Restriction of chronic Escherichia coli urinary tract infection depends upon T cell‐derived interleukin‐17, a deficiency of which predisposes to flagella‐driven bacterial persistence

The FASEB JournalVolume 34, Issue 11 p. 14572-14587 RESEARCH ARTICLEFree Access Restriction of chronic Escherichia coli urinary tract infection depends upon T cell-derived interleukin-17, a deficiency of which predisposes to flagella-driven bacterial persistence Michelle N. Chamoun, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorMatthew J. Sullivan, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorKelvin G. K. Goh, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorDhruba Acharya, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorDeepak S. Ipe, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorLahiru Katupitiya, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorDean Gosling, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorKate M. Peters, School of Chemistry and Molecular Biosciences, Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, QLD, AustraliaSearch for more papers by this authorMatthew J. Sweet, Institute for Molecular Bioscience (IMB), IMB Centre for Inflammation and Disease Research, Australian Infectious Diseases Research Centre, The University of Queensland, Brisbane, QLD, AustraliaSearch for more papers by this authorDavid P. Sester, TRI Flow Cytometry Suite (TRI.fcs), Translational Research Institute, Wooloongabba, QLD, AustraliaSearch for more papers by this authorMark A. Schembri, School of Chemistry and Molecular Biosciences, Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, QLD, AustraliaSearch for more papers by this authorGlen C. Ulett, Corresponding Author g.ulett@griffith.edu.au School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, Australia Correspondence Glen C. Ulett, School of Medical Science, and Menzies Health Institute Queensland, Griffith Health Centre, Griffith University, Gold Coast, QLD 4222, Australia. Email: g.ulett@griffith.edu.auSearch for more papers by this author Michelle N. Chamoun, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorMatthew J. Sullivan, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorKelvin G. K. Goh, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorDhruba Acharya, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorDeepak S. Ipe, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorLahiru Katupitiya, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorDean Gosling, School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, AustraliaSearch for more papers by this authorKate M. Peters, School of Chemistry and Molecular Biosciences, Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, QLD, AustraliaSearch for more papers by this authorMatthew J. Sweet, Institute for Molecular Bioscience (IMB), IMB Centre for Inflammation and Disease Research, Australian Infectious Diseases Research Centre, The University of Queensland, Brisbane, QLD, AustraliaSearch for more papers by this authorDavid P. Sester, TRI Flow Cytometry Suite (TRI.fcs), Translational Research Institute, Wooloongabba, QLD, AustraliaSearch for more papers by this authorMark A. Schembri, School of Chemistry and Molecular Biosciences, Australian Infectious Diseases Research Centre, University of Queensland, Brisbane, QLD, AustraliaSearch for more papers by this authorGlen C. Ulett, Corresponding Author g.ulett@griffith.edu.au School of Medical Sciences, And Menzies Health Institute Queensland, Griffith University, Parklands, QLD, Australia Correspondence Glen C. Ulett, School of Medical Science, and Menzies Health Institute Queensland, Griffith Health Centre, Griffith University, Gold Coast, QLD 4222, Australia. Email: g.ulett@griffith.edu.auSearch for more papers by this author First published: 09 September 2020 https://doi.org/10.1096/fj.202000760RCitations: 2 [Correction added on September 13, 2020, after first online publication: Affiliation 1 and present address has been amended with minor changes.] AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinked InRedditWechat Abstract Urinary tract infections (UTI) frequently progress to chronicity in infected individuals but the mechanisms of pathogenesis underlying chronic UTI are not well understood. We examined the role of interleukin (IL)-17A in UTI because this cytokine promotes innate defense against uropathogenic Escherichia coli (UPEC). Analysis of UPEC persistence and pyelonephritis in mice deficient in IL-17A revealed that UPEC CFT073 caused infection at a rate higher than the multidrug resistant strain EC958. Il17a−/− mice exhibited pyelonephritis with kidney bacterial burdens higher than those of wild-type (WT) mice. Synthesis of IL-17A in the bladder reflected a combination of γδ-T and TH17 cell responses. Analysis of circulating inflammatory mediators at 24h postinoculation identified predictors of progression to chronicity, including IL-6 and monocyte chemoattractant protein-1 (MCP-1). Histological analysis identified infiltrating populations of neutrophils, NK cells, and γδ T cells in the bladder, whereas neutrophils predominated in the kidney. Analysis of the contribution of flagella to chronicity using hyper-flagellated and fliC-deficient UPEC in WT and Il17a−/− mice revealed that, in a host that is deficient for the production of IL-17A, flagella contribute to bacterial persistence. These findings show a role for IL-17A in defense against chronic UTI and a contribution of flagella to the pathogenesis of infection. Abbreviations CFU colony forming unit CXCL1 chemokine (C-X-C motif) ligand 1 G-CSF granulocyte colony stimulating factor HlyA hemolysin A IL-17A interleukin (IL)-17A KC keratinocyte cytokine MCP-1 monocyte chemoattractant protein-1 MIP-1β macrophage inflammatory protein 1 beta PBS phosphate-buffered saline pflhDC plasmid pMG600 containing regulatory genes flhDC to confer flagella over-expression pi postinoculation PMA phorbol 12-myristate 13-acetate TH17 cell T Helper 17 cell TNF tumor necrosis factor alpha UPEC uropathogenic Escherichia coli UTI urinary tract infection WT wild-type γδ-T cell gamma-delta T cell 1 INTRODUCTION Urinary tract infections (UTI) are among the most prevalent infections of humans worldwide. More than half of all women will develop a UTI at least once in their lifetime, and half of these individuals will experience a recurrent UTI within 6 months of antibiotic treatment.1 Acute infection that progresses to long-lasting persistent infection is termed chronic cystitis, characterized by persistent high-titer bacteriuria, immunopathology, and high bladder bacterial burdens.2 UTI have considerable adverse impacts on the quality of life of infected individuals 3 and result in substantial financial cost to the healthcare industry (estimated at $3.5 billion in the United States annually, as recently reviewed elsewhere 1). It is thought that, of all cases of recurrent UTI, half are due to the same bacterial strain that was responsible for the initial infection.4 This indicates that immune responses in some patients are insufficient for control of uropathogens, even in the setting of recurrent infection with the same pathogen. In some cases, UTI can progress to urosepsis. The development of systemic invasive disease secondary to UTI can be fatal.5 Multiple factors can predispose an individual to UTI, including host genetic polymorphisms that can heighten the risk for the development of UTI,6 sexual activity,7 and the virulence of the uropathogen causing infection.8 The mechanisms of pathogenesis that contribute to the progression of UTI to chronicity are not well understood.9 Uropathogenic Escherichia coli (UPEC) cause most UTIs 10 and single strains of UPEC have been associated with reinfection of patients.9, 11 The recently emerged and globally disseminated UPEC sequence type 131 (ST131) clone is of particular concern because of its high level of antibiotic resistance.11 Many studies have examined the innate immune responses to UTI,12 however, there is limited knowledge on the interplay between host and pathogen during the progression of UTI to chronicity in terms of the mechanisms governing infection control. Murine models based on reinfection have been used to study the pathogenesis of chronic UTI.13 In mice, two separate experimental challenge doses of UPEC delivered 24 hours apart predisposes to persistent bacteriuria and the development of chronic cystitis; this progression of infection encompasses the inflammatory responses that depend on both the UPEC strain and mouse background.14-16 Experimental reinfection results in either chronic persistence of UPEC or resolution of infection,14, 16 with a small number of early circulating inflammatory markers being predicative for chronicity.16, 17 These include serum interleukin (IL)-5, IL-6, granulocyte colony stimulating factor (G-CSF), and chemokine (C-X-C motif) ligand 1 (CXCL1), also known as keratinocyte cytokine (KC).14, 16, 17 Roles for early inflammatory mediators in the pathogenesis of chronic UTI are underscored by studies showing that inhibition of cyclooxygenase-2 can prevent infection,18 and tumor necrosis factor alpha (TNF) can influence the bacterial persistence.19 Interleukin 17A (IL-17A; encoded by Il17a) is an inflammatory cytokine implicated in the control of acute and chronic bacterial infections, as well as inflammation-mediated disease.20 A variety of cell types can produce IL-17A,20 most notably TH17 cells and γδ T cells. Several studies of acute UTI have shown that IL-17A is induced in response to infection with the commonly studied UPEC reference strain CFT073, as well as other clinical UPEC strains. In acute UTI in mice, IL-17A is released from γδ T-cells during the innate immune response and is crucial for the control of UPEC.21 In another study of acute UTI in mice, elevated levels of IL-17 were detected in the kidneys.22 In adult humans, elevated levels of urinary IL-17A have also been associated with acute UTI.23 In this study, we examined the role of IL-17A in the control of chronic UTI that can result from experimental reinfection in mice. 2 MATERIALS AND METHODS 2.1 Ethics statement This study was carried out in accordance with the guidelines of the Australian National Health and Medical Research Council. The institutional Animal Ethics Committee of Griffith University reviewed and approved all experimental protocols for animal usage (approval: MSC/01/18/AEC). 2.2 Bacterial strains The UPEC strains used in this study, including reference strains CFT073 (O6:K2:H1)24 and EC958 (O25b:K100:H4)25 are listed in Table S1. CFT073 was cultured from the blood of a patient with urosepsis24; EC958 is a multidrug-resistant ST131 isolate cultured from the urine of a patient with cystitis.25 These isolates express type 1 fimbriae and flagella but differ in hemolysin, P-fimbriae (both of which are absent in EC958), and Afa adhesins (absent in CFT073).25 Both strains are able to persist in the urinary tract.14, 15 Additional strains were hlyA-deficient CFT073,26 fliC-deficient CFT073; and CFT073 over-expressing flagella due to pMG600 (pflhDC).27 All strains were enriched for type 1 fimbriae expression prior to mouse challenge, essentially as per methods described in Totsika et al.25 Briefly, three successive subcultures were grown using static conditions in Lysogeny Broth (LB), and were stored at −80°C. Prior to mouse challenge, type 1 fimbriae-enriched frozen stocks were subcultured (200 mL LB, 500 mL flask) and grown statically for 19-21 hours at 37°C; type 1 fimbriae-enrichment was confirmed by yeast-agglutination assay.28 2.3 Mouse model of chronic UTI based on super-infection Female mice at 8-12 weeks of age at the time of inoculation were used. C57BL/6 and BALB/c mice were purchased from the Animal Resources Centre, Perth. Il17a−/− mice (BALB/c background) were kindly provided by Yoichiro Iwakura (Tokyo University of Science, Japan) 29 and were maintained in a breeding colony managed by Griffith University Animal Facilities. Il17a−/− mice were genotyped by PCR and sequencing using primers reported in.29 For transurethral inoculation, the super-infection model was used,17 with minor modifications. Bacteria were prepared by washing three times in phosphate-buffered saline (PBS) prior to resuspension in 50 µL PBS containing 1% India ink. Initial assays compared doses ranging from 2 × 107 to 2 × 109 CFU using BALB/c and C57BL/6 mice; two equal doses were administered 24 h apart. For subsequent assays, doses of 2 × 108 CFU in BALB/c mice (wild-type, WT or Il17a−/−) were used. Mock super-infections used 50 µL of PBS (administered 24 h apart) containing 1% India ink. Urine was collected at 1, 3, 7 10, 14, 21, and 28 days following the second inoculation and was used for enumerating CFU by colony counts. In some assays, blood was also collected (at 1 day following super-infection), and plasma was frozen at −80°C for subsequent cytokine assays. Mice were monitored individually to quantify bacteriuria during the course of experiments. Mice were defined as being chronically infected when bacteriuria remained at ≥104 CFU/mL at all time points, to be consistent with the approach described in Schwartz et al.17 The definition of resolved infection was mice that exhibited bacteriuria <104 CFU/mL at one or more time points; this was applied as a discriminator against chronic infection and is distinct from the normally accepted definition of "resolved" in the context of infection, which generally implies clearance of infection based on culture-negative urine status30 or resolution of symptoms.31 Mice were euthanized at 28 days following the second inoculation and cardiac puncture was used to collect blood. Subsequently, the bladders and kidneys were collected and homogenized in PBS containing protease inhibitor (Complete Ultra Tablet mini, EDTA free, Roche), then used for CFU counts or processed for storage. Count data are reported as CFU/mL for urine, CFU/0.1 g/mL for bladder, and CFU/1 g/mL for kidney. The supernatants of plasma and tissues were clarified (10 000 g 15 min for tissues, and 14 000 g 10 min for plasma), then frozen at −80°C. 2.4 Cytokine assays ELISA using the mouse IL-17A (homodimer) Ready-SET-Go! Kit (Thermo-Fisher Scientific) was performed essentially according to the manufacturer protocols, with minor modification. Initially, bladder and plasma supernatants were used to determine matrix effects on the ELISA and subsequently, bladder samples were diluted 1:5 for assay. IL-17A concentrations were calculated in pg/mL using a 4-parameter standard curve. For multiplex assays, plasmas were diluted 1:4 and assayed according to the manufacturer's recommendations of the Bio-Plex Pro™ Mouse Cytokine 23-plex Assay (BioRad). Cytokine concentrations (pg/mL) were determined using a 5-parameter standard curve. 2.5 Immunohistochemistry Whole kidneys of mice super-infected with UPEC EC958 or PBS were sectioned longitudinally and fixed for at least 24 hours in 10% buffered formalin. The tissues were processed for immunohistochemistry labeling of Ly6G+, F480+, and were stained using DAPI (for nuclei) according to standard techniques at the Queensland Institute of Medical Research Berghofer core histology facility. Slides were imaged using an Aperio Imager and Aperio Slide Scanner. Aperio Image Scope software was used to generate pixel counts using V9 algorithm, which were quantitated as positive or negative for semiquantitative analysis. Pixel counts for three mice per group were analyzed to enable the comparison between the treatment groups. 2.6 Flow cytometry WT mice and Il17a−/− mice were super-infected with UPEC EC958 and euthanized at days 10 and 28 postinoculation (pi); bladders and kidneys were collected and placed into RPMI 1640 medium on ice. Tissues were placed on a glass slide and sliced into 0.5-1 mm3 pieces using scalpels, then digested in RPMI containing 0.5% heat-inactivated FBS, 20 mM HEPES, 0.057 Kunitz U/µL DNAse I, and 1mg/mL collagenase A (Roche) for 1 hour at 37°C; digested tissue was passaged repeatedly through 19 gauge needles after the initial 25 minutes to promote dissociation of the tissue.21 The cells were strained through a 40 µM strainer and resuspended in red blood cell lysis buffer (8.02 mg/mL NH4Cl, 0.84 mg/mL NaHCO3, and 0.37 mg/mL EDTA in dH2O) for 1 minute, then washed twice in 10% FBS FACS buffer (10% FBS + 0.01% w/vol sodium azide in PBS). The samples (using the entire volume for bladder or approximately 106 cells for kidneys) were added to the wells of non-adherent 24-well plates. Additional samples were used as staining controls. Cells were stimulated to elicit IL-17A production using 25 ng/mL phorbol 12-myristate 13-acetate (PMA; Sigma) and 1 µg/mL Ionomycin (Sigma), at 37°C in 5% CO2 for 1 hour, and 10 ng/mL Brefeldin A (Sigma) was added to inhibit export of IL-17A. Cells were incubated for a further 4 hours.32 Cells were retrieved from the 24-well plate, washed with 1% FBS FACS buffer, and were Fc receptor-blocked using BD CD16/CD32 Pure 2.4G2 for 10 min. Surface staining used the following antibodies (BD Biosciences) in the presence of Brilliant Stain Buffer Plus: CD4 (GK1.5) BUV737, CD45 (30-F11) BUV395, CD11c (HL3) BUV786, CD3 (145-2C11) BV711, F480 (T45-2342) BV650, CD49b (HMα2) BV605, IAIE (M5/114.15.2) BV480, CD103 (M290) BV421, CD8α (53-6.7) PerCP-Cy5.5, Ly6G (1A8) FITC, CD11b (M1/70) APC-Cy7, TCR-β (H57-597) PE-Cy7, Ly6C (AL-21) PE-CF594, and TCRγδ (GL3) APC (Biolegend). Samples were washed with PBS and Fixable Viability Stain 700 (BD Biosciences) was added for live/dead staining. Samples were washed following live/dead staining and processed with BD Fixation/Permeabilization solution (cat. No. 554722). Cells were washed with saponin buffer (0.1% saponin (Sigma), 1% FBS in PBS), and stained for intracellular IL-17A using IL-17A (TC11-18H10) PE. Cells were again washed with saponin buffer, fixed with 4% formaldehyde, washed with PBS, and placed into FACS tubes. Data were acquired using a BD FACS Symphony A5 flow cytometer, and data were analyzed using FlowJo v10.6.2 adopting best practices throughout acquisition and analysis as outlined in Cossarizza et al.33 2.7 Statistical analysis Comparisons of data used Mann-Whitney U tests, Kruskall-Wallis tests followed by post hoc analyses, Spearmans, ANOVA, and Tukey's multiple comparisons tests as described in the Figure Legends. Incidence of chronicity between groups was compared using Fisher's exact test. Statistical significance was accepted with P values of ≤.05. All data were analyzed using GraphPad Prism V8. 3 RESULTS 3.1 IL-17A promotes control of chronic UTI We compared different doses of EC958 and CFT073, two UPEC strains widely used in experimental UTI models, in a super-infection model, using 2 × 107 to 2 × 109 CFU to define the relative rates of chronic persistence. These experiments showed that a dose of 2 × 108 CFU caused the highest incidence of chronic persistence in BALB/c mice (Figure S1A), and this dose was selected for use in subsequent super-infections. BALB/c WT and BALB/c Il17a−/− mice were super-infected and bacteriuria was monitored over time, followed by measurement of UPEC loads in the bladders and kidneys at day 28 as summarized in Figure 1A. Infection with CFT073 led to median bacteriuria levels in Il17a−/− mice that were significantly higher compared to BALB/c WT mice at all time points (Figure 1B). Furthermore, the incidence of chronic persistence due to CFT073 at day 28 was significantly higher for Il17a−/− mice compared to WT mice (37% vs 7%, P = .002; Figure 1C). Contrastingly, the incidence of chronic persistence due to EC958 was similar between Il17a−/− and WT mice (17% vs 18%, ns). CFT073 trended toward a higher rate of chronicity compared to EC958 in Il17a−/− mice (37% vs 17%, P = .14). UPEC burdens in the bladders were significantly higher for CFT073-infected Il17a−/− mice compared to WT mice (Figure 1D). For the kidneys, UPEC were recovered in significantly higher numbers from Il17a−/− mice compared to WT mice for CFT073 and EC958 (Figure 1D). Taken together, these data establish that mice deficient in IL-17A are more susceptible to chronic UTI after super-infection compared to WT mice; additionally, super-infection with UPEC CFT073 leads to a higher incidence of chronicity in Il17a−/− mice compared to EC958. FIGURE 1Open in figure viewer Bladder IL-17A correlates with UPEC load, reduces the incidence of chronic UTI, and is protective against pyelonephritis. A, Schematic of super-infection model illustrating the two separate inoculations of mice with 2 × 108 CFU of UPEC, 24 h apart (day −1, day 0) followed by sampling for measurement of bacteriuria at days 1, 3, 7, 19, 14, 21, and 28, and enumeration of bladder and kidney UPEC at 28 days pi. B, Bacteriuria counts from each infection group at specified time points, *P < .05, **P < .01, ***P < .001, ****P < .0001, Mann-Whitney U test. C, The percentage of mice chronically infected at 28 days pi as determined by the presence of persistent bacteriuria >104 CFU/mL at all timepoints **P < .01, Fisher's exact test. D, Bladder and kidney bacterial loads at 28 days pi (*reported as CFU/0.1 g/mL for bladder and CFU/1 g/mL for kidney). **P < .01, ****P < .001, Mann-Whitney U test; Data from (B)-(D) are pooled from three independent experiments (n = 45 WT mice, n = 30 Il17a−/− mice). For (B) and (D), bars represent median and interquartile range 3.2 IL-17A levels correlate with UPEC load and reflect a response of γδ-T and TH17 cells Quantitation of IL-17A in the bladders of BALB/c WT mice infected with UPEC EC958 or CFT073 at 28 days pi showed significantly higher levels of IL-17A in mice with chronic infection compared to resolved mice and control (non-infected) mice (Figure 2A). The differences in IL-17A levels reflected a significant positive linear correlation with bladder UPEC titers (Figure 2B). These data show that higher numbers of UPEC in the bladders of mice correlate with increased production of IL-17A. FIGURE 2Open in figure viewer Correlation between IL-17A and bladder UPEC burdens. A, IL-17A levels in bladders of BALB/c mice at 28 days pi, as per Figure 1. B, Positive linear correlation between IL-17A levels and bladder UPEC loads (*reported as CFU/0.1 g/mL). ***P < .001, Kruskall-Wallis test. ***P = .001, Spearman R. Data shown represent combined bacterial titer measures and IL17A concentrations in mice infected with EC958 or CFT073 derived from four independent experiments (n = 13-82 [A], n = 95 [B]). For (A), bars represent median and interquartile range In mice that developed high bladder UPEC titers, potential cellular sources of IL-17A were examined using flow cytometry assay of bladders and kidneys at days 10 and 28 pi (gating strategies are illustrated in Figure 3 with kidney samples (identical gating was conducted on bladder samples)). This approach identified γδ-T cells and TcRβ+ CD4+ T cells (TH17 cells) as the main cell types producing IL-17A in both tissues from mice inoculated with EC958 (Figure 4). The frequency of IL-17A-producing cells was lower overall at day 10 compared to day 28, and there were significantly higher frequencies of IL-17A+ γδ T cells in bladders of mice at day 10 pi that resolved infection (<104 CFU/mL bacteriuria) compared to the control (non-infected) mice. The frequencies of IL-17A-producing γδ T cells were significantly higher in mice chronically infected (>104 CFU/mL bacteriuria) compared to mice that resolved infection at days 10 and 28 pi in bladder and at day 28pi in kidney. Moreover, significantly higher frequencies of IL-17A+ CD4+ and IL-17A+ γδ T cells were observed in the bladders of chronically infected mice compared to resolved or control groups, both at days 10 and 28 pi (Figure 4). In the kidneys, significantly higher frequencies of IL-17A-producing CD4+ T cells were detected in mice that had any level of UPEC compared to noninfected PBS controls (Figure 4). Additionally, there were significantly higher frequencies of γδ T cells in the kidneys from chronic mice compared to PBS controls at both time points. Taken together, these data show that IL-17A production in the bladders and kidneys of mice with chronic UTI due to UPEC reflect a combined γδ-T and TH17 cell response. FIGURE 3Open in figure viewer Flow cytometric gating strategy. Hierarchical gating strategy for identification and enumeration of cell populations by flow cytometry. Displayed is representative data for kidney, with an identical gating strategy used for bladder (not shown). Arrows denote direction of gates. A, Initial gating from the top left panel includes a time-gate to exclude anonomalies, CD45+ gate to identify hematopoietic cells, doublet discrimination on forward scatter followed by side scatter, live/dead gating, and exclusion of autofluorescent cells/debris using a not-gate. The resultant cells were examined in downstream analysis. B, Cells from (A) were gated for IL-17A+ cells as displayed. IL-17A was clearly detectable in stimulated cells, while absent when a fluorescence minus one control for IL-17A PE was employed. Similarly, staining was absent in un-stimulated WT cells, and stimulated IL-17 KO cells. C, IL-17+ cells were back-gated as to identify and enumerate the frequency of IL-17A+ γδ T cells, IL-17A+ TcRβ cells including CD4 and CD8 T cell subpopulations, IL17A+ NK, IL17A+ NKT, IL17A+ TcR- "other" cells including IL17A+ TcR- CD4+ cells. D, To enumerate the frequency of CD45+ infiltrating cells, cells from (A) were gated as displayed to identify the following populations for analysis: Neutrophils, macrophages, MHC2+ monocytes, CD11b+ DC, MHC2- monocytes, NK cells, CD11b- DC, NKT cells, γδTcR T cells, CD4+ and CD8+ TcRβ+ Tcells, CD103+ CD8 Tcells. IL-17A production in TcRβ+ T cells, CD4 and CD8+ TcRβ+ T cells and γδTcR T cells are displayed with corresponding fluorescence minus one stains for IL-17A FIGURE 4Open in figure viewer IL-17A in chronic UTI reflects a combined response of γδ-T cells and TH17 cells. Mice were super-infected with EC958 and the numbers of IL-17+ cells in the bladders and kidneys were quantified by flow cytometry. Mice are shown as grouped according to the level of bacteriuria (>104, <104 CFU) at day 28 alongside PBS (non-infected) controls. The strategy for back-gating subsequent to CD45+ gating is displayed in Figure 3, with the phenotype of analyzed sub-populations as follows: CD4+ T cells (IAIE-IL-17A+TCR-β+CD4+), CD8+ T cells (IAIE-IL-17A+TCR-β+CD8+), γδ T cells (IAIE-IL-17A+TCRγδ+), NK cells (IAIE-IL-17+TCR-β-TCRγδ-CD11b+CD49b+), NKT (IAIE-IL-17A+TCR-β-TCRγδ-CD11b-CD49b+), other (IAIE-IL-17A+TCR-β-TCRγδ-CD11b+CD49b-), and CD4+ TCR (IAIE-IL-17A+TCR-B-TCRγδ-CD11b+CD49b-CD4+). *P < .05, P < .01**, P < .001***, P < .0001**** two-way ANOVA, Tukey's multiple comparisons test. The data displays the percentage of IL-17A+ back-gated sub-populations with respect to CD45+ cells. Graphs represent combined data from three independent flow cytometry assays (n = 5-22). Bars represent median and interquartile range 3.3 Early circulating inflammatory markers predict chronic UTI outcomes and pyelonephritis Previous studies in mice identified several circulating inflammatory mediators predictive for chronicity in mice. These include interleukin 5 (IL-5), interleukin 6 (IL-6), granulocyte colony stimulating factor (G-CSF), and CXCL1 (also known as KC).14, 16, 17 We collected plasma from mice at 24 hours pi (ie, 24 h after super-infection) and analyzed the levels of 23 immune and inflammatory markers to discern potentially divergent responses in chronically infected mice vs resolved mice. In BALB/c WT mice infected with UPEC EC958, the levels of IL-6 and monocyte chemoattractant protein-1 (MCP-1) were significantly higher in mice that progressed to chronicity vs those that resolved infection (Figure 5A). Similarly, the median level of G-CSF showed a clear trend toward higher levels in mice that progressed to chronicity, con