Bone loss is one of the major health problems for astronauts during long-term spaceflight and for patients during prolonged bed rest or paralysis. Growing evidence suggests that osteocytes, the most abundant cells in the mineralized bone matrix, play a key role in sensing mechanical forces applied to the skeleton and in transducing them into subcellular biochemical signals to modulate bone homeostasis. However, the precise molecular mechanisms underlying both mechanosensation and mechanotransduction in osteocytes under the real microgravity (µG) condition are poorly understood. To unravel the mechanisms by which osteocyte, sense and responds to mechanical unloading, we exposed murine osteocytic cell line, Ocy454, seeded on a highly porous polystyrene 3D scaffold, to 2, 4, or 6 days of µG on board the International Space Station (ISS) and compared their gene expression with cells at 1G on Earth. Bioinformatics analysis of cells exposed to µG revealed several pathways differentially regulated upon exposure to microgravity.

Interaction of COP1 and UVR8 which regulate UV-B-induced photomorphogenesis and stress acclimation in Arabidopsis thaliana.

The wild type Col-0 plants and the Sku-6 mutant plants of the Col-0 background were germinated on ISS or on the ground and the gene expression profiles in roots at 4 days or 8 days were established. The Sku6 gene (At2g03680) codes for a protein that localizes to microtubule within the cortical array and putatively acting as an intramolecular linker. The development of Col-0 and Sku-6 plants on orbit differs from that on the ground as demonstrated by the comparison of the gene expression profiles between 4 days old to 8 days old plant in the two environments. However the development of Sku-6 mutant plants also differs from Col-0 at either age and in either environment suggesting the role of the genetic background in these developmental decisions. The 4 days old Sku-6 roots in orbit engaged more genes than the 4 days old Col-0 roots in orbit but also more than the 4 days old Sku-6 roots on the ground. Overall the 4 days old roots differentially expressed more genes in spaceflight relative to ground than the 8 days old roots of either genotype.

Whole seedlings of wild type (4d) and atm mutants (4d) have been analyzed after a gamma ray irradiation of 0.75h 1.5h 3h & 5h (time course). Roots of wt (4d) atm (3d) and atr (4d) mutants have been analyzed after a 1h irradiation. Ataxia Telangiectasia Mutated (ATM) encodes a large protein with a phosphatidylinositol 3-kinase (PI3K)-like domain at the C terminus (reviewed by Rotman and Shiloh 1998). PI3K-related proteins make up a large family of Ser-Thr protein kinases numerous members of which are involved in the regulation of cell cycle progression responses to DNA damage and the maintenance of genomic stability (Hoekstra 1997). AtATM plays an essential role in meiosis and in the somatic response to DNA damage in plants similar to the function of ATM in mammals and other eukaryotes. Ataxia telangiectasia-mutated and Rad3-related (ATR) plays a central role in cell-cycle regulation transmitting DNA damage signals to downstream effectors of cell-cycle progression.

Human deep space and planetary travel is limited by uncertainties regarding the health risks associated with exposure to galactic cosmic radiation (GCR) and in particular the high linear energy transfer (LET) heavy ion component. Here we assessed the impact of two high-LET ions 56Fe and 28Si and low-LET X rays on genome-wide methylation patterns in human bronchial epithelial cells. We found that all three radiation types induced rapid and stable changes in DNA methylation but at distinct subsets of CpG sites affecting different chromatin compartments. The 56Fe ions induced mostly hypermethylation and primarily affected sites in open chromatin regions including enhancers promoters and edges ( shores ) of CpG islands. The 28Si ion-exposure had mixed effects inducing both hyper and hypomethylation and affecting sites in more repressed heterochromatic environments whereas X rays induced mostly hypomethylation primarily at sites in gene bodies and intergenic regions. Significantly the methylation status of 56Fe ion irradiation sensitive sites but not those affected by X ray or 28Si ions could discriminate tumor from normal tissue for human lung adenocarcinomas and squamous cell carcinomas. Thus high LET radiation exposure leaves a lasting imprint on the epigenome and affects sites relevant to human lung cancer. The 56Fe ion signature may prove useful in monitoring the cumulative biological impact and associated cancer risks encountered by astronauts in deep space. Genome wide DNA methylation profiling of normal human bronchial epithelial cells irradiated with varying doses of 28Si-ion radiation ( 300 MeV/u at 0 0.3 1.0 Gy) 56Fe-ion radiation (600 MeV/u at 0 0.1 0.3 1.0 Gy) or X rays (320 kV at 0 1.0 Gy). Triplicate control and irradiated samples were incubated and sampled at 4 timepoints between 2 and 62 days. The Illumina Infinium 450k Human DNA methylation Beadchip was used to obtain DNA methylation profiles across >485,000 CpGs from collected samples. Samples include: 56Fe ions 4 doses x 4 time points x 3 replicates (4 removed in QC) = 44 samples; 28Si ions = 3 doses x 4 time points x 3 replicates = 36 samples; X ray 2 doses x 4 time points x 3 replicates (2 removed in QC)= 22 samples. Overall design: Bisulphite converted DNA from the 102 samples were hybridized to the Illumina Infinium 450k Human Methylation Beadchip.

Background: mRNA interactions with each other and other signaling molecules define different biological pathways and functions. Researchers have been investigating various tools to analyze these types of interactions. In particular gene co-expression network methods have proved useful in finding and analyzing these molecular interactions. Many different analytical pipelines to identify these interactions networks have been proposed with the aim of identifying an optimal partition of the network where the individual modules are neither too small to make any general inference or too large to be biologically interpretable. Results: In this study we propose a new pipeline to perform gene co-expression network analysis. The proposed pipeline uses WGCNA a widely used software to perform different aspects of gene co-expression network analysis and modularity maximization algorithm to analyze novel RNA-Seq data to understand the effects of low-dose 56Fe ion irradiation on the formation of hepatocellular carcinoma in mice. The network results along with experimental validation show that using WGCNA combined with Modularity provide a more biologically interpretable network in our dataset. Our pipeline showed better performance than the existing clustering algorithm in WGCNA in finding modules and identified a module with mitochondrial subunits that are supported by mitochondrial complex assay. Conclusions: We present a pipeline that can reduce the problem of parameter selection with the existing algorithm in WGCNA for comparable RNA-Seq datasets which may assist in future research to discover novel mRNA interactions and their downstream molecular effects. C57BL16 males were placed into 2 treatment groups and received the following irradiation treatments at Brookhaven National Laboratories (Long Island NY): 600 MeV/n 56Fe (0.2 Gy) and no irradiation. Left liver lobes were collected at 30 60 120 270 and 360 days post-irradiation flash frozen and stored at -80 xc2 xb0C until they could be processed for RNA-Seq. Livers were sampled by taking two 40-micron thick slices using a cryotome at -20 xc2 xb0C. This allowed multiple sampling of the tissue without the tissue going through multiple freeze/thaw cycles. Total RNA was isolated from the liver slices using RNAqueousTM Total RNA Isolation Kit (ThermoFisher Scientific Waltham MA) and rRNA was removed via Ribo-ZeroTM rRNA Removal Kit (Illumina San Diego CA) prior to library preparation with the Illumina TruSeq RNA Library kit. Samples were sequenced in a paired-end 50 base format on an Illumina HiSeq 1500. Reads were aligned to the mouse GRCm38 reference genome using the STAR alignment program version 2.5.3a with the recommended ENCODE options. The -quantMode GeneCounts option was used to obtain read counts per gene based on the Gencode release M14 annotation file. Total number of reads used in analysis varies between 23-35 millions of reads.

Physical inactivity decreases the mechanical load on the skeleton which when prolonged leads to losses of muscle strength and bone mass in humans and most mammalian species. Hibernating mammals show no loss in bone mass and less muscle atrophy than would be anticipated over such a prolonged period of physical inactivity. This suggests that diverse hibernating mammals have evolved natural mechanisms that reduce muscle atrophy and conserve bone mass.

Immune dysregulation is among the main adverse outcomes of spaceflight. Despite its crucial role in host protection effects on the human antibody repertoire are unknown. Consequently we examined the IgM repertoire of five cosmonauts 25 days before launch after 64 and 129 days spent on the International Space Station (ISS) and after 1 7 and 30 days of Earth reambulation using high-throughput sequencing. This is the first study of this kind. Our data revealed that the IgM repertoire of cosmonauts was different from the one of control subjects already prior to launch and that 2 out the 5 analyzed cosmonauts presented significant changes of their IgM repertoire during the mission. These modifications persisted up to 30 days after landing likely affected the specificities of IgM binding sites correlated with changes of the V(D)J recombination process in charge of creating functional antibody genes and coincided with a higher stress response. These data confirm that about half of the astronauts who spent six months on the ISS are subjected to immunological changes contribute to explain increased susceptibility to infection reveal individual responses and consequently that personalized approaches should be implemented during future deep-space exploration missions that will endure for an unprecedented amount of time.

The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation. Little is known about the contribution of genome level changes in neighboring bystander cells to tissue and organ stress after irradiation. The timing of these changes is critical in the physiological context and these questions can only be answered by studying signaling and global transcriptomics in a chronological way. Here we present a strategy to identify different biologically important signaling modules that act in concert in the radiation and bystander responses. We used time series gene expression analysis of normal human fibroblast cells measured at 0.5 hour 1 hour 2 hours 4 hours 6 hours and 24 hours after exposure to radiation coupled with a novel clustering method targeted to short time series Feature Based Partitioning around medoids Algorithm (FBPA) to look for genes that were potentially co-regulated. This method uses biologically meaningful features of the expression profile and dimension augmentation to address the analysis of sparse data sets such as ours. We applied FBPA and Short Time series Expression Miner (STEM) to the same datasets and present the results of our comparisons using computational metrics as well as biological enrichment. Enrichment showed that gene expression in irradiated cells fell into broad categories of signal transduction cell cycle/cell death and inflammation/immunity; but only FBPA clustered functions well. In bystander cells the gene expression response was also broadly categorized into functions associated with cell communication and motility signal transduction and inflammation; but neither STEM nor FBPA separated biological functions as well as in irradiated samples. Network analysis revealed that p53 and NF-kappaB were central players in gene expression in both irradiated and bystander gene clusters. Analysis of individual clusters also suggested new regulators of gene expression in the radiation and bystander response that may act at the epigenetic level such as histone deacetylases (HDAC1 and HDAC2) and methylases (KDM5B) that can act as strong transcription repressors. Based on these results we propose a novel time series clustering method FBPA as a powerful approach that can be applied to sparse data sets (including genomic profiling data) where the choice of features selected for clustering and stringent statistical outcome analysis can augment our knowledge of the underlying cellular mechanisms in biological processes. There are 72 total samples 4 corresponding biological replicates of IMR90 cells that were not irradiated (control=C) irradiated (alpha=A) and bystander (B) cells were harvested at 0.5 hour 1 hour 2 hours 4 hours 6 hours and 24 hours after treatment

This study s goal was to examine if any salivary microbiome changes were observed in astronauts as a result of spaceflight. In addition this study looked for any microbiome signature that may be associated with viral reactivation in humans