Automated benchmarking of peptide-MHC class I binding predictions

Motivation: Numerous in silico methods predicting peptide binding to major histocompatibility complex (MHC) class I molecules have been developed over the last decades. However, the multitude of available prediction tools makes it non-trivial for the end-user to select which tool to use for a given task. To provide a solid basis on which to compare different prediction tools, we here describe a framework for the automated benchmarking of peptide-MHC class I binding prediction tools. The framework runs weekly benchmarks on data that are newly entered into the Immune Epitope Database (IEDB), giving the public access to frequent, up-to-date performance evaluations of all participating tools. To overcome potential selection bias in the data included in the IEDB, a strategy was implemented that suggests a set of peptides for which different prediction methods give divergent predictions as to their binding capability. Upon experimental binding validation, these peptides entered the benchmark study. Results: The benchmark has run for 15 weeks and includes evaluation of 44 datasets covering 17 MHC alleles and more than 4000 peptide-MHC binding measurements. Inspection of the results allows the end-user to make educated selections between participating tools. Of the four participating servers, NetMHCpan performed the best, followed by ANN, SMM and finally ARB. Availability and implementation: Up-to-date performance evaluations of each server can be found online at http://tools.iedb.org/auto-bench/mhci/weekly. All prediction tool developers are invited to participate in the benchmark. Sign-up instructions are available at http://tools.iedb.org/auto-bench/mhci/join.Fil: Trolle, Thomas. Technical University of Denmark; DinamarcaFil: Metushi, Imir G.. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Greenbaum, Jason A.. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Kim, Yohan. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Sidney, John. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Lund, Ole. Technical University of Denmark; DinamarcaFil: Sette, Alessandro. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Peters, Bjoern. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentin

T-cell recognition is shaped by epitope sequence conservation in the host proteome and microbiome

Several mechanisms exist to avoid or suppress inflammatory T-cell immune responses that could prove harmful to the host due to targeting self-antigens or commensal microbes. We hypothesized that these mechanisms could become evident when comparing the immunogenicity of a peptide from a pathogen or allergen with the conservation of its sequence in the human proteome or the healthy human microbiome. Indeed, performing such comparisons on large sets of validated T-cell epitopes, we found that epitopes that are similar with self-antigens above a certain threshold showed lower immunogenicity, presumably as a result of negative selection of T cells capable of recognizing such peptides. Moreover, we also found a reduced level of immune recognition for epitopes conserved in the commensal microbiome, presumably as a result of peripheral tolerance. These findings indicate that the existence (and potentially the polarization) of T-cell responses to a given epitope is influenced and to some extent predictable based on its similarity to self-antigens and commensal antigens.Fil: Bresciani, Anne Gøther. Technical University of Denmark; Dinamarca. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Paul, Sinu. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Schommer, Nina. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Dillon, Myles B.. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Bancroft, Tara. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Greenbaum, Jason. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Sette, Alessandro. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Instituto de Investigaciones Biotecnológicas ; Argentina. Technical University of Denmark; DinamarcaFil: Peters, Bjoern. La Jolla Institute for Allergy and Immunology; Estados Unido

Towards Defining Molecular Determinants Recognized by Adaptive Immunity in Allergic Disease: An Inventory of the Available Data

Adaptive immune responses associated with allergic reactions recognize antigens from a broad spectrum of plants and animals. Herein a meta-analysis was performed on allergy-related data from the immune epitope database (IEDB) to provide a current inventory and highlight knowledge gaps and areas for future work. The analysis identified over 4,500 allergy-related epitopes derived from 270 different allergens. Overall, the distribution of the data followed expectations based on the nature of allergic responses. Namely, the majority of epitopes were defined for B cells/antibodies and IgE-mediated reactivity, and relatively fewer T-cell epitopes, mostly CD4+/class II. Interestingly, the majority of food allergen epitopes were B-cells epitopes whereas a fairly even number of B- and T-cell epitopes were defined for airborne allergens. In addition, epitopes from nonhumans hosts were mostly T-cell epitopes. Overall, coverage of known allergens is sparse with data available for only ~17% of all allergens listed by the IUIS database. Thus, further research would be required to provide a more balanced representation across different allergen categories. Furthermore, inclusion of nonpeptidic epitopes in the IEDB also allows for inventory and analysis of immunological data associated with drug and contact allergen epitopes. Finally, our analysis also underscores that only a handful of epitopes have thus far been investigated for their immunotherapeutic potential

Gemini Planet Imager Observational Calibrations VI: Photometric and Spectroscopic Calibration for the Integral Field Spectrograph

The Gemini Planet Imager (GPI) is a new facility instrument for the Gemini Observatory designed to provide direct detection and characterization of planets and debris disks around stars in the solar neighborhood. In addition to its extreme adaptive optics and corona graphic systems which give access to high angular resolution and high-contrast imaging capabilities, GPI contains an integral field spectrograph providing low resolution spectroscopy across five bands between 0.95 and 2.5 $\mu$m. This paper describes the sequence of processing steps required for the spectro-photometric calibration of GPI science data, and the necessary calibration files. Based on calibration observations of the white dwarf HD 8049B we estimate that the systematic error in spectra extracted from GPI observations is less than 5%. The flux ratio of the occulted star and fiducial satellite spots within coronagraphic GPI observations, required to estimate the magnitude difference between a target and any resolved companions, was measured in the $H$-band to be $\Delta m = 9.23\pm0.06$ in laboratory measurements and $\Delta m = 9.39\pm 0.11$ using on-sky observations. Laboratory measurements for the $Y$, $J$, $K1$ and $K2$ filters are also presented. The total throughput of GPI, Gemini South and the atmosphere of the Earth was also measured in each photometric passband, with a typical throughput in $H$-band of 18% in the non-coronagraphic mode, with some variation observed over the six-month period for which observations were available. We also report ongoing development and improvement of the data cube extraction algorithm.Comment: 15 pages, 6 figures. Proceedings of the SPIE, 9147-30

Overcoming the Ontology Enrichment Bottleneck with Quick Term Templates

The developers of the Ontology of Biomedical Investigations (OBI) primarily use Protégé for editing. However, adding many classes with similar patterns of logical definition is time consuming, error prone, and requires the editor to have some expertise in OWL. Therefore, the process is poorly suited for a large number of domain experts who have limited experience Protégé and ontology development. We have developed a procedure to ease this task and allow such domain experts to add terms to the ontology in a way that both effectively includes complex logical definitions yet requires minimal manual intervention by OBI developers. The procedure is based on editing a Quick Term Template in a spreadsheet format which is subsequently converted into an OWL file. This procedure promises to be a robust and scalable approach for ontology enrichment

IEDB-AR: immune epitope database - analysis resource in 2019

The Immune Epitope Database Analysis Resource (IEDB-AR, http://tools.iedb.org/) is a companion website to the IEDB that provides computational tools focused on the prediction and analysis of B and T cell epitopes. All of the tools are freely available through the public website and many are also available through a REST API and/or a downloadable command-line tool. A virtual machine image of the entire site is also freely available for non-commercial use and contains most of the tools on the public site. Here, we describe the tools and functionalities that are available in the IEDB-AR, focusing on the 10 new tools that have been added since the last report in the 2012 NAR webserver edition. In addition, many of the tools that were already hosted on the site in 2012 have received updates to newest versions, including NetMHC, NetMHCpan, BepiPred and DiscoTope. Overall, this IEDB-AR update provides a substantial set of updated and novel features for epitope prediction and analysis.Fil: Dhanda, Sandeep Kumar. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Mahajan, Swapnil. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Paul, Sinu. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Yan, Zhen. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Kim, Haeuk. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Jespersen, Martin Closter. Technical University of Denmark; DinamarcaFil: Jurtz, Vanessa. Technical University of Denmark; DinamarcaFil: Andreatta, Massimo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina. Technical University of Denmark; DinamarcaFil: Greenbaum, Jason A. La Jolla Institute for Allergy and Immunology; Estados UnidosFil: Marcatili, Paolo. Technical University of Denmark; DinamarcaFil: Sette, Alessandro. La Jolla Institute for Allergy and Immunology; Estados Unidos. University of California; Estados UnidosFil: Nielsen, Morten. Technical University of Denmark; Dinamarca. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; ArgentinaFil: Peters, Bjoern. University of California; Estados Unidos. La Jolla Institute for Allergy and Immunology; Estados Unido

TiArA: A Virtual Appliance for the Analysis of Tiling Array Data

Genomic tiling arrays have been described in the scientific literature since 2003, yet there is a shortage of user-friendly applications available for their analysis.Tiling Array Analyzer (TiArA) is a software program that provides a user-friendly graphical interface for the background subtraction, normalization, and summarization of data acquired through the Affymetrix tiling array platform. The background signal is empirically measured using a group of nonspecific probes with varying levels of GC content and normalization is performed to enforce a common dynamic range.TiArA is implemented as a standalone program for Linux systems and is available as a cross-platform virtual machine that will run under most modern operating systems using virtualization software such as Sun VirtualBox or VMware. The software is available as a Debian package or a virtual appliance at http://purl.org/NET/tiara

The Immune Epitope Database 2.0

The Immune Epitope Database (IEDB, www.iedb.org) provides a catalog of experimentally characterized B and T cell epitopes, as well as data on Major Histocompatibility Complex (MHC) binding and MHC ligand elution experiments. The database represents the molecular structures recognized by adaptive immune receptors and the experimental contexts in which these molecules were determined to be immune epitopes. Epitopes recognized in humans, nonhuman primates, rodents, pigs, cats and all other tested species are included. Both positive and negative experimental results are captured. Over the course of 4 years, the data from 180 978 experiments were curated manually from the literature, which covers ∼99% of all publicly available information on peptide epitopes mapped in infectious agents (excluding HIV) and 93% of those mapped in allergens. In addition, data that would otherwise be unavailable to the public from 129 186 experiments were submitted directly by investigators. The curation of epitopes related to autoimmunity is expected to be completed by the end of 2010. The database can be queried by epitope structure, source organism, MHC restriction, assay type or host organism, among other criteria. The database structure, as well as its querying, browsing and reporting interfaces, was completely redesigned for the IEDB 2.0 release, which became publicly available in early 2009