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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Congruence of Clusters Defined By Whole Genome Sequencing and MALDI-TOF for Bacteria Isolated From Cleanrooms

Introduction: Oligotrophic conditions can render cleanrooms inhospitable to microbes. Despite these constraints, fungi and bacteria are frequently isolated from surfaces in astromaterials cleanrooms at the Johnson Space Center. Bacillus species are of particular concern because endospores belonging to this genus are resilient and can affect astromaterials. Current monitoring programs rely on 16S rRNA sequencing and the VITEK2 Compact system. These methods have limited power to resolve Bacillus species. Matrix-assisted laser desorption - time of flight mass spectrometry (MALDI-TOF MS), provides a rapid, low cost, method of identifying bacterial isolates and has a higher resolution than 16S rRNA sequencing, particularly for Bacillus species; however, few studies have compared this method to the industry gold standard, whole genome sequencing (WGS). Methods: Based on 16S rRNA classification, we selected 14 isolates for analysis with MALDI-TOF and WGS. Mass spectra were generated with MALDI-TOF MS and processed with custom scripts to identify clusters of closely related isolates and calculate a matrix of pairwise cosine similarity scores. Hybrid Illumina and Nanopore sequencing were used to generate draft genomes. Pairwise similarity scores were calculated from these genomes based on the average amino acid identity (AAI) predicted from single copy core genes. Congruence of clustering between these methods, was assessed by calculating adjusted Rand and Wallace coefficients. Results: Clusters of species generated from MALDI-TOF MS showed good agreement of phylotypes generated with WGS. Pairs of strains that were > 94% similar to each other in terms of predicted amino acid sequences consistently showed cosine similarities of mass spectra > 0.65 and, of the 9 clusters identified with WGS, 8 were identical with MALDI-TOF. This corresponds to an adjusted Rand index of 0.95 and a 95% confidence interval of 0.80 – 1.00 for adjusted Wallace coefficients. The only discordance was for a pair of isolates that were classified as Paenibacillus species. This pair showed relatively high similarity (0.84) in terms of MALDI-TOF MS but only 85% similarity in terms of AAI. Conclusion: This study shows that MALDI-TOF and WGS exhibit a similar ability to delineate Bacillus species isolated from cleanrooms and taxonomic units described by these two methods are consistent with one another. Since MALDI-TOF MS is low in cost and high in throughput, this approach appears to be an ideal option for routine microbial monitoring and identifying Bacillus species.

Farnaz Mazhari↗
NASA NTRS2021

Application of Whole Genome Sequencing and MALDI-TOF to the Identifcation of Bacillus Species Isolated from Cleanrooms at NASA Johnson Space Center

Astromaterial cleanrooms at NASA Johnson Space Center are built environments that hold samples, such as lunar rocks, from different space exploration missions. Bacillus sp. are frequently detected in routine microbial monitoring of these facilities. Since this, and related genera, can form endospores that can withstand harsh conditions, they could contaminate astromaterials. This could confound searches for extraterrestrial life. Whole genome sequencing (WGS) is widely used for identifying bacterial strains and tracking their source; however, WGS is expensive and time consuming. Matrix-assisted laser desorption ionization– time of flight mass spectrometry (MALDI-TOF) shows promise as a low-cost, rapid method of identifying strains of bacteria, but few studies have compared this proteomics method to WGS. To evaluate a high throughput method of tracking the source of contamination of this built environment, WGS and MALDI-TOF was conducted on 18 bacterial strains isolated from surfaces in astromaterials cleanrooms. WGS identified 14 Bacillus, 2 Paenibacillus, 1 Solibacillus and 1 Alcaligenes strains. These isolates showed similarity to strains commonly observed in spacecraft assembly cleanrooms at other facilities. Cluster analysis of mass spectra generated by MALDI-TOF grouped strains together that were greater than 94% similar to each other in terms of amino acid sequences of single copy core genes, as assessed by WGS. This suggests that MALDI-TOF and WGS results are consistent with each other and MALDI-TOF can rapidly identify strains of Bacillus sp. isolated from cleanroom environments with a resolution comparable to WGS. Based on phylogenomic analysis, these results also suggest the presence of a cosmopolitan class of Bacillus sp. that are more likely to be found in cleanrooms and similar built environments than in natural systems.

Farnaz Mazhari↗
NASA NTRSDate not supplied

Resolution of Maldi-Tof Compared to Whole Genome Sequencing for Identification of Bacillus Species Isolated From Cleanrooms at Nasa Johnson Space Center

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center maintains cleanrooms to archive extraterrestrial materials returned from space exploration missions. Compared to typical built environments, oligotrophic conditions make these facilities inhospitable to microbes. Despite these controls, bacteria and fungi are regularly cultured from these cleanrooms. In particular, Bacillus sp. are frequently isolated during routine microbial monitoring. Endospores associated with this genus can survive extreme environments, such as cleanrooms. This microbial contamination may affect the integrity of astromaterials.

Microbiology↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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 part due to a culture of open data sharing and reuse. AI/ML methodology is 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 key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Inexperienced researchers can produce models that perform poorly outside of the training dataset. 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 Casaletto↗
NASA NTRS2017

Microbial Characteristics of ISS Environmental Surfaces

The microbiome of environmental surfaces from the International Space Station were characterized in order to examine the relationship to crew and hardware maintenance. The Microbial Observatory (ISS-MO) experiment generated a microbial census of ISS environments using advanced molecular microbial community analyses along with traditional culture-based methods. Since the “omics” methodologies generated an extensive microbial census, significant insights into spaceflight-induced changes in the populations of beneficial and/or potentially harmful microbes were gained. Surface samples were collected from several ISS surface locations from three flight opportunities, and were returned to Earth via the Soyuz TMA-14M or the Space X Dragon capsule. In addition to cultivation methods, viable microbial burden, iTag-based sequencing, and metagenome analyses were carried out. The cultivable microbial bioburden differed by location and sampling event. Exploring the ISS environmental microbiome revealed presence of opportunistic pathogens and antibiotic resistant microbes. Genes involved in ATP binding cassette transporters, two component systems, and beta-lactam resistance were among a diverse set of metabolic and genetic information processing pathways. Whole genome sequencing (WGS) of 50 ISS strains exhibiting resistance to various antibiotics was carried out. The antibiotic resistant genes deduced from the WGS were compared with the resistomes generated directly from the gene pool of the environmental samples. Two unique Aspergillus fumigatus strains isolated from the ISS were characterized and compared to the experimentally established clinical isolates Af293 and CEA10. A virulence assessment in a neutrophil-deficient larval zebrafish model of invasive aspergillosis indicated that both ISSFT-021 and IF1SW-F4 were significantly more lethal compared to Af293 and CEA10. The findings from this Environmental “Omics” project should be exploited to enhance human health and well-being of a closed system. In other words, the ISS-MO research aims to "translate" findings in fundamental research into medical practice (pathogen detection) and meaningful health outcomes (countermeasure development).

Perry, Jay↗
NASA NTRS2023

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↗
NASA NTRSDate not supplied

Cleanroom Microbes Survive Drying, Vacuum, and Proton Irradiation

Introduction : The goal of planetary protection at NASA is to mitigate the risk of contaminating sensitive target bodies with biological life. While many cleaning procedures have been put in place to reduce bioburden on spacecraft, microbes are experts at evolving to survive harsh conditions. Specifically, the dry, low-nutrient environment of a cleanroom (commonly used for assembly of spacecraft) can represent an environment where extremophiles can survive. Methods : Scientists at NASA MSFC wished to gather a snapshot of the microbial population within a variety of cleanrooms on site. A study was undertaken to collect air, surface, and floor samples from clean-rooms and isolate unique morphologies. From this study, 95 isolates were collected and saved in a microbial library. About 86% of these were identified at least to a genus level. Following identification, 24 microbes were selected, based on a literature review, as potential extremophiles. These were grown in liquid cultures, diluted to a set optical density, washed with water, and then applied to a sterilized Kapton coupon. Droplets were allowed to dry overnight in a biosafety cabinet. Coupons were then installed in a pelletron and pumped down to high vacuum (~1E-6 Torr). Samples were then subjected 100 keV protons at a fluence of 2x10 15 p+/cm 2 up to 4x10 15 p+/cm 2 . Following exposure, samples were returned to the microbiology lab where they were pro-cessed by submerging in water, vortexing, and then plating either droplets or spread plates. Recovery data collected was qualitative with a ranking or +, minor, or – for growth. Some selected radiotolerant strains were sequenced using the Illumina sequencing platform. The resulting genomes were annotated with the Rapid Annotations using Subsystems Technology (RAST) server and analyzed for conserved and unique stress response relevant genomic signatures to identify clues related to specific tolerances. Results and Discussion : After five rounds of proton radiation, we narrowed our isolates to five, non-spore forming bacteria that demonstrated survival: Arthrobacter koreensis, Paenarthrobacter nitroguajacolicus, Mycetocola manganoxydans , and an Erwinia sp. Furthermore, we exposed these four microbes to 254 nm wavelength light at an intensity of 80 W/m 2 at a distance of ~18 cm for 10 minutes. Only A. koreensis demonstrated survival following UV exposure. Finally, we performed whole genome sequencing on the four strains to look for genetic markers of stress resistance. When we compared the genomes of the four strains, we found that genes coding for GGDEF and EAL domains with PAS/PAC sensors were only found in A. koreensis . These domains, modulated by PAS/PAC sensors, are hypothesized to facilitate survival under drying, desiccation, and proton irradiation. Drying and Desiccation : PAS domains sense hydration changes and modulate GGDEF and EAL domain activity to adjust c-di-GMP levels, enhancing resistance to desiccation. For instance, in Pseudomonas aeruginosa , the PAS domain of RbdA modulates activity under varying hydration conditions, affecting stress responses [1]. Proton Irradiation : Proton irradiation causes oxidative stress, leading to ROS generation. PAS domains detect this stress and modulate GGDEF and EAL domains to manage oxidative stress responses. In Shewanella , EAL domain proteins modulated by PAS sensors help bacteria adapt to extreme conditions [2]. These genes upregulate other stress response genes, protecting membrane function, protein stability, DNA repair, and antioxidant defenses. The modulation of c-di-GMP by PAS domains is crucial for bacterial adaptation to stress conditions, enabling dynamic physio-logical adjustments [3]. Understanding these mechanisms provides insights into bacterial stress responses and strategies for controlling bacterial growth [4]. Conclusions : These findings indicate that clean-rooms harbor extremophile microbes that may be able to survive conditions in deep space. Furthermore, while we identified certain stress-response genes that may be at least partly responsible for the phenotypes observed in this study, there are likely unidentified genes or characteristics about A. koreensis , and other bacteria, that may allow them to survive in harsh environments. Future studies will focus on identifying these unknown genes and characteristics, further elucidating the mechanisms of extremophile survival and potentially informing the development of new biotechnologies for space exploration and other extreme environments.

Chelsi Cassilly↗
NASA NTRS2017

Identification of Novel Desiccation-Tolerant S. cerevisiae Strains for Deep Space Biosensors

NASA's BioSentinel mission, a secondary payload that will fly on the Space Launch System's first Exploration Mission (EM-1), utilizes the budding yeast S. cerevisiae to study the biological response to the deep space radiation environment. Yeast samples are desiccated prior to launch to suspend growth and metabolism while the spacecraft travels to its target heliocentric orbit beyond Low Earth Orbit. Each sample is then rehydrated at the desired time points to reactivate the cells. A major risk in this mission is the loss of cell viability that occurs in the recovery period following the desiccation and rehydration process. Cell survival is essential for the detection of the biological response to features in the deep space environment, including ionizing radiation. The aim of this study is to mitigate viable cell loss in future biosensors by identifying mutations and genes that confer tolerance to desiccation stress in rad51, a radiation-sensitive yeast strain. We initiated a screen for desiccation-tolerance after rehydrating cells that were desiccated for three years, and selected various clones exhibiting robust growth. To verify retention of radiation sensitivity in the isolated clones - a crucial feature for a successful biosensor - we exposed them to ionizing radiation. Finally, to elucidate the genetic and molecular bases for observed desiccation-tolerance, we will perform whole-genome sequencing of those rad51 clones that exhibit both robust growth and radiation sensitivity following desiccation. The identification and characterization of desiccation-tolerant strains will allow us to engineer a biological model that will be resilient in face of the challenges of the deep space environment, and will thus ensure the experimental success of future biosensor missions.

S. cerevisiae↗
NASA NTRS2017

Biosentinel: Improving Desiccation Tolerance of Yeast Biosensors for Deep-Space Missions

BioSentinel is one of 13 secondary payloads to be deployed on Exploration Mission 1 (EM-1) in 2019. We will use the budding yeast Saccharomyces cerevisiae as a biosensor to determine how deep-space radiation affects living organisms and to potentially quantify radiation levels through radiation damage analysis. Radiation can damage DNA through double strand breaks (DSBs), which can normally be repaired by homologous recombination. Two yeast strains will be air-dried and stored in microfluidic cards within the payload: a wild-type control strain and a radiation sensitive rad51 mutant that is deficient in DSB repairs. Throughout the mission, the microfluidic cards will be rehydrated with growth medium and an indicator dye. Growth rates of each strain will be measured through LED detection of the reduction of the indicator dye, which correlates with DNA repair and the amount of radiation damage accumulated. Results from BioSentinel will be compared to analog experiments on the ISS and on Earth. It is well known that desiccation can damage yeast cells and decrease viability over time. We performed a screen for desiccation-tolerant rad51 strains. We selected 20 re-isolates of rad51 and ran a weekly screen for desiccation-tolerant mutants for five weeks. Our data shows that viability decreases over time, confirming previous research findings. Isolates L2, L5 and L14 indicate desiccation tolerance and are candidates for whole-genome sequencing. More time is needed to determine whether a specific strain is truly desiccation tolerant. Furthermore, we conducted an intracellular trehalose assay to test how intracellular trehalose concentrations affect or protect the mutant strains against desiccation stress. S. cerevisiae cell and reagent concentrations from a previously established intracellular trehalose protocol did not yield significant absorbance measurements, so we tested varying cell and reagent concentrations and determined proper concentrations for successful protocol use.

BioSentinel↗
NASA NTRS2017

Identification of Novel Desiccation-Tolerant S. cerevisiae Strains for Deep Space Biosensors

NASA's BioSentinel mission, a secondary payload that will fly on the Space Launch Systems first Exploration Mission (EM-1), utilizes the budding yeast S. cerevisiae to study the biological response to the deep space radiation environment. Yeast samples are desiccated prior to launch to suspend growth and metabolism while the spacecraft travels to its target heliocentric orbit beyond Low Earth Orbit. Each sample is then rehydrated at the desired time points to reactivate the cells. A major risk in this mission is the loss of cell viability that occurs in the recovery period following the desiccation and rehydration process. Cell survival is essential for the detection of the biological response to features in the deep space environment, including ionizing radiation.The aim of this study is to mitigate viable cell loss in future biosensors by identifying mutations and genes that confer tolerance to desiccation stress in rad51, a radiation-sensitive yeast strain. We initiated a screen for desiccation-tolerance after rehydrating cells that were desiccated for three years, and selected various clones exhibiting robust growth. To verify retention of radiation sensitivity in the isolated clonesa crucial feature for a successful biosensorwe exposed them to ionizing radiation. Finally, to elucidate the genetic and molecular bases for observed desiccation-tolerance, we will perform whole-genome sequencing of those rad51 clones that exhibit both robust growth and radiation sensitivity following desiccation. The identification and characterization of desiccation-tolerant strains will allow us to engineer a biological model that will be resilient in face of the challenges of the deep space environment, and will thus ensure the experimental success of future biosensor missions.

S. cerevisiae↗
NASA NTRS2017

Biosentinel: Improving Desiccation Tolerance of Yeast Biosensors for Deep-Space Missions

BioSentinel is one of 13 secondary payloads to be deployed on Exploration Mission 1 (EM-1) in 2019. We will use the budding yeast Saccharomyces cerevisiae as a biosensor to determine how deep-space radiation affects living organisms and to potentially quantify radiation levels through radiation damage analysis. Radiation can damage DNA through double strand breaks (DSBs), which can normally be repaired by homologous recombination. Two yeast strains will be air-dried and stored in microfluidic cards within the payload: a wild-type control strain and a radiation sensitive rad51 mutant that is deficient in DSB repairs. Throughout the mission, the microfluidic cards will be rehydrated with growth medium and an indicator dye. Growth rates of each strain will be measured through LED detection of the reduction of the indicator dye, which correlates with DNA repair and the amount of radiation damage accumulated. Results from BioSentinel will be compared to analog experiments on the ISS and on Earth. It is well known that desiccation can damage yeast cells and decrease viability over time. We performed a screen for desiccation-tolerant rad51 strains. We selected 20 re-isolates of rad51 and ran a weekly screen for desiccation-tolerant mutants for five weeks. Our data shows that viability decreases over time, confirming previous research findings. Isolates L2, L5 and L14 indicate desiccation tolerance and are candidates for whole-genome sequencing. More time is needed to determine whether a specific strain is truly desiccation tolerant. Furthermore, we conducted an intracellular trehalose assay to test how intracellular trehalose concentrations affect or protect the mutant strains against desiccation stress. S. cerevisiae cell and reagent concentrations from a previously established intracellular trehalose protocol did not yield significant absorbance measurements, so we tested varying cell and reagent concentrations and determined proper concentrations for successful protocol use.

BioSentinel↗
NASA NTRSDate not supplied

Individual Variability and Predictive Biomarkers of Human Sensitivity to Ionizing Radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating personalized health risks from space radiation exposure requires understanding the factors underlying individual radiation sensitivity, which currently remain unknown. We started to address this challenge by identifying the genomic and demographic associations with sensitivity to low and high-LET ionizing radiation in the largest human sample cohort to date and by evaluating baseline DNA damage as a potential predictor of radiation responses. We have collected and irradiated peripheral blood mononuclear cells (PBMCs) from 768 healthy donors of matched ethnicity, 50/50 male/female, 18-70 years old. We have analyzed the responses of 576 donor PBMCs to irradiation with simulated galactic cosmic ray components: 350MeV/n 28Si, 350MeV/n 40Ar and 600MeV/n 56Fe, at 1.1 and 3 particles/100μm2 fluences, as well as 0.1Gy and 1Gy doses of gamma rays, at 4 and 24 hours post irradiation. We quantified post-irradiation DNA repair based on radiation-induced 53BP1+ foci formation, together with oxidative stress and cell death using a flow cytometry-based assay. We also assessed baseline levels of DNA repair in PBMCs at the time of sample collection prior to irradiation experiments. We observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing with LET, though oxidative stress being notably reduced by high-LET irradiation, potentially due to a switch between hydrogen peroxide and oxygen radical-based mechanisms. We also identified a relationship between few DNA repair foci at baseline and increased DNA repair after irradiation, accompanied by an alteration in immunoregulatory cytokine secretion, which might be adapted as biomarkers to predict ionizing radiation sensitivity. Among demographic variables, baseline foci levels were positively associated with age and latent cytomegalovirus infection. Finally, we have performed low-throughput whole genome sequencing of all samples and are currently in process of identifying the genes and pathways associated with low and high-LET ionizing radiation sensitivity in humans.

Space radiation, human spaceflight, DNA damage↗
NASA NTRSDate not supplied

BLOOD-BASED MULTI-SCALE MODEL FOR CANCER RISK FROM GCR IN GENETICALLY DIVERSE POPULATIONS

OBJECTIVES AND METHODS This project addresses the challenge of understanding and predicting individual radiation sensitivity by integrating genetics, demographics and biomarker characteristics across species (mice and humans). We hypothesize that ex vivo DNA repair response to GCR components is a central determinant of cancer risk from space radiation and can serve as a biomarker of radiation risk in combination with genetics. Automated image quantification of 53BP1+ radiation-induced foci (RIF) during the first 4-48 h post-irradiation was performed as a function of dose and LET in non-immortalized primary skin fibroblasts derived from 76 mice across 15 strains (5 inbred reference strains and 10 collaborative-cross strains) exposed to X rays (0.1, 1 and 4 Gy), 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100μm2), as well as in peripheral blood mononuclear cells (PBMCs) from 768 healthy donors (matched ethnicity, 50/50 male/female, 18-70 years old) exposed to gamma rays (0.1 and 1 Gy), 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe (1.1 and 3 particles/100μm2). QUANTIFICATION OF 53BP1+ FOCI IN VITRO AND ASSOCIATIONS TO IN VIVO RADIATION SUSCEPTIBILITY IN 15 MOUSE STRAINS We reported in vitro repair kinetic and repairable fractions of RIF for the 15 mouse strains and introduced a mathematical model for RIF as a function of time, dose and LET. We noted that the metabolic activity of cells modulates the RIF response, and we introduced the open access tool terRIFic (Tool for Enhanced Results of RIF In Cells, https://radbiolab.shinyapps.io/terrific/) to correct for such bias using confluence level. Notably, at 4h post-irradiation, RIF/Gy decreased with dose or LET: as the dose or LET increases, so does the proximity of DNA double-strand-breaks (DSB) and our data suggest that proximal DSBs are brought together inside isolated RIF for repair. The RIF/Gy trend was inverted at 24h, suggesting RIF with high DSB content are more difficult to repair. We showed that in vitro metrics correlate with in vivo measurements in the same 15 mouse strains, such as survival levels of immune cells or spontaneous cancer incidence, suggesting a relationship between the efficiency of DSB repair and cancer risk or radiation toxicity. In addition to the efficiency of repair and persistent RIF, the amount of spontaneous foci before irradiation was also found to be strain dependent. Finally, we performed genome-wide association study in the same 15 mouse strains using all RIF phenotypes measured in vitro, identifying genes of interest and validating RIF as an ideal biomarker for individual radiation sensitivity. BASELINE 53BP1+ FOCI PREDICTS INDIVIDUAL HUMAN RESPONSE TO GCR COMPONENTS Based on the analysis of radiation responses of 576 donor PBMCs (using quantification of 53BP1+ foci, oxidative stress and cell death), we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing with LET, though oxidative stress being notably reduced by high-LET irradiation, potentially due to a switch between hydrogen peroxide and oxygen radical-based mechanisms. We identified a relationship between few spontaneous DNA foci at baseline and increased DNA repair after irradiation, accompanied by an alteration in immunoregulatory cytokine secretion, which might be adapted as biomarkers to predict ionizing radiation sensitivity. Among demographic variables, only latent cytomegalovirus infection and age were predictive of high baseline foci formation. Finally, we have performed low-throughput whole genome sequencing of all samples and are currently in the process of identifying the genes and pathways associated with low and high-LET ionizing radiation sensitivity in humans.

53BP1↗
NASA NTRSDate not supplied

Determining Chlamydomonas reinhardtii resistance to ionizing radiation at a genome-wide scale

Spaceflight is a complex mixture of abiotic stresses that causes a myriad of cellular responses including increased genome-wide mutation load. The impact of spaceflight on mutation load is not well understood for most organisms and is especially critical to characterize for candidate microorganisms that could be part of biological life support systems. Prior research in our laboratory revealed an unexpectedly high level of mutation during spaceflight in the eukaryotic green algae, C. reinhardtii. Based on the spectrum of base changes observed, we concluded that the mutations were generated through a molecular mechanism unique to the spaceflight environment. Spaceflight is a complex set of stresses, and we are using an Earth-based analog to test ionizing radiation as a potential causative variable for the unique mutation spectrum observed in spaceflight. C. reinhardtii was grown exposed to chronic radiation from a Cesium-137 source. Four biological replicate cultures of wild-type cells were grown in gas permeable plastic tissue culture bags in liquid media following the design used on the International Space Station (ISS) during the previous space algae experiment. Radiation levels for this experiment approximate ionizing radiation observed on the moon, in low Earth orbit (LEO), and on Earth. Cells from each replicate were passaged to inoculate the next cycle of growth, then samples were taken from each culture to characterize cell morphology, quantify biomass, and extract DNA. Whole genome sequencing from each culture will be used to identify the frequency and types of mutations in each radiation level. In growth cycles 3 and 4, there was a significant increase in biomass accumulation under lunar radiation level compared to LEO or Earth radiation levels. These results such that ionizing radiation affected growth of C. reinhardtii.

Microbiology↗
NASA NTRSDate not supplied

Genomic and Phenotypic Associations to Predict Human Sensitivity to SpaceRadiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350MeV/n 28Si, 350MeV/n 40Ar and 600MeV/n 56Fe particles, at 1.1 and 3 particles/100 sq.m fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1+ radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radio sensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radio sensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radio sensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS radiation human↗
NASA NTRSDate not supplied

Genomic and Phenotypic Predictors of Human Ex Vivo Sensitivity to Simulated Deep Space Radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating this risk requires understanding the factors underlying individual radiation sensitivity. We started to address this challenge by identifying the genomic and phenotypic associations with sensitivity to low and high-LET ionizing radiation ex vivo in over 750 healthy human donors. We exposed primary human blood mononuclear cells to simulated galactic cosmic ray components: 350 MeV/n 28Si, 350 MeV/n 40Ar and 600 MeV/n 56Fe particles, at 1.1 and 3 particles/100 sq.m fluences, as well as 0.1 Gy and 1 Gy doses of gamma rays, and analyzed the outcomes at 4 and 24 hours post-irradiation. We quantified DNA damage and repair responses based on 53BP1+ radiation-induced foci formation, together with oxidative stress and changes in secreted factors including immune cytokines and exosomes. We also analyzed phenotypic associations with spontaneous DNA repair foci at baseline prior to irradiation. We identified an increase in spontaneous DNA repair associated with age and latent viral infection, and observed that human spontaneous DNA repair foci at baseline can serve as a negative predictor of DNA repair and immunoregulatory cytokine production after irradiation. Furthermore, we observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing by dose and LET, and high-LET particle radiation resulting in more residual DNA damage compared to low-LET particles and gamma rays. We have developed multiple metrics to quantify human radiosensitivity across the spectrum of conditions. Here we present their dependence on radiation quality and phenotypic variables, including an age-dependent decrease in DNA repair after irradiation, and genomic associations with radiosensitivity based on low-coverage whole genome sequencing. We anticipate that our work will pave the way for understanding the spectrum of human radiosensitivity and identifying targets for countermeasure development to reduce DNA and cellular damage and radiation carcinogenesis during deep space exploration.

GWAS↗