New approaches to eliciting protective immunity through T cell repertoire manipulation: the concept of thymic vaccination

Conventional vaccines afford protection against infectious diseases by expanding existing pathogen-specific peripheral lymphocytes, both CD8 cytotoxic effector (CTL) and CD4 helper T cells. The latter induce B cell maturation and antibody production. As a consequence, lymphocytes within the memory pool are poised to rapidly proliferate at the time of a subsequent infection. The "thymic vaccination" concept offers a novel way to alter the primary T cell repertoire through exposure of thymocytes to altered peptide ligands (APL) with reduced T cell receptor (TCR) affinity relative to cognate antigens recognized by those same TCRs. Thymocyte maturation (i.e. positive selection) is enhanced by low affinity interaction between a TCR and an MHC-bound peptide in the thymus and subsequent emigration of mature cells into the peripheral T lymphocyte pool follows. In principal, such variants of antigens derived from infectious agents could be utilized for peptide-driven maturation of thymocytes bearing pathogen-specific TCRs. To test this idea, APLs of gp(33–41), a D(b)-restricted peptide derived from the lymphocytic choriomeningitis virus (LCMV) glycoprotein, and of VSV8, a K(b)-restricted peptide from the vesicular stomatitis virus (VSV) nucleoprotein, have been designed and their influence on thymic maturation of specific TCR-bearing transgenic thymocytes examined in vivo using irradiation chimeras. Injection of APL resulted in positive selection of CD8 T cells expressing the relevant viral specificity and in the export of those virus-specific CTL to lymph nodes without inducing T cell proliferation. Thus, exogenous APL administration offers the potential of expanding repertoires in vivo in a manner useful to the organism. To efficiently peripheralize antigen-specific T cells, concomitant enhancement of mechanisms promoting thymocyte migration appears to be required. This commentary describes the rationale for thymic vaccination and addresses the potential prophylactic and therapeutic applications of this approach for treatment of infectious diseases and cancer. Thymic vaccination-induced peptide-specific T cells might generate effective immune protection against disease-causing agents, including those for which no effective natural protection exists

PEPVAC: a web server for multi-epitope vaccine development based on the prediction of supertypic MHC ligands

Prediction of peptide binding to major histocompatibility complex (MHC) molecules is a basis for anticipating T-cell epitopes, as well as epitope discovery-driven vaccine development. In the human, MHC molecules are known as human leukocyte antigens (HLAs) and are extremely polymorphic. HLA polymorphism is the basis of differential peptide binding, until now limiting the practical use of current epitope-prediction tools for vaccine development. Here, we describe a web server, PEPVAC (Promiscuous EPitope-based VACcine), optimized for the formulation of multi-epitope vaccines with broad population coverage. This optimization is accomplished through the prediction of peptides that bind to several HLA molecules with similar peptide-binding specificity (supertypes). Specifically, we offer the possibility of identifying promiscuous peptide binders to five distinct HLA class I supertypes (A2, A3, B7, A24 and B15). We estimated the phenotypic population frequency of these supertypes to be 95%, regardless of ethnicity. Targeting these supertypes for promiscuous peptide-binding predictions results in a limited number of potential epitopes without compromising the population coverage required for practical vaccine design considerations. PEPVAC can also identify conserved MHC ligands, as well as those with a C-terminus resulting from proteasomal cleavage. The combination of these features with the prediction of promiscuous HLA class I ligands further limits the number of potential epitopes. The PEPVAC server is hosted by the Dana-Farber Cancer Institute at the site

Recognition and classification of histones using support vector machine

Histones are DNA-binding proteins found in the chromatin of all eukaryotic cells. They are highly conserved and can be grouped into five major classes: H1/H5, H2A, H2B, H3, and H4. Two copies of H2A, H2B, H3, and H4 bind to about 160 base pairs of DNA forming the core of the nucleosome (the repeating structure of chromatin) and H1/H5 bind to its DNA linker sequence. Overall, histones have a high arginine/lysine content that is optimal for interaction with DNA. This sequence bias can make the classification of histones difficult using standard sequence similarity approaches. Therefore, in this paper, we applied support vector machine (SVM) to recognize and classify histones on the basis of their amino acid and dipeptide composition. On evaluation through a five-fold cross-validation, the SVM-based method was able to distinguish histones from nonhistones (nuclear proteins) with an accuracy around 98%. Similarly, we obtained an overall >95% accuracy in discriminating the five classes of histones through the application of 1-versus-rest (1-v-r) SVM. Finally, we have applied this SVM-based method to the detection of histones from whole proteomes and found a comparable sensitivity to that accomplished by hidden Markov motifs (HMM) profiles

Forward Vaccinology: CTL Targeting Based upon Physical Detection of HLA-Bound Peptides

Vaccine-elicited cytotoxic T lymphocytes (CTL) recognizing conserved fragments of a pathogen’s proteome could greatly impact infectious diseases and cancers. Enabling this potential are recent advances in mass spectrometry that identify specific target peptides among the myriad HLA-bound peptides on altered cells. Ultrasensitivity of these physical detection methods allows for the direct assessment of peptide presentation on small numbers of tissue-derived cells. In addition, concurrent advances in immunobiology suggest ways to induce CTLs with requisite functional avidity and tissue deployment. Elicitation of high-avidity resident-memory T cells through vaccination may shift the vaccinology paradigm both for preventive and therapeutic approaches to human disease control

Molecular Detection of Targeted Major Histocompatibility Complex I-Bound Peptides Using a Probabilistic Measure and Nanospray MS3 on a Hybrid Quadrupole-Linear Ion Trap

A nanospray MS3 method deployed on a quadrupole linear ion trap hybrid can detect targeted peptides with high dynamic range and high sensitivity from complex mixtures without separations. The method uses a recognition algorithm that is a modification of the relative (Kullback−Leibler, KL) entropy characterization of probabilistic distance to detect if reference MS3 fragmentation patterns are components of acquired MS3 spectra. The recognition reflects the probabilistic structure of physical MS measurements unlike the Euclidean or inner product metrics widely used for comparing spectra. It capably handles spectra with a significant chemical ion background in contrast to the Euclidean metric or the direct relative entropy. The full nanospray MS3 method allows both the detection and quantitation of targets without the need to obtain isotopically labeled standards. By avoiding chromatographic separations and its associated surface losses, the detection can be applied to complex samples on a very limited material scale. The methodology is illustrated by applications to the medically important problem of detecting targeted major histocompatibility complex (MHC) I associated peptides extracted from limited cell numbers

FLAVIdB: A data mining system for knowledge discovery in flaviviruses with direct applications in immunology and vaccinology

BACKGROUND: The flavivirus genus is unusually large, comprising more than 70 species, of which more than half are known human pathogens. It includes a set of clinically relevant infectious agents such as dengue, West Nile, yellow fever, and Japanese encephalitis viruses. Although these pathogens have been studied extensively, safe and efficient vaccines lack for the majority of the flaviviruses. RESULTS: We have assembled a database that combines antigenic data of flaviviruses, specialized analysis tools, and workflows for automated complex analyses focusing on applications in immunology and vaccinology. FLAVIdB contains 12,858 entries of flavivirus antigen sequences, 184 verified T-cell epitopes, 201 verified B-cell epitopes, and 4 representative molecular structures of the dengue virus envelope protein. FLAVIdB was assembled by collection, annotation, and integration of data from GenBank, GenPept, UniProt, IEDB, and PDB. The data were subject to extensive quality control (redundancy elimination, error detection, and vocabulary consolidation). Further annotation of selected functionally relevant features was performed by organizing information extracted from the literature. The database was incorporated into a web-accessible data mining system, combining specialized data analysis tools for integrated analysis of relevant data categories (protein sequences, macromolecular structures, and immune epitopes). The data mining system includes tools for variability and conservation analysis, T-cell epitope prediction, and characterization of neutralizing components of B-cell epitopes. FLAVIdB is accessible at cvc.dfci.harvard.edu/flavi/ CONCLUSION: FLAVIdB represents a new generation of databases in which data and tools are integrated into a data mining infrastructures specifically designed to aid rational vaccine design by discovery of vaccine targets

Strict Major Histocompatibility Complex Molecule Class-Specific Binding by Co-Receptors Enforces MHC-Restricted αβ TCR Recognition during T Lineage Subset Commitment

Since the discovery of co-receptor dependent αβTCR recognition, considerable effort has been spent on elucidating the basis of CD4 and CD8 lineage commitment in the thymus. The latter is responsible for generating mature CD4 helper and CD8αβ cytotoxic T cell subsets. Although CD4+ and CD8+ T cell recognition of peptide antigens is known to be MHC class II- and MHC class I-restricted, respectively, the mechanism of single positive (SP) thymocyte lineage commitment from bipotential double-positive (DP) progenitors is not fully elucidated. Classical models to explain thymic CD4 vs. CD8 fate determination have included a stochastic selection model or instructional models. The latter are based either on strength of signal or duration of signal impacting fate. More recently, differential co-receptor gene imprinting has been shown to be involved in expression of transcription factors impacting cytotoxic T cell development. Here, we address commitment from a structural perspective, focusing on the nature of co-receptor binding to MHC molecules. By surveying 58 MHC class II and 224 MHC class I crystal structures in the Protein Data Bank, it becomes clear that CD4 cannot bind to MHC I molecules, nor can CD8αβ or CD8αα bind to MHC II molecules. Given that the co-receptor delivers Lck to phosphorylate exposed CD3 ITAMs within a peptide/MHC (pMHC)-ligated TCR complex to initiate cell signaling, this strict co-receptor recognition fosters MHC class-restricted SP thymocyte lineage commitment at the DP stage even though both co-receptors are expressed on a single cell. In short, the binding preference of an αβTCR for a peptide complexed with an MHC molecule dictates which co-receptor subsequently binds, thereby supporting development of that subset lineage. How function within the lineage is linked further to biopotential fate determination is discussed

Evaluation of MHC class I peptide binding prediction servers: Applications for vaccine research

<b>Background</b> Protein antigens and their specific epitopes are formulation targets for epitope-based vaccines. A number of prediction servers are available for identification of peptides that bind major histocompatibility complex class I (MHC-I) molecules. The lack of standardized methodology and large number of human MHC-I molecules make the selection of appropriate prediction servers difficult. This study reports a comparative evaluation of thirty prediction servers for seven human MHC-I molecules.<p></p> <b>Results</b> Of 147 individual predictors 39 have shown excellent, 47 good, 33 marginal, and 28 poor ability to classify binders from non-binders. The classifiers for HLA-A*0201, A*0301, A*1101, B*0702, B*0801, and B*1501 have excellent, and for A*2402 moderate classification accuracy. Sixteen prediction servers predict peptide binding affinity to MHC-I molecules with high accuracy; correlation coefficients ranging from r = 0.55 (B*0801) to r = 0.87 (A*0201).<p></p> <b>Conclusion</b> Non-linear predictors outperform matrix-based predictors. Most predictors can be improved by non-linear transformations of their raw prediction scores. The best predictors of peptide binding are also best in prediction of T-cell epitopes. We propose a new standard for MHC-I binding prediction – a common scale for normalization of prediction scores, applicable to both experimental and predicted data. The results of this study provide assistance to researchers in selection of most adequate prediction tools and selection criteria that suit the needs of their projects

Tandem duplication, circular permutation, molecular adaptation: how Solanaceae resist pests via inhibitors

<p>Abstract</p> <p>Background</p> <p>The Potato type II (Pot II) family of proteinase inhibitors plays critical roles in the defense system of plants from <it>Solanaceae </it>family against pests. To better understand the evolution of this family, we investigated the correlation between sequence and structural repeats within this family and the evolution and molecular adaptation of Pot II genes through computational analysis, using the putative ancestral domain sequence as the basic repeat unit.</p> <p>Results</p> <p>Our analysis discovered the following interesting findings in Pot II family. (1) We classified the structural domains in Pot II family into three types (original repeat domain, circularly permuted domain, the two-chain domain) according to the existence of two linkers between the two domain components, which clearly show the circular permutation relationship between the original repeat domain and circularly permuted domain. (2) The permuted domains appear more stable than original repeat domain, from available structural information. Therefore, we proposed a multiple-repeat sequence is likely to adopt the permuted domain from contiguous sequence segments, with the N- and C-termini forming a single non-contiguous structural domain, linking the bracelet of tandem repeats. (3) The analysis of nonsynonymous/synonymous substitution rates ratio in Pot II domain revealed heterogeneous selective pressures among amino acid sites: the reactive site is under positive Darwinian selection (providing different specificity to target varieties of proteinases) while the cysteine scaffold is under purifying selection (essential for maintaining the fold). (4) For multi-repeat Pot II genes from <it>Nicotiana </it>genus, the proteolytic processing site is under positive Darwinian selection (which may improve the cleavage efficiency).</p> <p>Conclusion</p> <p>This paper provides comprehensive analysis and characterization of Pot II family, and enlightens our understanding on the strategies (Gene and domain duplication, structural circular permutation and molecular adaptation) of <it>Solanaceae </it>plants for defending pathogenic attacks through the evolution of Pot II genes.</p