Spaceflight has several detrimental effects on the physiology of astronauts, many of which are recapitulated in rodent models. Mouse studies performed on the Space Shuttle showed disruption of lipid metabolism in liver. However, given that these animals were not sacrificed on-orbit and instead returned live to earth, it is unclear if these disruptions were solely induced by space stressors (e.g. microgravity, space radiation) or in part explained by the stress of return to Earth. In this work we analyzed three liver datasets from two different strains of mice (C57BL/6 (Jackson) & BALB/c (Taconic)) flown aboard the International Space Station (ISS). Notably, these animals were sacrificed on-orbit and exposed to varying spaceflight durations (i.e. 21, 37, and 42 days vs 13 days for the Shuttle mice). Oil Red O (ORO) staining showed abnormal lipid accumulation in all space-flown mice compared to ground controls regardless of strain or exposure duration. Similarly, transcriptomic analysis by RNA-sequencing revealed several pathways that were affected in both strains related to increased lipid metabolism, fatty acid metabolism, lipid and fatty acid processing, lipid catabolic processing, and lipid localization. In addition, key upstream regulators were predicted to be commonly regulated across all conditions including Glucagon (GCG) and Insulin (INS). Moreover, quantitative proteomic analysis showed that a number of lipid related proteins were changed in the livers during spaceflight. Taken together, these data indicate that activation of lipotoxic pathways are the result of space stressors alone and this activation occurs in various genetic backgrounds during spaceflight exposures of weeks to months. If similar responses occur in humans, a prolonged change of these pathways may result in the development of liver disease and should be investigated further.

To understand the physiological changes that occur in response to spaceflight, mice are transported to the International Space Station (ISS) and housed for variable periods of time before euthanasia on-orbit or return to Earth. Sample collection under such difficult conditions introduces confounding factors that need to be identified and addressed. We found large changes in the transcriptome of mouse tissues dissected and preserved on-orbit compared with tissues from mice euthanized on-orbit, preserved, and dissected after return to Earth. Changes due to preservation method eclipsed those between flight and ground samples, making it difficult to identify spaceflight-specific changes. Follow-on experiments to interrogate the roles of euthanasia methods, tissue and carcass preservation protocols, and library preparation methods suggested that differences due to preservation protocols are exacerbated when coupled with polyA selection. This has important implications for the interpretation of existing datasets and the design of future experiments.

To understand the physiological changes that occur in response to spaceflight, mice are transported to the International Space Station (ISS) and housed for variable periods of time before euthanasia on-orbit or return to Earth. Sample collection under such difficult conditions introduces confounding factors that need to be identified and addressed. We found large changes in the transcriptome of mouse tissues dissected and preserved on-orbit compared to tissues from mice euthanized on-orbit, preserved, and dissected after return to Earth. Changes due to preservation method eclipsed those between flight and ground samples making it difficult to identify spaceflight-specific changes. Follow-on experiments to interrogate the roles of euthanasia methods, tissue and carcass preservation protocols, and library preparation methods suggested that differences due to preservation protocols are exacerbated when coupled with polyA selection. This has important implications for the interpretation of existing datasets and the design of future experiments.

Introduction: 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.Methods: 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). Principal component analysis (PCA) was used to identify library preparation method and mission as the primary sources of batch effect among the technical variables in the combined dataset. We next quantitatively evaluated the ability of each of the indicated methods to correct for each identified technical batch variable using the following criteria: BatchQC, PCA, 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.Results and Discussion: Using the method described for the combined dataset in this study, the library preparation variable/ComBat correction method pair out ranked the other candidate pairs, suggesting that this combined dataset should be corrected for library preparation using the ComBat correction method prior to downstream analysis. We describe the GeneLab multi-study analysis and visualization portal which will allow users to access the publicly available space biology ‘omics data, select multiple studies to combine for analysis, and 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.

In spaceflight experiments, model organisms are used to assess the effects of microgravity on specific biological systems. In many cases, only one biological system is of interest to the Principal Investigator. To maximize the scientific return of experiments, the remaining spaceflight tissue is categorized, documented, and stored in the biobank at NASA Ames Research Center, which is maintained by the Ames Life Science Data Archive (ALSDA). The purpose of this study is to evaluate the state of a sample set of tissues from the ALSDA biobank. Garnering information – such as downstream functional analysis for the generation of omics datasets – from tissues is, in part, dependent on the state of sample preservation. RNA integrity number (RIN) values have been calculated for rodent liver tissues that were part of scientific payloads returned from the International Space Station (ISS). Rat livers from Spacelab Life Sciences 1 (SLS-1) and mouse livers from Commercial Biomedical Test Module 3 (CBTM-3), Rodent Research 1 (RR1), and Rodent Research 3 (RR3) were tested. It was found that mean RIN values from CBTM-3, RR1, and RR3 were suitable for downstream functional analysis (RIN > 5) while the mean RIN value for SLS-1 was not (RIN = 2.5 ± 0.1). Information from this study lays the foundation for future efforts in determining the types of assays that are most appropriate for different tissues in the ALSDA biobank and similar preservation facilities, which would aid in shaping the design of experiments.