Concept: Polyclonal B cell response
Viral subunit vaccines often contain immunodominant non-neutralizing epitopes that divert host immune responses. These epitopes should be eliminated in vaccine design, but there is no reliable method for evaluating an epitope’s capacity to elicit neutralizing immune responses. Here we introduce a new concept ‘neutralizing immunogenicity index’ (NII) to evaluate an epitope’s neutralizing immunogenicity. To determine the NII, we mask the epitope with a glycan probe and then assess the epitope’s contribution to the vaccine’s overall neutralizing immunogenicity. As proof-of-concept, we measure the NII for different epitopes on an immunogen comprised of the receptor-binding domain from MERS coronavirus (MERS-CoV). Further, we design a variant form of this vaccine by masking an epitope that has a negative NII score. This engineered vaccine demonstrates significantly enhanced efficacy in protecting transgenic mice from lethal MERS-CoV challenge. Our study may guide the rational design of highly effective subunit vaccines to combat MERS-CoV and other life-threatening viruses.
Nanobodies are single-domain antibodies derived from the variable regions of Camelidae atypical immunoglobulins. They show promise as high-affinity reagents for research, diagnostics and therapeutics owing to their high specificity, small size (∼15 kDa) and straightforward bacterial expression. However, identification of repertoires with sufficiently high affinity has proven time consuming and difficult, hampering nanobody implementation. Our approach generates large repertoires of readily expressible recombinant nanobodies with high affinities and specificities against a given antigen. We demonstrate the efficacy of this approach through the production of large repertoires of nanobodies against two antigens, GFP and mCherry, with Kd values into the subnanomolar range. After mapping diverse epitopes on GFP, we were also able to design ultrahigh-affinity dimeric nanobodies with Kd values as low as ∼30 pM. The approach presented here is well suited for the routine production of high-affinity capture reagents for various biomedical applications.
By convention, CD4(+) T lymphocytes recognize foreign and self peptides derived from internalized antigens in combination with major histocompatibility complex class II molecules. Alternative pathways of epitope production have been identified, but their contributions to host defense have not been established. We show here in a mouse infection model that the CD4(+) T cell response to influenza, critical for durable protection from the virus, is driven principally by unconventional processing of antigen synthesized within the infected antigen-presenting cell, not by classical processing of endocytosed virions or material from infected cells. Investigation of the cellular components involved, including the H2-M molecular chaperone, the proteasome and γ-interferon-inducible lysosomal thiol reductase revealed considerable heterogeneity in the generation of individual epitopes, an arrangement that ensures peptide diversity and broad CD4(+) T cell engagement. These results could fundamentally revise strategies for rational vaccine design and may lead to key insights into the induction of autoimmune and anti-tumor responses.
HIV-1 accumulates mutations in and around reactive epitopes to escape recognition and killing by CD8+ T cells. Measurements of HIV-1 time to escape should therefore provide information on which parameters are most important for T cell-mediated in vivo control of HIV-1. Primary HIV-1-specific T cell responses were fully mapped in 17 individuals, and the time to virus escape, which ranged from days to years, was measured for each epitope. While higher magnitude of an individual T cell response was associated with more rapid escape, the most significant T cell measure was its relative immunodominance measured in acute infection. This identified subject-level or “vertical” immunodominance as the primary determinant of in vivo CD8+ T cell pressure in HIV-1 infection. Conversely, escape was slowed significantly by lower population variability, or entropy, of the epitope targeted. Immunodominance and epitope entropy combined to explain half of all the variability in time to escape. These data explain how CD8+ T cells can exert significant and sustained HIV-1 pressure even when escape is very slow and that within an individual, the impacts of other T cell factors on HIV-1 escape should be considered in the context of immunodominance.
Adaptive immune responses protect against infection with dengue virus (DENV), yet cross-reactivity with distinct serotypes can precipitate life-threatening clinical disease. We found that clonotypes expressing the T cell antigen receptor (TCR) β-chain variable region 11 (TRBV11-2) were ‘preferentially’ activated and mobilized within immunodominant human-leukocyte-antigen-(HLA)-A*11:01-restricted CD8(+) T cell populations specific for variants of the nonstructural protein epitope NS3133 that characterize the serotypes DENV1, DENV3 and DENV4. In contrast, the NS3133-DENV2-specific repertoire was largely devoid of such TCRs. Structural analysis of a representative TRBV11-2(+) TCR demonstrated that cross-serotype reactivity was governed by unique interplay between the variable antigenic determinant and germline-encoded residues in the second β-chain complementarity-determining region (CDR2β). Extensive mutagenesis studies of three distinct TRBV11-2(+) TCRs further confirmed that antigen recognition was dependent on key contacts between the serotype-defined peptide and discrete residues in the CDR2β loop. Collectively, these data reveal an innate-like mode of epitope recognition with potential implications for the outcome of sequential exposure to heterologous DENVs.
Development of specific inhibitors of allergy has had limited success, in part, owing to a lack of experimental models that reflect the complexity of allergen-IgE interactions. We designed a heterotetravalent allergen (HtTA) system, which reflects epitope heterogeneity, polyclonal response and number of immunodominant epitopes observed in natural allergens, thereby providing a physiologically relevant experimental model to study mast cell degranulation. The HtTA design revealed the importance of weak-affinity epitopes in allergy, particularly when presented with high-affinity epitopes. The effect of selective inhibition of weak-affinity epitope-IgE interactions was investigated with heterobivalent inhibitors (HBIs) designed to simultaneously target the antigen- and nucleotide-binding sites on the IgE Fab. HBI demonstrated enhanced avidity for the target IgE and was a potent inhibitor of degranulation in vitro and in vivo. These results demonstrate that partial inhibition of allergen-IgE interactions was sufficient to prevent mast cell degranulation, thus establishing the therapeutic potential of the HBI design.
One of the major challenges in designing a peptide-based vaccine is the identification of antigenic regions in an antigen that can stimulate B-cell’s response, also called B-cell epitopes. In the past, several methods have been developed for the prediction of conformational and linear (or continuous) B-cell epitopes. However, the existing methods for predicting linear B-cell epitopes are far from perfection. In this study, an attempt has been made to develop an improved method for predicting linear B-cell epitopes. We have retrieved experimentally validated B-cell epitopes as well as non B-cell epitopes from Immune Epitope Database and derived two types of datasets called Lbtope_Variable and Lbtope_Fixed length datasets. The Lbtope_Variable dataset contains 14876 B-cell epitope and 23321 non-epitopes of variable length where as Lbtope_Fixed length dataset contains 12063 B-cell epitopes and 20589 non-epitopes of fixed length. We also evaluated the performance of models on above datasets after removing highly identical peptides from the datasets. In addition, we have derived third dataset Lbtope_Confirm having 1042 epitopes and 1795 non-epitopes where each epitope or non-epitope has been experimentally validated in at least two studies. A number of models have been developed to discriminate epitopes and non-epitopes using different machine-learning techniques like Support Vector Machine, and K-Nearest Neighbor. We achieved accuracy from ∼54% to 86% using diverse s features like binary profile, dipeptide composition, AAP (amino acid pair) profile. In this study, for the first time experimentally validated non B-cell epitopes have been used for developing method for predicting linear B-cell epitopes. In previous studies, random peptides have been used as non B-cell epitopes. In order to provide service to scientific community, a web server LBtope has been developed for predicting and designing B-cell epitopes (http://crdd.osdd.net/raghava/lbtope/).
CD8(+) T cells play an important role in controlling Flavivirus infection, including Zika virus (ZIKV). Here, we have identified 25 HLA-B*0702-restricted epitopes and 1 HLA-A*0101-restricted epitope using interferon (IFN)-γ enzyme-linked immunospot (ELISPOT) and intracellular cytokine staining (ICS) in ZIKV-infected IFN-α/β receptor-deficient HLA transgenic mice. The cross-reactivity of ZIKV epitopes to dengue virus (DENV) was tested using IFN-γ-ELISPOT and IFN-γ-ICS on CD8(+) T cells from DENV-infected mice, and five cross-reactive HLA-B*0702-binding peptides were identified by both assays. ZIKV/DENV cross-reactive CD8(+) T cells in DENV-immune mice expanded post ZIKV challenge and dominated in the subsequent CD8(+) T cell response. ZIKV challenge following immunization of mice with ZIKV-specific and ZIKV/DENV cross-reactive epitopes elicited CD8(+) T cell responses that reduced infectious ZIKV levels, and CD8(+) T cell depletions confirmed that CD8(+) T cells mediated this protection. These results identify ZIKV-specific and ZIKV/DENV cross-reactive epitopes and demonstrate both an altered immunodominance pattern in the DENV-immune setting relative to naive, as well as a protective role for epitope-specific CD8(+) T cells against ZIKV. These results have important implications for ZIKV vaccine development and provide a mouse model for evaluating anti-ZIKV CD8(+) T cell responses of human relevance.
To determine the antigenic determinants and specific molecular requirements for the generation of autoregulatory neuroantigen-specific CD8(+) T cells in models of multiple sclerosis (MS).
Computational vaccine design, also known as computational vaccinology, encompasses epitope mapping, antigen selection and immunogen design using computational tools. The iVAX toolkit is an integrated set of tools that has been in development since 1998 by De Groot and Martin. It comprises a suite of immunoinformatics algorithms for triaging candidate antigens, selecting immunogenic and conserved T cell epitopes, eliminating regulatory T cell epitopes, and optimizing antigens for immunogenicity and protection against disease. iVAX has been applied to vaccine development programs for emerging infectious diseases, cancer antigens and biodefense targets. Several iVAX vaccine design projects have had success in pre-clinical studies in animal models and are progressing towards clinical studies. The toolkit now incorporates a range of immunoinformatics tools for infectious disease and cancer immunotherapy vaccine design. This article will provide a guide to the iVAX approach to computational vaccinology.