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Spaceflight is known to impose changes on human physiology with unknown molecular etiologies. To reveal these causes, we used a multi-omics, systems biology analytical approach using biomedical profiles from fifty-nine astronauts and data from NASA's GeneLab derived from hundreds of samples flown in space to determine transcriptomic, proteomic, metabolomic, and epigenetic responses to spaceflight. Overall pathway analyses on the multi-omics datasets showed significant enrichment for mitochondrial processes, as well as innate immunity, chronic inflammation, cell cycle, circadian rhythm, and olfactory functions. Importantly, NASA's Twin Study provided a platform to confirm several of our principal findings. Evidence of altered mitochondrial function and DNA damage was also found in the urine and blood metabolic data compiled from the astronaut cohort and NASA Twin Study data, indicating mitochondrial stress as a consistent phenotype of spaceflight.
Pubmed ID: 33242417 RIS Download
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Omics database for spaceflight experiments. Interactive, open access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Enables exploration of molecular network responses of terrestrial biology to space environment. Contains curated omics data, metadata and radiation dosimetry for model organisms. Supports standard guidelines for submission of datasets, MIAME for microarray, ENCODE Consortium Guidelines for RNA-seq and MIAPE Guidelines for proteomics.
View all literature mentionslaboratory mouse with name BALB/cAnNCrl from MGI.
View all literature mentionsMus musculus with name BALB/cJ from IMSR.
View all literature mentionsMus musculus with name C57BL/6J from IMSR.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsBioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
View all literature mentionsJava toolset for working with next generation sequencing data in the BAM format.
View all literature mentionsSoftware Python package that provides support for basic COnstraint-Based Reconstruction and Analysis (COBRA) methods.
View all literature mentionsSoftware R package to produce publication ready volcano plots with enhanced colouring and labeling. Used to visualise results of differential expression analyses.
View all literature mentionsNumPy is the fundamental package needed for scientific computing with Python. It contains among other things: * a powerful N-dimensional array object * sophisticated (broadcasting) functions * tools for integrating C/C and Fortran code * useful linear algebra, Fourier transform, and random number capabilities. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases. Sponsored by ENTHOUGHT
View all literature mentionsSoftware that supports biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiplehypothesis testing.
View all literature mentionsCollection of data of protein sequence and functional information. Resource for protein sequence and annotation data. Consortium for preservation of the UniProt databases: UniProt Knowledgebase (UniProtKB), UniProt Reference Clusters (UniRef), and UniProt Archive (UniParc), UniProt Proteomes. Collaboration between European Bioinformatics Institute (EMBL-EBI), SIB Swiss Institute of Bioinformatics and Protein Information Resource. Swiss-Prot is a curated subset of UniProtKB.
View all literature mentionsSoftware environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.
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View all literature mentionsSoftware package for the analysis of gene expression microarray data, especially the use of linear models for analyzing designed experiments and the assessment of differential expression.
View all literature mentionsAn R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing.
View all literature mentionsQuality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.
View all literature mentionsSoftware tool for quantifying abundances of transcripts from RNA-Seq data or target sequences using high-throughput sequencing reads.
View all literature mentionsCell line HUVEC-C is a Finite cell line with a species of origin Homo sapiens
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View all literature mentionsCell line AG01522 is a Finite cell line with a species of origin Homo sapiens (Human)
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View all literature mentionsA web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document. It offers a comprehensive library on top of which more sophisticated systems can be built. The project provides an enhanced interactive environment that includes support for data visualization and facilities for distributed and parallel computation.
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View all literature mentionsProgramming language for all operating systems that lets users work more quickly and integrate their systems more effectively. Often compared to Tcl, Perl, Ruby, Scheme or Java. Some of its key distinguishing features include very clear and readable syntax, strong introspection capabilities, intuitive object orientation, natural expression of procedural code, full modularity, exception-based error handling, high level dynamic data types, extensive standard libraries and third party modules for virtually every task, extensions and modules easily written in C, C (or Java for Python, or .NET languages for IronPython), and embeddable within applications as a scripting interface.
View all literature mentionsWeb server for statistical, functional and integrative analysis of metabolomics data. Web based tool suite used for metabolomic data processing, normalization, multivariate statistical analysis, and data annotation, biomarker discovery and classification.
View all literature mentionsA program that opens a new perspective to the analysis of microarray data (e.g., gene expression profiling). Unlike traditional gene clustering software, GEDI is primarily sample-oriented rather than gene-oriented. By treating each high-dimensional sample, such as one microarray experiment, as an object, it accentuates the genome-wide response of a tissue or a patient and treats it as an integrated biological entity. Hence, GEDI honors the new spirit of a system-level approach in biology. Yet, it also allows the researcher to quickly zoom-in from global patterns onto individual genes that exhibit interesting expression behavior and retrieve gene-specific information. Therefore, GEDI unites a novel holistic perspective with the traditional gene-centered approach in molecular biology. GEDI allows experimental biologists or clinicians with no bioinformatics background to efficiently and intuitively navigate through a large number of expression profiles, each with a memorizable face, and inspect, group and collect them, like managing a stack of baseball cards. DYNAMIC ANALYSIS: The unique strength of GEDI, for which GEDI was originally developed, is that it can display the results of parallel monitoring of multiple high-dimensional time courses, such as the comparison of expression profile time evolution in response to a series of drugs. GEDI creates animated graphics showing how 10,000s of genes change their expression over time in response to 100s of separately tested drugs. STATIC ANAYLSIS: The signature graphical output of GEDI, the GEDI-mosaics provide a unique, one-glance visual engram that gives each microarray or other high-dimensional dataset a face. A characteristic of GEDI''s analysis is that it does not prejudicate any particular structure in the data (such as clusters or hierarchical organization). Thus, it allows the researcher to use human pattern recognition to perform a global first-level analysis of the data. Sponsor. The project was supported by the Air Force Office of Scientific Research and the National Health Institutes. It is distributed for free academic use by the Childrens Hospital, Boston.
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