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At least 577 records · Page 32

Transcriptomic Changes in Peripheral Blood Mononuclear Cells of International Space Station Crewmembers

In space, living organisms are exposed to numerous stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. This study is part of the Functional Immune Project, intended to determine alterations in crewmembers` immunobiology before, during, and after spaceflight. For this project, blood samples were collected from International Space Station (ISS) crewmembers at the following time points: i) Blood was drawn at two pre-flight time points of 180 days (L180) and 45 days (L45) before launch. ii) During flight, blood was drawn at approximately the midpoint (mid-flight, MF) of the mission, and shortly before egress from the ISS (late-flight, LF). iii) Post-flight blood samples were collected within 36 hours (R0), 30 days (R30) and 90 days (R90) after landing. For each crewmember, blood was also drawn from a matching test subject on the ground at the corresponding time point. For both the ISS crewmembers and the ground control subjects, total RNA was isolated from peripheral blood mononuclear cells (PBMC) and mRNA was analysed using next generation RNA-sequencing (NGS). Differentially expressed genes were determined by performing contrast analysis. Using the ground control subjects of all time points combined as a control, a number of dysregulated genes were identified in astronauts at MF, LF and R0, including downregulations of SMAD7 and CDKN1A at MF and LF. Some of the genes such as SERPINE1 and VEGFA were downregulated at MF and LF, but upregulated at R0, while others such as NKG7 were down regulated at all 3 time points. Pathway analysis of these differentially expressed genes indicated that the NF-κB pathway was chronically activated in space. Analysis of the consequent diseases suggested potential associations with not only immune dysfunction, but also other health risks including osteoarthritis, cardiac hypertrophy and neuroinflammation.

Maria Moreno-Villanueva↗

Transcriptomic Changes in ISS Crewmembers Suggest Decreased Metabolic Activity in Peripheral Blood Mononuclear Cells

In space, living organisms are exposed to numerous stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. This study is part of the Functional Immune Project, intended to determine alterations in crewmembers` immunobiology before, during, and after spaceflight. For this project, blood samples were collected from International Space Station (ISS) crewmembers at the following time points: i) Blood was drawn at two pre-flight time points of 180 days (L180) and 45 days (L45) before launch. ii) During flight, blood was drawn at approximately the midpoint (mid-flight, MF) of the mission, and shortly before egress from the ISS (late-flight, LF). iii) Post-flight blood samples were collected within 36 hours (R0), 30 days (R30) and 90 days (R90) after landing. For each crewmember, blood was also drawn from a matching test subject on the ground at the corresponding time point. For both the ISS crewmembers and the ground control subjects, total RNA was isolated from peripheral blood mononuclear cells (PBMC) and mRNA was analysed using next generation RNA-sequencing (NGS). Differentially expressed genes were determined by performing contrast analysis. Using the ground control subjects of all time points combined as a control, a number of dysregulated genes were identified in astronauts at MF, LF and R0, Pathway analysis of these differentially expressed genes indicated that several of the pathways related to metabolism, including LXR/RXR, NAD signaling and fatty acid betta-oxidation, were downregulated at MF and LF. We suggest that the decreased metabolic activity in space may contribute to the immune dysfunction and delayed cell cycle progression as observed in the astronauts.

Maria Moreno-Villanueva↗

Batch Effect Correction Methods for NASA GeneLab Transcriptomic Datasets

RNA sequencing (RNA-seq) data from space biology experiments promise to yield invaluable insights into the effects of spaceflight on terrestrial biology. However, sample numbers from each study are low due to limited crew availability, hardware, and space. To increase statistical power, spaceflight RNA-seq datasets from different missions are often aggregated together. However, this can introduce technical variation or "batch effects", often due to differences in sample handling, sample processing, and sequencing platforms. Several computational methods have been developed to correct for technical batch effects, thereby reducing their impact on true biological signals. In this study, we combined 7 mouse liver RNA-seq datasets from NASA GeneLab (part of the NASA Open Science Data Repository) to evaluate several common batch effect correction methods (ComBat and ComBat-seq from the sva R package, and Median Polish, Empirical Bayes, and ANOVA from the MBatch R package). We quantitatively evaluated the ability of these methods to correct for technical batch variables in space biology RNA-seq data using the following criteria: BatchQC, principal component analysis, dispersion separability criterion, log fold change correlation, and differential gene expression analysis. Each batch variable / correction method combination was then assessed using a custom scoring approach to identify the optimal correction method for the combined dataset, by geometrically probing the space of all allowable scoring functions to yield an aggregate volume-based scoring measure. Finally, we describe the way in which the GeneLab multi-study analysis and visualization portal will allow users to examine the presence or absence of batch effects using multiple metrics. If the user chooses to perform batch effect correction, the scoring approach described here can be implemented to identify the optimal correction method to use for their specific combined dataset prior to analysis.

Lauren M. Sanders↗

Transcriptomic analysis of Clostridium thermocellum ATCC 27405 cellulose fermentation

The ability of Clostridium thermocellum ATCC 27405 wild-type strain to hydrolyze cellulose and ferment the degradation products directly to ethanol and other metabolic byproducts makes it an attractive candidate for consolidated bioprocessing of cellulosic biomass to biofuels. In this study, whole-genome microarrays were used to investigate the expression of C. thermocellum mRNA during growth on crystalline cellulose in controlled replicate batch fermentations. A time-series analysis of gene expression revealed changes in transcript levels of {approx}40% of genes ({approx}1300 out of 3198 ORFs encoded in the genome) during transition from early-exponential to late-stationary phase. K-means clustering of genes with statistically significant changes in transcript levels identified six distinct clusters of temporal expression. Broadly, genes involved in energy production, translation, glycolysis and amino acid, nucleotide and coenzyme metabolism displayed a decreasing trend in gene expression as cells entered stationary phase. In comparison, genes involved in cell structure and motility, chemotaxis, signal transduction and transcription showed an increasing trend in gene expression. Hierarchical clustering of cellulosome-related genes highlighted temporal changes in composition of this multi-enzyme complex during batch growth on crystalline cellulose, with increased expression of several genes encoding hydrolytic enzymes involved in degradation of non-cellulosic substrates in stationary phase. Overall, the results suggest that under low substrate availability, growth slows due to decreased metabolic potential and C. thermocellum alters its gene expression to (i) modulate the composition of cellulosomes that are released into the environment with an increased proportion of enzymes than can efficiently degrade plant polysaccharides other than cellulose, (ii) enhance signal transduction and chemotaxis mechanisms perhaps to sense the oligosaccharide hydrolysis products, and nutrient gradients generated through the action of cell-free cellulosomes and, (iii) increase cellular motility for potentially orienting the cells movement towards positive environmental signals leading to nutrient sources. Such a coordinated cellular strategy would increase its chances of survival in natural ecosystems where feast and famine conditions are frequently encountered.

09 BIOMASS FUELS↗