Identification of novel HIV-1 dependency factors in primary CCR4+CCR6+Th17 cells via a genome-wide transcriptional approach
- Aurélie Cleret-Buhot1, 2,
- Yuwei Zhang1, 2,
- Delphine Planas1, 2,
- Jean-Philippe Goulet3,
- Patricia Monteiro1, 2,
- Annie Gosselin2,
- Vanessa Sue Wacleche1, 2,
- Cécile L. Tremblay1, 2,
- Mohammad-Ali Jenabian4,
- Jean-Pierre Routy5, 6, 7,
- Mohamed El-Far2,
- Nicolas Chomont1, 2,
- Elias K. Haddad8,
- Rafick-Pierre Sekaly9 and
- Petronela Ancuta1, 2Email author
© Cleret-Buhot et al. 2015
Received: 15 September 2015
Accepted: 22 November 2015
Published: 10 December 2015
The HIV-1 infection is characterized by profound CD4+ T cell destruction and a marked Th17 dysfunction at the mucosal level. Viral suppressive antiretroviral therapy restores Th1 but not Th17 cells. Although several key HIV dependency factors (HDF) were identified in the past years via genome-wide siRNA screens in cell lines, molecular determinants of HIV permissiveness in primary Th17 cells remain to be elucidated.
In an effort to orient Th17-targeted reconstitution strategies, we investigated molecular mechanisms of HIV permissiveness in Th17 cells. Genome-wide transcriptional profiling in memory CD4+ T-cell subsets enriched in cells exhibiting Th17 (CCR4+CCR6+), Th1 (CXCR3+CCR6−), Th2 (CCR4+CCR6−), and Th1Th17 (CXCR3+CCR6+) features revealed remarkable transcriptional differences between Th17 and Th1 subsets. The HIV-DNA integration was superior in Th17 versus Th1 upon exposure to both wild-type and VSV-G-pseudotyped HIV; this indicates that post-entry mechanisms contribute to viral replication in Th17. Transcripts significantly enriched in Th17 versus Th1 were previously associated with the regulation of TCR signaling (ZAP-70, Lck, and CD96) and Th17 polarization (RORγt, ARNTL, PTPN13, and RUNX1). A meta-analysis using the NCBI HIV Interaction Database revealed a set of Th17-specific HIV dependency factors (HDFs): PARG, PAK2, KLF2, ITGB7, PTEN, ATG16L1, Alix/AIP1/PDCD6IP, LGALS3, JAK1, TRIM8, MALT1, FOXO3, ARNTL/BMAL1, ABCB1/MDR1, TNFSF13B/BAFF, and CDKN1B. Functional studies demonstrated an increased ability of Th17 versus Th1 cells to respond to TCR triggering in terms of NF-κB nuclear translocation/DNA-binding activity and proliferation. Finally, RNA interference studies identified MAP3K4 and PTPN13 as two novel Th17-specific HDFs.
The transcriptional program of Th17 cells includes molecules regulating HIV replication at multiple post-entry steps that may represent potential targets for novel therapies aimed at protecting Th17 cells from infection and subsequent depletion in HIV-infected subjects.
The Th17 cells represent a distinct lineage of CD4+ T-cells characterized by the expression of specific transcription factors (e.g., RORγt, RORA, and STAT3) and cytokines (e.g., IL-17A, IL-17F, IL-21, IL-22, IL-26, IL-8, and CCL20) [1–5]. Th17 cells represent unique players in immunity against pathogens at mucosal barrier surfaces where they orchestrate the functionality of epithelial cells, neutrophils, and B cells [3, 6, 7, 8, 9, 10]. Recruitment of Th17 cells into mucosal sites is mediated in part by the homing receptor CCR6/CCL20, with CCR6 being a well-established Th17 surface marker [11, 12]. Other homing receptors, such as CCR4 and CXCR3, distinguish between Th17 subsets with distinct antigenic specificity and effector cytokine expression: CCR4+CCR6+Th17 and CXCR3+CCR6+Th1Th17 [13–15]. During chronic HIV/SIV infections, the depletion of Th17 cells from gut-associated lymphoid tissues (GALT) leads to dramatic alterations of the mucosal barrier integrity, alterations that cause microbial translocation, chronic immune activation, and disease progression [16–28]. Studies in SIV models demonstrated an inverse correlation between peak and set point viral loads as well as the preexisting mucosal Th17 pool ; this strengthens the concept that Th17 cells significantly contribute to anti-viral immunity at mucosal sites . Studies in HIV-infected subjects demonstrated that the preservation of mucosal Th17 cells is associated with slow disease progression [31–36]. Despite the success of current antiretroviral therapies (ART) in reducing viral replication to undetectable plasma levels, the pool of Th17 cells is not fully restored at mucosal sites or in the peripheral blood of infected subjects [22, 31, 37, 38, 39]. Recent studies demonstrated that ART initiation during early but not late acute HIV infection preserves Th17 counts and their effector functions [40, 41]. However, early HIV diagnosis remains, however a challenge even in high income countries; this emphasizes the need for alternative strategies with the goal of Th17 preservation and/or restoration during chronic HIV infection.
The mechanisms underlying Th17 depletion during HIV/SIV infections include altered trafficking into mucosal sites [42, 43]; altered ratios between regulatory T-cells (Tregs) and Th17 cells [44, 45]; depletion of mucosal CD103+ dendritic cells (DC) , a subset involved in Th17 differentiation [47, 48]; limited IL-21 availability, a cytokine critical for Th17 survival ; and/or over expression of negative regulators of Th17 differentiation . In addition, studies by our group and others provided evidence that infection per se contributes to the depletion of memory Th17 cells [37, 38, 50] and the paucity of naive-like Th17 precursors [39, 51]. Despite their massive depletion, fractions of Th17 cells are long lived [52–54] and likely contribute to HIV persistence under ART  (Wacleche, Ancuta et al, unpublished observations). Genome-wide RNA interference studies performed in distinct cell lines identified large sets of HIV dependency factors (HDFs) and revealed the molecular complexity of virus-host cell interactions [56–60]. Nevertheless, the molecular determinants of HIV permissiveness in primary Th17 cells are not fully understood. This knowledge is essential for designing novel targeted therapies aiming at limiting HIV replication and persistence specifically in Th17 cells.
In this study, we investigated transcriptional and functional differences between primary memory CD4+ T-cell subsets enriched in Th17 (CCR4+CCR6+) and Th1 (CXCR3+CCR6−) polarized cells, subsets that we previously reported to be permissive and resistant to infection with R5 or X4 HIV strains, respectively . Our study revealed the existence of HDFs specifically expressed by Th17 cells that may be used as targets for novel therapeutic strategies aiming at limiting HIV replication and preserving the quality of Th17-mediated mucosal immunity in HIV-infected subjects.
Identification of a molecular signature associated with HIV permissiveness in Th17 cells at entry and post-entry levels
Top up regulated transcripts in CCR4+CCR6+ Th17 versus CXCR3+CCR6− Th1
Chemokine (C–C motif) receptor 6
Protein tyrosine phosphatase, non-receptor type 13 (APO-1/CD95 (Fas)-associated phosphatase)
Killer cell lectin-like receptor subfamily B, member 1
Chemokine (C–C motif) ligand 20
RAR-related orphan receptor C, transcript variant
G protein-coupled receptor 56, transcript variant 2
Legumain, transcript variant 2
Cathepsin H, transcript variant 1
Kruppel-like factor 2 (lung)
Retinoic acid receptor responder 3
Lymphocyte antigen 9, transcript variant 2
Tumor necrosis factor superfamily, member 13b
Nuclear localized factor 2
Peptidase inhibitor 16
MAX dimerization protein 4
Hydroxyprostaglandin dehydrogenase 15-(NAD)
Sorting nexin 29
Tribbles homolog 2
Purinergic receptor P2Y, G-protein coupled, 5
Zinc finger protein 831
Lck interacting transmembrane adaptor 1
Mitogen-activated protein kinase kinase kinase 4
CD96 molecule, transcript variant 1
G protein-coupled receptor 15
Peroxisome proliferator-activated receptor gamma
GLI pathogenesis-related 1
Aryl hydrocarbon receptor nuclear translocator-like
Forkhead box O3 (FOXO3), transcript variant 2, mRNA
Top down regulated transcripts in CCR4+CCR6+ Th17 vs. CXCR3+CCR6− Th1
Granzyme K (granzyme 3; tryptase II)
Chemokine (C–C motif) ligand 5
Granzyme H (cathepsin G-like 2, protein h-CCPX)
Interleukin 3 (colony-stimulating factor, multiple)
Natural killer cell group 7 sequence
Chemokine (C–C motif) ligand 4-like 2
Chemokine (C–C motif) ligand 3
Eomesodermin homolog (Xenopus laevis)
Chemokine (C–C motif) ligand 3-like 1
Chemokine (C–C motif) ligand 3-like 3
Homo sapiens napsin B aspartic peptidase pseudogene (NAPSB)
Basic leucine zipper transcription factor, ATF-like 3
Napsin A aspartic peptidase
Chemokine (C–X–C motif) receptor 3
Megakaryocyte-associated tyrosine kinase, transcript variant 3
Interferon regulatory factor 8
Monoamine oxidase A, nuclear gene encoding mitochondrial protein
DnaJ (Hsp40) homolog. subfamily C, member 12
Neuropeptide S receptor 1, transcript variant 1
ATPase. class I, type 8B. member 4
T-cell immunoglobulin and mucin domain containing 4
Lymphotoxin alpha (TNF superfamily. member 1)
Serpin peptidase inhibitor, clade B (ovalbumin). member 6
PTK2 protein tyrosine kinase 2, transcript variant 2
Chemokine (C–C motif) ligand 17
Nuclear factor interleukin 3 regulated
Gene Set Variation Analysis (GSVA) of differentially expressed genes (p < 0.05; FC cut-off 1.3) identified canonical pathways (C2) enriched in Th17 versus Th1, including those linked to circadian repression of expression by REV-ERBα, nuclear receptor transcription, T helper differentiation, CSK signaling, TCR signaling, Ras, anthrax, IL-7 signaling, phosphorylation of CD3 and TCR zeta, PTEN, ABCA transporters in lipid homeostasis, RhoA, longevity pathway, MEF2D signaling, the role of Nef in HIV replication, and TNF signaling (Fig. 1e). The GSVA also identified pathways down regulated in Th17 versus Th1, including pathways linked to metal ion SLC transporters, zinc transporters, STEM, glucose transport, extension of telomeres, protein synthesis as well as transcription initiation and termination (Additional file 3: Figure S1b; Additional file 4: Table S3). These results reveal overrepresentation of specific transcripts and cellular functions in Th17 versus Th1, with pathways enriched in Th17 cells likely being essential for both Th17 polarization and HIV permissiveness.
Similar to GSVA and GO, Gene Set Enrichment Analysis (GSEA)  identified top genes linked to canonical pathways (TCR signaling: PAK2, Lck, ZAP-70, CD96), transcription factors (RORC, RUNX1), and biological processes (stress activated protein kinase signaling: MAP4K1, MAP3K4, MAP3K5; protein amino acid dephosphorylation: PTPN12, PTPN13, PTPN22) as being up regulated in Th17 versus Th1 cells (Additional file 5: Figure S2).
In conclusion, genome-wide transcriptional profiling revealed differences in gene expression between human Th17 and Th1 subsets, validated previously described cell-specific transcripts, and identified a large panel of new transcripts that may contribute to Th17 when compared to Th1 lineage differentiation fate and/or HIV permissiveness at post-entry levels.
Th17 versus Th1 express higher Lck and ZAP-70 levels
Other downstream TCR signaling molecules overexpressed in Th17 versus Th1 include PAK2, PI3 K, and Fyn (Additional file 7: Figure S4). PAK2 is a well-established target of HIV-Nef that contributes to viral replication . PI3 K is required for HIV-1 Nef-mediated down-regulation of cell surface MHC-I molecules . Fyn has been demonstrated to be involved in NF-κB mediated HIV transcription . In contrast, Grb2 (growth factor receptor-bound protein 2) was found down regulated in Th17 versus Th1 (Additional file 7: Figure S4). This is consistent with the fact that Grb2 inhibits the Tat-mediated transactivation of HIV-1 LTR and subsequent viral replication  (Additional file 4: Table S3).
Altogether, these results demonstrate superior expression of signaling molecules associated with TCR signaling in Th17 versus Th1, including the active phosphorylated forms of Lck and ZAP-70. These differences very likely contribute to the superior ability of Th17 when compared to Th1 to respond to weak TCR signals, thus creating a cellular environment favorable to HIV replication.
Th17 versus Th1 exhibit superior NF-κB nuclear translocation and DNA-binding activity
Th17 versus Th1 proliferate in response to low intensity TCR triggering
MAP3K4, PTPN13, and SERPINB6 act as HIV permissiveness factors
HIV-1 targets for infection and subsequent depletion cells of the immune system that play key roles in the defense against pathogens, including the Th17-polarized CD4+ T-cells [19, 37, 38, 50]. The unique developmental plasticity (e.g., ability to convert into Th1, Th2 and Tregs [107, 108]), pathogen-specificity and functional heterogeneity [13, 14, 15, 109, 110, 111, 112], together with their long-lived properties [52–54], position Th17 cells at the very core of the immune system. Given their predominant location at mucosal surfaces, including the gut-associated lymphoid tissues (GALT), Th17 cells represent the first HIV/SIV targets at the portal sites of entry [25, 113]. Quantitative and qualitative alterations in Th17 cells within the GALT represent a major cause of HIV/SIV disease progression [24, 25, 114, 115, 116, 117, 118, 119]. Therefore, understanding molecular mechanisms of HIV permissiveness in Th17 cells represents a major research priority. Studies by our group , confirmed by others [38, 50], demonstrated that CCR4+CCR6+Th17 and CXCR3+CCR6+Th1Th17 cells are highly permissive, while CXCR3+CCR6−Th1 are relatively resistant to R5 and X4 HIV infection, and CCR4+CCR6−Th2 are permissive to X4 HIV only . In this manuscript, we used a systems biology approach to unveil molecular mechanisms of HIV replication in Th17 cells by comparing their transcriptome to those of Th1, Th2 and Th1Th17 cells. We reveal here for the first time to our knowledge a molecular signature associated with HIV permissiveness in primary Th17 cells.
Our genome-wide transcriptional profiles demonstrated superior expression of KLF2 in Th17 compared to Th1 cells. These findings were confirmed by RT-PCR. KLF2 is a transcription factor that binds to the CCR5 promoter and positively regulates its expression and the subsequent permissiveness of CD4+ T-cells to R5 HIV . CCR5 is indeed a key co-receptor for HIV entry  and one of the major determinants of disease progression [121, 122] involved in the early phases of HIV acquisition at mucosal surfaces [123, 124]. Activated CCR5+ T-cells are enriched within the GALT and represent the first HIV targets . However, superior HIV permissiveness in Th17 versus Th1 is not the reflection of their superior CCR5 expression ex vivo ; this suggests that CCR5 is essential but not sufficient to support R5 HIV entry and/or subsequent replication. Nevertheless, the stability of CCR5 expression upon TCR triggering in long-term cultures was not investigated in our system, and therefore the potential role of KLF2 in regulating superior/stable CCR5 expression in Th17 cells cannot be excluded. The autocrine production of CCR5 ligands was previously identified as a mechanism by which CMV-specific CD4+ T-cells are protected from HIV infection . The overexpression of transcripts for CCR5 ligands observed in this study in Th1 versus Th17 is consistent with previous reports by our group  and others [50, 114] where CCR5 ligand protein levels were investigated. Thus, the autocrine production of CCR5 ligands by Th1 cells may contribute to limited HIV entry in Th1 cells. Despite any potential regulatory mechanisms at entry level, we report superior HIV-DNA integration in Th17 versus Th1 cells upon exposure to both wild-type and VSV-G-pseudotyped HIV; this indicates that post-entry mechanisms contribute to viral permissiveness in Th17 cells.
Upon receptor-mediated entry, HIV-1 uses the host-cell molecular machinery to ensure its reverse transcription, integration and transcription [59, 60]. Large siRNA screens performed on cell lines identified networks of HDFs acting at different levels of the viral life cycle [56, 57, 58, 84]. Very few HDF identification studies were performed on primary cells [127–129]. JAK1 is one of the very few HDFs identified in more than two siRNA screens that is also included in the NCBI HIV interaction database . Of particular importance, our microarrays revealed an up-regulation of JAK1 transcripts in Th17 versus Th1. JAK1 is a tyrosine kinase associated with the signaling through the receptors of type I and II cytokines; activation of JAK1 induces STAT3 phosphorylation in response to IL-21 stimulation . Consistent with JAK1 up-regulation in Th17 cells, the JAK signaling pathway is altered in subjects with Hyper IgE syndrome that exhibit mutations in STAT3 and subsequent Th17 deficiency . JAK1 antagonists were reported to interfere with Th17 polarization in a mouse model of psoriasis . Considering the fact that JAK antagonists inhibit HIV replication and reactivation , JAK1 may represent a novel therapeutic target to interfere with infection in Th17 cells.
Despite a low degree of overlap among individual HDFs identified in different siRNA screens [56, 57, 58, 84], pathways such as NF-κB, peroxisome proliferator-activated receptor (PPAR), and retinoic acid receptor were identified as being important for HIV permissiveness in at least two distinct studies [59, 60]. A previous study by our group demonstrated that the transcription factor PPARγ is expressed at superior levels in Th1Th17 versus Th1 and acts as a negative regulator of HIV replication . Of note, PPARγ is also an intrinsic negative regulator of Th17 polarization . Therefore, mechanisms involved in Th17 polarization and HIV replication are overlapping. The present transcriptional profiles consistently demonstrated superior expression of PPARγ in Th17 versus Th1 cells. These findings provide further evidence that Th17, similar to Th1Th17 cells , are endowed with intrinsic mechanisms that control HIV permissiveness, mechanisms that should be targeted therapeutically.
Consistent with differential HIV replication in Th17, Th1Th17, Th1, and Th2 memory CD4+ T-cell subsets , the present genome-wide transcriptional profiling revealed the remarkable transcriptional differences between Th17 and Th1 cells. Gene set variation analysis revealed unique pathways enriched in Th17 versus Th1 cells, including TCR signaling, T-helper differentiation, IL-7 signaling, nuclear receptor transcription, and circadian repression of expression by REV-ERBα. Therefore, it is reasonable to assume that pathways preferentially expressed in Th17 cells are exploited by HIV for successful replication.
Similar to Th2 and in contrast to Th1 , Th17 polarization depends on low strength TCR signals . Consistently, we found an enriched expression of transcripts linked to the TCR signaling cascade in Th17 versus Th1, including the major kinases Lck and ZAP-70. These differences were validated by RT-PCR at the population level and further visualized/quantified at the single-cell level by confocal microscopy. Of note, Lck facilitates assembly of HIV-1 by targeting HIV-1 Gag to the plasma membrane in T cells , while ZAP-70 kinase regulates HIV cell-to-cell spread and virological synapse formation . Superior expression of phosphorylated active forms of Lck and ZAP-70 in Th17 versus Th1 cells coincided with superior expression of transcripts for multiple kinases and phosphatases downstream from the TCR. Among transcripts associated with the TCR reactome, our RNA interference experiments identified MAP3K4 and PTPN13 as positive regulators of HIV replication in Th17 cells. The phosphorylation of p38 MAPK by MAP3K4 was previously linked to Th17 polarization signals . We previously reported MAP3K4 up-regulation in HIV-permissive Th1Th17 cells . PTPN13, a tyrosine phosphatase involved in the negative regulation of Fas-dependent apoptosis upon TCR triggering [138–140], was identified as a Th1Th17 marker [62, 129]. Here, we confirmed by RT-PCR the exclusive expression of PTPN13 mRNA in Th17 versus Th1. Mechanisms by which MAP3K4 and PTPN13 regulate HIV replication remain to be further examined, but they are likely linked to the control of the state of cellular activation upon TCR engagement.
The replication of HIV is limited in resting CD4+ T-cells  through restriction mechanisms that are abrogated by activation/proliferation induced upon engagement of the TCR and/or cytokine receptors [141–144]. Our functional studies demonstrated that CD3/CD28 engagement resulted in superior cell proliferation and NF-κB nuclear translocation as well as DNA binding activity in Th17 versus Th1. Indeed, in contrast to IFN-γ+, IL-17A+ cells proliferated efficiently in response to low concentrations of CD3/CD28 Abs. A study by Santarlasci et al. reported an impaired ability of Th17 cells to proliferate . This report is in contrast to our results on superior NF-κB activation and proliferation in Th17 versus Th1 cells. These discrepancies may be explained by results generated with polyclonal subsets producing IL-17 ex vivo in our studies versus Th17 clones in studies by Santarlasci et al. 145], clones that are potentially exhausted or senescent due to long-term maintenance in vitro. Our findings are in line with publications by other groups on the long lived properties of Th17 cells [52–54]. In addition to the ability of NF-κB to regulate transcription of multiple host genes that may be critical for HIV permissiveness, NF-κB directly binds to the HIV promoter and positively regulates its activity [102, 103]. Accordingly, genome-wide siRNA screens for HDFs identified the NF-κB pathway as being a key regulator of HIV permissiveness [59, 60]. In our transcriptional studies, MALT1 (a paracaspase involved in NF-κB activation ) and TRIM8 (a regulator of NF-κB and STAT3-dependent signaling cascades [81, 82] and documented HDF ) were also found up regulated in Th17 versus Th1 cells. Of particular interest, MALT1 was recently linked to Th17 polarization . These results emphasize complex host cell-pathogen interactions by which HIV takes advantage of universal and Th17-specific proximal/distal components of the TCR signaling cascade for its efficient replication.
Our findings that Th17 cells proliferate in response to weak TCR signals are consistent with recent studies demonstrating that miR-181a, a microRNA involved in the regulation of TCR activation , is preferentially induced under Th17 polarizing conditions . MiR-181a lowers the TCR activation threshold through the modulation of ERK phosphorylation . Of note, miR-181a is also involved in the post-transcriptional regulation of SAMHD1 , an HIV restriction factor expressed in quiescent CD4+ T-cells  that limits HIV reverse transcription by its dNTPase  and RNase activity . The restriction ability of SAMHD1 is negatively regulated by phosphorylation . Our microarrays were not designed to detect microRNAs and did not reveal differences in SAMHD1 mRNA expression. Further studies are needed to clarify the potential role of SAMHD1 in controlling HIV replication in Th17 cells.
This study reveals a unique molecular signature of HIV permissiveness in Th17 cells (e.g., PPARG, PAK2, KLF2, PTEN, ITGB7, ATG16L1, Alix/AIP1/PDCD6IP, LGALS3, JAK1, TRIM8, MALT1, FOXO3, ARNTL, ABCB1, TNFSF13B/BAFF, and CDKN1B) and provides evidence that a unique TCR signaling cascade is favorable to HIV replication in Th17 cells. The current identification of novel Th17-specific HDFs is instrumental for designing novel therapeutic strategies aimed at interfering with viral replication, while maintaining the Th17 role in mucosal immunity.
Healthy HIV-uninfected donors were recruited at the Montreal Chest Institute, McGill University Health Centre, and Centre Hospitalier de l’Universite de Montreal (CHUM, Montreal, Quebec, Canada). Large quantities of PBMCs (109–1010 cells) were collected by leukapheresis as previously described .
This study, using PBMC samples from healthy HIV-uninfected subjects, was conducted in compliance with the principles included in the Declaration of Helsinki. This study received approval from the Institutional Review Board of the McGill University Health Centre and the CHUM-Research Centre, Montreal, Quebec, Canada. All human subjects that donated biological samples for this study provided written informed consent for their participation in the study. All human subjects agreed with the publication of the subsequent results generated using the samples.
Flow cytometry analysis
Fluorochrome-conjugated Abs used for polychromatic flow cytometry analysis were CD3-Pacific Blue (UCHT1), CD4-Alexa700 (RPA-T4), CD45RA-APC-Cy7 (custom), CCR4-PE-Cy7 (1G1), CXCR3-PE-Cy5 (1C6), CCR6-PE (11A9), Ki67-FITC, IFN-γ-AlexaFluor 700 (B27) (BD Pharmingen), CD56-FITC (MEM188), IL-17-PE (64DEC17) (eBioscience), HIV-p24-FITC (FH190-1-1) (Beckman Coulter), CD8-FITC (BW135/80), and CD19-FITC (LT19) (Miltenyi). A viability dye (Molecular Probes® LIVE/DEAD® Fixable Dead Cell Stain Kits, Invitrogen) was used to exclude dead cells. Cells were stained and analyzed by FACS using the BD LSRII cytometer and the FlowJo software, as previously described .
Magnetic (MACS) and fluorescence activated cell sorting (FACS)
Total or memory CD4+ T-cells were enriched from PBMC by negative selection using magnetic beads (MACS, Miltenyi), with a purity >95 % as previously described [37, 104]. Then, cells were stained with CD45RA-APC-Cy7, CCR6-PE, CCR4-PE-Cy7, CXCR3-PE-Cy5 Abs and a cocktail of FITC-conjugated Abs to exclude CD8+ T-cells (CD8), NK cells (CD56), and B cells (CD19). The sorting gates were set on FITCneg memory (CD45RAneg) T-cells. Four subsets were sorted by flow cytometry (BDAria II): CXCR3+CCR4−CCR6− (CXCR3+Th1), CXCR3−CCR4+CCR6− (CCR4+Th2), CXCR3−CCR4+CCR6+ (CCR4+CCR6+Th17), and CXCR3+CCR4−CCR6+ (CXCR3+CCR6+Th1Th17). In other experiments, memory CCR6+ and CCR6− T-cells were sorted upon staining with CD45RA-APC-Cy7 and CCR6-PE Abs as well as a mixture of FITC-conjugated CD8, CD56, and CD19 Abs. A viability dye was used to exclude dead cells. Post-sort FACS analysis demonstrated sorted T-cell subsets were >99 % pure, as reported earlier [37, 104, 129].
Genome-wide transcriptional profiling
Matched memory CD4+ T-cell subsets were isolated by FACS from five different HIV-uninfected donors and stimulated with immobilized CD3 and soluble CD28 (1 µg/ml) for 3 days. Total RNA was isolated using RNeasy columns kit (Qiagen) according to the manufacturer’s protocol. RNA quantity was determined by Pearl nanophotometer (Implen, Germany) (106 cells yielded 1–5 µg RNA). Genome-wide analysis of gene expression was performed on total RNA by Génome Québec (Montreal, Quebec, Canada). Briefly, the quality of total RNA was tested using the Agilent 2100 Bioanalyzer chip. High quality RNA was reverse transcribed and hybridized on the Illumina HumanHT-12 v4 Expression BeadChip providing coverage for more than 47,000 transcripts and known splice variants across the human transcriptome.
Transcriptional profiling analysis
Gene expression analyses were performed as previously described . Briefly, after quality control of the microarray data, the resulting expression matrix was used as input for linear modelling using Bioconductor’s limma package, which estimates the fold-change among predefined groups by fitting a linear model and using an empirical Bayes method to moderate standard errors of the estimated log-fold changes for expression values from each gene. A linear mixed model was designed with the population as a fixed effect and the donor ID as a random effect. P values from the resulting comparison were adjusted for multiple testing according to the method of Benjamini and Hochberg (1995). This method controls the false discovery rate (FDR), which was set to 0.05 in this analysis. Determination of regulated gene expression is based on p values or adjusted p values as indicated in the figure or table legends. The entire microarray dataset and technical information requested by Minimum Information About a Microarray Experiment (MIAME) are available at the Gene Expression Omnibus (GEO) database under accession number GSE70396. Differentially expressed genes (cut-off 1.3-fold; p < 0.05) were classified through Gene Ontology using the NetAffx web-based application (Affymetrix). Corresponding heat maps for biological function categories were generated using programming language R. Enrichment Statistics (ES) from the gene set variation analysis were calculated as the maximum distance of the random walk statistic using the GSVA bioconductor package  on the same databases described in Bernier et al. . Differential expression analysis of the ES was performed with the limma bioconductor package following the same model applied to probe-level expression. The gene networks were generated through the use of ingenuity pathways analysis (Ingenuity® systems, http://www.ingenuity.com).
One step SYBR Green real-time RT-PCR (Qiagen) was carried out in a LightCycler 480 II (Roche) according to manufacturer’s recommendations, as we previously reported [37, 104, 129]. Briefly, for standard curve preparation, 5-50 ng of total RNA were reverse transcribed using a SYBR Green mix (Qiagen) containing 0.5 μM primers. Agarose gel electrophoresis was used to visualize the size of the amplification products. cDNA purification was performed using the QIAquick Gel Extraction Kit (Qiagen). Serial dilutions of cDNA (20,000; 2000; 200; 20; 2; 0.2 fgs) were used for the absolute quantification of target gene expression. QuantiTect Primer Assays for KLF2, PPARγ, ARNTL, ZAP-70, Lck, PTPN13, RORC, MAP3K4, and SERPINB6 were purchased from Qiagen. The expression of each gene was normalized relative to the internal control 28S rRNA levels (forward 5′-CGAGATTCCTGTCCCCACTA-3′; reverse 5′-GGGGCCACCTCCTTATTCTA-3′, IDT). Melting curve analysis performed after real-time amplification revealed the uniformity of thermal dissociation profile for each amplification product. Samples without template or without reverse transcriptase were used as negative controls. Each RT-PCR reaction was performed in triplicate.
HIV infection and quantification of viral replication
The following HIV-1 molecular clones were used in this study: (1) replication-competent CCR5-using (R5) HIV NL4.3BAL; (2) replication-competent R5 NL4.3BAL-GFP expressing gfp in place of nef; and (3) single-round VSVG-HIV-GFP, an env-deficient NL4.3 provirus pseudotyped with the VSV-G envelope and expressing gfp in place of nef [37, 104, 129]. HIV stocks were produced, titrated, and used to infect cells (50 ng HIV-p24 per 106 cells) as previously described [37, 104, 129]. HIV-p24 levels were quantified in cell culture supernatants using a homemade ELISA [37, 104]. HIV-DNA integration was quantified in cell lysates by real-time nested PCR (105 cells per test in triplicate; detection limit: three HIV-DNA copies), as previously described [37, 104, 129, 154].
Fluorescence microscopy and quantitative image analysis
The visualization and quantification of protein expression was performed by confocal microscopy, as previously described . Briefly, FACS-sorted Th17 and Th1 subsets were stimulated via CD3/CD28 for 3 days (1 μg/ml) and placed into poly-l-lysine-coated eight-wells glass culture slides (BD Biosciences) (105 cells/well). Cells were stained with primary Abs against total Lck (clone 73A5), total ZAP-70 (clone 99F2), phosphorylated Lck on Tyr-394 (Santa Cruz Biotechnology) and Tyr-505 (clone 2751), phosphorylated ZAP-70 on Tyr319 (clone 65EA cross reacting with phosphorylated Syk on Tyr352), and NF-κB p65 (clone 3034) and Alexa Fluor 488-conjugated goat anti-rabbit Abs (Invitrogen) as secondary Abs. The above Abs were purchased from Cell Signaling Technology, unless otherwise specified. Slides were mounted using ProLong Gold Antifade medium with the nuclear dye DAPI (Invitrogen, Molecular Probes). Epi-fluorescent and Spinning Disc confocal microscopy images were acquired out on an automated Cell Observer Z1® microscope (Carl Zeiss) using the AxioVision 4.8.2 software (Carl Zeiss). For the analysis of protein cellular localization, spinning disc confocal images were acquired using the 100× oil immersion objective (numerical aperture, NA: 1.46) and maximum intensity projection of 0.2 μm z-stack sections were realized using ImageJ software (NIH) after background subtraction. For statistical analysis of protein expression, random epi-fluorescent images were acquired with the 40× oil immersion objective (NA: 1.3). All acquisitions between the different T-cell subsets were performed with the same illumination status in the same run. Integrated density was measured after background subtraction with ImageJ software. Data were compared by analysis of integrated density/area for 50–100 cells/subset.
NF-κB DNA-binding activity
Nuclear extracts were obtained from activated CD4+ T-cells using the BD transfactor extraction kit (Clonetech Laboratories). The active form of NF-κB p65 was quantified by ELISA (1 μg nuclear protein/test; Assay Designs & Stressgen). The specificity of NF-κB p65 DNA-binding was determined using wild-type and mutated NF-κB p65 duplex competitors, according to the manufacturer’s protocol.
CFSE dilution assay and intracellular cytokine staining
Cell proliferation was measured using the Carboxy Fluorescein Succinimidyl Ester (CFSE) dilution assay, as previously described . Briefly, memory CD4+ T-cells were loaded with CFSE and cultured in the presence of different doses of immobilized CD3 and soluble CD28 Abs (0.5, 0.25, and 0.1 µg/ml) for 1, 2, 3, or 4 days. Cells were further stimulated with PMA (50 ng/ml, Sigma) and Ionomycin (1 µg/ml, Sigma) in the presence of Brefeldin A (2 μg/ml, Sigma) for 18 h. The production of IL-17A and IFN-γ was measured by intracellular staining with appropriate Abs using the BD cytofix/cytoperm fixation/permeabilization solution kit (BD Biosciences) according to the manufacturer’s protocols.
RNA interference studies were performed as described earlier . Briefly, PBMCs were thawed and rested overnight at 37 °C. Memory CD4+ T-cells were isolated from PBMC by negative selection using magnetic beads (Miltenyi Biotec). Cells were stimulated by CD3/CD28 Abs for 2 days and nuclofected with 100 µM specific (MAP3K4, PTPN13, SERPINB6) or non-targeting (NT1) siRNA (ON-TARGETplus SMART pool, Dharmacon) using the Amaxa Human T cell Nucleofector Kit (Amaxa, Lonza), according to the manufacturer’s protocol. Cells were suspended in the NF solution (100 µl/2 × 106 cells) and nucleofected using the Amaxa Nucleofector II Device and the human activated T-cell protocol (T-20). Cells (2 × 106) were transferred into 48-well plates containing 1 ml of RPMI1640 (10 % FBS, 5 ng/ml IL-2, w/o antibiotics) and cultured for 24 h at 37 °C. Cells were exposed to HIV and cultured up to 9 days. Culture supernatants were harvested and media was refreshed every 3 days. The effectiveness of RNA silencing was assessed by SYBR Green real-time RT-PCR 24 h post-nucleofection. IL-17A production in cell supernatants was measured by ELISA at day 3 post-infection. Five days post-nucleofection, cells were stained with LIVE/DEAD® Fixable Dead Cell Stain Kit (invitrogen) and intracellular staining was performed using Ki67 Abs. Cell viability (vivid-) and cell cycle progression (Ki67+) were analyzed by FACS (BD LSRII).
All statistical analyses were performed using the Prism 5 (GraphPad software). Specifications are included in the figure legends.
The entire microarray dataset and technical information requested by Minimum Information About a Microarray Experiment (MIAME) are available at the Gene Expression Omnibus (GEO) database under accession number GSE70396.
ACB, YZ, and DP performed experiments, analyzed the results, prepared the figures, and contributed to manuscript writing. JPG performed the bioinformatic analysis of transcriptional profiles. PM prepared samples for the genome-wide analysis of gene expression and analyzed transcriptional profiles. AG and VSW contributed to all sorting experiments for transcriptional studies and functional validations. CT, MAJ, and JPR were involved in sample collection, access to clinical information, and manuscript revision. MEF, NC, EH, and RPS contributed to study design, provided experimental protocols, and revised the manuscript. PA designed the study, analyzed the results, contributed to figure preparation, and wrote the manuscript. All authors read and approved the final manuscript.
The authors thank Sylvain Gimmig, Laurence Lejeune, and Dr. Dominique Gauchat for expert technical support in FACS analysis and cell sorting (the CHUM-Research Centre FACS Core Facility), Anne Vassal and Mario Legault (HIV/AIDS and infectious diseases network of the Fonds de Recherche Québec-Santé (FRQ-S)) for help with ethical approvals and informed consents, Dr. Mohamed-Rachid Boulassel and Véronique Lafontaine for sample management, Dr. Dana Gabuzda (Dana-Farber Cancer Institute, Boston, MA, USA), Dr. Chris Aiken (Vanderbilt University, Nashville, TN, USA), Heinrich Gottlinger (University of Massachusetts, Worchester, MA, USA) for access to HIV-1 molecular clones, and Nadia Ketaf for technical assistance with the Illumina beads arrays technology. We thank Josée Girouard and Angie Massicotte (McGill University Health Centre) for their involvement in patient recruitment and leukapheresis collection. We finally acknowledge the major contribution to this work of all human donors through their gift of leukapheresis.
The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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