Ethics Statement

This study utilized pre-existing, de-identified specimens and was conducted under the approval of the local Institutional Review Boards (IRBs). The following IRBs conducted oversight for their respective sites: RV144- Ministry of Public Health (Bangkok, Thailand), Royal Thai Army (Thailand), Mahidol University (Bangkok, Thailand); Vax003 - The Bangkok Metropolitan Administration (Tropical Medicine of Mahidol University & HIV/AIDS Collaboration (Bangkok, Thailand); Vax004- Colorado Multiple Institution Review Board (Denver, CO), Saint Louis University (St Louis, MO), Johns Hopkins School of Medicine (Baltimore, MD), Fenway Community Health Center (Boston ,MA), Philadelphia Fight (Philadelphia, PA), Chicago Center for Clinical Research (Chicago, IL), AIDS Research Alliance (West Hollywood, CA), Louisiana State University Medical Center (New Orleans, LA), University of Rochester (Rochester, NY), Infectious Disease Research Institute, Inc. (Tampa, FL), Clinical Research Puerto Rico (San Jaun, PR), University of California, Irvine (Irvine, CA), University of California, San Francisco (San Francisco, CA), University of Washington (Seattle, WA), Hennepin County Medical Center (Minneapolis, MN), The Mount Sinai Medical Center (New York, NY), University Medical Center of southern Nevada (Las Vegas, NV), University of New Mexico (Albuquerque, NM), University of Illinois at Chicago Medical Center (Chicago, IL), Abbott Northwestern Hospital (Minneapolis, MN), St. John’s Doctors Building (Tulsa, OK), Dutchess County Dept of Health (Poughkeepsie, NY), New York Blood Center (New York, NY), New York Medical Center and Bellevue Hospital Center (New York, NY), Howard Brown Health Center (Chicago, IL), The Ohio State University (Columbus, OH), The University of Texas Medical Branch at Galveston (Galveston, TX), Kansas City AIDS Research Consortium (Kansas City, MO), University of California, Davis (Davis, CA), Central Florida Research Initiative (Maitland, FL), Community AIDS Resource, Inc (Coral Gables, FL), Palm Beach Research Center (West Palm Beach, FL), University of Hawaii (Honolulu, HI), AIDS Research Consortium of Atlanta, Inc (Atlanta, GA), University of California, San Francisco (San Francisco, CA), Erie County Medical Center (Buffalo, NY), ViRx Inc. (Palm Spring, CA), Municipal Health Services, Dept of Public Health and Environment (Amsterdam, Netherlands), Santa Public Health Dept. (San Jose, CA), Arizona Clinical Research Center, Inc. (Tucson, AZ), Albany Medical College (Albany, NY), New Jersey Community Research Initiative (Newark, NJ), Duval County Health Department (Jacksonville, FL), University Hospitals of Cleveland (Cleveland, OH), Oak Lawn Physicians Group (Dallas, TX), Nelson-Tebedo Community Clinic (Dallas, TX), The University of Alabama at Birmingham (Birmingham, AL), Community Hospitals Indianapolis (Indianapolis, IN), PW Clinical Research, LLC (Winston-Salem, NC), St. Paul’s Hospital (Vancouver British Columbia, Canada), Hospital Saint-Luc du CHUM (Montréal, Canada), Omaga Medical Research (Providance, RI), Wisconsin AIDS Research Consortium (Milwaukee, WI), The Research & Education Group (Portland, OR), University of Pittsburgh (Pittsburgh, PA), Phoenix Body Positive, Inc. (Phoenix, AZ), The Miriam Hospital (Providance, RI), Nalle Clinic (Charlotte, NC), Memorial Hospital of Rhode Island (Pawtucket, RI), Canadian HIV Trials Network (Toronto, ON, Canada); HIV-1-infected subjects- Duke University Medical Center (Durham, NC), Siriraj Ethics Committee (Bangkok, Thailand), Beth Israel Deaconess Medical Center (Boston, Massachusetts), Queen Mary’s School of Medicine and Dentistry (United Kingdom), Division of Human Subject Protection, Walter Reed Army Institute of Research (DHSP-WRAIR) (Bangkok, Thailand), Institutional Review Board for Chinese Center for Disease Control and Prevention/National Center for AIDS/STD Control and Prevention (Beijing, China), University of Witwatersrand – Human Research Ethics Committee (Human) (Johannesburg, South Africa), HIV/AIDS Research Committee of The Uganda National Council for Science and Technology (Kampala, Uganda). The data were analyzed anonymously.

Specimens

Serum and plasma samples were obtained from the RV144, Vax003 and Vax004 HIV-1 vaccine efficacy trials (registration numbers NCT00223080, NCT0006327 and NCT00002441, respectively, ClinicalTrials.gov). RV144 tested two inoculations (weeks 0, 4) with a recombinant canarypox vector (vCP1521) expressing Gag and Pro of HIV-1 MN (subtype B), and membrane-linked gp120 from strain 92TH023 (CRF01_AE), followed by two boosts at weeks 12 and 24 with vCP1521 plus bivalent gp120 protein (AIDSVAX B/E, MN and A244 strains) in a community-based heterosexual population in Thailand [17]. Plasma samples were obtained pre-immunization (week 0) and 2 weeks after the final inoculation (week 26) from 41 vaccine recipients (cases) who acquired HIV-1 infection after week 26, and from an additional 205 vaccine recipients (controls) selected randomly among those who had not acquire infection by the end of the trial (month 42) [32]. Vax003 tested seven inoculations with bivalent gp120 protein (AIDSVAX B/E, weeks 0, 1, 6, 12, 18, 24, and 36) in a cohort of mostly injection drug using men in Thailand [37]. Vax004 tested seven inoculations with bivalent gp120 protein (AIDSVAX B/B, MN and GNE8 strains) at weeks 0, 1, 6, 12, 18, 24, and 30 in mostly men who have sex with men in North America and Europe [38]. Peak antibody responses in both trials were observed 2 weeks after the fourth inoculation (month 12.5) [37,39]. Serum samples from Vax003 and Vax004 were obtained at baseline and month 12.5 from 90 vaccine recipients in Vax003 and from 20 vaccine recipients in Vax004, all of whom were uninfected at month 12.5. Additional plasma samples were obtained from 169 chronically infected individuals who were not part of any vaccine clinical trial and who were antiretroviral drug-naïve; these individuals were infected with HIV-1 subtypes A (n=8), B (n=59), C (n=57), D (n=8), CRF01-AE (n=13), CFR02_AG (n=2), CRF07_BC (n=1), CRF10_CD (n=2), AC (n=4), AD (n= 3) and ABCD (n=2). HIV-1 genetic subtypes were determined by single genome amplification and sequencing of a single plasma gp160 gene as described [40,41]. All clinical trials were conducted in accordance with the Declaration of Helsinki and local institutional review board requirements. Written informed consent was obtained from all clinical trial subjects.

Design of overlapping peptides

Peptides were designed to cover the entire gp160 consensus sequences for HIV-1 Group M, subtypes A, B, C, D, CRF01_AE and CRF02_AG [19] for a total of 1423 peptides (15-mers overlapping by 12 amino acids). Peptide sequences were generated by alignment of the 7 consensus gp160 sequences using the LANL PeptGen tool (www.hiv.lanl.gov), so that peptides remain in register throughout the Env despite insertions and deletions, and identical peptides found in more than one subtype were only represented once. A listing of all of the peptides and their sequences may be found in Table S1.

Peptide synthesis and microarray printing

PepStar peptide microarrays were produced by JPT Peptide Technologies GmbH (Berlin, Germany). A total of 1423 tiled Env peptides (peptide length 15 aa) were synthesized on cellulose membranes using SPOT synthesis technology. After a final synthesis step attaching a reactivity tag to each peptide’s N-terminus, the side chains were deprotected and the solid-phase bound peptides were transferred into 96-well microtiter filtration plates (Millipore, Bedford, MA, USA). Subsequently the peptides were treated them with aqueous triethylamine [2.5% (v/v)] cleaving the peptides from the cellulose membrane. The peptide-containing solution was centrifuge-filtered into daughter plates and the solvent was removed by evaporation under reduced pressure. Quality control measurements using LCMS were performed on random samples of final library. Dry peptide derivatives (50 nmol) were dissolved in 35 µl of printing buffer and transferred into 384-well microtiter plates. Peptide microarrays were produced using high performance contact printers on epoxy-modified slides (PolyAn; Germany). All peptides and controls were deposited in three identical subarrays, enabling analysis of assay homogeneity and reliability of the results. Peptide microarrays were scanned after printing process for identification and quality control of each individual spot. Subsequently, peptide microarray surfaces were deactivated using quenching solutions, washed with water and dried using microarray centrifuges. Resulting peptide microarrays were stored at 4°C until use.

Peptide array binding assay

Microarray binding was performed using the HS4800 Pro Hybridization Station (Tecan, Männedorf, Switzerland). All arrays were blocked with Superblock T20 PBS blocking buffer for 0.5 hour at 30°C, followed by a 2 hr incubation at 30°C with heat inactivated plasma diluted 1:100 in Superblock T20. Arrays were incubated for 45 minutes at 30°C with anti-IgG Cy5 secondary antibody (1.5 µg/ml final concentration) diluted with Superblock T20. Washes between all steps were with PBS containing 0.1% Tween. Arrays were scanned at a wavelength of 635 nm using an Axon Genepix 4300 Scanner (Molecular Devices, Sunnyvale, CA, USA) at a PMT setting of 600, 50% laser power. Images were analyzed using Genepix Pro 7 software (Molecular Devices).

Data Analysis

Magnitude and frequency of IgG binding in peptide arrays

Env-specific plasma IgG was assessed with overlapping peptides (15 mers overlapping by 12) spanning the entire consensus gp160 of HIV-1 subtypes A, B, C, D, CRF01_AE, CRF01_AG and Con-M. Figure 1A shows a heatmap of aggregate smoothed binding intensities against the gp120 peptides for samples obtained at peak immunity (2 weeks post 4^th inoculation) from 246 vaccine recipients in RV144, 90 vaccine recipients in Vax003 and 20 vaccine recipients in Vax004. Also shown are binding intensities for a multi-subtype panel of plasma samples from chronically HIV-1-infected individuals. Several linear B cell epitopes were identified. Among them, the V3 loop and C-terminus of the C5 region of gp120 were major targets for the IgG response in all four groups of subjects. C5 contained three adjacent reactive regions, designated C5a, C5b and C5c. C5a was a dominant response in Vax003, whereas C5b was a dominant response in all groups except for HIV-1-infected individuals. C5c was a dominant response in all groups except for RV144. The C1 region of gp120 was another major response in RV144, Vax003 and Vax004 but not in HIV-1-infected subjects. C1 contained two adjacent reactive regions, designated C1a and C1b, where C1a was a major response in RV144, Vax003 and Vax004, while the C1b response was primarily seen in Vax003. Finally, the V2 region of gp120 was a major response in RV144 and Vax003 but not in Vax004 and HIV-1-infected individuals. Overall, vaccination induced responses to more epitopes than did HIV-1 infection, including a V2 response that was substantially stronger in RV144 and Vax003 (including CRF01_AE infected subjects) and was absent in Vax004.

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Figure 1. Heatmaps of smoothed normalized peptide binding values for samples from RV144, Vax003, Vax004 and HIV-1-infected individuals as a function of HxB2 coordinates.

Each row represents a sample from a single individual, where stronger intensities of binding are shown as darker images. Columns represent amino acid positions using HxB2 numbering from the amino terminus (NH) to the carboxy terminus (COOH) as shown along the x-axis of each heatmap. Within the x-axis bar, areas of white and gray are used to show regions of strongest reactivity. Boxes are used to show group-specific regions of strongest reactivity. A. Gp120 peptides. B. Gp41 peptides.

https://doi.org/10.1371/journal.pone.0075665.g001

Additional major responses in HIV-1-infected individuals targeted several regions in gp41, including the N- and C- termini of heptad repeat 1 (HR-1), the immunodominant domain (ID) and the membrane proximal external region (MPER) (Figure 1B) (gp41 reactivity was not expected in the vaccine recipients because the immunogen was gp120). A subset of individuals infected with subtype C HIV-1, selected among 96 individuals for having the greatest neutralizing activity against a panel of six Tier 2 clade C viruses, demonstrated additional binding specificities. Thus, in addition to V3, C5, HR-1, ID and MPER, these subjects frequently responded to epitopes in the C1 (including C1a and C1b), C2, and C3/V4 regions of gp120, plus two sites in the HR-2 region of gp41 (Figure 2). This pattern was not associated with neutralization potency in general among the entire dataset, suggesting it is a relatively unique feature of stronger responses in subtype C-infected subjects. Figure 2 also shows that the MPER responses were mostly seen in subjects who were infected with subtype B and C viruses, with only rare reactivity in subtype A-infected subjects.

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Figure 2. Heatmap of smoothed normalized gp160 peptide binding values for samples from HIV-1-infected individuals as a function of genetic subtype and HxB2 coordinates.

Each row represents a sample from a single individual, where stronger intensities of binding are shown as darker images. Columns represent amino acid positions using HxB2 numbering from the amino terminus (NH) to the carboxy terminus (COOH) as shown along the x-axis. Within the x-axis bar, areas of white and gray are used to show regions of strongest reactivity from Figure 1. Boxes are used to show the regions of strongest reactivity from Figure 1, plus additional regions of interest.

https://doi.org/10.1371/journal.pone.0075665.g002

The gp41-ID reactive region was 23 amino acids in length, contained a disulfide bridge, and was relatively conserved among HIV-1 subtypes except at position 607, which accommodated asparagine, alanine or threonine; subtypes D and CRF01_AE contained additional changes, most notably in CRF01_AE (Figure 3). The two dominant epitopes in HR1 were highly conserved, with only a single change at position 567 in C-HR1 of subtype A and CRF02_AG. The MPER reactive region was the most variable and contained the 2F5 epitope but did not contain the most membrane proximal residues for other MPER-specific bnAbs.

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Figure 3. IgG response rates by peptide genetic subtype.

Response rates (percent positive responses) are shown for major reactive regions in gp120, as color-coded in the legend.

https://doi.org/10.1371/journal.pone.0075665.g003

IgG responses were compared based on frequencies of binding to different genetic subtype of the gp120 peptides (Figure 4). The overall response rate to C1a was highest in Vax003 (58-74%), followed by RV144 (48-61%) and Vax004 (24-35%). C1a spans a highly conserved region, and the consensus sequences for the M group, B, C, D, and CRF02_AG are identical in this region (Figure 3). There is only a single amino acid change in subtype A and one in CRF01_AE (Figure 3). These changes resulted in a somewhat higher frequency of responses in RV144, and diminished responses in Vax004, to subtype A and CRF01_AE relative to the other C1a subtypes. The peptide that is associated with C1b reactivity is so highly conserved that it is identical in all subtypes (Figure 3). C1b reactivity was only seen in Vax003 and as expected, it was high for all subtypes (60-68% response rates) (Figure 4).

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Figure 4. Sequences of major reactive regions in gp120 and gp41.

Sequences are shown for individual genetic subtypes in the major IgG binding regions of gp120 and gp41. Borders were defined by overlapping peptide binding intensities (only reactive regions are shown). Amino acid residues that differ from the group M consensus are shown in boldface type. Boxed is a key position in V2 that was identified by genetic sieve analyses of breakthrough viruses in RV144. The HXB2 numbering system is used to identify amino acid sites.

https://doi.org/10.1371/journal.pone.0075665.g004

The response rate to V2 was substantially higher in Vax003 and RV144 than in Vax004 and HIV-1-infected subjects (Figure 4). The anti-V2 response in RV144 was highly cross-reactive, with reactivity greatest against CRF01_AE and CRF02_AG consensus V2 peptides (which are identical) followed by Con-M and subtype C consensus V2 peptides (which are identical) and subtype A V2 peptides (38-55% response rates). Less frequent reactivity was seen to the consensus of subtypes D and B (27% and 8% response rate, respectively), which were very distinct in the V2 peptide region (Figure 3). The response in Vax003 was somewhat higher overall and reacted with subtypes A, D and CRF01_AE V2 peptides, in this descending order (60-72% response rates), with less frequent reactivity to CRF02_AG and subtypes B, C and group M V2 peptides (37-50% response rates). It is possible that the CRF01_AE gp120 presented the V2 loop more favorably than the subtype B gp120s, driving a more intense V2-CRF01_AE peptide response.

Notably, the response rate to V2 CRF01_AE in RV144 (52%) was no higher than in the non-protective Vax003 trial (61%). The reactive region in V2 contained position 169 that demonstrated a sieve effect in RV144 [35] and that is critical for the binding of V2-specific Abs from RV144 [33,34], including monoclonal Abs that mediate ADCC activity [36]. Among the reactive V2 peptides, subtype B was the only one lacking K169 (Figure 3), and it was the least reactive with RV144 and Vax003 samples (Figure 4). As noted previously [33], the linear epitope represented in these reactive V2 peptides is located proximal to, but does not span the LDI/V motif that has been shown to mediate gp120 binding to the α4β7 integrin [60].

For the most part, all four groups of subjects showed high response rates across multiple genetic subtypes of the V3 peptides (Figure 4) despite considerable sequence variability within the reactive region of 21 amino acids (Figure 3). An exception was a diminished response to CRF01_AE and subtype D in the three vaccine trials. The relatively low response rates against V3 CRF01_AE in RV144 (25%) and Vax003 (37%) were unexpected because both vaccines were comprised in part of two CRF01_AE gp120 immunogens. The V3 CRF01_AE consensus peptides were clearly reactive because a 100% response rate was seen with samples from HIV-1-infected subjects. Thus, for reasons that are not understood, the CRF01_AE gp120 immunogens elicited stronger IgG responses against non-CRF01_AE V3 peptides than against subtype-matched V3 peptides. Of note, the strongest vaccine-elicited V3 responses were to subtype B consensus peptides, and there was a B subtype gp120 in addition to two CRF01_AE gp120s in both RV144 and Vax003. It is possible that the B subtype gp120 presented the V3 loop more favorably than the CRF01_AE gp120s, driving a more intense V3 subtype B peptide response [34].

A high response rate to C5a was seen only in Vax003 (56-64% response rate) (Figure 4). C5a is a highly conserved peptide (Figure 3), and the response was naturally conserved across all subtypes (Figure 4). Response rates to C5b were highest in Vax004 (70-95%), followed by Vax003 (49-71%) and RV144 (34-60%), with only negligible responses seen in HIV-1-infected subjects (<20%). Minor differences were seen in the response across subtypes, which might be explained by a moderate level of sequence variability in C5b (Figure 3). Response rates to C5c were relatively high in Vax003, Vax004 and HIV-1-infected subjects (25-100%), and were low in RV144 (7-30%). As expected from the low sequence variability in C5c, responses to these peptides were relatively conserved across subtypes. One notable exception was a diminished response against CRF02_AG relative to the other subtypes in all three vaccine trials.

Structures of the major B cell epitopes

Next we evaluated conformational and other physical properties of the major reactive peptide regions in gp120, as the structures of these peptide regions in the context of the gp120 protein may reveal what makes them antigenic. Table 1 shows that all of the reactive regions are predicted to be solvent exposed. Figure 5 shows the conformations of these reactive regions from known structures of the gp120 core or fragments of gp120 solved with bound antibodies. C1a adopt a mostly helical conformation, whereas C5a forms a partially helical conformation (Figure 5A). C1b and C5b mostly exist as a β beta strand structure (Figure 5A). Figure 5B shows that V2, which is from a flexible region of gp120, adopts multiple structures upon binding to antibodies, including β strand, α helix and coil structures [12,36].

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Figure 5. Known conformations of reactive peptides.

A. Conformations of reactive peptides known from solved X-ray structures of gp120 core or fragments of gp120 in complex with antibodies. B. V2 peptide is shown with respect to different conformations it adopts depending on the bound antibody. Structures with antibodies PG9 (PDB: 3U4E), CH 58 (PDB: 4HPO) and CH 59 (PDB: 4HPY) are shown where tan and gray colors indicate the light and heavy chains of the antibody, respectively. C. The CD4 bound structure of gp120 with N-and C- terminal regions is used as a template to show the C1a, C5a, C5b peptides in the context of entire gp120 monomer structure (PDB: 3JWD). Also shown are the CD4 and CCR5 binding regions respect to these peptides. D. NMR structure of isolated region of C-terminal end of gp120 showing C5b and part of C5c peptides (PDB: 1MEQ). E. V3 peptide is shown with respect to the rest of the gp120 core (PDB: 2B4C).

https://doi.org/10.1371/journal.pone.0075665.g005

It is also useful to know whether the peptides are capable of adopting the same conformation when fragmented from the remainder of the gp120 structure. The ability of an isolated fragment to adopt the same conformation as when it is part of gp120 protein may further confirm the antigenicity of that region. At the same time, if the fragmented peptides adopt different structures or become random coils, then it raises the question of why they are reactive. Though the structure of the native gp120 trimer is not known, several three-dimensional structures have been reported for the liganded conformation of gp120 monomers. Most of these monomer structures capture only the gp120 core, which omits the V1, V2 and V3 loops and N- and C-termini. According to a recent study, when the V1V2 domain and gp41 contacts are removed, the native monomer gp120 core adopts a conformation similar to a CD4 bound monomer conformation [61]. In Table 1, we have listed several properties of these reactive peptide regions based on known X-ray structures of liganded gp120 [48-53]. Trends in properties, such as secondary structure and solvent exposure, are consistent among different peptide within a reactive region. A notable exception is the b12-bound structure of C1a(2NY7), which was more solvent exposed, lacked alpha helical structure and contained beta sheet and 3-helix conformations not seen in other representatives of this region.

The C1a and C1b peptides occur in the inner domain of the gp120 core. C1b forms the stem of the V1V2 loop projection at the apex of gp120. Only the C1a peptide occurs in the outer domain of the gp120 core. For each gp120-gp41 heterodimer, the N- and C- termini of gp120 come spatially close together and form the interface to gp41. These regions are conformationally variable and can be influenced by proteins that pack nearby. Recently, a liganded gp120 core structure was solved with N- and C-termini, but lacking the gp41 protein that interacts with this region [52]. We used that structure to highlight the reactive regions corresponding to C1a, C5a and C5b in the context of the gp120 structure (Figure 5C). These regions are not part of the CD4 or CCR5 binding regions. The C1a region is helical in most of the liganded gp120 core structures. However, this region may not be helical in its native conformation, as the inner domain undergoes significant conformational changes. As mentioned above, this region is non-helical in the b12-bound structure of gp120 [51]. In all known structures, C5a is helical (Table 1). It is not known whether the C5a peptide, when fragmented from rest of the gp120 core, adopts a helical structure. However, it appears that the C5b and C5c peptides can adopt different conformations when fragmented from gp120. Mapping of the epitope recognized by human monoclonal Ab 1331A places it in the C5b region, and molecular modeling results suggest it to be a discontinuous epitope in which the amino acids critical for Ab binding are located on opposite sides of the hydrophobic pocket, which is thought to be of importance for the interaction of HIV-gp120 with gp41 [62]. Figure 5D shows the conformation of C5b and part of C5c determined through NMR in a lipid environment [63]. In this case, the fragment is helical, not β stranded as part of gp120. Thus, the C-terminal region, where C5b and C5c are located, can adopt different conformations depending on its environment.

Peptides from variable regions are expected to be flexible in their native environment. Depending on the antibodies that bind to that region or the context of the rest of the gp120 structure, these flexible regions can adopt different conformations. As mentioned above, the reactive V2 peptide region can adopt multiple structures, including a β sheet conformation when bound to PG9 (Figure 5B). The same peptide region takes on helical conformation when bound to antibody CH 58, and it is predominantly random coil when bound to antibody CH 59. This conformational plasticity of V2 peptides is indicative of this region being intrinsically disordered and its conformation being strongly influenced by the binding partners and environment. The conformational plasticity coupled with sequence variation enables the V2 peptide to accommodate multiple binding modes with antibodies. As shown in Table 1, the amount of surface area that takes part in V2 peptide-antibody complex as well as the nature of electrostatic surface potential of V2 seen by the antibodies are similar for CH 58 and CH 59 but different to that of PG9. Even though this region may be disordered in the gp120 monomer, the conformational variability of this region in a gp120 trimer is expected to be restricted due to interaction with neighboring monomers. The reactive V3 peptide region at the crown of the V3 loop (Figure 5E) is also quite flexible. This region takes on β strand–turn–β strand conformation when bound to many anti-V3 monoclonal Abs [64]. Again, it was only possible to determine the structure of V3 peptide when bound to an antibody, indicating that it may be flexible within the gp120 monomer in the absence of antibody. Similar to V2 peptides, V3 is thought to assume a more stable conformation in the context of the native Env trimer.

V2 peptide-specific IgG as a correlate of infection risk in RV144

Among the 17 different types of immune assays and their 152 component variables used to assess correlates of infection risk in RV144, 6 assays were chosen as primary variables for optimal statistical power when adjusting for multiple comparisons [32]. The primary variables included Env-specific plasma IgA, Env-specific plasma IgG binding avidity, gp70-V1V2-specific plasma IgG, neutralizing Abs, ADCC and Env-specific CD4⁺ T cells. The major findings (based on a multivariate model including all six primary variables) were that gp70-V1V2-specific plasma IgG inversely correlated with infection rate (odds ratio 0.57, P=0.03, q=0.08) and that Env-specific plasma IgA was a direct correlate of infection rate (odds ratio 1.54, P=0.03, q=0.08) [32]. The remaining 4 variables showed inverse correlations with infection rate in subjects who had low levels of Env-specific plasma IgA. Also, there was no evidence that the gp70-V1V2 and IgA variables interacted; thus they were independent correlates if risk.

Although IgG responses to C1, V2, V3 and C5 in peptide arrays were part of the primary RV144 correlates study, only aggregate responses across all genetic subtypes within each of these regions were analyzed, and individual subtypes were not considered. In the primary study, IgG responses to all V2 subtypes in aggregate showed a borderline significant inverse correlation with infection risk, whereas no significant association with risk was seen for the C1, V3 and C5 responses [32]. In addition, no interaction analyses were tested between the peptide array data and the six primary variables defined in the main correlates study [32].

We assessed the IgG responses by individual genetic subtype and by aggregate subtypes within each major reactive region of gp120 as correlates of infection risk in RV144. Because the large number of comparisons diminished the robustness of our analysis, we included the 6 primary immune variables and subjected them to the same corrections for multiple tests as a reference. Figure 6 shows the distribution of aggregate V2 and subtype-specific V2 responses in infected and non-infected vaccine recipients. Stronger V2 responses correlated with a lower infection risk in the case of responses to V2.1 (OR=0.62, p=0.014, q=0.24), followed by V2.MC2 (OR=0.66, p=0.027, q=0.24), V2.aggregate (OR= 0.65, p=0.030, q=0.24), and V2.D (OR=0.66, p=0.037, q=0.24) (Table 2). Also, a trend was seen for the response to V2.A (OR=0.70, p=0.060, q=0.24). All five correlations were at least as significant as the correlation seen with the primary gp70-V1V2 variable as assessed by the same univariate model (OR= 0.71, p=0.063, q=0.24). No significant correlation was seen for IgG responses to V2.B, or any subtype of the C1, V3 and C5 peptides, although higher IgG to C5b.A showed a trend toward an increased risk of infection (OR=1.40, p=0.052, q=0.24) (Table 2). After adjusting for IgA level (Table 2), identified correlates became even more significant. Thus, all V2 correlates except V2.B now had q-values <0.15, and the IgA-adjusted V2.1 correlate (OR=0.54, p=0.004, q=0.12) remained more significant than the IgA adjusted gp70-V1V2 correlate (OR=0.63, p=0.02, q=0.13). These results indicate that stronger linear V2-specific IgG responses, especially against V2 CRF01_AE, were associated with a lower risk of HIV-1 infection in RV144.

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Figure 6. Subtype-specific and aggregate V2 responses in RV144.

Boxplots are stratified by infection status for peptides centered at the maximum hotspot region (position 174). Individuals with different risk and gender categories (used in our correlate model) are shown with different symbols and grey shades.

https://doi.org/10.1371/journal.pone.0075665.g006

Associations between peptide-specific IgG and primary immune variables in RV144

We sought to determine whether any peptide-specific IgG variables showed a significant interaction with the primary immune variables in RV144. As shown in Table 3, the V3.1 (CRF01_AE) IgG variable interacted significantly with several primary immune variables, including ADCC (p=0.01), avidity (p=0.002), IgA (p=0.002) and aggregate neutralizing Ab (p=0.0003). In addition, the V3.A, V3.C, V3.D and V3.M IgG variables all showed a significant interaction with aggregate neutralizing Abs (p=0.04, p=0.03, p=0.01, p=0.04, respectively). The V3.2, V3.A and V3.M IgG variables showed a significant interaction with the CD4 variable (p=0.05, p=0.04, p=0.05, respectively), whereas the V3.C and V3.D IgG variables interacted significantly with the IgA variable (p=0.01, p=0.03, respectively). The only other significant interactions were seen with the C1.1 and C1.MABCD2 IgG variables, both of which interacted with the CD4 variable (p=0.05 and p=0.03, respectively). After FDR adjustment, the V3.1 (CRF01_AE) IgG interaction remained significant for avidity (q=0.07), IgA (q=0.07) and aggregate neutralizing Ab (q=0.04) (Table 4). Also, the V3.D IgG interaction remained significant for aggregate neutralizing Ab (q=0.17), whereas a trend was seen for the V3.C IgG interaction with IgA (q=0.21).

V3 peptide-specific IgG as an additional correlate of reduced infection risk in RV144

Because the V3 CRF01_AE (V3.1) IgG response in RV144 interacted with multiple RV144 primary immune variables when predicting infection risk (Tables 3 and 4), we estimated its effect and significance when fixing the value of the interacting variables (Table 5, Figure 7). Higher levels of V3 CRF01_AE-specific IgG showed a significant inverse correlation with infection risk in subjects who were in the lower 20% and 50% of IgA values (OR= 0.31, p=0.002, q=0.02; OR=0.49, p= 0.007, q=0.04, respectively). They also showed an inverse correlation with risk in subjects who were in the lower 20% and 50% of aggregate neutralizing Ab values (OR=0.30, p=0.001, q=0.01; OR= 0.50, p=0.008, q=0.04, respectively), and in subjects who were in the lower 20% of ADCC values (OR=0.54, p=0.032, q=0.10) and avidity values (OR= 0.51, p=0.017, q=0.06). No other significant correlations were seen. These analyses are the first to demonstrate a correlation between V3-specific IgG and the risk of acquiring HIV-1-infection in RV144.

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Figure 7. Complementary cumulative distribution function (ccdf) for V3-CRF01_AE (V3.1) peptide binding in RV144.

The ccdf is broken down by infection status and by dichotomized IgA, neutralizing Ab and Avidity levels. Low/High dichotomized levels were defined by dividing the responses into two equal groups around the median. For a given V3.1 value, the ccdf gives the proportion of individuals who have a response above that value. At low levels of IgA, neutralizing Ab and Avidity, the infected groups have lower ccdf for nearly all values, supporting our correlates analysis. This pattern is inversed at high levels of IgA, neutralizing Ab and Avidity, supporting our interaction analysis.

https://doi.org/10.1371/journal.pone.0075665.g007