s2fieldsofstudy: Biology Medicine

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Diminished PRRX1 Expression Is Associated With Increased Risk of Atrial Fibrillation and Shortening of the Cardiac Action Potential

Background— Atrial fibrillation (AF) affects over 33 million individuals worldwide. Genome-wide association studies have identified at least 30 AF loci, but the mechanisms through which individual variants lead to altered disease risk have remained unclear for the majority of these loci. At the 1q24 locus, we hypothesized that the transcription factor PRRX1 could be a strong candidate gene as it is expressed in the pulmonary veins, a source of AF in many individuals. We sought to identify the molecular mechanism, whereby variation at 1q24 may lead to AF susceptibility. Methods and Results— We sequenced a ≈158 kb region encompassing PRRX1 in 962 individuals with and without AF. We identified a broad region of association with AF at the 1q24 locus. Using in silico prediction and functional validation, we identified an enhancer that interacts with the promoter of PRRX1 in cells of cardiac lineage. Within this enhancer, we identified a single-nucleotide polymorphism, rs577676, which alters enhancer activity in a mouse atrial cell line and in embryonic zebrafish and differentially regulates PRRX1 expression in human left atria. We found that suppression of PRRX1 in human embryonic stem cell–derived cardiomyocytes and embryonic zebrafish resulted in shortening of the atrial action potential duration, a hallmark of AF. Conclusions— We have identified a functional genetic variant that alters PRRX1 expression, ultimately resulting in electrophysiological alterations in atrial myocytes that may promote AF.

Introduction
Atrial fibrillation (AF) is the most common cardiac arrhythmia, currently affecting over 3 million people in the United States 1 , and 33.5 million worldwide 2 . AF also is associated with substantial morbidity and mortality 3 . Although many clinical risk factors have been described, in recent years it has become increasingly clear that AF is heritable 4 . To date, at least 30 distinct genetic loci for AF have been identified in genome wide association studies (GWAS) [5][6][7][8][9][10][11][12] . However, as with most GWAS loci, the specific mechanism(s) how an AFassociated risk variant leads to the arrhythmia remains unknown.
The top variant at the AF locus on chromosome 1q24 was previously identified approximately 63kb upstream of the gene PRRX1 in both Europeans (rs3903239; odds ratio (OR) = 1.14, 95% confidence interval (CI) = 1.10-1.17; P = 8.4 ×10 −14 ) 8 and Japanese (rs639652, r 2 of 0.935 with rs3903239). PRRX1 is a homeobox containing transcriptional co-activator 13,14 that is expressed throughout embryonic development, especially in mesenchymal tissues 14 , and has been implicated in regulation of epithelial to mesenchymal transition 15 . PRRX1 is an intriguing candidate gene for AF since it is known to be expressed in the heart and pulmonary veins 16,17 , the source of AF triggers in many patients 18 .
We therefore hypothesized that the AF associated variants at the 1q24 locus may regulate the expression of PRRX1. We identified an AF associated SNP which modulates the activity of an enhancer upstream of PRRX1 and results in diminished PRRX1 expression in human left atrial tissue. Furthermore, we found that loss of PRRX1 expression results in shortening of the atrial APD in human cardiomyocytes and embryonic zebrafish myocardium. In sum, our findings implicate PRRX1 as the causative gene at this locus and provide a mechanism for the genetic association at the 1q24 locus for AF.

Enhancer/Promoter Activity Detection in Zebrafish
Zebrafish embryos were microinjected at the single cell stage with 0.5nL of the enhancer sequence upstream of the cfos minimal promoter driving eGFP expression (25ng/μl) along with transposase mRNA (10ng/μl). The PRRX1 promoter region was cloned in frame upstream of eGFP using the backbone vector lacking cfos minimal promoter. EGFP fluorescence was assessed at 72 hpf. mRNA was collected (Zymo Research, USA) and cDNA synthesized (BioRad Laboratories, USA) according to standard protocols. qRT-PCR analysis was conducted using SYBR green supermix on a BioRad CFX384 Real-Time System. ef-1α and β-actin were used as housekeeping genes. Primer sequences are listed in Supplemental Table S1.

Study Samples for Sequencing of the PRRX1 Locus
Written informed consent was obtained from all participants prior to study enrollment. The study was approved by the Institutional Review Board at Massachusetts General Hospital. We selected cases from the Massachusetts General Hospital Atrial Fibrillation Study with AF onset before 66 years of age, and no history of myocardial infarction, heart failure, or structural heart disease as assessed by echocardiography. As expected, there is a male predominance among younger patients with AF. We selected referents from the Framingham Heart Study with no personal or family history of AF. Referents were further matched to cases on the basis of age, sex, and hypertension status. Principal components analysis on previously genotyped samples was performed to exclude ancestral outliers (Supplemental Figure 1). Both cases and referents were self-identified to be of European descent and both studies were from the same geographical region.

Sequencing and Bioinformatics Analysis of the PRRX1 Locus
A custom NimbleGen capture kit was created for chromosome 1: 170,555,163-170,713,376 and sequencing was performed on the Illumina HiSeq 2500 platform. We used BWA 19 to align the short reads to the reference human genome (NCBI Build 37, hg19), which were then converted into BAM files by SAMtools 20 . We also performed local realignment to minimize mismatching of bases across all the reads, and base quality recalibration to correct base qualities using the GATK software package. Duplicate reads were marked by MarkDuplicates using the Picard software package. Only the first read pair in each duplicate cluster was kept for downstream analysis. Single nucleotide variations were then called by the UnifiedGenotyper function using the GATK software package 21 . All samples were called simultaneously, and a project VCF file was created that included the genotype calls for all samples.
Common variants were defined as variants with a minor allele frequency (MAF) of ≥1% and rare variants with a MAF of <1.0%. Common variants were tested for association with AF using logistic regression and adjusting for age at enrollment, sex and hypertension status. We employed a conservative Bonferroni correction for the common variant analysis (0.05 / 333 common SNPs in the region sequenced = 1.5 × 10 −4 ). For the 1,285 rare variants, we examined the associations of SNP sets with AF, using sequence kernel association test (SKAT) with the default (Wu) weight 22 . We tested groups of common and rare variants sequenced at the PRRX1 gene region for association with AF using a rolling window approach (window size of 10,000 base pairs and an overlap of 5,000 base pairs). We also tested coding variants within the PRRX1 gene itself for association with AF. We then stratified analyses by allele frequency classes (MAF<0.01; MAF>0.01 and MAF<0.05; MAF<0.05) to specifically assess whether rare or low frequency variation associated with AF. All analyses were adjusted for age, sex, and hypertension status. SKAT testing was performed using the R version 3.1 seqMeta package (https://www.r-project.org/). The effect of variants on protein coding was predicted using the RefGene gene definition (https:// genome.ucsc.edu/). Analysis of evolutionary conservation of the amino acids was performed using the PhyloP tool. PolyPhen-2 was used to predict the effect of the amino acid substitution in protein function.

Identification of Putative Enhancers
To identify potential PRRX1 enhancers, we analyzed both mammalian conservation and defined genomic markers of transcriptional enhancers (H3K4Me1 and DNAse hypersensitivity from the ENCODE database 23 ). Region chr1:170560110-170642899, the region with a R 2 >0.3 (SNAP, 1000 Genomes Pilot 1) with the most significant AF SNP from GWAS, rs3903239, was screened for potential enhancer regions based on UCSC browser tracks(hg19) for mammalian conservation, H3K4Me1, and DNAseI hypersensitivity in human cardiac fibroblasts and human cardiac myoblasts. For the H3K4Me1 track, human skeletal muscle myoblasts (HSMM) or normal human lung fibroblasts (NHLF) were selected for further analysis. Potential enhancer regions were selected based on the fulfillment of 2 out of the 3 of the following criteria: 1) mammalian conservation score by PhyloP more than 1, 2) DNAseI hypersensitivity by ENCODE more than 50, and presence of DNAseI hypersensitivity peak (FDR=0.5%) in human cardiac fibroblasts or human cardiac myocytes, 3) ENCODE enhancer and promoter-associated histone mark (H3K4Me1) greater than 10 in (HSMM) or (NHLF).

Cell Culture and Luciferase Assays
HL-1 cells were grown on gelatin-fibronectin coated plates under standard conditions 24 . For luciferase assays, cells were transfected with reporter vectors (pGL4.23 [luc2/minP]) containing the various enhancer regions upstream of the CMV minimal promoter. Renilla luciferase driven by a SV40 promoter (pGL4.73[luc2/SV40]) was co-transfected as a transfection control. Transfection was performed using Lipofectamine LTX with Plus reagent (Invitrogen) according to manufacturer's instructions. Luciferase activity was assayed using the Dual-Luciferase Reporter (DLR) Assay System according to manufacturer's instructions in six biological replicates. Enhancer activity was calculated by normalization of Firefly luminescence to Renilla luminescence and the DNA concentration. To ensure that sufficient nucleotide context was provided for enhancer activity measurement, all final constructs were determined to have activity greater than an empty vector control with at least one allele.

Chromatin Conformation Capture
A human cardiac fibroblast (HCF) cell line was purchased from Promo Cell (Heidelberg, Germany) and maintained according to manufacturer's instructions. The H7 hESC line (WA07; WiCell) was used as a reference cell line. Cells were maintained in feeder-free culture in Essential 8 medium 25 on Geltrex coated plates (Invitrogen).
HCF and hESC were dissociated in 0.04% and 0.25% Trypsin EDTA, respectively, with subsequent neutralization with 0.05% trypsin inhibitor (for HCF) or DMEM medium containing 10% of fetal bovine serum (for hESC). 5×10 6 cells per experiment were used. The 3C library was generated as described by Naumova et al 26 using HindIII as restriction enzyme. BAC clone R11-907L24 was utilized as random ligation control. Interaction frequency was measured by TaqMan qPCR. Quality of primer pairs was assessed with mock controls, defined as samples in which one of the crucial steps: fixation, restriction, or ligation, was omitted. Primer pairs that showed amplification in any of the mock controls were excluded from the analysis. Supplemental Table S1 contains the primer sequences used with respective distance between the restriction site and the probe. A separate primer was designed to assess the rate of self-ligation (self-loop) to control for ligation efficiency. Serial dilutions of BAC clone random ligation DNA were used to generate a standard curve (lg[DNA] to cycle number) for each primer pair. The linear regression derived from the standard curve for each primer pair was used to calculate arbitrary concentration of the ligation product in the sample. This number was then divided by the number obtained for the self-loop in this sample to normalize for the ligation efficiency. For each cell type, values were normalized to the average value for the Pr6 and Pr4 primers (on each side of the enhancer) as internal control to normalize for the efficiency of the ligation of the enhancer with the nearby regions. The average value for different biological regions; enhancer region, PRRX1 promoter region, PRRX1 gene and distant region was used for comparison between the two cell types.

Hi-C Data Analysis
Hi-C data from Dixon et al., Jin et al. and Naumova et al. [27][28][29] were mapped and processed using hiclib software 30 at 10kb, 20kb and 40kb resolutions. All hESC Hi-C datasets from Dixon et al. 27 and Jinet et al. 28 were pooled together; all wild type IMR90 Hi-C datasets and were also pooled together. Hi-C interaction maps at 10kb and 20kb were processed as in Naumova et al. 29 ; directionality ratios were obtained as in Naumova et al 29 , with 20kb resolution and 400kb distances.

Expression Quantitative Trait Loci Analysis from Human Atrial Samples
A total of 121 human left atrial samples were used for the expression quantitative trait loci (eQTL) analysis. Surgical samples were obtained at Massachusetts General Hospital during cardiac surgery for valvular heart disease (n=83) or cardiac transplantation (n=27). Normal left atrial tissue was obtained from the National Disease Research Interchange repository (n=11). The sample collection was approved by the Institutional Review Board at Massachusetts General Hospital. Atrial tissue was homogenized in 1 ml of TRIZOL® Reagent (Applied Biosystems, Foster City, CA) and mRNA was extracted according to the manufacturer's instructions. Reverse transcription reaction was performed using iScript (BioRad). qRT-PCR analysis was conducted using SYBR green supermix (BioRad) on a BioRad CFX384 Real-Time System. TBP and HPRT were used as housekeeping genes.
Sequences of the qRT-PCR primers used are listed in Supplemental Table S1.

Optical Mapping in Human Embryonic Stem Cell Derived Cardiomyocytes
H7 embryonic stem cells (WA07; WiCell) were electroporated with PX458 construct (Addgene, 48138) carrying both spCas9-GFP nuclease and single guide RNA (sgRNA) targeting exon 1 of the PRRX1 gene (sgRNA sequence: GAGTCGCCGGGACTCACCAG, hg19 chr4:170633555-170633574). Cells positive for GFP signal were selected by flow cytometry and expanded as single colonies in 96-well plates. Sanger-sequencing was performed to identify the colonies with an insertion or deletion that led to a frameshift in the PRRX1 transcript. A single clone with a bi-allelic single base pair insertion after base 211 of the coding region induced a frameshift that resulted in a protein truncation at amino acid 81. Wild-type and PRRX1-knockout stem cells were differentiated towards cardiac lineage using previously published protocols 31 . Arclight, a genetically encoded fluorescent voltage sensor 32 , was transduced into the differentiated cardiomyocytes (ESC-CMs) using a lentiviral vector. At day 33 of differentiation, ESC-CMs were imaged 96 h post infection with Tyrode's solution (136mM NaCl, 5.4mM KCl, 10mM Dextrose, 1mM MgCl, 1.8mM CaCl 2 , 0.33mM NaH 2 PO 4 , 5mM HEPES, pH 7.35) perfusion at 37 °C. A CardioCCD-SMQ camera (RedShirt Imaging) and a Nikon Eclipse Ti-U inverted microscope equipped with a FITC filter set were used for ArcLight fluorescence recording at 500Hz. ESC-CMs were rate-controlled by field pacing using a S48 Stimulator (Grass Products). APD 80 was calculated for both wild-type and PRRX1-null ESC-CMs using a method described previously 32 .

Morpholino Design and Zebrafish Embryo Microinjections
Zebrafish of the Tübingen/AB strain were maintained according to standard methods. Morpholino oligonucleotides (MOs) designed to disrupt the proper splicing of zebrafish genes prrx1a (Exon1/Intron1 (1), Exon3/Intron3 (2)), prrx1b (Exon1/Intron1 (1), Exon2/ Intron2 (2)), were obtained from Gene Tools LLC. Semi-q RT-PCR was used to assess knock-down efficiency. For control of non-specific toxicity, a non-targeting MO of equal length but differing nucleotide concentration was used. MOs were diluted in injection buffer (0.4 mM MgSO 4 , 0.6 mM CaCl 2 , 0.7 mM KCl, 58 mM NaCl, 25 mM HEPES pH 7.1) and microinjected into the yolks of single cell stage embryos at a final concentration of 0.2 mM (for prrx1 E1I1 and prrx1b E1I1 MOs), 0.1mM (for prrx1a E3I3 MO), and 0.3 mM (for prrx1b E2I2) in a standardized volume. At 72 hours post fertilization (hpf) mRNA was extracted using TRIZOL® Reagent according to manufacturer's instructions; cDNA was synthesized using iScript (BioRad). Effective knockdown was confirmed by RT-PCR at 27 cycles. ef-1α was utilized as a reference gene. Densitometry analysis was performed using ImageJ version 1.47. All MOs and percent of calculated knock-down are listed in Supplemental Figure S2. All primers used for analysis of knock-down efficiency are contained with Supplemental Table S1.
Color brightfield images of morpholino-injected embryos were obtained on an Olympus SZX16 microscope at 72 hpf. Heart rate was measured at 72 hpf by phase contrast imaging on a Nikon Eclipse Ti equipped with a Hamamatsu Orca-Flashcam 2.8 at an effective framerate of acquisition 88fps. Heart rate was determined manually using ImageJ version 1.47. Measurements of cardiac contractility were conducted at 72 hpf. Ventricular fractional shortening was assessed by measuring the change in inner chamber diameter when measured perpendicular to the direction of blood flow. Atrial area was measured in ImageJ version 1.47 at the end of diastole. Optical mapping to determine atrial action potential durations at 72hpf was performed as previously described 33 .
To examine the presence of fibrosis in morpholino-injected embryonic zebrafish hearts (72 hpf), excised hearts were subjected to aniline blue stain for 5 min (Trichrome Stain; Abcam; ab150686), and mounted in synthetic resin (DPX Mountant for histology; Sigma; 06522). Color micrographs were generated using an Olympus SZX16 microscope.

Statistical Analyses
Results are presented as mean ± standard error of the mean. Statistical analysis was performed using Prism 6 (GraphPad Software, La Jolla, CA, USA). Statistical analysis of differences was determined by Student's two-tailed t-test for comparison of two groups, or one-way ANOVA with Dunnett's post hoc test for data with greater than two groups.

Targeted resequencing of the PRRX1 locus reveals a broad region of association with AF
The association between PRRX1/1q24 locus and AF had previously been established in a discovery sample consisting of 6,707 individuals with and 52,426 without AF, and replicated in an additional 5,381 individuals with and 10,030 without AF. 8 The identified SNP, rs3903239, was significantly associated with AF and resides upstream of PRRX1 (RR 1.14, CI 1.10-1.17, P= 8.4 × 10 −14 ). 8 To comprehensively identify the common and rare genetic variation at the PRRX1 locus, we sequenced an approximately 158kb region in 462 AF cases from the Massachusetts General Hospital (MGH) AF Study and 464 referents from the Framingham Heart Study (Table 1 and Figure 1). The sequencing was performed with >200X coverage. Raw reads were aligned to the reference human genome (NCBI Build 37, 2009) after which we applied stringent filters to exclude variants with low quality, as defined by those with a calling quality less than 30, a missing call rate higher than 5%, or a strand bias >−0.1, or depth of coverage <10× or higher than 300x.
We identified 333 common SNPs with a minor allele frequency of >1%, and 1,285 rare or singleton SNPs (Supplemental Table S2). Included within this set were 6 missense variants (Supplemental Table S3), 2 synonymous variants, and 1 proximal to a splice site, all of which were contained within the PRRX1 gene. We then tested the association of each common variant with AF status by logistic regression, and adjusted the analysis by age, sex, and hypertension. We identified a broad, approximately 82 kb, region that was associated with AF ( Figure 1). Within this region, the SNP most significantly associated with AF, rs10919449, is intronic to PRRX1 (OR 1.48, 95% CI 1.22-1.79; P = 4.4 × 10 −5 ) (Supplemental Table S2) and is located approximately 69kb away from the most significant SNP identified in a prior AF GWAS, rs3903239 (OR 1.41, 95%CI 1.17-1.71, P=2.8×10 −4 ) 8 .
We did not find any association between AF and rare variants (MAF<1%), indels or coding variants at this locus, although given our sample size the power for these analyses was limited (Supplemental Table S2, S3). Similarly, we did not observe associations between specific rolling windows comprised of both common and rare variants and AF, or coding variation in PRRX1 with AF.

Identification of functional regulatory elements at the PRRX1 locus
Given the broad and largely intergenic region that was associated with AF, we hypothesized that the causative variant for AF was regulating the expression of the adjacent PRRX1 gene. To identify potential PRRX1 enhancers, we analyzed both mammalian conservation and defined genomic markers of transcriptional enhancers (H3K4Me1 and DNAse hypersensitivity from the ENCODE database 23 ) within this region. Potential enhancer regions were selected from the genomic region (chr1:170560110-170642899 as defined by the region with R 2 >0.3 with the most significant AF SNP, rs3903239) based on fulfillment of two out of the three criteria: 1) mammalian conservation score by PhyloP 34 more than 0.5; 2) ENCODE DNAseI hypersensitivity raw signal of more than 50 in human cardiac fibroblasts or human cardiac myocytes; and 3)ENCODE enhancer and promoter-associated histone mark (H3K4Me1) of more than 10 in skeletal myoblasts (HSMM) or neonatal fibroblasts (NHLF). As a result, seven putative enhancer regions (E-K) and PRRX1 promoter region (Pr) were prioritized for further analysis. Genomic coordinates for these regions are contained within Supplementary Table S4. Microinjection of eGFP reporter constructs in embryonic zebrafish revealed that two putative enhancer regions, E and F, displayed strong eGFP expression in cardiac and skeletal muscle tissue while the PRRX1 promoter (Pr) exhibited a similar pattern of activity at notably lower levels (Figure 2A,B).

Chromatin conformation capture links active regulatory elements to PRRX1 promoter
To determine the interaction between the E and F enhancer regions and nearby promoters, we utilized a tiered approach, using both Hi-C and 3C (chromatin conformation capture) to further analyze the target regions. In silico analysis revealed that DNAse hypersensitivity around the E and F enhancer regions in human cardiac myocytes (HCM) and human cardiac fibroblasts (HCF) was lacking in human embryonic stem cells (hESC), establishing the hESC as a negative reference for further interaction analysis (Supplemental Figure S3). First, to determine which promoters may be in physical contact with the E and F enhancer regions at a lower resolution but with a wider genomic context we explored the Hi-C map in hESC and IMR90 fibroblasts. In hESC cells, the E and F enhancer regions are embedded in a topological domain that contains the PRRX1 promoter at the margin ( Figure 2C). In Hi-C data for a fibroblast cell line (IMR90) 27,29 , this region undergoes a major structural reorganization during differentiation, characterized by a merging of two adjacent topological domains ( Figure 2C, Supplemental Figure S4) and significant alterations in the patterns of interactions between the E and F enhancer regions and the PRRX1-containing domain (Supplemental Figure S4). Next, to identify a potential increase in interaction frequency between the enhancer region and PRRX1 promoter also occurs in cardiac cells, we employed a targeted approach using 3C on hESC and human cardiac fibroblast cell lines. The E and F enhancer region had an increased interaction frequency with the PRRX1 promoter in cardiac fibroblasts as compared to hESC (103 ± 57%, P=0.03; Figure 2D). No difference in relative contact probability was detected between the cell lines when examining regions proximal to the enhancer, the PRRX1 coding region, or a distant genomic region. In sum, these data demonstrate a physical link between the E and F enhancer regions and the PRRX1 promoter in relevant tissues, supporting the hypothesis that alterations in PRRX1 expression via the E and F enhancer regions may underlie the AF association signal.

Identification of a Functional SNP at 1q24 Locus
Next, we sought to identify any functional SNPs within the E and F enhancers and PRRX1 promoter. We cloned 100-300bp regions around the 21 common SNPs (MAF>5%) and compared the enhancer activity of risk vs non-risk alleles by luciferase assays in a murine atrial myocyte (HL-1) cell line. Among SNPs within E and F enhancer and PRRX1 promoter regions, only the region surrounding SNP rs577676 exhibited altered enhancer activity, with the AF risk allele displaying an approximately 1.5-fold decrease in luciferase activity ( Figure 3A, Supplemental Figure S5). Importantly, the immediate region surrounding rs577676 has a positive PhyloP conservation score of 0.99, suggesting the evolutionary stability expected for putative enhancers. Further, the enhancer activity of the rs577676 region in zebrafish embryos was localized to the heart and skeletal muscle, with consistently higher expression in non-risk allele shown by epifluorescence imaging and qRT-PCR ( Figure 3B,C). Interestingly, although rs577676 has moderate association with AF in the targeted sequencing analysis (P = 2.7×10 −4 , Risk Allele Frequency (RAF) = 0.57, OR = 1.33, 95% CI 1.10-1.38), it is only in modest linkage disequilibrium with adjacent SNPs at the 1q24 locus (r2=0.605 with rs3903239). Importantly, although rs577676 does not reach the genome wide significance threshold in the present study due to the limited sample size used for sequencing, it was significantly associated with AF in a previous GWAS (P = 1.3×10 −10 , RAF = 0.56, OR = 1.14, 95% CI 1.10-1.19). Importantly, after conditioning on the top SNP from previous GWAS (rs3903239), the association of rs577676 with AF is abrogated (p = 0.67). We also performed a sensitivity analysis to ensure that observed associations were not due to population sub-structure. After adjusting for principle components derived from previously genotyped samples, rs577676 remained significantly associated with AF, although the association was attenuated.
To define the necessity of the rs577676 to drive enhancer activity, we performed serial deletions within this region and found that removal of 20 base pairs surrounding rs577676 led to almost complete loss of the enhancer activity (Supplemental Figure S6). In silico analyses of potential transcription factor binding sites which may be disrupted by genotype at rs577676 were performed using JASPAR. 33 potential enhancers were predicted to be generated by the minor allele while 3 potential repressors were identified exclusively with the major allele (Supplemental Table S5).

eQTL analyses link AF associated SNP to expression of PRRX1
Chromatin conformation capture experiments demonstrate that the E enhancer is in contact with the PRRX1 promoter, but did not rule out the possibility of effects on other promoters within the topologically associated domain. Given the differential activity of the rs577676 enhancer by reporter assays, we then sought to directly link this altered enhancer activity to altered expression of nearby genes in human left atrial tissue samples. To ensure our approach was unbiased, we determined whether the genotype of rs577676 was associated with the expression of any genes in same topologically associated domain as defined by the Hi-C analysis. We performed expression quantitative trait loci (eQTL) analysis in 121 human left atrial tissue samples ( Figure 3D). Among the 5 genes within the topologically associated domain, only PRRX1 transcript levels correlated with genotype at rs577676, with a 1.7 fold decreased expression in those homozygous for the risk allele. Thus, PRRX1 expression is regulated by the PRRX1 enhancer in the heart and its expression is dependent on the genotype at rs577676.

PRRX1 suppression results in action potential shortening
Since shortening of the atrial APD is a well described in the pathophysiology of AF, 35 we determined the role of PRRX1 in cardiac electrophysiology in both stem cell derived cardiomyocytes ( Figure 4A,B,E) and embryonic zebrafish ( Figure 4C,D). For the former, we utilized CRISPR-Cas9 mediated knockout of PRRX1 in human embryonic stem cells and morpholino-mediated knockdown of the putative PRRX1 orthologues in the zebrafish (prrx1a and prrx1b). PRRX1-null human ES cells were differentiated into cardiomyocytes by standard protocols, infected with the fluorescent voltage reporter, Arclight, and then assayed for action potential duration (APD 80 ) by optical mapping. PRRX1 knockout cardiomyocytes displayed significantly shortened action potentials at all pacing rates when compared to controls ( Figure 4A,B). Interestingly, PRRX1 cells also maintained a relatively stable action potential duration regardless of pacing rate, a finding in contrast to the typical use-dependent action potential modulation observed in wild-type cardiomyocytes (p<0.001).
We then attempted to identify potential mechanisms by which PRRX1 modulation may affect the action potential duration. We assayed the expression levels of 5 major ion channels known to affect the action potential duration in cardiomyocytes (CACNA1C, KCNH2, KCNQ1, RYR2, and SCN5A). No significant differences were observed between control and PRRX1 null myocytes ( Figure 4E).
For the zebrafish, minimal effective doses of morpholino were evaluated by RT-PCR (Supplemental Figure S2). At 72 hours post fertilization, a time point when distinct cardiac chambers are formed and both prrx1a and prrx1b are robustly expressed within the cardiac regions (Supplemental Figure S2), the gross morphology of prrx1a and prrx1b knockdown embryos was indistinguishable from controls (Supplemental Figure S2). Similarly to the human myocytes, significant shortening of atrial action potential (114.7±1.9ms and 116.8±1.9ms vs 124.9±1.4ms in controls, P=0.0002 and P=0.006, respectively) was observed in prrx1a knockdown embryos ( Figure 4C,D). s rs577676-mediated modulation of PRRX1 expression in human left atrium is more modest than the severe diminishment utilized in our models, we next sought to examine action potential durations with various doses of prrx1a morpholinos. This action potential duration shortening was reduced in a dose-dependent manner when progressively lower amounts of prrx1a morpholinos were injected, suggesting that even small modulations in PRRX1 expression may be sufficient to modulate the action potential duration (Supplemental Figure S2). In contrast, knockdown of prrx1b had no effect on action potential duration when compared to controls (124.9±2.5ms and 122±3.4ms). 1 Neither prrx1a nor prrx1b knockdown had significant effect on resting heart rate or ventricular contractility, nor were any ectopic foci of contractile initiation observed (Supplemental Figure S2).

Discussion
Over the past decade, thousands of genetic loci have been identified for a wide variety of diseases and traits using GWAS. However, despite the rapid pace of discovery, relatively few studies have directly linked a genetic variant at a locus to plausible biological mechanism for disease. [36][37][38][39][40][41][42] For AF, at least 30 loci have been identified to date, yet the underlying molecular mechanism at most of these loci remains incompletely understood. In the present work, we have used an integrative functional genomics approach that combines resequencing of the candidate locus, phenotypic modeling in both zebrafish and stem cell derived cardiomyocytes, chromatin conformation analyses, the identification of gene regulatory elements, and eQTL mapping to elucidate a functional variant at the 1q24 locus for AF.

PRRX1 is the AF-associated gene at the 1q24 locus
Although genome wide studies have identified many genomic regions associated with AF, determining which nearby gene or genes are related to the association signal is a critical step for understanding the biological pathways underlying disease. In the present study, we provide three independent analyses that strongly suggest that PRRX1 is the causative gene at the 1q24 locus for AF. First, diminished PRRX1 expression in ES-derived cardiomyocytes and zebrafish resulted in action potential shortening, a hallmark of AF in humans. 35 Second, eQTL analyses directly linked the genotype of rs577676 to the expression of PRRX1 in human left atrial samples. Finally, chromatin conformation studies demonstrated that an enhancer modified by rs577676 is in close proximity to the PRRX1 promoter in threedimensional space. Additionally, in recent work Lin and colleagues found an increased frequency of rare, nonsynonymous variants in the coding region of PRRX1 in individuals with AF. In sum, these findings strongly suggest that PRRX1 is the gene related to AF at this locus. 43 Ideally, an RNA-seq based eQTL dataset from human left atrial tissue could be used to not only identify the cis-QTL, which is PRRX1 for the 1q24 locus, but also trans-QTLs which may give insight into downstream function of this gene alteration. Generation of these publically available datasets should be the focus of future effort.
In addition to the present data detailing a role for PRRX1 in atrial myocyte electrophysiology, previous work on PRRX1 also suggests plausible biological pathways whereby altered PRRX1 expression would result in an increased risk of AF. Among these, PRRX1 is highly expressed in mesenchymal tissues 14 including the heart and pulmonary veins, 16,17 and has been shown to regulate epithelial to mesenchymal transition 15 , a critical feature of human cardiac development. Moreover, Prrx1-deficient mice showed abnormalities of great vessels, such as abnormal positioning and awkward curvature of the aortic arch, misdirected and elongated ductus arteriosus and an anomalous retro-esophageal right subclavian artery 44 . In future studies, it will be interesting to examine function of atrial or pulmonary venous restricted knockouts of PRRX1 in mice to further delineate the role of this gene in atrial structure and function.

Identification of rs577676 as a functional variant for AF at the 1q24 locus
The disease variants identified by a GWAS are typically a proxy rather than the functional variant at a locus. It remains challenging to move from a SNP identified by GWAS to a functional variant, particularly when an association signal can tag a large haplotype block associated with disease. In our current work, we resequenced a large genomic region at 1q24, encompassing the entire PRRX1 gene as well as nearly 80kb upstream from the transcriptional start site. In order to be inclusive for potential functional variants which may be somewhat distant either in genomic distance or in modest linkage disequilibrium with a sentinel SNP, our sequencing efforts the sequencing included the genomic location bounded by and r 2 of 0.3, as well as the additional 75kb extending through the PRRX1 gene region. This sequencing effort was performed to identify not only common risk variants, but also rare genetic variation, structural, and copy number variation at the 1q24 locus. The latter were of particular interest as they are potential sources of AF risk that are not readily identified by traditional GWAS methodologies. Although our power was modest, we found a broad area of association with AF similar to our initial GWAS.
We therefore employed an in silico prioritization strategy for identifying functionally active regulatory regions at this locus. We took advantage of existing ENCODE datasets on histone post-translational modifications and DNase hypersensitivity in cardiac cells as a surrogate for active enhancers and tested their activity in a vertebrate model. We identified two enhancers and the PRRX1 proximal promoter as regions with tissue-specific activity in the heart. In reporter assays in a mouse atrial cell line, we found a single AF-associated variant, rs577676 that significantly alters enhancer activity. Conditional analyses definitively linked rs577676 to the top signal at this locus, although the possibility remains that other SNPs within the risk haplotype may also contribute to altered enhancer activity and gene regulation. Although our approach provided both qualitative and quantitative assessments of PRRX1 enhancer function, it is clear that future analyses of GWAS loci can be improved, particularly in light of the recent data releases from the NIH Roadmap Epigenomics Mapping Consortium. 45

Summary and Limitations
In summary, PRRX1 expression is associated with action potential shortening in two independent model systems. We have identified an enhancer upstream of PRRX1 that is physically associated with the PRRX1 promoter, and is modulated by SNP rs577676. This SNP in turn is associated with reduced PRRX1 expression. Thus, the AF risk allele (C) of rs577676 is associated with reduced PRRX1 expression and an electrophysiological phenotype that would be expected to promote AF. Based on the multiple lines of functional evidence, we believe that the rs577676 risk allele most likely acts through modulating PRRX1 expression.
Our study was subject to a number of potential limitations. First, despite our extensive analysis of functional variation at the PRRX1 locus, it is possible that there is more than a single functional variant at a locus. Second, it would be ideal to identify the specific transcription factor that is modulated by rs577676. Unfortunately, the in silico prediction of transcription factor binding remains imperfect and CHIP-seq databases are currently incomplete. Third, future studies directed at defining the spatiotemporal expression of the enhancer modulated by rs577676 would be interesting. Finally, while our study identifies the major effector of the AF risk, reduced PRRX1 expression, and the cellular phenotype which creates a pro-arrhythmic substrate, action potential shortening, the downstream transcriptional pathway through which this action potential shortening occurs remains unclear. We attempted a targeted candidate gene analysis in our stem cell derived cardiomyocyte model, but observed no significant alterations. Further work examining the entire transcriptome, ideally in a single cell manner due to the heterogeneity of stem cellderived cardiomyocyte cultures, will be necessary to further elaborate on these transcriptional pathways. It is also possible that additional pathogenic mechanisms for AF may not be sufficiently captured by our models, including fibrotic deposition, myolysis and inflammation. Determining whether these factors also result from altered PRRX1 activity would be of interest in future work. Ultimately, the best platform for studying these possibilities will be primary human atrial tissue, where the cardiovascular effects of the PRRX1 enhancer and gene may be studied in a more native context.

Conclusion
In conclusion, we have implicated PRRX1 as the causative gene at the 1q24 locus for AF, and we have identified a SNP that functionally modulates a PRRX1 enhancer. Our approach provides a potentially generalizable path for identifying the functional variants at other cardiovascular GWAS loci.

Supplementary Material
Refer to Web version on PubMed Central for supplementary material.

Clinical Perspective
Atrial fibrillation (AF) is a common and morbid arrhythmia. In addition to the wellknown clinical risk factors, AF has a considerable genetic risk component and nearly 30 genetic loci have been identified in genome-wide association studies. At the 1q24 locus for AF we found that a common genetic variant leads to altered expression of the transcription factor PRRX1 in human left atria. In turn, suppression of PRRX1 expression in zebrafish or stem cell models revealed significant shortening of the action potential duration. Our findings provide a link between the genetic association at this locus and a potential mechanistic link between PRRX1 and AF. Further study of this pathway will ultimately provide greater insight into the pathogenesis of AF and may provide new potential targets for therapeutic intervention.


extfieldsofstudy: Biology Medicine

text:
FDA-approved immunosuppressants targeting staphylococcal superantigens: mechanisms and insights

Immunostimulating staphylococcal enterotoxin B (SEB) and related superantigenic toxins cause diseases in human beings and laboratory animals by hyperactivating cells of the immune system. These protein toxins bind to the major histocompatibility complex class II (MHC II) molecules and specific Vβ regions of T-cell receptors (TCRs), resulting in the stimulation of both monocytes/macrophages and T lymphocytes. The bridging of TCR with MHC II molecules by superantigens triggers intracellular signaling cascades, resulting in excessive release of proinflammatory mediators and massive polyclonal T-cell proliferation. The early induction of tumor necrosis factor α, interleukin 1 (IL-1), interleukin 2 (IL-2), interferon gamma (IFNγ), and macrophage chemoattractant protein 1 promotes fever, inflammation, and multiple organ injury. The signal transduction pathways for staphylococcal superantigen-induced toxicity downstream from TCR/major histocompatibility complex (MHC) ligation and interaction of cell surface co-stimulatory molecules include the mitogen-activated protein kinase cascades and cytokine receptor signaling, activating nuclear factor κB (NFκB) and the phosphoinositide 3-kinase/mammalian target of rapamycin pathways. Knowledge of host regulation within these activated pathways and molecules initiated by SEB and other superantigens enables the selection of US Food and Drug Administration (FDA)-approved drugs to interrupt and prevent superantigen-induced shock in animal models. This review focuses on the use of FDA-approved immunosuppressants in targeting the signaling pathways induced by staphylococcal superantigens.

Introduction
Staphylococcal enterotoxin B (SEB) and the distantly related toxic shock syndrome toxin 1 (TSST-1) are common etiological agents that cause toxic shock syndrome. 1,2 The disease is characterized by fever, hypotension, desquamation of skin, and multiple organ system failure. [1][2][3] These virulence proteins produced by Staphylococcus aureus are commonly called superantigens as they potently stimulate T-cells, resulting in polyclonal T-cell activation. [4][5][6] Staphylococcal superantigens hyperactivate cells of the innate immune system and adaptive T-cells concomitantly by binding to the major histocompatibility complex class II (MHC II) molecules on antigen-presenting cells (APCs) and specific Vβ regions of T-cell receptors (TCRs). [6][7][8][9][10][11][12] However, their mode of interaction differs from conventional antigens in that they bind on the outside of the peptide-binding groove of MHC II and exert their biological effects as an intact molecule without being "processed" by APCs. In addition, recognition of a superantigen:MHC II complex by the TCR is not restricted by the major histocompatibility complex (MHC) and depends upon the variable region within a TCR β chain (Vβ). Structural properties of many superantigens are well characterized, and most residues involved in their binding to cell surface receptors on immune cells have been identified. 12,13 Various modes of interaction with MHC II and TCRVβ are used by superantigens to promote immunological synapse of interacting cells and cell activation. 14,15 Activated cells produce cytokines, chemokines, tissue factors, lytic enzymes, and reactive oxygen species (ROS), activating both inflammation and coagulation. [16][17][18] These cytokines include tumor necrosis factor α (TNFα), interferon gamma (IFNγ), and interleukin 1 (IL-1), proinflammatory mediators with potent immunoenhancing effects, known to be pathogenic at high levels in vivo. [18][19][20][21][22][23] Staphylococcal superantigens are stable, single-chain globular proteins of 22-30 kD that are highly resistant to proteases and heat denaturation. Despite differences in sequence homology among the staphylococcal enterotoxins (SEs) and TSST-1, they have similarities in their secondary and tertiary structures. 6,24 Crystallographic studies of staphylococcal superantigens reveal two conserved, tightly packed domains with a β-barrel domain at the N-terminal and a β-grasp motif at the C-terminal. The relatively conserved TCR-binding site is located in the shallow groove between these two domains. Superantigens bind to common, conserved elements outside the peptide-binding groove on MHC II molecules with a relatively high affinity. 6,24 There are at least two distinct binding sites on MHC II molecules for superantigens: 10 a common, low-affinity binding site involving the invariant α-chain of MHC II and a high-affinity, zinc-dependent binding site on the polymorphic β-chain. [24][25][26] The bridging of superantigens to MHC II and TCR allows cooperative interactions between receptors, hyperactivating the host immune system. Two decades of elegant structural and molecular studies defined binding motifs of bacterial superantigens with MHC II and TCRVβ. 6,24 Many excellent reviews are available on this topic so they will not be discussed further. 5,6,12,[24][25][26][27][28][29] Three signals of T-cell activation and signal transduction Similar to conventional antigen, the binding of superantigen/MHC II to TCR transmits the classical first signal for T-cell activation. 30 Upon superantigen binding, engagement of co-stimulatory molecules CD80 and CD86 on APCs with CD28 on T-cells delivers the second signal that optimizes T-cell activation through the formation of stable cell conjugates. 31,32 Other cell adhesion molecules and receptors such as intercellular adhesion molecule 1 (ICAM1) on APCs and leukocyte function-associated antigen 1 (LFA-1) on T-cells also participate in cell activation by superantigens. 33 Co-stimulatory signaling increases the stability of mRNA of IL-2, IFNγ, TNFα, granulocyte-macrophage colony-stimulating factor (GMCSF), and the expression of anti-apoptotic protein Bcl-xL to promote T-cell survival. [34][35][36] TCR and co-stimulatory receptors activate protein tyrosine kinases (PTKs), LCK, and ZAP-70, resulting in phospholipase C gamma (PLCγ) activation, release of intracellular second messengers, and increase in intracellular Ca ++ . 37,38 The increase in intracellular calcium concentration activates calcineurin phosphatase, which dephosphorylates nuclear factor of activated T-cells (NFAT), allowing for its translocation into the nucleus where it activates the expression of IL-2 and other T-cell cytokines for T-cell differentiation into T helper 1 (TH1) cells and other T-cell subsets. 30 Additionally, PTKs also activate protein kinase C (PKC) and Ras GTPase, both of which are also triggered by cell stress and growth factors. 30 The activation of PTK, PLCγ, and PKC initiates three important downstream signaling pathways: 1) Ca ++ /calcineurin pathway; 2) mitogen-activated protein kinase (MAPK) cascade; and 3) nuclear factor kB (NFkB) pathway, resulting in the activation of transcriptional factors NFAT, activating protein 1 (AP1), and NFkB. 30,[38][39][40] NFkB binds to the promoter region of many proinflammatory mediators, including IL-1 and TNFα, resulting in proinflammatory cytokine expression. 40 The third signal to fully activate T-cells consists of inflammatory cytokines and T-cell growth and differentiation factors, some of which can be induced by signals 1 and 2. 41 The signal transduction pathways of superantigen-activated T-cells are presented in Figure 1.

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FDA-approved immunosuppressants targeting staphylococcal superantigens resulting from all three signals of T-cell activation is essential for G1 to S phase transition as it controls cell proliferation and protein translation. 44,45 Additionally, mTORC1 also functions to integrate diverse signals of nutrient sufficiency and cellular energy via an upstream negative regulator, the adenosine monophosphate (AMP)-activated protein kinase (AMPK). 46

Cellular response to superantigens
Human peripheral blood mononuclear cells (PBMC) are often used to study immune cell activation and the subsequent cellular changes by superantigens as these cells are responsive to picomolar concentrations of SEs and TSST-1. 7,47,48 The cytokines IL-1, TNFα, IFNγ, IL-2, interleukin 6 (IL-6), and chemokines, specifically macrophage chemoattractant protein 1 (MCP-1), are induced early by superantigens in human PBMC. There is also a good correlation of the induction of these cytokines with lethal superantigeninduced shock in murine models. 19,21,23,[49][50][51][52] IL-1 and TNFα also activate other cells, including fibroblasts, epithelial, and endothelial cells, to perpetuate inflammation by inducing cell adhesion molecules and additional mediators from these cells. 53 Matrix metalloproteases (MMPs) and tissue factor induced by IL-1 and TNFα contribute to the damaging effects on the immune and cardiovascular systems, resulting in multi-organ dysfunction and lethal shock. Superantigenactivated T-cells induce the prototypic TH1 cytokine IFNγ, which augments immunological responses by increasing MHC class II and intercellular adhesion molecule (ICAM) on APCs, epithelial cells, and endothelial cells. 21,33 IFNγ also upregulates TNFα receptor and IL-1 receptor (IL-1R), thus synergizing with TNFα and IL-1 to promote tissue injury. 53 The T-cell growth factor IL-2 is induced by superantigenactivated T-cells and promotes T-cell proliferation and differentiation. 31,32 The receptors and signaling pathways for these mediators are diverse, accounting for the different immunoregulatory activities of cytokines. The intracellular signaling pathways and molecular components of cytokine  Krakauer receptor signaling have been studied extensively as they serve as targets of therapeutic interventions. [53][54][55][56][57] Cytokines as mediators of inflammation activating NFkB and mTORC1 IL-1 interacts with IL-1 receptor 1 (IL-1R1) and an accessory protein to activate NFkB via signaling adaptors myeloid differentiation factor 88 (MyD88), IL-1R-associated protein kinase (IRAK), and TNF receptor-associated factor 6 (TRAF6). 53,54 This activation pathway is highly conserved, and its signaling components are also triggered by the binding of pathogen-associated molecular patterns (PAMPs) to toll-like receptors (TLRs). 58,59 PAMPs such as lipoprotein, lipopolysaccharide (LPS), flagellin, dsRNA, and viral RNA bind to specific TLR to activate innate host response. A central component of IL-1R/TLR signaling is the activation of IkB kinases (IKKs), resulting in nuclear translocation and activation of NFkB. The MyD88/IRAK/TRAF6 pathway also activates the stress kinase c-Jun-N-terminal kinase (JNK) via the signaling molecule TRAF6. 60 SEB upregulates the expression of toll-like receptor 2 (TLR2) and toll-like receptor 4 (TLR4), thereby synergizing with other microbial products to activate innate immune response. 61,62 TNFα activates NFkB by binding to TNF receptor 1 (TNFR1) or TNF receptor 2 (TNFR2). The cytotoxic functions of TNFα are mostly mediated by its binding to TNFR1 via cytoplasmic death domains. 63,64 The death domain adaptors Fas-associated death domain (FADD) and TNF receptor (TNFR)-associated death domain (TRADD) form a complex with the kinase receptor-interacting protein kinase 1 (RIP1), which then binds TRAF2 to activate the MAPK cascade and NFkB. In addition, the deubiquitylation of RIP1 enables RIP1 to interact with RIP3 to promote necrosis. Activation of death domains by TNFα binding also activates caspase 8 and triggers apoptosis via the extrinsic cell death pathway commonly used by the TNFR superfamily. SEB upregulates the expression of CD95 (Fas), a receptor of the TNFR superfamily, and induces apoptosis via caspase 8 activation. 65 The TNFR superfamily members activate the caspase 8 cascade, JNK, and NFkB, accounting for the pleiotropic effects of TNFα, including cell activation, apoptosis, coagulation, inflammation, and host defense. 63,64 IFNγ (type II IFN) is produced by NK cells, CD8 T-cells, and TH1 subset of CD4 T-cells. IFNγ binds to IFNγR and signals via Janus kinase 1 (JAK1), Janus kinase 2 (JAK2), and signal transducer and activator of transcription 1 (STAT1). 66,67 Both type I (IFNα and IFNβ) and type II IFNs signal via PI3K/mTORC1 after binding to two different types of IFN receptors. Although the main function of type I IFN is antiviral, IFNα and IFNβ have overlapping activities with IFNγ as they induce many common interferon-stimulated genes (ISGs). 67,68 IFNs induce apoptosis, and many ISGs have antiviral, anti-angiogenic, and ubiquitylating activities. The immunomodulatory effects of IFNs are mediated by immunity-related GTPases (IRGs) and guanylate-binding proteins (GBPs). In addition to antimicrobial defense functions, IFNγ also induces immunoproteasomes and the expression of MHC class II molecules to enhance antigen processing. Similar to IL-1 and TNFα, IFNγ activates PKC leading to MAPK activation. Both types of IFNs induce and activate death receptors such as CD95, which then activates FADD, subsequently activating caspase 8. Activated caspase 8 can cleave proapoptotic molecule Bid to a truncated form, allowing for its interaction with two mitochondrial proapoptotic molecules, Bak and Bax. 69 The oligomerization of Bak/Bax results in mitochondrial outer membrane permeabilization and the release of cytochrome c to the cytosol. Cytochrome c binds cytosolic protein apoptotic protease-activating factor 1 (APAF1), leading to the formation of an apoptosome, a multi-protein complex of APAF1 and caspase 9. Activation of the initiator caspases, caspase 8 for the extrinsic apoptosis pathway or caspase 9 for the intrinsic apoptotic pathway, leads to the induction of caspase 3, caspase 6, and caspase 7 and subsequent apoptotic cell death. Damage to mitochondria also releases mitochondrial DNA (mtDNA), which has similar motifs to bacterial DNA and activates intracellular DNA sensors. [70][71][72] TNFα and IFNγ act synergistically on epithelial cells to increase ion transport and disrupt epithelial barrier function. 73,74 IFNγ also synergizes with IL-1 and TNFα to promote leukocyte recruitment, inflammation, and coagulation. 53 IL-2 is a T-cell growth factor and activates T-cell by binding to a high-affinity IL-2 receptor. It signals through JAK1 and Janus kinase 3 (JAK3), activating PI3K/mTORC1 and Ras to promote cell growth, differentiation, and proliferation. 75 Ras activates the MAPK cascade, leading to activation of AP1 and NFAT. IL-2 from SEB-activated T-cells has potent vascular effects and induces vasodilation, vascular leak, and edema. 50,76,77 TNFα synergizes with IL-2 to promote vascular leak as seen in acute lung injury induced by superantigens or pathogens. 50,78 The chemokines, IL-8, MCP-1, macrophage inflammatory protein (MIP)-1α, and MIP-1β, are induced directly by SEB or TSST-1. 21,79 Chemokines orchestrate leukocyte migration and activate leukocytes to promote inflammation and ImmunoTargets and Therapy 2017:6 submit your manuscript | www.dovepress.com

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FDA-approved immunosuppressants targeting staphylococcal superantigens tissue injury. 53,80,81 Chemokine binds to seven-transmembrane GPCR, induces early calcium flux, activates PLC, and signals via the PI3K/mTORC1 pathway. 53 Recruited and activated neutrophils produce ROS and MMPs, contributing to organ damage. 80 Either systemic or intranasal exposure to SEB can cause acute lung injury, characterized by increased expression of adhesion molecules ICAM-1 and vascular cell adhesion molecule (VCAM), increased neutrophils and mononuclear cell infiltrates, endothelial cell injury, and increased vascular permeability. 50,76,77 Oxidative stress and ROS damage mitochondria Superantigens induce massive proliferation in resting T-cells, which requires increased protein synthesis and metabolism. Enhanced glycolysis and fatty acid oxidation not only support protein biosynthesis but also generate oxidative stress and ROS. 82 Increased protein synthesis, ROS, and activated PKC from cell activation are upstream activators of endoplasmic reticulum (ER) stress. 83 SEB induces the expression of ubiquitin ligases, proteasome peptidases, and immunoproteasomes in multiple organs. 84 These ER stress response genes are likely a result of Ca ++ flux, misfolded proteins, and activated PKC. Prolonged ER stress activates the unfolded protein response and apoptosis via the induction of caspases. 85,86 Increased activity of the mitochondrial electron transport chain following superantigen-activated proliferation also promotes oxidative stress and the generation of ROS, ultimately activating mTORC1 (Figure 1).
Increased T-cell proliferation also switches cell metabolism from oxidative phosphorylation to glycolysis and deactivates AMPK, a critical sensor of nutrient and cellular energy, leading to mTORC1 activation. 44,45 AMPK is a conserved cellular energy sensor activated by decreasing cellular ATP and increasing AMP and ADP. A deleterious consequence of mTORC1 activation is the suppression of autophagy, a homeostatic, catabolic process for the lysosomal degradation of damaged organelles, protein aggregates, and intracellular pathogens. 87 Enhanced mitochondrial respiration and ROS damage mitochondria, activate caspase 9, and promote apoptosis. 69,87 Mitophagy, a special form of autophagy, normally removes damaged mitochondria resulting from damage and cell stress signals. However, hyperactivation of mTORC1 in superantigenactivated cells disrupts normal host mitophagy. Damaged mitochondria release cytochrome c and mtDNA to the cytosol, in addition to activating apoptosis via the intrinsic cell death pathway. 71,72 mtDNA binds endosomal toll-like receptor 9 (TLR9), activating the transcriptional factors NFkB and interferon regulatory factor 7 (IRF7). The leakage of mtDNA by damaged mitochondria exacerbates inflammation as mtDNA acts as a potent "damage-associated molecular pattern" (DAMP) to activate cytosolic pattern recognition receptors (PRRs).

DAMPs bind Nod-like receptors (NLRs) activating inflammatory cytokines and pyroptosis
Cytosolic DAMPs such as ROS and mtDNA are upstream activators of inflammasome, an intracellular multi-protein signaling complex that promotes the proteolytic activation of caspase 1. [87][88][89][90][91] DAMPs bind to intracellular NLRs (nucleotide-binding oligomerization domain [Nod] and leucinerich repeat-containing receptors), leading to recruitment of the adaptor apoptosis-associated speck-like protein, which consists of a pyrin domain and a caspase recruitment domain (CARD). The CARD domain recruits pro-caspase-1 into the inflammasome complex, and auto-proteolytic activation of caspase 1 leads to proteolytic processing and activation of proinflammatory cytokines IL-1β and interleukin 18 (IL-18). Inflammasome activation also induces pyroptosis, a specialized form of cell death that eliminates cells harboring intracellular pathogens. 91 ER stress, viral entry, and replication can destabilize lysosomes and activate inflammasome. 92 Other inflammasome activators include potassium efflux and phagocytosis of bacteria or particulates. 90 Thus, bacteria, bacterial-secreted products, viruses, viral DNA, and viral RNA are potent activators of inflammasome as they bind cytosolic NLRs and induce inflammatory cytokines IL-1 and IL-18 and pyroptotic cell death. [89][90][91] Apoptosis plays a critical role in downregulating immune responses but simultaneously has devastating effects when apoptotic cell death is unrestrained. Autophagy acts to counteract apoptosis and maintain cellular homeostasis. 87,93,94 A recent study indicates that blocking autophagy augments T-cell activation. 95 In superantigenactivated cells, autophagy likely contravenes apoptosis as it removes DAMPs and downregulates inflammation.

DAMPs and inflammatory cytokines induce multiorgan injury
IL-1 from inflammasome activation has pleiotropic effects initiating inflammation, NFkB, and pyroptosis. TNFα signaling has an established role that initiates cell death, MAPK cascade, and NFkB activation. The TNFR superfamily members, including TNFR1 and CD95, induce apoptosis by activating caspases, and damaged mitochondria also contributes to apop-ImmunoTargets and Therapy 2017:6 submit your manuscript | www.dovepress.com

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Krakauer totic cell death. IFNγ triggers innate host defense responses, antiviral genes, apoptotic programs, and immunoproteasomes and has many immunomodulatory functions. The cell death pathway triggered in vitro and in vivo by superantigens includes genes associated with apoptosis, such as FADD, death receptor ligand TRAIL (TNFSF10), caspases, CARD, and phospholipid scramblase 1 (PLSCR1). 84,96,97 These genes are observed in superantigen-activated PBMC and major organs from the "double-hit" SEB model. Cellular injury is also apparent from the expression of MMPs, cathepsins, and other cell matrix breakdown products such as versican and fibronectin in superantigen-activated cells. 84,97 DNA damage repair enzymes, poly(ADP-ribose) polymerases, are induced in PBMC and multiple organs of the "double-hit SEB" mouse model, indicating DNA damage and repair. 84

Potential drug targets of intervention
There is currently no effective therapeutic treatment for superantigen-induced shock except for the use of intravenous immunoglobulins. 98,99 Various humanized monoclonal antibodies are developed to neutralize SEs and TSST-1 by targeting specific epitopes on SEs and TSST-1. 100-103 However, targeting and neutralizing a superantigen directly is effective only at early stages of exposure before cell activation and initiation of the proinflammatory cytokine cascade.
There are at least three important host-directed targets based on superantigen interaction with host cells: 1) TCR and/or MHC class II interactions with toxins; 2) co-stimulatory receptor interactions; and 3) signaling pathways and molecules induced by activated T-cells and macrophages. Inhibition of all or one of the abovementioned three targets/ pathways has been reported both in vitro and in vivo, thus representing viable means of blocking the toxic effects of these bacterial superantigens. 104 The targeting of toxin-receptor interaction has been reviewed recently. 104 The disadvantage of this strategy is that to be effective, drugs inhibiting toxin-receptor interaction have to be administered early upon toxin exposure, which is not always possible. Blockade of superantigen-activated signal transduction molecules/pathways represents the most amenable mode of intervention as these molecules/pathways occur postexposure and will likely inhibit other superantigens. NFkB and mTORC1 are prime targets in this regard as the three initial signals provided by TCR, co-stimulatory receptors and cytokines converge on these two hubs of signal transduction (Figure 1). Interruption of these concurrent cascades to tissue injury after exposure of superantigens provides an effective strategy in preventing superantigen-induced lethal shock. Many of the superantigen-induced pathways and cell injury are similar to the pathological pathways activated in organ transplantation.

Mouse models of superantigeninduced shock
An obvious component of in vivo testing of therapeutics against superantigen-induced shock is finding a relevant animal model that mimics human disease. Mice are often used as models for obtaining a basic understanding of immunological mechanisms involved in superantigen-mediated shock as reagents such as antibodies against cell surface molecules and mediators are commercially available. However, mice are naturally less susceptible to SEs and TSST-1, compared to human beings, because of an inherent lower affinity of these exotoxins for murine MHC class II. 105 Potentiating agents such as d-galactosamine, actinomycin D, and LPS are used to amplify the toxic effects of superantigens. 19,49-52,106-108 These superantigen-induced shock models using potentiating agents have major drawbacks for therapeutic studies as the sensitizing agents themselves often induce the same mediators as SEs or TSST-1 by activating similar cells and signaling pathways. Both actinomycin D and d-galactosamine are hepatotoxic, and mouse models using these potentiating agents produce unrealistically high levels of TNFα and liver damage. 109 Drugs designed to inhibit TNFα have a higher therapeutic impact in models using these two potentiating agents. In the SEB plus LPS mouse model, the synergistic action of SEB and LPS promotes early TNFα release and prolongs the release of IFNγ, IL-2, IL-6, and MCP-1. 52 The higher and prolonged levels of these mediators lead to acute mortality with mice succumbing to toxic shock within 48 hours when LPS is used together with SEB. 49,51,52 Importantly, the lethal end point of these murine models is different from human and nonhuman primates exposed to SEB. 18 Two newer, simplified murine models have been developed to study SEB-induced shock without potentiating agents. Transgenic mice expressing human MHC class II respond to lower doses of SEB without synergistic agents due to the higher affinity binding of SEB to human MHC class II molecules. 10,18 Transgenic mice with HLA-DR3 or -DQ8 lethally respond to SEs without potentiation, and the serum levels of mediators correlate with lethal shock. [110][111][112] Pathological lesions in lungs of transgenic mice, temperature fluctuations, delayed lethal end point later at 96 hour are similar to those in nonhuman primates (NHPs) exposed to lethal doses of SEB. 18

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FDA-approved immunosuppressants targeting staphylococcal superantigens syndrome with multiple organ injury. 23 An alternative murine model deploys a "double-hit" strategy with two low doses of SEB using C3H/HeJ mice, an LPS-resistant mouse strain. 76 This "SEB-only" toxic shock model relies on the intranasal administration of SEB and the enhanced action of another dose of SEB later to induce pulmonary inflammation and lethal shock. Importantly, pathological lesions, cytokine response, multiple organ injury, and time to lethality in this "SEB-only" model resemble findings in NHPs and clinical staphylococcal toxic shock syndrome. 84,99 Gene profiling study in this mouse model with SEB reveals many damage response and IFN-induced genes in multiple organs, including 1) innate response; 2) pro-and anti-apoptotic molecules; 3) ER and oxidative stress; 4) intracellular DNA/RNA sensors; 5) immunoproteasome components and E3 ligases; and 6) antiviral ISGs. Upregulation of these damage response genes contributes to irreversible multi-organ damage seen in animal models of toxic shock and human toxic shock syndrome.
Other animal models used to study the in vivo biological effects of bacterial superantigens include NHPs, piglets, and rabbits. 18,20,22,107,[113][114][115][116][117][118][119][120][121][122] The SEs readily induce an emetic response in primates when ingested in low microgram quantities. 113 Inhalation of sublethal nanogram doses of aerosolized SEB causes severe incapacitation in NHPs. 115 Classic primate studies for SEs have been performed by various groups and are considered the "gold standard" as NHP models mimic different aspects of human disease induced by these superantigens. 18,20,[113][114][115] However, the high cost and animal welfare concerns associated with NHPs limit their use for routine therapeutic efficacy testing. Piglets were used to study TSST-1-induced effects and more recently for testing SEB vaccines. 116,117 Toxic shock models with rabbits using subcutaneous or continuous infusion of superantigen also mimic human disease closely, but lack of biological reagents hampers their use for immunological studies. 119 Other toxic shock rabbit models have been developed recently to study infective endocarditis, acute kidney injury, and sepsis using S. aureus producing various superantigens. 121,122 These rabbit models are invaluable in providing in vivo information for the development of sepsis and septic complications of bacterial infections.

Repurposing of US Food and Drug Administration (FDA)-approved immunosuppressants
Traditional drug discovery against pathogens and toxins produced by pathogens is a costly and lengthy process with low level of success to FDA approval for human use. 123 The intense investigations to define molecular mechanisms of superantigen activation of the immune system present multiple "drugable" targets and pathways. Based on these signaling pathways, an alternative low-cost yet faster approach to target superantigens is drug repurposing. This strategy of drug discovery takes advantage of the known mechanisms of FDA-approved drugs and their safety profile. A dominant signaling hub in superantigen-activated cells is mTORC1 as TCR, CD28, IL-2R, IFNγR, and chemokine receptors all signal through the PI3K/mTORC1 pathway (Figure 1).
Another key signaling hub is NFkB as TCR and CD28 via PKC also activate NFkB signaling. In addition, proinflammatory cytokines, IL-1 and TNFα, each independently activates NFkB via MyD88/TRAF6/IRAK and FADD/TRADD/RIP, respectively. Activation of NFkB leads to the induction of inflammatory genes, as well as antiviral, anti-apoptotic, and proapoptotic molecules seen in the "SEB-only" murine model. 84 Thus, the three initial signals provided by TCR, costimulatory receptors and cytokines converge on NFkB and mTORC1 ( Figure 1). There are many similarities between the pathways leading to the adverse events in transplant rejection and superantigen-induced shock as similar cells and receptors are involved in both types of diseases. 39 Out of the many approaches used against superantigen-induced shock, immunosuppressive agents used to prevent graft loss by suppressing T-cell activation have proven to be the most effective when tested in mouse models of superantigeninduced shock. 19,124,125 Major classes of FDA-approved immunosuppressants include: 1) co-stimulation blockers; 2) NFkB inhibitors; 3) calcineurin inhibitors; and 4) mTORC1 inhibitors. The use of FDA-approved immunosuppressants against staphylococcal superantigens and their mechanisms of action are presented in Figure 1 and Table 1.

Co-stimulation blockade
The CD28 co-stimulatory receptor binds CD80 or CD86 on APCs and generates signal 2 for T-cell activation. A transmembrane molecule homologous to CD28, cytotoxic T lymphocyte antigen-4 (CTLA4), is upregulated during T-cell activation and acts as a negative regulator to control T-cell responses. 31 The higher affinity of CTLA4 for CD80 and CD86 enables it to compete with CD28 for the binding to these co-stimulatory molecules and block co-stimulation. A synthetic fusion protein, CTLA4 immunoglobulin (CTLA4-Ig), inhibits CD28 signaling and prevents lethal TSS by inhibiting co-stimulation in a d-galactosamine-sensitized mouse model. 124 Blockade of the CD28 by CTLA4-Ig submit your manuscript | www.dovepress.com

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Krakauer effectively inhibits TSST-1-induced T-cell proliferation and TNFα and IFNγ production in vitro and in vivo. 124 A recent study shows that CTLA4-Ig promotes regulatory T-cell (Treg) development and function in a TGFβ-dependent manner. 126 Thus, blockade of the CD28-CD80/86 co-stimulatory pathway not only blocks co-stimulation and immunological synapse formation but might also enhance immunosuppression by increasing Treg activity. 127 Two versions of CTLA4-Ig, abatacept and belatacept, are FDA-approved biologics for rheumatoid arthritis and prevention of renal transplant rejection, respectively, but have not been tested against superantigen in animal models. 128,129

NFkB inhibitors
Dexamethasone is a potent immunosuppressant and NFkB inhibitor used to treat many types of inflammatory diseases and septic shock. 130,131 Dexamethasone is effective in preventing SEB-induced shock in the "SEB-only" model and the LPS plus SEB model of toxic shock. 108,132 However, inhibition of NFkB is protective in these mouse models only if blockade by dexamethasone is applied early after superantigen exposure and for a long duration. Interestingly, the combined effect of early dexamethasone treatment followed by the anti-oxidant N-acetyl cysteine later is also efficacious in the "SEB-only" murine model of toxic shock. 133 Although the NFkB pathway is an obvious target, other inhibitors of NFkB have only been partially successful in vivo 134 as the NFkB cascade is a major signal transduction pathway for many other cellular receptors, including PRRs and cytokine receptors. NFkB is a central regulator of apoptosis and inflammation and is essential for host defense. Inhibition of NFkB would likely compromise innate immune function.

Calcineurin inhibitors
Cyclosporine A (CsA) and tacrolimus (FK506) are two wellknown FDA-approved calcineurin inhibitors used clinically to prevent kidney graft rejection. 39 Both drugs form molecular complexes with their cellular receptors, cyclophilin and FK506-binding protein 12 (FKBP12), respectively, to inhibit the calcium-dependent phosphatase function of calcineurin. Although CsA inhibits SEB-induced T-cell proliferation in vitro, reduces serum cytokines, and attenuates pulmonary inflammation, it has no effect on lethality in non-human primates. 135 In contrast, CsA effectively prevents SEB-induced shock in a d-galactosamine-sensitized murine model of toxic shock. 19 Tacrolimus suppresses superantigen-induced T-cell activation in vitro but does not reduce lethality in transgenic mice. 136

mTORC1 inhibitors
Rapamycin is a well-known mTORC1 inhibitor as it binds to the immunophilin FKBP12, forming a complex that then blocks mTORC1 activation. Rapamycin (also known as sirolimus) is used clinically to prevent graft rejection in organ (kidney, liver, heart) transplantation. 39 Adverse effects of rapamycin include dose-dependent increase in serum cholesterol and myelosuppression with long-term use. 137 mTORC1 is a central integrator of environmental cues, including immune, nutrient, and energy signals arising from TCR, co-stimulatory receptors, growth factors,

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FDA-approved immunosuppressants targeting staphylococcal superantigens ATP, glucose, and amino acids. [44][45][46] As described earlier, superantigen induces mTORC1 downstream of PI3K/Akt via the three signals of T-cell activation. More recent studies indicate that mTORC1 regulates T-cell differentiation and Treg function. 138,139 Rapamycin inhibits cytokine release and T-cell proliferation by blocking mTORC1 signaling induced by SEB. 125,140 Rapamycin protects mice from SEB-induced shock even when administered 1 day after SEB administration, providing an effective drug postexposure. 140 Inhibition of mTORC1 by rapamycin likely prevents organ damage by inducing autophagy and increasing the numbers of Treg cells and their suppressive functions simultaneously. 138,139 Although studies using rapamycin to block SEB-induced shock in the "SEB-only" mouse model show that rapamycin is efficacious, the immunological mechanisms have not been fully elucidated. A subsequent study of gene profiling in the same model sheds light on the effects of "pure" SEB without potentiating agents in vivo by revealing damage response, DNA sensors, and ISG upregulation upon SEB exposure. 84 Furthermore, the same damage response activators are present in all organs (lung, spleen, liver, kidney, and heart) and mouse PBMC in the presence of SEB without confounding synergistic agents. Rapamycin is a potent autophagy inducer in addition to its ability to block mTORC1. 141 Recent studies show that mTORC1 regulates T-cell differentiation and its activation blocks FoxP3, a key transcription factor for Treg. 139,142 Thus, rapamycin blockade of mTORC1 likely induces a variety of regulatory pathways in SEB-stimulated cells, including autophagic removal of damaged mitochondria, induction of functional Treg, downregulation of apoptosis, inflammatory cytokines, and T-cell proliferation. The success of delayed administration of rapamycin in preventing the toxic effects of SEB indicates that the tissue damage from cytokine storm and resolution of inflammation in organs is critical in preventing shock.

Conclusion
The host response to superantigen initiated by cellular activation of monocyte/macrophages and T-cells leads to the early release of IFNs, inflammatory cytokines, and chemokines. The damage response induced by superantigens starts with effects from inflammatory cytokines and apoptotic programs activated by IFNs and TNFα. DAMPs such as mitochondrial ROS and mtDNA trigger additional apoptosis, activate inflammasomes, and induce transcription factors for ISGs. Inflammation, apoptosis, and cellular damage from superantigen activation lead to tissue injury and organ dysfunction. The induction of PI3K/mTORC1 in superantigen-activated cells blocks autophagy and also promotes damage in multiple organs. FDA-approved immunosuppressants directed at inhibiting mediator release and the downstream celldestructive events provide proof of concept that these drugs can be transitioned to clinical use against superantigens.