Spaceflight causes strain dependent gene expression changes associated with lipid and extracellular matrix dysregulation in the mouse kidney in vivo.

To explore new worlds we must ensure humans can survive and thrive in the space environment. Incidence of kidney stones in astronauts is a major risk factor associated with long term missions, caused by increased blood calcium levels due to bone demineralisation triggered by microgravity and space radiation. Transcriptomic changes have been observed in other tissues during spaceflight, including the kidney. We analysed kidney transcriptome patterns in two different strains of mice flown on the International Space Station, C57BL/6J and BALB/c. Here we show a link between spaceflight and transcriptome patterns associated with dysregulation of lipid and extracellular matrix metabolism and altered transforming growth factor-beta signalling. A stronger response was seen in C57BL/6J mice than BALB/c. Genetic differences in hyaluronan metabolism between strains may confer protection against extracellular matrix remodelling through downregulation of epithelial-mesenchymal transition. We intend for our findings to contribute to development of new countermeasures against kidney disease in astronauts and people here on Earth.

Enhancing European capabilities for application of multi-omics studies in biology and biomedicine space research.

Following on from the NASA twins' study, there has been a tremendous interest in the use of omics techniques in spaceflight. Individual space agencies, NASA's GeneLab, JAXA's ibSLS, and the ESA-funded Space Omics Topical Team and the International Standards for Space Omics Processing (ISSOP) groups have established several initiatives to support this growth. Here, we present recommendations from the Space Omics Topical Team to promote standard application of space omics in Europe. We focus on four main themes: i) continued participation in and coordination with international omics endeavors, ii) strengthening of the European space omics infrastructure including workforce and facilities, iii) capitalizing on the emerging opportunities in the commercial space sector, and iv) capitalizing on the emerging opportunities in human subjects research.

First Characterization of the Transcriptome of Lung Fibroblasts of SSc Patients and Healthy Donors of African Ancestry.

Systemic sclerosis (SSc) is a connective tissue disorder that results in fibrosis of the skin and visceral organs. SSc-associated pulmonary fibrosis (SSc-PF) is the leading cause of death amongst SSc patients. Racial disparity is noted in SSc as African Americans (AA) have a higher frequency and severity of disease than European Americans (EA). Using RNAseq, we determined differentially expressed genes (DEGs; q < 0.1, log2FC > |0.6|) in primary pulmonary fibroblasts from SSc lungs (SScL) and normal lungs (NL) of AA and EA patients to characterize the unique transcriptomic signatures of AA-NL and AA-SScL fibroblasts using systems-level analysis. We identified 69 DEGs in "AA-NL vs. EA-NL" and 384 DEGs in "AA-SScL vs. EA-SScL" analyses, and a comparison of disease mechanisms revealed that only 7.5% of DEGs were commonly deregulated in AA and EA patients. Surprisingly, we also identified an SSc-like signature in AA-NL fibroblasts. Our data highlight differences in disease mechanisms between AA and EA SScL fibroblasts and suggest that AA-NL fibroblasts are in a "pre-fibrosis" state, poised to respond to potential fibrotic triggers. The DEGs and pathways identified in our study provide a wealth of novel targets to better understand disease mechanisms leading to racial disparity in SSc-PF and develop more effective and personalized therapies.

Space omics research in Europe: Contributions, geographical distribution and ESA member state funding schemes.

The European research community, via European Space Agency (ESA) spaceflight opportunities, has significantly contributed toward our current understanding of spaceflight biology. Recent molecular biology experiments include "omic" analysis, which provides a holistic and systems level understanding of the mechanisms underlying phenotypic adaptation. Despite vast interest in, and the immense quantity of biological information gained from space omics research, the knowledge of ESA-related space omics works as a collective remains poorly defined due to the recent exponential application of omics approaches in space and the limited search capabilities of pre-existing records. Thus, a review of such contributions is necessary to clarify and promote the development of space omics among ESA and ESA state members. To address this gap, in this review, we i) identified and summarized omics works led by European researchers, ii) geographically described these omics works, and iii) highlighted potential caveats in complex funding scenarios among ESA member states.

miRNA and lncRNA Expression Networks Modulate Cell Cycle and DNA Repair Inhibition in Senescent Prostate Cells.

Cellular senescence is a state of permanent growth arrest that arises once cells reach the limit of their proliferative capacity. It creates an inflammatory microenvironment favouring the initiation and progression of various age-related diseases, including prostate cancer. Non-coding RNAs (ncRNAs) have emerged as important regulators of cellular gene expression. Nonetheless, very little is known about the interplay of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and how deregulation of ncRNA networks promotes cellular senescence. To investigate this, human prostate epithelial cells were cultured through different passages until senescent, and their RNA was extracted and sequenced using RNA sequencing (RNAseq) and microRNA sequencing (miRNA-seq) miRNAseq. Differential expression (DE) gene analysis was performed to compare senescent and proliferating cells with Limma, miRNA-target interactions with multiMiR, lncRNA-target interactions using TCGA data and network evaluation with miRmapper. We found that miR-335-3p, miR-543 and the lncRNAs H19 and SMIM10L2A all play central roles in the regulation of cell cycle and DNA repair processes. Expression of most genes belonging to these pathways were down-regulated by senescence. Using the concept of network centrality, we determined the top 10 miRNAs and lncRNAs, with miR-335-3p and H19 identified as the biggest hubs for miRNAs and lncRNA respectively. These ncRNAs regulate key genes belonging to pathways involved in cell senescence and prostate cancer demonstrating their central role in these processes and opening the possibility for their use as biomarkers or therapeutic targets to mitigate against prostate ageing and carcinogenesis.

Antifibrotic factor KLF4 is repressed by the miR-10/TFAP2A/TBX5 axis in dermal fibroblasts: insights from twins discordant for systemic sclerosis.

OBJECTIVES: Systemic sclerosis (SSc) is a complex disease of unknown aetiology in which inflammation and fibrosis lead to multiple organ damage. There is currently no effective therapy that can halt the progression of fibrosis or reverse it, thus studies that provide novel insights into disease pathogenesis and identify novel potential therapeutic targets are critically needed. METHODS: We used global gene expression and genome-wide DNA methylation analyses of dermal fibroblasts (dFBs) from a unique cohort of twins discordant for SSc to identify molecular features of this pathology. We validated the findings using in vitro, ex vivo and in vivo models. RESULTS: Our results revealed distinct differentially expressed and methylated genes, including several transcription factors involved in stem cell differentiation and developmental programmes (KLF4, TBX5, TFAP2A and homeobox genes) and the microRNAs miR-10a and miR-10b which target several of these deregulated genes. We show that KLF4 expression is reduced in SSc dFBs and its expression is repressed by TBX5 and TFAP2A. We also show that KLF4 is antifibrotic, and its conditional knockout in fibroblasts promotes a fibrotic phenotype. CONCLUSIONS: Our data support a role for epigenetic dysregulation in mediating SSc susceptibility in dFBs, illustrating the intricate interplay between CpG methylation, miRNAs and transcription factors in SSc pathogenesis, and highlighting the potential for future use of epigenetic modifiers as therapies.

A Systems Approach to Interrogate Gene Expression Patterns in African American Men Presenting with Clinically Localized Prostate Cancer.

An emerging theory about racial differences in cancer risk and outcomes is that psychological and social stressors influence cellular stress responses; however, limited empirical data are available on racial differences in cellular stress responses among men who are at risk for adverse prostate cancer outcomes. In this study, we undertook a systems approach to examine molecular profiles and cellular stress responses in an important segment of African American (AA) and European American (EA) men: men undergoing prostate biopsy. We assessed the prostate transcriptome with a single biopsy core via high throughput RNA sequencing (RNA-Seq). Transcriptomic analyses uncovered impacted biological pathways including PI3K-Akt signaling pathway, Neuroactive ligand-receptor interaction pathway, and ECM-receptor interaction. Additionally, 187 genes mapping to the Gene Ontology (GO) terms RNA binding, structural constituent of ribosome, SRP-dependent co-translational protein targeting to membrane and the biological pathways, translation, L13a-mediated translational silencing of Ceruloplasmin expression were differentially expressed (DE) between EA and AA. This signature allowed separation of AA and EA patients, and AA patients with the most severe clinical characteristics. AA patients with elevated expression levels of this genomic signature presented with higher Gleason scores, a greater number of positive core biopsies, elevated dehydroepiandrosterone sulfate levels and serum vitamin D deficiency. Protein-protein interaction (PPI) network analysis revealed a high degree of connectivity between these 187 proteins.

Immunological and hematological outcomes following protracted low dose/low dose rate ionizing radiation and simulated microgravity.

Using a ground-based model to simulate spaceflight [21-days of single-housed, hindlimb unloading (HLU) combined with continuous low-dose gamma irradiation (LDR, total dose of 0.04 Gy)], an in-depth survey of the immune and hematological systems of mice at 7-days post-exposure was performed. Collected blood was profiled with a hematology analyzer and spleens were analyzed by whole transcriptome shotgun sequencing (RNA-sequencing). The results revealed negligible differences in immune differentials. However, hematological system analyses of whole blood indicated large disparities in red blood cell differentials and morphology, suggestive of anemia. Murine Reactome networks indicated majority of spleen cells displayed differentially expressed genes (DEG) involved in signal transduction, metabolism, cell cycle, chromatin organization, and DNA repair. Although immune differentials were not changed, DEG analysis of the spleen revealed expression profiles associated with inflammation and dysregulated immune function persist to 1-week post-simulated spaceflight. Additionally, specific regulation pathways associated with human blood disease gene orthologs, such as blood pressure regulation, transforming growth factor-ß receptor signaling, and B cell differentiation were noted. Collectively, this study revealed differential immune and hematological outcomes 1-week post-simulated spaceflight conditions, suggesting recovery from spaceflight is an unremitting process.

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.

Comprehensive Multi-omics Analysis Reveals Mitochondrial Stress as a Central Biological Hub for Spaceflight Impact.

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.

PALMER: improving pathway annotation based on the biomedical literature mining with a constrained latent block model.

BACKGROUND: In systems biology, it is of great interest to identify previously unreported associations between genes. Recently, biomedical literature has been considered as a valuable resource for this purpose. While classical clustering algorithms have popularly been used to investigate associations among genes, they are not tuned for the literature mining data and are also based on strong assumptions, which are often violated in this type of data. For example, these approaches often assume homogeneity and independence among observations. However, these assumptions are often violated due to both redundancies in functional descriptions and biological functions shared among genes. Latent block models can be alternatives in this case but they also often show suboptimal performances, especially when signals are weak. In addition, they do not allow to utilize valuable prior biological knowledge, such as those available in existing databases. RESULTS: In order to address these limitations, here we propose PALMER, a constrained latent block model that allows to identify indirect relationships among genes based on the biomedical literature mining data. By automatically associating relevant Gene Ontology terms, PALMER facilitates biological interpretation of novel findings without laborious downstream analyses. PALMER also allows researchers to utilize prior biological knowledge about known gene-pathway relationships to guide identification of gene-gene associations. We evaluated PALMER with simulation studies and applications to studies of pathway-modulating genes relevant to cancer signaling pathways, while utilizing biological pathway annotations available in the KEGG database as prior knowledge. CONCLUSIONS: We showed that PALMER outperforms traditional latent block models and it provides reliable identification of novel gene-gene associations by utilizing prior biological knowledge, especially when signals are weak in the biomedical literature mining dataset. We believe that PALMER and its relevant user-friendly software will be powerful tools that can be used to improve existing pathway annotations and identify novel pathway-modulating genes.

Prominence of IL6, IGF, TLR, and Bioenergetics Pathway Perturbation in Lung Tissues of Scleroderma Patients With Pulmonary Fibrosis.

Scleroderma-associated pulmonary fibrosis (SSc-PF) and idiopathic pulmonary fibrosis (IPF) are two of many chronic fibroproliferative diseases that are responsible for nearly 45% of all deaths in developed countries. While sharing several pathobiological characteristics, they also have very distinct features. Currently no effective anti-fibrotic treatments exist that can halt the progression of PF or reverse it. Our goal is to uncover potential gene targets for the development of anti-fibrotic therapies efficacious in both diseases, and those specific to SSc-PF, by identifying universal pathways and molecules driving fibrosis in SSc-PF and IPF tissues as well as those unique to SSc-PF. Using DNA microarray data, a meta-analysis of the differentially expressed (DE) genes in SSc-PF and IPF lung tissues (diseased vs. normal) was performed followed by a full systems level analysis of the common and unique transcriptomic signatures obtained. Protein-protein interaction networks were generated to identify hub proteins and explore the data using the centrality principle. Our results suggest that therapeutic strategies targeting IL6 trans-signaling, IGFBP2, IGFL2, and the coagulation cascade may be efficacious in both SSc-PF and IPF. Further, our data suggest that the expression of matrikine-producing collagens is also perturbed in PF. Lastly, an overall perturbation of bioenergetics, specifically between glycolysis and fatty acid metabolism, was uncovered in SSc-PF. Our findings provide insights into potential targets for the development of anti-fibrotic therapies that could be effective in both IPF and SSc-PF.

NASA GeneLab Platform Utilized for Biological Response to Space Radiation in Animal Models.

Background: Ionizing radiation from galactic cosmic rays (GCR) is one of the major risk factors that will impact the health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. The NASA GeneLab project has detailed information on radiation exposure using animal models with curated dosimetry information for spaceflight experiments. Methods: We analyzed multiple GeneLab omics datasets associated with both ground-based and spaceflight radiation studies that included in vivo and in vitro approaches. A range of ions from protons to iron particles with doses from 0.1 to 1.0 Gy for ground studies, as well as samples flown in low Earth orbit (LEO) with total doses of 1.0 mGy to 30 mGy, were utilized. Results: From this analysis, we were able to identify distinct biological signatures associating specific ions with specific biological responses due to radiation exposure in space. For example, we discovered changes in mitochondrial function, ribosomal assembly, and immune pathways as a function of dose. Conclusions: We provided a summary of how the GeneLab's rich database of omics experiments with animal models can be used to generate novel hypotheses to better understand human health risks from GCR exposures.

Mice Exposed to Combined Chronic Low-Dose Irradiation and Modeled Microgravity Develop Long-Term Neurological Sequelae.

Spaceflight poses many challenges for humans. Ground-based analogs typically focus on single parameters of spaceflight and their associated acute effects. This study assesses the long-term transcriptional effects following single and combination spaceflight analog conditions using the mouse model: simulated microgravity via hindlimb unloading (HLU) and/or low-dose γ-ray irradiation (LDR) for 21 days, followed by 4 months of readaptation. Changes in gene expression and epigenetic modifications in brain samples during readaptation were analyzed by whole transcriptome shotgun sequencing (RNA-seq) and reduced representation bisulfite sequencing (RRBS). The results showed minimal gene expression and cytosine methylation alterations at 4 months readaptation within single treatment conditions of HLU or LDR. In contrast, following combined HLU+LDR, gene expression and promoter methylation analyses showed multiple altered pathways involved in neurogenesis and neuroplasticity, the regulation of neuropeptides, and cellular signaling. In brief, neurological readaptation following combined chronic LDR and HLU is a dynamic process that involves pathways that regulate neuronal function and structure and may lead to late onset neurological sequelae.

GAIL: An interactive webserver for inference and dynamic visualization of gene-gene associations based on gene ontology guided mining of biomedical literature.

In systems biology, inference of functional associations among genes is compelling because the construction of functional association networks facilitates biomarker discovery. Specifically, such gene associations in human can help identify putative biomarkers that can be used as diagnostic tools in treating patients. Although biomedical literature is considered a valuable data source for this task, currently only a limited number of webservers are available for mining gene-gene associations from the vast amount of biomedical literature using text mining techniques. Moreover, these webservers often have limited coverage of biomedical literature and also lack efficient and user-friendly tools to interpret and visualize mined relationships among genes. To address these limitations, we developed GAIL (Gene-gene Association Inference based on biomedical Literature), an interactive webserver that infers human gene-gene associations from Gene Ontology (GO) guided biomedical literature mining and provides dynamic visualization of the resulting association networks and various gene set enrichment analysis tools. We evaluate the utility and performance of GAIL with applications to gene signatures associated with systemic lupus erythematosus and breast cancer. Results show that GAIL allows effective interrogation and visualization of gene-gene networks and their subnetworks, which facilitates biological understanding of gene-gene associations. GAIL is available at http://chunglab.io/GAIL/.

Primary cilia defects causing mitral valve prolapse.

Mitral valve prolapse (MVP) affects 1 in 40 people and is the most common indication for mitral valve surgery. MVP can cause arrhythmias, heart failure, and sudden cardiac death, and to date, the causes of this disease are poorly understood. We now demonstrate that defects in primary cilia genes and their regulated pathways can cause MVP in familial and sporadic nonsyndromic MVP cases. Our expression studies and genetic ablation experiments confirmed a role for primary cilia in regulating ECM deposition during cardiac development. Loss of primary cilia during development resulted in progressive myxomatous degeneration and profound mitral valve pathology in the adult setting. Analysis of a large family with inherited, autosomal dominant nonsyndromic MVP identified a deleterious missense mutation in a cilia gene, DZIP1 A mouse model harboring this variant confirmed the pathogenicity of this mutation and revealed impaired ciliogenesis during development, which progressed to adult myxomatous valve disease and functional MVP. Relevance of primary cilia in common forms of MVP was tested using pathway enrichment in a large population of patients with MVP and controls from previously generated genome-wide association studies (GWAS), which confirmed the involvement of primary cilia genes in MVP. Together, our studies establish a developmental basis for MVP through altered cilia-dependent regulation of ECM and suggest that defects in primary cilia genes can be causative to disease phenotype in some patients with MVP.

A Human Skin Model Recapitulates Systemic Sclerosis Dermal Fibrosis and Identifies COL22A1 as a TGFß Early Response Gene that Mediates Fibroblast to Myofibroblast Transition.

: Systemic sclerosis (SSc) is a complex multi-system autoimmune disease characterized by immune dysregulation, vasculopathy, and organ fibrosis. Skin fibrosis causes high morbidity and impaired quality of life in affected individuals. Animal models do not fully recapitulate the human disease. Thus, there is a critical need to identify ex vivo models for the dermal fibrosis characteristic of SSc. We identified genes regulated by the pro-fibrotic factor TGFß in human skin maintained in organ culture. The molecular signature of human skin overlapped with that which was identified in SSc patient biopsies, suggesting that this model recapitulates the dermal fibrosis characteristic of the human disease. We further characterized the regulation and functional impact of a previously unreported gene in the setting of dermal fibrosis, COL22A1, and show that silencing COL22A1 significantly reduced TGFß-induced ACTA2 expression. COL22A1 expression was significantly increased in dermal fibroblasts from patients with SSc. In summary, we identified the molecular fingerprint of TGFß in human skin and demonstrated that COL22A1 is associated with the pathogenesis of fibrosis in SSc as an early response gene that may have important implications for fibroblast activation. Further, this model will provide a critical tool with direct relevance to human disease to facilitate the assessment of potential therapies for fibrosis.

Molecular Profiling of RNA Tumors Using High-Throughput RNA Sequencing: Overview of Library Preparation Methods.

RNA sequencing (RNA-seq) is revolutionizing the study of cancer by providing a highly sensitive and robust tool to interrogate the transcriptome. It leverages the power of deep sequencing technology and provides global and multidimensional views of transcriptional landscapes in healthy and tumor tissues. Such information is contributing innovative insights to our understanding of the genetic basis of cancer and the progression of the disease. RNA-seq is a superior technology to DNA microarrays in that it provides digital rather than analog information on transcripts and their isoforms. The front end (sequencing library preparation and validation) is technically complex and time intensive. The primary objective in preparing a sequencing library is to eliminate or minimize bias, so that the library is reflective of the input RNA sample in terms of both sequence content and transcript abundance. This chapter describes the RNA-seq approach, and reviews methods and good practices for library preparation and sequencing.

Molecular Profiling of RNA Tumors Using High-Throughput RNA Sequencing: From Raw Data to Systems Level Analyses.

RNAseq is a powerful technique enabling global profiles of transcriptomes in healthy and diseased states. In this chapter we review pipelines to analyze the data generated by sequencing RNA, from raw data to a system level analysis. We first give an overview of workflow to generate mapped reads from FASTQ files, including quality control of FASTQ, filtering and trimming of reads, and alignment of reads to a genome. Then, we compare and contrast three popular options to determine differentially expressed (DE) transcripts (The Tuxedo Pipeline, DESeq2, and Limma/voom). Finally, we examine four tool sets to extrapolate biological meaning from the list of DE genes (Genecards, The Human Protein Atlas, GSEA, and ToppGene). We emphasize the need to ask a concise scientific question and to clearly under stand the strengths and limitations of the methods.