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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptNIH Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
J Infect Dis. Author manuscript; available in PMC Jul 26, 2013.
Published in final edited form as:
PMCID: PMC3724235
NIHMSID: NIHMS347972

Differential HIV epitope processing in monocytes and CD4 T cells affects cytotoxic T lymphocyte recognition

Abstract

The ability of cytotoxic T lymphocytes (CTL) to clear virus-infected cells is dependent on the presentation of viral peptides processed intracellularly and displayed by MHC-I. Most CTL functional assays utilize exogenously added peptides, which does not account for kinetics and quantity of antigenic peptides produced by infectable cells. Here we examined the relative ability of two major HIV-infectable cell subsets - CD4 T lymphocytes and monocytes- to produce antigenic peptides, using cytosol as a source of peptidases and mass spectrometry to define the degradation products. We show clear subset-specific differences in the kinetics of peptide production and the ability of the peptides produced to sensitize cells for lysis by CTL, with primary CD4 T lymphocytes possessing significantly lower proteolytic activities than monocytes. These differences in epitope processing by cell subsets may impact the efficiency of CTL-mediated clearance of infected subsets and contribute to the establishment of chronic infection.

Keywords: Antigen processing, HIV, MHC-I, epitope, Cytotoxic T Lymphocytes, CD4 T cells monocytes, proteasome, aminopeptidases, immune recognition

Introduction

The recognition and killing of HIV-infected cells by HIV-specific CTL [1] require the presentation of adequate amounts of MHC-I-epitope complexes at the cell surface, and subsequent recognition by the T cell receptor [26]. Most assays used to assess HIV-specific CTL functions rely on exogenous addition of supraphysiologic concentrations of synthetic peptides to HLA-matched target cells. Such assays allow high throughput analysis of responses to HIV proteome [710], but have failed to show a clear relationship between viral load and breadth or magnitude of these responses [7, 1113]. Critical assumptions are inherent in these assays, including that the specifics of peptide processing do not affect recognition, and that there are no cell-specific differences in these parameters.

HIV infects several cellular subsets: CD4 T lymphocytes [1417], monocytes [18, 19], macrophages [20] and dendritic cells (DC) [21]. Whether these subsets have equivalent capacity to produce MHC-I-restricted epitopes is unknown. Epitopes originate from proteins undergoing intracellular degradation in antigen processing pathways involving proteasomes [22], aminopeptidases [2326] and sometimes tripeptidylpeptidase II [27, 28] before being loaded onto MHC-I and displayed to CTL. Differences in antigen processing activities of HIV-infectable cell subsets may affect the timing and amount of epitopes presented and potentially their capacity to be killed by CTL. In support of this hypothesis, mouse dendritic and fibroblast cell lines infected with lymphocytic choriomeningitis virus (LCMV) stimulate different LCMV-specific CTL responses despite equal production of viral proteins by the two cell lines [29]. Similarly priming against Influenza by DC and secondary infection of lung macrophages by the same virus stimulate different CTL responses [30]. One possibility is that these differences may be due to variations in epitope processing by these cells, but this remains to be demonstrated.

Interestingly primary murine macrophages possess high lysosomal proteolytic activity that results in complete degradation of exogenous antigens, whereas lower lysosomal hydrolytic activity of DC and B cells allows incomplete antigen degradation, thus rendering DC and B cells more efficient at presenting MHC-II-epitopes to CD4 T cells [31]. Furthermore, variations in proteasome composition have been observed during DC maturation [32] or within tissues [33], suggesting an overall heterogeneity of the protein degradation machinery. The impact of differences in antigen processing among human cell subsets on the processing of pathogen epitopes and stimulation of CTL during infections is unknown.

Here we compared antigen processing activities of two major cell subsets infected by HIV, primary CD4 T lymphocytes and monocytes. We linked antigen processing activities to kinetics, identity and amount of viral peptides produced, as well as the ability of degradation products to sensitize target cells for lysis by cognate CTL clones. The results indicate that epitope processing in these subsets leads to sets of peptides with variable antigenicity, suggesting that the efficacy of CTL-mediated clearance may differ among cell subsets.

Experimental procedures

Study participants

HIV-negative and HIV-positive donors were recruited at the Massachusetts General Hospital (MGH), Boston, MA. This study was approved by the institutional review board at MGH. All participants provided a written informed consent for participation in the study.

Cell subset sorting and cytosol preparation

CD4 T cells were enriched from freshly isolated PBMC by magnetic immunodepletion of cells expressing either CD8, CD14, CD16, CD19, CD20, CD36, CD56, CD123, TCRγδ or Glycophorin A. Monocytes (CD14+ and CD14+/CD16+) were enriched by magnetic immunodepletion of cells expressing either CD2, CD3, CD19, CD20, CD56, CD66b, CD123 or glycophorin A according to manufacturer’s instructions (StemCell, Vancouver, Canada). The purity of cell subsets was checked by FACS analysis and reached >96% for CD4 T lymphocytes and >85% for monocytes (unpublished observations). Cytosol was purified detergent-free by centrifugations [34] or by 0.0125% digitonin permeabilization [35]. Protein concentration was measured with a Bio-Rad protein assay and checked by Western blot against various proteasome subunits, actin and glyceraldehyde 3-phosphate dehydrogenase (GAPDH).

Antigen processing activities

Chymotryptic, tryptic and caspase-like activities of proteasomes present in 3ug cytosol were measured with specific fluorogenic substrates (1mM Suc-LLVY-amc, 25uM Boc-LR-amc, 750uM Ac-YAVD-amc respectively, where amc is 7-amino-4-methylcoumarin, EMD Bioscience) [34, 36]. Aminopeptidase and tripeptidylpeptidase II activities required 50uM Leucine-amc or 100uM AAF-amc respectively [34, 37]. The specificity of the reaction was checked by preincubation of extracts with inhibitors of proteasomes (MG132 10uM), aminopeptidases (Bestatin 120mM) or tripeptidylpeptidase II (butabindide 330nM). After a 1-hour incubation at 37°C, fluorescence emission was measured at 380/460nm with a TKO fluorometer (Hoefer). Alternatively fluorescence emission was recorded every 5 minutes for 1 hour with a Victor-3 plate reader (Perkin Elmer, Boston).

HIV epitope processing assay

8 nmol of peptides (MGH peptide core facility, >95% pure) were degraded with 40ug cytosol as described previously [34]. Peptides present in the digestion mix at designated times were identified and quantified by reverse-phase high pressure liquid chromatography (RP-HPLC) [34]. The 4.6×50mm 3mm C18 column (Waters, Milford, MA) was calibrated with defined amounts of peptides covering the corresponding HIV sequence. The original undigested peptide and shorter peptides produced during in vitro digestion in cytosol form distinct peaks whose areas under curve are proportional to concentrations. The amount of peptides is calculated by integration of peaks. The identity of each peak is determined by comparing its elution time to that of known synthetic peptides covering the HIV sequence. The identity of peptides in the digestion mix was confirmed by mass spectrometry (Partners Proteomics, Cambridge, MA).

Antigenicity of degradation products

Peptides present in the digestion mix were purified, diluted in RPMI without serum and pH was readjusted to 7.4. 51Chromium (Cr)-labeled HLA-matched B cells were pulsed with 0.07 ug/ml digestion products without serum and used as targets in killing assays with epitope-specific CTL clones at a 4:1 ratio. Lysis % were compared to those of HLA-matched B cells pulsed with undigested long peptides, optimal epitopes or extended peptides containing each epitope at concentrations ranging from 0 to 0.2ug/ml [34].

Statistical analysis

Data were analyzed using GraphPad Prism version 5.

Results

CD4 T lymphocytes and monocytes have different antigen processing activities

In order to examine the relative antigen processing abilities of cell subsets, we measured the main proteolytic activities: chymotryptic, tryptic and caspase-like activities of proteasomes (i.e cleaving after hydrophobic, basic and acidic amino acids respectively), aminopeptidase and tripeptidylpeptidase II activities in primary CD4 T cells and monocytes sorted from freshly isolated PBMC of HIV-uninfected donors. Each activity was measured with a fluorogenic substrate composed of a peptide specific for each proteolytic activity and a fluorogenic coumarin-derivative moiety [36]. Fluorescence is emitted upon peptide hydrolysis proportional to the activity. Western blot against actin and GAPDH in CD4 T cells and monocytes was used to control for the use of equal amounts of cytosol.

In a representative subject (figure 1A), proteasome, aminopeptidase and tripeptidylpeptidase II activities were significantly higher in monocytes than in CD4 T cells. The specificity of these assays was confirmed by preincubation with specific inhibitors: proteasome, aminopeptidase and tripeptidylpeptidase II activities were inhibited by >75–98% when extracts were preincubated with MG132, bestatin or butabindide, respectively. We then compared antigen processing activities of 14 healthy donors whose CD4 T cells and/or monocytes were sorted from PBMC (figure 1B). Proteasome, aminopeptidase and tripeptidylpeptidase II hydrolytic activities in extracts after 1 hour incubation were significantly higher in monocytes than CD4 T cells for all donors (1.5, 1.7 and 2.7 fold differences for proteasome chymotryptic, tryptic and caspase-like activities, respectively and 4.4 and 2 fold higher for aminopeptidases and tripeptidylpeptidase II, respectively). PBMC and CD4 T cells had similar antigen processing activities except for aminopeptidases which were extremely low in CD4 T cells (0.4 fold difference between CD4 T and PBMC; unpublished observations). In 7 donors antigen processing activities were measured again 2 to 6 months later. Despite an intra-donor variability of 5–20% for some activities in each subset, proteasome and aminopeptidase activities were consistently significantly higher in monocytes with an average fold difference between monocytes and CD4 T cells activities being within 85–99.6% of those of the first time point (unpublished observations).

Figure 1
Monocytes have higher antigen processing activities than CD4 T cells. (A) Antigen processing activities of one representative donor. Proteasome (upper panel, chymotryptic, caspase-like and tryptic activities), aminopeptidase and tripeptidylpeptidase II ...

We next determined if steady state differences in hydrolytic activities between monocytes and CD4 T cells reflected differences in the kinetics of substrate degradation. Hydrolytic activities were measured with specific substrates over an hour and maximum slopes were calculated (figure 1C). The kinetics of substrate hydrolysis for proteasome and aminopeptidase activities were fastest in monocytes. Maximum slopes for chymotryptic, caspase-like and tryptic degradation were 1.9, 2.4 and 2.4-fold higher, respectively, in monocytes compared to CD4 T lymphocytes, while slopes for aminopeptidase degradation were 3.2 higher for monocytes. These results indicate significantly higher proteolytic activities in monocytes than in CD4 T cells.

Differences in antigen processing activities among CD4 T lymphocytes and monocytes affect the production of HIV epitopes

The hydrolysis of fluorogenic peptide substrates demonstrated differences in the proteolytic potential of CD4 T lymphocytes and monocytes but fails to inform about their impact on epitope processing. We have developed an in vitro degradation assay of polypeptides that recapitulates the complete endogenous processing and presentation of epitopes derived from endogenous proteins [34]. This assay enables us to identify the degradation products by mass spectrometry, to quantify them by RP-HPLC profile analysis and to measure the ability of peptides produced to sensitize cells for lysis by CTL (figure 2A). Using this assay we previously showed that the in vitro processing of HIV-1 Gag p17 fragments in PBMC cytosol yielded peptides whose antigenicity was comparable to that of HLA-A3 cells endogenously expressing Gag p17, processing and presenting epitopes [34].

Figure 2
Monocytes quickly produce short peptides fitted for loading onto MHC-I. (A) Experimental design: Highly purified long HIV peptides are incubated at 37#x000B0;C with cytosol or whole extracts from CD4 T lymphocytes or monocytes. The degradation of the ...

Initially, we examined the processing of an HIV Gag p17 peptide fragment (RWEKIRLRPGGKKKYKL aa 15–31), previously shown to contain three HLA A3-restricted CTL epitopes (KK9, aa 18–26 KIRLPPGGK; RK9, aa 20–28 RLRPGGKKK; RY10, aa 20–29 RLRPGGKKKY) targeted in acute infection [8]. The complete processing of these epitopes is performed by proteasomes, tripeptidylpeptidase II and aminopeptidases in the cytosol [34], and is ERAAP/ERAP1-independent since ERAAP/ERAP1 cannot cleave peptides rich in charged residues [38]. Equal amounts of cytosol from CD4 T cells or monocytes were used for degradation. Peptides produced during degradation were identified by mass spectrometry (figure 2B) and quantified by RP-HPLC profile analysis (figure 2C). After 2 minutes, most fragments produced in extracts from the two subsets were identical, whereas 60-minute incubation resulted in major differences in the fragments produced by these subsets. Extracts from CD4 T cells yielded longer p17 fragments (8 to 16-mers) whereas peptides produced in monocyte extracts yielded shorter peptides compatible with MHC-I loading (8 to 11-mers) [39]. They included four known overlapping optimal HIV epitopes: HLA-A3-restricted KK9, RK9 and RY10 and HLA-B27 IK9 (IRLPPGGKK) [40]. The four remaining peptides generated by monocyte extracts were optimal epitopes with a 1- or 2-residue extension [34]. Interestingly, although this p17 fragment contains 8 known epitopes [40], only the three HLA-A3-restricted optimal epitopes presented during acute HIV infection (with RK9 and RY10 being co-dominant in HLA-A3+ persons [8]) were produced using extracts from CD4 T cells and monocytes. Similar results were obtained with extracts from three healthy donors. This indicates that the previously defined link between the efficiency of HIV epitope processing and the frequency of early CTL responses during HIV infection in PBMC [34] also applies to two main subsets targeted by HIV, but that the cytosol from these subsets differs in the kinetics and quantity of peptide produced: the CD4 T cell antigen processing machinery yielded only two optimal epitopes (HLA-A3 RK9 and RY10) and many longer fragments.

In order to further investigate these apparent differences, peptides produced by each of the extracts were next quantified by RP-HPLC profile analysis (figure 2C). The column was calibrated using defined amounts of peptides included in the polypeptide and degradation products were identified and quantified over time. Each peptide was defined according to its elution time and quantified by calculating the area under peak, which is proportional to the amount of peptides. For these studies we made use of peptides for which we had previously precisely defined degradation products [34]. The degradation of 5-RK9-3 (nomenclature based on the length of N- and C-terminal extensions around the optimal HLA A3-restricted CTL epitope RK9) into 5-RK9-2 is performed by proteasomes [34] and was faster in monocyte extracts than those generated from CD4 T cells. This result is in agreement with the higher proteasome activities detected in monocytes (figure 1). In accordance with mass spectrometry analyses (figure 2B), this 16-mer persisted in extracts from CD4 T cells (1.28nmol remained after 60 minutes) whereas it was fully degraded into smaller fragments in monocyte extracts in less than 30 minutes. The production of epitopes RK9 and RY10 was also substantially faster and greater in monocyte extracts than in CD4 T cell extracts (yield 3.5 and 2.5 fold higher in monocytes, respectively). In contrast, longer fragments such as 5-RK9-2, 5-RK9-1, which are less likely to optimally bind to MHC-I, constituted the bulk of peptides produced by CD4 T cell extracts after 1 hour. Similar results were obtained with three donors.

We performed a similar study using a fragment from HIV-1 Reverse Transcriptase (RT) (WKGSPAIFQSSMTKILE, aa 152–169 containing HLA-A3/11-restricted ATK9 epitope) (figure 2D). Consistent with our studies with the Gag peptide, the RT peptide was degraded more quickly by monocyte than CD4 T cell extracts. Optimal epitope ATK9 and peptides with an N-extension of 1 to 3 residues (10- to 12-mers) were exclusively produced in monocyte cytosol whereas peptides produced in CD4 T cells cytosol were mostly either longer (14 or 15-mers) or did not contain the complete epitope (figure 2D).

These results demonstrate that the antigen processing machinery of monocytes rapidly degrades long peptides and is likely to be more efficient at generating greater amounts of epitopes of length compatible with MHC-I binding.

Differential antigen processing activities among CD4 T lymphocytes and monocytes affect the antigenicity of HIV peptides

We next examined whether differences in antigen processing would impact the generation of peptides able to sensitize cells for lysis by the cognate CTL, by comparing the antigenicity of degradation products yielded by CD4 T cells and monocyte extracts. In order to strictly compare antigenicity independently of potential variations of surface markers expressed by cells, equal amounts of HIV peptide degradation products produced in subsets extracts were pulsed onto a HLA-matched B cell line used as a target in a 51Cr killing assay with an epitope-specific clone (figure 3). Degradation products of the p17 fragment (5-RK9-3) yielded an increasing CTL response over time as expected for increasing production of shorter peptides containing RK9 (similar results were obtained with 2 different RK9-specific CTL clones). Peptides generated in monocyte extracts had the highest antigenicity with a plateau of 37% lysis of target cells reached after 1 hour. In contrast degradation products of the p17 fragment yielded in CD4 T cell extracts never reached more that 5% lysis in keeping with the qualitative and quantitative identification of long peptides with poor binding capacity to HLA A3 (figure 2B–C). By comparing the lysis of B cell lines pulsed with degradation products to that of B cell lines pulsed with increasing amounts of optimal peptide RK9, we estimate that the antigenic RK9 equivalent produced in extracts from CD4 T cells and monocytes at 60 minute is 0.07 and 25nM RK9 respectively, corresponding to a 357-fold increased antigenicity of peptides produced by the antigen processing machinery of monocytes compared to that of CD4 T lymphocytes.

Figure 3
The antigen processing machinery of monocytes produces more antigenic peptides than that of CD4 T lymphocytes. Long HIV peptides named 5-RK9-3 (aa 15–31 in Gag p17; left panel) and 5-ATK9-3 (aa 152–169 in Pol RT; right panel) were degraded ...

Similarly we compared the antigenicity of peptides obtained during the degradation of 5-ATK9-3 from HIV-1 RT (figure 3 right panel). The degradation of 5-ATK9-3 in monocyte extracts yielded antigenic peptides with an ATK9-specific CTL lysis of 26% reached after 60 minutes of degradation, whereas the antigenicity of degradation products from CD4 T cells never exceeded 13% in accordance with the detection of optimal or shortly extended ATK9 peptides by mass spectrometry in figure 2D. The antigenic ATK9 equivalent of degradation products corresponds to 0.05 and 1nM ATK9, a 20-fold increased antigenicity of peptides processed by the monocyte processing machinery versus that of CD4 T cells.

These results show that the degradation of various HIV peptides in monocyte extracts was faster and yielded shorter peptides with higher antigenicity.

Antigen processing activities of HIV-infected persons are highest in monocytes

Since Tat expression affects proteaseome activities in cell lines [41], we examined whether antigen processing activities of HIV-infected persons may be altered. We measured proteasome and aminopeptidase activities in CD4 T cells and monocytes from 18 persons chronically infected with HIV and compared them to healthy donors (figure 4). Monocytes from HIV-infected donors have higher antigen processing activities than fresh CD4 T lymphocytes in proportion similar to those found in subsets of healthy donors. For each subset, we observed no significant differences between infected and healthy donors. However the low percentage of circulating HIV-infected cells in chronic infection may mask any potential impact of HIV infection on antigen processing activities. The heterogeneity of the population of infected persons requires a larger study.

Figure 4
Monocytes of both healthy and HIV-infected individuals have higher antigen processing activities. Proteasome (chymotryptic, caspase-like and tryptic activities) and aminopeptidase activities were measured in triplicate in CD4 T cells (squares) and monocytes ...

Discussion

The capacity of cellular subsets to process and present endogenous antigens is likely to have a critical impact on the ability of CTL to kill pathogen-infected cells. This study focused on two subsets targeted by HIV, CD4 T lymphocytes and monocytes. We demonstrate more rapid kinetics, higher quantities and increased antigenicity of several HIV peptides produced by the monocyte antigen processing machinery compared to that of CD4 T lymphocytes.

Differences in epitope processing and antigenicity between the two cell subsets will likely vary according to peptidases involved in the processing of each epitope and according to the viral polypeptide being degraded. The greatest differences between monocytes and CD4 T cells were observed for aminopeptidase activities. Thus epitopes requiring aminopeptidase trimming may be poorly presented by CD4 T cells, whereas epitopes requiring mainly chymotryptic proteasome trimming would be less affected by the cell subset from which they originate. Since aminopeptidases are the main post-proteasomal peptidases involved in antigen processing [23, 25, 28, 42], our data suggest that the landscape of epitopes presented by CD4 T cells may be significantly different from that of monocytes. This difference may be further increased by additional processing pathways specific to monocytes, involving endosomal/lysosomal degradation of exogenous antigens [43]. Studies of processing of additional HIV epitopes in these subsets are needed to extend this observation.

The differences in lengths and amounts of peptides produced by each subset may affect the binding capacity to MHC-I and T cell receptor (TCR). The binding affinity of peptides to MHC-I [6], the longevity of surface display of peptide-MHC complexes, partly dependent on TCR specificity and avidity [26] will affect the presentation of epitopes. High affinity MHC-I-epitope complexes may continue to function despite lower epitope availability. It is likely that differences in the antigenicity of degradation products between monocytes and CD4 T cells, and subsequent killing by CTL will become more apparent for epitopes displaying lower affinity for MHC-I and for CTL with lower functional avidity. Furthermore if CD4 T cells are less efficiently recognized by some CTL due to suboptimal epitope production, it may provide them with a survival advantage and a higher probability of establishing viral reservoirs [1417].

Cell populations examined here can be explored in additional detail. Monocytes are composed of several subpopulations [44], including >80% of CD14+ cells and a subpopulation CD14dim/CD16+ monocytes more permissive to HIV infection [18]. Whether these monocyte subsets display different processing activities is unknown. Since CD16+ monocytes represent <10% of the monocyte population, it is unlikely that they would be solely responsible for higher activities measured in our study performed with the total monocyte population. Similarly antigen processing activities of naïve, effector and memory CD4 T cells, macrophages and DC, as well as potential differences in co-stimulatory molecules among subsets need to be investigated further. These results, however, are among the first to highlight the functional relevance of differences in antigen processing activities between cell types, which may help understand HIV pathogenesis. The priming of naïve CD8 T cells is executed by DC displaying endogenously processed HIV epitopes. If CD4 T cells and monocytes process and present different peptides or different amounts of peptides than those displayed during priming, recognition and clearance of infected subsets by CTL may be affected.

The potential impact of HIV-induced cellular activation on antigen processing activities should also be considered. Since activated CD4 T cells are the most likely to be infected by HIV, we measured proteasome activities in PHA-activated CD4 T cells and monocytes. PHA-activated subsets have significantly higher chymotryptic, caspase-like and tryptic proteasome activities than their fresh counterparts (1.1, 1.4, 1.2-fold higher for CD4 T cells and 1.4, 2.7, 1.1-fold higher for monocytes, respectively), which resulted in faster degradation of the p17 fragment (unpublished observations). Nevertheless even PHA-activated CD4 T cells possess antigen processing activities 2- to 5-fold lower than that of monocytes, suggesting that CD4 T cells regardless of their activation state are not the most efficient subset at producing epitopes tested here.

Together, these data indicate that the specificity of epitope processing and presentation, not only in pathogen-infectable cells but also in cells targeted by vaccines, should be carefully analyzed during vaccine development as vaccine-induced CTL should recognize epitopes processed by infected cell subsets.

Acknowledgments

The authors thank Dr K. Parker for help with the mass spectrometry analysis, Dr Kaufmann for help with the FACS analysis of PBMC subsets and K. Moss for collecting blood samples. We thank Drs R. Siliciano, M. Brockman, Z. Brumme, D. Kaufmann and D. Kavanagh for stimulating discussions and critical reading of the manuscript.

Sources of financial support: This study was supported in part by research funding from the Bill and Melinda Gates Foundation (The Collaboration for AIDS Vaccine Discovery), (B.D.W. and S.L.G.), Microsoft Research (S.L.G.), NIAID (AI28568) (B.D.W.) and (AI60502) (S.L.G.) the International AIDS Vaccine Initiative (B.D.W). E.L. was the recipient of the Egide/Lavoisier fellowship from the French Ministry of Foreign Affairs.

Footnotes

Conflict-of-interest disclosure: The authors declare no competing financial interests.

Presentation at meetings: Conference on Retroviruses and Opportunistic Infections. February 2008, Boston, MA

References

1. Yang OO, Kalams SA, Trocha A, et al. Suppression of human immunodeficiency virus type 1 replication by CD8+ cells: evidence for HLA class I-restricted triggering of cytolytic and noncytolytic mechanisms. J Virol. 1997;71:3120–3128. [PMC free article] [PubMed]
2. Kageyama S, Tsomides TJ, Sykulev Y, Eisen HN. Variations in the number of peptide-MHC class I complexes required to activate cytotoxic T cell responses. J Immunol. 1995;154:567–576. [PubMed]
3. Christinck ER, Luscher MA, Barber BH, Williams DB. Peptide binding to class I MHC on living cells and quantitation of complexes required for CTL lysis. Nature. 1991;352:67–70. [PubMed]
4. Reay PA, Matsui K, Haase K, Wulfing C, Chien YH, Davis MM. Determination of the relationship between T cell responsiveness and the number of MHC-peptide complexes using specific monoclonal antibodies. J Immunol. 2000;164:5626–5634. [PubMed]
5. Sykulev Y, Joo M, Vturina I, Tsomides TJ, Eisen HN. Evidence that a single peptide-MHC complex on a target cell can elicit a cytolytic T cell response. Immunity. 1996;4:565–571. [PubMed]
6. Krogsgaard M, Davis MM. How T cells 'see' antigen. Nat Immunol. 2005;6:239–245. [PubMed]
7. Addo MM, Yu XG, Rathod A, et al. Comprehensive epitope analysis of human immunodeficiency virus type 1 (HIV-1)-specific T-cell responses directed against the entire expressed HIV-1 genome demonstrate broadly directed responses, but no correlation to viral load. J Virol. 2003;77:2081–2092. [PMC free article] [PubMed]
8. Altfeld M, Kalife ET, Qi Y, et al. HLA class I alleles that contribute strongly to the initial CD8+ T cell responses against HIV-1 are associated with delayed progression to AIDS. Plos Med. 2006;3:1851–1863.
9. Frahm N, Goulder P, Brander C. Broad HIV-1 Specific CTL Responses Reveal Extensive HLA Class I Binding Promiscuity of HIV-Derived. Optimally Defined CTL Epitopes. 2003
10. Kiepiela P, Ngumbela K, Thobakgale C, et al. CD8(+) T-cell responses to different HIV proteins have discordant associations with viral load. Nat Med. 2007;13:46–53. [PubMed]
11. Betts MR, Ambrozak DR, Douek DC, et al. Analysis of total human immunodeficiency virus (HIV)-specific CD4(+) and CD8(+) T-cell responses: relationship to viral load in untreated HIV infection. J Virol. 2001;75:11983–11991. [PMC free article] [PubMed]
12. Cao J, McNevin J, Holte S, Fink L, Corey L, McElrath MJ. Comprehensive analysis of human immunodeficiency virus type 1 (HIV-1)-specific gamma interferon-secreting CD8+ T cells in primary HIV-1 infection. J Virol. 2003;77:6867–6878. [PMC free article] [PubMed]
13. Edwards BH, Bansal A, Sabbaj S, Bakari J, Mulligan MJ, Goepfert PA. Magnitude of functional CD8+-T-cell responses to the Gag protein of HIV-1 correlates inversely with viral load in plasma. J Virol. 2002;76:2298–2305. [PMC free article] [PubMed]
14. Eckstein DA, Penn ML, Korin YD, et al. HIV-1 actively replicates in naive CD4(+) T cells residing within human lymphoid tissues. Immunity. 2001;15:671–682. [PubMed]
15. Chun TW, Carruth L, Finzi D, et al. Quantification of latent tissue reservoirs and total body viral load in HIV-1 infection. Nature. 1997;387:183–188. [PubMed]
16. Chun TW, Stuyver L, Mizell SB, et al. Presence of an inducible HIV-1 latent reservoir during highly active antiretroviral therapy. Proc Natl Acad Sci U S A. 1997;94:13193–13197. [PMC free article] [PubMed]
17. Douek DC, Brenchley JM, Betts MR, et al. HIV preferentially infects HIV-specific CD4+ T cells. Nature. 2002;417:95–98. [PubMed]
18. Ellery PJ, Tippett E, Chiu YL, et al. The CD16+ monocyte subset is more permissive to infection and preferentially harbors HIV-1 in vivo. J Immunol. 2007;178:6581–6589. [PubMed]
19. Zhu T, Muthui D, Holte S, et al. Evidence for human immunodeficiency virus type 1 replication in vivo in CD14(+) monocytes and its potential role as a source of virus in patients on highly active antiretroviral therapy. J Virol. 2002;76:707–716. [PMC free article] [PubMed]
20. Koenig S, Gendelman HE, Orenstein JM, et al. Detection of AIDS virus in macrophages in brain tissue from AIDS patients with encephalopathy. Science. 1986;233:1089–1093. [PubMed]
21. Keele BF, Tazi L, Gartner S, et al. Characterization of the follicular dendritic cell reservoir of human immunodeficiency virus type 1. J Virol. 2008;82:5548–5561. [PMC free article] [PubMed]
22. Goldberg A, Cascio P, Saric T, Rock KL. The importance of the proteasome and subsequent proteolytic steps in the generation of antigenic peptides. Mol Immunol. 2002;39:147. [PubMed]
23. Saric T, Chang SC, Hattori A, et al. An IFN-gamma-induced aminopeptidase in the ER, ERAP1, trims precursors to MHC class I-presented peptides. Nat Immunol. 2002;3:1169–1176. [PubMed]
24. Serwold T, Gaw S, Shastri N. ER aminopeptidases generate a unique pool of peptides for MHC class I molecules. Nat Immunol. 2001;2:644–651. [PubMed]
25. Serwold T, Gonzalez F, Kim J, Jacob R, Shastri N. ERAAP customizes peptides for MHC class I molecules in the endoplasmic reticulum. Nature. 2002;419:480–483. [PubMed]
26. Lopez D, Gil-Torregrosa BC, Bergman C, Del Val M. Sequential cleavage by metallopeptidases and proteasomes is involved in processing HIV-1 ENV epitope for endogenous MHC class I antigen presentation. J Immunol. 2000;164:5070–5077. [PubMed]
27. Seifer U, Maranon C, Shmueli A, et al. An essential role for tripeptidyl peptidase in the generation of an MHC class I epitope. Nat Immunol. 2003;4:375–379. [PubMed]
28. Wherry EJ, Golovina TN, Morrison SE, et al. Re-evaluating the generation of a "proteasome-independent" MHC class I-restricted CD8 T cell epitope. J Immunol. 2006;176:2249–2261. [PubMed]
29. Butz EA, Bevan MJ. Differential presentation of the same MHC class I epitopes by fibroblasts and dendritic cells. J Immunol. 1998;160:2139–2144. [PubMed]
30. Crowe SR, Turner SJ, Miller SC, et al. Differential antigen presentation regulates the changing patterns of CD8+ T cell immunodominance in primary and secondary influenza virus infections. J Exp Med. 2003;198:399–410. [PMC free article] [PubMed]
31. Delamarre L, Pack M, Chang H, Mellman I, Trombetta ES. Differential lysosomal proteolysis in antigen-presenting cells determines antigen fate. Science. 2005;307:1630–1634. [PubMed]
32. Ossendorp F, Fu N, Camps M, et al. Differential expression regulation of the alpha and beta subunits of the PA28 proteasome activator in mature dendritic cells. J Immunol. 2005;174:7815. [PubMed]
33. Dahlmann B, Ruppert T, Kuehn L, Merforth S, Kloetzel PM. Different proteasome subtypes in a single tissue exhibit different enzymatic properties. J Mol Biol. 2000;303:643–653. [PubMed]
34. Le Gall S, Stamegna P, Walker BD. Portable flanking sequences modulate CTL epitope processing. J Clin Invest. 2007;117:3563–3575. [PMC free article] [PubMed]
35. Le Gall S, Neuhof A, Rapoport TA. The ER membrane is permeable to small molecules. Mol Biol Cell. 2004;15:447–455. [PMC free article] [PubMed]
36. Kisselev AF, Goldberg AL. Monitoring activity and inhibition of 26S proteasomes with fluorogenic peptide substrates. Methods Enzymol. 2005;398:364–378. [PubMed]
37. Beninga J, Rock KL, Goldberg A. Interferon-gamma can stimulate post-proteasomal trimming of the N terminus of an antigenic peptide by inducing leucine aminopeptidase. J Biol Chem. 1998;273:18734–18742. [PubMed]
38. Chang SC, Momburg F, Bhutani N, Goldberg AL. The ER aminopeptidase, ERAP1, trims precursors to lengths of MHC class I peptides by a "molecular ruler" mechanism. Proc Natl Acad Sci U S A. 2005;102:17107–17112. [PMC free article] [PubMed]
39. Sette A, Sidney J. Nine major HLA class I supertypes account for the vast preponderance of HLA-A and -B polymorphism. Immunogenetics. 1999;50:201–212. [PubMed]
40. Korber BT, Brander C, Haynes BF, et al. HIV Molecular Immunology 2008. Los Alamos, New Mexico: Los Alamos National Laboratory, Theoretical Biology and Biophysics; 2008.
41. Gavioli R, Gallerani E, Fortini C, et al. HIV-1 tat protein modulates the generation of cytotoxic T cell epitopes by modifying proteasome composition and enzymatic activity. J Immunol. 2004;173:3838–3843. [PubMed]
42. Saveanu L, Carroll O, Lindo V, et al. Concerted peptide trimming by human ERAP1 and ERAP2 aminopeptidase complexes in the endoplasmic reticulum. Nat Immunol. 2005;6:689–697. [PubMed]
43. Noursadeghi M, Katz DR, Miller RF. HIV-1 infection of mononuclear phagocytic cells: the case for bacterial innate immune deficiency in AIDS. Lancet Infect Dis. 2006;6:794–804. [PubMed]
44. Grage-Griebenow E, Flad HD, Ernst M. Heterogeneity of human peripheral blood monocyte subsets. J Leukoc Biol. 2001;69:11–20. [PubMed]
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