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NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗

NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Machine Learning↗

NASA NTRSDate not supplied

Histological and Transcriptomic Analysis of Spaceflight-Induced Ocular Changes in the Mouse Retina

Anatomical changes have been observed in astronauts’ eyes after long duration spaceflight missions. These alterations can lead to visual impairment which in part constitutes the spaceflight-associated neuroocular syndrome (SANS), one of the top risk priorities for deep space missions. The HRP Systems Biology (SysBio) Translation Project will apply systems biology approaches utilizing current human physiological spaceflight data, molecular results from rodents, and future research with a multi-level, multi-system, and multi-species perspective to augment the existing research plan to resolve the SANS risk. Not much is known about SANS at the cellular and molecular level, but studies in mice and rats have recently begun to determine how spaceflight might affect the biology of the eye. Preliminary studies of mice that flew on the Space Shuttle, and more recently the International Space Station (ISS), have shown changes in retinal physiology as assessed by histology and gene expression analysis. The study presented here obtained samples from the CASIS sponsored Rodent Research 8 Experiment delivered to the ISS by SpaceX CRS-16 on 12/08/2018. Female BALB/cAnNTac mice flew on the ISS for 45 days, while ground controls were housed in a standard vivarium or animal enclosure module. Sacrifice and sample acquisition occurred once mice returned to Earth, possibly allowing for readaptation affecting retinal homeostasis. We applied standard transcriptomic (RNAseq) and histological approaches to characterize genes and pathways in the mouse retina affected by spaceflight or age. The differentially expressed gene (DEG) data was analyzed using Galaxy (GeneLab) and Ingenuity Pathway Analysis. Significant DEGs between flight and ground samples were relatively few but biologically meaningful. Pathways identified related to neuronal differentiation, cellular transport/movement, and wound healing. Age effects were detected between the young (10–12 weeks) and old (32 weeks) groups and between the baseline and end of experiment (~46 days). The biological relevance of specific DEGs were confirmed through immunohistochemical evaluation using fixed histological sections of the eye from four flight group mice and four habitat control mice. Staining was performed specific for synaptophysin, glial fibrillary acidic protein (GFAP), and neurofilament in the retinal periphery, equator, and peripapillary regions. For synaptophysin staining, the innerplexiform and outerplexiform layers were scored; for GFAP staining, Mueller cells and perivascular astrocytes were scored. Results show flight samples typically had more staining of GFAP and neurofilament while, conversely, the habitat control group had more staining of synaptophysin.

C. Perez↗

NASA NTRS2011

Effects and Responses to Spaceflight in the Mouse Retina

Several stress environmental factors are combined in a unique fashion during spaceflight, affecting living beings widely across their physiological systems. Recently, attention has been placed on vision changes in astronauts returning from long duration missions. Alterations include hyperoptic shift, globe flattening, choroidal folds and optic disc edema, which are probably associated with increased intracranial pressure. These observations justify a better characterization of the ocular health risks associated with spaceflight. This study investigates the impact of spaceflight on the biology of the mouse retina. Within a successful tissue sharing effort, eyes from albino Balb/cJ mice aboard STS-133 were collected for histological analysis and gene expression profiling of the retina at 1 and 7 days after landing. Both vivarium and AEM (Animal Enclosure Module) mice were used as ground controls. Oxidative stress-induced DNA damage was higher in the flight samples compared to controls on R+1, and decreased on R+7. A trend toward higher oxidative and cellular stress response gene expression was also observed on R+1 compared to AEM controls, and these levels decreased on R+7. Several genes coding for key antioxidant enzymes, namely, heme-oxygenase-1, peroxiredoxin, and catalase, were among those upregulated after flight. Likewise, NF B and TGFbeta1, were upregulated in one flight specimen that overall showed the most elevated oxidative stress markers on R+1. In addition, retinas from vivarium control mice evidenced higher oxidative stress markers, NF B and TGFbeta1, likely due to the more intense illumination in vivarium cages versus the AEM. These preliminary data suggest that spaceflight represents a source of environmental stress that translates into oxidative and cellular stress in the retina, which is partially reversible upon return to Earth. Further work is needed to dissect the contribution of the various spaceflight factors (microgravity, radiation) and to evaluate the impact of the stress response on retinal health.

Zanello, Susana B.↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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) 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 24 hrs (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 of the 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 of the 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↗

NASA NTRSDate not supplied

A Pipeline for Assessing the Quality of Rna-Seq Datasets in GeneLab

Transcriptome profiling by RNA sequencing (RNA-seq) is a powerful approach to identify gene expression changes in organisms exposed to unique environments such as spaceflight. One of the challenges of evaluating RNA-seq data both within and across different space-relevant studies is the ability to control for technical differences, including the use of different library preparation kits, sequencing platforms, RNA yield, and person-to-person variation. To help address this issue, the National Institute of Standards and Technology (NIST, nist.gov) initiated a consortium, at the request of industry and academia, to develop a set of controls for gene expression measurements. The result was a set of 92 unlabeled, polyadenylated transcripts that range from 250 – 2,000 nucleotides in length to mimic natural eukaryotic mRNAs. These External RNA Controls Consortium (ERCC) genes can be used in any RNA-seq experiment, by adding known concentrations of the ERCC genes to samples after RNA extraction, to offer a standard measurement for data comparison. At NASA GeneLab, we employ these controls as part of our standard operating procedures for every in-house RNA-seq study to assess the limit of detection, dynamic range, and power of differential expression analysis both within and across experiments. Here we will discuss the use, benefits, and limitations of ERCC genes and other types of controls, such as universal RNA references, to generate quality control information for RNA-seq studies conducted at GeneLab.

GeneLab↗

NASA NTRS2017

Network Analysis of Rodent Transcriptomes in Spaceflight

Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.

genomics↗

NASA NTRS2019

Deciphering the Effects of Microgravity Cell by Cell

Forces generated by gravity have a profound impact on the behavior of cells in tissues affecting the course of the cell cycle and differentiation fate of progenitors in mammalian tissues. These cells are contributing to normal tissue regenerative health and defence against disease. In Human space exploration context, it is extremely important to determine spaceflight provoked changes in tissue's regenerational capabilities. Microgravity experienced during spaceflight causes unloading and mechanical disuse on all orthostatic support tissues, therefore impacting stem cell fate and lineage commitment decisions. Investigating how ESCs respond to mechanical stimulation is a platform for fundamental developmental and regeneration research applicable for spaceflight. However, the gene expression programs associatiated with early committment stem cell pathways in response to physical stimulation are not readily known. Single-cell RNA-seq technologies have recently revolutionized the world of molecular biology by providing the capability to assess gene expression pattern within a single cell. Our method isolates and separately barcodes mRNAs from thousands of single cells and sequences their expressomes. Understanding regenerative processes on a molecular level would not only help reduce long-term spaceflight impact on health, but also may enable the development of novel tissue regenerative approaches to tissue degeneration on Earth.

Single cell sequencing↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets such as sex or age of the model organism used. In the present study, NASA GeneLab-hosted RNAseq datasets from rodent liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC, to determine statistical differences between datasets before and after correction, Principal Component Analysis, to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the standard approach. Thus, the most robust standard correction will be implemented in the GeneLab Visualization 2.0 platform when datasets are combined.

GeneLab, RNA-seq, Batch Correction↗

NASA NTRSDate not supplied

Evaluation of Correction Methods for NASA GeneLab Transcriptomic Datasets

Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. The results showed that the reference-based approach introduced several additional (and likely artificial) DEGs when compared with the respective standard approach. Of the methods tested, standard ComBat and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

GeneLab↗

NASA NTRS1998

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗

NASA NTRS2017

Renin-Angiotensin System (RAS) in Hematopoietic Stem/Progenitor Cells (HS/PC) Predicts Vaso-Reparative Dysfunction and Progression of Diabetic Retinopathy (DR)

Purpose: We tested the hypothesis that loss of angiotensin converting enzyme 2 (ACE2) within diabetic HS/PCs (Hematopoietic Stem/Progenitor Cells) would be detrimental to HS/PC reparative function, and alter their ability to contribute to vascular remodeling in human subjects and rodent models of DR (Diabetic Retinopathy). Methods: Subjects (n52) were recruited as controls (n13) or diabetics (n39) with either no DR, mild non-proliferative DR (NPDR), moderate NPDR, severe NPDR or proliferative DR (PDR). Fluorescein angiograms were analyzed using Vessel Generation Analysis (VESGEN) software in a cohort of subjects. CD34+ HS/PCs were isolated from peripheral blood. RAS (Renin-Angiotensin System) gene expression and migration was measured. Diabetic ACE2 knockout (KO)C57BL6-Ins2 (Akita) mice at 3, 6 and 9 months of diabetes were compared to age-matched controls. Bone marrow HS/PC populations were analyzed by flow cytometry and migration and proliferation studies performed. Results: ACE2 gene expression in human CD34+ cells from diabetics without DR was increased compared to controls (p0.0437). Mas receptor mRNA was also increased in diabetics without DR, but reduced with the onset of NPDR (p0.0002), suggesting a loss of compensation. DR was associated with CD34+ cell migratory dysfunction. By VESGEN analysis, vessel density measured by several confirming parameters in early NPDR (n3) was greater than in normal retina (n6) in both arteries and veins, which suggests active retinal remodeling. ACE2KO-Akita and Akita cohorts showed reduced retinal thickness by OCT (Optical Coherence Tomography) at 9 months of diabetes. Absence of ACE2 in 9-month Akita mice led to an accelerated increase in acellular capillaries compared to diabetic alone. Electroretinogram (ERG) in ACE2KO-Akita mice resulted in persistent deterioration of the neural retina. Reparative function studies showed that ACE2KO exacerbated diabetes-induced impairment of LK (Low Potassium) cell migration and proliferative functions as early as 3-month of diabetes (p0.0019). Conclusions: Retinopathy and adverse vascular remodeling in subjects with diabetes was associated with a loss of the protective arm of RAS in HS/PCs. Loss of ACE2 exacerbated vascular dysfunction in diabetic mice.

retina↗

NASA NTRS1997

Up-regulation of cyclooxygenase-2 by product-prostaglandin E2

The development of prostate cancer has been linked to high level of dietary fat intake. Our laboratory investigates the connection between cancer cell growth and fatty acid products. Studying human prostatic carcinoma PC-3 cells, we found that prostaglandin E2 (PGE2) increased cell growth and up-regulated the gene expression of its own synthesizing enzyme, cyclooxygenase-2 (COX-2). PGE2 increased COX-2 mRNA expression dose-dependently with the highest levels of stimulation seen at the 3-hour period following PGE2 addition. The NSAID flurbiprofen (5 microM), in the presence of exogenous PGE2, inhibited the up-regulation of COX-2 mRNA and cell growth. These data suggest that the levels of local intracellular PGE2 play a major role in the growth of prostate cancer cells through an activation of COX-2 gene expression.

NASA Discipline Cell Biology↗

NASA NTRS1998

Arabidopsis thaliana responses to mechanical stimulation do not require ETR1 or EIN2

Plants exposed to repetitive touch or wind are generally shorter and stockier than sheltered plants. These mechanostimulus-induced developmental changes are termed thigmomorphogenesis and may confer resistance to subsequent stresses. An early response of Arabidopsis thaliana to touch or wind is the up-regulation of TCH (touch) gene expression. The signal transduction pathway that leads to mechanostimulus responses is not well defined. A role for ethylene has been proposed based on the observation that mechanostimulation of plants leads to ethylene evolution and exogenous ethylene leads to thigmomorphogenetic-like changes. To determine whether ethylene has a role in plant responses to mechanostimulation, we assessed the ability of two ethylene-insensitive mutants, etr1-3 and ein2-1, to undergo thigmomorphogenesis and TCH gene up-regulation of expression. The ethylene-insensitive mutants responded to wind similarly to the wild type, with a delay in flowering, decrease in inflorescence elongation rate, shorter mature primary inflorescences, more rosette paraclades, and appropriate TCH gene expression changes. Also, wild-type and mutant Arabidopsis responded to vibrational stimulation, with an increase in hypocotyl elongation and up-regulation of TCH gene expression. We conclude that the ETR1 and EIN2 protein functions are not required for the developmental and molecular responses to mechanical stimulation.

Non-NASA Center↗

NASA NTRS1998

Simulated Microgravity Induced Cytoskeletal Rearrangements are Modulated by Protooncogenes

Microgravity is the environment living systems encounter during space flight and gravitational unloading is the effect of this environment on living systems. The cell, being a multiphasic chemical system, is a useful starting point to study the potential impact of gravity unloading on physiological function. In the absence of gravity, sedimentation of organelles including chromosomes, mitochondria, nuclei, the Golgi apparatus, vacuoles, and the endoplasmic reticulum may be affected. Most of these organelles, however, are somewhat held in place by cytoskeleton. Hansen and Igber suggest that intermediate filaments act to stabilize the nuleus against rotational movement, and integrate cell and nuclear structure. The tensegrity theory supports the idea that mechanical or physical forces alters the cytoskeletal structures of a cell resulting in the changes in cell: matrix interactions and receptor-signaling coupling. This type of stress to the cytoskeleton may be largely responsible regulating cell shape, growth, movement and metabolism. Mouse MC3T3 El cells under microgravity exhibited significant cytoskeletal changes and alterations in cell growth. The alterations in cytoskeleton architecture may be due to changes in the expression of actin related proteins or integrins. Philopott and coworkers reported on changes in the distribution of microtubule and cytoskeleton elements in the cells of heart tissue from space flight rats and those centrifuged at 1.7g. Other researchers have showed that microgravity reduced EGF-induced c-fos and c-jun expression compared to 1 g controls. Since c-fos and c-jun are known regulators of cell growth, it is likely that altered signal transduction involving protooncogenes may play a crucial role in the reduced growth and alterations in cytoskeletal arrangements found during space flight. It is clear that a microgravity environment induces a number of changes in cell shape, cell surface molecules, gene expression, and cytoskeletal reorganization. However the underlying mechanism for these cellular changes have not been clearly defined. We examined alterations in endothelial migration, and cytoskeleton architecture (microfilamentous f-actin and vimentin-rich- intermediate filaments) following wounding under simulated microgravity. We also examined the possibility that altered signal transduction pathways, involving protooncogenes, may play a crucial role in microgravity-induced retardation of cell migration and alterations in cytoskeletal organization. We hypothesize that, based on the tensegrity theory, cytoskeletal organization respond to gravitational unloading and through this response, cell behavior, function and gene expression are modified.

Melhado, C. D.↗

NASA NTRS2017

Responses of Cardiac Tissue to Simulated Weightlessness

Our current study aims to determine the molecular mechanisms that underlie these cardiac changes in response to spaceflight. The central hypothesis of our study is that long duration simulated weightlessness and subsequent recovery causes select and persistent changes in gene expression and oxidative defense-related pathways. In this study, we will first conduct general analyses of three-month old male and female animals, focusing on two key long-duration time points, (i.e. after 90 days of simulated weightlessness (HU) and after 90 days recovery from 90 days of HU. Both rat-specific gene arrays and qPCR will be performed focusing on genes already implicated in oxidative stress responses and cardiac disease. Gene expression analyses will be complemented by biochemical tests of frozen tissue lysates for select markers of oxidative damage.

heart↗

NASA NTRS2016

Biospecimen Retrieval from NASA's Rodent Research-1: Maximizing Science Return from Flight Missions

Rodent Research (RR)-1 was conducted to validate flight hardware, operations, and science capabilities that were developed to support long duration missions on the International Space Station. After 37 days in microgravity twenty mice were euthanized and frozen on orbit. Upon return to Earth the carcasses were dissected and yielded 32 different types of tissues from each mouse and over 3200 tissue aliquots. Many tissues were distributed to the Space Life and Physical Sciences (SLPS) Biospecimen Sharing Program (BSP) Principal Investigators (PIs) through the Ames Life Science Data Archive (ALSDA). A second round of dissections was performed to collect additional tissues from the remaining carcasses thawed for a second time for additional BSP PIs. Tissues retrieved included vaginal walls, aorta, pelvis, brown adipose tissue, tail, spine and forearms. Although the analyses are still in progress, some of the PIs have reported that the quality of the tissues was acceptable for their study. In a separate experiment we tested the RNA quality of the tissues that were dissected from frozen carcasses that were subjected to euthanasia, freezing, first and second thaw dissections. Timelines simulated the on-orbit RR-1 procedures to assess the quality of the tissues retrieved from the second thaw dissections. We analyzed the RIN values of select tissues including kidney, brain, white adipose tissue (WAT) and brown adipose tissue (BAT). Overall the RIN values from the second thaw were lower compared to those from the first by about a half unit; however, the tissues yielded RNA that are acceptable quality for some quantitative gene expression assays. Interestingly, RIN values of brain tissues were 8.4+/-0.6 and 7.9+/-0.7 from first and second round dissections, respectively (n5). Kidney and WAT yielded RIN values less than 8 but they can still be used for qPCR. BAT yielded higher quality RNA (8.2+/-0.5) than WAT (5.2+/-20.9), possibly due to the high fat content. Together, these data show that select tissues can be utilized for gene expression studies even if they are retrieved from carcasses that were subjected to at least two freezing and thawing processes; this further expands science return from valuable and infrequent rodent experiments in space.

rodents↗