The Immune Epitope Database (IEDB): 2018 update.

The Immune Epitope Database (IEDB, iedb.org) captures experimental data confined in figures, text and tables of the scientific literature, making it freely available and easily searchable to the public. The scope of the IEDB extends across immune epitope data related to all species studied and includes antibody, T cell, and MHC binding contexts associated with infectious, allergic, autoimmune, and transplant related diseases. Having been publicly accessible for >10 years, the recent focus of the IEDB has been improved query and reporting functionality to meet the needs of our users to access and summarize data that continues to grow in quantity and complexity. Here we present an update on our current efforts and future goals.

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.

Benchmark datasets of immune receptor-epitope structural complexes.

BACKGROUND: The development of accurate epitope prediction tools is important in facilitating disease diagnostics, treatment and vaccine development. The advent of new approaches making use of antibody and TCR sequence information to predict receptor-specific epitopes have the potential to transform the epitope prediction field. Development and validation of these new generation of epitope prediction methods would benefit from regularly updated high-quality receptor-antigen complex datasets. RESULTS: To address the need for high-quality datasets to benchmark performance of these new generation of receptor-specific epitope prediction tools, a webserver called SCEptRe (Structural Complexes of Epitope-Receptor) was created. SCEptRe extracts weekly updated 3D complexes of antibody-antigen, TCR-pMHC and MHC-ligand from the Immune Epitope Database and clusters them based on antigen, receptor and epitope features to generate benchmark datasets. SCEptRe also provides annotated information such as CDR sequences and VDJ genes on the receptors. Users can generate custom datasets based by selecting thresholds for structural quality and clustering parameters (e.g. resolution, R-free factor, antigen or epitope sequence identity) based on their need. CONCLUSIONS: SCEptRe provides weekly updated, user-customized comprehensive benchmark datasets of immune receptor-epitope structural complexes. These datasets can be used to develop and benchmark performance of receptor-specific epitope prediction tools in the future. SCEptRe is freely accessible at http://tools.iedb.org/sceptre .

Jumping between protein conformers using normal modes.

The relationship between the normal modes of a protein and its functional conformational change has been studied for decades. However, using this relationship in a predictive context remains a challenge. In this work, we demonstrate that, starting from a given protein conformer, it is possible to generate in a single step model conformers that are less than 1 Å (Cα -RMSD) from the conformer which is the known endpoint of the conformational change, particularly when the conformational change is collective in nature. Such accurate model conformers can be generated by following either the so-called robust or the 50 lowest-frequency modes obtained with various Elastic Network Models (ENMs). Interestingly, the quality of many of these models compares well with actual crystal structures, as assessed by the ROSETTA scoring function and PROCHECK. The most accurate and best quality conformers obtained in the present study were generated by using the 50 lowest-frequency modes of an all-atom ENM. However, with less than ten robust modes, which are identified without any prior knowledge of the nature of the conformational change, nearly 90% of the motion described by the 50 lowest-frequency modes of a protein can be captured. Such results strongly suggest that exploring the robust modes of ENMs may prove efficient for sampling the functionally relevant conformational repertoire of many proteins. © 2017 Wiley Periodicals, Inc.

Highly stable digital holographic microscope using Sagnac interferometer.

Interferometric microscopy has grown into a very potent tool for quantitative phase imaging of biological samples. Among the interfermetric methods, microscopy by digital holography is one of the most effective techniques, especially for studying dynamics of cells. Imaging of cell fluctuations requires digital holographic setups with high temporal stability. Common path setups in which the object and the reference beams encounter the same set of optical elements provide better temporal stability compared to two-beam setups. Here, we present a compact, easy-to-implement, common path digital holographic microscope based on Sagnac interferometer geometry. The microscope is implemented using a diode laser module employing a CCD array or a webcam sensor to record holograms. The system was tested for three-dimensional imaging capability, numerical focusing ability, and temporal stability. Sub-nanometer temporal stability without external vibration isolation components was obtained in both cases. The higher temporal stability makes the microscope compatible to image cell fluctuations, which is demonstrated by imaging the oscillation of the cell membrane of human red blood cells.

On the relationship between low-frequency normal modes and the large-scale conformational changes of proteins.

Normal mode analysis is a computational technique that allows to study the dynamics of biological macromolecules. It was first applied to small protein cases, more than thirty years ago. The interest in this technique then raised when it was realized that it can provide insights about the large-scale conformational changes a protein can experience, for instance upon ligand binding. As it was also realized that studying highly simplified protein models can provide similar insights, meaning that this kind of analysis can be both quick and simple to handle, several applications were proposed, in the context of various structural biology techniques. This review focuses on these applications, as well as on how the functional relevance of the lowest-frequency modes of proteins was established.

Neoepitopes prediction strategies: an integration of cancer genomics and immunoinformatics approaches.

A major near-term medical impact of the genomic technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Next-generation sequencing technologies have accelerated the characterization of a tumor, leading to the comprehensive discovery of all the major alterations in a given cancer genome, followed by the translation of this information using computational and immunoinformatics approaches to cancer diagnostics and therapeutic efforts. In the current article, we review various components of cancer immunoinformatics applied to a series of fields of cancer research, including computational tools for cancer mutation detection, cancer mutation and immunological databases, and computational vaccinology.

Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins.

BACKGROUND: Most signalling and regulatory proteins participate in transient protein-protein interactions during biological processes. They usually serve as key regulators of various cellular processes and are often stable in both protein-bound and unbound forms. Availability of high-resolution structures of their unbound and bound forms provides an opportunity to understand the molecular mechanisms involved. In this work, we have addressed the question "What is the nature, extent, location and functional significance of structural changes which are associated with formation of protein-protein complexes?" RESULTS: A database of 76 non-redundant sets of high resolution 3-D structures of protein-protein complexes, representing diverse functions, and corresponding unbound forms, has been used in this analysis. Structural changes associated with protein-protein complexation have been investigated using structural measures and Protein Blocks description. Our study highlights that significant structural rearrangement occurs on binding at the interface as well as at regions away from the interface to form a highly specific, stable and functional complex. Notably, predominantly unaltered interfaces interact mainly with interfaces undergoing substantial structural alterations, revealing the presence of at least one structural regulatory component in every complex.Interestingly, about one-half of the number of complexes, comprising largely of signalling proteins, show substantial localized structural change at surfaces away from the interface. Normal mode analysis and available information on functions on some of these complexes suggests that many of these changes are allosteric. This change is largely manifest in the proteins whose interfaces are altered upon binding, implicating structural change as the possible trigger of allosteric effect. Although large-scale studies of allostery induced by small-molecule effectors are available in literature, this is, to our knowledge, the first study indicating the prevalence of allostery induced by protein effectors. CONCLUSIONS: The enrichment of allosteric sites in signalling proteins, whose mutations commonly lead to diseases such as cancer, provides support for the usage of allosteric modulators in combating these diseases.

Fibrous Dysplasia of Temporal Bone Presented as a Solitary Osteochondroma: A Case Report.

Introduction: Fibrous dysplasia is a benign disorder of unknown etiology. It represents a disturbance of normal bone development - a defect in osteoblastic differentiation and maturation that originates in the mesenchymal precursor of the bone. It is characterized by slow progressive replacement of bone by abnormal isomorphic fibrous tissue. Temporal bone involvement is extremely rare. We report an unusual case of fibrous dysplasia presented like a solitary osteochondroma. Case Report: A 14-year-old girl presented with the complaints of slow-growing swelling on the left temporal region in scalp near left eye for 2 years. The swelling was small to begin with, which increased gradually over a period of 2 years. There were no other presenting symptoms. Hearing was normal. Parents of the patient were concerned with cosmesis only. She had undergone 3D CT scan of skull where it showed bony outgrowth with features suggestive of exostosis. This bony outgrowth had cortex in continuity to cortex of temporal bone and medullary canal same as that of the temporal bone and ground-glass appearance. Repeat CT scan showed bony outgrowth with cortical continuity and had pedicle. It was suggestive of pedunculated osteochondroma. There was no evidence of malignant transformation as swelling showed calcified osteoid-like mass throughout. Hence, the clinical and radiological diagnosis of the left temporal bone solitary osteochondroma was made. However, histopathology showed irregularly shaped bony trabeculae in fibrous stroma of variable cellularity without accompanying osteoblast rimming. Thus, diagnosis was fibrous dysplasia of bone. Histopathological slide was reviewed by two independent pathologists with same conclusion. Conclusion: Our case was unique in that the lesion presented clinically and radiologically as solitary osteochondroma. However, in hindsight, lack of cartilage cap on CT scan should have prompted us to look for another diagnosis. To the best of our knowledge, this was unique varied presentation of fibrous dysplasia of temporal bone.

Immunodominant T-cell epitopes from the SARS-CoV-2 spike antigen reveal robust pre-existing T-cell immunity in unexposed individuals.

The COVID-19 pandemic has revealed a range of disease phenotypes in infected patients with asymptomatic, mild, or severe clinical outcomes, but the mechanisms that determine such variable outcomes remain unresolved. In this study, we identified immunodominant CD8 T-cell epitopes in the spike antigen using a novel TCR-binding algorithm. The predicted epitopes induced robust T-cell activation in unexposed donors demonstrating pre-existing CD4 and CD8 T-cell immunity to SARS-CoV-2 antigen. The T-cell reactivity to the predicted epitopes was higher than the Spike-S1 and S2 peptide pools in the unexposed donors. A key finding of our study is that pre-existing T-cell immunity to SARS-CoV-2 is contributed by TCRs that recognize common viral antigens such as Influenza and CMV, even though the viral epitopes lack sequence identity to the SARS-CoV-2 epitopes. This finding is in contrast to multiple published studies in which pre-existing T-cell immunity is suggested to arise from shared epitopes between SARS-CoV-2 and other common cold-causing coronaviruses. However, our findings suggest that SARS-CoV-2 reactive T-cells are likely to be present in many individuals because of prior exposure to flu and CMV viruses.

TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors.

The adaptive immune system in vertebrates has evolved to recognize non-self antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared seven metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR ß-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

Synthesis of silver nanoparticles colloids in imidazolium halide ionic liquids and their antibacterial activities for gram-positive and gram-negative bacteria.

Four 1-butyl-3-methylimidazolium halide ionic liquids were synthesized via metathesis and anion exchange reactions. Silver nanoparticles (AgNPs) colloids were synthesized in four ionic liquids in the pressurized reactor by reduction of silver nitrate with hydrogen gas, without adding solvents or stabilizing agents. Antibacterial activities of base ionic liquids and AgNPs colloids in ionic liquids were reviewed by well-diffusion method for gram-positive Bacillus cereus (NCIM-2155) and gram-negative Escherichia coli (NCIM-2931) bacteria. Antibacterial activities of ionic liquids and AgNPs colloids in ionic liquids were observed to be controlled by ionic liquids anions and AgNPs particle size. The 1-butyl-3-methylimidazolium iodide ionic liquid exhibited higher antibacterial activities among the studied ionic liquids. Further, the presence of AgNPs in 1-butyl-3-methylimidazolium iodide, ionic liquid enhanced its antibacterial activity for Bacillus cereus and Escherichia coli bacteria.

Antibody Specific B-Cell Epitope Predictions: Leveraging Information From Antibody-Antigen Protein Complexes.

B-cells can neutralize pathogenic molecules by targeting them with extreme specificity using receptors secreted or expressed on their surface (antibodies). This is achieved via molecular interactions between the paratope (i.e., the antibody residues involved in the binding) and the interacting region (epitope) of its target molecule (antigen). Discerning the rules that define this specificity would have profound implications for our understanding of humoral immunogenicity and its applications. The aim of this work is to produce improved, antibody-specific epitope predictions by exploiting features derived from the antigens and their cognate antibodies structures, and combining them using statistical and machine learning algorithms. We have identified several geometric and physicochemical features that are correlated in interacting paratopes and epitopes, used them to develop a Monte Carlo algorithm to generate putative epitopes-paratope pairs, and train a machine-learning model to score them. We show that, by including the structural and physicochemical properties of the paratope, we improve the prediction of the target of a given B-cell receptor. Moreover, we demonstrate a gain in predictive power both in terms of identifying the cognate antigen target for a given antibody and the antibody target for a given antigen, exceeding the results of other available tools.

A survey of known immune epitopes in the enteroviruses strains associated with acute flaccid myelitis.

Enteroviruses are potentially linked to the emergence of Acute Flaccid Myelitis (AFM), a rare but very serious condition that affects the nervous system. AFM has been associated with coxsackievirus A16, enterovirus A71 (EVA71) and enterovirus D68 (EVD68). Little is known about host-pathogen interactions for these viruses, and whether immune responses may have a protective or immunopathological role in disease presentations. Towards addressing this issue, we used the Immune Epitope Database to assess the known inventory of B and T cell epitopes from enteroviruses, focusing on data related to human hosts. The extent of conservation in areas that are targets of B and T cell immune responses were examined. This analysis sheds light on regions of the enterovirus polypeptide that can be probed to induce a specific or cross-reactive B or T cell the immune response to enteroviruses, with a particular focus on coxsackievirus A16, EVA71 and EVD68. In addition, these analyses reveal the current gap-of-knowledge in the T and B cell immune responses that future studies should aim to address.

TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexes.

The interaction between the class I major histocompatibility complex (MHC), the peptide presented by the MHC and the T-cell receptor (TCR) is a key determinant of the cellular immune response. Here, we present TCRpMHCmodels, a method for accurate structural modelling of the TCR-peptide-MHC (TCR-pMHC) complex. This TCR-pMHC modelling pipeline takes as input the amino acid sequence and generates models of the TCR-pMHC complex, with a median Cα RMSD of 2.31 Å. TCRpMHCmodels significantly outperforms TCRFlexDock, a specialised method for docking pMHC and TCR structures. TCRpMHCmodels is simple to use and the modelling pipeline takes, on average, only two minutes. Thanks to its ease of use and high modelling accuracy, we expect TCRpMHCmodels to provide insights into the underlying mechanisms of TCR and pMHC interactions and aid in the development of advanced T-cell-based immunotherapies and rational design of vaccines. The TCRpMHCmodels tool is available at http://www.cbs.dtu.dk/services/TCRpMHCmodels/ .

Wavefront division digital holographic microscopy.

Digital holographic microscopy is the state of the art quantitative phase imaging of micro-objects including living cells. It is an ideal tool to image and quantify cell thickness profiles with nanometer thickness resolution. Digital holographic techniques usually are implemented using a two-beam setup that may be bulky and may not be field portable. Self-referencing techniques provide compact geometry but suffer from a reduction of the field of view. Here, we discuss the development of a wavefront division digital holographic microscope providing the full field of view with a compact system. The proposed approach uses a wavefront division module consisting of two lenses. The developed microscope is tested experimentally by measuring the physical and mechanical properties of red blood cells.

Epitope Specific Antibodies and T Cell Receptors in the Immune Epitope Database.

The Immune Epitope Database (IEDB) is a free public resource which catalogs experiments characterizing immune epitopes. To accommodate data from next generation repertoire sequencing experiments, we recently updated how we capture and query epitope specific antibodies and T cell receptors. Specifically, we are now storing partial receptor sequences sufficient to determine CDRs and VDJ gene usage which are commonly identified by repertoire sequencing. For previously captured full length receptor sequencing data, we have calculated the corresponding CDR sequences and gene usage information using IMGT numbering and VDJ gene nomenclature format. To integrate information from receptors defined at different levels of resolution, we grouped receptors based on their host species, receptor type and CDR3 sequence. As of August 2018, we have cataloged sequence information for more than 22,510 receptors in 18,292 receptor groups, shown to bind to more than 2,241 distinct epitopes. These data are accessible as full exports and through a new dedicated query interface. The later combines the new ability to search by receptor characteristics with previously existing capability to search by epitope characteristics such as the infectious agent the epitope is derived from, or the kind of immune response involved in its recognition. We expect that this comprehensive capture of epitope specific immune receptor information will provide new insights into receptor-epitope interactions, and facilitate the development of novel tools that help in the analysis of receptor repertoire data.

[Gastroschisis repair under caudal anesthesia: a series of three cases]. / Correção de gastrosquise sob anestesia caudal: uma série de três casos.

Gastroschisis is a congenital anomaly characterized by a defect in the anterior abdominal wall with protrusion of abdominal viscera. Perioperative mortality is very high in these patients. Traditionally gastroschisis repair has been performed under general anesthesia with endotracheal intubation, requiring postoperative intensive care admission and mechanical ventilation. Caudal block is an attractive alternative to general anesthesia. We present a series of three neonates with gastroschisis, repaired solely under caudal anesthesia.

The Immune Epitope Database and Analysis Resource in Epitope Discovery and Synthetic Vaccine Design.

The task of epitope discovery and vaccine design is increasingly reliant on bioinformatics analytic tools and access to depositories of curated data relevant to immune reactions and specific pathogens. The Immune Epitope Database and Analysis Resource (IEDB) was indeed created to assist biomedical researchers in the development of new vaccines, diagnostics, and therapeutics. The Analysis Resource is freely available to all researchers and provides access to a variety of epitope analysis and prediction tools. The tools include validated and benchmarked methods to predict MHC class I and class II binding. The predictions from these tools can be combined with tools predicting antigen processing, TCR recognition, and B cell epitope prediction. In addition, the resource contains a variety of secondary analysis tools that allow the researcher to calculate epitope conservation, population coverage, and other relevant analytic variables. The researcher involved in vaccine design and epitope discovery will also be interested in accessing experimental published data, relevant to the specific indication of interest. The database component of the IEDB contains a vast amount of experimentally derived epitope data that can be queried through a flexible user interface. The IEDB is linked to other pathogen-specific and immunological database resources.

Knowledge-based prediction of protein backbone conformation using a structural alphabet.

Libraries of structural prototypes that abstract protein local structures are known as structural alphabets and have proven to be very useful in various aspects of protein structure analyses and predictions. One such library, Protein Blocks, is composed of 16 standard 5-residues long structural prototypes. This form of analyzing proteins involves drafting its structure as a string of Protein Blocks. Predicting the local structure of a protein in terms of protein blocks is the general objective of this work. A new approach, PB-kPRED is proposed towards this aim. It involves (i) organizing the structural knowledge in the form of a database of pentapeptide fragments extracted from all protein structures in the PDB and (ii) applying a knowledge-based algorithm that does not rely on any secondary structure predictions and/or sequence alignment profiles, to scan this database and predict most probable backbone conformations for the protein local structures. Though PB-kPRED uses the structural information from homologues in preference, if available. The predictions were evaluated rigorously on 15,544 query proteins representing a non-redundant subset of the PDB filtered at 30% sequence identity cut-off. We have shown that the kPRED method was able to achieve mean accuracies ranging from 40.8% to 66.3% depending on the availability of homologues. The impact of the different strategies for scanning the database on the prediction was evaluated and is discussed. Our results highlight the usefulness of the method in the context of proteins without any known structural homologues. A scoring function that gives a good estimate of the accuracy of prediction was further developed. This score estimates very well the accuracy of the algorithm (R2 of 0.82). An online version of the tool is provided freely for non-commercial usage at http://www.bo-protscience.fr/kpred/.