FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the FAIRness of NASAs GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility

Using OpenTarget to Generate Potential Countermeasures for Long-Term Space Exposure from Data Available on GeneLab

GeneLab as a general tool for the scientific community; Utilizing GeneLab datasets to generate hypothesis and determining potential biological targets against health risks due to long-term space missions; How can OpenTarget be used to discover novel drugs to test as countermeasures that can be utilized by astronauts

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

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems

GeneLab: Visualization and VWG - Introduction

No abstract availabl

Systemic Response to Microgravity: Utilizing GeneLab Datasets to Identify Molecular Targets for Future Hypotheses-Driven Spaceflight Studies

Biological risks associated with microgravity are a major concern for long-term space travel. Although determination of risk has been a focus for NASA research, data examining systemic (i.e., multi- or pan-tissue) responses to space flight are sparse. To perform our analysis, we utilized the NASA GeneLab database which is a publicly available repository containing a wide array of omics results from experiments conducted with: i) with different flight conditions (space shuttle (STS) missions vs. International Space Station (ISS); ii) a variety of tissues; and 3) assays that measure epigenetic, transcriptional, and protein expression changes. Meta-analysis of the transcriptomic data from 7 different murine and rat data sets, examining tissues such as liver, kidney, adrenal gland, thymus, mammary gland, skin, and skeletal muscle (soleus, extensor digitorum longus, tibialis anterior, quadriceps, and gastrocnemius) revealed for the first time, the existence of potential master regulators coordinating systemic responses to microgravity in rodents. We identified p53, TGF(beta)1 and immune related pathways as the highly prevalent pan-tissue signaling pathways that are affected by microgravity. Some variability in the degree of change in their expression across species, strain and time of flight was also observed. Interestingly, while certain skeletal muscle (gastrocnemius and soleus) exhibited an overall down-regulation of these genes, some other muscle types such as the extensor digitorum longus, tibialis anterior and quadriceps, showed an up-regulated expression, indicative of potential compensatory mechanisms to prevent microgravity-induced atrophy. Key genes isolated by unbiased systems analyses displayed a major overlap between tissue types and flight conditions and established TGF(beta)1 to be the most connected gene across all data sets. Finally, a set of microgravity responsive miRNA signature was identified and based on their predicted functional state and subsequent impact on health, a theoretical health risk score was calculated. The genes and miRNAs identified from our analyses can be targeted for future research involving efficient countermeasure design. Our study thus exemplifies the utility of GeneLab data repository to aid in the process of performing novel hypothesis based spaceflight research aimed at elucidating the global impact of environmental stressors at multiple biological scales

GeneLab: "Omics" Data Systems for Spaceflight and Simulated Spaceflight Environment

NASA's GeneLab Data System is a repository that hosts multi-omics datasets generated by biological experiments flown onboard the International Space Station. Strategies regarding how GeneLab envisions the involvement of the scientific community and the public at large will be discussed, and current and future capabilities of the system will be described. Information describing how scientists can participate in analyzing the current datasets on plants, microbes, invertebrates or mammals will be provided, and initial findings from the current datasets will be discussed during this presentation. Anyone interested in genomics, transcriptomics, epigenomics and proteomics, and systems biology, or who is curious to understand how space modifies living organisms should attend

GeneLab: "Omics" Data Systems for Spaceflight and Simulated Spaceflight Environment

Determining the biological impact of spaceflight through novel approaches is essential to reduce the health risks to astronauts for long-term space missions. The current established health risks due to spaceflight are only reflecting known symptomatic and physiologic responses and do not reflect early onset of other potential diseases. There are many unknown variables which still need to be identified to fully understand the health impacts due to the environmental factors in space. One method to uncover potential novel biological mechanisms responsible for health risks in astronauts is by utilizing NASA's GeneLab Data Systems (genelab.nasa.gov). GeneLab is public repository that hosts multiple omics datasets generated from space biology experiments that include experiments flown in space, simulated cosmic radiation experiments, and simulated microgravity experiments. This presentation will provide an overview of GeneLab and examples of analysis that are being done with GeneLab datasets. These example will include novel data and work being generated with various scientists around the world involved with GeneLab's Analysis Working Groups (AWG) that are assisting with the development of pipelines and advancing GeneLab to the next phase, a publication from GeneLab discovering novel Carbon Dioxide impact due to rodent habitats, another publication from GeneLab discovering a potential master regulator responsible for health risk associated due to spaceflight, and potential cardiovascular risk from space radiatio

GeneLab: Omics Data Systems for Spaceflight and Simulated Spaceflight Environment

No abstract availabl

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility