- Open Access
The role of antigen presenting cells in the induction of HIV-1 latency in resting CD4+ T-cells
Retrovirology volume 12, Article number: 76 (2015)
Combination antiretroviral therapy (cART) is able to control HIV-1 viral replication, however long-lived latent infection in resting memory CD4+ T-cells persist. The mechanisms for establishment and maintenance of latent infection in resting memory CD4+ T-cells remain unclear. Previously we have shown that HIV-1 infection of resting CD4+ T-cells co-cultured with CD11c+ myeloid dendritic cells (mDC) produced a population of non-proliferating T-cells with latent infection. Here we asked whether different antigen presenting cells (APC), including subpopulations of DC and monocytes, were able to induce post-integration latent infection in resting CD4+ T-cells, and examined potential cell interactions that may be involved using RNA-seq.
mDC (CD1c+), SLAN+ DC and CD14+ monocytes were most efficient in stimulating proliferation of CD4+ T-cells during syngeneic culture and in generating post-integration latent infection in non-proliferating CD4+ T-cells following HIV-1 infection of APC-T cell co-cultures. In comparison, plasmacytoid DC (pDC) and B-cells did not induce latent infection in APC-T-cell co-cultures. We compared the RNA expression profiles of APC subpopulations that could and could not induce latency in non-proliferating CD4+ T-cells. Gene expression analysis, comparing the CD1c+ mDC, SLAN+ DC and CD14+ monocyte subpopulations to pDC identified 53 upregulated genes that encode proteins expressed on the plasma membrane that could signal to CD4+ T-cells via cell–cell interactions (32 genes), immune checkpoints (IC) (5 genes), T-cell activation (9 genes), regulation of apoptosis (5 genes), antigen presentation (1 gene) and through unknown ligands (1 gene).
APC subpopulations from the myeloid lineage, specifically mDC subpopulations and CD14+ monocytes, were able to efficiently induce post-integration HIV-1 latency in non-proliferating CD4+ T-cells in vitro. Inhibition of key pathways involved in mDC-T-cell interactions and HIV-1 latency may provide novel targets to eliminate HIV-1 latency.
Despite the successes of cART in the reduction of morbidity and mortality world wide, treatment is required life long. HIV-1 persists in individuals on cART in resting CD4+ T-cells as latent infection [1–3]. Latency occurs when viral DNA is integrated within the host genome and remains transcriptionally silent. Latent infection of resting CD4+ T-cells therefore represents the major barrier to HIV-1.
It remains unclear how latency is established in resting CD4+ T-cells in vivo. Initial studies in vitro, showed that direct HIV-1 infection of resting CD4+ T-cells isolated from peripheral blood was inefficient and integration rarely occurred due to incomplete reverse transcription, reduced nuclear import of the viral DNA and/or limited integration within the host genome [4–6]. However, in vitro latent infection can occur following the reversion of a HIV-1 infected, activated CD4+ T-cell to a resting state [7–10]. Alternatively, latent infection can also occur following the direct infection of a resting CD4+ T-cell exposed to high viral titers and spinoculation [11, 12], chemokines  or co-culture with other cell types [14, 15].
As professional APCs, DC interact with HIV-1 during initial infection at vaginal and rectal mucosa sites and in blood. Langerhan cells (LC) and dermal (D)DC at mucosa and, bone marrow derived classical or myeloid (m)DC and plasmacytoid (p)DC in blood are able to interact with T-cells, but their role in the establishment and maintenance of HIV-1 latency remain unclear [16–18]. Blood derived mDC subpopulations differ from tissue DC. CD141+ and CD1c+ mDC are both found as resident cells in tissue (lymph node (LN), spleen, lungs), skin and, as more mature cells, circulating through the lymphatics to the LN [19–22]. SLAN+ DC represent a subpopulation of monocytic cells with increased potential to secrete pro-inflammatory cytokines and develop a DC phenotype, however precise residence remains unknown [23, 24]. CD14+ monocytes represent DC and macrophage precursors in blood [Reviewed in 25], and were also tested for their ability to establish latent infection in resting CD4+ T-cells.
We have previously developed an in vitro co-culture model demonstrating that CD11c+ myeloid dendritic cells (mDC) induce post-integration latency in non-proliferating memory CD4+ T-cells. Here we demonstrate that in addition to the mDC subsets (CD1c+, SLAN+ and CD141+), CD14+ monocytes were also able to induce post-integration HIV-1 latency in non-proliferating CD4+ T-cells. In comparison, T-cells co-cultured with pDC and B-cells were inefficient in the induction of latency. Using RNA-seq and Illumina gene expression microarrays, we also identified potential mediators of latent infection expressed by APC that could induce latency in the non-proliferating CD4+ T-cells during APC-T cell interactions.
Monocytes are able to induce latency in resting CD4+ T-cells
We have previously reported that mDC, but not pDC, are able to efficiently induce post-integration latent infection in resting CD4+ T-cells using an in vitro DC-T-cell co-culture model . However, mDC and their subpopulations represent only a small proportion of peripheral blood mononuclear cells (PBMC) compared to monocytes, which represent a precursor to some DC and macrophage subpopulations. Therefore we compared monocytes and mDC isolated from healthy donors for their ability to induce latent infection in resting CD4+ T-cells (Fig. 1). eFluor670 labeled resting CD4+ T-cells were cultured alone, with CD11c+ mDC or bulk monocytes and infected with an R5 using virus that expresses enhanced green fluorescent protein (EGFP). Similar to mDC, monocytes were able to induce productive infection in CD4+ T-cells, as measured by total EGFP expression at day 5 post-infection (Fig. 1b). At day 5 post-infection non-proliferating (eFluor670hiEGFP−) CD4+ T-cells were sorted and cultured with phytohemagglutinin (PHA)-stimulated feeder peripheral blood mononuclear cells (PBMC), where the number of EGFP+ cells was quantified by flow cytometry as a surrogate marker of inducible latent infection. CD14+ monocytes were also able to significantly increase the induction of latent infection in non-proliferating cells (p > 0.05; Fig. 1c).
Isolation of functional APC
Given that we were able to show induction of latency in non-proliferating CD4+ T-cells following co-culture with both bulk monocytes and mDC, we next compared the latency inducing potential of the different monocyte and mDC subpopulations. Monocytes were sorted into CD14+ and CD14loCD16+ (CD16+) cells and mDC were sorted into CD1c+, CD141+ and SLAN+ DC, B-cells and pDC were also isolated by sorting (Fig. 2a). The final purity for all sorted APC subpopulations was >90 %, as determined post-sort by expression of specific known surface markers for the various subpopulations [26–30]. The APC subpopulations were examined using brightfield microscopy after culture (Fig. 2b, c). The mDC and monocyte subpopulations were characterized with the formation of both long and short dendritic processes (Fig. 2b, c) Comparatively, pDC and B-cells had few processes or ruffles (Fig. 2b, c; [28, 29, 31–33]).
APC function was tested in a syngeneic mixed leukocyte reaction (MLR) using the proliferation dye eFluor670 to measure proliferation of resting CD4+ T-cells. In the absence of mitogen stimulation, the relative potency of the various APC to induce T-cell proliferation at a ratio of 1 APC:10 CD4+ T-cells is shown (Fig. 3a). CD1c+ DC were the most potent at activating resting CD4+ T-cells, while pDC and CD141+ DC were least potent. The use of superantigen staphylococcal enterotoxin B (SEB) at low dose in the MLR had a modest effect on enhancing the capacity of APC to induce T-cell proliferation. T-cell proliferation following co-culture and SEB treatment was highest with CD1c+ DC and lowest with B-cells (Fig. 3b), confirming previous observations by others . B-cells had a similar stimulatory capacity with and without superantigen (1.0 and 1.3 % proliferated CD4+ T-cells). Finally, there was a dose response of CD4+ T-cell proliferation with decreasing APC:T-cell ratio (1:10–1000). Together, these data confirm that all the APC subpopulations isolated remained functional in the co-cultures used for infection.
T-cell stimulation by APC subpopulations in HIV-1 infected co-cultures
We then measured T-cell proliferation following co-culture with different APC subpopulations at 3 days following HIV-1 infection. The pattern of APC potency in induction of CD4+ T-cell proliferation in the presence of HIV-1 was similar to uninfected, sygeneic, co-cultures (Fig. 3c), where proliferation of CD4+ T-cells was highest with CD1c+ DC and lowest with pDC. These experiments demonstrate that HIV-1 infection did not independently alter APC or T-cell function with respect to T-cell proliferation.
Several APC subpopulations enhanced productive infection of resting CD4+ T-cells
We tested the ability of APC subpopulations to induce both productive and latent infection in resting CD4+ T-cells when cultured alone or co-cultured with one of the seven sorted APC subpopulations (Fig. 2a). Five days following infection, EGFP expression was quantified by flow cytometry as a measure of productive infection (Fig. 4a). We observed a significant increase in productive infection following HIV-1 infection in all APC co-cultured with T-cells compared to resting CD4+ T-cells cultured alone (p = 0.03 for all APC co-cultures; Fig. 4b).
Different APC subpopulations can effectively induce latent infection in non-proliferating CD4+ T-cells
Five days following infection, non-proliferating (eFluor670hiEGFP−) CD4+ T-cells were sorted from the APC-T-cell co-cultures to quantify latent infection (Fig. 4a). The sorted CD4+ T-cells were directly stimulated with anti-CD3/CD28 and IL-7 (Fig. 4c) in the presence and absence of an integrase inhibitor, L8. EGFP was quantified by flow cytometry as a measure of inducible latent infection. Total latent infection (no L8) was significantly increased in non-proliferating CD4+ T-cells co-cultured with all mDC subpopulations, CD14+ monocytes and B-cells, when compared to CD4+ T-cells cultured alone (p = 0.03; Fig. 4d). In comparison, total latent infection following co-culture with CD14loCD16+ monocytes, that were depleted of SLAN+ DC, was highly variable and not significantly different to T-cells cultured alone. As previously shown, latent infection was not found in T-cells co-cultured with pDC (p = 0.03 compared to mDC co-cultures; Fig. 4d).
We also quantified post-integration latent infection by stimulating T-cells with anti CD3/CD28 and IL-7 stimulation in the presence of L8. (Fig. 4c). The integrase inhibitor, L8, prevented any progression of pre-integration complexes to integration and inhibited secondary rounds of infection. Following infection of CD4+ T-cells co-cultured with each APC subpopulation, post-integration latency followed a similar pattern to that observed for total latency, but at a lower frequency (Fig. 4d, e). Post-integration latency was significantly increased in CD4+ T-cells following co-culture with mDC subpopulations CD1c+ and SLAN+, and CD14+ monocytes (p = 0.03, 0.02 and 0.01, respectively; Fig. 4e). Post-integration latency induced by CD141+ DC was elevated, similar to what was induced by other mDC subsets, but this did not reach statistical significance. In comparison, HIV-1 infection of T-cells co-cultured with SLAN DC depleted CD14− CD16+ monocytes, B-cells and pDC was similar to infection of CD4+ T cells alone. Together these data show that only CD1c+mDC, SLAN+ DC and CD14+ monocytes were able to establish post-integration latent infection in non-proliferating CD4+ T-cells, while B-cells and CD141+ mDC were able to establish pre-integration latent infection. CD14loCD16hi SLAN− monocytes, like pDC, were unable to establish either pre or post-integration latency.
Next, we looked for a correlation between productive infection and post-integration latency following infection of T-cells co-cultured with different APC (Fig. 4f). Overall, we found a weak correlation between productive and latent infection (Spearman’s r = 0.12; p = 0.02), which supports our previous findings . However, the induction of productive infection does not inevitably lead to post-integration latency in resting CD4+ T-cells, as observed following co-culture with CD14loCD16hi monocytes, B-cells and pDC. We conclude that cells able to establish both productive and latent infection likely share common functional characteristics, which favour the establishment and maintenance of latent infection.
Differential gene expression of cell-surface expressed molecules on APC
We next used RNA-seq to compare gene expression for genes involved in T-cell interactions with APC subpopulations that induce latency (CD1c+ DC, SLAN+ DC and CD14+ monocytes) compared to APC that could not (pDC). Due to difficulties isolating APC from T-cell co-cultures and HIV-1 infection, gene expression analysis was performed on freshly isolated APC subpopulations [34–36]. Component analysis showed clustering of the SLAN DC and CD14 monocytes and separate clusters of pDC and mDC (Additional file 1: Figure S1). Given that we have previously shown that cell contact is important in mDC-induced latency , we specifically selected genes encoding proteins that mediate mDC-T-cell interactions, including those in cell membrane compartments at the cell surface, and in intracellular vesicles such as endosomes and compartments giving rise to exosomes.
In APC subpopulations that induced post-integration HIV-1 latency compared to APC that didn’t induce latency, we found 754 differentially upregulated genes (fold change ≥2, p-value <0.01; Fig. 5a). Analysis for expression in cellular compartment (GeneCodis; http://genecodis.cnb.csic.es), identified 285 known genes expressed in: membrane, plasma membrane, integral to membrane, integral to plasma membrane and cell junction ([37–39]; Fig. 5a). Of these, 53 protein-encoding genes that could establish cell contact with CD4+ T-cells and potentially induce T-cell signaling were selected (Table 1, Additional file 2: Table S1). Functionally these genes included; cellular adhesion (32 genes), antigen presentation (1 gene), T-cell activation (9 genes), immune checkpoints (5 genes), regulation of apoptosis (5 gene), and an unknown protein (1 genes). We further analysed the role of each gene in HIV-1 infection of DC and CD4+ T-cells using a PubMed search for the interactions between DC and T-cells, and potential roles in the establishment of HIV-1 latency (Additional file 2: Table S1).
We performed the same comparisons between selected APC subpopulations using our previously published microarray data  and found 27 genes that could potentially induce T-cell signalling (Additional file 4: Figure S2; Additional file 5: Table S2; ). Five of these genes were common between microarray and RNAseq analyses, seven genes shared protein family and thirteen genes fell outside of significance (cut off of p < 0.01), often with inconsistent replicates (n = 3). The common genes included C-type lectin domain family 7 member A (CLEC-7A), endoglin, intracellular adhesion molecule 3 (ICAM-3), sialic acid-binding immunoglobulin-type lectins (SIGLEC)-10 and CD1d. CD1d is involved in lipid antigen presentation to T-cells, while the other 4 surface expressed proteins are involved in cellular adhesion . The common protein families included the SIGLEC family, CLEC family, leukocyte associated immunoglobulin like receptor (LILRA) family, G-Protein coupled receptor (GCPR) family and the tumor necrosis factor (TNF) receptor superfamily.
Latently infected cells are infrequent in HIV-1-infected patients on cART, and therefore robust in vitro models are needed to better understand the establishment and maintenance of latent infection. We have now shown that multiple APCs, in addition to mDC, are able to induce HIV-1 latency in non-proliferating CD4+ T cells . Here, we have shown that the myeloid lineage cells capable of producing latent T-cell infection include subpopulations of blood derived mDC; CD1c+, SLAN+ DC and CD14+ monocytes, and confirmed that pDC are distinct in not generating latent infection. We have used RNA-seq analysis to define genes differentially expressed between APC subpopulations that could (CD1c+, SLAN+, CD14+ monocytes) and could not induce latent infection (pDC), and identified genes mediating cell adhesion, T-cell activation, immune checkpoints (IC) and regulation of apoptosis as important pathways differentially upregulated in the APC that are able to induce latent infection.
Our results show that multiple blood derived mDC subsets can induce latent infection in non-proliferating CD4+ T-cells, suggesting that this observation may extend to other DC and myeloid lineage cells, such as LC and dermal DC (DDC) though they may have different ontogeny [42–44]. It is likely that mDC and monocyte lineage cells in lymphoid tissue, skin, mucosal surfaces, gastrointestinal tract (GIT) and sites of inflammation could allow seeding of CD4+ T-cell viral reservoirs early following infection or during ART in tissue sites were cART penetration may not be optimal .
We observed a trend between the ability of the different APCs to induce latent infection and efficient T-cell proliferation. This suggests that there may be a common mechanism for the induction of T-cell proliferation and induction of latent infection, even in non-proliferating cells, perhaps through a bystander mechanism. Efficient T-cell proliferation is favoured by the formation of an immunological synapse [46, 47] with cellular proximity , major-histocompatibility complex (MHC)-T-cell receptor (TcR) interaction and co-stimulation [49–52]. ICAM-1 interaction with leukocyte function-associated antigen (LFA)-1 can facilitate induction of latent infection in the DC-T-cell model , while in other models of in vitro latency CD2 expression, a molecule that binds to LFA-3, was increased on latently infected cells . A large portion (60 %) of genes identified in the gene expression analysis mediates cellular proximity and cell adhesion. Taken together these data suggest that cell adhesion/contact is important in the induction of latency. However, identification of a single specific adhesion molecule critical for the induction of latent infection is likely limited by functional redundancy in mediators of APC-T-cells interactions.
Compared to the other DCs, the pDC were least efficient for T-cell proliferation and induced significantly less productive and latent infection compared to mDC. The differences between mDC and pDC in induction of productive infection [54, 55] and suppression of virus production has been observed previously . We have also previously shown that pDC were unable to induce HIV-1 latency, and that there was a more substantial suppressive effect on the establishment of latency compared to productive infection. We and others have shown multiple differences between mDC and pDC that may reduce the ability of pDC to establish close interactions with T-cells [26, 40, 56, 57], which in combination with increased type-I IFN secretion from pDC may inhibit the capacity of pDC to establish latency in T-cells.
The ability of B-cells to induce latent infection in non-proliferating CD4+ T-cells was also tested in this study as B-cells express MHC-II, circulate through LN, and have been reported to transfer HIV-1 infection to T-cells . Induction of latency occurred only at low level and was only in the form of pre-integration latency suggesting that B-cells lack factors that facilitate efficient induction of post-integration latency.
Comparison of APC subpopulations that could and could not induce latent infection in non-proliferating CD4+ T-cells identified several functions that may be important in the establishment of latency, including cell adhesion, IC, T-cell co-stimulation, antigen presentation and regulation of apoptosis. The IC, programmed death receptor (PD)-1, is proposed to play a role in the establishment and/or maintenance of HIV-1 latency [59, 60]. Engagement of ICs, led to reduced T-cell activation by inhibition of signaling cascades, as well as physical inhibition of the formation of lipid rafts and cellular interactions . In this study, we observed an up-regulation of the ICs; CD101, T-cell immunoglobulin mucin-3 (Tim-3, HAVR2), leukocyte immunoglobulin-like receptor member 6 (LILR6) and CD52, on latency inducing APC subpopulations when compared to pDC. IC expression may be important for the establishment of HIV-1 latency in this model, but further work is required to confirm this.
Additionally, we identified differential expression of the SIGLEC family of proteins between APC subpopulations that could and could not induce latent infection. We specifically found SIGLEC 5, 7, 9, 10 and 14 to be upregulated on latency inducing APCs. From this family, SIGLEC 3, 5-11 have all been implicated in the inhibition of T-cell activation [62–64]. SIGLEC 5 has been shown to inhibit T-cell activation in chimpanzees, where blockade of SIGLEC 5 led to increased T-cell activation, and transfection of SIGLEC 5 into SIGLEC negative cells reduced T-cell activation [64–67]. SIGLEC 10 is hypothesized to have similar function in inhibition of T-cell activation [68, 69]. Together these data suggest that SIGLEC 5 or 10 binding to its ligand on the CD4+ T-cell may reduce T-cell activation, reduce productive infection and potentially promote latent infection. This is a novel association but further work will be required to explore any direct effects of SIGLEC proteins and the establishment of latency.
This study has established that multiple myeloid lineage APC subpopulations can facilitate latent infection in resting CD4+ T-cells. Particularly important is the observation that CD14+ monocytes can induce latent infection in resting CD4+ T-cells. The use of CD14+ monocytes will greatly enhance the utility of this model. In addition, through a comparative analysis of APC populations, we have identified new pathways that may potentially be involved in the establishment and/or maintenance of HIV-1 latency. Inhibition of key pathways involved in mDC-T-cell interactions and HIV-1 latency may provide novel targets to eliminate HIV-1 latency.
Isolation and preparation of resting CD4+ T-cells and B-cells
PBMC were isolated by Ficoll-Paque density gradient centrifugation (GE Healthcare, Chalfont St. Giles, UK) from healthy buffy coats obtained from the Australian Red Cross. PBMC were further separated into three populations by counter-current elutriation using Beckman J-6M/E centrifuge equipped with a JE 5.0 rotor (Beckman Coulter, Pasedena, CA, USA; ). The three fractions were isolated at rates of 12 (small lymphocytes), 16 (large lymphocytes) and 20 (DC/Monocytes fractions) ml/min. Resting CD4+ T-cells, negative for the activation markers CD69 and HLA-DR, were sorted from the “small lymphocyte” fraction, as previously described , with a purity always >98 %. B-cells were isolated with a purity of ≥90 % from the “small and large lymphocyte” fractions using positive magnetic bead selection on an autoMACS (Miltenyi) using anti-CD19+ hybridoma (clone FMC63) and anti-IgG microbeads (Miltenyi, Bergisch Gladbach, Germany).
Isolation of DC and monocytes
The remaining elutriated fraction, containing the larger cells (20 ml/min), was used to isolate DC and monocytes. The large cell fraction was first stained with antibodies specific for the DC subsets, which included CD1c-APC (Miltenyi), CD141-VioBlue (Miltenyi), CD123-PE (BD BioSciences, Franklin Lakes, NJ, USA) and SLAN-FITC (Miltenyi), and labeled with anti-IgG beads (Miltenyi). DC were then isolated using an AutoMACS (Miltenyi) into positive and negative fractions. The positive fraction (DC enriched) was further sorted into four DC subsets: CD1c+ mDC, SLAN+ DC, CD141+ mDC and CD123+ pDC, using a FACSAria (BD BioSciences). The negative fraction (DC depleted/mono) was stained with anti-CD14-FITC and anti-CD16-PE (BD Biosciences) antibodies, labeled with IgG beads (Miltenyi) and a positive selection performed using an AutoMACS (Miltenyi) to obtain a bulk monocyte population. These cells were further sorted to obtain the CD14+CD16− (CD14+) and CD16+CD14lo (CD16+) monocyte subsets using a FACSAria. Cell populations with a purity ≥90 % were used, as determined by flow cytometry (LSR II or FACSAria; BD Bioscience). In the event of low yields of some APC subpopulation, the experiment was continued without that population. In these experiments the missing data was omitted from the plots and therefore not every donor has data shown for all conditions tested.
Imaging antigen presenting cell subpopulations
After isolation, each antigen presenting cell (APC) subpopulation was cultured in RF10 media (RPMI 1640; Life Technologies, Carlsbad, CA, USA), supplemented with 10 % fetal bovine serum (FBS; Interpath, Heidelberg, Australia), Penicillin–Streptomycin-Glutamine (PSG; Life Technologies) for 1–2 h at 37 °C in glass-bottom imaging plates (μ-slide, ibidi, Martinsried, Germany). Ten representative images were captured on a CCD camera through a 10 × 0.3 NA lens on a Olympus IX51 microscope and annotated with ImageJ software.
Syngeneic mixed leukocyte reactions
Resting CD4+ T-cells were labeled with eFluor670 and co-cultured with decreasing concentrations of each APC subpopulation; log 1 (10:1), 2 (100:1) and 3 (1000:1), in the absence (syngeneic) or presence of superantigen SEB (10 ng/mL; Sigma). At day 5, cells were harvested and labeled with antibody against CD3 (V450, BD Bioscience). Cells were analysed by flow for T-cells that proliferated and therefore expressed low levels of eFluor670.
Viral plasmids, virus preparation and infection
In all experiments, we used HIV-1 NL4.3 plasmid backbone with an AD8 envelope and EGFP inserted in the nef open reading frame at position 75 (NL(AD8)ΔnefEGFP) , kindly provided by Damian Purcell, University of Melbourne (Melbourne, Australia). Viral stocks were generated by FuGene (Promega, Madison, WI, USA) transfection of 293T cells as previously described . Cells were infected at an MOI of 0.5, as determined by limiting dilution in PHA-stimulated PBMC using the Reed and Muench method .
In vitro latency model
Resting CD4+ T-cells were labeled with the proliferation dye eFluor670 and cultured alone or with one of seven sorted syngeneic APC subpopulations at a ratio of 10:1 for 24 h in IL-2 (2U/mL, Roche Diagnostics, Basel, Switzerland) supplemented RF10 media. APC included monocyte subpopulations (CD14+CD16− and CD14loCD16+), DC subpopulations (pDC, CD1c+, CD141+ and SLAN+), and B-cells. Co-cultures were then infected with NL(AD8)ΔnefEGFP for 2 h, after which time excess virus was washed away and cells were cultured for an additional 5 days. In order to compare APC stimulatory capacity between APC-T-cell co-cultures, at day 3 post-infection, cells were stained with anti-CD3-V450 (BD Biosciences) to differentiate between T-cell and APC, and the proportion of proliferated (eFluor670lo) CD4+ T-cells were determined. Day 3 was used because this is when productive infection reached is maximum and remained high until day 5 (unpublished data). Additional APC-T-cell ratio’s were not used due to low APC yields. At day 5 post-infection, productive infection was determined by EGFP expression and non-proliferating, non-productively infected (eFluor670hi EGFP−) CD4+ T-cells were sorted using a FACSAria.
Reactivation of latency from resting T-cells
Latent infection in the sorted, non-proliferating CD4+ T-cells (eFluor670hiEGFP−) was determined by comparison of stimulated with un-stimulated T-cells sorted from APC-T-cell co-cultures (control). 1x105 sorted CD4+ T-cells were stimulated with immobilized anti-CD3 (7 μg/ml; Beckman Coulter), in RF10 media supplemented with CD28 (5 μg/mL; BD Biosciences), IL-7 (50 ng/mL; Sigma, St Louis, MO, USA), IL-2 (5U/mL; Roche), with (post-integrated latency) or without (total latency: pre- and post-integrated latency) integrase inhibitor L8 (1 μM; Merck, White House Station, NJ, USA). The concentration of L8 was determined previously by titration of L8 in phytohaemagglutinin (PHA; 10 μg/mL) activated PBMC infected with R5-EGFP virus at an MOI of 0.5, same concentration usedin co-cultures, and showed productive infection was completely blocked at 1 μM. This concentration used for all subsequent experiments. Cells were harvested after 72 h of stimulation and EGFP expression was quantified on the FacsCalibur (BD BioSciences).
In some experiments PHA (10ug/mL) and IL-2 (10 U/mL) stimulated feeder PBMC were used to activate T-cells as a measure of inducing virus replication form latency, as described previously .
Cell preparation for next generation sequencing and generation of gene lists
APC from 3 donors were sorted as described above to obtain mDC subpopulations CD1c+, SLAN+, CD14+ monocytes and pDC which were immediately stored in RLT buffer (Qiagen, Limburg, The Netherlands). Total RNA was isolated from low cell number samples (<500,000 cells) using Qiagen ALL prep micro kits (Qiagen), while RNA from samples with >500,000 cells were isolated using Qiagen RNA easy mini kits (Qiagen), according to the manufacturer’s instructions. Total RNA content varied from 270.0 to 1879.7 ng.
The Australian Gene Research Facility Ltd (AGRF, Melbourne, Australia) prepared cDNA libraries, which were multiplexed on the Illumina HiSeq 2000 (Illumina, San Diago, CA, USA). For gene expression analysis, single reads were selected with 20 million reads of 50 bp read size gathered. The RNA-seq reads were aligned to the human reference hg19 using the TopHat2 aligner [72, 73] and quantified using htseq-count . Mapping rates for RNA seq are shown (Additional file 6: Table S3). Differential expression was calculated using Voom/Limma  and visualization performed using Degust  (http://victorian-bioinformatics-consortium.github.io/degust/) and Vennt  (http://drpowell.github.io/vennt/). Genes with fewer than 10 reads across every sample were removed from the analysis.
APC subsets were categorized as latency-inducing and latency-non-inducing subsets. Using a fold change of greater than 2 and false discovery rate (FDR) of 0.01, we identified 754 genes that were significantly upregulated in latency inducing populations (CD1c+ mDC, CD14+ monocytes, SLAN+ DC) compared to latency non-inducing populations (pDC; Fig. 4). As direct cell contact is required for the establishment of mDC induced latency, only protein encoding genes from APC implicated in cell contact were selected using the GeneCodis database (http://genecodis.cnb.csic.es). We identified 285 genes from the initial list that encode for proteins known to be expressed on the plasma-membrane, membrane, integral to the plasma-membrane/membrane and cell junctions [37–39]. Finally, we manually curated this list to identify 53 genes known to be involved in T-cell signaling (Table 1; Additional file 1: Table S1). RNA-seq data is available through Gene Omnibus (GEO), serial number GSE70106.
As a comparison, we performed a similar analysis using our previously published microarray data using the same APC subpopulations . Microarray data was kindly provided by Andrew Harman, Westmead Millennium Institute for Medical Research, Sydney University, Sydney . The RNA extraction, labeling, hybridization, data processing, and analysis procedures used by Harman et al. are described previously for the cDNA gene array  and Illumina arrays . Hybridization and data processing was performed by AGRF using sentrix human 6 v2 expression chips (Illumina).
The use of blood samples from normal donors for this study was approved by the Alfred Hospital (HREC 156/11) and Monash University (CF11/1888) Human Research and Ethics Committees. Donors were recruited by the Red Cross Blood Transfusion Service as normal blood donors and all provided written informed consent for the use of their blood products for the research.
Differences between experimental conditions were analyzed using Wilcoxon matched pairs signed rank test (n ≥ 5) or paired student T-test (n < 5) on GraphPad Prism (Version 6). P-values ≤0.05 were considered significant. Differentially expressed RNA-seq and microarray genes were found to be significant using ANOVA .
antigen presenting cell
combination antiretroviral therapy
C-type lectin domain family 7 member A
dermal dendritic cell
emerald-green fluorescent protein
fetal bovine serum
false discovery rate
G-coupled protein receptor
Hepatitis A virus cellular receptor 2
human immunodeficiency virus
intracellular adhesion molecule 3
immune checkpoint blocker
leukocyte function associated antigen
leukocyte-associated immunoglobulin like receptor
myeloid dendritic cell
major histocompatibility complex
mixed leukocyte reaction
peripheral blood mononuclear cells
programmed death receptor-1
plasmacytoid dendritic cell
staphylococcal enterotoxin B
sialic acid-binding immunoglobulin-type lectins
T-cell immunoglobulin mucin-3
tumor necrosis factor
Chun TW, Finzi D, Margolick J, Chadwick K, Schwartz D, Siliciano RF. In vivo fate of HIV-1-infected T cells: quantitative analysis of the transition to stable latency. Nat Med. 1995;1:1284–90.
Finzi D, Hermankova M, Pierson T, Carruth LM, Buck C, Chaisson RE, Quinn TC, Chadwick K, Margolick J, Brookmeyer R, Gallant J, Markowitz M, Ho DD, Richman DD, Siliciano RF. Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy. Science. 1997;278:1295–300.
Hermankova M, Siliciano JD, Zhou Y, Monie D, Chadwick K, Margolick JB, Quinn TC, Siliciano RF. Analysis of human immunodeficiency virus type 1 gene expression in latently infected resting CD4+ T lymphocytes in vivo. J Virol. 2003;77:7383–92.
Stevenson M, Stanwick TL, Dempsey MP, Lamonica CA. HIV-1 replication is controlled at the level of T cell activation and proviral integration. EMBO J. 1990;9:1551–60.
Zack JA, Arrigo SJ, Weitsman SR, Go AS, Haislip A, Chen IS. HIV-1 entry into quiescent primary lymphocytes: molecular analysis reveals a labile, latent viral structure. Cell. 1990;61:213–22.
Zack JA, Haislip AM, Krogstad P, Chen IS. Incompletely reverse-transcribed human immunodeficiency virus type 1 genomes in quiescent cells can function as intermediates in the retroviral life cycle. J Virol. 1992;66:1717–25.
Bosque A, Planelles V. Induction of HIV-1 latency and reactivation in primary memory CD4+ T cells. Blood. 2009;113:58–65.
Marini A, Harper JM, Romerio F. An in vitro system to model the establishment and reactivation of HIV-1 latency. J Immunol. 2008;181:7713–20.
Sahu GK, Lee K, Ji J, Braciale V, Baron S, Cloyd MW. A novel in vitro system to generate and study latently HIV-infected long-lived normal CD4+ T-lymphocytes. Virology. 2006;355:127–37.
Yang H-C, Xing S, Shan L, O’Connell K, Dinoso J, Shen A, Zhou Y, Shrum CK, Han Y, Liu JO, Zhang H, Margolick JB, Siliciano RF. Small-molecule screening using a human primary cell model of HIV latency identifies compounds that reverse latency without cellular activation. J Clin Invest. 2009;119:3473–86.
Pace MJ, Graf EH, Agosto LM, Mexas AM, Male F, Brady T, Bushman FD, O’Doherty U. Directly infected resting CD4+ T cells can produce HIV gag without spreading infection in a model of HIV latency. PLoS Pathog. 2012;8:e1002818–33.
Swiggard WJ, Baytop C, Yu JJ, Dai J, Li C, Schretzenmair R, Theodosopoulos T, O’Doherty U. Human immunodeficiency virus type 1 can establish latent infection in resting CD4+ T cells in the absence of activating stimuli. J Virol. 2005;79:14179–88.
Saleh S, Solomon A, Wightman F, Xhilaga M, Cameron PU, Lewin SR. CCR7 ligands CCL19 and CCL21 increase permissiveness of resting memory CD4+ T cells to HIV-1 infection: a novel model of HIV-1 latency. Blood. 2007;110:4161–4.
Evans VA, Kumar N, Filali A, Procopio FA, Yegorov O, Goulet J-P, Saleh S, Haddad EK, da Fonseca Pereira C, Ellenberg PC, Sekaly RP, Cameron PU, Lewin SR. Myeloid dendritic cells induce HIV-1 latency in non-proliferating CD4+ T Cells. PLoS Pathog. 2013;9:e1003799–813.
Shen A, Baker JJ, Scott GL, Davis YP, Ho Y-Y, Siliciano RF. Endothelial cell stimulation overcomes restriction and promotes productive and latent HIV-1 infection of resting CD4+ T Cells. J Virol. 2013;87:9768–79.
Hladik F, Sakchalathorn P, Ballweber L, Lentz G, Fialkow M, Eschenbach D, McElrath MJ. Initial events in establishing vaginal entry and infection by human immunodeficiency virus type-1. Immunity. 2007;26:257–70.
Hussain LA, Lehner T. Comparative investigation of Langerhans’ cells and potential receptors for HIV in oral, genitourinary and rectal epithelia. Immunology. 1995;85:475–84.
Zaitseva M, Blauvelt A, Lee S, Lapham CK, Kiaus-Kovrun V, Mostowski H, Manischewitz J, Golding H. Expression and function of CCR5 and CXCR4 on human Langerhans cells and macrophages: implications for HIV primary infection. Nat Med. 1997;3:1369–75.
Cerovic V, Houston SA, Scott CL, Aumeunier A, Yrlid U, Mowat AM, Milling SWF. Intestinal CD103(-) dendritic cells migrate in lymph and prime effector T cells. Mucosal Immunol. 2012;6:104–113
Chu C-C, Ali N, Karagiannis P, Di Meglio P, Skowera A, Napolitano L, Barinaga G, Grys K, Sharif-Paghaleh E, Karagiannis SN, Peakman M, Lombardi G, Nestle FO. Resident CD141 (BDCA3) + dendritic cells in human skin produce IL-10 and induce regulatory T cells that suppress skin inflammation. J Exp Med. 2012;209:935–45.
Ginhoux F, Liu K, Helft J, Bogunovic M, Greter M, Hashimoto D, Price J, Yin N, Bromberg J, Lira SA, Stanley ER, Nussenzweig M, Merad M. The origin and development of nonlymphoid tissue CD103 + DCs. J Exp Med. 2009;206:3115–30.
Yu CI, Becker C, Wang Y, Marches F, Helft J, Leboeuf M, Anguiano E, Pourpe S, Goller K, Pascual V, Banchereau J, Merad M, Palucka K. Human CD1c(+) dendritic cells drive the Differentiation of CD103(+) CD8(+) mucosal effector T cells via the cytokine TGF-β. Immunity. 2013;38:818–30.
Hänsel A, Günther C, Baran W, Bidier M, Lorenz HM, Schmitz M, Bachmann M, Döbel T, Enk AH, Schäkel K: Human 6-sulfo LacNAc (slan) dendritic cells have molecular and functional features of an important pro-inflammatory cell type in lupus erythematosus. J Autoimmun. 2012.
Qu C, Edwards EW, Tacke F, Angeli V, Llodrá J, Sanchez-Schmitz G, Garin A, Haque NS, Peters W, van Rooijen N, Sanchez-Torres C, Bromberg J, Charo IF, Jung S, Lira SA, Randolph GJ. Role of CCR8 and other chemokine pathways in the migration of monocyte-derived dendritic cells to lymph nodes. J Exp Med. 2004;200:1231–41.
Ginhoux F, Jung S. Monocytes and macrophages: developmental pathways and tissue homeostasis. Nat Rev Immunol. 2014;14:392–404.
MacDonald KPA, Munster DJ, Clark GJ, Dzionek A, Schmitz J, Hart DNJ. Characterization of human blood dendritic cell subsets. Blood. 2002;100:4512–20.
Nagasawa T. Microenvironmental niches in the bone marrow required for B-cell development. Nat Rev Immunol. 2006;6:107–16.
Rissoan M-C, Duhen T, Bridon J-M, Bendriss-Vermare N, Péronne C, Vis B de S, Brière F, Bates EEM. Subtractive hybridization reveals the expression of immunoglobulinlike transcript 7, Eph-B1, granzyme B, and 3 novel transcripts in human plasmacytoid dendritic cells. Blood. 2002;100:3295–303.
Schäkel K, Mayer E, Federle C, Schmitz M, Riethmüller G, Rieber EP. A novel dendritic cell population in human blood: one-step immunomagnetic isolation by a specific mAb (M-DC8) and in vitro priming of cytotoxic T lymphocytes. Eur J Immunol. 1998;28:4084–93.
Ziegler-Heitbrock L, Ancuta P, Crowe S, Dalod M, Grau V, Hart DN, Leenen PJM, Liu Y-J, MacPherson G, Randolph GJ, Scherberich J, Schmitz J, Shortman K, Sozzani S, Strobl H, Zembala M, Austyn JM, Lutz MB. Nomenclature of monocytes and dendritic cells in. Blood. 2010;116:e74–80.
Geissmann F, Jung S, Littman DR. Blood monocytes consist of two principal subsets with distinct migratory properties. Immunity. 2003;19:71–82.
O’Doherty U, Steinman RM, Peng M, Cameron PU, Gezelter S, Kopeloff I, Swiggard WJ, Pope M, Bhardwaj N. Dendritic cells freshly isolated from human blood express CD4 and mature into typical immunostimulatory dendritic cells after culture in monocyte-conditioned medium. J Exp Med. 1993;178:1067–76.
Steinman RM, Cohn ZA. Identification of a novel cell type in peripheral lymphoid organs of mice. I. Morphology, quantitation, tissue distribution. J Exp Med. 1973;137:1142–62.
Ahn JH, Lee Y, Jeon C, Lee S-J, Lee B-H, Choi KD, Bae Y-S. Identification of the genes differentially expressed in human dendritic cell subsets by cDNA subtraction and microarray analysis. Blood. 2002;100:1742–54.
Huang Q, Liu D, Majewski P, Schulte LC, Korn JM, Young RA, Lander ES, Hacohen N. The plasticity of dendritic cell responses to pathogens and their components. Science. 2001;294:870–5.
Verdijk P, van Veelen PA, de Ru AH, Hensbergen PJ, Mizuno K, Koerten HK, Koning F, Tensen CP, Mommaas AM. Morphological changes during dendritic cell maturation correlate with cofilin activation and translocation to the cell membrane. Eur J Immunol. 2004;34:156–64.
Carmona-Saez P, Chagoyen M, Tirado F, Carazo JM, Pascual-Montano A. GENECODIS: a web-based tool for finding significant concurrent annotations in gene lists. Genome Biol. 2007;8:R3.
Nogales-Cadenas R, Carmona-Saez P, Vazquez M, Vicente C, Yang X, Tirado F, Carazo JM, Pascual-Montano A. GeneCodis: interpreting gene lists through enrichment analysis and integration of diverse biological information. Nucleic Acids Res. 2009;37(Web Server issue):W317–22.
Tabas-Madrid D, Nogales-Cadenas R, Pascual-Montano A. GeneCodis3: a non-redundant and modular enrichment analysis tool for functional genomics. Nucleic Acids Res. 2012;4(Web Server issue):W478–83.
Harman AN, Bye CR, Nasr N, Sandgren KJ, Kim M, Mercier SK, Botting RA, Lewin SR, Cunningham AL, Cameron PU. Identification of lineage relationships and novel markers of blood and skin human dendritic cells. J Immunol Baltim Md. 1950;2013(190):66–79.
Kelly H, Mandraju R, Coelho-dos-Reis JGA, Tsuji M. Effects of HIV-1-induced CD1c and CD1d modulation and endogenous lipid presentation on CD1c-restricted T-cell activation. BMC Immunol. 2013;14:1–10.
Haniffa M, Shin A, Bigley V, McGovern N, Teo P, See P, Wasan PS, Wang X-N, Malinarich F, Malleret B, Larbi A, Tan P, Zhao H, Poidinger M, Pagan S, Cookson S, Dickinson R, Dimmick I, Jarrett RF, Renia L, Tam J, Song C, Connolly J, Chan JKY, Gehring A, Bertoletti A, Collin M, Ginhoux F. Human tissues contain CD141hi cross-presenting dendritic cells with functional homology to mouse CD103+ nonlymphoid dendritic cells. Immunity. 2012;37:60–73.
McGovern N, Schlitzer A, Gunawan M, Jardine L, Shin A, Poyner E, Green K, Dickinson R, Wang X-N, Low D, Best K, Covins S, Milne P, Pagan S, Aljefri K, Windebank M, Saavedra DM, Larbi A, Wasan PS, Duan K, Poidinger M, Bigley V, Ginhoux F, Collin M, Haniffa M. Human dermal CD14+ cells are a transient population of monocyte-derived macrophages. Immunity. 2014;41:465–77.
Satpathy AT, Wu X, Albring JC, Murphy KM. Re(de)fining the dendritic cell lineage. Nat Immunol. 2012;13:1145–54.
Trezza CR, Kashuba ADM: Pharmacokinetics of antiretrovirals in Genital Secretions and Anatomic Sites of HIV Transmission: Implications for HIV Prevention. Clin Pharmacokinet. 2014.
Revy P, Sospedra M, Barbour B, Trautmann A. Functional antigen-independent synapses formed between T cells and dendritic cells. Nat Immunol. 2001;2:925–31.
Hochweller K, Wabnitz GH, Samstag Y, Suffner J, Hämmerling GJ, Garbi N. Dendritic cells control T cell tonic signaling required for responsiveness to foreign antigen. Proc Natl Acad Sci. 2010;107:5931–6.
Jolly C, Mitar I, Sattentau QJ. Adhesion molecule interactions facilitate human immunodeficiency virus type 1-induced virological synapse formation between T cells. J Virol. 2007;81:13916–21.
Seya T, Matsumoto M, Tsuji S, Begum NA, Nomura M, Azuma I, Hayashi A, Toyoshima K. Two receptor theory in innate immune activation: studies on the receptors for bacillus Culmet Guillen-cell wall skeleton. Arch Immunol Ther Exp (Warsz). 2001;49(Suppl 1):S13–21.
Groot F, van Capel TMM, Schuitemaker J, Berkhout B, de Jong EC. Differential susceptibility of naïve, central memory and effector memory T cells to dendritic cell-mediated HIV-1 transmission. Retrovirology. 2006;3:52.
Sabado RL, Babcock E, Kavanagh DG, Tjomsland V, Walker BD, Lifson JD, Bhardwaj N, Larsson M. Pathways utilized by dendritic cells for binding, uptake, processing and presentation of antigens derived from HIV-1. Eur J Immunol. 2007;37:1752–63.
Sanchez-Lockhart M, Rojas AV, Fettis MM, Bauserman R, Higa TR, Miao H, Waugh RE, Miller J. T cell receptor signaling can directly enhance the avidity of CD28 ligand binding. PLoS One. 2014;9:e89263.
Iglesias-Ussel M, Vandergeeten C, Marchionni L, Chomont N, Romerio F. High levels of CD2 expression identify HIV-1 latently infected resting memory CD4+ T cells in virally suppressed subjects. J Virol. 2013;87:9148–58.
Cella M, Jarrossay D, Facchetti F, Alebardi O, Nakajima H, Lanzavecchia A, Colonna M. Plasmacytoid monocytes migrate to inflamed lymph nodes and produce large amounts of type I interferon. Nat Med. 1999;5:919–23.
Groot F, van Capel TM, Kapsenberg ML, Berkhout B, de Jong EC. Opposing roles of blood myeloid and plasmacytoid dendritic cells in HIV-1 infection of T cells: transmission facilitation versus replication inhibition. Blood. 2006;108:1957–64.
Dzionek A, Fuchs A, Schmidt P, Cremer S, Zysk M, Miltenyi S, Buck DW, Schmitz J. BDCA-2, BDCA-3, and BDCA-4: three markers for distinct subsets of dendritic cells in human peripheral blood. J Immunol Baltim Md. 1950;2000(165):6037–46.
O’Doherty U, Peng M, Gezelter S, Swiggard WJ, Betjes M, Bhardwaj N, Steinman RM. Human blood contains two subsets of dendritic cells, one immunologically mature and the other immature. Immunology. 1994;82:487–93.
Rappocciolo G, Piazza P, Fuller CL, Reinhart TA, Watkins SC, Rowe DT, Jais M, Gupta P, Rinaldo CR. DC-SIGN on B lymphocytes is required for transmission of HIV-1 to T lymphocytes. PLoS Pathog. 2006;2:e70.
Porichis F, Kaufmann DE. Role of PD-1 in HIV pathogenesis and as target for therapy. Curr HIV/AIDS Rep. 2012;9:81–90.
Chomont N, El-Far M, Ancuta P, Trautmann L, Procopio FA, Yassine-Diab B, Boucher G, Boulassel MR, Ghattas G, Brenchley JM, Schacker TW, Hill BJ, Douek DC, Routy JP, Haddad EK, Sekaly RP. HIV reservoir size and persistence are driven by T cell survival and homeostatic proliferation. Nat Med. 2009;15:893–900.
Parry RV, Chemnitz JM, Frauwirth KA, Lanfranco AR, Braunstein I, Kobayashi SV, Linsley PS, Thompson CB, Riley JL. CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Mol Cell Biol. 2005;25:9543–53.
Whitney G, Wang S, Chang H, Cheng KY, Lu P, Zhou XD, Yang WP, McKinnon M, Longphre M. A new siglec family member, siglec-10, is expressed in cells of the immune system and has signaling properties similar to CD33. Eur J Biochem FEBS. 2001;268:6083–96.
Avril T, Floyd H, Lopez F, Vivier E, Crocker PR. The membrane-proximal immunoreceptor tyrosine-based inhibitory motif is critical for the inhibitory signaling mediated by Siglecs-7 and -9, CD33-related Siglecs expressed on human monocytes and NK cells. J Immunol Baltim Md. 1950;2004(173):6841–9.
Ikehara Y, Ikehara SK, Paulson JC. Negative regulation of T cell receptor signaling by Siglec-7 (p70/AIRM) and Siglec-9. J Biol Chem. 2004;279:43117–25.
Bibollet-Ruche F, McKinney BA, Duverger A, Wagner FH, Ansari AA, Kutsch O. The quality of chimpanzee T-cell activation and simian immunodeficiency virus/human immunodeficiency virus susceptibility achieved via antibody-mediated T-cell receptor/CD3 stimulation is a function of the anti-CD3 antibody isotype. J Virol. 2008;82:10271–8.
Nguyen DH, Hurtado-Ziola N, Gagneux P, Varki A. Loss of Siglec expression on T lymphocytes during human evolution. Proc Natl Acad Sci. 2006;103:7765–70.
Soto PC, Karris MY, Spina CA, Richman DD, Varki A. Cell-intrinsic mechanism involving Siglec-5 associated with divergent outcomes of HIV-1 infection in human and chimpanzee CD4 T cells. J Mol Med Berl Ger. 2013;91:261–70.
Chen G-Y, Tang J, Zheng P, Liu Y. CD24 and Siglec-10 selectively repress tissue damage-induced immune responses. Science. 2009;323:1722–5.
Bandala-Sanchez E, Zhang Y, Reinwald S, Dromey JA, Lee B-H, Qian J, Böhmer RM, Harrison LC. T cell regulation mediated by interaction of soluble CD52 with the inhibitory receptor Siglec-10. Nat Immunol. 2013;14:741–8.
Grosse J, Meier K, Bauer TJ, Eilles C, Grimm D. Cell separation by countercurrent centrifugal elutriation: recent developments. Prep Biochem Biotechnol. 2012;42:217–33.
Reed LJ, Muench H. A simple method of estimating fifty per cent endpoints. Am J Epidemiol. 1938;27:493–7.
Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14:R36.
Langmead B, Trapnell C, Pop M, Salzberg SL. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10:R25.
Anders S, Pyl PT, Huber W. HTSeq–a Python framework to work with high-throughput sequencing data. Bioinforma Oxf Engl. 2015;31:166–9.
Law CW, Chen Y, Shi W, Smyth GK. voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 2014;15:R29.
Victorian bioinformatics consortium [Internet]. Monash University, Australia, 2014b. [Available from: http://victorian-bioinformatics-consortium.github.io/degust/]. Accessed August 2014.
Dynamic Venn diagrams for Differential Gene Expression [Internet]. Dyn. Venn Diagr. Differ. Gene Expr. Monash University, Australia, 2014a. [Available from: http://drpowell.github.io/vennt/]. Accessed August 2014.
Harman AN, Wilkinson J, Bye CR, Bosnjak L, Stern JL, Nicholle M, Lai J, Cunningham AL. HIV induces maturation of monocyte-derived dendritic cells and Langerhans cells. J Immunol. 2006;177:7103–13.
Harman AN, Kraus M, Bye CR, Byth K, Turville SG, Tang O, Mercier SK, Nasr N, Stern JL, Slobedman B, Driessen C, Cunningham AL. HIV-1–infected dendritic cells show 2 phases of gene expression changes, with lysosomal enzyme activity decreased during the second phase. Blood. 2009;114:85–94.
DAVID Bioinformatics resources 6.7 [Internet]. Database Annot. Vis. Integr. Discov., National Institute of Allergy and Infectious Diseases (NIAID), NIH, USA, 2015. [Available from: http://david.abcc.ncifcrf.gov]. Accessed in August 2014.
NK carried out cell isolations and infection experiments with the assistance of KC. CdfP and JA assisted with imaging experiments NK performed RNA isolation. DRP performed most of the bioinformatics analysis for RNA-seq data and with NK generated and analysed genes lists. Microarray analysis was completed by PUC and NK. PUC, NK and SRL conceived the study, and participated in its design and coordination. Manuscript was prepared by PUC, NK, VE and JA. All authors read and approved the final manuscript.
We thank Damian Purcell (University of Melbourne, Parkville, Australia) for providing us with the EGFP-reporter virus. We thank J. Le Masurier, M. Thomson, P. Donaldson and G. Paukovics (Alfred Medical Research and Educational Precinct (AMREP) Flow Cytometry Core Facility, Melbourne, Australia) for flow cytometric cell sorting. We thank the Australian Gene Research Facility Ltd (AGRF, Melbourne, Australia) for the guidance and support in processing of samples for RNA-seq. We thank A. Harman (Westmead Millennium Institute for Medical Research, Sydney University, Sydney, Australia) for access to microarray data, Jingling Zhou for assistance with elutriation protocol and Ajantha Solomon for assistance with RNA isolation techniques. We thank Renee van der Sluis for support in preparation of the manuscript.
NK is the recipient of the Australian Postgraduate Award (APA) (fund # Q05201 6609004). S.R.L is an NHMRC practitioner fellow. This work was supported by NHMRC project grant 1041795 and National Institutes of Health Delany AIDS Research Enterprise (DARE) to find a cure Collaboratory (U19 AI096109).
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Competing interests The authors declare that they have no competing interests.
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Kumar, N.A., Cheong, K., Powell, D.R. et al. The role of antigen presenting cells in the induction of HIV-1 latency in resting CD4+ T-cells. Retrovirology 12, 76 (2015). https://doi.org/10.1186/s12977-015-0204-2
- Dendritic cells
- HIV Latency
- Resting CD4+ T-cells
- Antigen presenting cells
- Viral reservoir
- Latency induction
- Post-integration latency