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At least 253 records · Page 14

Simulated Weightlessness Alters Cardiomyocyte Structure and Transcriptional Regulation of Mediators Related to Immunity and Cardiovascular Disease

Spaceflight and the ensuing fluid shifts, together with an overall reduction in physical activity, lead to acute and latent effects on the cardiovascular system. This current study makes use of the rodent hindlimb unloading (HU) model to determine how factors such as sex, age, and duration of exposure impact cardiac responses to weightlessness. We hypothesize that extended exposure to simulated weightlessness and the ensuing recovery alters cardiac structure and expression of select genes, including those involved in redox signaling which together, negatively impact long-term cardiac tissue health. To begin to test this hypothesis, male and female rats underwent HU at various durations up to 90 days, with a subset reambulated after 90 days of HU. Physiological stress or contractility changes lead to alterations in ventricular cardiomyocyte size and ventricular wall thickness to adapt to greater functional demand and mitigate mechanical stress to ventricular tissue; under certain conditions, these changes also may mark progression to cardiac failure. Hence, left ventricular cardiomyocyte size (cardiomyocyte cross sectional area, CSA) was quantified to determine if HU leads to structural adaptation responses in cardiac tissue and if age and sex had any impact on this outcome. Cardiomyocyte CSA of older males (9 months) were altered by HU in a time-dependent manner, where HU led to decreases in CSA at 14 days and increases at 90 days. In contrast, younger males (3 months) did not show any changes at day 14 of HU. CSA of females (3 months) was increased in response to short-term HU (14 days) suggesting sex-dependence of structural changes. In older HU males, cardiomyocyte CSA was comparable to controls after 90 days of re-ambulation. Levels of the DNA oxidative damage marker, 8-hydroxydeoxyguanosine (8-OHdG) were greater in left ventricular tissue of females that underwent HU compared to sex-matched controls, while there were no such differences in older or younger males. To gain insight into the signals that drive cardiac adaptations to HU, global transcriptomic analysis (RNAseq) was performed on left ventricular tissue of older males that underwent 14 days of HU. Short-term simulated weightlessness led to differential expression of genes involved in immune and pro-inflammatory signaling. A subset of these genes play a role in autoimmune and cardiovascular disease and are targets of current drugs used to treat bradycardia, hypertension, atherosclerosis and rheumatoid arthritis, amongst others. Oxidative damage/redox signaling pathways were not enriched at the timepoint tested in older males. Since young females displayed greater oxidative damage to DNA, activation of oxidative stress responses at earlier or later time points cannot be ruled out. In summary, simulated weightlessness in adult rats caused changes in cardiomyocyte structure in a sex and age-dependent manner, and the transcriptional regulation of key mediators of immunity and cardiovascular disease, meriting further study to define cardiac risks for interplanetary travel of human crew. Our findings also confirm the value of the rat HU model for cardiac health and countermeasure research.

Tahimic, Candice↗

Methylation Pattern Detection in the Genome of Bacillus Pumilus Strain SAFR-032

Bacillus pumilus SAFR-032, an endospore-forming bacterial strain that was isolated from a spacecraft assembly facility (SAFR), was investigated to determine its methylation pattern (methylome) across the genome in comparison to the previously sequenced reference genome. In addition, a version of SAFR-032 that was flown as spores for 18 months on the International Space Station (ISS) was also investigated for possible genomic changes due to long-duration ISS-flight and to determine if methylation patterns may have changed. Both the genomics and methylomics were conducted using a Nanopore MinION sequencing device. In addition to the omics investigation, the two SAFR-032 strains, ISS flown and non-ISS flown, were compared phenotypically in chamber experiments testing individual environmental insults: ionizing radiation, UV exposure, and cold desiccation (i.e. freeze drying). Results from this study inform on Planetary Protection concerns and will reveal potential DNA damage associated with long-term spaceflight and how such damage may influence survivors after being transported to an extraterrestrial environment, such as Mars.

Serda, Bianca M.↗

Gene and MicroRNA Expression Profile Changes in ISS Crewmembers’ Blood Samples

In space, living organisms are exposed to multiple stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. This study is part of the Functional Immune Project, intended to determine alterations in crewmember immunobiology before, during, and after spaceflight. It emphasizes the study of DNA damage in the ISS crewmembers’ peripheral blood mononuclear cells (PBMCs), expression patterns of damage-response and inflammatory process genes, and changes in latent virus reactivation biomarkers.

Moreno-Villanueva, Maria↗

BioSentinel ISS Control Experiment Investigation Summary Form

The main science objective of BioSentinel is to develop biosensors to study the effects of the space radiation environment on biological organisms. Given its similarities to human cells, we decided to use the budding yeast Saccharomyces cerevisiae. Yeast cells share homology to human cells, particularly in the response to DNA damage caused by ionizing radiation. Most importantly, yeast cells can be desiccated and survive in that form for long periods of time. Thus, budding yeast is the ideal model organism for long-term experiments in preparation for future manned missions to deep space. In addition to the ISS mission, our biosensors will fly in a nanosatellite designed for deep space, which is manifested to fly as a secondary payload onboard NASA’s Artemis-1 rocket.

BioSentinel↗

Developing Technologies for Biological Experiments in Deep Space

NASA Ames Research Center is the leader in developing autonomous nanosatellites or CubeSats to address strategic knowledge gaps about the effects of space travel on biological organisms, including GeneSat, PharmaSat, and EcAMSat. Now that NASA has set its sights on human exploration in deep space, such missions require significant technological and biomedical countermeasures to protect astronauts from chronic radiation exposure. CubeSats can inform these countermeasures by querying relevant space environments with model organisms and/or biosensors. BioSentinel will be the first interplanetary CubeSat to study the biological response to space radiation outside low Earth orbit in almost 50 years. BioSentinel is an autonomous platform able to support biology and to investigate the effects of space radiation on a model organism in interplanetary deep space. It will fly onboard Artemis-1, from which it will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel, a 6U CubeSat (1U = 10-cm cube), will measure the DNA damage response to ambient space radiation in a model organism, which will be compared to information provided by an onboard radiation spectrometer and to data obtained on the ISS and on Earth. Even though the primary objective of the mission is to develop an autonomous spacecraft capable of conducting biological experiments in deep space, the 4U BioSensor science payload contained within the free-flyer is an adaptable instrument that can perform bio measurements with different microorganisms and in multiple space environments, including the ISS, lunar gateway, and on the surface of the Moon. Thus, nanosatellites like BioSentinel can be used to study the effects of both reduced gravity and space radiation and can house different organisms to answer specific science questions. In addition to their flexibility, nanosatellites also provide a low-cost alternative to more complex and larger missions, and require minimal crew support, if any

biosenses↗

Developing Technologies for Biological Experiments in Deep Space

NASA Ames Research Center is the leader in developing autonomous nanosatellites or CubeSats to address strategic knowledge gaps about the effects of space travel on biological organisms, including GeneSat, PharmaSat, and EcAMSat. Now that NASA has set its sights on human exploration in deep space, such missions require significant technological and biomedical countermeasures to protect astronauts from chronic radiation exposure. CubeSats can inform these countermeasures by querying relevant space environments with model organisms and/or biosensors. BioSentinel will be the first interplanetary CubeSat to study the biological response to space radiation outside low Earth orbit in almost 50 years. BioSentinel is an autonomous platform able to support biology and to investigate the effects of space radiation on a model organism in interplanetary deep space. It will fly onboard Artemis-1, from which it will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel, a 6U CubeSat (1U = 10-cm cube), will measure the DNA damage response to ambient space radiation in a model organism, which will be compared to information provided by an onboard radiation spectrometer and to data obtained on the ISS and on Earth. Even though the primary objective of the mission is to develop an autonomous spacecraft capable of conducting biological experiments in deep space, the 4U BioSensor science payload contained within the free-flyer is an adaptable instrument that can perform bio measurements with different microorganisms and in multiple space environments, including the ISS, lunar gateway, and on the surface of the Moon. Thus, nanosatellites like BioSentinel can be used to study the effects of both reduced gravity and space radiation and can house different organisms to answer specific science questions. In addition to their flexibility, nanosatellites also provide a low-cost alternative to more complex and larger missions, and require minimal crew support, if any.

biosenses↗

BioSentinel - ISS mission

BioSentinel will be the first interplanetary CubeSat to study the biological response to space radiation outside low Earth orbit in almost 50 years. BioSentinel is an autonomous platform able to support biology and to investigate the effects of space radiation on a model organism in interplanetary deep space. It will fly onboard Artemis-1, from which it will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel, a 6U CubeSat (1U = 10-cm cube), will measure the DNA damage response to ambient space radiation in a model organism, which will be compared to information provided by an onboard radiation spectrometer and to data obtained on the ISS and on Earth. Even though the primary objective of the mission is to develop an autonomous spacecraft capable of conducting biological experiments in deep space, the 4U BioSensor science payload contained within the free-flyer is an adaptable instrument that can perform bio measurements with different microorganisms and in multiple space environments, including the ISS. Thus, nanosatellites like BioSentinel can be used to study the effects of both reduced gravity and space radiation and can house different organisms to answer specific science questions. In addition to their flexibility, nanosatellites also provide a low-cost alternative to more complex and larger missions, and require minimal crew support, if any

space biosensors↗

Lunar BioSensor: An Autonomous Instrument to Study the Effects of the Lunar Environment on Biological Organisms

One of the major challenges to long-duration space travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Nonetheless, due to the near impossibility of simulating prolonged exposure to these combined effects in terrestrial facilities, actual missions are needed to characterize the radiobiological hazards of this environment. NASA Ames has been the leader in developing autonomous bio nanosatellites to address strategic knowledge gaps about the effects of space travel on biological organisms, including GeneSat, PharmaSat, EcAMSat, and BioSentinel. BioSentinel will be the first interplanetary bio nanosatellite or CubeSat to study the biological response to space radiation outside Low Earth Orbit (LEO). BioSentinel is an autonomous platform able to support biology and to investigate the effects of space radiation on a model organism in interplanetary deep space. It will fly onboard NASA’s Artemis-1, from which it will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. The BioSentinel nanosatellite, a 6U deep space CubeSat (1U = 10-cm cube), will measure the DNA damage and response to ambient space radiation in a model biological organism, the budding yeast S. cerevisiae, which will be compared to information provided by an onboard physical radiation sensor and to data obtained in LEO (on the ISS) and on Earth. Even though the primary objective of the mission is to develop an autonomous spacecraft capable of conducting biological experiments in deep space, the 4U BioSensor science payload contained within the 6U free-flyer is an adaptable instrument platform that can perform biological measurements with different microorganisms and in multiple space environments, including the ISS, lunar gateway, and on the surface of the Moon. The proposed 4U instrument will leverage the payload design of the 6U free-flyer, utilizing the lunar lander or vehicle for power and data relay. Thus, nanosatellites like BioSentinel (and Lunar BioSensor) can be used to study the effects of both reduced gravity and space radiation and can house different bio organisms to answer specific science questions. In addition to their flexibility, nanosatellites also provide a low-cost alternative to more complex and larger missions, and require minimal crew support, if any.

space biosensors↗

Adaptation to environmental extremes structures functional traits in biological soil crust and hypolithic microbial communities

Biological soil crusts (biocrusts) are widespread in drylands and deserts. At the microhabitat scale, they also host hypolithic communities that live under semi-translucent stones. Both environmental niches experience exposure to extreme conditions such as high UV radiation, desiccation, temperature fluctuations, and resource limitation. However, hypolithic communities are somewhat protected from extremes relative to biocrust communities. Conditions are otherwise similar, so comparing them can answer outstanding questions regarding adaptations to environmental extremes. Using metagenomic sequencing, we assessed the functional potential of dryland soil communities and identified the functional underpinnings of ecological niche differentiation in biocrusts versus hypoliths. We also determined the effect of the anchoring photoautotroph (moss or cyanobacteria). Genes and pathways differing in abundance between biocrusts and hypoliths indicate that biocrust communities adapt to the higher levels of UV radiation, desiccation, and temperature extremes through an increased ability to repair damaged DNA, sense and respond to environmental stimuli, and interact with other community members and the environment. Intracellular competition appears to be crucial to both communities, with biocrust communities waging war using the Type VI Secretion System (T6SS) and hypoliths favoring diversity of antibiotics. The dominant primary producer had a reduced effect on community functional potential compared with niche, but an abundance of genes related to monosaccharide, amino acid, and osmoprotectant uptake in moss-dominated communities indicates reliance on resources provided to heterotrophs by mosses. Our findings indicate that functional traits in dryland communities are driven by adaptations to extremes and we identify strategies that likely enable survival in dryland ecosystems.

Biological soil crusts↗

Differential Responses to Mechanostimulation in Embryonic Stem Cells Versus the Embryoid Body Model of Development Assessed at Single Cell RNA-Seq Resolution

Mechanicalforces generated by gravity have shaped life on Earth and impact gene expression and morphogenesis during early development. In contrast disuse canreduce normal mechanical loading, resulting in altered cell and tissue function. Although loading in adult mammals is known to promote increased cell proliferation and differentiation, little is known about how cells respondto this stimulusduring early development. In this study we sought to understand, with single cell RNA-sequencing resolution, how a 60-minute pulse of 50xg hypergravity-generated 5kPa hydrostatic pressure, influences transcriptomic regulation of developmental processes in the Embryoid Body (EB) model. Our study included both day-9 EBs and progenitor mouse embryonic stem cells (ESCs) with or without the hydrostatic pressurepulse. Single cell tSNE mapping shows limited transcriptome shifts in response to thispulse in either ESCs or EBs; this pulse,however, induces greater positional shifts in EB mapping compared to ESCs, indicating the influence of mechanotransduction is more pronounced in later states of cell commitment within the developmental program.We assessed ESCs and EBs for differentially expressed (DE) genes with hydrostatic pressurepulse and found approximately 1/3 DE genes were shared. However, gene ontology (GO) pathway analysis show that EBs have choreographed responses associated with upregulation ofpathways formulticellular development, mechanical signal transduction, and DNA damage repair. Cluster transcriptome analysis of the EBs showsmechanostimulationpromotes maintenance of transitory cell phenotypes in early development,including EB cluster co-expression of markers for progenitor, post-implant epiblast and primitive endoderm phenotypes versus expression exclusivity in the non-pulsed clusters. Pseudotime analysisidentified three branching cell types susceptible tohydrostatic pressureinduction of cell fate decisions. In summary, this study provides novel evidence that ESC maintenance and EB development can be regulated by mechanostimulation,and that stem cells committed to a differentiation program are more sensitive to force-induced changes to their transcriptome.

Cassandra Juran↗

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS and ISS ground control segments.

BioSentinel↗

Transcriptomic Changes in Seedlings from Seeds Exposed to Simulated Space Radiation

Outside the protection of Earth’s magnetic field, living organisms are constantly exposed to space radiation that consists of energetic protons and other heavier charged particles. With the goal of manned Mars exploration, the production of fresh crop during long duration space missions can be beneficial for meeting astronauts’ nutritional and psychological needs. In our study, we not only evaluated plant/fruit morphometrics and edible fresh mass, but also analyzed transcriptomic changes in seedlings from seeds of three plant species (Arabidopsis, mizuna, and tomato) exposed to simulated Galactic Cosmic Rays(GCR) and solar particle events(SPE). The radiation experiments were performed in the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). 10-day Arabidopsis seedlings were exposed acutely (~240 cGy/hr) to simulated GCR scenarios of combined ions including protons, helium, oxygen, titanium, and/or iron ions at 40 or 80 cGy. Seeds of Arabidopsis, mizuna, and tomato were exposed to 40 or 80 cGy simulated GCR (dry seeds) or SPE (imbibed seeds) at lower dose rates(20-26 cGy/hr). Seedlings from control and irradiated seeds were then collected in RNAlater at similar growth stages with true leaves emerged. Total RNA was isolated and analyzed via Illumina whole transcriptome sequencing technology. Plant species-specific bioinformatics revealed transcriptional biomarkers and signaling pathways induced by simulated space radiation that were found to be dose, dose-rate, and species dependent. DNA damage response, stress signaling, and metabolic pathways are among the most significant changes. These data highlight some critical insights on the mechanisms of how plants respond and adapt to the space radiation environment and provide a molecular basis for crop selection and refinement in deep space exploration.

Anirudha Dixit↗

BioSentinel: NASA’s First Deep Space Biological Mission

Since Apollo 17 in 1972, NASA has sent no humans or other biological organisms outside of Earth’s protective magnetosphere. NASA’s current Artemis program plans to put astronauts back on the Moon and eventually land human missions on Mars. One of the major challenges to long-duration crewed travel and habitation in deep space is an in-depth understanding of the biological effects of space radiation, often convoluted by the impact of reduced gravity. Such missions will require significant countermeasures, likely both technological and biomedical, to protect organisms from chronic radiation exposure. Small satellite missions like CubeSats can inform these countermeasures by investigating model organisms in relevant space environments. The BioSentinel mission is comprised of four segments developed at NASA Ames Research Center: a 6U CubeSat (1U = 10-cm cube), an ISS payload launched in December 2021 and two ground units, one for the mission’s CubeSat and one for the ISS payload. The last three segments have been operational since January 2022 and serve as experimental controls. BioSentinel’s 6U CubeSat is planned to launch as a secondary payload on the Artemis-1 rocket. It will be deployed on a lunar fly-by trajectory and into a heliocentric orbit. BioSentinel will be the first interplanetary satellite to study the biological response to space radiation outside Low Earth Orbit (LEO) in almost 50 years. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles. Once it reaches its orbit, BioSentinel’s CubeSat will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical measurements. This paper describes BioSentinel’s objectives, science, data management, and preliminary results from the ISS segment.

BioSentinel↗

Evolution of Biological Satellites: From Low Earth Orbit to NASA’s BioSentinel Deep Space Mission

NASA has set its sights on human exploration in deep space with the Artemis missions, with an ambitious plan to put astronauts back on the Moon and to eventually land human missions on Mars. Such missions will require significant countermeasures, likely both technological and biomedical, to protect biology from chronic radiation exposure. Small satellites like CubeSats can inform these countermeasures by querying relevant space environments with model organisms over relevant durations. NASA has launched five biological CubeSats into low Earth orbit (LEO) from GeneSat in 2006 to EcAMSat in 2017. Each one of these missions increased our understanding of the effects of spaceflight, while refining technologies and imparting valuable lessons to the next generation of CubeSats. The Artemis I rocket will carry ten CubeSats, each of them with its own objective. One in particular, BioSentinel, will conduct the first study of the biological response to interplanetary space radiation beyond LEO since Apollo 17. Once it reaches its heliocentric orbit – after a short lunar fly-by – BioSentinel will measure the DNA damage response to ambient radiation in a model organism, the budding yeast Saccharomyces cerevisiae, which will be compared to information provided by an onboard radiation sensor and to data obtained in LEO (on ISS) and on Earth. Once in interplanetary space, fluidic cards containing desiccated yeast cells will be activated by growth medium addition at different time points throughout the mission. Growth and metabolic activity will be tracked continuously via optical density. BioSentinel is a complete, autonomous spacecraft capable of conducting experiments in deep space. Its 4U BioSensor payload is a fully automated and adaptable platform that can perform biological measurements with a range of microorganisms in multiple space environments, including the ISS, free flyers, and other platforms like the Lunar Gateway and lander vehicles.

Sergio R Santa Maria↗

Benchmark Models for Classification of Radiation Type Induced in Immune Cells

NASA Biological and Physical Sciences and the Science Mission Directorate have published a benchmark dataset of mouse immune cells subjected to radiation-induced DNA damage. The dataset comprises ML-ready microscopic imagery of said cells, including labels indicating radiation type and dose. The machine learning team at NASA Interagency Implementation and Advanced Concept Team (IMPACT) created multiple benchmark models. Initially, we conducted a preliminary analysis using thresholding. The algorithm used thresholds on average brightness of the available images to classify them into their respective radiation type. We also tested machine learning approaches. Convolutional Neural Networks (CNN) emerged as the best-performing model. This poster presents the benchmark scores obtained by the models.

Vishal Perekadan↗

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗

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↗

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↗