preserve computational resources. These workflows are used to generate GeneLab processed data hosted on the OSDR, and are publicly available as open source software for others to use at: https://github.com/nasa/GeneLab_Data_Processing.
In this interdisciplinary lecture, we will delve into the fascinating world of Space Biology and the realm of Open Science at NASA. Join us as we explore the profound insights gained from the groundbreaking twin study, which was published several years ago and continues to shape our understanding of spaceflight's impact on human health. We will highlight the study's key findings and contextualize them alongside more recent research endeavors, including the remarkable Inspiration 4 mission and several comprehensive meta-analysis publications enabled by the NASA GeneLab Omics database and the Ames Life Science Data Archive for physiological and phenotypic data.
The utility of the nematode Caenorhabditis elegans in studies spanning aspects of development, aging, and radiobiology is reviewed. These topics are interrelated via cellular and DNA repair processes especially in the context of oxidative stress and free-radical metabolism. The relevance of these research topics to problems in space biology is discussed and properties of the space environment are outlined. Exposure to the space-flight environment can induce rapid changes in living systems that are similar to changes occurring during aging; manipulation of these environmental parameters may represent an experimental strategy for studies of development and senescence. The current and future opportunities for such space-flight experimentation are presented.
The differences in rack requirements for Spacelab, the Shuttle Orbiter, and the United States (U.S.) laboratory module, European Space Agency (ESA) Columbus module, and the Japanese Experiment Module (JEM) of Space Station Freedom are identified. The feasibility of designing standardized mechanical, structural, electrical, data, video, thermal, and fluid interfaces to allow space flight hardware designed for use in the U.S. laboratory module to be used in other locations is assessed.
A guideline is provided for developing NASA's long-term mission plans and a rational, coherent research program. Ten topical areas for research are addressed: developmental biology, gravitropism in plants, sensorimotor integration, bone and mineral metabolism, cardiovascular/pulmonary function, muscle remodeling, nutrition, human reproduction, space anemia, and human behavior. Scientific goals, objectives, and required measurements and facilities for each of the major areas of space biology and medicine are identified and described along with primary goals and objectives for each of these disciplines. Proposals are made concerning the use of scientific panels to oversee the implementation of the strategy, life sciences' need for continuous access to spaceflight opportunities, the advantages of a focused mission strategy, certain design features that will enhance spaceflight experimentation, and general facilities. Other topics that are considered include mission planning, crew selection and training, and interagency and international cooperation.
NASA and international partners have conducted experiments in space to understand the biological impacts and address hazards to health. The resulting basic and applied science is imperative to enabling humanity to venture back to the Moon and then to Mars and beyond. Sending organisms into space is a costly endeavor. All biospecimens not required by spaceflight-relevant Principal Investigators are harvested, preserved, and archived in the NASA Biological Institutional Scientific Collection (NBISC) to maximize the scientific return. The NASA Biological and Physical Sciences (BPS) Division has an ‘Open Science’ endeavor which includes NASA Genelab, the Space Biology Program’s Biospecimen Sharing Program, Physical Sciences Informatics, the Ames Life Sciences Data Archive, and NBISC. Its purpose is to integrate extensive data and biospecimen resources from spaceflight and/or ground-based analog experiments. NBISC biospecimens are collected and preserved according to well-established standard operating procedures to maintain scientific quality and are available on-request by the international scientific community. NBISC currently stores over 32,000 biospecimens from Shuttle, International Space Station, and ground-based space analog investigations. Tissue sharing has resulted in at least 33 publications since 2011 and 48 requests since 2016. Many requests for NBISC biospecimen come from first-time investigators who subsequently submit grants as the port-of-entry into the field of space biology. Some NBISC biospecimens have been awarded to NASA Genelab, who then generate various ‘Open Science’ -omics data sets on their platform for bioinformatics. Other NBISC biospecimen awards have led to multiple studies such as fecal microbiome analysis, DNA damage analysis using single-cell DNA sequencing, enzymatic-pathway identification involved in spaceflight muscle atrophy, and characterization of ocular morphological changes. Of note, NBISC has expanded to include a new Space Microbial Culture Collection (SMCC) for the collection, identification, documentation, long-term preservation, and distribution of space-related microbial isolates.
Aerospace biology curriculum for secondary schools including life support, physiological, and psychological aspects of manned space flight, and exobiology
This slide presentation concerns the 5th volume of a joint publication that describes the cooperation between the United States and Russia in research into space biology and medicine. Each of the chapters is briefly summarized.
The White House Office of Science and Technology Policy (OSTP) has declared 2023 to be the Year of Open Science following an initiative to democratize scientific knowledge. Simultaneously, new sensor technologies have broadened the experimental space available to bioastronautics research. With these open-science goals and technological advances in mind, we have designed and constructed a data acquisition platform for high-precision, real-time monitoring of liquid culture systems. The vessel rig is fitted with six Atlas Scientific probes (micro pH, electrical conductivity, dissolved oxygen, oxidation-reduction potential, liquid temperature, air CO2) and a custom optical density probe similar to the one on BioSentinel’s BioSensor payload. A custom dielectric spectroscopy probe is also planned. The structure of the vessel is resin 3-D printed on a hobbyist-level machine, reducing the production cost and iteration time by over 60% each while increasing extensibility. Data acquisition and storage is controlled with a standalone C state machine-based program running on a Raspberry Pi 3 Model B. When not running headless, an additional program automatically generates and updates plots for live data visualization. Validation of the rig as a data collection system was performed with a yeast liquid culture experiment. While the vessel rig is currently used for standalone experiments, it can also be used as the base perception unit in a self-driving laboratory (SDL). SDLs are high-throughput data collection systems that employ automation and artificial intelligence to conduct and manage routine experiments. Here, we envision an SDL driven by several vessel rigs in which an automated script compares key results, informing the design of future experiments. A vessel rig SDL would streamline many operations, including 1) strain selection for the Lunar Explorer Instrument for space biology Applications (LEIA) investigation and 2) the study of bioregenerative life support systems (BLSS). Ultimately, the datasets that can now be acquired will provide crucial information for accelerating bioastronautics application development in the era of commercial space.
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Humans are poised to explore deep space: the realm of space beyond Earth's orbit. NASA will soon send humans back to the Moon with the Artemis program, and is developing programs to support crewed missions to Mars. Human exploration of such new environments demands fundamental research that can provide the knowledge necessary to ensure the safety of explorers and aid in the development of a sustainable presence in space. Accordingly, the Agency's Moon to Mars objectives1 include three goals in the area of Human Biological Sciences (HBS-1, -2, -3), with the aim to "Advance understanding of how biology responds to the environments of the Moon, Mars, and deep space to advance fundamental knowledge, support safe, productive human space missions and reduce risks for future exploration." Advancing this understanding is a task that is both complex-- comprising diverse organisms, processes, and methods-- and difficult-- because the very aspects of deep space that we strive to understand are the aspects that make it hard to conduct research in that environment. This report of the Beyond LEO Instrumentation & Science Series Science Working Group (BLISS-SWG) represents input from a group of scientists from diverse disciplines within the space biology research and engineering community on the nature of the science and technology that can be used to achieve those aims.
The JSC Life Sciences Project Division has been directly supporting NASA Headquarters, Life Sciences Division, in the preparation of data from JSC and ARC to assist in defining the Space Biology Initiative (SBI). GE Government Services and Horizon Aerospace have provided contract support for the development and integration of review data, reports, presentations, and detailed supporting data. An SBI Definition (Non-Advocate) Review at NASA Headquarters, Code B, has been scheduled for the June-July 1989 time period. In a previous NASA Headquarters review, NASA determined that additional supporting data would be beneficial to determine the potential advantages in modifying commercial off-the-shelf (COTS) hardware for some SBI hardware items. In order to meet the demands of program implementation planning with the definition review in late spring of 1989, the definition trade study analysis must be adjusted in scope and schedule to be complete for the SBI Definition (Non-Advocate) Review. The relative costs of modifying existing commercial off-the-shelf (COTS) hardware is compared to fabricating new hardware. An historical basis for new build versus modifying COTS to meet current NMI specifications for manned space flight hardware is surveyed and identified. Selected SBI hardware are identified as potential candidates for off-the-shelf modification and statistical estimates on the relative cost of modifying COTS versus new build are provided.
Preliminary crop testing using Veggie indicates the environmental conditions provided by the ISS are generally suitable for food crop production. When plant samples were returned to Earth for analysis, their levels of nutrients were comparable to Earth-grown ground controls. Veggie-grown produce food safety microbiology analysis indicated that space-grown crops are safe to consume. Produce sanitizing wipes were used on-orbit to further reduce risk of foodborne illness. Validation growth tests indicated abiotic challenges of insufficient or excess fluid delivery, potentially reduced air flow leading to excess water, elevated CO2 leading to physiological responses, and microorganisms that became opportunistic pathogens. As NASA works to develop future space food production, several areas of research to define these systems pull from the Veggie technology validation tests. Research into effective, reusable water delivery and water recovery methods for future food production systems arises from abiotic challenges observed. Additionally, impacts of elevated CO2 and refinement of fertilizer and light recipes for crops needs to be assessed. Biotic pulls include methods or technologies to effectively sanitize produce with few consumables and low inputs; work to understand the phytomicrobiome and potentially use it to protect crops or enhance growth; selection of crops with high harvest index and desirable flavors for supplemental nutrition; crops that provide psychosocial benefits, and custom space crop development. Planning for future food production in a deep space gateway or a deep space transit vehicle requires methods of handling and storing seeds, and ensuring space seeds are free of contaminants and long-lived. Space food production systems may require mechanization and autonomous operation, with preliminary testing initiated to identify operations and capabilities that are candidates for automation. Food production design is also pulling from Veggie logistics lessons, as we learn about growing at different scales and move toward developing systems that require less launch mass. Veggie will be used as a test bed for novel food production technologies. Veggie is a relatively simple precursor food production system but the knowledge gained from space biology validation tests in Veggie will have far reaching repercussions on future exploration food production.
Preliminary crop testing using Veggie indicates the environmental conditions provided by the ISS are generally suitable for food crop production. When plant samples were returned to Earth for analysis, their levels of nutrients were comparable to Earth-grown ground controls. Veggie-grown produce food safety microbiology analysis indicated that space-grown crops are safe to consume. Produce sanitizing wipes were used on-orbit to further reduce risk of foodborne illness. Validation growth tests indicated abiotic challenges of insufficient or excess fluid delivery, potentially reduced air flow leading to excess water, elevated CO2 leading to physiological responses, and microorganisms that became opportunistic pathogens. As NASA works to develop future space food production, several areas of research to define these systems pull from the Veggie technology validation tests. Research into effective, reusable water delivery and water recovery methods for future food production systems arises from abiotic challenges observed. Additionally, impacts of elevated CO2 and refinement of fertilizer and light recipes for crops needs to be assessed. Biotic pulls include methods or technologies to effectively sanitize produce with few consumables and low inputs; work to understand the phytomicrobiome and potentially use it to protect crops or enhance growth; selection of crops with high harvest index and desirable flavors for supplemental nutrition; crops that provide psychosocial benefits, and custom space crop development. Planning for future food production in a deep space gateway or a deep space transit vehicle requires methods of handling and storing seeds, and ensuring space seeds are free of contaminants and long-lived. Space food production systems may require mechanization and autonomous operation, with preliminary testing initiated to identify operations and capabilities that are candidates for automation. Food production design is also pulling from Veggie logistics lessons, as we learn about growing at different scales and move toward developing systems that require less launch mass. Veggie will be used as a test bed for novel food production technologies. Veggie is a relatively simple precursor food production system but the knowledge gained from space biology validation tests in Veggie will have far reaching repercussions on future exploration food production. This work is supported by NASA.
Astronauts are subject to unique stressors during spaceflight, leading to changes in their cellular function. However, neither astronauts nor model organisms respond the same to spaceflight, and research implicates a contribution of omics components in differential responses. Understanding how gene expression affects astronaut health is critical for the success of long-term space missions, prompting interest in developing personalized predictive models leveraging artificial intelligence (AI) and machine learning (ML) techniques. Developing such models requires extensive data, which is challenging to obtain and share. This study explores the use of conditional variational autoencoders (CVAEs) to synthetically generate single-nuclei RNA-seq (snRNA-seq) data. CVAEs build on standard variational autoencoders (VAEs) by conditioning data generation on covariates like sample identity and mission parameters, enhancing the relevance of generated data for specific contexts. For our work, we built two CVAEs with varying degrees of sparsity to optimize both interpretability and generative power. We train and validate models on existing snRNA-seq data collected from the brain tissue of mice subjected to spaceflight conditions and their ground control counterparts. We evaluate model performance using statistical tests and visualizations to compare synthetic data to real data. We aim to demonstrate that these prototype CVAE architectures could be used in future space biology work and that this is a method worth further exploring.
In light of future missions beyond low Earth orbit (LEO) and the potential establishment of bases on the Moon and Mars, the effects of the deep space environment on biology need to be examined in order to develop protective countermeasures. Although many biological experiments have been performed in space since the 1960s, most have occurred in LEO and for only short periods of time. These LEO missions have studied many biological phenomena in a variety of model organisms, and have utilized a broad range of technologies. However, given the constraints of the deep space environment, upcoming deep space biological missions will be largely limited to microbial organisms and plant seeds using miniaturized technologies. Small satellites such as CubeSats are capable of querying relevant space environments using novel, miniaturized instruments and biosensors. CubeSats also provide a low-cost alternative to larger, more complex missions, and require minimal crew support, if any. Several have been deployed in LEO, but the next iterations of biological CubeSats will travel beyond LEO. They will utilize biosensors that can better elucidate the effects of the space environment on biology, allowing humanity to return safely to deep space, venturing farther than ever before.
NASA’s GeneLab project provides researchers open access to space-relevant multi-omics data via the Open Science Data Repository (OSDR) that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct (training students) and indirect (training educators) approaches. The GL4U pilot programs were conducted in June 2021 (direct training) and 2022 (indirect training). During the pilots, students and educators at Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs) participated in a week-long (direct training) or two-week-long (indirect training) bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze space biology RNA sequencing data from OSDR. During the educator pilot, participants received materials, training, and the necessary compute resources to enable them to run the bootcamp at their home institutions, thereby extending the reach of this initiative. In July 2023, GeneLab is partnering with JPL to expand GL4U to include amplicon sequencing (Amp-Seq) analysis training. During the GL4U Amp-Seq bootcamp, student and educator participants will receive training on how to analyze and interpret Amp-Seq data using the NASA GeneLab data processing pipeline. All bootcamp material, including instructions for requesting compute resources, will be made publicly available on GitHub for educators to teach the GL4U content in subsequent semesters. GL4U provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. We present results from pre- and post-training surveys completed by all participants of the Amp-Seq bootcamp.