NASA GeneLab Project: Bridging Space Radiation Omics with Ground Studies

Accurate assessment of risk factors for long-term space missions is critical for human space exploration: therefore it is essential to have a detailed understanding of the biological effects on humans living and working in deep space. Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) currently includes datasets from both spaceflight and ground-based studies, a majority of which involve exposure to ionizing radiation. In addition to detailed information for ground-based studies, we are in the process of adding detailed, curated dosimetry information for spaceflight missions. GeneLab is the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. In addition to previously acquired data, the GLDS is continually expanding as Omics related data are generated by the space life sciences community. Here we provide a brief summary of space radiation related data available at GeneLab

Computational approaches for discovery of common immunomodulators in fungal infections: towards broad-spectrum immunotherapeutic interventions

BACKGROUND: Fungi are the second most abundant type of human pathogens. Invasive fungal pathogens are leading causes of life-threatening infections in clinical settings. Toxicity to the host and drug-resistance are two major deleterious issues associated with existing antifungal agents. Increasing a host’s tolerance and/or immunity to fungal pathogens has potential to alleviate these problems. A host’s tolerance may be improved by modulating the immune system such that it responds more rapidly and robustly in all facets, ranging from the recognition of pathogens to their clearance from the host. An understanding of biological processes and genes that are perturbed during attempted fungal exposure, colonization, and/or invasion will help guide the identification of endogenous immunomodulators and/or small molecules that activate host-immune responses such as specialized adjuvants. RESULTS: In this study, we present computational techniques and approaches using publicly available transcriptional data sets, to predict immunomodulators that may act against multiple fungal pathogens. Our study analyzed data sets derived from host cells exposed to five fungal pathogens, namely, Alternaria alternata, Aspergillus fumigatus, Candida albicans, Pneumocystis jirovecii, and Stachybotrys chartarum. We observed statistically significant associations between host responses to A. fumigatus and C. albicans. Our analysis identified biological processes that were consistently perturbed by these two pathogens. These processes contained both immune response-inducing genes such as MALT1, SERPINE1, ICAM1, and IL8, and immune response-repressing genes such as DUSP8, DUSP6, and SPRED2. We hypothesize that these genes belong to a pool of common immunomodulators that can potentially be activated or suppressed (agonized or antagonized) in order to render the host more tolerant to infections caused by A. fumigatus and C. albicans. CONCLUSIONS: Our computational approaches and methodologies described here can now be applied to newly generated or expanded data sets for further elucidation of additional drug targets. Moreover, identified immunomodulators may be used to generate experimentally testable hypotheses that could help in the discovery of broad-spectrum immunotherapeutic interventions. All of our results are available at the following supplementary website: http://bioinformatics.cs.vt.edu/~murali/supplements/2013-kidane-bm

Global Gene Expression Profiling in Lung Tissues of Rat Exposed to Lunar Dust Particles

The Moon's surface is covered by a layer of fine, potential reactive dust. Lunar dust contain about 12% respirable very fine dust (less than 3 micrometers). The habitable area of any lunar landing vehicle and outpost would inevitably be contaminated with lunar dust that could pose a health risk. The purpose of the study is to analyze the dynamics of global gene expression changes in lung tissues of rats exposed to lunar dust particles. F344 rats were exposed for 4 weeks (6h/d; 5d/wk) in noseonly inhalation chambers to concentrations of 0 (control air), 2.1, 6.8, 21, and 61 mg/m3 of lunar dust. Animals were euthanized at 1 day and 13 weeks after the last inhalation exposure. After being lavaged, lung tissue from each animal was collected and total RNA was isolated. Four samples of each dose group were analyzed using Agilent Rat GE v3 microarray to profile global gene expression of 44K transcripts. After background subtraction, normalization, and log transformation, t tests were used to compare the mean expression levels of each exposed group to the control group. Correction for multiple testing was made using the method of Benjamini, Krieger, and Yekuteli (1) to control the false discovery rate. Genes with significant changes of at least 1.75 fold were identified as genes of interest. Both low and high doses of lunar dust caused dramatic, dosedependent global gene expression changes in the lung tissues. However, the responses of lung tissue to low dose lunar dust are distinguished from those of high doses, especially those associated with 61mg/m3 dust exposure. The data were further integrated into the Ingenuity system to analyze the gene ontology (GO), pathway distribution and putative upstream regulators and gene targets. Multiple pathways, functions, and upstream regulators have been identified in response to lunar dust induced damage in the lung tissue

The cartilage matrisome in adolescent idiopathic scoliosis

The human spinal column is a dynamic, segmented, bony, and cartilaginous structure that protects the neurologic system and simultaneously provides balance and flexibility. Children with developmental disorders that affect the patterning or shape of the spine can be at risk of neurologic and other physiologic dysfunctions. The most common developmental disorder of the spine is scoliosis, a lateral deformity in the shape of the spinal column. Scoliosis may be part of the clinical spectrum that is observed in many developmental disorders, but typically presents as an isolated symptom in otherwise healthy adolescent children. Adolescent idiopathic scoliosis (AIS) has defied understanding in part due to its genetic complexity. Breakthroughs have come from recent genome-wide association studies (GWAS) and next generation sequencing (NGS) of human AIS cohorts, as well as investigations of animal models. These studies have identified genetic associations with determinants of cartilage biogenesis and development of the intervertebral disc (IVD). Current evidence suggests that a fraction of AIS cases may arise from variation in factors involved in the structural integrity and homeostasis of the cartilaginous extracellular matrix (ECM). Here, we review the development of the spine and spinal cartilages, the composition of the cartilage ECM, the so-called "matrisome" and its functions, and the players involved in the genetic architecture of AIS. We also propose a molecular model by which the cartilage matrisome of the IVD contributes to AIS susceptibility

Microgravity induces proteomics changes involved in endoplasmic reticulum stress and mitochondrial protection

On Earth, biological systems have evolved in response to environmental stressors, interactions dictated by physical forces that include gravity. The absence of gravity is an extreme stressor and the impact of its absence on biological systems is ill-defined. Astronauts who have spent extended time under conditions of minimal gravity (microgravity) experience an array of biological alterations, including perturbations in cardiovascular function. We hypothesized that physiological perturbations in cardiac function in microgravity may be a consequence of alterations in molecular and organellar dynamics within the cellular milieu of cardiomyocytes. We used a combination of mass spectrometry-based approaches to compare the relative abundance and turnover rates of 848 and 196 proteins, respectively, in rat neonatal cardiomyocytes exposed to simulated microgravity or normal gravity. Gene functional enrichment analysis of these data suggested that the protein content and function of the mitochondria, ribosomes, and endoplasmic reticulum were differentially modulated in microgravity. We confirmed experimentally that in microgravity protein synthesis was decreased while apoptosis, cell viability, and protein degradation were largely unaffected. These data support our conclusion that in microgravity cardiomyocytes attempt to maintain mitochondrial homeostasis at the expense of protein synthesis. The overall response to this stress may culminate in cardiac muscle atrophy

Gene Expression Profiling in Lung Tissues from Rat Exposed to Lunar Dust Particles

The Moon's surface is covered by a layer of fine, reactive dust. Lunar dust contain about 1-2% of very fine dust (< 3 micron), that is respirable. The habitable area of any lunar landing vehicle and outpost would inevitably be contaminated with lunar dust that could pose a health risk. The purpose of the study is to analyze the dynamics of global gene expression changes in lung tissues from rats exposed to lunar dust particles. F344 rats were exposed for 4 weeks (6h/d; 5d/wk) in nose-only inhalation chambers to concentrations of 0 (control air), 2.1, 6.8, 21, and 61 mg/m(exp 3) of lunar dust. Five rats per group were euthanized 1 day, and 3 months after the last inhalation exposure. The total RNAs were isolated from lung tissues after being lavaged. The Agilent Rat GE v3 microarray was used to profile global gene expression (44K). The genes with significant expression changes are identified and the gene expression data were further analyzed using various statistical tools

Proteomic and phosphoproteomic characterization of cardiovascular tissues after long term exposure to simulated space radiation

Introduction: It may take decades to develop cardiovascular dysfunction following exposure to high doses of ionizing radiation from medical therapy or from nuclear accidents. Since astronauts may be exposed continually to a complex space radiation environment unlike that experienced on Earth, it is unresolved whether there is a risk to cardiovascular health during long-term space exploration missions. Previously, we have described that mice exposed to a single dose of simplified Galactic Cosmic Ray (GCR 5-ion) develop cardiovascular dysfunction by 12 months post-radiation. Methods: To investigate the biological basis of this dysfunction, here we performed a quantitative mass spectrometry-based proteomics analysis of heart tissue (proteome and phosphoproteome) and plasma (proteome only) from these mice at 8 months post-radiation.Results: Differentially expressed proteins (DEPs) for irradiated versus sham irradiated samples (fold-change ≥1.2 and an adjusted p-value of ≤0.05) were identified for each proteomics data set. For the heart proteome, there were 87 significant DEPs (11 upregulated and 76 downregulated); for the heart phosphoproteome, there were 60 significant differentially phosphorylated peptides (17 upregulated and 43 downregulated); and for the plasma proteome, there was only one upregulated protein. A Gene Set Enrichment Analysis (GSEA) technique that assesses canonical pathways from BIOCARTA, KEGG, PID, REACTOME, and WikiPathways revealed significant perturbation in pathways in each data set. For the heart proteome, 166 pathways were significantly altered (36 upregulated and 130 downregulated); for the plasma proteome, there were 73 pathways significantly altered (25 upregulated and 48 downregulated); and for the phosphoproteome, there were 223 pathways significantly affected at 0.1 adjusted p-value cutoff. Pathways related to inflammation were the most highly perturbed in the heart and plasma. In line with sustained inflammation, neutrophil extracellular traps (NETs) were demonstrated to be increased in GCR 5-ion irradiated hearts at 12-month post irradiation. NETs play a fundamental role in combating bacterial pathogens, modulating inflammatory responses, inflicting damage on healthy tissues, and escalating vascular thrombosis. Discussion: These findings suggest that a single exposure to GCR5-ion results in long-lasting changes in the proteome and that these proteomic changes can potentiate acute and chronic health issues for astronauts, such as what we have previously described with late cardiac dysfunction in these mice

NASA Space Radiation Risk Project: Overview and Recent Results

The NASA Space Radiation Risk project is responsible for integrating new experimental and computational results into models to predict risk of cancer and acute radiation syndrome (ARS) for use in mission planning and systems design, as well as current space operations. The project has several parallel efforts focused on proving NASA's radiation risk projection capability in both the near and long term. This presentation will give an overview, with select results from these efforts including the following topics: verification, validation, and streamlining the transition of models to use in decision making; relative biological effectiveness and dose rate effect estimation using a combination of stochastic track structure simulations, DNA damage model calculations and experimental data; ARS model improvements; pathway analysis from gene expression data sets; solar particle event probabilistic exposure calculation including correlated uncertainties for use in design optimization

NASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data

With the development of transcriptomic technologies, we are able to quantify precise changes in gene expression profiles from astronauts and other organisms exposed to spaceflight. Members of NASA GeneLab and GeneLab-associated analysis working groups (AWGs) have developed a consensus pipeline for analyzing short-read RNA-sequencing data from spaceflight-associated experiments. The pipeline includes quality control, read trimming, mapping, and gene quantification steps, culminating in the detection of differentially expressed genes. This data analysis pipeline and the results of its execution using data submitted to GeneLab are now all publicly available through the GeneLab database. We present here the full details and rationale for the construction of this pipeline in order to promote transparency, reproducibility, and reusability of pipeline data; to provide a template for data processing of future spaceflight-relevant datasets; and to encourage cross-analysis of data from other databases with the data available in GeneLab

The Landscape of Host Transcriptional Response Programs Commonly Perturbed by Infectious Pathogens: Towards Host-Oriented Broad-Spectrum Drug

The threat from infectious diseases dates as far back as prehistoric times. Pathogens continue to pose serious challenges to human health. The emergence and spread of diseases such as HIV/AIDS, Severe Acute Respiratory Syndrome (SARS), avian influenza, and the threats of bioterrorism have made infectious diseases major public health concerns. Despite many successes in the discovery of anti-infective medications, the treatment of infectious diseases faces serious challenges, which include (i) the emergence and reemergence of infectious pathogens, (ii) the ability of pathogens to adapt and develop resistance to drugs, and (ii) a shortage in the development and discovery of new anti-infective drugs. Host-Oriented Broad-Spectrum (HOBS) treatments have the promising potential to alleviate these problems. The HOBS treatment paradigm focuses on finding drug targets in human host that are simultaneously effective against a wide variety of infectious agents and toxins. In this dissertation, we present a computational approach to predict HOBS treatments by integrative analysis of three types of data, namely, (a) gene expression data representing host responses upon infection by a pathogen, (b) annotations of genes to pre-defined biological pathways and processes, and (iii) genes that are targets of known drugs. Our methods combine gene set-level enrichment with biclustering. We applied our approach to a compendium of gene expression data sets derived from host cells exposed to bacterial or to fungal pathogens, to functional annotation data from multiple databases, and to drug targets from DrugBank. We present putative host drug targets and drugs with extensive support in the literature for their potential to treat multiple bacterial and fungal infections. These results showcase the potential of our computational approach to predict HOBS drug targets that may be effective against two or more pathogens. Our study takes a clean-slate approach that promises to yield unsuspected or unknown associations between pathogens and biological processes, and thus discern candidate gene/proteins to be further probed as HOBS targets. Furthermore, by focusing on host responses to pathogens as captured by transcriptional data, our proposed approach stimulates host-oriented drug target identification, which has potential to alleviate the problem of drug resistance.Ph. D