Toxic shock syndrome (TSS) is an acute, serious systemic illness caused by bacterial superantigens. Nonavailability of a suitable animal model until recently has hampered an in-depth understanding of the pathogenesis of TSS. In the current study, we characterized the early molecular events underlying TSS using our HLA-DR3 transgenic mouse model. Gene expression profiling using DNA microarrays identified a rapid and significant upregulation of several pro- as well as anti-inflammatory mediators, many of which have never been previously described in TSS. In vivo administration of staphylococcal enterotoxin B (SEB) led to an increase in the expression of Th0- (IL-2, 240-fold); Th1- (IFN-γ, 360-fold; IL-12, 8-fold); Th2- (IL-4, 53-fold; IL-5, 4-fold) as well as Th17-type cytokines (IL-21, 19-fold; IL-17, 5-fold). The immunoregulatory cytokines (IL-6, 700-fold; IL-10, 18-fold); CC chemokines (such as CCL 2, 11, 3, 24, 17, 12, 7), CXC chemokines (such as CXCL 1, 2, 5, 11, 10, 19); and several proteases (matrix metalloproteinases 13, 8, 3, and 9) were also upregulated. Serum levels of several of these cytokines/chemokines were also significantly elevated. Pathway analyses revealed significant modulation in a variety of biochemical and cellular functions, providing molecular insights into the pathogenesis of TSS. Administration of bortezomib, a clinically approved proteasome inhibitor capable of blocking NF-κB pathway, was able to significantly modulate the expression of a variety of genes induced by SEB. Thus, our study showed that TSS is a complex process and emphasized the potential of use of bortezomib in the therapy of superantigen-induced TSS.
- toxic shock
- T cell response
- HLA class II transgenic mice
the gram-positive cocci, Staphylococcus aureus and Streptococcus pyogenes elaborate a family of exotoxins called “superantigens,” which are among the most powerful T cell activators known (46). Superantigens bind directly to α- or β-chain of cell surface MHC class II molecules (outside of the peptide-binding groove), without undergoing any intracellular processing. Subsequently, they activate T cells by interacting directly with the variable region of the β-chain (in rare cases α-chain) of the T cell receptor (TCR), irrespective of their antigen specificities (32). T cell activation by superantigens does not require CD4 or CD8 coreceptors. Thus, MHC class II-bound superantigens can vigorously activate both CD4+ and CD8+ T cells in a TCR-dependent but cognate antigen-independent manner. Superantigens are thus able to activate a large pool of T cells (30–70% of total T cells) as opposed to the very low T cell frequency (1 in 104 to 1 in 106) for conventional peptide antigens.
Bacterial superantigens have been implicated in several human diseases ranging from self-limiting food poisoning to much severe toxic shock syndrome (TSS) (36, 46). In addition to their clinical significance, bacterial superantigens are also of public health importance because some bacterial superantigens, particularly staphylococcal enterotoxin B (SEB), could be used as biological weapons (35). While bacterial superantigens have been implicated in a spectrum of diseases, the TSS, characterized by systemic inflammatory response syndrome (SIRS) and multiple organ dysfunction syndrome (MODS), is a well-recognized clinical entity. TSS (either menstrual or nonmenstrual) has a rapid onset, often associated with high morbidity/mortality and treated only symptomatically as specific therapies are lacking (38, 65). A robust superantigen-induced T cell activation and the concomitant cytokine production are believed to be the underlying causes for TSS (14). Nevertheless, the precise molecular mechanisms by which T cell activation by superantigens lead to multiple organ dysfunction and ultimately death are unclear (36).
The lack of understanding of the immunopathogenesis of superantigen-induced TSS, particularly the acute early events, could be attributed to nonavailability of a robust animal model. It should be noted that several mouse models for sepsis-associated shock are available and sepsis is also characterized by SIRS and MODS. In spite of these similarities, the early pathogenesis of bacterial superantigen (BSAg)-induced TSS could be different from sepsis for the following reasons (61a). Sepsis is characterized by a robust activation of the “innate immune system” by the microbial components (such as LPS, peptidoglycans etc.) predominantly through the Toll-like receptors (54). Superantigen-induced TSS is characterized by direct activation of the “adaptive immune system” (T lymphocytes). While it is established beyond doubt that the innate and adaptive immune systems are interlinked (21), there are major intrinsic differences between these two arms of immunity, particularly during their earlier stages of activation, with respect to the effector cell types involved, cytokines, and their associated pathways, etc. (8, 20, 37). These discrepancies might complicate a direct comparison between sepsis and superantigen-induced TSS. In any case, the pathogenesis BSAg-induced TSS has to be fully understood so that we could decipher the similarities and/or differences between TSS and sepsis.
The major setback for this approach is that conventional mice are not susceptible to the classical superantigen-induced TSS due to poor binding of BSAg to murine MHC class II molecules. Even high concentrations of superantigens are unable to cause TSS in conventional mice, while they are readily susceptible to sepsis. This necessitates the use of certain sensitizing agents such as d-galactosamine or bacterial lipopolysaccharides (LPS) along with superantigen to induce mortality in conventional mice strains (26, 36). The use of such sensitizing agents complicates interpretation of data from such studies. However, we have recently established that endogenous MHC class II-null mice transgenically expressing the human MHC (called the human leukocyte antigen or HLA) class II molecules, either HLA-DR3 or HLA-DQ8, mount a robust immune response to bacterial superantigens and are susceptible to TSS without any sensitizing agents (48–53). Thus, HLA class II transgenic mice provide the unique opportunity to dissect the immunopathogenesis of bacterial superantigen-induced TSS. Therefore, we carried out the current study with two major objectives. One, to delineate the early molecular events associated with the pathogenesis of superantigen-induced TSS caused by the SEB, using microarrays. Two, to explore the effects of bortezomib, a clinically approved proteasomal inhibitor with established ability to inhibit activation of the transcription factor NF-κB, on SEB-induced gene expression profile so that we can predict the use of bortezomib in the treatment of TSS. Our results might provide novel insights into the pathogenesis of TSS and, for the first time, provide molecular insight into the in vivo effects of bortezomib on bacterial superantigen-induced gene expression changes.
MATERIALS AND METHODS
AEo.HLA-DR3 transgenic mice expressing the functional HLA-DRA1*0101 and HLA-DRB1*0301 transgenes on the complete mouse MHC class II-deficient background have been described earlier and were used in this study (50). Mice were bred within the barrier facility of Mayo Clinic Immunogenetics Mouse Colony (Rochester, MN) and moved to a conventional facility after weaning. All the experiments were approved by the Institutional Animal Care and Use Committee.
Bortezomib (Velcade; Millennium Pharmaceuticals, Cambridge, MA) was obtained from Mayo Clinic pharmacy (Mayo Clinic, Rochester, MN). It was used either within 2 days of reconstitution or stored frozen in aliquots at −80°C. Frozen bortezomib was used within 15 days. Endotoxin-reduced highly purified SEB (Toxin Laboratories, Sarasota, FL) was dissolved in PBS at 1 mg/ml and stored frozen at −80°C in aliquots. Bortezomib was used at a dose of 1 mg/kg as has been used in several murine studies. This dose given repeatedly is well tolerated by mice (1, 63, 67). SEB was injected as indicated in a final volume of 200 μl.
Gene Expression Profiling Using Microarrays
Gene expression profiling following SEB challenge was carried out following standard techniques (50). In brief, HLA-DR3 transgenic mice were intraperitoneally treated with either PBS or bortezomib on days −1 and 0. On day 0, each treatment group was further divided into two groups: one received 10 μg of endotoxin-reduced highly purified SEB, and the other PBS alone, thus making a total of four groups (i.e., PBS+PBS, bortezomib+PBS, PBS+SEB, bortezomib+SEB). Three hours later, mice were euthanized by CO2 asphyxiation, and spleens were immediately collected and frozen in liquid nitrogen. Once all the animals had been killed, total RNA from spleens was extracted with TRIzol (Invitrogen) per the manufacturer's recommendations, followed by purification using Qiagen RNeasy columns (Qiagen). Integrity of RNA was verified by electrophoretic analysis using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA). All samples contained 18S and 28S rRNA peaks with no degradation. A minimum of 8 μg of RNA from each sample was subsequently processed.
Synthesis and cleaning of double-stranded cDNA followed by synthesis of biotin-labeled cRNA and fragmentation of biotinylated cRNA into 100- to 150-nt fragments were carried out in the Mayo Clinic Advanced Genomics Technology Center core facility, according to protocols described in the Affymetrix GeneChip Expression Analysis manual (Affymetrix, Santa Clara, CA). For each sample, 15 μg of fragmented, biotinylated cRNA was hybridized to a Mouse Genome 430A 2.0 array (Affymetrix), then washed with buffers of varying stringencies, stained with streptavidin-PE, and scanned with a Hewlett-Packard GeneArray Scanner (Hewlett-Packard, Santa Clara, CA). The GeneChip Microarray Suite v4.01 software program (Affymetrix) was then used to generate data for subsequent analysis.
The CEL files were processed, and the expression values for each transcript were calculated by GC-RMA algorithm (69). The absent/present/marginal calls for each transcript were calculated using Affymetrix MAS 5.0 algorithm. Transcripts with “absent” calls in all samples were excluded from further analysis. Next, we filtered out “not expressed genes” based on the concept that only a small percentage of total genes are expressed in a cell at any given time. In a two-group comparison, if a transcript has average expression levels in both groups lower than the 50 percentile of all expression values from all samples, this transcript is considered “not expressed.” Mice from PBS- and SEB-treated groups were compared by unpaired t-test with unequal variances. Also false discovery rate (FDR) values, a more robust indicator of significance, were calculated by the Benjamini and Hochberg method in GeneSpring software (Agilent Technologies, Palo Alto, CA). Pathway analysis was carried out using GenMAPP (gene map annotator and pathway provider, Gladstone Institutes at the University of California at San Francisco, http://www.genmapp.org/default.html), version 2.1 (60), Ingenuity Pathways Analysis 5.0 (Ingenuity Systems, Redwood City, CA), and MetaCore (GeneGo, San Diego, CA).
Serum Cytokine Quantification
At the time of death for RNA extraction from spleens (3 h post-SEB challenge), blood from mice were collected from PBS+SEB and PBS+PBS groups in serum separation tubes, and sera were separated and stored frozen at −80°C in aliquots. For the bortezomib study, separate groups of mice were used and were bled 6 h after SEB challenge so that we could study the effect of bortezomib on gene transcription at 3 h (using microarrays) and on cytokine levels at 6 h. Cytokine concentrations in serum were determined with a multiplex bead assay, per the manufacturer's protocol using their software and hardware (Bio-Plex, Bio-Rad).
SEB-induced Gene Expression Changes
First, to decipher the molecular signature of BSAg-induced TSS, splenic gene expression patterns in HLA-DR3 transgenic mice treated with either PBS or SEB were analyzed using microarrays. Based on the criteria discussed in materials and methods, there were 10,780 transcripts that passed the two steps of filtering process (call filtering and expression filtering). These differentially expressed genes were further filtered out on the basis of their P values (P ≤ 0.001, unpaired t-test), resulting in 2,361 transcripts, which had FDR ≤0.0389. The 2,361 transcripts that were differentially expressed between the control and toxin-treated groups were used as focus gene list in Ingenuity Pathway Analysis (IPA, described later), and the 10,780 transcripts, as the reference (Supplementary Data S1, http://www.ncbi.nlm.nih.gov/projects/geo/index.cgi; GEO accession number, GSE15571).1
Robust upregulation of cytokine gene expression by SEB.
Unlike conventional antigens, SEB rapidly activates both CD4+ and CD8+ T cells. One of the primary functions of activated T cells is to produce cytokines. Therefore, in the microarray data we specifically looked for various members of the interleukin family, whose expression was modulated in SEB-treated mice (Table 1). The highest upregulated cytokine gene was IL-6 (700-fold), followed by interferon (IFN-γ, 360-fold), IL-2 (240-fold), and IL-22 (90-fold). Expression of IL-4 and IL-10 was increased by ∼50- and 18-fold, respectively. Expression of tumor necrosis factor (TNF)-α, a cytokine traditionally associated with shock, was increased by 6.5-fold. Expression of IL-1α and -β was upregulated by 13- and 8-fold, respectively. Interestingly, splenic expression of IL-17, a relatively new member of the proinflammatory cytokine family, was increased by nearly fivefold in SEB-treated mice. While majority of these cytokines were upregulated by SEB (ranging from 200- to 1.5-fold), expression of some cytokines was downregulated in SEB-treated mice. These included TGF-β1 and IL-7, 16, and 18 (Table 1).
Since cytokines mediate their effects through their receptors, we also analyzed the expression pattern of several cytokine receptors (Table 2). The expression of IL-2Rα chain gene was significantly increased (by 25-fold) in SEB-treated mice. However, there was only a minor increase in expression of the other IL-2R subunits (IL-2Rβ, twofold; IL-2Rγ, onefold) in SEB-treated mice (Table 2). Expression of IL-1R type II, the decoy receptor for IL-1, was increased by nearly 17-fold (12). Whereas the expression of IL-6 and IFN-γ was increased by several hundredfold, the expression of their receptors was decreased significantly (Table 2).
Chemokine gene expression modulated by SEB.
The list of chemokines whose expression was altered by SEB is given in Table 3. CXCL2, also called macrophage inflammatory protein 2-alpha (MIP2-α), growth-regulated protein-beta, or Gro oncogene-2, topped the list (525-fold). Other members of the CXC-family of chemokines were also robustly upregulated by SEB. These include CXCL1, also called GRO1 oncogene or neutrophil-activating protein 3 (330-fold), CXCL5 (225-fold), CXCL11 (170-fold), CXCL10 (48-fold), and CXCL9 (36-fold). Many members of the CC family of chemokines were also strongly upregulated by SEB. These included CCL2, also called as monocyte chemotactic protein-1 or MCP-1 (277-fold); CCL11, also known as eotaxin-1, (188-fold); CCL3 and 4, also known as macrophage inflammatory proteins-α and -β, respectively (130- and 70-fold). While the majority of the chemokines were upregulated by SEB (ranging from 500 to 1.5-fold), expression of some chemokines decreased. Some of the chemokines whose expression was decreased were CCL5, CXCL13, CXCL12, and CCL21. Among the chemokine receptors, expression of the orphan chemokine receptor, CCRL2, or chemokine (CC motif) receptor-like 2, was increased by 13-fold, followed by CCR1 (sixfold) and CCR5 (twofold) (Table 3). Expression of other chemokine receptors was decreased (Table 3).
Systemic cytokine storm following SEB challenge.
Validation of microarray data is generally done by performing real-time RT-PCR analysis of selected gene transcripts. However, we were able to demonstrate the presence of translational products of several of the cytokines and chemokines in the sera even at 3 h, confirming the microarray findings. As indicated in Fig. 1, systemic concentrations of many cytokines/chemokines were dramatically elevated in SEB-treated mice. Among the cytokines, G-CSF levels were the highest in the sera (nearly 40,000 pg/ml), followed by IL-2 (10 000 pg/ml) and IL-6 (8,000 pg/ml). Levels of IL-12 (both subunits), IL-17, and IFN-γ were also significantly elevated. In addition, systemic levels of Th2-type cytokines such as IL-4 (400 pg), IL-5 (200 pg), and IL-10 (500 pg) were also increased, albeit not to a lesser extent. As expected, PBS-challenged mice had barely detectable levels of these cytokines in their sera (Fig. 1). However, as per the sensitive bioplex assay, while the level of TNF-α in SEB-treated mice was certainly increased (∼2,000 pg/ml), naïve mice also had relatively high levels of TNF-α (∼500 pg/ml). Thus, there was only a four- to fivefold increase in systemic TNF-α levels as opposed to several hundred- to several thousandfold increases for other proinflammatory cytokines. Among the chemokines, the systemic level of MCP-1 was highest (∼17,000 pg/ml), whereas the levels of MIP-1β, eotaxin, RANTES, and KC were between 2,000 and 3,000 pg/ml. Thus, there was a very good correlation between the splenic gene expression pattern and their actual concentrations in the sera.
Proteases and SEB-induced TSS.
Gene expression profiling identified that expression of several proteases was upregulated within 3 h of exposure to SEB (Supplementary Data S1). Matrix metalloproteinase 13 (MMP13) was topmost in the list (199-fold). A disintegrin-like and metallopeptidase (reprolysin type) with thrombospondin type 1 motif 4 (also called as ADAMTS4 or aggrecanase-1) was another protease whose expression was significantly upregulated by SEB treatment (108-fold). In addition, there were three other MMPs that were significantly increased in SEB-treated mice. These included MMPs 8, 3, and 9, which were increased by 38-, 5-, and 3-fold, respectively. On the other hand, expression of MMP12 and -23 were decreased by 4.3- and 2.6-fold, respectively. Tissue factor pathway inhibitor 2 (TFPI-2) is a Kunitz-inhibitory domain containing protein that has serine proteases inhibitor activity. It can inhibit kallikrein, trypsin, chymotrypsin, and plasmin and weakly inhibits coagulation proteins. However, its biological function remains unknown (9). Expression of TFPI-2 was increased by 128-fold.
Modulation of other inflammatory mediators and molecules involved in signal transduction by SEB.
In addition to these important cytokines and chemokines, several enzymes that have been documented to be involved in acute inflammatory cascades in other models were also significantly upregulated in SEB-treated mice (Supplementary Data S1). These included prostaglandin endoperoxidase synthase 2 (PTGS2, 450-fold), granzyme B (106-fold), hyaluronan synthase 2 (66-fold), histidine decarboxylase (40-fold), and arginase type II (19-fold). Many enzymes that are involved in signal transduction in T lymphocytes were also significantly upregulated by SEB. These included mitogen-activated protein kinase kinase kinase 8 (fivefold), mitogen-activated protein kinase kinase 3 (fourfold), calcium/calmodulin-dependent protein kinase II, delta (fourfold), TNF receptor (TNFRSF)-interacting serine-threonine kinase 1 (fivefold), Jun oncogene (14-fold), mitogen-activated protein kinases 3 and 6 (3.5-fold), many members of the IFN-inducible GTPases, Janus kinase 2 and 3 (2.5-fold), many members of the dual-specificity phosphatases (DUSP) etc. Thus, SEB was able to significantly upregulate several genes whose products either directly or indirectly participate in the inflammatory responses.
Global Changes in Gene Expression Patterns Reveal the Systemic Effects of SEB During TSS
In the approach described above, we specifically looked for changes in the expression of genes that have known effects in an immune response or inflammation. Next, we made use of sophisticated algorithms that are developed to study the global effects of gene expression changes. First, we used the IPA program. The canonical (metabolic and signaling) pathways associated with differentially expressed transcripts are listed in supplemental work sheets (Supplementary Data S2). Ratio is the ratio between “number of changed transcripts from this pathway” and “total transcripts from this pathway,” and “P value” indicates overrepresentation of this pathway among changed transcripts. The details of each pathway are also listed in the supplemental work sheet named “Canonical Pathway Details” (Supplementary Data S2). We also performed IPA functional analysis, which has three primary categories of functions: molecular and cellular functions; physiological system development and function; and diseases and disorders (Supplementary Data S3–S5). As evident from Figs. 2–⇓4, expression of genes associated with several functions was significantly modulated by SEB. These results provide novel information as to how SEB, the bacterial exotoxin that robustly activates the adaptive immune system, can cause changes in a variety of molecular and cellular functions in vivo. We also performed IPA Tox function analysis to identify toxicity that might be occurring to any particular systems. Based on the extent of alterations in the gene expression, IPA Tox function analysis predicted significant liver (55 molecules) and kidney (41 molecules) inflammation (Fig. 5, Supplementary Data S6).
Microarray data were also analyzed by GenMAPP and MAPFinder 2.0 for gene ontology analysis (ranked by Z score). Gene Ontology terms associated with immune response consistently attained high positive Z score, indicating that there are more genes meeting the criterion in a gene ontology term than would be expected by random chance (Supplementary Data S7 and S8). In MetaCore Pathway Analysis, the top 10 canonical pathways are graphically represented in worksheet “MetaCore_pathways” (Supplementary Fig. S1 and Supplementary Data S9), again highlighting the systemic effects of SEB.
Modulation of SEB-induced Gene Expression by Bortezomib
Proteasomes can modulate gene transcription by several mechanisms (3). However, their ability to regulate the activation of the transcription factor, NF-κB, through controlling the degradation of phosphorylated inhibitory protein, IκB, is thought to be one of their primary mechanisms of transcriptional regulation by proteasomes (22). Given the central role of NF-κB in multiple proinflammatory cytokine pathways and the requirement of proteasome in NF-κB activation (42, 70), we investigated the effects of bortezomib, a clinically approved proteasome inhibitor on SEB-induced gene expression. Because of the central role of spleen in the systemic immune response in BSAg-induced TSS, splenic RNA was used in the analyses.
Comparison analyses of gene expression profiles between different groups using IPA software identified the protein ubiquitination pathway as the top pathway that was significantly affected by bortezomib. While the protein ubiquitination pathway was not significantly different in the comparison between PBS+SEB vs. PBS+PBS groups, which did not receive bortezomib, this pathway was significantly affected in all other groups that received bortezomib treatment (Fig. 6A). This indicated that bortezomib does indeed affect the protein ubiquitination pathway. In addition, cell cycle progression, T cell signaling pathways etc. were also significantly modulated by bortezomib, consistent with the known outcomes of proteasome inhibition (3) (Fig. 6B).
Our primary aim was to verify if proteasome inhibition could modulate SEB-induced gene expression favorably such that it could be used in the therapy of TSS. Therefore, we focused only on the transcripts that were differentially regulated between SEB-challenged mice that were left untreated or treated with bortezomib (i.e., PBS+SEB vs. bortezomib+SEB groups). Ratio (fold-change) in the expression levels of mRNA between these two groups was determined; transcripts that were significantly changed (up- or downregulated, P < 0.05) were identified and tabulated (Supplementary Data S10). Among these genes, we first focused on the modulatory effect of bortezomib on selected proinflammatory cytokines, chemokines, and their receptors (from Tables 1–3) whose expressions were greatly modulated by SEB. Expression of IL-6, IFN-γ, IL-2, LIF, IL-33, and IL-12a genes was significantly reduced in SEB-challenged mice treated with bortezomib compared with SEB-challenged untreated mice (Table 4). Other cytokines did not show significant changes in expression except IL-1β, whose gene expression was significantly increased in SEB-challenged mice treated with bortezomib. We also determined the serum levels of the above-mentioned cytokines whose gene expression was significantly modulated by bortezomib. Only the serum levels of IFN-γ and IL-12p40 were significantly reduced by bortezomib: for IFN-γ, 1,565 ± 815 pg/ml for PBS+SEB vs. 520 ± 190 pg/ml for Bortezomib+SEB (P < 0.05); for IL-12p40, 3,612 ± 647 pg/ml for PBS+SEB vs. 2,320 ± 439 pg/ml for Bortezomib+SEB (P < 0.05). Even though transcription of IL-1β was increased, there was no significant change in serum levels of IL-1β (not shown). With respect to cytokine receptors, except for IL-2 receptor α-chain, expression of other cytokine receptors registered no inhibition. Interestingly, expression of receptors for colony-stimulating factor 2, lymphotoxin-β, and IL-10 β-chain was increased modestly but to significant levels. Among the chemokines, while expression of CXCL1, CCL4, and CCL22 was decreased, expression of CCL9, CXCL12, and 13 was increased (Table 4).
Further detailed analysis of gene expression data revealed that there were ∼125 genes in SEB-challenged mice whose expression was increased by more than twofold by bortezomib treatment, and the top 10 of them are shown in Table 5. There were ∼85 genes in SEB-challenged mice whose expressions were decreased because of bortezomib treatment, and the top 10 are also shown in Table 5. Pathway analysis using IPA showed that in this comparison group, the protein ubiquitination signaling pathway was significantly affected (P = 1.06E-07), followed by Huntington disease, Parkinson's disease, cell cycle check point regulation, and mitochondrial dysfunction signaling pathways (Fig. 6B). Figure 7 is another diagrammatic representation of differential gene expression pattern in different groups, and Supplementary Data S11 lists the genes in corresponding groups.
Acute exposure to bacterial superantigens causes TSS characterized by a profound systemic cytokine storm that culminates in multiple organ dysfunction syndrome and often death (36, 46). In spite of its clinical significance, the pathogenesis of TSS is poorly understood. While TSS might share several pathogenic pathways with sepsis, the early molecular events underlying sepsis and TSS could be different as distinct immune mediators are involved in these two processes, the innate immune system in the former and the adaptive immune system in the latter (62). Since a detailed study of TSS induced by purified BSAg has not been carried out before due to the lack of a good animal model, we first undertook the gene expression profiling approach to gain some molecular insights into TSS, using the humanized HLA-DR3 transgenic mice. We then substantiated the findings of gene expression profile by quantifying the translational products and finally investigated the possible therapeutic utility of a clinically approved proteasome inhibitor in TSS by studying its ability to suppress or modulate transcription of genes that were induced by SEB.
Bacterial superantigens robustly activate CD4+ as well as CD8+ T cells (32). The CD4+ T cells could be classified into Th0, Th1, Th2, and Th17 cells based on their cytokine secretion profiles (Ref. 19 and reviewed in Ref. 6). The Th0 are naïve precursor cells or the uncommitted cells that primarily produce IL-2 upon activation. Th0 cells following activation can differentiate into Th1, Th2, or the Th17 pathways depending on the local cytokine milieu (73). Th1 cell types mainly produce IFN-γ; Th2 cells, IL-4, 5, and 13; and Th17 cells, IL-17, and IL-22. During a classical immune response, the differentiation of T helper subsets from Th0 to Th1, Th2, or T17 types occurs over days, if not weeks. In our model, we could detect a robust increase in the transcription as well as translation of cytokines characteristics of Th0, Th1, Th2, and Th17 cell types as early as 3 h. This implies that SEB is activating the preexisting Th0, Th1, Th2, as well as Th17 cells that are expressing the appropriate TCR Vβ, irrespective of their cytokine secretion pattern. However, from the extent of gene transcription and the relative levels of their translational products, it becomes apparent that the Th0, Th1, and Th17 cytokines predominated over the Th2 type cytokines. This probably tilts the response more toward the inflammatory side, leading to MODS, high morbidity, and mortality.
The CD8+ T cells can also be classified as Tc1, Tc2 cells (59), and probably Tc17 cells (17), based on the cytokines they secrete. As bacterial SAg can robustly activate CD8+ T cells expressing the appropriate TCR Vβ elements, the CD8+ T cells could have also contributed to the cytokine storm. The other primary effector function of activated CD8+ T cells is cytotoxicity. CD8+ T cells mediate cytotoxicity primarily through granzyme B (33). Some reports have shown that CD4+ T helper cells can also contain granzyme B and mediate cytotoxicity. Irrespective of the source, granzyme B can cause death of the target cells by several mechanisms. Strong upregulation of granzyme B in our model suggests that it may play a role in MODS during TSS, as suggested in sepsis (29, 72).
TSS has been traditionally considered as a disease mediated by TNF-α. However, in the current study both the relative expression of TNF-α gene as well the serum cytokine level were increased only by sixfold. On the other hand, expression of Th1 type cytokines (particularly IFN-γ) and other newly described Th17 cytokines such as IL-17, IL-21, and IL-22 was upregulated by several hundredfold by SEB. While these cytokines have several known potent proinflammatory activities (2, 25, 31, 44), our study suggests that in addition to TNF-α, these cytokines might also play an important role in the pathogenesis of TSS. Expression of cytokines such as IL-10, IL-4, IL-13, and IL-33 (13) was also upregulated in SEB-treated mice. While the protective roles of IL-4 and IL-10 in superantigen-induced toxic shock have been shown (1a, 4, 15), the roles of IL-13 and IL-33, which are generally associated with Th2 type responses, in the pathogenesis of TSS are not known. Similarly, expression of the SOCS family of proteins, which are strong inhibitors of cytokine signaling pathways (71), was also upregulated in TSS (SOCS1 87-fold; SOCS3 28-fold; SOCS2 8-fold). While mice deficient in SOCS1 and SOCS3 have exaggerated inflammatory responses, the role of SOCS in superantigen-induced TSS has never been reported. It remains to be answered whether these anti-inflammatory molecules are produced as a feedback mechanism to counteract the acute proinflammatory systemic cytokine storm induced by SEB or if they are produced directly as a result of activation by SEB. Nonetheless, their significant upregulation suggests an important role for them in TSS. Thus, SEB is capable of inducing a spectrum of Th1, Th2, and Th17 type cytokines as well as other pro- and anti-inflammatory molecules.
Chemokines are small polypeptides produced by a variety of cell types and play an important role in directing the movement of circulating leukocytes to sites of inflammation or injury (10). A wide variety of chemokines belonging to CC as well as CXC families, targeting monocytes, neutrophils, eosinophils, as well as lymphocytes were markedly upregulated in our study. Upregulation of chemokines during sepsis is well known (24). However, to our knowledge, such a robust upregulation of chemokines by bacterial superantigens during TSS has never been reported. Not only were their gene expression levels increased, serum levels of several of these chemokines were also significantly increased implying a definite role for these mediators in the pathogenesis of TSS.
Extracellular matrix proteases play an important role in the pathogenesis of inflammatory diseases by a variety of mechanisms (11, 27, 43, 64, 68). For example, Kawasaki disease (KD) is an acute inflammatory syndrome of children believed to be caused by bacterial superantigens. Systemic vasculitis and coronary aneurysm are important features of KD and are allegedly caused by elevated levels of MMPs (28, 61). KD is also characterized by elevated cytokine and chemokine levels. The serum cytokine and chemokine profiles as well as the increased levels of proteases as seen in our study suggest a role for bacterial superantigens in the etiopathogenesis of KD (45). Our observations that expression of certain MMPs and other proteases is robustly upregulated by superantigen lend support to the pathogenic role of MMP during TSS (and related acute diseases caused by BSAg) and protease inhibitors might be of therapeutic use (11). Strong upregulation in the expression of the endogenous proteinase inhibitor TFPI-2 also suggests that the balance between proteases and their inhibitors might determine certain pathogenic processes. Similarly, PTGS2 (also called cyclooxygenase 2 or COX-2) is a rate-limiting enzyme involved in the prostaglandin biosynthesis (66). COX-2 expression is inducible by a variety of extracellular and intracellular stimuli, including LPS, TNF, and IFN-γ (30). The robust upregulation of COX-2 in vivo by bacterial superantigen is a novel finding and could be a potential target for therapy (47).
TSS is characterized by multiple organ failure. In accordance with these clinical observations, IPA Tox function analysis predicted significant inflammatory changes in liver and kidneys based on the gene expression. In fact, we have shown that significant lung and liver inflammation does occur in HLA-DR3 transgenic mice at 48 h following intranasal exposure to SEB, which also causes SIRS and TSS (50, 56). Overall, a strong upregulation of T cell-derived cytokines/chemokines by SEB underscores the foremost underlying difference between the pathogenesis of sepsis and superantigen-induced TSS. Nonetheless, identification of several other pro- as well as anti-inflammatory genes that are also noticed in other inflammatory diseases, such as sepsis, trauma, burn, hemorrhagic shock (7, 16) etc., indicates the presence of common pathways that lead to SIRS, MODS, and mortality in these conditions, which could be potential targets for pharmacologic intervention.
To this end we tested the effect of bortezomib on SEB-induced gene expression patterns. Bortezomib is a reversible proteasome inhibitor approved for clinical use for the therapy of multiple myeloma (55). However, because of its established ability to inhibit NF-κB pathway, efforts are being made to use bortezomib in treating a variety of inflammatory conditions. Studies in murine models have shown that bortezomib or other proteasome inhibitors could be of therapeutic use in mouse models of lupus (39), multiple sclerosis (14a), and inflammatory bowel disease (20a). Since several proinflammatory genes were significantly upregulated by SEB, and the NF-κB pathway is known to be involved in many of these cascades, we tested the role of bortezomib in TSS. There is currently no information available on the in vivo effects of proteasome inhibition on SEB-induced gene expression changes.
Although bortezomib treatment was able to suppress the induction of IL-6, IFN-γ, IL-2, LIF, IL-33, and IL-12a by SEB, when the actual serum levels were determined, only the levels of IFN-γ and IL-12 were significantly reduced. Similarly, while the expression of IL-1β gene was augmented by bortezomib in SEB-treated mice, serum IL-1β did not show significant changes. Surprisingly, bortezomib treatment increased the expression of many genes, at the same time decreasing the expression of some. Chitinase 3-like 3, the foremost gene upregulated by bortezomib treatment as identified by microarray, belongs to a family of enzymes called chitinases, which cleave chitin. Certain members of the chitinase family, such as chitinase 3-like-1, are implicated in some inflammatory conditions such as colitis (23) and asthma (41). However, no information regarding the role of chitinase 3-like-3, particularly in TSS or sepsis, is available. Moreover, the relationship between chitinase and proteasome has also not been investigated in mammals barring one plant study, which has shown that expression of chitinase is regulated by proteasomes (5). This warrants further investigation. F box protein 2 (FBP2) is the other gene whose expression was significantly increased in SEB-challenged bortezomib-treated mice. While it is known that FBP2 participates in the ubiquitin-proteasomal pathway of protein degradation (18), there are no reports available on the modulation of FBP2 expression by bortezomib in splenic cells in vivo and its role in superantigen-induced TSS. In similar lines, expressions of several other genes (profilin, synuclein-α etc.) were significantly affected (either increased or decreased) by bortezomib treatment. However, none of these molecules have been shown to be directly involved either in the normal immune responses or in the pathogenesis of TSS. Overall, our preliminary studies using bortezomib showed that it could have potential application in the treatment of TSS. However, more studies need to be performed to substantiate its use. In conclusion, our model provides novel insights into the pathogenesis of superantigen-induced TSS and might help in identifying new targets for therapeutic intervention during TSS.
This study was funded by National Institute of Allergy and Infectious Diseases Grant 1R01AI-068741-01A1.
We thank Julie Hanson and her crew for excellent mouse husbandry, Michelle Smart for characterizing the transgenic mice, and Jane C. Kahl for help with microarray data analysis.
↵1 The online version of this article contains supplemental material.
Address for reprint requests and other correspondence: G. Rajagopalan, Dept. of Immunology, Mayo Clinic College of Medicine, 200 1st St., SW, Rochester, MN 55905 (e-mail:).
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