The distribution of CTL epitopes in HIV-1 appears to be random, and similar to that of other proteomes

Physicochemical determinants of antibody-protein interactions

Antibodies are specialized proteins generated by immune system for high specificity and affinity binding to target antigens. Because of their essential roles in immune system, antibodies have been successfully developed and engineered as biopharmaceuticals for treatment of various diseases. Analysis of antibody-protein interactions is always required to get detailed information on effectivity of such antibody-based therapeutics. Although physicochemical rules cannot be generalized for every antibody-protein interaction, there are some features which should be taken into account during antibody development and engineering efforts. In this chapter, physicochemical analysis of antibody paratope-protein epitope interactions will be discussed to highlight important characteristics. First, paratope and non-paratope regions of antibodies will be described and important roles of these regions on binding and biophysical features of antibodies will be discussed. Then, general features of epitope regions of protein antigens will be introduced along with several computational/experimental tools to identify them. Lastly, a rising star of antibody biopharmaceuticals, nanobodies, will be described to show importance of next-generation antibody fragment based biopharmaceuticals in drug development.

Analysis of HIV-1 envelope evolution suggests antibody-mediated selection of common epitopes among Chinese former plasma donors from a narrow-source outbreak

The HIV-1 envelope mutates rapidly to evade recognition and killing, and is a major target of humoral immune responses and vaccine development. Identification of common epitopes for vaccine development have been complicated by genetic variation on both virus and host levels. We studied HIV-1 envelope gp120 evolution in 12 Chinese former plasma donors infected with a purportedly single founder virus, with the aim of identifying common antibody epitopes under immune selection. We found five amino acid sites under significant positive selection in ≥50% of the study participants, and 22 sites consistent with antibody-mediated selection. Despite strong selection pressure, some sites housed a limited repertoire of amino acids. Structural modelling revealed that most of the variable amino acid sites were located on the exposed distal edge of the Gp120 trimer, whilst invariant sites clustered within the centre of the protein complex. Two sites, flanking the V3 hypervariable loop, represent novel antibody sites. Analysis of HIV-1 evolution in hosts infected with a narrow-source virus may provide insight and novel understanding of common epitopes under antibody-mediated selection. If verified in functional studies, such epitopes could be suitable as targets in vaccine development.

Predicted MHC peptide binding promiscuity explains MHC class I 'hotspots' of antigen presentation defined by mass spectrometry eluted ligand data

Peptides that bind to and are presented by MHC class I and class II molecules collectively make up the immunopeptidome. In the context of vaccine development, an understanding of the immunopeptidome is essential, and much effort has been dedicated to its accurate and cost-effective identification. Current state-of-the-art methods mainly comprise in silico tools for predicting MHC binding, which is strongly correlated with peptide immunogenicity. However, only a small proportion of the peptides that bind to MHC molecules are, in fact, immunogenic, and substantial work has been dedicated to uncovering additional determinants of peptide immunogenicity. In this context, and in light of recent advancements in mass spectrometry (MS), the existence of immunological hotspots has been given new life, inciting the hypothesis that hotspots are associated with MHC class I peptide immunogenicity. We here introduce a precise terminology for defining these hotspots and carry out a systematic analysis of MS and in silico predicted hotspots. We find that hotspots defined from MS data are largely captured by peptide binding predictions, enabling their replication in silico. This leads us to conclude that hotspots, to a great degree, are simply a result of promiscuous HLA binding, which disproves the hypothesis that the identification of hotspots provides novel information in the context of immunogenic peptide prediction. Furthermore, our analyses demonstrate that the signal of ligand processing, although present in the MS data, has very low predictive power to discriminate between MS and in silico defined hotspots.

Key role of human leukocyte antigen in modulating human immunodeficiency virus progression: An overview of the possible applications

Host and viral factors deeply influence the human immunodeficiency virus (HIV) disease progression. Among them human leukocyte antigen (HLA) locus plays a key role at different levels. In fact, genes of the HLA locus have shown the peculiar capability to modulate both innate and adaptive immune responses. In particular, HLA class I molecules are recognized by CD8⁺ T-cells and natural killers (NK) cells towards the interaction with T cell receptor (TCR) and Killer Immunoglobulin Receptor (KIR) 3DL1 respectively. Polymorphisms within the different HLA alleles generate structural changes in HLA class I peptide-binding pockets. Amino acid changes in the peptide-binding pocket lead to the presentation of a different set of peptides to T and NK cells. This review summarizes the role of HLA in HIV progression toward acquired immunodeficiency disease syndrome and its receptors. Recently, many studies have been focused on determining the HLA binding-peptides. The novel use of immune-informatics tools, from the prediction of the HLA-bound peptides to the modification of the HLA-receptor complexes, is considered. A better knowledge of HLA peptide presentation and recognition are allowing new strategies for immune response manipulation to be applied against HIV virus.

Role of individual's T-cell immunome in controlling HIV-1 progression

Viral and host factors can influence HIV-1 progression, among them human leucocyte antigen (HLA) has shown the strongest effect. However, studies on the functional contribution of HLA in controlling HIV progression toward AIDS are limited by multiple issues, including the viral strain variability within the study subjects. In this study, in a cohort of children infected with a monophyletic strain (CRF02_AG) during an outbreak, we evaluated the HIV-1 Gag, Vif, Vpr, Tat and hepatitis C virus E1/E2 (as control) proteins circulating in a cohort for the capability to be presented by the HLA molecules in the same population. A total of 70 Non-progressors and 37 Progressors to AIDS were evaluated. In the presence of a constant capability of HIV-1 to mutate in the region containing epitopes of Gag protein, the number of epitopes recognized in silico by the combination of the HLA alleles along the Gag consensus sequence is significantly higher in the Non-progressors compared with Progressors (HLA-A: Non-progressors = 1.532 ± 1.211, Progressors = 0.7714 ± 1.031, P = 0.0016; HLA-B: Non-progressors = 1.556 ± 1.298, Progressors = 1.000 ± 0.817, P = 0.0319; HLA-DR: Non-progressors = 13.30 ± 9.488, Progressors = 7.294 ± 6.952, P = 0.0006). Similar results were obtained for the other HIV-1 proteins Vif and Vpr, whereas no differences were obtained in the number of epitopes for the hepatitis C virus E1/E2 protein sequence or for the scrambled HIV-1 sequence. Finally, the results were confirmed also in a subgroup of subjects where both HLA typing and Gag sequence were available. In conclusion, in the absence of bias due to viral strain diversity, it is the overall fitting of the HLA molecules that are capable of better binding HIV-1 proteins in determining the major role in the control of HIV-1 replication and progression to AIDS.

In silico predicted mycobacterial epitope elicits in vitro T-cell responses

Epitope-based vaccines permit the selection of only a specific subset of epitopes to induce the necessary immune response, thus providing a rational alternative to conventional design approaches. Using a range of immunoinformatics tools, we identified a novel, contiguous 28 amino acid multi-epitope cluster within the highly conserved secretory protein Ag85B of Mycobacterium tuberculosis, the causative agent of TB. This cluster, named Ep85B, is composed of epitopes which bind to three HLA Class I and 15 Class II molecules, and harbors the potential to generate 99% population coverage in TB-endemic regions. We experimentally evaluated the capacity of Ep85B to elicit T-cell immune responses using whole blood cells and, as predicted, observed significant increases in populations of both CD4+ and memory CD4+ CD45RO+ T-cells. Our results demonstrate the practical utility of an epitope-based design methodology - a strategy that, following further evaluation, may serve as an additional tool for the development of novel vaccine candidates against TB and other diseases.

HLA supertypes contribute in HIV type 1 cytotoxic T lymphocyte epitope clustering in Nef and Gag proteins

Induction of HIV-1-specific cytotoxic T lymphocyte (CTL) responses largely depends upon the presentation of CTL epitopes to the CD8(+) T cells aided by a large number of different HLA class I alleles. Although several studies showed the clustering pattern of HIV-1 CTL epitopes, the underlying reason for this tendency remains unresolved. Moreover, the hypothesis that the CTL epitope clusters tend to coincide with the conserved and hydrophobic regions of HIV-1 proteins has been challenged in recent times. The present study aims to characterize and compare the HIV-1 CTL epitope clusters in terms of restricting HLA alleles, hydrophobicity, and sequence conservation in a proteome-wide manner by including a large number of experimentally validated CTL epitopes from the HIV Molecular Immunology Database. CTL epitope cluster distribution analysis in a proteome-wide manner revealed that only two HIV-1 proteins, namely Nef and Gag, have significant cluster-forming capacity where their epitope localization coincides with the hydrophobic and conserved regions. Furthermore, analyses of proteasomal cleavage sites and HLA anchoring motif frequencies in the epitope-dense regions highlighted the role of specific HLA supertypes such as HLA B*07, HLA B*58, HLA A*02, and HLA A*03 in selecting the hydrophobic and conserved amino acid positions within Nef and Gag proteins to be presented as epitopes. Based on our results, we hypothesize that the cluster-forming tendency of HIV-1 CTL epitopes is not a proteome-wide feature confined to Nef and Gag proteins. Their cluster-forming tendency largely depends on the host HLA alleles that contribute significantly in selecting functionally constrained hydrophobic regions within the HIV-1 proteome.

HIV-1 evolution in relation to molecular epidemiology and antiretroviral resistance

HIV/AIDS has become one of the most important infectious diseases with a cumulative number of almost 60 million infections worldwide. The prevalence and epidemiological patterns are unevenly distributed across the globe and also within countries. HIV is one of the fastest evolving organisms known. Several genetically distinct subtypes are present and new circulating recombinant forms are continuously emerging. This review discusses HIV-1 evolution in relation to molecular epidemiology and antiretroviral resistance. Factors and concepts that influence global spread and within-patient evolution of HIV-1 are discussed as well as future perspectives on the use of phylodynamics in HIV epidemiology.

Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef

Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

Whole-genome immunoinformatic analysis of F. tularensis: predicted CTL epitopes clustered in hotspots are prone to elicit a T-cell response

The cellular arm of the immune response plays a central role in the defense against intracellular pathogens, such as F. tularensis. To date, whole genome immunoinformatic analyses were limited either to relatively small genomes (e.g. viral) or to preselected subsets of proteins in complex pathogens. Here we present, for the first time, an unbiased bacterial global immunoinformatic screen of the 1740 proteins of F. tularensis subs. holarctica (LVS), aiming at identification of immunogenic peptides eliciting a CTL response. The very large number of predicted MHC class I binders (about 100,000, IC₅₀ of 1000 nM or less) required the design of a strategy for further down selection of CTL candidates. The approach developed focused on mapping clusters rich in overlapping predicted epitopes, and ranking these “hotspot” regions according to the density of putative binding epitopes. Limited by the experimental load, we selected to screen a library of 1240 putative MHC binders derived from 104 top-ranking highly dense clusters. Peptides were tested for their ability to stimulate IFNγ secretion from splenocytes isolated from LVS vaccinated C57BL/6 mice. The majority of the clusters contained one or more CTL responder peptides and altogether 127 novel epitopes were identified, of which 82 are non-redundant. Accordingly, the level of success in identification of positive CTL responders was 17–25 fold higher than that found for a randomly selected library of 500 predicted MHC binders (IC₅₀ of 500 nM or less). Most proteins (ca. 2/3) harboring the highly dense hotspots are membrane-associated. The approach for enrichment of true positive CTL epitopes described in this study, which allowed for over 50% increase in the dataset of known T-cell epitopes of F. tularensis, could be applied in immunoinformatic analyses of many other complex pathogen genomes.

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.