A major concern about the ongoing swine-origin H1N1 influenza virus (S-OIV) outbreak is that the virus may be so different from seasonal H1N1 that little immune protection exists in the human population. In this study, we examined the molecular basis for pre-existing immunity against S-OIV, namely the recognition of viral immune epitopes by T cells or B cells/antibodies that have been previously primed by circulating influenza strains. Using data from the Immune Epitope Database, we found that only 31% (8/26) of B-cell epitopes present in recently circulating H1N1 strains are conserved in the S-OIV, with only 17% (1/6) conserved in the hemagglutinin (HA) and neuraminidase (NA) surface proteins. In contrast, 69% (54/78) of the epitopes recognized by CD8 ؉ T cells are completely invariant. We further demonstrate experimentally that some memory T-cell immunity against S-OIV is present in the adult population and that such memory is of similar magnitude as the pre-existing memory against seasonal H1N1 influenza. Because protection from infection is antibody mediated, a new vaccine based on the specific S-OIV HA and NA proteins is likely to be required to prevent infection. However, T cells are known to blunt disease severity. Therefore, the conservation of a large fraction of T-cell epitopes suggests that the severity of an S-OIV infection, as far as it is determined by susceptibility of the virus to immune attack, would not differ much from that of seasonal flu. These results are consistent with reports about disease incidence, severity, and mortality rates associated with human S-OIV.databases ͉ epitopes ͉ meta-analysis ͉ pandemic

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

Vaccinia virus (VACV) was used as the vaccine strain to eradicate smallpox. VACV is still administered to healthcare workers or researchers who are at risk of contracting the virus, and to military personnel. Thus, VACV represents a weapon against outbreaks, both natural (e.g., monkeypox) or man-made (bioterror). This virus is also used as a vector for experimental vaccine development (cancer/infectious disease). As a prototypic poxvirus, VACV is a model system for studying host-pathogen interactions. Until recently, little was known about the targets of host immune responses, which was likely owing to VACVs large genome (>200 open reading frames). However, the last few years have witnessed an explosion of data, and VACV has quickly become a useful model to study adaptive immune responses. This review summarizes and highlights key findings based on identification of VACV antigens targeted by the immune system (CD4, CD8 and antibodies) and the complex interplay between responses. Keywords adaptive immunity; epitopes; immunodominant; protection; vaccinia virus Structure & taxonomy of poxviruses, & their relevance to human healthAmongst the viruses of relevance to human health, members of the poxvirus family have some of the largest viral genomes (ranging from 130 to 300 kb), with as many as 260 open reading frames (ORFs). All poxviruses replicate exclusively in the cytoplasm of their hosts and have an enveloped viral particle that carries the single, linear dsDNA genome. In general, the genes located in the center of the genome are relatively conserved among poxviruses and have essential molecular functions for replication and survival. By contrast, terminally located genes are more variable and encode proteins that interfere with the host response to infection (virulence factors) and determine host-range restriction [1].The poxviruses that infect vertebrate hosts comprise eight genera and, of these, the orthopox genus has the best-known members and also those most relevant to human health. The most prominent is variola virus (VARV), the causative agent of smallpox, and vaccinia virus (VACV), the vaccine used to prevent and eradicate this once dreaded disease. With smallpox conquered in the 1980s, attention was focused on the use of recombinant VACV as a vector for protein expression in the study of cancer and infectious disease vaccines [2]. A variety of strains of VACV have been used for these studies. The high rates of severe adverse events associated with the traditional smallpox vaccine led to the development of attenuated strains, exemplified by modified vaccinia virus Ankara (MVA). MVA was generated by extensive passaging of VACV Ankara on chicken embryo fibroblasts, resulting NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript in the loss of several genes compared with the parental genome and loss of the ability to replicate in most mammalian cells, including primary human cells [3]. By contrast to the extreme attenuation of MVA, the most commonly used VACV strain for laborat...

Introduction: The current outbreak of Zika virus has resulted in a massive effort to accelerate the development of ZIKV-specific diagnostics and vaccines. These efforts would benefit greatly from the definition of the specific epitope targets of immune responses in ZIKV, but given the relatively recent emergence of ZIKV as a pandemic threat, few such data are available.Methods: We used a large body of epitope data for other Flaviviruses that was available from the IEDB for a comparative analysis against the ZIKV proteome in order to project targets of immune responses in ZIKV.Results: We found a significant level of overlap between known antigenic sites from other Flavivirus proteins with residues on the ZIKV polyprotein. The E and NS1 proteins shared functional antibody epitope sites, whereas regions of T cell reactivity were conserved within NS3 and NS5 for ZIKV. Discussion: Our epitope based analysis provides guidance for which regions of the ZIKV polyprotein are most likely unique targets of ZIKV-specific antibodies, and which targets in ZIKV are most likely to be cross-reactive with other Flavivirus species. These data may therefore provide insights for the development of antibody- and T cell-based ZIKV-specific diagnostics, therapeutics and prophylaxis.

SummaryEpitopes identified in large‐scale screens of overlapping peptides often share significant levels of sequence identity, complicating the analysis of epitope‐related data. Clustering algorithms are often used to facilitate these analyses, but available methods are generally insufficient in their capacity to define biologically meaningful epitope clusters in the context of the immune response. To fulfil this need we developed an algorithm that generates epitope clusters based on representative or consensus sequences. This tool allows the user to cluster peptide sequences on the basis of a specified level of identity by selecting among three different method options. These include the ‘clique method’, in which all members of the cluster must share the same minimal level of identity with each other, and the ‘connected graph method’, in which all members of a cluster must share a defined level of identity with at least one other member of the cluster. In cases where it is not possible to define a clear consensus sequence with the connected graph method, a third option provides a novel ‘cluster‐breaking algorithm’ for consensus sequence driven sub‐clustering. Herein we demonstrate the tool's clustering performance and applicability using (i) a selection of dengue virus epitopes for the ‘clique method’, (ii) sets of allergen‐derived peptides from related species for the ‘connected graph method’ and (iii) large data sets of eluted ligand, major histocompatibility complex binding and T‐cell recognition data captured within the Immune Epitope Database (IEDB) with the newly developed ‘cluster‐breaking algorithm’. This novel clustering tool is accessible at http://tools.iedb.org/cluster2/.

Epitopes that arise from a somatic mutation, also called neoepitopes, are now known to play a key role in cancer immunology and immunotherapy. Recent advances in high-throughput sequencing have made it possible to identify all mutations and thereby all potential neoepitope candidates in an individual cancer. However, most of these neoepitope candidates are not recognized by T cells of cancer patients when tested in vivo or in vitro, meaning they are not immunogenic. Especially in patients with a high mutational load, usually hundreds of potential neoepitopes are detected, highlighting the need to further narrow down this candidate list. In our study, we assembled a dataset of known, naturally processed, immunogenic neoepitopes to dissect the properties that make these neoepitopes immunogenic. The tools to use and thresholds to apply for prioritizing neoepitopes have so far been largely based on experience with epitope identification in other settings such as infectious disease and allergy. Here, we performed a detailed analysis on our dataset of curated immunogenic neoepitopes to establish the appropriate tools and thresholds in the cancer setting. To this end, we evaluated different predictors for parameters that play a role in a neoepitope’s immunogenicity and suggest that using binding predictions and length-rescaling yields the best performance in discriminating immunogenic neoepitopes from a background set of mutated peptides. We furthermore show that almost all neoepitopes had strong predicted binding affinities (as expected), but more surprisingly, the corresponding non-mutated peptides had nearly as high affinities. Our results provide a rational basis for parameters in neoepitope filtering approaches that are being commonly used.Abbreviations: SNV: single nucleotide variant; nsSNV: nonsynonymous single nucleotide variant; ROC: receiver operating characteristic; AUC: area under ROC curve; HLA: human leukocyte antigen; MHC: major histocompatibility complex; PD-1: Programmed cell death protein 1; PD-L1 or CTLA-4: cytotoxic T-lymphocyte associated protein 4

Background: Tuberculosis, caused by the bacterium Mycobacterium tuberculosis, remains a leading cause of infectious disease morbidity and mortality, and is responsible for more than 2 million deaths a year. Reports about extremely drug resistant (XDR) strains have further heightened the sense of urgency for the development of novel strategies to prevent and treat TB. Detailed knowledge of the epitopes recognized by immune responses can aid in vaccine and diagnostics development, and provides important tools for basic research. The analysis of epitope data corresponding to M. tuberculosis can also identify gaps in our knowledge, and suggest potential areas for further research and discovery. The Immune Epitope Database (IEDB) is compiled mainly from literature sources, and describes a broad array of source organisms, including M. tuberculosis and other Mycobacterial species.

A meta-analysis was performed in order to inventory the immune epitope data related to viruses in the genus Flavivirus. Nearly 2000 epitopes were captured from over 130 individual Flavivirus-related references identified from PubMed and reported as of September 2009. This report includes all epitope structures and associated immune reactivity from the past and current literature, including: the epitope distribution among pathogens and related strains, the epitope distribution among different pathogen antigens, the number of epitopes defined in human and animal models of disease, the relationship between epitopes identified in different disease states following natural (or experimental) infection, and data from studies focused on candidate vaccines. We found that the majority of epitopes were defined for dengue virus (DENV) and West Nile virus (WNV). The prominence of DENV and WNV data in the epitope literature is likely a reflection of their overall worldwide impact on human disease, and the lack of vaccines. Conversely, the relatively smaller number of epitopes defined for the other viruses within the genus (yellow fever and Japanese encephalitis virus) most likely reflects the presence of established prophylaxis and/or their more modest impact on morbidity and mortality globally. Through this work we hope to provide useful data to those working in the area of Flavivirus research.