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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Metabolic rewiring and biomass redistribution enable optimized mixotrophic growth in Chlamydomonas

Aquatic photosynthetic systems account for approximately one-half of all global carbon assimilation and could be a significant source of renewable fuels and feedstocks. However, rapid growth and biomass production in algae have not always translated into high product yields, partly because central metabolism is context specific, with metabolic fluxes being influenced by nutrient conditions and other environmental factors. In the green microalga Chlamydomonas reinhardtii (Chlamydomonas), mixotrophic cultures (acetate + light) grow far faster than phototrophic (light only) or heterotrophic (acetate + dark) cultures, even though acetate partially suppresses photosynthesis. Here, an isotopic dilution strategy with unlabeled acetate was combined with 13 CO 2 transient labeling to perform isotopically nonstationary metabolic flux analysis (INST-MFA) and to directly compare autotrophic and mixotrophic metabolism in Chlamydomonas supported by data from transcriptomics, proteomics, and metabolomics. INST-MFA indicated that acetate induces a synergistic rewiring of metabolism, conserving carbon by using the glyoxylate cycle and suppressing gluconeogenesis, the latter of which was discordant with omics results and prior models. Additionally, our data provide a plausible rationale for the well-known suppression of photosynthesis by acetate. We propose that reduced total protein content in mixotrophic versus phototrophic cells, much of which is attributed to reduced levels of photosynthetic proteins, decreases the costly metabolic burden of protein synthesis and represents a growth rate optimization strategy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Integrated multi-omic characterizations of the synapse reveal RNA processing factors and ubiquitin ligases associated with neurodevelopmental disorders

The molecular composition of the excitatory synapse is incompletely defined due to its dynamic nature across developmental stages and neuronal populations. To address this gap, we apply proteomic mass spectrometry to characterize the synapse in multiple biological models including the fetal human brain and hiPSC-derived neurons. To prioritize the identified proteins, we develop an orthogonal multi-omic screen of genomic, transcriptomic, interactomic, and structural data. This data-driven framework identifies proteins with key molecular features intrinsic to the synapse, including characteristic patterns of biophysical interactions and cross-tissue expression. The multi-omic analysis captures synaptic proteins across developmental stages and experimental systems, including 493 synaptic candidates supported by proteomics. We further investigate three such proteins that are associated with neurodevelopmental disorders – the CUL3 E3 ubiquitin ligase, the DDX3X and YBX1 nucleic-acid binding proteins – by mapping their networks of physically interacting synapse proteins or transcripts. Our study demonstrates the potential of an integrated multi-omic approach to systematically and more comprehensively resolve the synaptic architecture.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Enabling Biological Discovery Through Biospecimen Sharing: The Nasa Biological Institutional Scientific Collection

Understanding biological impacts from spaceflight hazards and the subsequent development of countermeasures are a high priority to enable humanity to venture back to the Moon, and then to Mars and beyond. Experiments have been conducted with model organisms flown to space and analogous investigations terrestrially, to identify biological mechanistic impacts from spaceflight hazards and to develop mitigation countermeasures, thus contributing towards basic and applied science goals. However, sending organisms into space is a costly endeavor. To maximize scientific return, all biospecimens not required by spaceflight-relevant Principal Investigators are harvested, preserved, and archived in the NASA Biological Institutional Scientific Collection (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 51 requests since 2016. Many requests for NBISC biospecimens come from first-time investigators who subsequently submit grants as their point-of-entry into the field of spaceflight biology and health. The NBISC biorepository is part of the NASA ‘Open Science for Life in Space’ collaborative group of projects, which includes NASA Genelab, the Space Biology Program’s Biospecimen Sharing Program, Physical Sciences Informatics, and the Ames Life Sciences Data Archive. NBISC biospecimens have been awarded to NASA Genelab, who then generated various open access science ‘omics datasets through the GeneLab Sample Processing laboratory, with resulting data widely used for biological study. Other NBISC biospecimen awards have led to studies on 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 is 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.

Biospecimens↗
NASA NTRS2024

Tracking Community Building in Open Science

Open Science is enabled by a vibrant community of researchers who regularly engage with the data, from its production to its organization, curation, archiving, dissemination, analysis, and publication. This presentation will examine community building in open science. The NASA Open Science Data Repository (OSDR) makes data available to the public following the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles. OSDR takes open science further with the OS Analysis Working Groups (AWGs) that facilitate community development and promotion. The primary activity of each AWG is to establish and validate analytical processes to generate higher-order data from data housed in OSDR. There are a number of these groups on various topics, including the Animal AWG, Plant AWG, Microbial AWG, Multi-Omics AWG, AI/ML AWG, and the Ames Life Sciences Data Archive (ALSDA) AWG. The international volunteers participating in these AWGs come from academia, citizen science initiatives, industry, and government. They include researchers, principal investigators, professors, trained hobbyists, and students from various domains and disciplines. Anyone may request to join the AWGs, and membership requests are vetted monthly by the group organizers before granting admission. Core to membership is demonstrated expertise through records of training, integrity, work in the professed domain(s), and good community standing. Regular virtual meetings are held for each AWG, with a varying cadence depending on the group's needs and goals. AWG communities share their expertise in research including cutting edge tools, software, frameworks, data formats, and libraries accelerating research collectively. This collaborative approach helps community members cross technology gaps and identify emerging challenges. These diverse communities encompass a wide range of individuals hailing from various sectors within the Science Mission Directorate and beyond. They serve as a means to promote and enhance transparency, accessibility, and inclusion. An annual AWG Symposium brings contributors together in person. Participation in AWGs can be synchronous or asynchronous, with some groups performing most of their work in off hours. Participants gain valuable skills and connections that allow them to add value to their communities and new organizations that they join, resulting in an expanded return on investment for the space life science community. Open science is increasingly a federal mandate and initiatives like NASA's Transform to Open Science and instruments like the Decadal Survey of Biological and Physical Sciences in Space demonstrate the need to carefully consider best practices in this domain. Here, we present greater detail about the makeup and participation metrics of the various AWGs affiliated with OSDR and details of successful peer-reviewed publication campaigns.

Christina M Johnson↗
NASA NTRSDate not supplied

Tracking Community Building in Open Science

Open Science is enabled by a vibrant community of researchers who regularly engage with the data, from its production to its organization, curation, archiving, dissemination, analysis, and publication. This presentation will examine community building in open science. The NASA Open Science Data Repository (OSDR) makes data available to the public following the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles. OSDR takes open science further with the OS Analysis Working Groups (AWGs) that facilitate community development and promotion. The primary activity of each AWG is to establish and validate analytical processes to generate higher-order data from data housed in OSDR. There are a number of these groups on various topics, including the Animal AWG, Plant AWG, Microbial AWG, Multi-Omics AWG, AI/ML AWG, and the Ames Life Sciences Data Archive (ALSDA) AWG. The international volunteers participating in these AWGs come from academia, citizen science initiatives, industry, and government. They include researchers, principal investigators, professors, trained hobbyists, and students from various domains and disciplines. Anyone may request to join the AWGs, and membership requests are vetted monthly by the group organizers before granting admission. Core to membership is demonstrated expertise through records of training, integrity, work in the professed domain(s), and good community standing. Regular virtual meetings are held for each AWG, with a varying cadence depending on the group's needs and goals. AWG communities share their expertise in research including cutting edge tools, software, frameworks, data formats, and libraries accelerating research collectively. This collaborative approach helps community members cross technology gaps and identify emerging challenges. These diverse communities encompass a wide range of individuals hailing from various sectors within the Science Mission Directorate and beyond. They serve as a means to promote and enhance transparency, accessibility, and inclusion. An annual AWG Symposium brings contributors together in person. Participation in AWGs can be synchronous or asynchronous, with some groups performing most of their work in off hours. Participants gain valuable skills and connections that allow them to add value to their communities and new organizations that they join, resulting in an expanded return on investment for the space life science community. Open science is increasingly a federal mandate and initiatives like NASA's Transform to Open Science and instruments like the Decadal Survey of Biological and Physical Sciences in Space demonstrate the need to carefully consider best practices in this domain. Here, we present greater detail about the makeup and participation metrics of the various AWGs affiliated with OSDR and details of successful peer-reviewed publication campaigns.

Christina M Johnson↗
DOE OSTI2026

Single-cell and spatial omics in plants: from cellular atlases to regulatory mechanisms

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.

Li, Miaomiao [ORNL] (ORCID:0000000321326168)↗
NASA NTRS2019

Systemic Alterations with Spaceflight Associated Health Risks Originating from Both Circulating miRNAs and Mitochondrial Biology

The many known health risks currently associated with space travel include increased risk of cardiovascular disease, cancer, central nervous system related diseases, muscle degeneration, and changes with host-gut microbiome interactions that can have profound impact with these and other health risks. The majority of the risk from space travel stem of the two components of the space environment which are microgravity and radiation. Two specific systemic effects have been uncovered by us to impact the body as a whole due to the space environment. One factor is related from our earlier work (Beheshti et al, PLOS One, 2018), we predicted that there is a systemic component of the host that causes general increased health risks due to spaceflight driven by a circulating microRNA (miRNA) signature consisting of 13 miRNAs that directly regulates both p53 and TGF1. MiRNAs are small non-coding RNA molecules with a negative and post-transcriptional regulation on gene expression) are increasingly recognized as major systemic regulators of responses to stressors, including microgravity, oxidative stress, and DNA damage. In addition, due to the size and stability of miRNAs, it is known that miRNAs can circulate throughout the body and have been found in the majority of the bodily fluids including blood, urine, saliva, and tears. Here, we start to dissect the actual impact of this miRNA signature on both the radiation and microgravity components and prove that this miRNA signature actually exists in the circulation of a host. The other systemic factor we uncovered was the impact the mitochondria on the whole body due to spaceflight. We hypothesize that spaceflight may promote a physiologic response driven by systemic mitochondria pathways leading to metabolic disorder stemming from the liver and directly impacting other organs and tissues. A systems biology method was implemented utilizing GeneLab datasets that involved in vitro experiments performed at the low Earth orbit, in vivo experiments involving mice flown to space, and finally human physiological data from astronauts. A comprehensive multi-omics approach was implemented which involved correlating transcriptomic analysis with proteomics, metabolomics, and methylation analysis. This approach led us to confirm our hypothesis that a systemic mitochondrial driven response is responsible for increasing potential health risk and is conserved from the in vitro studies, to the in vivo studies, and finally confirmed in astronauts.

Radiation↗
NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks associated with deep space crewed missions (cis-Lunar, Mars transit/surface) require development of health countermeasures, novel ecosystem support, risk modeling, and fundamental space biological knowledge discovery. Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from space biological and health studies are needed for reuse by scientists to address these tasks. The data as well as space-relevant biospecimens are being made more findable, accessible, interoperable, and reusable through NASA’s Open Science Data Repository (OSDR). This new OSDR umbrella grouping includes NASA GeneLab, the NASA Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection. The OSDR system design appropriately handles metadata and processed-tabular results from ALSDA studies collected from space experiments. But raw and processed ALSDA bioimage and video datasets require an expansion of OSDR’s data architecture to handle ingestion, curation, and egress. The academic-industry bioimaging field saw a scientific renaissance in the past several years through leveraging open-source software, international collaborations, machine learning, and other open science/programming approaches. As crewed missions and more biological experiments are on the deep space horizon, OSDR is embracing data stewardship through listening to feedback from subject matter experts and designing an expanded architecture which is appropriate for NASA’s goals to enable analysis and reuse of bioimaging and video data for the public science community.Discovery Through Image and Video Data Sharing

space biology↗
NASA NTRSDate not supplied

The GeneLab Buffet: A Bioinformatic MATRIX of MANGO and TOAST

The GeneLab data repository provides an unparalleled resource for exploring how spaceflight affects organisms with omics-level insights. However, two major interlinked challenges to capitalizing on the information within these data are their vast breadth and the often-specialized expertise that has been required in the past for their analysis. How do you compare responses within and between studies, especially if you are a non-bioinformatics specialist? This presentation will discuss how Space Biology data can be accessed using software to help provide these data resources to address research questions and generate new hypotheses. The presentation will cover a wide range of the available space life science tools but will focus on TOAST, MANGO, the MATRIX, RadBioApp and other interactive relational databases (https://genelab.nasa.gov/external-vis-apps). These exploration environments have been developed to search the GeneLab data repository for new insights that inform how model organisms respond to microgravity, radiation and other factors associated with spaceflight. The presentation will be interactive, and participants will have the opportunity to ask questions and learn more about the data viz and modeling tools that are available to them.

AstroBotany↗
NASA NTRS2020

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

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

Elongase↗
NASA NTRS2016

GeneLab: Multi-Omics Investigation of Rodent Research-1 Bio-Banked Tissues

NASAs Rodent Research (RR) project is playing a critical role in advancing biomedical research on the physiological effects of space environments. Due to the limited resources for conducting biological experiments aboard the International Space Station (ISS), it is imperative to use crew time efficiently while maximizing high-quality science return. NASAs GeneLab project has as its primary objectives to 1) further increase the value of these experiments using a multi-omics, systems biology-based approach, and 2) disseminate these data without restrictions to the scientific community. The current investigation assessed viability of RNA, DNA, and protein extracted from archived RR-1 tissue samples for epigenomic, transcriptomic, and proteomic assays. During the first RR spaceflight experiment, a variety of tissue types were harvested from subjects, snap-frozen or RNAlater-preserved, and then stored at least a year at -80OC after return to Earth. They were then prioritized for this investigation based on likelihood of significant scientific value for spaceflight research. All tissues were made available to GeneLab through the bio-specimen sharing program managed by the Ames Life Science Data Archive and included mouse adrenal glands, quadriceps, gastrocnemius, tibialis anterior, extensor digitorum longus, soleus, eye, and kidney. We report here protocols for and results of these tissue extractions, and thus, the feasibility and value of these kinds of omics analyses. In addition to providing additional opportunities for investigation of spaceflight effects on the mouse transcriptome and proteome in new kinds of tissues, our results may also be of value to program managers for the prioritization of ISS crew time for rodent research activities. Support from the NASA Space Life and Physical Sciences Division and the International Space Station Program is gratefully acknowledged.

GeneLab↗
DOE OSTI2025

Metabolic interactions underpinning high methane fluxes across terrestrial freshwater wetlands

Current estimates of wetland contributions to the global methane budget carry high uncertainty, particularly in accurately predicting emissions from high methane-emitting wetlands. Microorganisms drive methane cycling, but little is known about their conservation across wetlands. To address this, we integrate 16S rRNA amplicon datasets, metagenomes, metatranscriptomes, and annual methane flux data across 9 wetlands, creating the Multi-Omics for Understanding Climate Change (MUCC) v2.0.0 database. This resource is used to link microbiome composition to function and methane emissions, focusing on methane-cycling microbes and the networks driving carbon decomposition. We identify eight methane-cycling genera shared across wetlands and show wetland-specific metabolic interactions in marshes, revealing low connections between methanogens and methanotrophs in high-emitting wetlands. Methanoregula emerged as a hub methanogen across networks and is a strong predictor of methane flux. In these wetlands it also displays the functional potential for methylotrophic methanogenesis, highlighting the importance of this pathway in these ecosystems. Collectively, our findings illuminate trends between microbial decomposition networks and methane flux while providing an extensive publicly available database to advance future wetland research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A standards perspective on genomic data reusability and reproducibility

Genomic and metagenomic sequence data provides an unprecedented ability to re-examine findings, offering a transformative potential for advancing research, developing computational tools, enhancing clinical applications, and fostering scientific collaboration. However, effective and ethical reuse of genomics data is hampered by numerous technical and social challenges. The International Microbiome and Multi’Omics Standards Alliance (IMMSA, https://www.microbialstandards.org/) and the Genomic Standards Consortium (GSC, https://gensc.org) hosted a 5-part seminar series “A Year of Data Reuse” in 2024 to explore challenges and opportunities of data reuse and reproducibility across disparate domains of the genomic sciences. Addressing these challenges will require a multifaceted approach, including common metadata reporting, clear communication, standardized protocols, improved data management infrastructure, ethical guidelines, and collaborative policies that prioritize transparency and accessibility. We offer strategies to enable responsible and technically feasible data reuse, recognition of data reproducibility challenges, and emphasizing the importance of cross-disciplinary efforts in the pursuit of open science and data-driven innovation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format

Advances in mass spectrometry (MS) instrumentation, such as higher resolution, faster scan speeds, and improved sensitivity, have significantly increased the volume and complexity of data. The growing adoption of imaging and ion mobility further amplifies these challenges across MS-based omics fields, including proteomics, metabolomics, and lipidomics. While these technologies unlock new possibilities, they also present significant challenges in data management, storage, and accessibility. Existing open formats, such as the XML-based community standards mzML and imzML, struggle to meet the demands of modern MS workflows due to their large file sizes, slow data access, and limited metadata support. Vendor-specific formats, while optimized for proprietary instruments, lack interoperability, comprehensive metadata support and long-term archival reliability. This white paper lays the groundwork for mzPeak, a next-generation community data format designed to address these challenges and support high-throughput, multi-dimensional MS workflows. By adopting a hybrid model that combines efficient binary storage for numerical data and both human and machine-readable metadata storage, mzPeak will reduce file sizes, accelerate data access, and offer a scalable, adaptable solution for evolving MS technologies. For researchers, mzPeak will enable enhanced interoperability across platforms, seamless support for complex workflows including ion mobility and MS imaging, and faster data access compared to existing community formats such as mzML. Its design will ensure data is managed in compliance with regulatory standards, essential for applications such as precision medicine and chemical safety, where long-term data integrity and accessibility are critical. For vendors, mzPeak provides a streamlined, open alternative to proprietary formats, reducing the burden of regulatory compliance while aligning with the industry's push for transparency and standardization. By offering a high-performance, interoperable solution, mzPeak positions vendors to meet customer demands for sustainable data management tools which will be able to handle emerging and future data types and workflows. mzPeak aspires to become the cornerstone of MS data management, empowering researchers, vendors, and developers to innovate and collaborate more effectively.

data formats↗
DOE OSTI2024

Automated annotation of scientific texts for ML-based keyphrase extraction and validation

Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lack the essential metadata required for researchers to find, curate, and search them effectively. The lack of metadata poses a significant challenge in the utilization of these data sets. Machine learning (ML)–based metadata extraction techniques have emerged as a potentially viable approach to automatically annotating scientific data sets with the metadata necessary for enabling effective search. Text labeling, usually performed manually, plays a crucial role in validating machine-extracted metadata. However, manual labeling is time-consuming and not always feasible; thus, there is a need to develop automated text labeling techniques in order to accelerate the process of scientific innovation. This need is particularly urgent in fields such as environmental genomics and microbiome science, which have historically received less attention in terms of metadata curation and creation of gold-standard text mining data sets. In this paper, we present two novel automated text labeling approaches for the validation of ML-generated metadata for unlabeled texts, with specific applications in environmental genomics. Our techniques show the potential of two new ways to leverage existing information that is only available for select documents within a corpus to validate ML models, which can then be used to describe the remaining documents in the corpus. The first technique exploits relationships between different types of data sources related to the same research study, such as publications and proposals. The second technique takes advantage of domain-specific controlled vocabularies or ontologies. In this paper, we detail applying these approaches in the context of environmental genomics research for ML-generated metadata validation. Our results show that the proposed label assignment approaches can generate both generic and highly specific text labels for the unlabeled texts, with up to 44% of the labels matching with those suggested by a ML keyword extraction algorithm.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS2016

Integrating Large Scale Data Sets to Develop Predictive Hypotheses of Low-Dose Radiation-Induced Health Effects

Over one hundred years of radiation biology research has revealed much about the DNA damages induced by the deposition of energy from exposure to ionizing radiation and the subsequent cellular responses. However, there are still significant gaps in our understanding of how these might lead to detrimental health effects, particularly at low doses (100 mGy (milligray)). Recent advances in high throughput omics technologies enable interrogation of induced radiation effects at the genomic, proteomic and metabolomic levels. These include changes in gene expression, protein modifications, e.g., phosphorylation, acetylation, and methylation, and metabolic changes. We will discuss the integration of data obtained from multiple omics platforms to understand radiation dose, and dose rate effects in a complex human tissue model as a function of time. We will use as an example our results on the low dose responses in a 3D human skin model.

ionizing radiation↗
NASA NTRSDate not supplied

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

The fast-growing array of space biological data, which in the past was simply archived after minimal analysis, holds great potential if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its diverse nature (molecular, cellular, tissue, whole organism, behavior; tabular, imagery). Open Science is the concept that the more people have access to scientifically curated data, the more knowledge will be gained. This led NASA to start the development of GeneLab in 2015. GeneLab houses spaceflight and space-analog multi-omics datasets from plant, rodent, small animal, and microbial experiments. The success and knowledge gained from GeneLab led to a new alliance of NASA “Open Science Data Repositories” (OSDR), which include the Ames Life Sciences Data Archive (ALSDA) and the NASA Biological Institutional Scientific Collection (NBISC). Both are adopting the GeneLab data system, so data are more findable, accessible, interoperable, and reusable (FAIR). OSDR systems provide users the ability to upload, download, search, share, analyze, and visualize. Open Science also needs strong confidence in the data, which is gained through building science communities. With ~400 current members, GeneLab and ALSDA formed Analysis Working Groups (AWGs) to provide feedback on processing pipelines, metadata curation standards (for ‘omics and phenotypic-physiological-behavioral assays), and to collaborate in effectively reusing data. The AWG also led to the development of the Radiation Biology Ontology (RBO), ensuring radiation metadata are efficiently captured, connected, and interoperable. Feedback from the AWG provided design input toward the new single point-of-entry data submission portal for all investigators to submit, curate, and share their research data. Space biological data is now maximally open access, collected-curated with rich metadata, and formatted for interoperability to enable systems biology, meta-analysis, knowledge graphs, machine learning, modeling, and other reuse approaches. With potential for further federation of OSDR for data mining with traditional biological and medical databases (NIH, NCI, EBI, etc.), a new era for space biology has begun to support the knowledge discovery necessary for Lunar and Martian missions.

Ryan T Scott↗