Leveraging information across HLA alleles/supertypes improves epitope prediction

HLA-I Associated Adaptation Dampens CD8 T-Cell Responses in HIV Ad5-Vectored Vaccine Recipients

HLA-I-associated human immunodeficiency virus (HIV) adaptation is known to negatively affect disease progression and CD8 T-cell responses. We aimed to assess how HLA-I-associated adaptation affects HIV vaccine-induced CD8 T-cell responses in 2 past vaccine efficacy trials. We found that vaccine-encoded adapted epitopes were less immunogenic than vaccine-encoded nonadapted epitopes, and adapted epitope-specific responses were less polyfunctional than nonadapted epitope-specific responses. Along those lines, vaccine recipients with higher HLA-I adaptation to the Gag vaccine insert mounted less polyfunctional CD8 T-cell responses at the protein level. Breadth of response, which correlated with viral control in recipients who became infected, is also dampened by HLA-I adaptation. These findings suggest that HLA-I-associated adaptation is an important consideration for strategies aiming to induce robust CD8 T-cell responses.

HIV-1 adaptation to NK cell-mediated immune pressure

The observation, by Alter et al., of the enrichment of NK cell "escape" variants in individuals carrying certain Killer-cell Immunoglobulin-like Receptor (KIR) genes is compelling evidence that natural killer (NK) cells exert selection pressure on HIV-1. Alter et al hypothesise that variant peptide, in complex with HLA class I molecules binds KIR receptors and either increases NK cell inhibition or decreases NK cell activation compared to wild type peptide thus leading to virus escape from the NK cell response. According to this hypothesis, in order for NK cells to select for an escape variant, an individual must carry both the KIR and an HLA ligand that binds the variant peptide. In this study we estimate the proportion of the population that is capable of selecting for escape variants and use both epidemiological modelling and a model-free approach to investigate whether this proportion explains the observed variant enrichment. We found that the fraction of individuals within whom the variant would have a selective advantage was low and was unable to explain the high degree of enrichment observed. We conclude that whilst Alter et al's data is consistent with selection pressure, the mechanism that they postulate is unlikely. The importance of this work is two-fold. Firstly, it forces a re-evaluation of some of the clearest evidence that NK cells exert a protective effect in HIV-1 infection. Secondly, it implies that there is a significant aspect of immunology that is not understood: it is possible that KIRs bind much more widely than was previously appreciated; that a gene in linkage with the KIR genes is responsible for considerable peptide-dependent selection or that variant peptides are indirectly impacting KIR ligation.

Allergenicity Assessment of Transgenic Wheat Lines In Silico

Agriculture biotechnology is a promising tool for developing varieties with enhanced quality and quantity. Transgenic proteins expressed by genetically modified (GM) food crops improve crop characteristics like nutritional value, taste, and texture, and endow plants with resistance against fungus, pests, and insects. Despite such potential benefits, there are concerns regarding possible adverse effects of GM crops on human health, animals and the environment. Among the proposed guidelines for GM food safety testing-the weight-of-evidence approach proposed by the Codex Alimentarius Commission (ALINORM 03/34A) is the most recent. Till date, several transgenic wheat lines have been developed and research is underway for further improvement. However, GM wheat is not being grown or consumed in any part of the world. In the present study, in silico tools were employed for safety testing of eight transgenes used for the development of transgenic wheat lines. Among the genes studied, none of them shared sequence homology with the reported allergens and may be safe for use in genetic engineering. In conclusion, gene selection for developing transgenic wheat lines should be done with utmost care to ensure its safety for feed and fodder.

Mark-specific hazard ratio model with missing multivariate marks

An objective of randomized placebo-controlled preventive HIV vaccine efficacy (VE) trials is to assess the relationship between vaccine effects to prevent HIV acquisition and continuous genetic distances of the exposing HIVs to multiple HIV strains represented in the vaccine. The set of genetic distances, only observed in failures, is collectively termed the 'mark.' The objective has motivated a recent study of a multivariate mark-specific hazard ratio model in the competing risks failure time analysis framework. Marks of interest, however, are commonly subject to substantial missingness, largely due to rapid post-acquisition viral evolution. In this article, we investigate the mark-specific hazard ratio model with missing multivariate marks and develop two inferential procedures based on (i) inverse probability weighting (IPW) of the complete cases, and (ii) augmentation of the IPW estimating functions by leveraging auxiliary data predictive of the mark. Asymptotic properties and finite-sample performance of the inferential procedures are presented. This research also provides general inferential methods for semiparametric density ratio/biased sampling models with missing data. We apply the developed procedures to data from the HVTN 502 'Step' HIV VE trial.

Goodness-of-fit test of the stratified mark-specific proportional hazards model with continuous mark

Motivated by the need to assess HIV vaccine efficacy, previous studies proposed an extension of the discrete competing risks proportional hazards model, in which the cause of failure is replaced by a continuous mark only observed at the failure time. However the model assumptions may fail in several ways, and no diagnostic testing procedure for this situation has been proposed. A goodness-of-fit test procedure for the stratified mark-specific proportional hazards model in which the regression parameters depend nonparametrically on the mark and the baseline hazards depends nonparametrically on both time and the mark is proposed. The test statistics are constructed based on the weighted cumulative mark-specific martingale residuals. The critical values of the proposed test statistics are approximated using the Gaussian multiplier method. The performance of the proposed tests are examined extensively in simulations for a variety of the models under the null hypothesis and under different types of alternative models. An analysis of the 'Step' HIV vaccine efficacy trial using the proposed method is presented. The analysis suggests that the HIV vaccine candidate may increase susceptibility to HIV acquisition.

Enhanced Recognition of HIV-1 Cryptic Epitopes Restricted by HLA Class I Alleles Associated With a Favorable Clinical Outcome

BACKGROUND

Cryptic epitopes (CEs) are peptides derived from the translation of 1 or more of the 5 alternative reading frames (ARFs; 2 sense and 3 antisense) of genes. Here, we compared response rates to HIV-1-specific CE predicted to be restricted by HLA-I alleles associated with protection against disease progression to those without any such association.

METHODS

Peptides (9mer to 11mer) were designed based on HLA-I-binding algorithms for B*27, B*57, or B*5801 (protective alleles) and HLA-B*5301 or B*5501 (nonprotective allele) in all 5 ARFs of the 9 HIV-1 encoded proteins. Peptides with >50% probability of being an epitope (n = 231) were tested for T-cell responses in an IFN-γ enzyme-linked immunosorbent spot (ELISpot) assay. Peripheral blood mononuclear cell samples from HIV-1 seronegative donors (n = 42) and HIV-1 seropositive patients with chronic clade B infections (n = 129) were used.

RESULTS

Overall, 16%, 2%, and 2% of chronic HIV infected patients had CE responses by IFN-γ ELISpot in the protective, nonprotective, and seronegative groups, respectively (P = 0.009, Fischer exact test). Twenty novel CE-specific responses were mapped (median magnitude of 95 spot forming cells/10 peripheral blood mononuclear cells), and most were both antisense derived (90%) and represented ARFs of accessory proteins (55%). CE-specific CD8 T cells were multifunctional and proliferated when assessed by intracellular cytokine staining.

CONCLUSIONS

CE responses were preferentially restricted by the protective HLA-I alleles in HIV-1 infection, suggesting that they may contribute to viral control in this group of patients.

Machine Learning Methods for Predicting HLA-Peptide Binding Activity

As major histocompatibility complexes in humans, the human leukocyte antigens (HLAs) have important functions to present antigen peptides onto T-cell receptors for immunological recognition and responses. Interpreting and predicting HLA–peptide binding are important to study T-cell epitopes, immune reactions, and the mechanisms of adverse drug reactions. We review different types of machine learning methods and tools that have been used for HLA–peptide binding prediction. We also summarize the descriptors based on which the HLA–peptide binding prediction models have been constructed and discuss the limitation and challenges of the current methods. Lastly, we give a future perspective on the HLA–peptide binding prediction method based on network analysis.

Immune screening identifies novel T cell targets encoded by antisense reading frames of HIV-1

Cytotoxic-T lymphocyte (CTL) responses to epitopes in alternative HIV reading frames have been reported. However, the extent of CTL responses to putative proteins encoded in antisense reading frames is unknown. Using sequence alignments and computational approaches, we here predict five potential antisense HIV proteins and characterize common CTL responses against them. Results suggest that antisense-derived sequences are commonly transcribed and translated and could encode functional proteins that contain important targets of anti-HIV cellular immunity.

Comparison of experimental fine-mapping to in silico prediction results of HIV-1 epitopes reveals ongoing need for mapping experiments

Methods for identifying physiologically relevant CD8 T-cell epitopes are critically important not only for the development of T-cell-based vaccines but also for understanding host-pathogen interactions. As experimentally mapping an optimal CD8 T-cell epitope is a tedious procedure, many bioinformatic tools have been developed that predict which peptides bind to a given MHC molecule. We assessed the ability of the CD8 T-cell epitope prediction tools syfpeithi, ctlpred and iedb to foretell nine experimentally mapped optimal HIV-specific epitopes. Randomly - for any of the subjects' HLA type and with any matching score - the optimal epitope was predicted in seven of nine epitopes using syfpeithi, in three of nine epitopes using ctlpred and in all nine of nine epitopes using iedb. The optimal epitope within the three highest ranks was given in four of nine epitopes applying syfpeithi, in two of nine epitopes applying ctlpred and in seven of nine epitopes applying iedb when screening for all of the subjects' HLA types. Knowing the HLA restriction of the peptide of interest improved the ranking of the optimal epitope within the predicted results. Epitopes restricted by common HLA alleles were more likely to be predicted than those restricted by uncommon HLA alleles. Epitopes with aberrant lengths compared with the usual HLA-class I nonamers were most likely not predicted. Application of epitope prediction tools together with literature searches for already described optimal epitopes narrows down the possibilities of optimal epitopes within a screening peptide of interest. However, in our opinion, the actual fine-mapping of a CD8 T-cell epitope cannot yet be replaced.

Differential T-cell responses of semi-immune and susceptible malaria subjects to in silico predicted and synthetic peptides of Plasmodium falciparum

Malaria remains a public health hazard in tropical countries as a consequence of the rise and spread of drug and insecticide resistances; hence the need for a vaccine with widespread application. Protective immunity to malaria is known to be mediated by both antibody and cellular immune responses, though characterization of the latter has been less extensive. The aim of the present investigation was to identify novel T-cell epitopes that may contribute to naturally acquired immune responses against malaria. Using the Microsoft software, Epitome™ T-cell peptide epitopes on 19 Plasmodium falciparum proteins in the Plasmodium Database (www.plasmodb.org.PlasmoDB 9.0) were predicted in-silico. The peptides were synthesized and used to stimulate peripheral blood mononuclear cells (PBMCs) in 14 semi-immune and 21 malaria susceptible subjects for interferon-gamma (IFN-γ) production ex-vivo. The level of IFN-γ production, a marker of T-cell responses, was measured by ELISPOT assay in semi-immune subjects (SIS) and frequently sick subjects (FSS) from an endemic zone with perennial malaria transmission. Of the 19 proteins studied, 17 yielded 27 pools (189 peptides), which were reactive with the subjects' PBMCs when tested for IFN-γ production, taking a stimulation index (SI) of ≥2 as a cutoff point for a positive response. There were 10 reactive peptide pools (constituting eight protein loci) with an SI of 10 or greater. Of the 19 proteins studied, two were known vaccine candidates (MSP-8 and SSP2/TRAP), which reacted both with SIS and FSS. Similarly the hypothetical proteins (PFF1030w, PFE0795c, PFD0880w, PFC0065c and PF10_0052) also reacted strongly with both SIS and FSS making them attractive for further characterization as mediators of protective immunity and/or pathogenesis.

Deep sequencing of viral genomes provides insight into the evolution and pathogenesis of varicella zoster virus and its vaccine in humans

Immunization with the vOka vaccine prevents varicella (chickenpox) in children and susceptible adults. The vOka vaccine strain comprises a mixture of genotypes and, despite attenuation, causes rashes in small numbers of recipients. Like wild-type virus, the vaccine establishes latency in neuronal tissue and can later reactivate to cause Herpes zoster (shingles). Using hybridization-based methodologies, we have purified and sequenced vOka directly from skin lesions. We show that alleles present in the vaccine can be recovered from the lesions and demonstrate the presence of a severe bottleneck between inoculation and lesion formation. Genotypes in any one lesion appear to be descended from one to three vaccine-genotypes with a low frequency of novel mutations. No single vOka haplotype and no novel mutations are consistently present in rashes, indicating that neither new mutations nor recombination with wild type are critical to the evolution of vOka rashes. Instead, alleles arising from attenuation (i.e., not derived from free-living virus) are present at lower frequencies in rash genotypes. We identify 11 loci at which the ancestral allele is selected for in vOka rash formation and show genotypes in rashes that have reactivated from latency cannot be distinguished from rashes occurring immediately after inoculation. We conclude that the vOka vaccine, although heterogeneous, has not evolved to form rashes through positive selection in the mode of a quasispecies, but rather alleles that were essentially neutral during the vaccine production have been selected against in the human subjects, allowing us to identify key loci for rash formation.

Influence of HLA-C expression level on HIV control

A variant upstream of human leukocyte antigen C (HLA-C) shows the most significant genome-wide effect on HIV control in European Americans and is also associated with the level of HLA-C expression. We characterized the differential cell surface expression levels of all common HLA-C allotypes and tested directly for effects of HLA-C expression on outcomes of HIV infection in 5243 individuals. Increasing HLA-C expression was associated with protection against multiple outcomes independently of individual HLA allelic effects in both African and European Americans, regardless of their distinct HLA-C frequencies and linkage relationships with HLA-B and HLA-A. Higher HLA-C expression was correlated with increased likelihood of cytotoxic T lymphocyte responses and frequency of viral escape mutation. In contrast, high HLA-C expression had a deleterious effect in Crohn's disease, suggesting a broader influence of HLA expression levels in human disease.

HIV escape mutations occur preferentially at HLA-binding sites of CD8 T-cell epitopes

OBJECTIVE

To define the relative frequencies of different mechanisms of viral escape.

DESIGN

A population-based approach to examine the distribution of HIV polymorphism associated with diverse population human leucocyte antigens (HLAs) at sites within and flanking CD8 T-cell epitopes as a correlate of likely mechanisms of viral escape.

METHODS

Sequence windows surrounding 874 HLA allele-specific polymorphisms across the full HIV-1 proteomic consensus sequence were scanned by an epitope-prediction programme. Either already known or probable CD8 T-cell epitopes with HLA restriction matching that of the proximal HLA association were identified and synthesized. These peptides were used as stimulating antigens in automated enzyme-linked immunospot (ELISpot) assays. Peptide arrays were customized to each individual based on their HLA genotype.

RESULTS

Among HLA-associated HIV polymorphisms detected in the viral sequences of a cohort of 800 individuals with chronic subtype B HIV infection, those which were likely to affect HLA peptide binding were significantly more common than polymorphisms at nonanchor HLA binding sites. HIV epitopes with such polymorphisms were associated with reduced IFNγ responses in ELISpot assays. HIV escape at sites affecting T-cell receptor (TCR) engagement and epitope processing were also evident.

CONCLUSION

HIV escape from HLA-peptide binding predominates as an effective viral evasion strategy and therefore has implications for inclusion of HLA-adapted epitopes in vaccine immunogens.

tat Exon 1 exhibits functional diversity during HIV-1 subtype C primary infection

Human immunodeficiency virus type 1 (HIV-1) Tat is a mediator of viral transcription and is involved in the control of virus replication. However, associations between HIV-1 Tat diversity and functional effects during primary HIV-1 infection are still unclear. We estimated selection pressures in tat exon 1 using the mixed-effects model of evolution with 672 viral sequences generated from 20 patients infected with HIV-1 subtype C (HIV-1C) over 500 days postseroconversion. tat exon 1 residues 3, 4, 21, 24, 29, 39, and 68 were under positive selection, and we established that specific amino acid signature patterns were apparent in primary HIV-1C infection compared with chronic infection. We assessed the impact of these mutations on long terminal repeat (LTR) activity and found that Tat activity was negatively affected by the Ala(21) substitution identified in 13/20 (65%) of patients, which reduced LTR activity by 88% (± 1%) (P < 0.001). The greatest increase in Tat activity was seen with the Gln(35)/Lys(39) double mutant that resulted in an additional 49% (± 14%) production of LTR-driven luciferase (P = 0.012). There was a moderate positive correlation between Tat-mediated LTR activity and HIV-1 RNA in plasma (P = 0.026; r = 0.400) after 180 days postseroconversion that was reduced by 500 days postseroconversion (P = 0.043; r = 0.266). Although Tat activation of the LTR is not a strong predictor of these clinical variables, there are significant linear relationships between Tat transactivation and patients' plasma viral loads and CD4 counts, highlighting the complex interplay between Tat mutations in early HIV-1C infection.

MRKAd5 HIV-1 Gag/Pol/Nef vaccine-induced T-cell responses inadequately predict distance of breakthrough HIV-1 sequences to the vaccine or viral load

Background

The sieve analysis for the Step trial found evidence that breakthrough HIV-1 sequences for MRKAd5/HIV-1 Gag/Pol/Nef vaccine recipients were more divergent from the vaccine insert than placebo sequences in regions with predicted epitopes. We linked the viral sequence data with immune response and acute viral load data to explore mechanisms for and consequences of the observed sieve effect.

Methods

Ninety-one male participants (37 placebo and 54 vaccine recipients) were included; viral sequences were obtained at the time of HIV-1 diagnosis. T-cell responses were measured 4 weeks post-second vaccination and at the first or second week post-diagnosis. Acute viral load was obtained at RNA-positive and antibody-negative visits.

Findings

Vaccine recipients had a greater magnitude of post-infection CD8+ T cell response than placebo recipients (median 1.68% vs 1.18%; p = 0·04) and greater breadth of post-infection response (median 4.5 vs 2; p = 0·06). Viral sequences for vaccine recipients were marginally more divergent from the insert than placebo sequences in regions of Nef targeted by pre-infection immune responses (p = 0·04; Pol p = 0·13; Gag p = 0·89). Magnitude and breadth of pre-infection responses did not correlate with distance of the viral sequence to the insert (p>0·50). Acute log viral load trended lower in vaccine versus placebo recipients (estimated mean 4·7 vs 5·1) but the difference was not significant (p = 0·27). Neither was acute viral load associated with distance of the viral sequence to the insert (p>0·30).

Interpretation

Despite evidence of anamnestic responses, the sieve effect was not well explained by available measures of T-cell immunogenicity. Sequence divergence from the vaccine was not significantly associated with acute viral load. While point estimates suggested weak vaccine suppression of viral load, the result was not significant and more viral load data would be needed to detect suppression.

Mark-specific proportional hazards model with multivariate continuous marks and its application to HIV vaccine efficacy trials

For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates (Prentice and others, 1978. The analysis of failure time in the presence of competing risks. Biometrics 34, 541-554). Inspired by previous research in HIV vaccine efficacy trials, the cause of failure is replaced by a continuous mark observed only in subjects who fail. This article studies an extension of this approach to allow a multivariate continuum of competing risks, to better account for the fact that the candidate HIV vaccines tested in efficacy trials have contained multiple HIV sequences, with a purpose to elicit multiple types of immune response that recognize and block different types of HIV viruses. We develop inference for the proportional hazards model in which the regression parameters depend parametrically on the marks, to avoid the curse of dimensionality, and the baseline hazard depends nonparametrically on both time and marks. Goodness-of-fit tests are constructed based on generalized weighted martingale residuals. The finite-sample performance of the proposed methods is examined through extensive simulations. The methods are applied to a vaccine efficacy trial to examine whether and how certain antigens represented inside the vaccine are relevant for protection or anti-protection against the exposing HIVs.

Predictions versus high-throughput experiments in T-cell epitope discovery: competition or synergy?

Prediction methods as well as experimental methods for T-cell epitope discovery have developed significantly in recent years. High-throughput experimental methods have made it possible to perform full-length protein scans for epitopes restricted to a limited number of MHC alleles. The high costs and limitations regarding the number of proteins and MHC alleles that are feasibly handled by such experimental methods have made in silico prediction models of high interest. MHC binding prediction methods are today of a very high quality and can predict MHC binding peptides with high accuracy. This is possible for a large range of MHC alleles and relevant length of binding peptides. The predictions can easily be performed for complete proteomes of any size. Prediction methods are still, however, dependent on good experimental methods for validation, and should merely be used as a guide for rational epitope discovery. We expect prediction methods as well as experimental validation methods to continue to develop and that we will soon see clinical trials of products whose development has been guided by prediction methods.

Uncommon pathways of immune escape attenuate HIV-1 integrase replication capacity

An attenuation of the HIV-1 replication capacity (RC) has been observed for immune-mediated escape mutations in Gag restricted by protective HLA alleles. However, the extent to which escape mutations affect other viral proteins during natural infection is not well understood. We generated recombinant viruses encoding plasma HIV-1 RNA integrase sequences from antiretroviral-naïve individuals with early (n = 88) and chronic (n = 304) infections and measured the in vitro RC of each. In contrast to data from previous studies of Gag, we observed little evidence that host HLA allele expression was associated with integrase RC. A modest negative correlation was observed between the number of HLA-B-associated integrase polymorphisms and RC in chronic infection (R = -0.2; P = 0.003); however, this effect was not driven by mutations restricted by protective HLA alleles. Notably, the integrase variants S119R, G163E, and I220L, which represent uncommon polymorphisms associated with HLA-C*05, -A*33, and -B*52, respectively, correlated with lower RC (all q < 0.2). We identified a novel C*05-restricted epitope (HTDNGSNF(114-121)) that likely contributes to the selection of the S119R variant, the polymorphism most significantly associated with lower RC in patient sequences. An NL4-3 mutant encoding the S119R polymorphism displayed a ~35%-reduced function that was rescued by a single compensatory mutation of A91E. Together, these data indicate that substantial HLA-driven attenuation of integrase is not a general phenomenon during HIV-1 adaptation to host immunity. However, uncommon polymorphisms selected by HLA alleles that are not conventionally regarded to be protective may be associated with impaired protein function. Vulnerable epitopes in integrase might therefore be considered for future vaccine strategies.

Minor contribution of HLA class I-associated selective pressure to the variability of HIV-1 accessory protein Vpu

Host HLA class I (HLA-I) allele-associated immune responses are major forces driving the evolution of HIV-1 proteins such as Gag and Nef. The viral protein U (Vpu) is an HIV-1 accessory protein responsible for CD4 degradation and enhancement of virion release by antagonizing tetherin/CD317. Although Vpu represents one of the most variable proteins in the HIV-1 proteome, it is still not clear to what extent HLA-I influence its evolution. To examine this issue, we enrolled 240 HLA-I-typed, treatment naïve, chronically HIV-infected subjects in Japan, and analyzed plasma HIV RNA nucleotide sequences of the vpu region. Using a phylogenetically-informed method incorporating corrections for HIV codon covariation and linkage disequilibrium among HLA alleles, we investigated HLA-associated amino acid mutations in the Vpu protein as well as in the translational products encoded by alternative reading frames. Despite substantial amino acid variability in Vpu, we identified only 4 HLA-associations in all possible translational products encoded in this region, suggesting that HLA-associated immune responses had minor effects on Vpu variability in this cohort. Rather, despite its size (81 amino acids), Vpu showed 103 codon-codon covariation associations, suggesting that Vpu conformation and function are preserved through many possible combinations of primary and secondary polymorphisms. Taken together, our study suggests that Vpu has been comparably less influenced by HLA-I-associated immune-driven evolution at the population level compared to other highly variable HIV-1 accessory proteins.

The efficiency of the human CD8+ T cell response: how should we quantify it, what determines it, and does it matter?

Multidisciplinary techniques, in particular the combination of theoretical and experimental immunology, can address questions about human immunity that cannot be answered by other means. From the turnover of virus-infected cells in vivo, to rates of thymic production and HLA class I epitope prediction, theoretical techniques provide a unique insight to supplement experimental approaches. Here we present our opinion, with examples, of some of the ways in which mathematics has contributed in our field of interest: the efficiency of the human CD8+ T cell response to persistent viruses.

Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools

Binding of short antigenic peptides to major histocompatibility complex (MHC) molecules is a core step in adaptive immune response. Precise identification of MHC-restricted peptides is of great significance for understanding the mechanism of immune response and promoting the discovery of immunogenic epitopes. However, due to the extremely high MHC polymorphism and huge cost of biochemical experiments, there is no experimentally measured binding data for most MHC molecules. To address the problem of predicting peptides binding to these MHC molecules, recently computational approaches, called pan-specific methods, have received keen interest. Pan-specific methods make use of experimentally obtained binding data of multiple alleles, by which binding peptides (binders) of not only these alleles but also those alleles with no known binders can be predicted. To investigate the possibility of further improvement in performance and usability of pan-specific methods, this article extensively reviews existing pan-specific methods and their web servers. We first present a general framework of pan-specific methods. Then, the strategies and performance as well as utilities of web servers are compared. Finally, we discuss the future direction to improve pan-specific methods for MHC-peptide binding prediction.

Translation of HLA-HIV associations to the cellular level: HIV adapts to inflate CD8 T cell responses against Nef and HLA-adapted variant epitopes

Strong statistical associations between polymorphisms in HIV-1 population sequences and carriage of HLA class I alleles have been widely used to identify possible sites of CD8 T cell immune selection in vivo. However, there have been few attempts to prospectively and systematically test these genetic hypotheses arising from population-based studies at a cellular, functional level. We assayed CD8 T cell epitope-specific IFN-γ responses in 290 individuals from the same cohort, which gave rise to 874 HLA-HIV associations in genetic analyses, taking into account autologous viral sequences and individual HLA genotypes. We found immunological evidence for 58% of 374 associations tested as sites of primary immune selection and identified up to 50 novel HIV-1 epitopes using this reverse-genomics approach. Many HLA-adapted epitopes elicited equivalent or higher-magnitude IFN-γ responses than did the nonadapted epitopes, particularly in Nef. At a population level, inclusion of all of the immunoreactive variant CD8 T cell epitopes in Gag, Pol, Nef, and Env suggested that HIV adaptation leads to an inflation of Nef-directed immune responses relative to other proteins. We concluded that HLA-HIV associations mark viral epitopes subject to CD8 T cell selection. These results can be used to guide functional studies of specific epitopes and escape mutations, as well as to test, train, and evaluate analytical models of viral escape and fitness. The inflation of Nef and HLA-adapted variant responses may have negative effects on natural and vaccine immunity against HIV and, therefore, has implications for diversity coverage approaches in HIV vaccine design.

Demographic processes affect HIV-1 evolution in primary infection before the onset of selective processes

HIV-1 transmission and viral evolution in the first year of infection were studied in 11 individuals representing four transmitter-recipient pairs and three independent seroconverters. Nine of these individuals were enrolled during acute infection; all were men who have sex with men (MSM) infected with HIV-1 subtype B. A total of 475 nearly full-length HIV-1 genome sequences were generated, representing on average 10 genomes per specimen at 2 to 12 visits over the first year of infection. Single founding variants with nearly homogeneous viral populations were detected in eight of the nine individuals who were enrolled during acute HIV-1 infection. Restriction to a single founder variant was not due to a lack of diversity in the transmitter as homogeneous populations were found in recipients from transmitters with chronic infection. Mutational patterns indicative of rapid viral population growth dominated during the first 5 weeks of infection and included a slight contraction of viral genetic diversity over the first 20 to 40 days. Subsequently, selection dominated, most markedly in env and nef. Mutants were detected in the first week and became consensus as early as day 21 after the onset of symptoms of primary HIV infection. We found multiple indications of cytotoxic T lymphocyte (CTL) escape mutations while reversions appeared limited. Putative escape mutations were often rapidly replaced with mutually exclusive mutations nearby, indicating the existence of a maturational escape process, possibly in adaptation to viral fitness constraints or to immune responses against new variants. We showed that establishment of HIV-1 infection is likely due to a biological mechanism that restricts transmission rather than to early adaptive evolution during acute infection. Furthermore, the diversity of HIV strains coupled with complex and individual-specific patterns of CTL escape did not reveal shared sequence characteristics of acute infection that could be harnessed for vaccine design.

Variable HIV peptide stability in human cytosol is critical to epitope presentation and immune escape

Induction of virus-specific CD8⁺ T cell responses is critical for the success of vaccines against chronic viral infections. Despite the large number of potential MHC-I-restricted epitopes located in viral proteins, MHC-I-restricted epitope generation is inefficient, and factors defining the production and presentation of MHC-I-restricted viral epitopes are poorly understood. Here, we have demonstrated that the half-lives of HIV-derived peptides in cytosol from primary human cells were highly variable and sequence dependent, and significantly affected the efficiency of cell recognition by CD8⁺ T cells. Furthermore, multiple clinical isolates of HLA-associated HIV epitope variants displayed reduced half-lives relative to consensus sequence. This decreased cytosolic peptide stability diminished epitope presentation and CTL recognition, illustrating a mechanism of immune escape. Chaperone complexes including Hsp90 and histone deacetylase HDAC6 enhanced peptide stability by transient protection from peptidase degradation. Based on empirical results with 166 peptides, we developed a computational approach utilizing a sequence-based algorithm to estimate the cytosolic stability of antigenic peptides. Our results identify sequence motifs able to alter the amount of peptide available for loading onto MHC-I, suggesting potential new strategies to modulate epitope production from vaccine immunogens.

Large-scale characterization of peptide-MHC binding landscapes with structural simulations

Class I major histocompatibility complex proteins play a critical role in the adaptive immune system by binding to peptides derived from cytosolic proteins and presenting them on the cell surface for surveillance by T cells. The varied peptide binding specificity of these highly polymorphic molecules has important consequences for vaccine design, transplantation, autoimmunity, and cancer development. Here, we describe a molecular modeling study of MHC-peptide interactions that integrates sampling techniques from protein-protein docking, loop modeling, de novo structure prediction, and protein design in order to construct atomically detailed peptide binding landscapes for a diverse set of MHC proteins. Specificity profiles derived from these landscapes recover key features of experimental binding profiles and can be used to predict peptide binding with reasonable accuracy. Family wide comparison of the predicted binding landscapes recapitulates previously reported patterns of specificity divergence and peptide-repertoire diversity while providing a structural basis for observed specificity patterns. The size and sequence diversity of these structure-based binding landscapes enable us to identify subtle patterns of covariation between peptide sequence positions; analysis of the associated structural models suggests physical interactions that may mediate these sequence correlations.

Genetic impact of vaccination on breakthrough HIV-1 sequences from the STEP trial

We analyzed HIV-1 genome sequences from 68 newly-infected volunteers in the Step HIV-1 vaccine trial. To determine whether the vaccine exerted selective T-cell pressure on breakthrough viruses, we identified potential T-cell epitopes in the founder sequences and compared them to epitopes in the vaccine. We found greater distances for sequences from vaccine recipients than from placebo recipients (p-values ranging from < 0.0001 to 0.09). The most significant signature site distinguishing vaccine from placebo recipients was Gag-84, a site encompassed by several epitopes contained in the vaccine and restricted by HLA alleles common in the cohort. Moreover, the extended divergence was confined to the vaccine components of the virus (Gag, Pol, Nef) and not found in other HIV-1 proteins. These results represent the first evidence of selective pressure from vaccine-induced T-cell responses on HIV-1 infection.

MHC-I prediction using a combination of T cell epitopes and MHC-I binding peptides

We propose a novel learning method that combines multiple experimental modalities to improve the MHC Class-I binding prediction. Multiple experimental modalities are often accessible in the context of a binding problem. Such modalities can provide different labels of data, such as binary classifications, affinity measurements, or direct estimations of the binding profile. Current machine learning algorithms usually focus on a given label type. We here present a novel Multi-Label Vector Optimization (MLVO) formalism to produce classifiers based on the simultaneous optimization of multiple labels. Within this methodology, all label types are combined into a single constrained quadratic dual optimization problem. We apply the MLVO to MHC class-I epitope prediction. We combine affinity measurements (IC50/EC50), binary classifications of epitopes as T cell activators and existing algorithms. The multi-label vector optimization algorithms produce classifiers significantly better than the ones resulting from any of its components. These matrix based classifiers are better or equivalent to the existing state of the art MHC-I epitope prediction tools in the studied alleles.

HLA class I binding of HBZ determines outcome in HTLV-1 infection

CD8(+) T cells can exert both protective and harmful effects on the virus-infected host. However, there is no systematic method to identify the attributes of a protective CD8(+) T cell response. Here, we combine theory and experiment to identify and quantify the contribution of all HLA class I alleles to host protection against infection with a given pathogen. In 432 HTLV-1-infected individuals we show that individuals with HLA class I alleles that strongly bind the HTLV-1 protein HBZ had a lower proviral load and were more likely to be asymptomatic. We also show that in general, across all HTLV-1 proteins, CD8(+) T cell effectiveness is strongly determined by protein specificity and produce a ranked list of the proteins targeted by the most effective CD8(+) T cell response through to the least effective CD8(+) T cell response. We conclude that CD8(+) T cells play an important role in the control of HTLV-1 and that CD8(+) cells specific to HBZ, not the immunodominant protein Tax, are the most effective. We suggest that HBZ plays a central role in HTLV-1 persistence. This approach is applicable to all pathogens, even where data are sparse, to identify simultaneously the HLA Class I alleles and the epitopes responsible for a protective CD8(+) T cell response.

Exploiting knowledge of immune selection in HIV-1 to detect HIV-specific CD8 T-cell responses

Since HLA-restricted cytotoxic T-cell responses select specific polymorphisms in HIV-1 sequences and HLA diversity is relatively static in human populations, we investigated the use of peptide epitopes based on sites of HLA-associated adaptation in HIV-1 sequences to stimulate and detect T-cell responses ex vivo. These "HLA-optimised" peptides captured more HIV-1 Nef-specific responses compared with overlapping peptides of a single consensus sequence, in interferon-gamma enzyme linked immunospot assays. Sites of immune selection can reveal more immunogenic epitopes in HLA-diverse populations and offer insights into the nature of HLA-epitope targeting, which could be applied in vaccine design.

Major histocompatibility complex class I binding predictions as a tool in epitope discovery

SUMMARY

Over the last decade, in silico models of the major histocompatibility complex (MHC) class I pathway have developed significantly. Before, peptide binding could only be reliably modelled for a few major human or mouse histocompatibility molecules; now, high-accuracy predictions are available for any human leucocyte antigen (HLA) -A or -B molecule with known protein sequence. Furthermore, peptide binding to MHC molecules from several non-human primates, mouse strains and other mammals can now be predicted. In this review, a number of different prediction methods are briefly explained, highlighting the most useful and historically important. Selected case stories, where these 'reverse immunology' systems have been used in actual epitope discovery, are briefly reviewed. We conclude that this new generation of epitope discovery systems has become a highly efficient tool for epitope discovery, and recommend that the less accurate prediction systems of the past be abandoned, as these are obsolete.

Adaptive interactions between HLA and HIV-1: highly divergent selection imposed by HLA class I molecules with common supertype motifs

Currently, 1.1 million individuals in the United States are living with HIV-1 infection. Although this is a relatively small proportion of the global pandemic, the remarkable mix of ancestries in the United States, drawn together over the past two centuries of continuous population migrations, provides an important and unique perspective on adaptive interactions between HIV-1 and human genetic diversity. HIV-1 is a rapidly adaptable organism and mutates within or near immune epitopes that are determined by the HLA class I genotype of the infected host. We characterized HLA-associated polymorphisms across the full HIV-1 proteome in a large, ethnically diverse national United States cohort of HIV-1-infected individuals. We found a striking divergence in the immunoselection patterns associated with HLA variants that have very similar or identical peptide-binding specificities but are differentially distributed among racial/ethnic groups. Although their similarity in peptide binding functionally clusters these HLA variants into supertypes, their differences at sites within the peptide-binding groove contribute to race-specific selection effects on circulating HIV-1 viruses. This suggests that the interactions between the HLA/HIV peptide complex and the TCR vary significantly within HLA supertype groups, which, in turn, influences HIV-1 evolution.

Effects of HIV type-1 immune selection on susceptability to integrase inhibitor resistance

BACKGROUND

All site-specific interactions between HIV type-1 (HIV-1) subtype, human leukocyte antigen (HLA)-associated immune selection and integrase inhibitor resistance are not completely understood. We examined naturally occurring polymorphisms in HIV-1 integrase sequences from 342 antiretroviral-naive individuals from the Western Australian HIV Cohort Study and the Swiss HIV Cohort Study.

METHODS

Standard bulk sequencing and sequence-based typing were used to generate integrase sequences and high-resolution HLA genotypes, respectively. Viral residues were examined with respect to drug resistance mutations and CD8(+) T-cell escape mutations.

RESULTS

In both predominantly subtype B cohorts, 12 of 38 sites that mediate integrase inhibitor resistance mutations were absolutely conserved, and these included the primary resistance mutations. There were 18 codons with non-primary drug resistance-associated substitutions at rates of up to 58.8% and eight sites with alternative polymorphisms. Five viral residues were potentially subject to dual-drug and HLA-associated immune selection in which both selective pressures either drove the same amino acid substitution (codons 72, 157 and 163) or HLA alleles were associated with an alternative polymorphism that would alter the genetic barrier to resistance (codons 125 and 193). The common polymorphism T125A, which was characteristic of non-subtype B and was also associated with carriage of HLA-B*57/*5801, increased the mutational barrier to the resistance mutation T125K.

CONCLUSIONS

Primary integrase inhibitor resistance mutations were not detected in the absence of drug exposure in keeping with sites of high constraint. Viral polymorphisms caused by immune selection and/or associated with non-subtype B might alter the genetic barrier to some non-primary resistance-associated mutations.

Epitope discovery with phylogenetic hidden Markov models

Existing methods for the prediction of immunologically active T-cell epitopes are based on the amino acid sequence or structure of pathogen proteins. Additional information regarding the locations of epitopes may be acquired by considering the evolution of viruses in hosts with different immune backgrounds. In particular, immune-dependent evolutionary patterns at sites within or near T-cell epitopes can be used to enhance epitope identification. We have developed a mutation-selection model of T-cell epitope evolution that allows the human leukocyte antigen (HLA) genotype of the host to influence the evolutionary process. This is one of the first examples of the incorporation of environmental parameters into a phylogenetic model and has many other potential applications where the selection pressures exerted on an organism can be related directly to environmental factors. We combine this novel evolutionary model with a hidden Markov model to identify contiguous amino acid positions that appear to evolve under immune pressure in the presence of specific host immune alleles and that therefore represent potential epitopes. This phylogenetic hidden Markov model provides a rigorous probabilistic framework that can be combined with sequence or structural information to improve epitope prediction. As a demonstration, we apply the model to a data set of HIV-1 protein-coding sequences and host HLA genotypes.

Immunoinformatics and modeling perspective of T cell epitope-based cancer immunotherapy: a holistic picture

Cancer immunotherapy is fast gaining global attention with its unique position as a potential therapy showing promise in cancer prevention and cure. It utilizes the natural system of immunity as opposed to chemotherapy and radiotherapy that utilize chemical drugs and radiation, respectively. Cancer immunotherapy essentially involves treatment and/or prevention with vaccines in the form of peptide vaccines (T and B cell epitopes), DNA vaccines and vaccination using whole tumor cells, dendritic cells, viral vectors, antibodies and adoptive transfer of T cells to harness the body's own immune system towards the targeting of cancer cells for destruction. Given the time, cost and labor involved in the vaccine discovery and development, researchers have evinced interest in the novel field of immunoinformatics to cut down the escalation of these critical resources. Immunoinformatics is a relatively new buzzword in the scientific circuit that is showing its potential and delivering on its promise in expediting the development of effective cancer immunotherapeutic agents. This review attempts to present a holistic picture of our race against cancer and time using the science and technology of immunoinformatics and molecular modeling in T cell epitope-based cancer immunotherapy. It also attempts to showcase some problem areas as well as novel ones waiting to be explored where development of novel immunoinformatics tools and simulations in the context of cancer immunotherapy would be highly welcome.

Viral adaptation to immune selection pressure by HLA class I-restricted CTL responses targeting epitopes in HIV frameshift sequences

CD8+ cytotoxic T lymphocyte (CTL)-mediated immune responses to HIV contribute to viral control in vivo. Epitopes encoded by alternative reading frame (ARF) peptides may be targeted by CTLs as well, but their frequency and in vivo relevance are unknown. Using host genetic (human leukocyte antigen [HLA]) and plasma viral sequence information from 765 HIV-infected subjects, we identified 64 statistically significant (q<0.2) associations between specific HLA alleles and sequence polymorphisms in alternate reading frames of gag, pol, and nef that did not affect the regular frame protein sequence. Peptides spanning the top 20 HLA-associated imprints were used to test for ex vivo immune responses in 85 HIV-infected subjects and showed responses to 10 of these ARF peptides. The most frequent response recognized an HLA-A*03-restricted +2 frame-encoded epitope containing a unique A*03-associated polymorphism at position 6. Epitope-specific CTLs efficiently inhibited viral replication in vitro when viruses containing the wild-type sequence but not the observed polymorphism were tested. Mutating alternative internal start codons abrogated the CTL-mediated inhibition of viral replication. These data indicate that responses to ARF-encoded HIV epitopes are induced during natural infection, can contribute to viral control in vivo, and drive viral evolution on a population level.

CD8 T cell response and evolutionary pressure to HIV-1 cryptic epitopes derived from antisense transcription

Retroviruses pack multiple genes into relatively small genomes by encoding several genes in the same genomic region with overlapping reading frames. Both sense and antisense HIV-1 transcripts contain open reading frames for known functional proteins as well as numerous alternative reading frames (ARFs). At least some ARFs have the potential to encode proteins of unknown function, and their antigenic properties can be considered as cryptic epitopes (CEs). To examine the extent of active immune response to virally encoded CEs, we analyzed human leukocyte antigen class I–associated polymorphisms in HIV-1 gag, pol, and nef genes from a large cohort of South Africans with chronic infection. In all, 391 CEs and 168 conventional epitopes were predicted, with the majority (307; 79%) of CEs derived from antisense transcripts. In further evaluation of CD8 T cell responses to a subset of the predicted CEs in patients with primary or chronic infection, both sense- and antisense-encoded CEs were immunogenic at both stages of infection. In addition, CEs often mutated during the first year of infection, which was consistent with immune selection for escape variants. These findings indicate that the HIV-1 genome might encode and deploy a large potential repertoire of unconventional epitopes to enhance vaccine-induced antiviral immunity.

Towards in silico design of epitope-based vaccines

BACKGROUND

Epitope-based vaccines (EVs) make use of immunogenic peptides (epitopes) to trigger an immune response. Due to their manifold advantages, EVs have recently been attracting growing interest. The success of an EV is determined by the choice of epitopes used as a basis. However, the experimental discovery of candidate epitopes is expensive in terms of time and money. Furthermore, for the final choice of epitopes various immunological requirements have to be considered.

METHODS

Numerous in silico approaches exist that can guide the design of EVs. In particular, computational methods for MHC binding prediction have already become standard tools in immunology. Apart from binding prediction and prediction of antigen processing, methods for epitope design and selection have been suggested. We review these in silico approaches for epitope discovery and selection along with their strengths and weaknesses. Finally, we discuss some of the obvious problems in the design of EVs.

CONCLUSION

State-of-the-art in silico approaches to MHC binding prediction yield high accuracies. However, a more thorough understanding of the underlying biological processes and significant amounts of experimental data will be required for the validation and improvement of in silico approaches to the remaining aspects of EV design.

HLA-associated immune escape pathways in HIV-1 subtype B Gag, Pol and Nef proteins

BACKGROUND

Despite the extensive genetic diversity of HIV-1, viral evolution in response to immune selective pressures follows broadly predictable mutational patterns. Sites and pathways of Human Leukocyte-Antigen (HLA)-associated polymorphisms in HIV-1 have been identified through the analysis of population-level data, but the full extent of immune escape pathways remains incompletely characterized. Here, in the largest analysis of HIV-1 subtype B sequences undertaken to date, we identify HLA-associated polymorphisms in the three HIV-1 proteins most commonly considered in cellular-based vaccine strategies. Results are organized into protein-wide escape maps illustrating the sites and pathways of HLA-driven viral evolution.

METHODOLOGY/PRINCIPAL FINDINGS

HLA-associated polymorphisms were identified in HIV-1 Gag, Pol and Nef in a multicenter cohort of >1500 chronically subtype-B infected, treatment-naïve individuals from established cohorts in Canada, the USA and Western Australia. At q< or =0.05, 282 codons commonly mutating under HLA-associated immune pressures were identified in these three proteins. The greatest density of associations was observed in Nef (where close to 40% of codons exhibited a significant HLA association), followed by Gag then Pol (where approximately 15-20% of codons exhibited HLA associations), confirming the extensive impact of immune selection on HIV evolution and diversity. Analysis of HIV codon covariation patterns identified over 2000 codon-codon interactions at q< or =0.05, illustrating the dense and complex networks of linked escape and secondary/compensatory mutations.

CONCLUSIONS/SIGNIFICANCE

The immune escape maps and associated data are intended to serve as a user-friendly guide to the locations of common escape mutations and covarying codons in HIV-1 subtype B, and as a resource facilitating the systematic identification and classification of immune escape mutations. These resources should facilitate research in HIV epitope discovery and host-pathogen co-evolution, and are relevant to the continued search for an effective CTL-based AIDS vaccine.

T-cell epitope prediction: rescaling can mask biological variation between MHC molecules

Theoretical methods for predicting CD8+ T-cell epitopes are an important tool in vaccine design and for enhancing our understanding of the cellular immune system. The most popular methods currently available produce binding affinity predictions across a range of MHC molecules. In comparing results between these MHC molecules, it is common practice to apply a normalization procedure known as rescaling, to correct for possible discrepancies between the allelic predictors. Using two of the most popular prediction software packages, NetCTL and NetMHC, we tested the hypothesis that rescaling removes genuine biological variation from the predicted affinities when comparing predictions across a number of MHC molecules. We found that removing the condition of rescaling improved the prediction software's performance both qualitatively, in terms of ranking epitopes, and quantitatively, in the accuracy of their binding affinity predictions. We suggest that there is biologically significant variation among class 1 MHC molecules and find that retention of this variation leads to significantly more accurate epitope prediction.

Evaluation of MHC-II peptide binding prediction servers: applications for vaccine research

BACKGROUND

Initiation and regulation of immune responses in humans involves recognition of peptides presented by human leukocyte antigen class II (HLA-II) molecules. These peptides (HLA-II T-cell epitopes) are increasingly important as research targets for the development of vaccines and immunotherapies. HLA-II peptide binding studies involve multiple overlapping peptides spanning individual antigens, as well as complete viral proteomes. Antigen variation in pathogens and tumor antigens, and extensive polymorphism of HLA molecules increase the number of targets for screening studies. Experimental screening methods are expensive and time consuming and reagents are not readily available for many of the HLA class II molecules. Computational prediction methods complement experimental studies, minimize the number of validation experiments, and significantly speed up the epitope mapping process. We collected test data from four independent studies that involved 721 peptide binding assays. Full overlapping studies of four antigens identified binding affinity of 103 peptides to seven common HLA-DR molecules (DRB1*0101, 0301, 0401, 0701, 1101, 1301, and 1501). We used these data to analyze performance of 21 HLA-II binding prediction servers accessible through the WWW.

RESULTS

Because not all servers have predictors for all tested HLA-II molecules, we assessed a total of 113 predictors. The length of test peptides ranged from 15 to 19 amino acids. We tried three prediction strategies - the best 9-mer within the longer peptide, the average of best three 9-mer predictions, and the average of all 9-mer predictions within the longer peptide. The best strategy was the identification of a single best 9-mer within the longer peptide. Overall, measured by the receiver operating characteristic method (AROC), 17 predictors showed good (AROC > 0.8), 41 showed marginal (AROC > 0.7), and 55 showed poor performance (AROC < 0.7). Good performance predictors included HLA-DRB1*0101 (seven), 1101 (six), 0401 (three), and 0701 (one). The best individual predictor was NETMHCIIPAN, closely followed by PROPRED, IEDB (Consensus), and MULTIPRED (SVM). None of the individual predictors was shown to be suitable for prediction of promiscuous peptides. Current predictive capabilities allow prediction of only 50% of actual T-cell epitopes using practical thresholds.

CONCLUSION

The available HLA-II servers do not match prediction capabilities of HLA-I predictors. Currently available HLA-II prediction servers offer only a limited prediction accuracy and the development of improved predictors is needed for large-scale studies, such as proteome-wide epitope mapping. The requirements for accuracy of HLA-II binding predictions are stringent because of the substantial effect of false positives.

Protective HLA class I alleles that restrict acute-phase CD8+ T-cell responses are associated with viral escape mutations located in highly conserved regions of human immunodeficiency virus type 1

The control of human immunodeficiency virus type 1 (HIV-1) associated with particular HLA class I alleles suggests that some CD8(+) T-cell responses may be more effective than others at containing HIV-1. Unfortunately, substantial diversities in the breadth, magnitude, and function of these responses have impaired our ability to identify responses most critical to this control. It has been proposed that CD8 responses targeting conserved regions of the virus may be particularly effective, since the development of cytotoxic T-lymphocyte (CTL) escape mutations in these regions may significantly impair viral replication. To address this hypothesis at the population level, we derived near-full-length viral genomes from 98 chronically infected individuals and identified a total of 76 HLA class I-associated mutations across the genome, reflective of CD8 responses capable of selecting for sequence evolution. The majority of HLA-associated mutations were found in p24 Gag, Pol, and Nef. Reversion of HLA-associated mutations in the absence of the selecting HLA allele was also commonly observed, suggesting an impact of most CTL escape mutations on viral replication. Although no correlations were observed between the number or location of HLA-associated mutations and protective HLA alleles, limiting the analysis to mutations selected by acute-phase immunodominant responses revealed a strong positive correlation between mutations at conserved residues and protective HLA alleles. These data suggest that control of HIV-1 may be associated with acute-phase CD8 responses capable of selecting for viral escape mutations in highly conserved regions of the virus, supporting the inclusion of these regions in the design of an effective vaccine.

Phylogenetic dependency networks: inferring patterns of CTL escape and codon covariation in HIV-1 Gag

HIV avoids elimination by cytotoxic T-lymphocytes (CTLs) through the evolution of escape mutations. Although there is mounting evidence that these escape pathways are broadly consistent among individuals with similar human leukocyte antigen (HLA) class I alleles, previous population-based studies have been limited by the inability to simultaneously account for HIV codon covariation, linkage disequilibrium among HLA alleles, and the confounding effects of HIV phylogeny when attempting to identify HLA-associated viral evolution. We have developed a statistical model of evolution, called a phylogenetic dependency network, that accounts for these three sources of confounding and identifies the primary sources of selection pressure acting on each HIV codon. Using synthetic data, we demonstrate the utility of this approach for identifying sites of HLA-mediated selection pressure and codon evolution as well as the deleterious effects of failing to account for all three sources of confounding. We then apply our approach to a large, clinically-derived dataset of Gag p17 and p24 sequences from a multicenter cohort of 1144 HIV-infected individuals from British Columbia, Canada (predominantly HIV-1 clade B) and Durban, South Africa (predominantly HIV-1 clade C). The resulting phylogenetic dependency network is dense, containing 149 associations between HLA alleles and HIV codons and 1386 associations among HIV codons. These associations include the complete reconstruction of several recently defined escape and compensatory mutation pathways and agree with emerging data on patterns of epitope targeting. The phylogenetic dependency network adds to the growing body of literature suggesting that sites of escape, order of escape, and compensatory mutations are largely consistent even across different clades, although we also identify several differences between clades. As recent case studies have demonstrated, understanding both the complexity and the consistency of immune escape has important implications for CTL-based vaccine design. Phylogenetic dependency networks represent a major step toward systematically expanding our understanding of CTL escape to diverse populations and whole viral genes.

HLA-driven convergence of HIV-1 viral subtypes B and F toward the adaptation to immune responses in human populations

BACKGROUND

Cytotoxic T-Lymphocyte (CTL) response drives the evolution of HIV-1 at a host-level by selecting HLA-restricted escape mutations. Dissecting the dynamics of these escape mutations at a population-level would help to understand how HLA-mediated selection drives the evolution of HIV-1.

METHODOLOGY/PRINCIPAL FINDINGS

We undertook a study of the dynamics of HIV-1 CTL-escape mutations by analyzing through statistical approaches and phylogenetic methods the viral gene gag sequenced in plasma samples collected between the years 1987 and 2006 from 302 drug-naïve HIV-positive patients. By applying logistic regression models and after performing correction for multiple test, we identified 22 potential CTL-escape mutations (p-value<0.05; q-value<0.2); 10 of these associations were confirmed in samples biologically independent by a Bayesian Markov Chain Monte-Carlo method. Analyzing their prevalence back in time we found that escape mutations that are the consensus residue in samples collected after 2003 have actually significantly increased in time in one of either B or F subtype until becoming the most frequent residue, while dominating the other viral subtype. Their estimated prevalence in the viral subtype they did not dominate was lower than 30% for the majority of samples collected at the end of the 80's. In addition, when screening the entire viral region, we found that the 75% of positions significantly changing in time (p<0.05) were located within known CTL epitopes.

CONCLUSIONS

Across HIV Gag protein, the rise of polymorphisms from independent origin during the last twenty years of epidemic in our setting was related to an association with an HLA allele. The fact that these mutations accumulated in one of either B or F subtypes have also dominated the other subtype shows how this selection might be causing a convergence of viral subtypes to variants which are more likely to evade the immune response of the population where they circulate.

Evidence of differential HLA class I-mediated viral evolution in functional and accessory/regulatory genes of HIV-1

Despite the formidable mutational capacity and sequence diversity of HIV-1, evidence suggests that viral evolution in response to specific selective pressures follows generally predictable mutational pathways. Population-based analyses of clinically derived HIV sequences may be used to identify immune escape mutations in viral genes; however, prior attempts to identify such mutations have been complicated by the inability to discriminate active immune selection from virus founder effects. Furthermore, the association between mutations arising under in vivo immune selection and disease progression for highly variable pathogens such as HIV-1 remains incompletely understood. We applied a viral lineage-corrected analytical method to investigate HLA class I-associated sequence imprinting in HIV protease, reverse transcriptase (RT), Vpr, and Nef in a large cohort of chronically infected, antiretrovirally naïve individuals. A total of 478 unique HLA-associated polymorphisms were observed and organized into a series of "escape maps," which identify known and putative cytotoxic T lymphocyte (CTL) epitopes under selection pressure in vivo. Our data indicate that pathways to immune escape are predictable based on host HLA class I profile, and that epitope anchor residues are not the preferred sites of CTL escape. Results reveal differential contributions of immune imprinting to viral gene diversity, with Nef exhibiting far greater evidence for HLA class I-mediated selection compared to other genes. Moreover, these data reveal a significant, dose-dependent inverse correlation between HLA-associated polymorphisms and HIV disease stage as estimated by CD4(+) T cell count. Identification of specific sites and patterns of HLA-associated polymorphisms across HIV protease, RT, Vpr, and Nef illuminates regions of the genes encoding these products under active immune selection pressure in vivo. The high density of HLA-associated polymorphisms in Nef compared to other genes investigated indicates differential HLA class I-driven evolution in different viral genes. The relationship between HLA class I-associated polymorphisms and lower CD4(+) cell count suggests that immune escape correlates with disease status, supporting an essential role of maintenance of effective CTL responses in immune control of HIV-1. The design of preventative and therapeutic CTL-based vaccine approaches could incorporate information on predictable escape pathways.

Statistical resolution of ambiguous HLA typing data

High-resolution HLA typing plays a central role in many areas of immunology, such as in identifying immunogenetic risk factors for disease, in studying how the genomes of pathogens evolve in response to immune selection pressures, and also in vaccine design, where identification of HLA-restricted epitopes may be used to guide the selection of vaccine immunogens. Perhaps one of the most immediate applications is in direct medical decisions concerning the matching of stem cell transplant donors to unrelated recipients. However, high-resolution HLA typing is frequently unavailable due to its high cost or the inability to re-type historical data. In this paper, we introduce and evaluate a method for statistical, in silico refinement of ambiguous and/or low-resolution HLA data. Our method, which requires an independent, high-resolution training data set drawn from the same population as the data to be refined, uses linkage disequilibrium in HLA haplotypes as well as four-digit allele frequency data to probabilistically refine HLA typings. Central to our approach is the use of haplotype inference. We introduce new methodology to this area, improving upon the Expectation-Maximization (EM)-based approaches currently used within the HLA community. Our improvements are achieved by using a parsimonious parameterization for haplotype distributions and by smoothing the maximum likelihood (ML) solution. These improvements make it possible to scale the refinement to a larger number of alleles and loci in a more computationally efficient and stable manner. We also show how to augment our method in order to incorporate ethnicity information (as HLA allele distributions vary widely according to race/ethnicity as well as geographic area), and demonstrate the potential utility of this experimentally. A tool based on our approach is freely available for research purposes at http://microsoft.com/science.

Broad and Gag-biased HIV-1 epitope repertoires are associated with lower viral loads

BACKGROUND

HLA class-I alleles differ in their ability to control HIV replication through cell-mediated immune responses. No consistent associations have been found between the breadth of Cytotoxic T Lymphocytes (CTL) responses and the control of HIV-1, and it is unknown whether the size or distribution of the viral proteome-wide epitope repertoire, i.e., the intrinsic ability to present fewer, more or specific viral epitopes, could affect clinical markers of disease progression.

METHODOLOGY/PRINCIPAL FINDINGS

We used an epitope prediction model to identify all epitope motifs in a set of 302 HIV-1 full-length proteomes according to each individual's HLA (Human Leukocyte Antigen) genotype. The epitope repertoire, i.e., the number of predicted epitopes per HIV-1 proteome, varied considerably between HLA alleles and thus among individual proteomes. In a subgroup of 270 chronically infected individuals, we found that lower viral loads and higher CD4 counts were associated with a larger predicted epitope repertoire. Additionally, in Gag and Rev only, more epitopes were restricted by alleles associated with low viral loads than by alleles associated with higher viral loads.

CONCLUSIONS/SIGNIFICANCE

This comprehensive analysis puts forth the epitope repertoire as a mechanistic component of the multi-faceted HIV-specific CTL response. The favorable impact on markers of disease status of the propensity to present more HLA binding peptides and specific proteins gives impetus to vaccine design strategies that seek to elicit responses to a broad array of HIV-1 epitopes, and suggest a particular focus on Gag.

A statistical framework for modeling HLA-dependent T cell response data

The identification of T cell epitopes and their HLA (human leukocyte antigen) restrictions is important for applications such as the design of cellular vaccines for HIV. Traditional methods for such identification are costly and time-consuming. Recently, a more expeditious laboratory technique using ELISpot assays has been developed that allows for rapid screening of specific responses. However, this assay does not directly provide information concerning the HLA restriction of a response, a critical piece of information for vaccine design. Thus, we introduce, apply, and validate a statistical model for identifying HLA-restricted epitopes from ELISpot data. By looking at patterns across a broad range of donors, in conjunction with our statistical model, we can determine (probabilistically) which of the HLA alleles are likely to be responsible for the observed reactivities. Additionally, we can provide a good estimate of the number of false positives generated by our analysis (i.e., the false discovery rate). This model allows us to learn about new HLA-restricted epitopes from ELISpot data in an efficient, cost-effective, and high-throughput manner. We applied our approach to data from donors infected with HIV and identified many potential new HLA restrictions. Among 134 such predictions, six were confirmed in the lab and the remainder could not be ruled as invalid. These results shed light on the extent of HLA class I promiscuity, which has significant implications for the understanding of HLA class I antigen presentation and vaccine development.

At the core of the human adaptive immune response is the train-to-kill mechanism in which specialized immune cells are sensitized to recognize small peptides from foreign pathogens (e.g., HIV virus). Following this sensitization, these cells are then activated to kill other cells that display this same peptide (and that are infected by this same pathogen). However, for sensitization and killing to occur, the pathogen peptide must be “paired up” with one of the infected person's other specialized immune molecules—an HLA (human leukocyte antigen) molecule. The way in which pathogen peptides interact with these HLA molecules defines if and how an immune response will be generated, which has implications for vaccine design where one may artificially introduce select peptides to pre-train the immune system. Furthermore, there is a huge repertoire of such HLA molecules, with almost no two people having the same set. We introduce a statistical approach for identifying which HLA molecules interact with which pathogen peptides, given a particular kind of laboratory data. Our approach takes as input, data that tells us only which pathogen peptides generate a response, but not which HLA molecules support the response. Our statistical approach fills in this missing information.

Strength in numbers: achieving greater accuracy in MHC-I binding prediction by combining the results from multiple prediction tools

Background

Peptides derived from endogenous antigens can bind to MHC class I molecules. Those which bind with high affinity can invoke a CD8⁺ immune response, resulting in the destruction of infected cells. Much work in immunoinformatics has involved the algorithmic prediction of peptide binding affinity to various MHC-I alleles. A number of tools for MHC-I binding prediction have been developed, many of which are available on the web.

Results

We hypothesize that peptides predicted by a number of tools are more likely to bind than those predicted by just one tool, and that the likelihood of a particular peptide being a binder is related to the number of tools that predict it, as well as the accuracy of those tools. To this end, we have built and tested a heuristic-based method of making MHC-binding predictions by combining the results from multiple tools. The predictive performance of each individual tool is first ascertained. These performance data are used to derive weights such that the predictions of tools with better accuracy are given greater credence. The combined tool was evaluated using ten-fold cross-validation and was found to signicantly outperform the individual tools when a high specificity threshold is used. It performs comparably well to the best-performing individual tools at lower specificity thresholds. Finally, it also outperforms the combination of the tools resulting from linear discriminant analysis.

Conclusion

A heuristic-based method of combining the results of the individual tools better facilitates the scanning of large proteomes for potential epitopes, yielding more actual high-affinity binders while reporting very few false positives.