STAT1 Gain-of-Function Mutations Cause High Total STAT1 Levels With Normal Dephosphorylation

ORIGINAL RESEARCH published: 10 July 2019 doi: 10.3389/fimmu.2019.01433 Frontiers in Immunology | www.frontiersin.org 1July 2019 | Volume 10 | Article 1433 Edited by: Anne Puel, Institut National de la Santé et de la Recherche Médicale (INSERM), France Reviewed by: Emma Haapaniemi, University of Oslo, Norway Olli Silvennoinen, University of Helsinki, Finland *Correspondence: Steven M. Holland [email protected] Specialty section: This article was submitted to Primary Immunodeficiencies, a section of the journal Frontiers in Immunology Received: 02 February 2019 Accepted: 07 June 2019 Published: 10 July 2019 Citation: Zimmerman O, Olbrich P, Freeman AF, Rosen LB, Uzel G, Zerbe CS, Rosenzweig SD, Kuehn HS, Holmes KL, Stephany D, Ding L, Sampaio EP, Hsu AP and Holland SM (2019) STAT1 Gain-of-Function Mutations Cause High Total STAT1 Levels With Normal Dephosphorylation. Front. Immunol. 10:1433. doi: 10.3389/fimmu.2019.01433 STAT1 Gain-of-Function Mutations Cause High Total STAT1 Levels With Normal Dephosphorylation Ofer Zimmerman1, Peter Olbrich1,2, Alexandra F. Freeman1, Lindsey B. Rosen1, Gulbu Uzel1, Christa S. Zerbe1, Sergio D. Rosenzweig3, Hye Sun Kuehn3, Kevin L. Holmes4, David Stephany4, Li Ding1, Elizabeth P. Sampaio1, Amy P. Hsu1and Steven M. Holland1* 1Laboratory of Clinical Immunology and Microbiology, Immunopathogenesis Section, National Institute of Allergy and Immunology, National Institutes of Health, Bethesda, MD, United States, 2Sección de Infectología, Reumatología e Inmunología Pediátrica (SIRIP), Hospital Infantil Virgen del Rocío, Instituto de Biomedicina de Sevilla (IBiS), Seville, Spain, 3Immunology Service, Department of Laboratory Medicine, National Institutes Clinical Center, National Institutes of Health, Bethesda, MD, United States, 4Flow Cytometry Section, Research Technologies Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States Signal transducer and activator of transcription (STAT1)1 gain of function (GOF) pathogenic variants have been associated with increased levels of phosphorylated STAT1 and STAT1-dependent cellular responses. Delayed dephosphorylation was proposed as the underlying mechanism leading to the characteristically raised pSTAT1 levels. We examined the levels of STAT1 protein and message as well as rates of STAT1 phosphorylation, dephosphorylation, and degradation associated with STAT1 GOF pathogenic variants. Fresh peripheral blood mononuclear cells (PBMC) from 14 STAT1 GOF patients carrying 10 different pathogenic variants in the coiled-coil, DNA binding, and SH2 domains and healthy donors were used to study STAT1 levels and phosphorylation (pSTAT1) following IFNγand IFNαstimulation. STAT1 protein levels were measured by flow cytometry and immunoblot. STAT1 mRNA levels were measured using quantitative reverse transcription PCR. STAT1 protein degradation was studied using cycloheximide. Patient IFNγand IFNαinduced peak pSTAT1 was higher than in healthy controls. The velocity of pSTAT1 dephosphorylation after treatment of IFNγstimulated CD14+monocytes with the Janus Kinase (JAK)-inhibitor ruxolitinib was significantly faster in patient cells. STAT1 protein levels in patient CD14+monocytes and CD3+T cells were higher than in healthy donors. There was a strong and positive correlation between CD14+STAT1 protein levels and peak pSTAT1 levels. Patient fresh PBMC STAT1 mRNA levels were increased at rest and after 16 h of incubation. STAT1 protein degradation was similar in patient and healthy volunteer cells. Patient IFNγreceptors 1 and 2 and JAK2 levels were normal. One patient in our cohort was treated with the oral JAK inhibitor ruxolitinib. Treatment was associated with normalization of both STAT1 protein and peak pSTAT1 levels. After JAK inhibitor treatment was stopped the Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations patient’s CD14+monocyte STAT1 protein and peak phosphorylation levels increased proportionally. These findings suggest that patients with STAT1 GOF mutations have higher levels of total STAT1 protein, leading to high levels of pSTAT1 after stimulation, despite rapid STAT1 dephosphorylation and normal degradation. Keywords: STAT1, gain of function, dephosphorylation, protein, mRNA, monocytes, T cells, JAK inhibitors INTRODUCTION In 2011 van de Veerdonk et al. and Liu et al., described heterozygous germline pathogenic variants in the coiled-coil domain of STAT1 in patients with chronic mucocutaneous candidiasis (CMC) (1,2). Soon after, mutations in the DNA binding domain were described in patients with CMC along with patients who suffered from invasive fungal infections and autoimmune phenomena (3,4). All mutations were characterized as gain of function (GOF), due to increased STAT1-dependent cellular responses. High levels of tyrosine phosphorylated STAT1 (pSTAT1) were found in different immune cells (PBMC, CD3+ T cells, CD14+monocytes and EBV transformed B cell lines) and cell lines (U3A and U3C) transfected with mutant vectors following stimulation with IFNγ, IFNα, IL-6, IL-21, and IL-27 (2–5). The high levels of STAT1 phosphorylation were attributed to delayed dephosphorylation, as demonstrated by elevated pSTAT1 levels up to 120 min from stimulation and by use of the kinase inhibitor staurosporine (2–5). Most of these data were generated by immunoblotting. We revisited these high pSTAT1 levels, along with the kinetics of STAT1 phosphorylation and dephosphorylation, STAT1 message level, STAT1 protein level and degradation, in primary cells from patients carrying STAT1 GOF pathogenic variants. We also evaluated the effect of oral JAK inhibitor treatment with ruxolitinib on STAT1 phosphorylation and protein levels. MATERIALS AND METHODS Patients, Controls, and PBMC Isolation Fourteen patients carrying STAT1 GOF mutations were enrolled (2014–2017) on approved NIH protocols and provided written informed consent. Healthy donor blood samples were obtained under approved protocols through the Department of Transfusion Medicine, Clinical Center, NIH. Patient and healthy donor peripheral blood mononuclear cells (PBMC) were isolated by density-gradient centrifugation using lymphocyte separation media (Lonza). PBMC were resuspended in RPMI culture media (Gibco), supplemented with pyruvate (100 mM, Sigma Aldrich), glutamate (200 mM, Life Technologies), penicillin/streptomycin (100 U/100 µg/ml, Life Technologies), 10% fetal bovine serum (Serum Source International), and 20 mM HEPES (GE). PBMC Stimulation PBMC were stimulated in polystyrene round-bottom tubes (Becton Dickinson Falcon), at 107/ml in 100 mcl total volume. Stimulation was performed with IFNγ1b (ACTIMMUNE) 400 or 800 U/ml, or IFNα(PBL) 100 ng/ml. Intracellular Staining for STAT1, pSTAT1, STAT2, and JAK2 Intracellular pSTAT1, total STAT1, total STAT2, total JAK2, and STAT1 dephosphorylation kinetics were determined by FACS analysis. Freshly isolated PBMC were re-suspended at 106/100 mcl in plain RPMI and serum starved for 30 min. Cells were incubated with anti-human CD14-FITC or anti-human CD14APC (Becton Dickinson 555397 and 555399, respectively) and anti-human CD3 APC-eFluor R 780 (eBioscence 47-0037-42) or anti-human CD3 APC-H7 (Becton Dickinson 560275). Cells were stimulated with IFNγ400 or 800 U/ml for 15–180 min at 37◦C, or with IFNα100 ng/ml for 30 min, fixed with PFA 2% at 37◦C for 10 min, permeabilized with 100% methanol on ice for 30 min, washed with PBS/2%FBS, and incubated for 1 h in the dark at 4◦C with combinations or one of the following antibodies: anti-human pSTAT1-Alexa fluor 647/ PerCP-CyTM5.5 (Y701) (Becton Dickinson 612597 and 560113, respectively), anti-human STAT1 N-terminus-Alexa Fluor R 647/PE (Becton Dickinson 558560 and 558537, respectively), anti-human STAT2 (Cell Signaling 72604) or anti-human JAK2-PE (Cell Signaling 5941 s) mixed in Fix and Perm Permeabilization Medium (Medium B) (Life technologies). Antibodies with the same fluorochrome (e.g., anti-human pSTAT1 AF647, anti-human STAT1 AF647, or anti-human STAT1 PE, anti-human JAK2 PE) were never used in the same tube. Alexa Fluor R 647 Mouse IgG1 κIsotype control (Becton Dickinson 557783) and rabbit (DA1E) mAb IgG XP R Isotype Control (Cell Signaling 3900) were used as a control for anti-human STAT1 AF647 (Becton Dickinson) and anti-human STAT2 (Cell Signaling) primary antibodies, respectively. For STAT2, cells were washed with PBS/2%FBS and incubated with anti-Rabbit IgG Alexa Fluor R  488 Conjugated antibody (Cell Signaling 4412) for 30 min. Before analysis each sample was washed once with PBS/2%FBS and resuspended in PFA 1%. All data were collected with FACSCaliburTM, LSRFortessaTM or LSR II (all Becton Dickinson) and analyzed with FlowJo software (Treestar, Ashland, OR, USA). Kinase Inhibitor Use in STAT1 Dephosphorylation Assays To study STAT1 dephosphorylation we sought a potent kinase inhibitor and optimal concentrations for complete inhibition of STAT1 phosphorylation. We compared the kinase inhibitor staurosporine and the JAK inhibitor ruxolitinib for their effects on healthy donor CD14+STAT1 phosphorylation after IFNγ stimulation. Healthy donor PBMC were incubated with antihuman CD14-FITC (Becton Dickinson 555397) for 15 min. Either staurosporine (both products from Sigma Aldrich and from Selleckchem) or ruxolitinib (Selleckchem) were added Frontiers in Immunology | www.frontiersin.org 2July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations at concentrations of 25, 50, 100, 200, 500, or 1,000 nM for 15 min, following which cells were stimulated with IFNγ (ACTIMMUNE) 800 U/ml for 15 min at 37◦C. After 15 min of stimulation cells were fixed with PFA 2% for 10 min at 37◦C. Cells were stained for pSTAT1 as described above. To determine the kinetics of dephosphorylation in healthy controls, fresh PBMC were incubated with anti-human CD14FITC as above, and then stimulated with IFNγ800 U/ml at 37◦C. Fifteen minutes after IFNγstimulation staurosporine at final concentration of 500 nM, or 1,000 nM or ruxolitinib at 1,000 nM were added to the media. Cells were incubated for 15– 90 min after the administration of staurosporine or ruxolitinib, and then fixed and stained for pSTAT1 as described above. Finally, to understand patient dephosphorylation kinetics, both fresh patient and fresh healthy control PBMC were incubated with anti-human CD14-FITC for 15 min, and then stimulated with IFNγ800 U/ml, at 37◦C. Fifteen minutes after stimulation ruxolitinib at a final concentration of 1,000 nM was added. Cells were incubated at 37◦C for 15–120 min after the administration of ruxolitinib, and then fixed and stained for pSTAT1 as described above. STAT1 Degradation Assay We studied STAT1 degradation using the protein synthesis inhibitor cycloheximide (Sigma Aldrich). 106patient or healthy control fresh PBMC in 200 mcl of culture media (see above) were incubated with cycloheximide at 100 ng/ml for 4 and 16 h. Each patient and healthy volunteer had STAT1 protein levels determined at 0, 4, and 16 h of incubation in culture with and without cycloheximide. Three and a half and 15.5 h after incubation, cells were live/dead stained (LIVE/DEADTM Fixable Aqua Dead Cell Stain Kit, Thermo Fisher) for 10 min, incubated with anti-human CD14 FITC conjugated antibody (BD) for 15 min, washed with 37◦C RPMI media and fixed with PFA 2% for 10 min at 37◦C. Cells were than permeabilized with methanol 3 ml at −20◦C in the dark. All samples were incubated at the same time with anti-human STAT1 Alexa Fluor R 647 (Becton Dickinson 558560), anti-human CD3 APC-H7 (Becton Dickinson 560275), anti-huamn CD11b Alexa Fluor R 700 (Becton Dickinson 557918) and anti-human CD64 PE-CyTM7 (Becton Dickinson 561191) antibodies. After 1 h of incubation cells were washed as described above. All data were collected with LSR II (Becton Dickinson) and analyzed with FlowJo software (Treestar, Ashland, OR, USA). Extracellular Staining for IFNγReceptors 1 and 2 Levels of IFNγreceptors 1 and 2 were determined by FACS analysis. Freshly isolated PBMC were resuspended at 106/100 mcl as described above. Cells were incubated for 30 min in the dark at 4◦C with anti-human CD14-FITC (Becton Dickinson 555397), and anti-human CD119-PE (IFNγR1, Becton Dickinson 558937) or anti-human IFNγR2-APC (R&D FAB773A), washed with PBS/2%FBS and fixed with PFA 1%. Mouse anti-IgG2b, κPE (Becton Dickinson 555058) and Goat anti-IgG-APC (R&D IC108A) were used as isotype controls. Data were collected with LSRFortessaTM (Becton Dickinson) and analyzed with FlowJo software (Treestar, Ashland, OR, USA). Immunoblotting Assays Immunoblotting was used to determine STAT1 protein and pSTAT1 levels in both patient and healthy donor PBMC, at rest and after 30 min of IFNγstimulation. To optimize immunoblotting for quantitation, we determined the linear range for STAT1 and beta actin antibodies that were used (6,7). Both STAT1 and beta actin had low and narrow linear ranges between 2 and 16 mcg total protein (Figure S6). Hence, we loaded only 10–15 mcg total protein per sample. Data were acquired using ChemiDoc MP imaging system (Bio Rad) and analyzed using Image Lab software (BioRad Laboratories; version 5.2.1). Please refer to the online Supplementary Material for complete details. Quantitative Reverse Transcription Polymerase Chain Reaction (RT-qPCR) Analysis Fresh PBMC relative STAT1 mRNA levels were determined by qPCR. Patient and healthy volunteer PBMC were stimulated with IFNγ400 IU/ml for 16 h. For each patient and healthy volunteer, a non-stimulated control was prepared, which was run in parallel for 16 h. Patient and healthy volunteer baseline controls were obtained from fresh PBMC, immediately after their separation from whole blood. Cells were spun down at 4◦degrees, and then washed with cold PBS. Total RNA was extracted using RNeasy mini kit (QIAGEN) with a DNase reaction (QIAGEN). cDNA was generated using HighCapacity cDNA Reverse Transcription (Applied Biosystems) and oligo dT priming. Relative STAT1 mRNA levels were determined with Taqman probes (Life, Hs01013996), using the ddCt algorithm. The results were normalized with respect to the values obtained for the endogenous Beta Actin (Life, Hs99999903) cDNA. All procedures were performed with technical triplicates and with biological duplicates or triplicates when available. STAT1 Sequencing Genomic DNA was extracted from whole blood, amplified and sequenced for STAT1 exons and flanking splice sites as previously described (3). Statistics Data from all experiments acquired on the same flow cytometer machine, using the same settings and the same fluorochromes were analyzed in raw values of geometric mean of fluorescence. Data were also analyzed as average of the same day healthy donors pSTAT1 and STAT1 protein levels as measured by geometric mean of fluorescence. Each healthy donor and patient pSTAT1 or STAT1 level was expressed as percentage of the same day healthy donors’ average level. Statistical analyses were performed using GraphPad Prism7 (La Jolla, CA, USA). Results are expressed as mean ± standard deviation (SD) unless otherwise indicated. For group comparisons, the parametric independent Student’s t-test was used to analyze differences in continuous variables. The ShapiroWilk normality test was used to verify Gaussian distribution. Comparison between groups that did not pass the normality test Frontiers in Immunology | www.frontiersin.org 3July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations TABLE 1 | Genetics and main phenotypical features of 14 patients with STAT1 GOF mutations. Mutation (cDNA)/(amino acid) Affected domain Sex Age (y) Clinical onset CMC Infections Autoimmunity/ inflammatory Endocrinopathy Immunosuppressive therapy at the time of the study P1 c.(493G>C) D165H (2) CCD M 30 1st year of life Oral cavity, esophagus, skin and genital mucosa Recurrent sinopulmonary infections; HSV esophagitis; recurrent herpes zoster Upper GI ulcers Type 1 DM None P2 c.(704A>G) E235G (9) CCD F 62 1st year of life Oral cavity, skin and genital mucosa Recurrent sinopulmonary infections; bacterial skin infections with abscesses; recurrent HSV labialis Alopecia None P3 c.(704A>G) E235G (9) CCD F 34 1st week of life Oral cavity Recurrent sinopulmonary infections None P4 c.(800 C>T) A267V (1,3) CCD M 19 6 months old Oral cavity, esophagus and skin Recurrent RSV; Mycobacterium fortuitum lymphadenitis None P5 c.(820C>T) R274W (1,10) CCD F 30 1st year of life Oral cavity, esophagus and genital mucosa Recurrent pneumonia; recurrent bacteremia; bacterial skin infections Myopathy; SLE Type I DM Ruxolitinib P6 c.(821G>A) R274Q (1,2,10) CCD F 30 3 years old Oral cavity, esophagus, skin and genital mucosa Recurrent sinopulmonary infections; bacterial skin infections with abscesses; recurrent herpes zoster None P7 c.(821G>A) R274Q (1,2,10) CCD M 4 3 years old Oral cavity and genital mucosa None P8 c.(963A>T) R321S (11,12) DBD F 18 6 years old Skin Recurrent sinopulmonary infections; bacterial skin infections; dermatophytosis; recurrent herpes zoster Alopecia Hypothyroidism; GH deficiency None P9 c.(963A>T) R321S (11,12) DBD F 21 6 years old Oral cavity and skin Recurrent sinopulmonary infections; bacterial skin infections with abscesses; dermatophytosis; warts Autoimmune hepatitis; alopecia Type I DM None P10 c.(963A>T) R321S (11,12) DBD M 25 1st year of life Oral cavity, esophagus and skin Recurrent sinopulmonary infections; disseminated MAC; severe acute varicella zoster infection; Parvo B19 viremia; BK viruria; HCV Cytopenia; HLH GH deficiency None P11 c.(983A>G) H328R DBD M 10 1st year of life Recurrent sinopulmonary infections Colitis Hypothyroidism; Type I DM; GH deficiency HSCT with low chimerism 5 years prior to the study P12 c.(1057G>A) E353K (3) DBD M 27 14 years old Disseminated coccidioidomycosis; dermatophytosis Ruxolitinib (Continued) Frontiers in Immunology | www.frontiersin.org 4July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations TABLE 1 | Continued Mutation (cDNA)/(amino acid) Affected domain Sex Age (y) Clinical onset CMC Infections Autoimmunity/ inflammatory Endocrinopathy Immunosuppressive therapy at the time of the study P13 c.(1154C>T) T385M (3,4,10) DBD M 27 1st week of life Oral cavity and skin Histoplasma pneumonia; recurrent herpes zoster; Mycobacterium fortuitum lymphadenitis None P14 c.1885C>T H629Y (13) SH2D F 25 1st year of life Oral cavity and genital mucosa Recurrent pneumonia requiring lobectomy; rectal abscesses; C. dif; recurrent herpes zoster Rectovaginal fistula Hypothyroidism None CCD, coiled-coil domain; CMC, chronic mucocutaneous candidiasis; C. diff., Clostridium difficile; DBD, DNA-binding domain; DM, Diabetes mellitus; GH, growth hormone; HSCT, Hematopoietic stem cell transplantation; HCV, Hepatitis C virus; HSV, Herpes simplex virus; MAC, Mycobacterium avium complex; RSVrespiratory syncytial virus. References for the nine mutations that were published in the past are in parentheses. was performed using the Mann-Whitney non-parametric test, for continuous variables. Simple linear regression was performed to analyze changes in pSTAT1 levels over time. To test whether dephosphorylation kinetics differed between controls and patients we used a method equivalent to analysis of covariance (ANCOVA) (8). The Pearson product-moment correlation coefficient was used for analysis of correlations between variables. The p-value for significance was set at <0.05. RESULTS We examined pSTAT1 (Tyr701) levels in CD14+monocytes of 13 patients with 10 different coiled-coil, DNA binding, and SH2 domains STAT1 pathogenic variants by flow cytometry and compared them to healthy controls. Patients’ clinical data were collected from medical records and are briefly summarized in Table 1. pSTAT1 levels were measured at rest and with IFNγ stimulation. We focused first on IFNγsince it potently induces STAT1 phosphorylation and homo-dimerization (14,15). We focused on CD14+monocytes because of their relatively high levels of IFNγreceptors 1 and 2, which allow for rapid activation of STAT1 (16). In 25 separate experiments, patient cells were compared with one or two healthy controls per experiment, such that each patient was compared to 2–5 separate healthy controls. We looked at the kinetics of pSTAT1 formation in CD14+monocytes stimulated with IFNγin healthy controls and GOF patients (up to 180 min) (Figure 1A and Figure S1A). In both healthy control and patient cells, pSTAT1 levels peaked around 15 to 30 min and gradually decreased toward baseline. However, they typically did not reach pre-stimulation baseline levels, even after 3 h, in either healthy control or patient cells. Patient CD14+monocyte pSTAT1 levels at rest were not significantly different from healthy control cells after 30 min of serum starvation (Figure 1B and Figures S1B, S2A,B, S3A1). With IFNγstimulation patient cell peak pSTAT1 levels were significantly higher than those of healthy volunteers (Figure 1B and Figures S1B, S2A,B, S3A1). The mean pSTAT1 levels of 13 patients tested compared to 40 healthy donors was 2.7 times higher (±0.24) after 15 min and 2.8 times higher (±0.25) after 30 min of IFNγstimulation, respectively (P<0.0001 for all) (Figure S1B). The pattern of post-peak decline in pSTAT1 was linear in both patient and healthy volunteer cells (Figures 1A,C and Figures S1A,E). However, the slope of pSTAT1 decrease was 3.1 times steeper on average in GOF patient cells than healthy controls (Figure 1C and Figure S1E). We analyzed the same raw flow cytometry data looking at the average absolute decrease in pSTAT1 level per minute, after it reached its peak level 15– 30 min after IFNγstimulation. The average delta pSTAT1 per minute was higher in the patient group at every tested time point, however these differences were significant during the first 15 min after pSTAT1 reached its peak level, in one set of experiments (Figure S1C) and during the first 30–60 min after pSTAT1 reached its peak in a second set of experiments (Figure S1D). Frontiers in Immunology | www.frontiersin.org 5July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations FIGURE 1 | Increased peak pSTAT1 levels with normal STAT1 dephosphorylation rate in GOF CD14+monocytes. (A) Average CD14+monocytes pSTAT1 level at rest (time 0) and up to 3 h of IFNγstimulation in GOF patients (red line, n=6) and healthy donors (blue line, n=12), as measured by flow cytometry with an anti pSTAT1 AF647 antibody. Levels are expressed in geometric mean of fluorescence. (B) Patients’ (red squares, n=6) and healthy donors’ (blue dots, n=12) pSTAT1 at rest and after 15′and 30′of IFNγstimulation, as measured by flow cytometry. Each red square represents the average of repeated measurement (1–3) of each patient. Each blue dot represents one measurement of one healthy control. Comparisons between the two groups were performed for each time point independently. (C) Linear regression lines of pSTAT1 level over time (minutes), from peak level, starting 15 min after IFNγstimulation, of patients’ (red lines, n=6) and healthy controls’ (blue lines, n=12) CD14+monocytes, as measured by flow cytometry. (D) Average CD14+monocytes pSTAT1 level over time as expressed in percentage from peak level of each tested healthy donor (blue line, n=36) or GOF patient (red line, n=12). Peak phosphorylation point was defined as time zero for each patient or healthy control, independently. **P<0.01; ****P<0.0001, by t-test (B) or ANCOVA (C). Quantitative data represent mean ±SEM. We looked at the rate of decrease in pSTAT1 level as a percentage of its peak level in cells from healthy donors and patients (Figure 1D). For each healthy donor and patient, pSTAT1 levels were expressed as % of maximum. The peak pSTAT1 level as measured by flow cytometry and expressed in geometric mean fluorescence level was defined as 100%, and the peak pSTAT1 time point was defined as time 0. As can be seen in Figure 1D, when expressed as % of maximum level, the average decrease in pSTAT1 level over time in both healthy volunteer and GOF patient cells was almost identical. As seen in Figure S1F the decreases in pSTAT1 levels were linear and superimposable when the values were expressed in percentages. The equations of the regression lines were almost identical for both healthy controls and GOF patients. Therefore, the rate of decrease in pSTAT1 from its peak level is similar in GOF patients and healthy controls. To explain these observations, we sought to examine STAT1 dephosphorylation following complete blockade of STAT1 phosphorylation after peak pSTAT1. We examined the relative efficacies of staurosporine and ruxolitinib in blocking STAT1 phosphorylation in healthy donor CD14+ monocytes. Ruxolitinib blocked STAT1 phosphorylation better than staurosporine at every concentration tested (Figure 2A). Moreover, staurosporine, a non-specific kinase inhibitor, had paradoxical activity at lower concentrations in some healthy controls (Figure 2A). Ruxolitinib 500 or 1,000 nM completely inhibited STAT1 phosphorylation following IFNγ stimulation, blocking IFNγsignaling. Neither 500 nor 1,000 nM of staurosporine completely blocked IFNγsignaling (Figure 2A), regardless of the commercial source of staurosporine. We compared the velocity of pSTAT1 dephosphorylation in cells treated with 500 nM of staurosporine, 1,000 nM of staurosporine or 1,000 nM of ruxolitinib 15 min after stimulation with IFNγ. The average pSTAT1 level was lower at every tested time point in the cells treated with ruxolitinib compared to cells treated with staurosporine (Figure 2B). In light of these findings we chose to use ruxolitinib 1,0000 nM to study pSTAT1 dephosphorylation. We stimulated fresh PBMC from three patients with three different GOF pathogenic variants and nine healthy controls with IFNγ. At 15 min after stimulation we added ruxolitinib 1,000 nM and monitored pSTAT1 over time by flow cytometry. Average patient CD14+monocyte pSTAT1 level 15 min after IFNγ stimulation was 4.5 ±0.79 times the average control level (p<0.05) (Figure 2C). Healthy volunteer average pSTAT1 levels returned to baseline by 60 min after ruxolitinib, while Frontiers in Immunology | www.frontiersin.org 6July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations FIGURE 2 | Ruxolitinib is more potent than staurosporine in inhibiting STAT1 phosphorylation. (A) Healthy donors CD14+monocytes pSTAT1 level after 15′of IFNγ stimulation with pre-incubation with a kinase inhibitor ruxolitinib (blue dots, n=16) or staurosporine (red dot, n=14) at increasing concentration (25–1,000 nM). Each individual’s pSTAT1 level is expressed in percentage of the same healthy donor pSTAT1 level after 15′of IFNγstimulation, without pre-incubation with a kinase inhibitor. (B) CD14+monocytes pSTAT1 level 15–90′after introduction of staurosporine (500 or 1,000nM) or ruxolitinib (1,000nM) to healthy donors fresh PBMC stimulated with IFNγfor 15 min. Levels are expressed in geometric mean of fluorescence. (C) Average CD14+monocytes pSTAT1 level of healthy controls (blue, n= 9) and patients (red, n=3 with 1–3 repeated measurements per patient) over 2.5 h after introduction of ruxolitinib 1,000 nM to fresh PBMC, stimulated first with IFNγ for 15 min. Levels are expressed in geometric mean of fluorescence. (D) Average decrease per minute in CD14+monocytes pSTAT1 level in healthy controls (blue, n =9) and patients (red, n=3) over 2 h after introduction of ruxolitinib 1,000 nM to fresh PBMC, stimulated first with IFNγfor 15 min. *P<0.05; **P<0.01; ***P< 0.001; ****P<0.0001, by t-test. Quantitative data represent mean ±SEM. patient average pSTAT1 levels came back to baseline after ruxolitinib only by 150 min (Figure 2C). As seen in Figure 2D the absolute decrease in STAT1 phosphorylation per minute was significantly higher in the patient group at every time point during the first hour after ruxolitinib administration. Therefore, more pSTAT1 was being dephosphorylated per minute in GOF patients. These data indicated that the absolute decrease in the level of pSTAT1 molecules was significantly greater in the GOF patient group, while the rate of GOF pSTAT1 dephosphorylation was equivalent to normal. However, it was also clear that pSTAT1 levels in STAT1 GOF patients were elevated. Therefore, we sought explanations for the persistence of high levels of pSTAT1 in STAT1 GOF patient cells. We hypothesized that increased levels of total STAT1 might explain the increased levels of pSTAT1. We measured total STAT1 protein levels in CD14+and CD3+cells by flow cytometry in 14 patients with 10 different mutations (Table 1), in 22 experiments alongside 44 healthy controls. Each patient was compared with 1–6 healthy controls. All 14 patients had increased total STAT1 protein levels in CD14+monocytes at rest and with IFNγstimulation (Figure 3A and Figures S3A2, S4A). Patient CD14+monocyte mean STAT1 protein levels at rest were 2.9 ±0.34 times healthy controls (P< 0.0001) (Figure S4A). After 15 and 30 min of IFNγstimulation patient mean CD14+monocyte STAT1 protein levels were 2.9 ± 0.46 and 3.1 ±0.38 times healthy donor average STAT1 protein levels, respectively (p=0.004 and p=0.0005, respectively). CD3+cell STAT1 protein levels were also increased in the 12 tested patients. The mean patient CD3+STAT1 level was 4.5 ±0.44 times the average healthy donor levels (P<0.0001) (Figure 3B and Figure S3A2). We next looked to see whether there was a correlation between total CD14+monocytes STAT1 protein levels and stimulated peak pSTAT1 levels. The Pearson r coefficient of CD14+monocytes total STAT1 protein vs. peak pSTAT1 level as measured by flow cytometry was 0.92 (95% CI 0.79–0.97, R2 0.84; p<0.0001) (Figure 3C). Therefore, the higher level of total STAT1 protein was directly correlated with higher peak pSTAT1 levels. When we corrected patient and healthy control CD14+ monocytes pSTAT1 levels for their total STAT1 levels we found that the average ratio of pSTAT1 to total STAT1 protein in patient Frontiers in Immunology | www.frontiersin.org 7July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations FIGURE 3 | STAT1 protein levels are increased in GOF CD14+monocytes and CD3+lymphocytes. (A) GOF patients’ (red squares, n=13) and healthy controls’ (blue dots, n=38) CD14+monocytes STAT1 protein level, at rest, 15′and 30′after IFNγstimulation, as measured by flow cytometry with anti-STAT1 AF647 antibody. Each red dot represents the average of repeated measurement of one patient (1–3). Each blue dot represents one measurement of a healthy control. Comparisons between the two groups were performed for each time point independently. Levels are expressed in geometric mean of fluorescence. (B) CD3+cells STAT1 protein level in 12 tested GOF (red) patients compared with healthy controls (blue, n=27), as measured by flow cytometry. Each red dot represents the average of repeated measurement of one patient (1–4). Each blue dot represents one measurement of a healthy control. (C) Pearson correlation of STAT1 protein level (x axis) vs. peak pSTAT1 level (y axis) in CD14+monocytes of both patients (red squares, n=8) and healthy controls (blue circles, n=12) as measured by flow cytometry. Levels are presented in geometric mean of fluorescence. (D) CD14+monocytes pSTAT1 level corrected by STAT1 protein level in healthy controls (blue dots, n=5–20 per time point) and GOF patients (red squares, n=4–11 per time point) 15–180′after IFNγstimulation. Data is presented in percentages of healthy controls average level. *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001, by t test (A,B,D), and Pearson correlation (C). Quantitative data represent mean ±SEM. cells after IFNγstimulation was the same or slightly lower than that of healthy controls (Figure 3D). To confirm these findings, we used immunoblotting to measure total STAT1 and pSTAT1 levels in lysates of PBMC stimulated with IFNγ. The relative levels of total STAT1 and pSTAT1 protein compared to beta actin levels were significantly higher in patients than healthy volunteers (Figures 4A–C). By optical densitometry (OD), patient median relative total STAT1 protein levels at rest, and 30 min after IFNγstimulation were 4.2 and 3.5 times those of healthy volunteers, respectively (Figure 4B,p=0.002 for all), while patient relative pSTAT1 levels 30 min after IFNγstimulation were 4.9 times healthy volunteer levels (Figure 4C, 487%±101 vs. 100%±10, p=0.019). After correcting pSTAT1 levels for total STAT1 levels, there was no significant difference between patient and control pSTAT1 levels (Figure 4D). Three of the five tested patients had increased levels of pSTAT1 at baseline (Supplementary Material), but these levels were below the level of reliable quantification (0.5–3% of the OD of IFNγstimulated samples). We did not find this by flow cytometry based pSTAT1 assay, likely because of the serum starvation used for flow cytometry. Oral ruxolitinib has been reported to normalize STAT1 phosphorylation in patients with STAT1 GOF mutations (17). Therefore, we hypothesized that the normalization of STAT1 phosphorylation might be associated with normalization of total STAT1 protein levels. Patient five was started on ruxolitinib treatment for CMC and arthritis. Prior to treatment, both her CD14+monocyte STAT1 protein and CD14+monocyte peak pSTAT1 levels were 2.3 and 2.6 times those of healthy volunteers, respectively (Figures 5A,B). After 14 days of oral ruxolitinib treatment, both her total STAT1 protein and phosphorylated STAT1 were similar to healthy volunteer levels (Figures 5C,D). After several weeks on ruxolitinib she was hospitalized with a viral respiratory infection and ruxolitinib was stopped. Fortyeight hours after ruxolitinib cessation her CD14+monocyte STAT1 protein levels were twice the average of two healthy volunteer CD14+STAT1 levels (data not shown). At the same time, patient CD14+monocyte peak pSTAT1 levels after IFNγ stimulation was 1.8 times the average peak level of the same two healthy volunteer peak pSTAT1 levels (data not shown). Five days after ruxolitinib cessation patient CD14+monocyte STAT1 protein levels were 3.55 times healthy volunteer levels and her Frontiers in Immunology | www.frontiersin.org 8July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations FIGURE 4 | Increased level of PBMC STAT1 protein and pSTAT1 in GOF patients—by immunoblotting. (A) Pt. 5 pSTAT1 and STAT1 protein levels at rest and after 30′ of IFNγstimulation, compared with a healthy control, as measured by immunoblotting (blots of STAT1 and Beta Actin are from the same gel. pSTAT1 blots are from a duplicate gel of the same samples). (B) STAT1 protein/Beta actin ratio at rest and after 30′of IFNγstimulation in five patients (red squares) compared with eight healthy controls (blue dots), as measured by immunoblotting. Data is presented in percentages of the same day healthy controls’ average ratio of STAT1/Beta actin, as measured by optical densitometry (OD). (C) pSTAT1/Beta actin ratio after 30′of IFNγstimulation in five patients (red squares) compared to eight healthy controls (blue dots), as measured by immunoblotting. Data is presented in percentages of the same day healthy controls’ average ratio of pSTAT1/Beta actin, as measured by optical densitometry (OD). (D) pSTAT1/STAT1 protein ratio, 30 min after IFNγstimulation level in healthy controls (blue dots, n=8) and GOF patients (red squares, n= 5) as measured by immunoblotting. Data is presented in percentages of the same day healthy controls’ pSTAT1/STAT1average ratio as measured by optical densitometry (OD). *P<0.05; **P<0.01, by Mann-Whitney (B) or t test (C,D). Quantitative data represent median with interquartile range (B) or mean ±SEM (C,D). pSTAT1 peak level was 3.4 times the healthy volunteer peak level (Figures 5E,F). Patient CD3+cells showed a similar pattern. When ruxolitinib naïve her CD3+cell STAT1 protein levels were increased, while on ruxolitinib her CD3+cell STAT1 protein levels came down to normal. After the treatment was stopped her CD3+STAT1 levels rose again (Figure S4B). Increased pSTAT1 formation is not unique to IFNγ stimulation. Increased levels of pSTAT1 occur following stimulation with IFNγ, IFNα, IL-6, IL-21, and IL-27 (2–5). Previous data showed that pSTAT1 level peaks 30 min after IFNαstimulation and declines gradually thereafter (18). We verified this in two patients and two healthy donors (Figure 6A). Furthermore, we stimulated fresh PBMC of six patients and 12 healthy donors with IFNαand measured both CD14+ monocyte STAT1 protein and pSTAT1 at baseline and after 30 min using flow cytometry (Figures 6C,D). In parallel, we used the same patient and healthy donor samples to measure CD14+monocyte STAT1 and pSTAT1 levels following 30 min of IFNγstimulation (Figures 6B–D). Patient pSTAT1 levels were significantly higher compared to healthy donors following both IFNαand IFNγstimulation (Figure 6C). However, in both patients and healthy donors, pSTAT1 levels following IFNγstimulation were significantly higher than following IFNα stimulation (Figure 6C). Thirty minutes after IFNαstimulation, the average patient pSTAT1 level was 2.1 times the healthy donor average level. In contrast, the average patient pSTAT1 level following IFNγstimulation was 3.1 times the healthy donor average pSTAT1 level (Figure 6C). Mean STAT1 protein levels 30 min after IFNγstimulation were higher compared to mean STAT1 levels after IFNαstimulation in both patients and healthy donors, however these differences were not significant (p=0.41 and p=0.52, respectively) (Figure 6D). Thirty minutes after IFNαor IFNγstimulation, the average patient STAT1 levels were 2.8 and 3.2 times the healthy donor average STAT1 level, respectively (Figure 6D). IFNγstimulation induces STAT1 phosphorylation and homodimerization (14,15), whereas IFNαstimulation induces a more complex cascade of STAT1 and STAT2 phosphorylation, heterodimerization, and formation of the IFN-stimulated gene factor (ISGF)3 complex with a third protein, interferon regulatory factor (IRF)9 (15,19,20). We measured STAT2 levels in CD14+monocytes of the same six patients and 12 healthy donors at baseline, prior to IFNαstimulation. STAT2 protein levels were significantly higher in patients compared to healthy controls (Figure 6D and Figures S5A,B). Interestingly, the ratio between the patient and healthy donors average STAT2 levels was Frontiers in Immunology | www.frontiersin.org 9July 2019 | Volume 10 | Article 1433 Zimmerman et al. Normal Dephosphorylation in STAT1 Mutations 18. Kaleviste E, Saare M, Leahy TR, Bondet V, Duffy D, Mogensen TH, et al. Interferon signature in patients with STAT1 gain-of-function mutation is epigenetically determined. Eur J Immunol. (2019) 49:790–800. doi: 10.1002/eji.201847955 19. Improta T, Schindler C, Horvath CM, Kerr IM, Stark GR, Darnell JE. Transcription factor ISGF-3 formation requires phosphorylated Stat91 protein, but Stat113 protein is phosphorylated independently of Stat91 protein. Proc Natl Acad Sci USA. (1994) 91:4776–80. doi: 10.1073/pnas.91.11.4776 20. Li X, Leung S, Kerr IM, Stark GR. Functional subdomains of STAT2 required for preassociation with the alpha interferon receptor and for signaling. Mol Cell Biol. (1997) 17:2048–56. doi: 10.1128/MCB.17.4.2048 21. Lehtonen A, Matikainen S, Julkunen I. Interferons up-regulate STAT1, STAT2, and IRF family transcription factor gene expression in human peripheral blood mononuclear cells and macrophages. J Immunol. (1997) 159:794–803. 22. Zimmerman O, et al. Ruxolitinib effects on STAT1 gain of function mutations. In: Clinical Immunology Society Annual Meeting. Houston, TX (2015). 23. Weinacht KG, Charbonnier LM, Alroqi F, Plant A, Qiao Q, Wu H, et al. Ruxolitinib reverses dysregulated T helper cell responses and controls autoimmunity caused by a novel signal transducer and activator of transcription 1 (STAT1) gain-of-function mutation. J Allergy Clin Immunol. (2017) 139:1629–40.e2. doi: 10.1016/j.jaci.2016.11.022 24. 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Elevated levels of STAT1 in Fanconi anemia group A lymphoblasts correlate with the cells’ sensitivity to DNA interstrand crosslinking drugs. Haematologica. (2013) 98:705–13. doi: 10.3324/haematol.2012. 074187 28. Koutna I et al. Flow Cytometry Analysis of Intracellular Protein, Flow Cytometry - Recent Perspectives, M.Sc. Ingrid Schmid ed. InTech. Available online at: https://www.intechopen.com/books/flow-cytometryrecent-perspectives/flow-cytometry-analysis-and-determination-ofintracellular-protein (accessed June 15, 2019). 29. Krutzik PO, Nolan GP. Intracellular phospho-protein staining techniques for flow cytometry: monitoring single cell signaling events. Cytometry A. (2003) 55:61–7 doi: 10.1002/cyto. a.10072 Conflict of Interest Statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Copyright © 2019 Zimmerman, Olbrich, Freeman, Rosen, Uzel, Zerbe, Rosenzweig, Kuehn, Holmes, Stephany, Ding, Sampaio, Hsu and Holland. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Immunology | www.frontiersin.org 16 July 2019 | Volume 10 | Article 1433