Shared Metabolic Remodeling Processes Characterize the Transcriptome of Arabidopsis thaliana within Various Suborbital Flight Environments

The analysis of spaceflight- and gravity-associated effects on plants is key to understanding the fundamental impact of the novel environment of spaceflight, as well as for the improvement of astroculture habitats and potential crop species. The interest in the effects of microgravity and spaceflight environments on terrestrial biology increases with the desire to expand the horizons of human exploration. Access to long-term spaceflight-induced microgravity currently remains restricted to the International Space Station (ISS), but long-term exposure to the orbital environment is only one aspect of the effect that spaceflight has on biology. Understanding the effects of short-term microgravity exposure and the transition into and from altered gravity environments provide insights into the mechanisms of physiological adaptation to these unfamiliar situations. Parabolic aircraft flights, sounding rockets, and drop towers are useful for short-term microgravity exposures and exploration of transitions between gravity states. Suborbital human-rated spacecraft are increasingly available as commercial platforms for research payloads that are specialized for observing short-term and spaceflight-transitional microgravity effects in living systems. Experiments within flight vehicles enable comparisons that inform future studies and better characterize the short-term spaceflight and altered gravity responses (AGRs) of biology, including those of the model plant Arabidopsis thaliana.

The spaceflight response of plants has been characterized using a variety of hardware, approaches, and flight platforms, yet some generalized aspects of the spaceflight response have emerged. Light signaling and photosynthesis, heat and cold responses, cell wall remodeling, defense responses, drought responses, hypoxic responses, and reactive oxygen species (ROS) responses are among the biological processes commonly noted as altered in spaceflight (Paul et al., 2005a; Paul et al., 2012b; Correll et al., 2013; Zupanska et al., 2013; Sugimoto et al., 2014; Kwon et al., 2015; Johnson et al., 2017; Paul et al., 2017; Choi et al., 2019; Zhou et al., 2019; Califar et al., 2020). Direct comparisons of the transcriptomic data of multiple spaceflight experiments, processed using a singular pipeline, corroborate the conserved alteration of oxidative stress responses, ROS signaling, and mitochondrial function (Barker et al., 2020). Furthermore, though the precise patterns of spaceflight transcriptomes in Arabidopsis ecotypes can vary among independent experiments of similar design, similar metabolic processes are conserved in their spaceflight responses (Paul et al., 2012b; Paul et al., 2013; Kwon et al., 2015; Johnson et al., 2017). The transcriptomic response of Arabidopsis to spaceflight is also genotype-dependent in studies using multiple Arabidopsis ecotypes (Paul et al., 2017; Choi et al., 2019; Califar et al., 2020). Therefore, remodeling of processes conserved across experiments and unique to Arabidopsis genotypes has been observed in spaceflight responses. Comparisons of transcriptomic data from suborbital and other altered gravity flight platforms enable characterization of both the platforms and the processes that are involved in the short-term responses of Arabidopsis genotypes to flights on these platforms.

Parabolic flights and drop towers are perhaps the most widely used platforms for atmospheric microgravity research. The parabolic flight pattern involves cycles of hypergravity acceleration upward, followed by a 20–30 s free-fall period of microgravity. Drop towers offer 2–5 s of pure free fall. Drop tower exposures have yet to be deeply explored for biological research; however, parabolic flights have been extensively used to characterize biological responses to altered gravity at distinct points within flights. The transcriptomic responses of Arabidopsis, sampled at up to forty parabolas, show differential expression of genes in key metabolic processes such as auxin metabolism, calcium signaling, cell wall remodeling, defense, light signaling, temperature stress responses, ROS signaling and responses, and metabolism involving carbon and/or nitrogen (Paul et al., 2011; Aubry-Hivet et al., 2014; Hausmann et al., 2014; Fengler et al., 2016). Calcium and ROS signaling pathways are induced in parabolic flight, in conjunction with phosphoproteomic changes associated with these processes and carbon metabolism (Toyota et al., 2013; Hausmann et al., 2014). Thus, remodeling of central processes is indicated by shifts in disparate signaling and response pathways in both spaceflight and altered gravity conditions.

The breadth of the spaceflight and AGRs across core metabolism and signal transduction pathways raise the question of which genes have the potential to have major impacts on the spaceflight response. A loss of function mutation in a single gene can have significant impacts on the spaceflight-induced transcriptomic response of plants, manifesting both as decreases in the number of differentially expressed genes (DEGs), such as in phyD light signaling mutants, or as increases in the cases of cell lines defective in the arg1 gravitropism and hsfA2 heat shock genes and the sku5 root skewing mutant (Paul et al., 2017; Zupanska et al., 2017; Zupanska et al., 2019; Califar et al., 2020). An increase in DEGs in response to spaceflight may indicate that a genotype is less robust than the comparable wild type. For instance, the sku5 mutant shows reduced germination in spaceflight in conjunction with a large increase in DEGs (Califar et al., 2020). The sensitivity of the sku5 mutants to spaceflight may be connected to the potential role of SKU5 in an auxin-responsive signaling pathway modulating the plant TARGET OF RAPAMYCIN (TOR) complex, which connects skewing to centralized environmental and endogenous signaling pathways regulating energy expenditure and growth (Sedbrook et al., 2002; Xu et al., 2014; Schepetilnikov et al., 2017; Schultz et al., 2017; Ryabova et al., 2019; Zhou, 2019; Califar et al., 2020). Suborbital flight enables a dissection of some of the transcriptomic effects seen in sku5 during spaceflight growth from those observed in a short-term exposure to spaceflight.

Genes encoding signal transduction proteins can have large impacts on metabolism not only when they are deleted but also when they are overexpressed, as is the case for 14-3-3 regulatory proteins (Diaz et al., 2011; Shin et al., 2011). The 14-3-3 proteins bind a variety of client proteins dependent on the phosphorylation states of clients, regulating protein function, stability, and localization (Denison et al., 2011; Camoni et al., 2018). The 14-3-3 kappa isoform (14-3-3κ) regulates myriad processes such as carbon and nitrogen metabolism, light signaling, brassinosteroid signaling, ethylene signaling, calcium signaling, salt responses, temperature responses, and pathogen responses (Kanamaru et al., 1999; Gampala et al., 2007; Diaz et al., 2011; Shin et al., 2011; Wang et al., 2011; Yoon and Kieber, 2013; Adams et al., 2014; van Kleeff et al., 2014; Yasuda et al., 2014; Zhou et al., 2014; Liu et al., 2017; Huang et al., 2018; Chen et al., 2019; Yang et al., 2019). Skewing-associated and 14-3-3κ-regulated pathways thus overlap with processes altered in parabolic flight and/or spaceflight experiments.

This paper explores the transcriptomic responses of different genotypes of Arabidopsis across a variety of vehicles representing a diversity of gravity environments. The data reported here were developed from two different atmospheric parabolic flight platforms and two suborbital rocket flights, all using human-activated harvests of Arabidopsis before, after, and, in some cases, during the flights. Our goal is to explore the operational possibilities of using multiple flight platforms to develop insights into biological responses to spaceflight, which will enhance the overall understanding of the range of physiological adaptations that occur during spaceflight.

Multiple analytical approaches and several genotypes were used over the collection of flights involved in these experiments. Individual DEGs, enriched GO terms, and enriched pathways in the KEGG database were examined, and these data are provided in Supplementary File 1. The PF2013 and F-104 experiments used the 14-3-3κ:GFP overexpression line in the WS background, BO used the sku5 mutant, and other samples were of the WS wild type (Figure 1A). The conserved and unique components of the transcriptomic data corresponding to the AGRs were the primary points of interest due to the variety of platforms and genotypes used.

The DEG count, timing, and composition of the overall transcriptomic responses to altered gravity were modulated by both genotype and platform (Figure 2A). The transcriptomic response of VG WS consisted of a small number of DEGs of high fold-change. The BO dataset contrasted VG, where both BO WS and BO sku5 required more DEGs of predominantly lower fold-changes. Within the PF2015 experiment, more DEGs were measured in the earlier time-points, and the response of WS diminished over the experimental time course. In contrast, the PF2013 AGR required more DEGs than that of PF2015 at each shared time-point, and this count increased from P1 to P10. The F-104 dataset was reminiscent of both PF2013 and PF2015, where a larger number of DEGs were involved in the response, but this response diminished across the experimental time course in both F-104 flights. DEGs in PF2013, PF2015, and F-104 that were conserved across multiple time-points within each experiment tended to retain their directionality of differential expression. The magnitude of transcriptional response in PF2013 at P10 (1,005 DEGs) was comparable to that seen in BO WS (865 DEGs) and sku5 (923 DEGs), whereas PF2015 P10 was among the smallest of the responses (41 DEGs). Together, the noted trends demonstrated the interplay between genotypic and platform-specific effects.

Coordinately expressed DEGs were identified across transcriptomic comparisons, despite differences in experimental workflows and parameters. However, the overlap between VG and BO was minimal, and different genes were engaged despite the similarity between their altered-gravity exposure profiles (Figures 1A and 2B). Within BO, WS and sku5 shared a greater proportion of DEGs than were unique to each genotype, and the shared DEGs were generally of similar fold-change in each genotype (Figures 2A and 2B). The majority of the PF2015 DEGs were shared with other experiments, and the level of overlap with PF2013 was highest (Figure 2C). PF2013, however, overlapped most with the F-104 data, though many of these DEGs opposed in directionality between the two experiments (Figures 2A and 2C). The overlapping DEGs were also well-represented across the longer PF2013 time course, but were mostly represented early in the F-104 flight profiles (Figure 2A).

Figure 2

Conserved and unique processes were identified among these transcriptomic responses to altered gravity (Figure 3). All experiments, with the exception of VG WS, were enriched with GO terms in at least one time-point. Responses to antibiotics, hypoxia, and oxidative stress were among those that were conserved across all experiments. However, the conserved terms were overrepresented among upregulated DEGs in BO and F-104, and downregulated DEGs in BO, PF2013, and PF2015. The enrichment of the conserved terms differed across the time spans of PF2013, where they were enriched throughout, and PF2015, where they were enriched at early time-points. Less-conserved terms that were shared between three experiments included nitrogen responses, sulfur metabolism, and the response to karrikins. The least-conserved terms included defense-associated responses, senescence-associated processes, flavonoid metabolism, and branched-chain amino acid (BCAA) metabolism. Each experiment also showed unique process enrichments. BO WS and sku5 were enriched for water transport, protein ubiquitination, and pigment metabolism. BO WS was uniquely enriched in nitrogen responses, cell wall remodeling, and the aforementioned BCAA metabolism, while sku5 uniquely showed a response to iron. A separate analysis that used only DEGs that were unshared between BO WS and sku5 revealed that the sku5-specific aspect of the response was enriched with glutathione and phenylpropanoid metabolism genes (data not shown). Processes unique to PF2015 were associated with sulfur metabolism, defense responses, and metal ion homeostasis. The PF2013 dataset was enriched in DEGs annotated to signal transduction, oligopeptide and terpenoid transport, and amino acid metabolism. The unique aspects of F-104 responses involved protein folding, carbohydrate metabolism, and photosynthetic processes. Thus, comparisons of GO term enrichments identified links between the experiments in specific stress-responsive biological processes.

Figure 3

KEGG pathway mapping illuminated specific metabolic steps with varying levels of conservation between the experiments (Figure 4). The combined DEG lists for each experiment, with the exception of VG WS and BO sku5, were mapped against the KEGG metabolic pathways, and the individual maps for each experiment were overlaid to visualize different levels of pathway conservation. Altered pathways conserved between all experiments were distinguished with red, and they were generally associated with valine, leucine, and isoleucine degradation, nitrogen metabolism, starch and carbon metabolism, and glutathione metabolism. The conserved pathways represented metabolic remodeling events that were required in some fashion in the AGR regardless of genotypic or platform-specific differences between PF, F-104, and BO. Less-conserved changes encompassed a much wider area of these centralized metabolic pathways, as well as a small number of peripheral pathways.

Figure 4

A mixture of fully and less-conserved pathways were also identified as enriched among the DEG data, some of which were associated with the pathway nodes identified as conserved in metabolic pathway mapping (Figures 4 and 5A). As in the GO term analysis, VG WS showed no KEGG pathway enrichments (Figures 3 and 5A). All other experiments showed an enrichment of general metabolic pathways, as illustrated in Figure 4, and the valine, leucine, and isoleucine degradation pathway. The BO WS and sku5 DEGs were the most significantly enriched with genes annotated to KEGG pathways, and PF2015 showed the lowest levels of enrichment, with PF2013 and F-104 falling in between. The timing of the enrichment also differed between PF2015 and F-104, which showed early responses, and PF2013, which was enriched across a wider timescale later in the experiment. Less-conserved pathway enrichments were associated with the biosynthesis of secondary metabolites, flavonoids, phenylpropanoids, glutathione metabolism, and the MAPK signaling pathway. BO was uniquely enriched in alanine, aspartate and glutamate metabolism, and nitrogen metabolism. BO WS and sku5 differed, with WS being enriched in glucosinolate biosynthesis, glycine, serine, threonine, and tryptophan metabolism, and starch and sucrose metabolism. The only pathway overrepresented in BO sku5 but not in BO WS was glutathione metabolism, which was also shared with PF2015 and PF2013. PF2015 showed enrichments in sulfur and propanoate metabolism, whereas PF2013 showed enrichment in alpha-linolenic and linoleic acid metabolism. The F-104 DEGs were enriched with protein processing in the endoplasmic reticulum and galactose metabolism, and these DEGs mapped specifically to the ER-associated degradation subsection of this protein processing pathway (data not shown). The KEGG enrichments thus outlined the involvement of metabolic remodeling processes generally associated with amino acids, carbon, and sulfur in the AGR.

Isolation of DEGs annotated to enriched pathways demonstrated that DEGs from each experiment generally mapped to the pathways, regardless of the conservation of enrichment (Figures 5A and 5B). The number of DEGs that mapped to the conserved pathways reflected the overall transcriptomic load seen in that experiment, which indicated that the level of metabolic remodeling was proportional to the DEG count of the overall response, in a manner similar to the pathway enrichments (Figures 2 and 5). The alterations in specific pathways were made with a mixture of DEGs that were shared or unique. Examples of different DEGs within a pathway being altered included protein processing in the ER and glutathione metabolism. The same genes being differentially expressed were seen most clearly in the flavonoid biosynthetic pathway between BO and PF2013, and in the valine, leucine, and isoleucine degradation pathway. Some DEGs were also overlapped in their pathway annotations, indicating that these DEGs served overarching functions in the metabolic remodeling required of the AGR. Together, the data showed that the lack of conservation of a pathway enrichment in an experiment did not preclude alteration of that pathway as part of the AGR.

Figure 5

The conservation of an enrichment of the valine, leucine, and isoleucine degradation pathway prompted a closer analysis, and revealed that each of the experiments had examples of differentially expressed genes from this pathway, although not all examples were coordinately expressed (Figures 5 and 6). DEGs associated with this BCAA degradation pathway tended toward up- and/or downregulation on an experimentally dependent basis, with only F-104 showing a mixture of directionality at the node representing the first step of the pathway. In this manner, BO WS and PF2013 tended toward upregulation whereas PF2015 and F-104 tended toward downregulation. BO sku5 showed an almost identical response to BO WS within this pathway, whereas VG WS DEGs did not map to this pathway; both were excluded as a result (data not shown). The majority of nodes that showed a similar pattern that, when upregulated, may then be involved in the movement of BCAAs toward the production of coenzyme A-linked compounds suitable for energy production. Both BO WS and PF2013 showed downregulation in only one node that represented a step catalyzing the conversion of 2-methylacetoacetyl-CoA to acetyl-CoA. This pattern, shared by both BO WS and the PF2013 experiment, was not seen in the other parabolic experiment (PF2015).

Figure 6

Atmospheric parabolic flights, such as those in F-104, C-9, and B727 aircraft, currently provide capabilities for in-flight human activities and sample preservation, and the data presented here include samples taken by human operators at different portions of the flight profiles within those vehicles. While BO and VG may soon provide similar capabilities for their suborbital spacecraft, sampling is presently limited to access only after the vehicles have landed. Therefore, the data presented here represent the aggregate effects of the entire suborbital flight profiles in comparison to the experiences at various time-points in the parabolic flights. Even so, conserved and unique aspects of the transcriptomes were identified among the flight experiments, the parsing of which allowed for platform- and flight profile-specific and genotypic inferences regarding the processes and pathways that characterize these flight responses.

The metabolic processes most commonly affected across the flights were those associated with responses to hypoxia, oxidative stress, remodeling of central carbon and nitrogen metabolism, and alterations of the degradation pathway for Branched Chain Amino Acids (BCAA; valine, leucine, and isoleucine) (Figures 3–6). The specific characteristics of these metabolic responses were greatly influenced by the genotype of the plant, as seen by the distinctive gene expression patterns in the sku5 knockout and 14-3-3κ:GFP overexpression lines compared to the WS wild-type genotype (Figures 2, 3, 5A, and 6). Altering the contribution of even a single gene changes the manner in which a plant responds to these altered gravity environments, suggesting that these responses are genetically controlled. The genome-dependent nature of the parabolic and suborbital responses conceptually links these short-term responses to the long-term acclimations to spaceflight observed on orbit (Paul et al., 2017; Zupanska et al., 2017; Zupanska et al., 2019; Califar et al., 2020).

The WS genotype responded with many more DEGs to flight on BO than either VG or PF2015, and each platform elicited a largely unique response profile (Figure 2). Those differences in DEG response profiles, alongside the noted differences in fold-changes of DEGs in BO WS and VG WS, indicated that the aggregate suborbital flight experiences were differentially impactful, with a more robust response of BO WS remaining detectable at the time of sampling post-flight (Figure 2A). The difference in response is likely related to the differing VG and BO flight and g-profiles, with VG having a 1 h pre-suborbital flight period and BO reaching higher maximal levels of hyper-g. In contrast to the suborbital flight samples, PF2015 parabolic samples were fixed during the flight at progressive time-points (Figures 1A and 1C). In the multi-parabola PF2015 WS experiment, the transcriptomic response at later time-points is greatly reduced compared to earlier time-points despite cyclical restimulation of seedlings (Figures 1A and 2A). This trend of a recovery type response may explain the reduced transcriptomic response of VG WS, but the inability for sample fixation during suborbital flight is an operational limitation that precludes the validation of this hypothesis at present. However, WS has exhibited transcriptomic responses at 20 and 40 parabolas, indicating that the responses observed in this study may correspond to a non-specific response that is disengaged and then replaced by distinct acclimatized responses over time (Paul et al., 2011).

The 14-3-3κ:GFP overexpression line responded to parabolic flight in a manner distinct from wild-type WS, indicating that it was differentially sensitive to the flight profiles. The 14-3-3κ:GFP line showed more DEGs than WS at all time-points shared between PF2013 and PF2015 experiments, and demonstrated higher enrichment of stress-associated GO terms and KEGG pathways over a wider range of time-points (Figures 2A, 2C, 3, and 5A). The 14-3-3 proteins associate with calcium signaling and ROS burst pathways, which are induced in Arabidopsis exposed to parabolic flight, suggesting that disruption of these pathways may be responsible for this differential response (Hausmann et al., 2014; Lozano-Durán et al., 2014; Zhou et al., 2014; Yang et al., 2019). In a less direct manner, 14-3-3κ:GFP may impact the AGR through its links to spaceflight-associated signaling processes such as defense, light, and ROS signaling (Adams et al., 2014; Lozano-Durán et al., 2014; Huang et al., 2018). However, a complementary explanation may be that the basal reduction of available metabolites, including amino acids and starches, and alteration of C/N ratio signaling in 14-3-3κ overexpression lines may impair the ability of 14-3-3κ:GFP plants to physiologically adapt to altered gravity environments (Diaz et al., 2011; Shin et al., 2011; Yasuda et al., 2014). This interpretation is supported by the KEGG pathway data, in which 14-3-3κ:GFP plants tended to respond more similarly to BO WS than PF2015 WS (Figures 5 and 6). These data together suggest that the 14-3-3κ:GFP overexpression mutant is more highly sensitive to altered gravity than is WS.

The sku5 mutant line presents distinct responses to spaceflight environments as compared to the WS wild-type, both when grown entirely in the ISS (Califar et al., 2020) and in the shorter flight profiles presented here (Figures 2A, 2B, 3, and 5). The primary components of the orbital sku5 spaceflight response are an elevated DEG count comprising gene signatures of osmotic stress, abscisic acid (ABA) responses associated with growth regulation and germination, and the plant TOR signaling cascade via AUXIN-BINDING PROTEIN 1 (Shimomura, 2006; Xu et al., 2014; Schepetilnikov et al., 2017; Zhou, 2019; Califar et al., 2020). The sku5 suborbital transcriptome showed GO term or KEGG pathway enrichment levels in processes associated with glutathione, BCAA, starch, and nitrogen metabolism (Figures 2A, 2B, 3, and 5). These data collectively support the hypothesis that SKU5 acts upstream of centralized stress-responsive TOR signaling in its contribution to both short-and long-term spaceflight responses (Califar et al., 2020).

Hypoxic and oxidative stress, BCAA degradation, and carbon and nitrogen metabolism all interact to regulate energy generation and expenditure (Figures 3, 5A, and 6) (Geigenberger, 2003). Hypoxia tolerance requires both increased starch catabolism and constraint of energy-consuming anabolic processes involving carbon and nitrogen due to the energy limitations imposed by reduction of O₂ availability within tissues (Geigenberger, 2003; Loreti et al., 2018). Though the starch and sucrose metabolism pathway was not generally enriched across all flights, all experiments did have DEGs mapping within the starch and sucrose metabolism pathway (Figure 5). BCAA degradation pathways similarly augment energy production in energy-deprived conditions (Figures 5 and 6) (Cavalcanti et al., 2017). Though enrichments associated with the BCAA degradation pathway have not appeared in previous parabolic flight transcriptomes at higher parabola counts, the BCAA transaminase 7 (BCAT7) gene has been identified as a DEG at 30 parabolas (Paul et al., 2011; Aubry-Hivet et al., 2014; Hausmann et al., 2014; Fengler et al., 2016). The divergent responses of WS and 14-3-3κ:GFP to parabolic flight may be due to the involvement of 14-3-3κ in carbon and nitrogen metabolism and changes in basal metabolite pools (Figures 2A, 2C, and 6) (Kanamaru et al., 1999; Diaz et al., 2011; Shin et al., 2011). Thus, it is possible that central metabolic pathways are transiently altered in a conserved manner to produce the metabolic state required to facilitate the hypothesized early and non-specific portion of AGRs, which are less relevant on longer timescales (Figures 3, 5, and 6).

The modulation of the TOR signaling pathway by the potential interaction of SKU5 with auxin signaling pathways known to regulate TOR activity (e.g., Schepetilnikov et al., 2017; Zhou et al., 2019) suggests that a web of several interacting metabolic processes modulate the response of plants to altered gravity or other aspects of these flight profiles. We have hypothesized that this central signaling regulates spaceflight-induced stress responses (e.g., Califar et al., 2020), which have been characterized by changes in disparate but related processes including light signaling and defense responses (Paul et al., 2012b; Correll et al., 2013; Paul et al., 2017; Choi et al., 2019). TOR signaling regulates autophagy and senescence, as well as resource reallocation mechanisms (Ryabova et al., 2019; Signorelli et al., 2019) that are similarly connected to light signaling and defense processes (Buchanan-Wollaston et al., 2005; Yoshimoto et al., 2009; De Vleesschauwer et al., 2018). BCAAs also affect TOR activity directly (Cao et al., 2019). Furthermore, BCAA and starch metabolism are affected by light signaling, being elevated under dark treatments, and BCAAs are produced via protein catabolism dependent on functional autophagy pathways under energy-deprivation conditions (Barros et al., 2017; Hirota et al., 2018). Altered phytohormone signaling processes are enriched within longer-duration parabolic flight transcriptomic responses but not in the short-term responses examined here (Figure 3; Paul et al., 2011; Aubry-Hivet et al., 2014; Hausmann et al., 2014; Fengler et al., 2016). Therefore, early responses to microgravity may transiently alter central signaling and metabolism, which could then lead to long-term alterations in phytohormone signaling and new homeostatic set points associated with common spaceflight response signatures.

The transcriptomic data derived from these diverse human-rated parabolic and suborbital flight platforms reveal the common involvement of certain central metabolic processes in the physiological adjustment to these flight profiles that present entry into, and exit from, microgravity. These metabolic processes also play a role in sustained plant growth wholly within microgravity environments such as in the ISS. While the specific DEGs may differ, the common involvement of these processes among such diverse platforms, vehicles, and environments presents a compelling notion that these pathways help define the underlying strategies that guide adaptation to altered gravity environments. However, validation of this concept for early spaceflight acclimation requires rigorous experimental replication, which must include temporal resolution of the response profiles, especially during suborbital flight profiles. Through increased development of human tended suborbital flight capabilities, the initial concepts outlined here can be further refined and understood, allowing deeper insights into the mechanisms that terrestrial biology uses to acclimate to changes in the spaceflight environment.