The Rel/NF-κB pathway and transcription of immediate early genes in T cell activation are inhibited by microgravity

Transactivation of immediate early genes, especially targets of the Rel/NFκB pathway, is disrupted in T cells activated in microgravity.

Abstract

This study tested the hypothesis that transcription of immediate early genes is inhibited in T cells activated in μg. Immunosuppression during spaceflight is a major barrier to safe, long-term human space habitation and travel. The goals of these experiments were to prove that μg was the cause of impaired T cell activation during spaceflight, as well as understand the mechanisms controlling early T cell activation. T cells from four human donors were stimulated with Con A and anti-CD28 on board the ISS. An on-board centrifuge was used to generate a 1g simultaneous control to isolate the effects of μg from other variables of spaceflight. Microarray expression analysis after 1.5 h of activation demonstrated that μg- and 1g-activated T cells had distinct patterns of global gene expression and identified 47 genes that were significantly, differentially down-regulated in μg. Importantly, several key immediate early genes were inhibited in μg. In particular, transactivation of Rel/NF-κB, CREB, and SRF gene targets were down-regulated. Expression of cREL gene targets were significantly inhibited, and transcription of cREL itself was reduced significantly in μg and upon anti-CD3/anti-CD28 stimulation in simulated μg. Analysis of gene connectivity indicated that the TNF pathway is a major early downstream effector pathway inhibited in μg and may lead to ineffective proinflammatory host defenses against infectious pathogens during spaceflight. Results from these experiments indicate that μg was the causative factor for impaired T cell activation during spaceflight by inhibiting transactivation of key immediate early genes.

Introduction

There is growing international interest to return humans to the moon and explore onward toward Mars. Spaceflight immunosuppression is recognized as a major obstacle to longer-term human space travel required for these missions and remains incompletely understood [1]. There is mounting evidence that increased pathogen virulence [2] combined with weakened host immune responses in μg, 10⁻³–10⁻⁶ of 1g experienced in orbital spaceflight, poses a double jeopardy for human health in space [1]. In addition to its importance for optimizing human health for space travel, understanding the mechanism of how μg dysregulates immune responses will improve our understanding of normal immune responses and of immunosuppressed conditions here on earth [3].

The first evidence of immunosuppression during spaceflight was observed in returning astronauts of the Apollo and Skylab missions [4]. More than 50% of the Apollo astronauts experienced respiratory, gastrointestinal, urinary tract, or skin infections [5]. Numerous studies have described changes in leukocyte subsets in humans and animals after spaceflight. Blood samples taken from Shuttle astronauts postflight demonstrated increased numbers of neutrophils and decreased or unchanged numbers of lymphocytes [6, 7]. Experimental rats [8, 9] and mice [10] after spaceflight demonstrated decreased absolute numbers of circulating T and B lymphocytes. Importantly, activation of lymphocytes isolated from crew members after spaceflight was depressed [11]. Splenocytes from rats harvested during spaceflight demonstrated significantly lower proliferation in response to mitogen stimulation [12]. There was also evidence that cytokine responses were altered by spaceflight. The production of IFN-γ was inhibited significantly in activated rat splenocytes after spaceflight [13], and the response of bone marrow cells to GM-CSF was depressed [14, 15]. Moreover, DTH reactions mediated by CD4⁺ Th1 cells and macrophages were markedly decreased in astronauts during flight missions compared with preflight [16]. Lowered DTH responses strongly suggested that proinflammatory Th functions were impaired during spaceflight and that the susceptibility of astronauts to infections would be increased.

Although stress-related neuroendocrine factors may play a role in some of the immunological alterations observed during and after spaceflight [17], in vitro experiments with isolated lymphocytes demonstrated that μg impaired T cell functions independent of systemic factors. Experiments on board Spacelab 1 demonstrated that human PBLs stimulated with the T cell mitogen Con A for 3 days in spaceflight had profoundly suppressed T cell proliferation compared with ground controls, as measured by ³H-thymidine incorporation [18]. Sounding rocket experiments showed that fluorescently tagged Con A bound to T cells normally in μg, and the processes of patching and capping were comparable between 1g and μg conditions [19], indicating that inhibition of T cell proliferation was not at the level of agonist binding. Follow-up spaceflight experiments demonstrated that PBLs stimulated with Con A in μg produced significantly lower levels of IL-2, IL-2R, IFN-γ, and TNF [20] and that exogenous addition of IL-2 did not rescue proliferative activity in μg [21]. Similar findings were demonstrated in “simulated μg”, in which cells were cultured in ground-based machines, such as the clinostat, random positioning machine, or RWV that generated a residual 10⁻³g force that approximated μg [22, 23]. In ongoing studies, the Hughes-Fulford Laboratory has found similar levels of gene expression when activation was initiated using anti-CD3/anti-CD28 bead or Con A/anti-CD28 activation for human and mouse T cells under 1g and with reduced expression under μg conditions (unpublished results). T cells activated with anti-CD3 alone or anti-CD3 plus anti-CD28 demonstrated significantly decreased surface expression of CD25 (high-affinity IL-2R or IL-2Rα) and CD69 (early T cell activation marker) in μg and simulated μg compared with 1g [24]. Moreover, transcription of IL-2 and IL-2Rα mRNA is decreased significantly in T cells activated in simulated μg compared with 1g [25]. These experiments indicated that spaceflight immunosuppression was at least in part a result of impaired T cell activation and proliferation as a result of decreased IL-2 and IL-2Rα induction.

Further experiments began to delineate the T cell signal transduction pathways that may be dysregulated in μg leading to impaired IL-2 and IL-2Rα production. Our lab characterized the global gene expression of T cells after 4 h of stimulation with Con A and anti-CD28 and reported significant down-regulation of 99 genes in simulated μg compared with 1g. In addition to IL-2 and IL-2Rα, expression of many important proinflammatory cytokines and chemokines were inhibited. Promoter region analysis indicated that activation of transcription factors NF-κB, CREB, Ets-like protein-1, AP-1, and STAT was likely impaired, leading to the down-regulation of those genes [26]. Indeed, phosphorylation of CREB was decreased significantly in T cells activated in simulated μg [26]. Upstream signal transduction pathways potentially involved include PKA and/or PKC, and both are capable of activating and phosphorylating CREB [27, 28]. The PKA catalytic subunit (PKAc) can also phosphorylate RelA (p65), the transactivating subunit of the NF-κB dimeric complex, and increase its transcriptional activity independent of cAMP [28, 29]. We have shown that phosphorylation of CREB in T cells stimulated with Con A and anti-CD28 required PKA activation [27]. Other investigators showed that CREB phosphorylation, after cross-linking of CD3 alone or CD3 with CD28, was dependent on the PKC/Ras/MAPK and calcium/calmodulin pathways [30, 31].

Moreover, PKCθ is an important signal transduction molecule in T cell activation. Phosphorylated PKCθ activates the Ras/MAPK pathway and downstream transcription factor AP-1 [32]. PKCθ also acts immediately upstream of NF-κB activation by phosphorylating IKKβ, which leads to IκBα degradation and the release of sequestered NF-κB for nuclear translocation [33, 34]. Localization of PKC to the cellular membrane fraction is reduced upon activation of T cell and monocyte cell lines with phorbol esters in μg [35, 36]. This is potentially significant, as localization of PKCθ to cell surface membrane supramolecular activation complexes is required for its activation [32]. However, phosphorylation of PKC is intact in T cells activated in μg [26]. Of note, phosphorylation of other proximal T cell activation signal transduction molecules, including LAT and PI3K, is also comparable between μg and 1g [26]. These findings illustrate that the specific mechanisms of how μg causes dysregulated T cell activation are still unclear and that further research is required to determine the earliest events disrupted in μg that lead to spaceflight immunosuppression.

The LEUKIN spaceflight experiment reported here determined the global gene expression pattern of human T cells after 1.5 h of stimulation by Con A and anti-CD28 to identify the immediate early genes whose transcription may be inhibited in μg. Important to the experimental design was the KUBIK facility aboard the ISS that provided simultaneously static μg positions and onboard 1g centrifuge positions. This approach avoided potential variability introduced by vibrational launch forces, temperature differences, and cosmic radiation that may confound the interpretation of biological differences between spaceflight and ground-control samples. Analysis of the microarray data characterized the earliest transcriptional events inhibited in μg and identified the upstream mediators affected. Detailed examination of the 47 genes most significantly down-regulated in μg after 1.5 h of activation demonstrated inhibition of key IER genes, as opposed to the secondary response genes determined at 4 h of activation (e.g., IL-2). Promoter analysis revealed that the Rel/NF-κB pathway was the principal transcription pathway inhibited in very early T cell activation in μg. Finally, pathway analysis of the down-regulated genes predicted that downstream TNF effector functions would be severely disrupted in μg.

MATERIALS AND METHODS

Flight-mission profile

Whole peripheral blood was obtained from four human volunteers. Red blood cells were lysed and PBLs, isolated using Ficoll gradients. Human T cells were purified further using enrichment columns, per the manufacturer's instructions (R&D Systems, Minneapolis, MN, USA). Human T cells were resuspended into RPMI 1640 with 10% FCS and loaded at 7 × 10⁶ cells/chamber into the spaceflight hardware, LYCIS. The spaceflight hardware consisted of eight cassettes, each with four chambers. Some units had smart-button temperature data-storage capability, and temperatures of the containers were tracked for the duration of the mission. T cells from each donor were kept separate and loaded into four individual chambers in separate cassettes for the following treatments: μg-nonactivated, μg-activated, and 1g-activated. Units were loaded 1 day prior to mission launch and stored in insulated pouches. On September 18, 2006, the experimental units were launched into space on board the Soyuz 13S (TMA-09) rocket from Baikonur, Kazakhstan. Prior to the inflight experimental procedures, cassettes were kept in ambient temperatures that ranged from 16°C to 22°C. On Flight Day 3, cassettes were transferred to the ISS and placed into the KUBIK facility at 36.5°C. The 1g units were placed in the central centrifuge positions and centrifuged with an applied 1g force. The μg units were placed in the static positions for continued μg exposure. After 30 min of preincubation, μg-nonactivated units were fixed by addition of RNAlater (Qiagen, Valencia, CA, USA), removed from the incubator, and stored in 4°C. The μg- and 1g-activated units were injected with final concentration 10 microgram/ml Con A and 4 microgram/ml anti-CD28. These cassettes were replaced into KUBIK on the centrifuge or static positions and activated for 1.5 h. Activation was stopped with the addition of RNAlater, and the units were then moved to 4°C storage. All units were returned to earth upon Soyuz landing on September 28, 2006, and transported to the investigators' laboratory for analysis.

RNA isolation

RNA was isolated using RNeasy mini kit (Qiagen), according to the manufacturer's protocol. The samples were then stored at −80°C until further analysis. Isolated RNA from spaceflight samples were all of high quality with initial 260 nm/280 nm values between 1.75 and 2.2.

Microarray sample preparation and analysis

Initial RNA integrity was verified by the Agilent 2100 bioanalyzer (Santa Clara, CA, USA). Three of the four donor samples were chosen from each condition for microarray hybridization (Donors 1–3 for μg- and 1g-activated and Donors 1, 2, and 4 for μg-nonactivated), based on the highest RNA quality, as determined by the RNA integrity number. All four donor RNA samples for each condition were subsequently evaluated by qRT-PCR for selected differentially regulated genes (see below in Materials and Methods). For microarray hybridization, RNA was amplified and biotinylated using the MessageAmp II-Biotin Enhanced Kit, per the manufacturer's instructions (Ambion, Austin, TX, USA). Biotinylated amplified RNA (10 micrograms) was hybridized on to the Human U133 Plus 2.0 Array (Affymetrix, Santa Clara, CA, USA) through the University of California, San Francisco, Gladstone Institute Genomics Core (San Francisco, CA, USA).

Microarray data were analyzed using the GeneSpring GX 11.0.2 software (Silicon Genetics, Redwood City, CA, USA) and the GC-RMA algorithm. The background normalization was set to the average level of expression in μg-nonactivated T cells. Statistical analysis was performed using one-way ANOVA and the Benjamini-Hochberg multiple testing correction with P < 0.05. Post hoc Tukey analysis was performed to identify genes significantly, differentially regulated between 1g- and μg-activated samples. Significant genes were further filtered for a twofold or greater difference in expression between 1g- and μg-activated samples to generate the final gene list of 47 genes. MIAME (Minimum Information About a Microarray Experiment) –compliant microarray data can be found under the accession number GSE38836 and are posted on http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE38836.

Promoter region analysis

We used the oPOSSOM Web-based program to identify over-representation of TFBSs in the 47 genes most significantly inhibited in μg. oPOSSOM is a validated algorithm that identifies statistically over-represented TFBSs within a set of coregulated genes compared with a database of conserved TFBSs derived from phylogenetic footprinting enriched for functional binding sites. The search for TFBS was limited to within 2000 nucleotides upstream of the transcription start site. The two calculated statistical scores, when used in combination (Z-score >10 and Fisher score <0.01), correctly identified the regulating transcription factor in reference gene sets and results in only a false-positive rate of 15% in random gene sets [37].

qRT-PCR

RNA (1.5 micrograms) was added to 30 μl RT reaction buffer containing 5 mM MgCl₂, 10 mM Tris-HCl (pH 8.3), 50 mM KCl, 1 mM dNTPs, 2.5 μM oligo d(T) primer, 2.5 U/μl Moloney murine leukemia virus, and 1 U/μl RNase inhibitor. The reaction was incubated at room temperature for 10 min, 42°C for 30 min, inactivated at 99°C for 5 min, and cooled at 5°C for 5 min. cDNA (2 μl) from the RT reaction was added to 20 μl qRT-PCR mixture containing 10 μl 2× SYBR Green PCR Master Mix (Applied Biosystems, Foster City, CA, USA) and 12 pmol oligonucleotide primers. PCRs were carried out in a Bio-Rad MyiQ Single-Color Real-Time PCR detection system (Hercules, CA, USA). The thermal profile was 50°C for 2 min, 95°C for 10 min to activate the Taq polymerase, followed by 40 amplification cycles, consisting of denaturation at 95°C for 1 min, annealing at 63°C for 1 min, and elongation at 72°C for 1 min. Fluorescence was measured and used for quantitative purposes. At the end of the amplification period, melting curve analysis was performed to confirm the specificity of the amplicon. RNA samples were normalized to CPHI internal standard. Relative quantification of gene expression was calculated by using the 2^{ΔΔcomparative threshold} equation. All data derived using qRT-PCR were from independent biological samples (n=4).

RWV culture and T cell activation

CD4⁺ T cells from four human donors were isolated from blood bank leukocyte reduction system containers (Stanford Blood Center, Stanford, CA, USA) by Ficoll gradient, followed by Dynal Human CD4 Negative Isolation Kit (Life Technologies, Grand Island, NY, USA). The cells were resuspended in RPMI-1640 media with 10% FBS at 3 × 10⁶/ml. Disposable high-aspect ratio vessels (10 ml capacity) were filled with the cell suspension. Simulated μg samples were prerotated at 14 rpm for 2 h, while 1g samples were preincubated in a stationary position at 37°C. After the preincubation period, cells were stimulated with the addition of Dynabeads Human T-Activator CD3/CD28 beads (Life Technologies) to a final concentration of 2.4 × 10⁵ beads/ml. Samples were incubated for another 1.5 h at 14 rpm (simulated μg samples) or at a stationary position (1g samples). After 1.5 h of activation, cells were collected for RNA analysis.

RESULTS

T cells activated in 1g and μg have distinct gene expression patterns

T cells were purified from four human volunteers and launched into orbit on board the Soyuz 13S rocket from Baikonur, Kazakhstan. To control for experimental variables, samples stimulated with Con A and anti-CD28 were located inside of the KUBIK facility on the static positions (μg) or on the centrifuge positions. The centrifuge was set up to apply a 1g force, as the earth's gravity control, on the samples. In this way, all samples experienced the same launch forces, temperature variations, culture conditions, and cosmic radiation, and the only difference was the presence or absence of 1g gravitational force during the experiment. After 1.5 h of activation, cells were fixed in RNAlater while in orbit. Upon return to earth, the preserved RNA samples were analyzed with the Affymetrix Human U133 microarray gene chip. Data were normalized by the GC-RMA algorithm, and genes with statistically significant differential expression among the conditions of μg-nonactivated, μg-activated, and 1g-activated were identified by ANOVA analysis.

A total of 617 differentially expressed genes was identified (Fig. 1). Nonactivated T cells from the three donors demonstrated distinct gene expression patterns reflecting the environmental and genetic backgrounds of the individual donor. μg-Nonactivated samples from each donor constituted a separate individual branch in sample clustering analysis (horizontal clustering tree, yellow columns). Upon activation with Con A and anti-CD28 in 1g, the gene expression patterns of the three donors became significantly more uniform and clustered together (blue columns). This indicated that, as expected, common pathways and genes were being induced in T cells of the three donors upon activation in 1g. Importantly, samples from the same three donors activated in μg clustered together separately from 1g-activated samples (red columns). The clustered μg-activated samples demonstrated statistically significant differences from 1g-activated samples in overall gene expression pattern. Common pathways and genes of T cell activation were inhibited or suppressed in μg compared with 1g in all three donors. Taken together, these results are powerful evidence that there are fundamental alterations in early T cell activation events in reduced gravity conditions.

Figure 1. Differentially regulated genes 1.5 h after T cell activation in μg and 1g.

Each column represents the expression profile of an individual donor. Red-labeled columns are T cells activated in μg, blue-labeled columns are T cells activated in 1g, and yellow-labeled columns are μg-nonactivated T cells. A total of 617 genes is differentially expressed compared with the nonactivated control. There is baseline variability of gene expression between the donors in nonactivated T cells. After activation, the gene expression patterns of the donors become remarkably uniform. This is reflected in the condition clustering tree displayed horizontally across expression columns. The gene expression clustering tree along the vertical axis segregates the expression pattern of these genes into six groups (A–F). NA, Nonactivated; μg Act, μg-activated; 1g Act, 1g-activated.

More detailed analysis showed that the differentially expressed genes may be segregated into six distinct groups by gene expression clustering (Fig. 1, vertical axis clustering tree). Group A consisted of 72 genes that demonstrated increased expression in μg- and 1g-activated T cells compared with nonactivated T cells, and expression in 1g T cells was significantly higher than μg. Group B had 315 genes significantly induced in μg- and 1g-activated T cells compared with nonactivated, with no difference in level of expression between activated μg and 1g. Group C showed 77 genes in which expression was several-fold greater in 1g- compared with μg-activated T cells. Group D included six genes in which expression was increased in μg-activated T cells but not 1g-activated T cells. Group E consisted of 127 genes with significantly decreased expression in μg- and 1g-activated T cells compared with nonactivated and no difference between activated μg and 1g. Finally, Group F included 20 genes in which expression was slightly decreased in μg-activated samples but even more significantly decreased in 1g-activated samples compared with nonactivated μg samples.

Overall, 72% (315 genes in Group B and 127 genes in Group E) of the differentially regulated genes in T cell activation was regulated similarly between T cells activated in μg and 1g. Many more genes were up-regulated after T cell activation in μg and 1g (75%; Groups A–C) than were down-regulated (24%; Groups E and F) compared with nonactivated T cells. Expression of 12% of the genes (Group A; 72 genes) was induced upon μg activation but significantly lower than T cells activated in 1g. This group may represent genes in pathways that were relatively inhibited in μg in a gradation of response. Another 12% of the genes (Group C; 77 genes) demonstrated expression that was minimally induced or not induced at all in μg-activated T cells compared with the highly up-regulated expression levels in 1g-activated T cells. These genes likely participated in pathways that were inhibited even more profoundly in the μg environment.

The significance of the clustering of sample gene expression patterns is illustrated further by principal components analysis (Fig. 2). The mathematical representation of the principal variances of the gene expression dataset demonstrates that the nonactivated donor leukocytes had distinct individual gene expression characteristics. After activation in 1g or μg, the gene expression from all donors clustered closer together, indicating up-regulation of common T cell activation genetic programs. T cell samples activated in μg clustered closely together and separately from those activated in 1g. Whereas the 1g and μg samples clustered comparably along the x-axis, they distinguished themselves along the y- and z-axes. This gives the overall mathematical impression that the majority of genes expressed in 1g-activated T cells is also expressed in μg-activated T cells. A few specific genetic programs are differentially regulated in μg-activated T cells, resulting in the distinct clustering from the 1g-activated T cells.

Figure 2. Principal component analysis of the 617 differentially regulated genes in μg-activated, 1g-activated, and nonactivated T cells.

The donor T cells that were not activated are distributed in a scattered pattern (yellow). T cells activated in μg clustered together (red), and the T cells activated in 1g clustered together in a distinct group (blue).

T cell proliferation and differentiation genes are inhibited in T cells activated in μg

To determine the genes most significantly modulated by the presence or absence of 1g during T cell activation, post hoc Tukey analysis was performed on the 617 genes that were identified by ANOVA analysis. Differentially regulated genes were further filtered for twofold or greater expression difference between μg- and 1g-activated samples. This resulted in 47 genes for which expression was twofold or higher in 1g-activated compared with μg-activated samples. There were no genes for which expression was twofold or higher in μg compared with 1g.

As presented in Table 1, the 47 genes are annotated through a combination of Gene Ontogeny Analysis, Online Mendelian Inheritance in Man, Uniprot, Entrez, and PubMed searches. The genes are broadly classified by biologic process, which includes apoptosis, antiapoptosis, cell cycle regulation, cytokine/chemokine, cell surface molecule, signal transduction, transcription factor/regulator, and unknown. Expression is presented as the ratio of 1g/μg. Therefore, the higher the fold difference, the more profoundly the expression of the gene is inhibited in μg during T cell activation.

Table 1. List of 47 Genes Inhibited Significantly Twofold or More in μg-Activated Compared with 1g-Activated Samples^a.

Gene symbol	Gene name	Expression 1g/μg	Molecular function
Apoptosis
GRAMD4	GRAM domain-containing 4	2.29	Mediate E2F1-induced apoptosis; mitochondrial protein
Antiapoptosis
IER3	Immediate early response 3	6.66	Protect from FAS and TNF-mediated apoptosis
BCL2A1	B cell lymphoma 2-related protein A1	5.32	Block caspase activation
SERPINB9	Serpin peptidase inhibitor, clade B (OVA), member 9	2.33	Serine proteinase inhibitor
Cell-cycle regulation
BTG2	BTG family, member 2	5.00	Inhibit G1/S transition
SERTAD1	SERTA domain-containing 1	2.17	Promote G1/S transition
Cytokine/chemokine
TNF	TNF superfamily, member 2	15.24	Proinflammatory, Th1 cytokine
CCL3	Chemokine (C–C motif) ligand 3 (MIP-1α)	6.28	Proinflammatory, PMN recruitment
AREG	Amphiregulin	4.87	Th2 cytokine; clear nematodes
Cell surface molecule
TNFSF9	TNF (ligand) superfamily, member 9 (41BB-L)	8.43	TNFR superfamily, costimulation
TNFS14	TNF (ligand) superfamily, member 14 (LIGHT)	5.17	TNFR superfamily, T cell activation
CD83	CD83 molecule	2.54	Early activation marker, lymphocyte proliferation, adhesion
CD69	CD69 molecule	2.33	Early activation marker, lymphocyte proliferation
Signal transduction
NFKBID	NFκ light polypeptide gene enhancer in B cells inhibitor, δ	7.07	Proinflammatory, cRel pathway, IL-2 production
NLRP3	Nucleotide-binding oligomerization-like receptor family, pyrin domain-containing 3	4.83	Proinflammatory, IL-1 production
DUSP2	Dual-specificity phosphatase 2	4.35	Phosphatase, dephosphorylate MAPK
SPRY2	Sprouty homolog 2 (Drosophila)	3.28	Inhibitor of tyrosine kinase signaling
TAGAP	T cell activation RhoGTPase-activating protein	2.91	GTPase-activating protein
RILPL2	Rab-interacting lysosomal protein-like 2	2.77	Interact with RAB7 GTPase, endocytic transport
ZFP36	Zinc finger protein 36, C3H type, homolog	2.65	Anti-inflammatory, destabilize TNF mRNA
NFKBIA	NF[kappa] light polypeptide gene enhancer in B cells inhibitor, α	2.63	Sequester cRel in cytoplasm, cRel pathway
PPP1R10	Protein phosphatase 1, regulatory (inhibitor) subunit 10	2.62	Inhibits protein phosphatase 1
CMIP	c-Maf-inducing protein	2.15	Th2 cytokine production, c-Maf pathway
Transcription factor/regulator
NR4A3	Nuclear receptor subfamily 4, group A, member 3	28.70	Steroid hormone receptor family
NR4A2	Nuclear receptor subfamily 4, group A, member 2	11.01	Steroid hormone receptor family
NR4A1	Nuclear receptor subfamily 4, group A, member 1	10.11	Steroid hormone receptor family
EGR2	Early growth response 2	13.18	Mitogenesis
EGR1	Early growth response 1	12.82	Mitogenesis
MYC	v-myc Myelocytomatosis viral oncogene homolog	4.62	Proto-oncogene, mitogenesis
FOSL2	FOS-like antigen 2	4.38	Mitogenesis, Th2 differentiation
JUNB	jun B Proto-oncogene	3.16	Tumor suppressor; antiproliferation
REL	v-rel Reticuloendotheliosis viral oncogene homolog	2.75	Mitogenesis, IL-2 production, Th1 cytokine production
NAB2	Nerve growth factor I-A-binding protein 2 (EGR1-binding protein 2)	2.18	Repress EGR1 and EGR2
EGR3	Early growth response 3	11.35	Mitogenesis
KLF10	Kruppel-like factor 10	5.36	Antiproliferative; induce apoptosis
IRF4	IFN regulatory factor 4	4.05	Th2 cytokine production
MAFF	v-Maf musculoaponeurotic fibrosarcoma oncogene homolog F	3.53	Transcription regulation
KDM6B	Lysine (K)-specific demethylase 6B	3.52	Transcriptional regulation
CSRNP1	Cysteine-serine-rich nuclear protein 1	3.51	Tumor suppressor
BTBD11	BTB (POZ) domain-containing 11	3.62	Transcriptional regulation
IER2	Immediate early response 2	2.80	Transcription regulation
ZC3H12A	Zinc finger CCCH-type-containing 12A	2.44	Anti-inflammatory, immune modulator
ARID5B	AT-rich interactive domain 5B (MRF1-like)	2.24	Regulate cell growth and differentiation
KLF9	Kruppel-like factor 9	2.22	Transcription regulation
Unknown
C10orf54	Chromosome 10 ORF 54	6.95

^aGenes captured by the pathway analysis (see Fig. 5) are in bold type.

A substantial proportion of the genes most significantly inhibited in μg plays important roles in signal transduction and transcription regulation. Ten of the 47 genes (21%) encode members of signal transduction pathways, including the cRel pathway, small G-protein signaling, as well as phosphatases and inhibitors. Twenty-one of the 47 genes (45%) encode transcription factors or regulators, many of which are inducers of mitogenesis (e.g., EGRs, MYC, and REL). Other transcription factors significantly inhibited in μg are involved in Th1 (e.g., REL) or Th2 differentiation (e.g., FOSL2 and IRF4).

These data from spaceflight indicate that gravity modulates the expression of genes that promote lymphocyte proliferation and inflammation, as well as those that may have a down-regulatory role. CD83 and CD69, both early surface markers of T cell activation, are expressed more than twofold lower in μg compared with 1g (Table 1), providing further evidence that T cell activation is significantly inhibited in μg. Whereas antiapoptotic genes IER3, BCL2A1, and SERPINB9 are inhibited in μg, GRAMD4, an effector of apoptosis, is also inhibited. BTG2, which inhibits G1/S transition, is inhibited fivefold in μg; on the other hand, SERTAD1 promotes G1/S transition and is inhibited twofold. Overall, taking into account the fold-expression differences, lymphocyte mitogenic and inflammatory responses appear to be inhibited most profoundly in μg. TNF, a critical proinflammatory cytokine, is inhibited 15-fold in μg, and CCL3, a chemokine important for neutrophil recruitment, is inhibited sixfold. EGR1, -2, and -3 are all inhibited more than tenfold in μg; NAB2, a repressor of EGR1 and EGR2, is inhibited twofold. Several other transcription factors important for mitogenesis are significantly inhibited in μg, including MYC (4.62-fold), FOSL2 (4.38-fold), and REL (2.75-fold). JUNB, a transcription factor with antiproliferative properties, is inhibited 3.16-fold.

We selectively performed qRT-PCR on several genes to verify their differential expression in μg versus 1g. T cells that were μg-nonactivated, μg-activated, or 1g-activated during spaceflight from all four human volunteers were tested for quantitative expression of MYC, IRF4, TNF, NFKBIA (IκBα), NR4A3, and TAGAP (Fig. 3). Each data point represents four biologically independent samples stimulated by Con A and anti-CD28 during spaceflight in μg or 1g control. Fold expression was normalized to the housekeeping gene CPHI and then to μg-nonactivated values. Comparing μg-activated with 1g-activated samples, expression of these genes were all decreased significantly in μg-activated samples, as determined by qRT-PCR. These results, along with the microarray analysis, suggest that lymphocyte mitogenesis (as represented by MYC expression), cytokine production (IRF4), proinflammatory response (TNF), and the REL signaling pathway (NFKBIA) are decreased significantly in T cells activated in the absence of gravity. In addition, we identified two novel, gravity-responsive genes that play a role in T cell activation. NR4A3 is a steroid hormone receptor family transcription factor involved in mediating the inflammatory response [38]. TAGAP is a T cell activation-specific GTPase-activating protein genetically linked to inflammatory diseases, such as rheumatoid arthritis, Crohn's disease, and celiac disease [39, 40]. NR4A3 and TAGAP represent novel pathways that are inhibited significantly in μg during T cell activation, as their roles were not identified by previous experiments in reduced gravity.

Figure 3. qRT-PCR of selected genes in nonactivated, μg-activated, and 1g-activated T cells.

RNA from all four donors were used in qRT-PCR to determine level of expression of MYC, TNF, NFKBIA, IRF4, NR4A3, and TAGAP. *P < 0.05; **P < 0.01; ***P < 0.001 comparing μg-activated and 1g-activated samples.

Transcription of immediate early genes are inhibited in T cells upon CD3/CD28 cross-linking in simulated μg

To further investigate the effects of μg on early T cell activation signal transduction, we determined whether expression of immediate early genes was inhibited in purified CD4⁺ T cells stimulated by CD3/CD28 cross-linking in simulated μg. CD4⁺ T cells were purified from the peripheral blood of four human volunteers. Simulated μg was created by RWVs that produced freefall conditions for cultured lymphocytes through rotation along a horizontal axis. Purified CD4⁺ T cells were activated in stationary culture vessels as 1g controls. After 1.5 h of incubation with CD3/CD28 activation beads, the CD4⁺ T cells were lysed for RNA isolation. Expression levels of immediate early genes, previously shown to be inhibited in μg in the spaceflight microarray experiment, were determined by qRT-PCR in nonactivated, activated-simulated μg, and activated 1g cultures. Expression of cREL, TNF, EGR1, EGR2, and JUNB was reduced significantly in simulated μg compared with 1g controls (Fig. 4). Expression level of cREL in activated simulated μg cultures was the same as nonactivated T cells and sixfold less than activated 1g cultures. Expression levels of TNF, EGR1, EGR2, and JUNB in activated-simulated μg T cells increased from nonactived T cells but were all significantly lower than 1g-activated T cells. Compared with 1g-activated T cells, expression of TNF was 3.1-fold less, EGR1 was 4.5-fold less, EGR2 was 2.9-fold less, and JUNB was 2.1-fold less in simulated μg-activated T cells. These immediate early genes are known to be transcribed within 30 min to 1 h of T cell activation and do not require de novo protein synthesis. The markedly reduced expression of these genes underscores that early signal transduction events are inhibited in CD4⁺ T cells activated in simulated μg.

Figure 4. qRT-PCR of immediate early genes in nonactivated, simulated μg-activated, and 1g-activated T cells upon CD3/CD28 bead activation.

RNA from four human donors were used in qRT-PCR to determine level of expression of cREL, TNF, EGR1, EGR2, and JUNB. **P < 0.01; ***P < 0.001 comparing simulated μg-activated and 1g-activated samples.

Rel/NF-κB signaling is a key pathway inhibited in μg

To identify the signaling pathways that were inhibited by μg during early T cell activation, we performed promoter region analysis on the 47 genes that showed significant down-regulated expression after 1.5 h of activation in the spaceflight experiment (Table 1). The 47 genes were analyzed for statistically significant over-representation of TFBSs using the oPOSSOM algorithm. Remarkably, three of the top five over-represented TFBSs were in the Rel/NF-κB family (Table 2), indicating it to be a major pathway inhibited by μg in T cell activation. Of note, 20 of the 47 analyzed genes (43%) had cRel-binding sites in their promoter regions, making cRel the most highly represented promoter site in genes with down-regulated expression in μg. The over-representation of cRel sites is highly statistically significant with a Z-score of 25.2 and a Fisher score of 4.4 × 10⁻⁹. Likewise, the over-representation of RelA (p65) and NF-κB-1 (p50)-binding sites was also highly statistically significant with Z-scores of 27.3. and 23.4 and Fisher scores on the order of 10⁻⁸ and 10⁻⁶, respectively. As Rel/NF-κB transcription factors positively regulate their own transcription [41, 42], these data suggest that transcription of downstream effectors of the Rel/NF-κB pathway would be reduced greatly in T cells activated in μg. Indeed, expression of cREL itself is significantly inhibited in T cells activated in μg, as demonstrated by the spaceflight microarray data (Table 1) and CD3/CD28 bead activation experiment in simulated μg (Fig. 4).

Table 2. Over-represented Transcription-Binding Sites in the Promoter Regions of 47 Genes with Inhibited Expression in μg after T Cell Activation.

Transcription factor	Class	# of Genes	Z-score	Fisher score
c-Rel	REL	20	25.3	4.4 × 10−9
RelA (p65)	REL	15	27.3	1.5 × 10−8
NF-κB-1 (p50)	REL	14	23.4	3.9 × 10−6
CREB1	bZIP	13	30.8	1.6 × 10−6
SRF	MADS	5	42.1	4.8 × 10−6

In addition to members of the Rel/NF-κB family, CREB1 and SRF-binding sites were highly represented in the promoter of genes inhibited in T cells activated in μg. CREB1 is a transcription factor that can be activated by cAMP/PKA, calcium/calmodulin, and/or Ras/MAPK pathways. Our previous work showed that phosphorylation of CREB1 was inhibited in μg at 4 h after T cell activation and was dependent on PKA activity [26, 27]. SRF is the major promoter response element of immediate early genes and an important target for the Ras/MAPK and Rho/actin pathways [43]. Together, these data suggest that in early T cell activation, the Rel/NF-κB pathway may be the predominant pathway dysregulated in μg. Other signal transduction pathways, including cAMP/PKA, Ras/MAPK, and calcium/calmodulin, may also be affected. In contrast to the promoter analysis of genes down-regulated in μg, no TFBSs for any particular family of transcription factors were over-represented in the 315 genes that were activated equally in μg and 1g (Group C in Fig. 1; data not shown).

Pathway analysis predicts that TNF downstream signaling would be inhibited significantly in μg

In addition to identifying the early gravity-responsive signals downstream of CD3 and CD28 engagement, we performed a pathway analysis on the 47 genes down-regulated most significantly in μg to predict the T cell effector functions that are likely to be dysregulated most severely later in the response. Pathway analysis was performed with the GeneSpring GX 11.0.2 software, in which molecular interactions were curated from databases, such as IntAct [30] and Natural Language Processing algorithms of published literature. We generated a pathway diagram of direct interactions between the molecules in the list of 47 genes from Table 1 and set the relation score to greater than or equal to nine on a scale of one to 10, to include only interactions that have the highest degree of support (Fig. 5). Types of relations included binding, expression, member, metabolism, promoter binding, protein modification, regulation, and transport. Twenty-two genes were captured as part of this pathway in which TNF was the central element. These genes are also highlighted in Table 1 with bold type and outlines. The remaining 25 genes were not linked to TNF signals and were excluded by the analysis.

Figure 5. Pathway analysis of genes significantly inhibited in μg-activated samples by twofold or more compared with activated 1g.

Ovals represent the significant genes as determined by microarray analysis and presented in Table 1. These same genes are highlighted by bold type and outlined in Table 1. Location of the molecule encoded by the gene is segregated to the cell membrane, cytoplasm, and nucleus. Pink ovals represent molecules of the input gene list involved in direct interaction with each other. The purple oval indicates that although MAPK is not part of the input list, its involvement is strongly suggested. Yellow circles represent signaling intermediaries not identified within the input gene list. Black lines with arrowheads indicate a positive association or regulation. Black lines without arrowheads indicate a neutral association or participant. Blue lines indicate a negative association or regulation.

The pathway diagram localized the molecules to the cell membrane, cytoplasm, or nucleus. The molecules of the input gene list involved in direct interactions with each other are denoted by ovals. MAPK (purple symbol) was not part of the input list, but its involvement in the pathway was strongly suggested by the other genes involved. Yellow circles represent signaling intermediaries not identified within the input gene list. The black lines connecting the molecules indicate various types of interactions with the direction of the arrowhead indicating a positive association or regulation. Black lines without arrowheads indicate a neutral association or participant. Blue lines indicate a negative association or regulation.

The generated pathway diagram predicts that TNF is a key gravity-dependent effector function that would be inhibited in μg. TNF transcription is normally induced rapidly in T cells activated by CD3/CD28 cross-linking [44], and it is markedly reduced in T cells activated in μg (Fig. 4). In addition, the pathway analysis demonstrates that TNF downstream signals and interactions involve many cytokines, surface molecules, signaling molecules, and transcription factors that are also inhibited in μg. As TNF is an important proinflammatory effector cytokine, this analysis suggests that downstream inflammatory responses may be lowered significantly in μg.

DISCUSSION

Data presented in this report prove that it is the μg environment of spaceflight that leads to impaired T cell activation and that transcription of immediate early genes is profoundly down-regulated. The first evidence that μg may suppress T cell activation showed that human PBLs stimulated with Con A during spaceflight demonstrated markedly reduced proliferation compared with ground-control samples [18]. Subsequent experiments using ground-based culture systems to produce simulated μg showed that decreased expression of IL-2 and IL-2Rα was likely responsible for the decreased proliferation of T cells in μg [25, 26]. These results demonstrated that reduced gravity can perturb molecular signals leading to impaired immune function. The spaceflight experiment presented here adds to this body of knowledge with the use of appropriate spaceflight hardware that allowed for activation of T cells during spaceflight and preservation of high-quality RNA for microarray analysis. The KUBIK facility on board the ISS produced a simultaneous 1g control while in orbit, which isolated the effects of μg from the other variables of spaceflight mentioned above. Experimental μg and control 1g T cells underwent the same launch forces, ambient temperatures, culture conditions, and cosmic radiation prior to and during activation. The only difference was whether cells were activated in static μg positions or in centrifuge positions with an applied 1g force. Although it is possible that unidentified spaceflight variables may contribute to our experimental observations, it is highly likely that μg is the dominant factor determining the observed changes in gene expression. Microarray analysis 1.5 h after activation provided a wealth of information regarding the expression of immediate early genes and the early signal transduction cascades likely dysregulated in μg. Having global gene expression data from three genetically distinct individuals provided a high degree of confidence in the statistical analysis of the differentially regulated genes. This was illustrated by the fact that the three μg-nonactivated samples showed distinct gene expression patterns, whereas the three μg-activated and the three 1g-activated samples showed significant concordance within the experimental condition but clustered separately from each other. Importantly, differentially regulated genes in μg identified by microarray analysis were confirmed by qRT-PCR in the spaceflight samples. Finally, whereas Con A stimulation in the spaceflight experiment evaluated the T cell mitogenic response to cross-linking of membrane glycosidic residues, CD3/CD28 bead activation of CD4⁺ T cells in simulated μg specifically showed that impaired immediate early gene transcription was a result of altered downstream TCR and costimulatory signaling.

Our previous work characterized the global gene expression of activated T cells in simulated μg after 4 h of activation [26]. This time-point was determined to be the peak for IL-2 expression postactivation in 1g [27], and there was significant inhibition in simulated μg [26]. Ninety-eight other genes were also found to be down-regulated significantly in simulated μg compared with 1g at 4 h. These included critical effector cytokines, such as IFN-γ, and cytokine receptors, such as the high-affinity IL-2R (IL-2Rα, CD25) [26]. Whereas the IFN-γ and IL-2Rα genes were reduced significantly in simulated μg at 4 h, they were not induced significantly in μg or 1g at 1.5 h. This difference was likely a result of the early 1.5-h time-point, chosen to detect immediate early genes rather than the subsequent wave of secondary response genes (e.g., IL-2), which became detectable at 4 h [27]. There were also examples in which up-regulation of immediate early genes at 1.5 h was sustained at 4 h in 1g samples and inhibited in μg at both time-points. These included the key antiapoptotic regulator BCL2A1, IRF4 (T cell differentiation regulator), EGR1 and EGR2, and the cytokines TNF (Th1 and proinflammatory response) and CCL3 (recruitment and activation of PMN leukocytes). In comparison, the early T cell activation marker, CD69, was found to be differentially expressed in 1g versus μg only at the 1.5-h and not the 4-h time-point. Of note, cREL, the critical Rel/NF-κB transcription factor, was also only differentially expressed at 1.5 h and not at 4 h. Although differences between simulated μg and μg and the use of differing activators may play a role, differences in gene expression between the two time-points most likely represent genes transiently expressed in 1g at 1.5 h at the start of the cascade, which are then normally down-regulated by 4 h. Taken together, these differences reflect the time course of gene expression after T cell activation and the pattern of how μg inhibits the first wave of immediate early genes with downstream effects on a wider range of secondary response genes.

One of the most interesting results from our analysis is that the Rel/NF-κB pathway appears to be the principal signaling pathway adversely affected by μg in very early T cell activation. The Rel/NF-κB transcription factor family is comprised of five subunits: cRel, RelA (p65), NF-κB-1 (p50), NF-κB-2 (p52), and RelB. These subunits form heterodimers that then bind DNA. cRel, RelA, and RelB have transactivation domains and are required for gene transcription; NF-κB-1 and NF-κB-2 do not have transactivation domains and serve as dimerization and DNA-binding partners [23, 38]. Three of these five subunits, cRel, RelA (p65), and NF-κB-1 (p50), were among the most significantly over-represented TFBSs found in the promoters of genes down-regulated during T cell activation in μg (Table 2). cRel TFBSs were the most highly represented sites and were present in almost one-half (20 of the 46 genes) of the genes inhibited in μg-activated T cells. In addition, transcription of cRel itself is reduced significantly in simulated μg upon CD3/CD28 stimulation (Fig. 4). cRel transcription is subject to positive autoregulation by p50/p65, as well as cRel itself [42]. Similarly, cRel and p50/p65 also induce transcription of the p50 gene [41]. Importantly, gene-targeting studies have demonstrated a critical role for cRel and p50 in T cell function and survival. cRel^−/− T cells stimulated by anti-CD3 and anti-CD28 fail to proliferate and produce little to no detectable IL-3, IL-5, GM-CSF, TNF, and IFN-γ [39]. T cells from cRel^−/−p50^−/− double-deficient mice demonstrated impaired cell-cycle entry and increased apoptotic cell death upon activation [40]. With such critical roles in T cell activation, disruption of the Rel/NF-κB pathway and the normal positive-feedback loop for Rel/NF-κB transcription-factor expression in μg is likely a key mechanism leading to downstream severe immune dysfunction.

It is possible that μg causes dysregulation of signal transduction and transcription pathways at several points. For the Rel/NF-κB pathway, NF-κB subunits are sequestered in the cytoplasm through binding to the inhibitory protein IκBα (NFKBIA) in the nonactivated state. Upon ligation of the TCR, through a PKCθ-dependent pathway, IKKs (IKKα and IKKβ) phosphorylate IκBα, targeting it for ubiquitination and proteasome-mediated degradation. This results in release of the NF-κB subunits and their translocation into the nucleus for gene transcription [23, 38]. In addition to Rel/NF-κB, our analysis suggested that CREB1 and SRF-regulated genes were down-regulated significantly in μg. Our previous work showed that phosphorylation of CREB1 was inhibited in μg [26]. The cAMP/PKA, calcium/calmodulin, and PKC/Ras/MAPK are three independent pathways capable of inducing CREB1 phosphorylation [30]. We have shown previously that Con A/anti-CD28-induced phosphorylation of CREB1 was dependent on the PKA and PKC pathways [27]. Others demonstrated that CREB1 activation resulting from CD3 and CD28 engagement required the calcium/calmodulin and PKC/Ras/MAPK pathways [31, 45]. The specific upstream steps in these pathways disrupted by μg are yet to be determined. Finally, SRF is essential to the induction of many immediate early genes, including EGR1, EGR2, and JUNB [43], whose expression levels were decreased significantly in μg. Ras/MAPK and Rho/actin pathways are capable of activating SRF target genes [43] and may be inhibited in μg.

Our previous work demonstrated that proximal TCR signal transduction, including LAT, PI3K, and PKC phosphorylation, was not affected in T cells activated in μg [26]. Our microarray analysis, which was confirmed by qRT-PCR, showed that IκBα (NFKBIA) was down-regulated significantly in μg-activated T cells (Table 1 and Fig. 3). This suggests that the normal gene expression of IκBα may not occur in μg-activated T cells, as in 1g-activated cells, and that the Rel/NF-κB pathway may be dysregulated. Work is ongoing to explore the upstream regulation of very early T cell activation in μg. It is possible that inhibited expression of the 47 genes whose expression was twofold lower in μg occurs at the level of TCR activation, altered signal transduction, altered cytoskeleton function, transcription factor nuclear translocation, DNA binding, or transcription machinery assembly. Indeed, the next great challenge in understanding immune dysregulation in μg is to determine the specific mechanisms through which μg inhibits activation of these key genes of very early T cell activation. In addition to transcriptional regulation, in future studies, it will be important to design well-controlled spaceflight experiments that investigate translational, post-translational, and signaling events (e.g., phosphorylation) regulating T cell activation in μg.

In addition to determining the signal transduction pathways immediately downstream of TCR and CD28 disrupted in μg, our analysis of the microarray data predicted pathways likely to be down-regulated most severely later in the immune response. Pathway analysis of the genes down-regulated significantly in μg revealed an interconnected subset of genes clustered around TNF. TNF is one of the earliest genes to be transcribed after T cell activation [44] and is a proinflammatory cytokine that mediates a variety of effector functions, including proliferation, differentiation, apoptosis/cytotoxicity, and systemic shock [46]. Induction of TNF transcription requires the calcium/calmodulin-dependent activation of NFAT, although NF-κB signaling also has a role [47]. TNF exerts its effect through binding to TNFR1 and -2 and activation of the AP-1 and NF-κB transcription factors [48]. Our pathway analysis showed that TNF, whose expression itself was inhibited significantly in T cells activated in μg (Table 1 and Fig. 4), is interconnected with many cytokines, signaling molecules, and transcription factors down-regulated in μg. This suggests that the TNF pathway and downstream effector functions likely will be impaired severely in immune responses in μg and may have significant negative consequences on the body's ability to mount proinflammatory responses against infectious agents during long-term space travel.

In conclusion, we have demonstrated that the transcription of immediate early genes is inhibited in T cells activated in μg and that disrupted activation of Rel/NF-κB, CREB1, and SRF transcription factors is involved. Future research should focus on delineating the specific mechanisms of how μg causes dysregulation of these signal transduction pathways to further clarify the molecular basis of spaceflight immunosuppression.

AUTHORSHIP

T.T.C. analyzed the microarray data and wrote the manuscript. I.W. was the ESA principal investigator and leading scientist for the mission organization and preparation of the flight experiment in Baikonur. C-F.L. developed preflight protocols and performed postflight isolation and analysis of the RNA samples. J.B. performed the promoter analysis. G.G. and M.A.M. performed preliminary preflight ground experiments and prepared the cultures and hardware in Baikonur. P.P. was the senior investigator of the team based at Sassari University; he provided technical and administrative support for preflight operations. A.C. was the principal investigator responsible for the manufacture, testing, and space qualification of the flight hardware. M.H-F. was the NASA grant principal investigator; designed the experiment setup and analysis; provided the laboratory, personnel, equipment, and supplies necessary for experimental analysis; and was integrally involved with the experimental analysis and writing of the manuscript and its revisions.