Upon activation, CD4+ T cells release cytokines, chemokines, and other soluble factors that influence the kinetics of HIV-1 replication in macrophages (Mϕ). In this article, we show that activation of human primary T cells suppresses the early stages of HIV-1 replication in human primary Mϕ by downregulating the main cellular receptor for the virus CD4. The secreted factors responsible for this effect have a molecular mass greater than conventional cytokines, are independent of Th1 or Th2 polarization, and are not IFN-γ, IL-16, RANTES, or macrophage inhibitory factor, as revealed by cytokine array analysis and neutralization assays. CD4 downregulation is entirely posttranslational and involves serine phosphorylation of CD4 and its targeting to an intracellular compartment destined for acidification and degradation. CD4 downregulation is dependent on the activities of both protein kinase C and NF-κB as well as the proteasomes. Using high-resolution liquid chromatography-tandem mass spectrometry analysis in conjugation with label-free protein quantitation software, we found that proteins that promote Mϕ adherence and spreading, such as attractin, fibronectin, and galectin-3–binding protein, were significantly overrepresented in the activated T cell supernatant fractions. These results reveal the existence of previously unreported anti–HIV-1 proteins, released by activated T cells that downregulate CD4 expression, and are of fundamental importance to understand the kinetics of HIV infection in vivo.

CD4 is a type 1 transmembrane glycoprotein expressed at the surface of helper and regulatory subsets of T cells, monocytes (Mo)/macrophages (Mϕ), dendritic cells, B cells, eosinophils, megakaryocytes, and mast cells (14). In T cells, CD4 is well characterized and is known to mediate T cell development and maturation (5), to stabilize TCR interactions with peptide–MHC II complexes on APC, and to amplify intracellular T cell signal transduction through the constitutive association with lymphocyte-specific protein tyrosine kinase (LCK) (6). CD4 expression levels in cells of myeloid lineage (Mo/Mϕ and dendritic cells) are 10- to 20-fold less than in T cells (2). CD4 is also the receptor for IL-16, a chemoattractant to CD4-expressing cells (7). The primary site of CD4 function is at the outer cell surface, and several biological and experimental stimuli can trigger CD4 downregulation. Ab-based CD4 cross-linking (8), treatment with soluble forms of HIV-1 gp120 (9), exposure to gangliosides (10), and phorbol esters (1115) trigger CD4 downregulation. However, the mechanisms leading to its downregulation have remained unclear. In myeloid cells, lacking LCK expression, CD4 undergoes constitutive endocytosis and recycling back to the cell surface, and at steady state, ∼40–50% is found inside the cell. LCK expression in T cells confers stability to CD4 molecules, which remain at the cell surface, and the absence of LCK correlates with enhanced CD4 endocytosis rates (16). CD4 downregulation induced by PMA is a multistep process, which involves initial CD4 serine phosphorylation, thought to increase its affinity to clathrin adaptors, increased rates of CD4 endocytosis, and altered endosomal sorting and degradation in the lysosomes (13, 17).

Since the discovery of HIV-1, many cellular products that inhibit its replication have been discovered. These are produced by a variety of cells from different sources and activation states. One of these molecules is the CD8+ cell antiviral factor (CAF). CAF has a molecular mass of 10–50 kDa and lacks identity to conventional ILs, cytokines, and chemokines (reviewed in Ref. 18). The block induced by CAF is at the LTR-driven transcription of viral proteins (19, 20), and albeit, CAF has not yet been identified, it has highlighted the existence of naturally occurring leukocyte-derived soluble factors with anti–HIV-1 activity. Another unidentified soluble factor initially described by Verani et al. (21) is the macrophage-derived anti–HIV-1 factor (MDAF). MDAF is produced by LPS-stimulated Mϕ (22) and is able to inhibit replication of primary ×4 isolates of HIV-1 in both Mϕ and T cells at the entry level (21). In Mϕ, MDAF decreases the expression levels of CD4 and CXCR4, but in T cells, MDAF only decreases CCR5 expression levels. MDAF is sensitive to heat and proteinase K treatment and is already preformed in Mϕ. MDAF lacks identity to IL-10, IL-12, IL-16, IFN-γ, and α-defensins, and the molecular mechanisms underlying the downregulation of HIV-1’s receptors remain to be fully elucidated, as does its positive identification.

In common with other laboratories, we found the kinetics of HIV-1 replication was modulated in complex ways by the simultaneous presence of Mϕ and T cells in different ratios and activation states (23, 24). To tackle one aspect of this complex problem, we studied the effect of activated uninfected CD4+ T cell secretion products on HIV-1–challenged Mϕ from healthy blood donors. We found that the activation of T cells leads to the release of soluble factors into culture supernatants, distinct of conventional cytokines of both Th1- and Th2-polarized cells that trigger internalization and degradation of CD4 glycoprotein, rendering Mϕ significantly less susceptible to infection. We characterized these molecular mechanisms using specific inhibitors to several molecules involved in intracellular signaling and proteolysis. Using high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis in conjunction with label-free protein quantitation software, we found that proteins reported to promote Mϕ adherence and spreading, such as attractin, fibronectin (FN), and galectin-3–binding protein, were significantly overrepresented in the activated T cell supernatant fractions with CD4 downregulating and anti–HIV-1 activities.

mAbs used were as follows: anti–CD4-FITC (clone RPA-T4; BD Pharmingen), anti–CCR5-FITC (clone CTC5; R&D Systems), and anti–CXCR4-PE (clone 44717.111; R&D Systems) and matching isotype controls (R&D Systems), anti-CD4 (clone 34915; R&D Systems), and anti–IFN-γ (clone K3.53; R&D Systems; ED50 = 0.06–0.3 μg/ml in the presence of 5 ng/ml IFN-γ). Polyclonal Abs (pAb) used were as follows: rabbit anti–IL-16 (PeproTech; ED50 = 0.07–0.012 μg/ml in the presence of 4.20 ng/ml IL-16), rabbit anti-RANTES (PeproTech; ED50 = 5–7 μg/ml in the presence of 100 ng/ml RANTES), chicken anti-macrophage inhibitory factor (MIF) (Lifespan Biosciences), rabbit anti-proteasome subunit 20S low molecular mass protein 2 (LMP2) C-terminal (Abcam), rabbit anti-GAPDH (R&D Systems), and rabbit anti-phosphoserine (pS) conjugates (Millipore). rIL-2, rIL-4, and rM-CSF were purchased from R&D Systems and PHA from Sigma-Aldrich. Inhibitor of proteasomal activity Z-Leu-Leu-Leu-al (MG132), inhibitor of vacuolar type H+-ATPases bafilomycin A1 (BafA1), and inhibitor of protein synthesis and secretion brefeldin A (5 μg/ml) were purchased from Sigma-Aldrich. Inhibitor of NF-κB activation Bay11-7082 and the inhibitor of protein kinase C (PKC) activity Gö6976 were purchased from Calbiochem, dissolved in DMSO (Sigma-Aldrich), and used at described concentrations. Recombinant fragment corresponding to aa 1–398 of human CD4 (Abcam) was used a concentration of 10 μg/ml.

Adult human blood was obtained from anonymous donors through the U.K. National Blood Service and tested negative for HIV-1, hepatitis B/C, and syphilis. Local Institutional Review Board approval was sought for this work from Oxford University’s Central University Research Ethics Committee, and we were informed that specific ethical approval was unnecessary for this study. PBMC were isolated using Ficoll-Plaque Plus (GE Healthcare) by density gradient centrifugation from heparinized buffy coats. Monocytes were isolated by CD14-positive selection using MACS (Miltenyi Biotec), according to the manufacturer’s instructions, and seeded in RPMI 1640-10% FCS (PAA), 2 mM l-glutamine (PAA), 100 U/ml penicillin (PAA), and 100 μg/ml streptomycin (PAA) (complete medium [CM]), supplemented with 50 ng/ml rM-CSF for 7 d. For quantitative PCR (qPCR), Mϕ were either left untreated or pretreated with supernatants from activated T cells for 18 h prior to infection with DNase-treated HIV-1BaL R5-tropic strain [AIDS Research and Reference Reagent Program, National Institutes Health (25)] by spinoculation for 90 min at 37°C. Viral inoculum was removed, cells were washed and overlaid with fresh CM+rM-CSF, and infections were left to proceed for 28 h. DNA was extracted using a DNeasy Blood and Tissue Kit (Qiagen), according to the manufacturer’s instructions, and qPCR to measure early stages of HIV-1 replication were carried out to detect late-stage reverse transcription products (HIV-1 cDNA sequence between the 5′-LTR sequence and the 5′ of the gag gene) as described previously (2628). To measure multiple rounds of HIV-1 infection, Mϕ were either left untreated or pretreated with supernatants from activated T cells for 18 h prior to infection with HIV-1BaL for 2 h at 37°C, followed by extensive washing, and cells were overlaid with fresh CM+rM-CSF. Supernatant samples of infected cultures were taken at different time intervals over 14 d and stored at −80°C until use. p24 Ag was quantified by ELISA, as described previously (28, 29).

CD4+ Th cells were isolated from the CD14-depleted PBMC, by negative selection using MACS (Miltenyi Biotec) according to the manufacturer’s protocol and seeded at 1.0 × 106 cells/ml. Freshly purified CD4+ T cells were >99% CD3+ and >98% CD4+ and anti-CD19 and anti-CD8 staining showed little or no contamination with B cells or CD8+ T cells. To induce Th1 secretion profile, CD4+ T cells were either activated in CM+rIL-2 (70 U/ml) with 1 μg/ml PHA for 5 d or using anti-biotin MACSiBead particles coupled to biotinylated Abs against human anti-CD2, -CD3, and -CD28 (Miltenyi Biotec) for 3 d, according to the manufacturer’s instructions. To induce Th2 secretion profile, CD4+ T cells were activated using anti-CD2, -CD3, and -CD28 beads in CM+rIL-4 (50 ng/ml) with 3 μg/ml mAb IFN-γ (clone K3.53) for 3 d. In the experiments regarding the proteomic analysis of the T cell supernatant fractions, CD4+ T cells were activated as described above but in OpTmizer T cell expansion serum-free media (Invitrogen), supplemented with 2 mM l-glutamine (PAA), 100 U/ml penicillin (PAA), and 100 μg/ml streptomycin (PAA).

Conditioned cell-free supernatants of activated CD4+ T cells were collected, filtered (0.45 μm; Millipore), and stored at −80°C until used. For dose- and temperature-dependent studies, T cell supernatants were diluted in fresh CM or heated at 56 or 100°C for 30 min. Supernatants were fractionated into <3-, <5-, <10-, <30-, <50-, <100-, and 50–100-kDa molecular mass fractions using Amicon centrifugal filter devices (Millipore), according to the manufacturer’s protocol. The obtained fractions were further diluted and tested for activity. Neat supernatants from activated T cells were neutralized of IFN-γ with 2 μg/ml mAb against IFN-γ (clone K3.53), neutralized of IL-16 with 2 μg/ml pAb against IL-16, neutralized of RANTES with 5 μg/ml pAb against RANTES, and neutralized of MIF with 10 μg/ml pAb against MIF or a mixture of appropriate control Ig incubated for 1 h at room temperature.

The expression of CD4, CCR5, and CXCR4 was determined by direct immunofluorescence 18 h posttreatment with supernatants from activated T cells. Mϕ in staining buffer (10 μg/ml human IgG [Sigma-Aldrich], 1% FCS, and 0.01% NaN3) were incubated with 5 μg/ml specific mAbs or matched isotype controls on ice for 30–45 min. For intracellular staining, cells were fixed, permeabilized with 0.2% saponin (Sigma-Aldrich), and stained. The percentage of positive cells and mean fluorescence intensities (MFI) were analyzed by FACSCalibur (BD Biosciences) with 15,000–20,000 gated events collected, and data were processed using FlowJo (version 7.2.4). Protein expression levels were determined by dividing the geometrical MFI of the Ab staining over the MFI of the isotype control.

Untreated or T cell supernatant-treated Mϕ for 18 h were washed and fixed for 60 min, followed by quenching in ammonium chloride for 20 min at room temperature. Cells were permeabilized, washed, and stained for LMP2. Primary Ab was detected using Alexa Fluor 555 goat anti-rabbit IgG (Molecular Probes). Coverslips were mounted on slides with VectaShield-DAPI Mounting medium (Vector Laboratories) and analyzed at room temperature using a noninverted Pascal LSM8 laser-scanning confocal microscope linked to Pascal software (Zeiss). Images were acquired using a ×63 oil immersion objective (1.4 aperture) and processed using Adobe Photoshop.

Total cellular RNA of untreated Mϕ or Mϕ treated for 18 h with T supernatants was isolated using the RNeasy Blood mini kit (Qiagen), according to the manufacturer’s recommendations. cDNA was produced using the Ambion RETROscript kit (Qiagen), according to the manufacturer’s protocol. qPCR were performed using the SYBR Green detection system and primers against CD4 (described in Ref. 30) and β-actin (Eurogentec primer mix). Data were collected and analyzed using an OpticonMonitor (version 2.03). CD4 levels were normalized to the corresponding β-actin levels according to the protocol described in Ref. 31. Results were normalized to 1, with 1 being defined as CD4 expression in control Mϕ.

Untreated Mϕ or Mϕ treated for 18 h with T cell supernatants were lysed in ice-cold lysis buffer (50 mM Tris-HCl [pH 8], 150 mM NaCl, 1% [v/v] n-dodecyl β-d-maltoside [Sigma-Aldrich]), 1× protease inhibitor mixture [Roche], and phosphatase inhibitor mixture 2 [1:100; Sigma-Aldrich]). Western blots were carried out, and membranes were scanned using Odyssey (LI-COR). For CD4 phosphorylation, Mϕ were washed free of media, detached, and treated with concentrated, molecular mass-fractionated T cell supernatants (1:5 dilution) for 0, 5, 10, 90, and 360 min. Cells were spun and lysed, and Western blots were performed to detect CD4 serine phosphorylation.

The effect of the pharmacological inhibitors on Mϕ viability was evaluated using the MTS assay (Promega), according to the manufacturer’s protocol. Background absorbance readings from reagent and media alone were deducted, and the values were expressed as a percentage of the untreated control cells absorbance.

The large dynamic range of protein abundance in the concentrated 50–100-kDa T cell supernatant fractions was reduced using the ProteoMiner kit (Bio-Rad), in accordance with the manufacturer’s instructions. For downstream mass spectrometry analysis, enriched samples were reduced and loaded onto NuPAGE 4–12% Bis-Tris precast gels (Invitrogen). Coomassie-stained gel lanes were cut into 10 equal pieces, digested with trypsin, and analyzed by LC-MS/MS using label-free software.

ProteoMiner-treated unactivated 50–100 kDa and activated 50–100-kDa fractions of T cell supernatants were in gel-digested and analyzed by LC-MS/MS using an Orbitrap mass spectrometer (Thermo Scientific) coupled to a U3000 nano-HPLC system (Dionex). Each sample was injected in triplicate using a 120-min LC gradient and a data-dependent acquisition method in which 2+, 3+, and 4+ charged species were selected for fragmentation. Fold changes in protein abundance between unactivated and activated samples of the T cell supernatants was estimated using two label-free quantitation methods. MaxQuant Label Free (version 1.0.13.13) (32, 33) calculates the intensity under the reconstructed ion chromatograms for individual peptides and compares between samples to estimate protein abundance changes (http://www.maxquant.org). Spectral Index Normalized Quantitation (SINQ) (D.C. Trudgian, manuscript in preparation) is an in-house developed label-free quantitation tool, based on the accepted method normalized spectral index (SIn) (34). The tool is incorporated into Oxford University’s Central Proteomics Facility Pipeline (35) and allows the quantification of relative protein abundances between different samples and the absolute amount of protein within a sample to be estimated in an automated manner from the calculated SIn. Data were searched using the search engines Mascot, Open Mass Spectrometry Search Algorithm, and X!Tandem against International Protein Index Human database for the SINQ calculation and using Mascot for only the MaxQuant calculation. The precursor mass tolerance was set at 20 ppm and the MS/MS mass accuracy at 0.5 Da. Data were statistically analyzed, and false-discovery rate was determined using iProphet. Proteins identified at <1% false-discovery rate with two or more unique peptides were imported to ProteinCenter software (version 3.3.2; Proxeon) and filtered for extracellular proteins using a Gene Ontology (GO) filter. Protein identifications are listed in Supplemental Tables I and II. Fold changes in relative protein abundance were estimated by submitting data to the SINQ software tool for automated calculation of the SIn. Technical triplicates were used for each label free analysis and the same data were used for both MaxQuant and SINQ label-free analysis. The mean relative protein abundance ratios between the activated and the unactivated T cell supernatant fraction were calculated and plotted onto a graph.

Human cytokine array panel A kits were used according to the manufacturer’s protocol (R&D Systems). Although membranes were blocked for 1 h, cell-free supernatants from CD4+ T cells were incubated with cytokine array panel A detection biotinylated Ab mixture (1 in 100) at room temperature. T cell supernatants were added to the membranes and incubated overnight at 4°C. Membranes were washed and incubated with HRP-conjugated streptavidin (1 in 2000) at room temperature for 30 min, developed using chemiluminescence-type solution, and exposed to x-ray film for 5–10 min.

Endotoxin levels were measured in supernatants from activated or control unactivated T cells using a granulocyte CD62L-shedding assay, following the method described by Ref. 36 in which granulocytes respond to endotoxin by cleavage of the ectodomain of surface CD62L. In brief, heparinized whole blood was incubated with an equal volume of supernatant or known endotoxin standards (Escherichia coli O55:B5 endotoxin; Lonza) for 1 h at 37°C, then an R-PE–conjugated mouse Ab against CD62L (Serotec) was added at a final concentration of 1:40 for an additional hour at 4°C. Erythrocytes in the samples were subsequently lysed with FACS Lysing Solution (BD Biosciences) for 5 min, remaining leukocytes were washed with PBS, and then analyzed using a FACSCalibur (BD Biosciences), with CellQuest acquisition software and FlowJo (version 7.6) analysis software. Granulocytes were gated according to their high forward/side scatter characteristics, and gates were then established for this population to determine CD62L-positive versus CD62L-negative granulocyte populations. All standards and samples were tested against three independent blood donors.

Statistical analysis was performed by paired t test using GraphPad Prism (version 5.01). Asterisks indicate the p values as follows: *p = 0.05–0.01, **p = 0.01–0.001, ***p < 0.001, and p > 0.05, NS. Significance refers to difference from the controls, unless otherwise stated; n refers to the number of blood donors tested.

The capacity of conditioned activated T cell supernatants to block HIV-1 infection of Mϕ was investigated by p24 ELISA quantification over 14 d. HIV-1 infection of Mϕ pretreated for 18 h showed slower kinetic rates of infection and reduced p24 production when compared with infected and untreated Mϕ (Fig. 1A). By qPCR analysis, Mϕ pretreated for 18 h with T cell supernatants contained lower levels of HIV-1 reverse transcription products (Fig. 1B), indicating that the block in viral replication is at an early stage. Viral replication was unaffected by the reagents (PHA or IL-2) used to activate the T cells (Fig. 1B).

FIGURE 1.

Soluble factors released by activated T cells protect HIV-1 infection in Mϕ and reduce CD4 protein expression levels. A, Mϕ were pretreated with supernatants from anti-CD2–, anti-CD3–, and anti-CD28–activated T cells (T cell activated T cell supernatant [Sup], gray line) for 18 h or left untreated (control, black line), prior to infection with HIV-1BaL. Supernatant samples of infected cultures were harvested at different time intervals, and p24 levels were quantified by ELISA (means ± SEM, n = 3). B, Quantification of HIV-1 reverse transcripts. Mϕ were pretreated with supernatants from the following: IL-2/PHA–activated T cells; anti-CD2–, anti-CD3–, and anti-CD28–activated T cells; unconditioned media supplemented with IL-2; unconditioned media supplemented with IL-2/PHA; or left untreated (control, black bar) for 18 h, prior to infection with HIV-1BaL. Cells were harvested 28 h postinfection, and real-time qPCR were carried out, as described in 1Materials and Methods (means + SD error bars, n = 4). C, Surface receptor levels. Mϕ were treated with supernatants from activated T cells (gray bars) or left untreated (control, black bars) for 18 h. Receptor levels were determined by flow cytometry. See 1Materials and Methods for settings (means + SD error bars; CD4 control: n = 6; CXCR4 control: n = 9; CCR5 control: n = 6; CD4 T cell Sup: n = 8; CXCR4 T cell Sup: n = 7; CCR5 T cell Sup: n = 6). D, Percentage of Mϕ expressing surface (black bars) and total (gray bars) CD4. Mϕ were treated with supernatants from the following: IL-2/PHA–activated T cells; anti-CD2–, anti-CD3–, and anti-CD28–activated T cells; unactivated T cells; activated T cells in the presence of 5 μg/ml brefeldin A; or left untreated for 18 h, followed by flow cytometry (means + SD error bars, n = 4). E, Kinetics of CD4 downregulation. Mϕ were treated with supernatants from anti-CD2–, anti-CD3–, and anti-CD28–activated T cells for 0, 2, 4, 6, 18, and 24 h (T cell Sup, gray line) or left untreated (control, black line), followed by flow cytometry analysis of total CD4 expression levels (MFI means ± SEM, n = 3). F, CD4 downregulation is mediated by a soluble factor of 50–100 kDa. Size fractionation of activated T cell supernatants was performed as described in 1Materials and Methods. Mϕ were treated with unfractionated (neat) or T cell supernatant size fractions (<3, <5, <10, <30, <50, <100, and 50–100 kDa) or left untreated (control, black bar) for 18 h, followed by flow cytometry analysis of CD4 surface expression levels (means + SD error bars, n = 3). G, Anti–HIV-1 activity is present in the 50–100-kDa size fraction. Mϕ were pretreated with unfractionated (neat) or T cell supernatant size fractions (<30, <50, <100, and 50–100 kDa) or left untreated (control, black bar) for 18 h prior to infection with HIV-1BaL. Cells were harvested 28 h postinfection, and real-time qPCR were carried out as described in 1Materials and Methods (means + SD error bars, n = 4). H, Anti–HIV-1 activity is dose dependent and (I) temperature sensitive. Mϕ were pretreated with undiluted (100%) or diluted (50–5%) of the original concentration of T cell supernatants for 18 h and pretreated with heat inactivated (56 or 100°C for 30 min) T cell supernatants or left untreated (control, black bars) for 18 h, prior to infection with HIV-1BaL. Cells were harvested 28 h postinfection, and real-time qPCR were carried out as described in 1Materials and Methods (means + SD error bars, n = 4). Significance is compared with control, unless otherwise indicated. *p = 0.05–0.01, **p < 0.01–0.001, ***p < 0.001.

FIGURE 1.

Soluble factors released by activated T cells protect HIV-1 infection in Mϕ and reduce CD4 protein expression levels. A, Mϕ were pretreated with supernatants from anti-CD2–, anti-CD3–, and anti-CD28–activated T cells (T cell activated T cell supernatant [Sup], gray line) for 18 h or left untreated (control, black line), prior to infection with HIV-1BaL. Supernatant samples of infected cultures were harvested at different time intervals, and p24 levels were quantified by ELISA (means ± SEM, n = 3). B, Quantification of HIV-1 reverse transcripts. Mϕ were pretreated with supernatants from the following: IL-2/PHA–activated T cells; anti-CD2–, anti-CD3–, and anti-CD28–activated T cells; unconditioned media supplemented with IL-2; unconditioned media supplemented with IL-2/PHA; or left untreated (control, black bar) for 18 h, prior to infection with HIV-1BaL. Cells were harvested 28 h postinfection, and real-time qPCR were carried out, as described in 1Materials and Methods (means + SD error bars, n = 4). C, Surface receptor levels. Mϕ were treated with supernatants from activated T cells (gray bars) or left untreated (control, black bars) for 18 h. Receptor levels were determined by flow cytometry. See 1Materials and Methods for settings (means + SD error bars; CD4 control: n = 6; CXCR4 control: n = 9; CCR5 control: n = 6; CD4 T cell Sup: n = 8; CXCR4 T cell Sup: n = 7; CCR5 T cell Sup: n = 6). D, Percentage of Mϕ expressing surface (black bars) and total (gray bars) CD4. Mϕ were treated with supernatants from the following: IL-2/PHA–activated T cells; anti-CD2–, anti-CD3–, and anti-CD28–activated T cells; unactivated T cells; activated T cells in the presence of 5 μg/ml brefeldin A; or left untreated for 18 h, followed by flow cytometry (means + SD error bars, n = 4). E, Kinetics of CD4 downregulation. Mϕ were treated with supernatants from anti-CD2–, anti-CD3–, and anti-CD28–activated T cells for 0, 2, 4, 6, 18, and 24 h (T cell Sup, gray line) or left untreated (control, black line), followed by flow cytometry analysis of total CD4 expression levels (MFI means ± SEM, n = 3). F, CD4 downregulation is mediated by a soluble factor of 50–100 kDa. Size fractionation of activated T cell supernatants was performed as described in 1Materials and Methods. Mϕ were treated with unfractionated (neat) or T cell supernatant size fractions (<3, <5, <10, <30, <50, <100, and 50–100 kDa) or left untreated (control, black bar) for 18 h, followed by flow cytometry analysis of CD4 surface expression levels (means + SD error bars, n = 3). G, Anti–HIV-1 activity is present in the 50–100-kDa size fraction. Mϕ were pretreated with unfractionated (neat) or T cell supernatant size fractions (<30, <50, <100, and 50–100 kDa) or left untreated (control, black bar) for 18 h prior to infection with HIV-1BaL. Cells were harvested 28 h postinfection, and real-time qPCR were carried out as described in 1Materials and Methods (means + SD error bars, n = 4). H, Anti–HIV-1 activity is dose dependent and (I) temperature sensitive. Mϕ were pretreated with undiluted (100%) or diluted (50–5%) of the original concentration of T cell supernatants for 18 h and pretreated with heat inactivated (56 or 100°C for 30 min) T cell supernatants or left untreated (control, black bars) for 18 h, prior to infection with HIV-1BaL. Cells were harvested 28 h postinfection, and real-time qPCR were carried out as described in 1Materials and Methods (means + SD error bars, n = 4). Significance is compared with control, unless otherwise indicated. *p = 0.05–0.01, **p < 0.01–0.001, ***p < 0.001.

Close modal

By qPCR analysis, we showed that the early stages of HIV-1 were affected. Therefore, we investigated whether treatment with the T cell supernatants had any effect on protein expression levels of HIV-1’s receptor and coreceptors. No statistically significant change was observed in the MFI levels of coreceptors CXCR4 and CCR5, compared with untreated control Mϕ (Fig. 1C). CD4 expression levels at the surface of treated Mϕ were reduced 2-fold compared with untreated Mϕ (p = 0.0074; n = 8) (Fig. 1C), and the percentage of Mϕ expressing surface CD4 was reduced by 60% (p < 0.001; n = 10) (Fig. 1D). In addition, a 2- to 3-fold reduction in total CD4 expression (surface and intracellular) was observed in treated Mϕ (Fig. 1D, gray bars). Mϕ treated with cell culture supernatants from unactivated and activated T cells in the presence of brefeldin A (inhibitor of protein synthesis and secretion) did not exhibit altered CD4 levels, suggesting the factors responsible for CD4 downregulation are dependent on the de novo protein synthesis and secretion induced by cellular activation of T cells (Fig. 1D).

To investigate the kinetics of CD4 downregulation, we determined the expression levels of the receptor after the addition of the T cell supernatants over a period of 24 h. After an initial lag of 4 h, CD4 expression levels were reduced by 2-fold after 6 h of treatment, as observed in the drop of MFI levels, and downregulation was maximal by 18 h (Fig. 1E). The reduced levels of CD4 expression in treated Mϕ correlate with the low susceptibility to infection by HIV-1 at the viral entry stage (Fig. 1A, 1B).

Size fractionation and concentration of the T cell supernatants were performed using different molecular mass cutoff filters. The resultant <3-, <5-, <10-, <30-, and <50-kDa fractions were shown to have no effect on the level of CD4 expressed by Mϕ, but the <100- and 50–100-kDa fractions resulted in a significant decrease in the levels of CD4 (p = 0.0301; n = 3) (Fig. 1F). In addition, the <30- and <50-kDa fractions did not affect HIV-1 replication, whereas the <100- and 50–100-kDa fractions resulted in a significant block of the early stages on HIV-1 replication by 86 and 87%, respectively (p < 0.001; n = 4) (Fig. 1G). The block on the early stages of HIV-1 replication induced by the <100- and 50–100-kDa fractions correlates with low levels of CD4 in treated Mϕ. Anti–HIV-1 activity induced by the T cell supernatants was shown to be dose dependent (Fig. 1H) and temperature sensitive (Fig. 1I). This suggests that the T cell-derived soluble factors responsible for CD4 downregulation and anti–HIV-1 activity are heat sensitive and with a molecular mass greater than that of conventional known cytokines and chemokines.

The decrease in the expression levels of cellular CD4 protein in treated Mϕ prompted us to examine whether this effect could be observed at the transcriptional level. We showed by Western blot that total cellular CD4 levels were reduced by 2-fold in treated Mϕ (p < 0.001; n = 10) (Fig. 2A, left panel) and, using quantitative real-time qPCR analysis, that the levels of CD4 transcript remained unaffected by treatment with T cell supernatants (p = 0.1102; n = 3) (Fig. 2A, right panel). This shows that the observed effect is due to a posttranslational modification of CD4.

FIGURE 2.

CD4 downregulation is a posttranslational mechanism that involves the proteasomes and acidic compartments and is dependent on PKC and NF-κB activities. A, CD4 downregulation is posttranslational. Mϕ were treated with supernatants from activated T cells for 18 h (gray bars) or left untreated (control, black bars), CD4 protein expression levels were determined by quantitative Western blotting analysis (n = 10, left panel), and CD4 mRNA levels were determined by quantitative RT-PCR (n = 3, right panel), as described in 1Materials and Methods. B, CD4 expression levels remain reduced up to 8 d after removal of the T cell supernatants. Mϕ were treated with supernatants from activated T cells for 18 h (gray bars) or left untreated (control, black bars), washed, and left in culture with fresh media for 24 h, 48 h, and 8 d. At the indicated time points, cells were used for flow cytometry analysis of total CD4 expression levels (means + SD error bars, n = 5) C, Downregulation mechanism involves CD4 serine phosphorylation. CD4 pS levels in Mϕ were determined by quantitative Western blotting analysis after treatment with concentrated size fraction of 50–100 kDa for 0, 5, 10, 90, and 360 min. Figure depicts histograms corresponding to CD4 and pS stains. CD4 and pS pixel intensity bands and pS/CD4 ratios are shown. D, CD4 downregulation involves the proteasomes and acidic compartments. The percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants in the presence of 5 μM MG132 and/or 100 nM BafA1 (n = 4) was determined by flow cytometry (left panel) or by quantitative Western blotting analysis (right panel). CD4 and GAPDH pixel intensities are depicted. E, Cellular localization of LMP2 in control (top panel) and T cell supernatant-treated (lower panel) Mϕ was conducted by immunofluorescence microscopy 18 h posttreatment with supernatants from activated T cells. LMP2 expression levels in Mϕ were determined by quantitative Western blotting analysis 18 h posttreatment with supernatants from activated T cells in the presence or absence of 5 μM MG132 and 100 nM BafA1. F, CD4 downregulation is dependent on the activities of NF-κB and (G) PKC. The percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants in the presence or absence of Bay11-7082 (n = 3) and in the presence or absence of Gö6976 (n = 3) was determined by flow cytometry. Bars represent means + SD error bars. **p < 0.01–0.001, ***p < 0.001.

FIGURE 2.

CD4 downregulation is a posttranslational mechanism that involves the proteasomes and acidic compartments and is dependent on PKC and NF-κB activities. A, CD4 downregulation is posttranslational. Mϕ were treated with supernatants from activated T cells for 18 h (gray bars) or left untreated (control, black bars), CD4 protein expression levels were determined by quantitative Western blotting analysis (n = 10, left panel), and CD4 mRNA levels were determined by quantitative RT-PCR (n = 3, right panel), as described in 1Materials and Methods. B, CD4 expression levels remain reduced up to 8 d after removal of the T cell supernatants. Mϕ were treated with supernatants from activated T cells for 18 h (gray bars) or left untreated (control, black bars), washed, and left in culture with fresh media for 24 h, 48 h, and 8 d. At the indicated time points, cells were used for flow cytometry analysis of total CD4 expression levels (means + SD error bars, n = 5) C, Downregulation mechanism involves CD4 serine phosphorylation. CD4 pS levels in Mϕ were determined by quantitative Western blotting analysis after treatment with concentrated size fraction of 50–100 kDa for 0, 5, 10, 90, and 360 min. Figure depicts histograms corresponding to CD4 and pS stains. CD4 and pS pixel intensity bands and pS/CD4 ratios are shown. D, CD4 downregulation involves the proteasomes and acidic compartments. The percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants in the presence of 5 μM MG132 and/or 100 nM BafA1 (n = 4) was determined by flow cytometry (left panel) or by quantitative Western blotting analysis (right panel). CD4 and GAPDH pixel intensities are depicted. E, Cellular localization of LMP2 in control (top panel) and T cell supernatant-treated (lower panel) Mϕ was conducted by immunofluorescence microscopy 18 h posttreatment with supernatants from activated T cells. LMP2 expression levels in Mϕ were determined by quantitative Western blotting analysis 18 h posttreatment with supernatants from activated T cells in the presence or absence of 5 μM MG132 and 100 nM BafA1. F, CD4 downregulation is dependent on the activities of NF-κB and (G) PKC. The percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants in the presence or absence of Bay11-7082 (n = 3) and in the presence or absence of Gö6976 (n = 3) was determined by flow cytometry. Bars represent means + SD error bars. **p < 0.01–0.001, ***p < 0.001.

Close modal

To investigate how stable and for how long CD4 downregulation was maintained in treated Mϕ, we determined the recovery of CD4 expression levels after the T cell supernatants were removed from the cells by flow cytometry. Twenty-four and 48 h after the T cell supernatants were removed, CD4 expression levels were still significantly reduced by 2- and 1.5-fold (Fig. 2B). Eight days after T cell supernatants were removed, CD4 expression levels were fully restored, and no significant difference was observed when compared with control untreated Mϕ (Fig. 2B). These data indicate that CD4 downregulation induced by the T cell supernatants can be fully reverted after 1 wk.

Because serine phosphorylation has been reported to be involved in early posttranslational modification and downregulation mechanisms of CD4 (11, 14, 15), we used quantitative Western blotting to detect any increase in CD4 serine phosphorylation after treatment with concentrated 50–100-kDa T cell supernatant fractions. Analysis of the individual CD4 and pS band intensities showed an increase in the ratio of pS/CD4 as early as 5 min after treatment (Fig. 2C).

To investigate whether the underlying mechanisms leading to CD4 downregulation involved the protein degradation pathways in Mϕ, we tested whether inhibitors of these pathways would restore its cellular abundance. CD4 expression levels were determined by flow cytometry and quantitative Western blotting after 18 h posttreatment with T cell supernatants in the presence of nonlethal concentrations of MG132 (proteasomal inhibitor) and/or BafA1 (inhibitor of vacuolar type H+-ATPases). Flow cytometry analysis of CD4 expression levels in treated Mϕ showed that both MG132 and BafA1, when added individually, significantly inhibited CD4 downregulation by >20% (p = 0.0013; n = 4 and p = 0.0020; n = 4, respectively), and the decrease in the expression levels of CD4 was completely blocked when both inhibitors were added together (Fig. 2D, left panel). Using quantitative Western blotting analysis, we confirmed the protection of CD4 by MG132 and BafA1 (Fig. 2D, right panel). Taken together, these data suggest that CD4 degradation induced by components in the T cell supernatants is dependent on both the proteasomes and acidic compartments. Treatment of Mϕ with both inhibitors in unconditioned media had no effect on the number of cells expressing CD4 (Supplemental Fig. 1A) and did not affect cell viability (Supplemental Fig. 1B).

Because CD4 degradation induced by the T cell supernatants was dependent on the proteasome, we investigated the cellular distribution of LMP2, a catalytic active subunit of the proteasome, by immunofluorescence microscopy and LMP2 expression levels by quantitative Western blotting 18 h posttreatment. In control untreated Mϕ, LMP2 is located in clusters in the perinuclear region of the cell and inside the nucleus, as demonstrated previously (37, 38). In contrast, LMP2 in treated Mϕ appears to be dispersed throughout the cytosol (Fig. 2E, upper panel). Using quantitative Western blotting analysis, we detected an increase in the expression levels of LMP2 in treated Mϕ. We also detected the appearance of a higher molecular mass band, reported to be an unprocessed or posttranslationally modified intermediate of LMP2 (pre-LMP2) (37). Eighteen-hour treatment with T cell supernatants in the presence of MG132 and BafA1 restored LMP2 expression levels back to control levels and led to the disappearance of the pre-LMP2 form (Fig. 2E, lower panel). The increased levels of LMP2 expression coincide with the increased proteasomal activity and degradation of CD4 in treated Mϕ.

The genes for TAP1 and LMP2 are adjacent in the human genome and are expressed divergently from a shared bidirectional promoter, which is under the regulatory control of NF-κB (39). Therefore, we assessed whether inhibiting NF-κB activity had any effect on proteasomal activity through an effect on LMP2 expression and hence restored CD4 levels in treated Mϕ. Bay11-7082, an anti-inflammatory agent that selectively and irreversibly inhibits IκBα phosphorylation, preventing the activation of NF-κB (40) was used in our assays. The results showed that CD4 degradation induced by the T cell supernatants 18 h posttreatment was inhibited by increasing, nonlethal concentrations of Bay11-7082, reaching statistical significance at 5 μg/ml (p = 0.0027; n = 3) with 30% increase in the percentage of Mϕ expressing CD4 (Fig. 2F). Bay11-7082 had no statistically significant effect on CD4 levels in unconditioned media-treated Mϕ (Supplemental Fig. 1C) or affected cell viability (Supplemental Fig. 1D).

It has been demonstrated that both HIV-1 infection and phorbol esters induce serine phosphorylation and degradation of CD4. This process is accompanied by an increase in intracellular calcium, 1,2-diacylglycerol, and inositol 1,4,5-triphosphate concentrations and suggested to be dependent on PKC activity (4144). We investigated whether T cell supernatant-induced CD4 degradation was dependent on the activity of PKC. We used Gö6976, a cell-permeable, reversible, and ATP-competitive inhibitor of PKC activity (45, 46). The presence of PKC inhibitor blocked CD4 degradation in 18-h treated Mϕ at the lowest concentration tested (Fig. 2G) and had no effect on CD4 in control cells (Supplemental Fig. 1E). Gö6976 did not affect cell viability (Supplemental Fig. 1F). This suggests that CD4 degradation induced by the T cell supernatants is dependent upon PKC activity.

Cassol et al. (47) reported that activation of Mϕ through the classical M1 pathway by the addition of exogenous IFN-γ and TNF-α downregulates CD4 expression and is refractory to HIV-1 infection. In contrast, M2-activated Mϕ by the addition of exogenous IL-4 and showed no significant effect on either receptor expression or HIV-1 DNA levels.

To test whether CD4 downregulation induced by T cell supernatants was due to an indirect effect through the modulation of Mϕ activation state, we investigated the protein content of supernatants once T cells were polarized into Th1 and Th2 phenotypes using proteomic cytokine arrays (Fig. 3A, membrane coordinates). Unstimulated CD4+ T cells released IL-2 and the MIF. Th1-polarized T cells released IFN-γ, TNF-α, GM-CSF, RANTES, MIF, CCL3, CCL4 and low amounts of IL-17 and IL-13. Th2-polarized T cells (rIL-4 and anti–IFN-γ–blocking Ab) released IL-5, IL-8, IL-13, and IL-17, but no detectable levels of IFN-γ were detected. Because we had evidence that a component in the 50–100-kDa fractions reduced the amount of CD4 and efficiently blocked HIV-1 infection in treataed-Mϕ, we investigated the cytokine profile of this fraction and found it contained none of the molecules that could be detected using the array (Fig. 3A).

FIGURE 3.

IFN-γ, IL-16, RANTES, and MIF are not responsible for CD4 downregulation induced by the T cell supernatants. A, Human proteome profiler cytokine array panel A membrane coordinates containing 36 different anticytokines printed in duplicate (see details in 1Materials and Methods). Representative membranes of day 3 supernatants from unactivated T cells; day 3 anti-CD2–, anti-CD3–, and anti-CD28–activated T cells (Th1 Sup); day 3 anti-CD2–, anti-CD3–, and anti-CD28–activated T cells in the presence of IL-4 and anti–IFN-γ–neutralizing Abs (Th2 Sup); and 50–100-kDa fraction of day 3 anti-CD2–, anti-CD3–, and anti-CD28–activated T cells. B, CD4 downregulation is independent of Th1- and Th2-released cytokines by polarized T cells. The percentage of Mϕ expressing total CD4 after 18 h treatment with Th1 or Th2 supernatants from polarized T cells (n = 3). C, CD4 downregulation is not because of IFN-γ, IL-16, RANTES, or MIF. Percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants neutralized for 1 h with 2 μg/ml mAb against IFN-γ Ab (clone K3.53) (n = 3), 2 μg/ml pAb against IL-16, 5 μg/ml pAb against RANTES, and 10 μg/ml pAb against MIF (n = 3). D, Active factors in the T cell supernatants do not interact with surface CD4. The percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants preincubated for 1 h in the presence of 10 μg/ml rCD4 (n = 3). Bars represent means + SD error bars. The significance is compared with control, unless otherwise indicated. **p < 0.01–0.001. PC, positive control.

FIGURE 3.

IFN-γ, IL-16, RANTES, and MIF are not responsible for CD4 downregulation induced by the T cell supernatants. A, Human proteome profiler cytokine array panel A membrane coordinates containing 36 different anticytokines printed in duplicate (see details in 1Materials and Methods). Representative membranes of day 3 supernatants from unactivated T cells; day 3 anti-CD2–, anti-CD3–, and anti-CD28–activated T cells (Th1 Sup); day 3 anti-CD2–, anti-CD3–, and anti-CD28–activated T cells in the presence of IL-4 and anti–IFN-γ–neutralizing Abs (Th2 Sup); and 50–100-kDa fraction of day 3 anti-CD2–, anti-CD3–, and anti-CD28–activated T cells. B, CD4 downregulation is independent of Th1- and Th2-released cytokines by polarized T cells. The percentage of Mϕ expressing total CD4 after 18 h treatment with Th1 or Th2 supernatants from polarized T cells (n = 3). C, CD4 downregulation is not because of IFN-γ, IL-16, RANTES, or MIF. Percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants neutralized for 1 h with 2 μg/ml mAb against IFN-γ Ab (clone K3.53) (n = 3), 2 μg/ml pAb against IL-16, 5 μg/ml pAb against RANTES, and 10 μg/ml pAb against MIF (n = 3). D, Active factors in the T cell supernatants do not interact with surface CD4. The percentage of Mϕ expressing total CD4 after 18 h treatment with T cell supernatants preincubated for 1 h in the presence of 10 μg/ml rCD4 (n = 3). Bars represent means + SD error bars. The significance is compared with control, unless otherwise indicated. **p < 0.01–0.001. PC, positive control.

Close modal

The supernatants used for cytokine profiling were tested for their capacity to decrease CD4 expression levels in Mϕ. When assayed for activity, Th2-derived supernatants resulted in a 30% decrease of CD4 levels (p = 0.0088; n = 3) and Th1 produced a 50% decrease (p = 0.0012; n = 3) (Fig. 3B). This indicates that CD4 downregulation and anti–HIV-1 activity cannot be attributed to any of the soluble factors detectable using the arrays, and are unlikely to be a consequence of Mϕ polarization.

Even though the total molecular mass of IFN-γ homodimer is ∼40 kDa and so below the threshold of the 50–100-kDa fraction, and the finding that supernatants from Th2-polarized cells lacking IFN-γ induced CD4 downregulation, it could still be possible that IFN-γ was responsible for the observation we reported. To address this, we neutralized any IFN-γ in the supernatants of activated T cells and found that CD4 levels remained significantly reduced in neutralized supernatants (Fig. 3C), compared with controls (p = 0.0048; n = 4).

IL-16 selectively decreases CD4 at the protein and transcriptional levels in Mϕ but not in T cells or dendritic cells (30). Although IL-16 was not detected by cytokine profiling analysis of Th1 culture supernatants or the 50–100-kDa fraction, and the finding that CD4 transcriptional levels were unaffected, we still investigated whether neutralizing any IL-16 present in the culture supernatants would restore CD4 expression. Mϕ treated with IL-16 neutralized supernatants from activated T cells contained reduced levels of CD4 expression, compared with control (p =0.0068; n = 3) (Fig. 3C). We also tested whether the presence of RANTES and MIF in the supernatants could contribute to CD4 downregulation using neutralizing Abs and found no restoration in CD4 expression levels (Fig. 3C). Altogether, these data indicate that IFN-γ, IL-16, RANTES, and MIF do not account for the decrease in CD4 expression levels induced by the T cell supernatants.

We then tested whether proteins in the T cell supernatant would directly bound to surface CD4, thereby inducing its internalization and degradation. Preincubation of the T cell supernatants with high concentrations of a recombinant protein fragment corresponding to the first 398 aa of human CD4 still induced CD4 downregulation (Fig. 3D).

Endotoxin analysis of supernatants from activated or control unactivated T cells was performed using a granulocyte CD62L-shedding assay to rule out the possibility that the observed CD4 downregulation was due to high endotoxin levels in the supernatants. This assay was chosen because it is compatible with tissue culture samples containing FCS, in contrast to commercially available recombinant Limulus Factor C/fluorogenic substrate endotoxin assay kits. Supplemental Fig. 2A shows that endotoxin levels in T cell supernatants (which were concurrently validated as active regarding macrophage CD4 downregulation) (Supplemental Fig. 2B) were not significantly different from unactivated T cell supernatants (p = 0.53) or from complete unconditioned medium or the blank standard (p = 0.82; two-way ANOVA; df = 16), and all were below the level of detection of this assay, which was 0.01 EU/ml endotoxin. These data indicate that endotoxin is not responsible for CD4 downregulation in Mϕ treated with activated T cell supernatants.

The large dynamic range resulting from highly abundant albumin peptides and other cell culturing conditions related contaminants made detection of secreted proteins problematic. To reduce the protein dynamic range present in the concentrated T cell supernatant fractions, we used ProteoMiner enrichment kit (48, 49).

Supplemental Fig. 3A shows the capacity of ProteoMiner to deplete highly abundant contaminants from the supernatant fractions. To perform a comparative analysis of the proteins differentially expressed in the active fraction of the activated T cell supernatants, we used unstimulated T cell supernatant fractions as a negative control. CD4+ T cells were activated for 3 d in OpTmizer T cell expansion serum-free media, and alternatively, CD4+ T cells were left unstimulated for 3 d. At day 3, culture supernatants were harvested, filtered, and size fractionated through 50- and 100-kDa centrifugal filters. The dynamic range of protein abundance was reduced prior to LC-MS/MS analysis using ProteoMiner.

A representative Coomassie-stained gel is shown in Supplemental Fig. 3B. Supplemental Table I lists the proteins identified in the unactivated T cell supernatant fraction after GO-Slim extracellular component filtering. Abundant serum proteins such as albumin, transthyretin, lactotransferrin, afamin, many classes of SERPINs, and complement-related proteins were identified with large numbers of peptides. Proteins reported to be membrane associated or cell derived and secreted were also detected including vitamin D-binding protein, N-acetylmuramoyl-l-alanine amidase (50), fibulin-1 (51), and matrix metalloproteinase-9. Supplemental Table II lists the proteins identified in the activated T cell supernatant fraction after GO-Slim extracellular component filtering. Attractin (dipeptidylpeptidase-L, “L” from lymphocytes), reported to be expressed upon activation of T cells and targeted to the membrane, followed by the release of the secreted form (5254), was identified with 13 unique peptides. Galectin-3–binding protein (Mac-2–binding protein) promotes integrin-mediated cell adhesion and stimulates host defense against viruses, and tumor cells (55, 56) and FN involved in cell adhesion, cell motility, opsonization, wound healing, and maintenance of cell shape were uniquely identified only in the activated T cell supernatant fraction (57).

Relative protein abundance in unactivated and activated T cell supernatant fractions were determined using label-free proteomic software, SINQ and MaxQuant, and the relative protein abundance ratios are shown in Fig. 4. Albumin, apolipoproteins D and H, hemopexin, complement-related protein C3, transthyretin, and antithrombin-III (SERPINC1) have ratios close to 1, indicating that the protein abundances between the two fractions did not change. In contrast, AMBP protein, haptoglobin, and α-2-HS-glycoprotein were 10-fold more abundant in the activated T cell fraction, and attractin was >40-fold more abundant in the activated fraction. FN, QSOX1, biotinidase, fetuin-B, and galectin-3–binding protein were only found in the activated fractions.

FIGURE 4.

Proteomic and relative protein abundance analysis of the concentrated T cell supernatant fraction. SINQ and MaxQuant label-free quantitative analysis of the relative protein abundance in the activated T cell supernatant fraction over the unstimulated supernatant fraction. Box lists the uniquely identified proteins in the activated fractions and the number of unique peptides (parentheses).

FIGURE 4.

Proteomic and relative protein abundance analysis of the concentrated T cell supernatant fraction. SINQ and MaxQuant label-free quantitative analysis of the relative protein abundance in the activated T cell supernatant fraction over the unstimulated supernatant fraction. Box lists the uniquely identified proteins in the activated fractions and the number of unique peptides (parentheses).

Close modal

In this study, we demonstrate that conditioned supernatants, in which T cells were stimulated, reduce the capacity of HIV-1 to replicate and decrease the expression levels of CD4 in treated Mϕ.

The proteins responsible for decreasing the levels of CD4 are dependent on de novo synthesis and secretion triggered by T cell activation. CD4 downregulation in treated Mϕ is entirely posttranslational, involves rapid serine phosphorylation of CD4, and is a complex process, dependent on vacuolar acidification and proteasomal activity. In fact, when proteasomal or vacuolar acidification-dependent pathways were individually blocked in treated Mϕ, CD4 expression levels were only partially restored, suggesting that both pathways are required for full CD4 degradation. Proteomic-based identification of CD4-interacting proteins in Mϕ (58) detected an E3 ubiquitin ligase to be associated with CD4 in the presence of MG132, strengthening the involvement of the proteasomes in induced CD4 degradation. We were unable to detect ubiquitin-modified CD4 in treated Mϕ (data not shown), which might be due to the low expression of CD4 in these cells. In treated Mϕ, LMP2-containing proteasomes are redistributed from the nucleus to the cytosol, and LMP2 expression levels are upregulated. Both redistribution to the cytosol and upregulation of LMP2-containing proteasomes favor the interaction of newly internalized CD4 molecules with the proteasomes and hence increased rates of CD4 degradation. We have also shown that degradation of intracellular CD4 in treated Mϕ was dependent on NF-κB activation. LMP2 expression, being dependent on NF-κB activation (39), was upregulated in treated Mϕ and restored back to normal levels in the presence of MG132 and BafA1. MG132 blocks the activity of the proteasomes and reduces IκB degradation, essential for the activation of NF-κB. Taken together, our data suggest that CD4 degradation is mediated by an NF-κB–dependent upregulation of LMP2. It is also clear that these pathways are induced by components in the T cell supernatants rather than constitutively active in the Mϕ, promoting effective degradation of CD4.

A link among PKC activity, CD4 phosphorylation, and the capacity of HIV-1 to infect target cells has been established, and concentrations of PKC inhibitors that effectively block PKC activity also block HIV-1 replication (45). PMA, which induces CD4 internalization and degradation, has been linked to the activation of PKC and CD4 phosphorylation (59). Our data have shown that treatment of Mϕ with concentrated active fractions of the T cell supernatants result in CD4 serine phosphorylation, which prompted us to investigate the involvement of PKC in this process. CD4 degradation was sensitive to the PKC inhibitor Gö6976, indicating a role for PKC in induced CD4 downregulation. In vitro work using pharmacological inhibitors and genetic manipulation of PKC gene expression identified NF-κB as a downstream target. In vivo work has also associated the loss of PKC activity with defects in the regulation of NF-κB target genes (Refs. 60 and 61 and reviewed in Ref. 62). Activation of NF-κB is dependent on the appropriate degradation of its inhibitory interaction partner, IκB, after phosphorylation by the IκB kinase (62). In B cells, PKC activity is necessary for the activation of NF-κB through the phosphorylation of IκB kinase (63), and in the monocytic cell line U937, PKC activity is necessary and sufficient for IκB phosphorylation/degradation and NF-κB nuclear translocation (64). In our experiments, inhibition of both activities of PKC and NF-κB blocked CD4 degradation in treated Mϕ, suggesting that genes under the regulatory control of NF-κB, such as the proteasomal subunit LMP2, play a role in this pathway.

Released products from both Th1- and Th2-polarized T cells induced CD4 downregulation in Mϕ and the concentrated 50–100-kDa fraction, which we showed had potent anti–HIV-1 activity and induced CD4 downregulation, contained no detectable levels of cytokines and chemokines. Nevertheless, the use of a combination of neutralizing Ab against likely candidates such as IFN-γ and IL-16 led to the conclusion that these cytokines do not account for the decreased levels of CD4 induced by the T cell supernatants. We have also demonstrated that induced CD4 downregulation was not a consequence of the direct bounding of components in the T cell supernatants with CD4 at the surface of the Mϕ. In addition, we showed that endotoxin cannot be accounted for in the CD4 downregulation phenotype because the detected levels of endotoxin in both control and T cell supernatant samples were indistinguishable and extremely low (<0.01 EU/ml).

Last, we applied a combination of different proteomic-based techniques to identify the proteins present in the 50–100-kDa active fraction from the activated T cell supernatants. The use of ProteoMiner bead technology allowed the better separation and resolution of least abundant proteins, which would otherwise be undetected by LC-MS/MS analysis. As we had initially shown using the proteomic cytokine array, the 50–100-kDa active fraction was free of conventional cytokines and chemokines.

Antithrombin-III (SERPINC1) has been shown in a previous study attempting to identify CAF as having anti–HIV-1 properties (65). We detected SERPIN1 in the supernatants, but because its relative abundance remained unchanged between the unactivated and activated fractions, it cannot account for the observed effects.

Attractin (dipeptidylpeptidase-L) was the most upregulated protein by activation of T cells, and its abundance increased >40-fold. Attractin has been shown to mediate T cell and Mo/Mϕ interactions, leading to strong Mo adherence and spreading, allowing a more rapid and efficient presentation of Ags to T cells (66). T cell activation induces its rapid expression and secretion to the culture medium. The immunoregulatory activity of attractin results from its ability to promote formation of immune cell clusters and to reduce the activity of cytokines/chemokines (67).

FN was identified only in activated T cell supernatant fractions. It is a multifunctional glycoprotein present in the extracellular matrix and shown to be associated with the membrane of T lymphocytes and neutrophils (68). A T cell-derived soluble form of FN has also been reported to act as a lymphokine and to mediate Mo/Mϕ agglutination and adherence induced by T cell activation (57, 69, 70). Mϕ agglutination requires interactions between fibronectin and cell surface integrin receptors. Binding of FN to its integrin receptor (α5β1) triggers intracellular kinases and activates downstream signal transduction pathways, of which PI3K, PKC, and MAPK are involved (71).

Galectin-3–binding protein (Mac-2–binding protein) was also uniquely identified in the activated T cell supernatant fractions. Mac-2–binding protein has been shown to promote cell–cell contacts through cross-linking of surface-bound galectin-3 (Mac-2 Ag) and promotes cell adhesion and spreading in a process mediated by β integrins (55).

Using high-resolution LC-MS/MS analysis, we found that proteins that promote Mϕ adherence and spreading, such as attractin, fibronectin, and galectin-3–binding protein, were significantly overrepresented in the activated T cell supernatant fractions. Potentially, their promotion of Mϕ adherence and spreading may allow better antigenic presentation to T cells. The engagement of these proteins to their surface receptors triggers intracellular activation of signaling molecules, in particular PKC. In fact, PKC has been implicated in integrin-mediated events, including focal adhesion formation, cell spreading, cell migration, and cytoskeletal rearrangements. Treatment of many cell types with phorbol esters directly stimulates the activation of PKC, promoting adhesion, spreading, and migration on extracellular matrices (72, 73). By contrast, inhibition of PKC activity blocks cell adhesion, cell spreading (74), and cell migration (75).

We propose that activation of PKC initiates a cascade of events, including CD4 phosphorylation, downstream activation of NF-κB, and transcription of NF-κB–dependent genes, such as the LMP2, promoting CD4 internalization and further degradation (Fig. 5). Our data show strong evidence for the influence of T cells in mediating Mϕ susceptibility to HIV-1. T cell-derived soluble factors have the capacity to induce CD4 internalization and degradation in Mϕ, which render the cells refractory to infection by HIV-1.

FIGURE 5.

Proposed mechanism of CD4 internalization and degradation induced by T cell-derived soluble factors. T cell activation triggers the de novo synthesis and secretion of soluble factors including integrin binding molecules. Engagement to integrin receptors induces the intracellular activation of PKC and serine phosphorylation of CD4. Phosphorylated CD4 is internalized and targeted for proteolytic degradation in intracellular acidic compartments. In parallel, PKC activation leads to the downstream phosphorylation of IκBa, which disassembles from NF-κB, allowing its nuclear translocation and activation of NF-κB–dependent genes, including LMP2, a catalytic active subunit of the proteasome. Newly internalized CD4 is proteolytic degraded by cytosolic proteasomes.

FIGURE 5.

Proposed mechanism of CD4 internalization and degradation induced by T cell-derived soluble factors. T cell activation triggers the de novo synthesis and secretion of soluble factors including integrin binding molecules. Engagement to integrin receptors induces the intracellular activation of PKC and serine phosphorylation of CD4. Phosphorylated CD4 is internalized and targeted for proteolytic degradation in intracellular acidic compartments. In parallel, PKC activation leads to the downstream phosphorylation of IκBa, which disassembles from NF-κB, allowing its nuclear translocation and activation of NF-κB–dependent genes, including LMP2, a catalytic active subunit of the proteasome. Newly internalized CD4 is proteolytic degraded by cytosolic proteasomes.

Close modal

Our findings are of crucial importance for the understanding of Mo/Mϕ biology as well as the immunopathogenesis of HIV, and the proteins identified in our study could have implications as potential antiviral therapies.

We thank Dr. Gemma Carter, Dr. Michael (Kenny) Moore, and Dr. Claudia Brockmeyer for helpful discussions and Gabriela Ridlova for helping with the mass spectrometry analysis. We also thank Dr. Fernando Martinez for advice on performing the CD62L endotoxin assay.

This work was supported by a Ph.D. grant from the Portuguese Foundation for Science and Technology (SFRH/BD/15903/2005 to R.A.S.R.). S.A.C. is funded by a Wellcome Trust Career Re-entry fellowship (WT082260). B.v.W. is funded by the Medical Research Council (U.K.) and Edward Penley Abraham trust funds.

The online version of this article contains supplemental material.

Abbreviations used in this article:

BafA1

bafilomycin A1

CAF

CD8+ cell antiviral factor

FN

fibronectin

GO

Gene Ontology

LCK

lymphocyte-specific protein tyrosine kinase

LC-MS/MS

liquid chromatography-tandem mass spectrometry

LMP2

low molecular mass protein 2

macrophage

MDAF

macrophage-derived anti–HIV-1 factor

MG132

Z-Leu-Leu-Leu-al

MIF

macrophage inhibitory factor

Mo

monocyte

pAb

polyclonal Ab

PKC

protein kinase C

pS

phosphoserine

qPCR

quantitative PCR

SIn

normalized spectral index

SINQ

Spectral Index Normalized Quantitation.

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:
309
316
.

The authors have no financial conflicts of interest.