302 research outputs found

    Computer aided selection of candidate vaccine antigens

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    Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens

    T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

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    Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics

    Integrating In Silico and In Vitro Analysis of Peptide Binding Affinity to HLA-Cw*0102: A Bioinformatic Approach to the Prediction of New Epitopes

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    Background: Predictive models of peptide-Major Histocompatibility Complex (MHC) binding affinity are important components of modern computational immunovaccinology. Here, we describe the development and deployment of a reliable peptide-binding prediction method for a previously poorly-characterized human MHC class I allele, HLA-Cw*0102. Methodology/Findings: Using an in-house, flow cytometry-based MHC stabilization assay we generated novel peptide binding data, from which we derived a precise two-dimensional quantitative structure-activity relationship (2D-QSAR) binding model. This allowed us to explore the peptide specificity of HLA-Cw*0102 molecule in detail. We used this model to design peptides optimized for HLA-Cw*0102-binding. Experimental analysis showed these peptides to have high binding affinities for the HLA-Cw*0102 molecule. As a functional validation of our approach, we also predicted HLA-Cw*0102-binding peptides within the HIV-1 genome, identifying a set of potent binding peptides. The most affine of these binding peptides was subsequently determined to be an epitope recognized in a subset of HLA-Cw*0102-positive individuals chronically infected with HIV-1. Conclusions/Significance: A functionally-validated in silico-in vitro approach to the reliable and efficient prediction of peptide binding to a previously uncharacterized human MHC allele HLA-Cw*0102 was developed. This technique is generally applicable to all T cell epitope identification problems in immunology and vaccinology

    Serum autoantibody measurement for the detection of hepatocellular carcinoma

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    Background: Individuals with liver disease, and especially those with Hepatitis B or C, are at an increased risk of developing hepatocellular carcinoma (HCC) which is the third most common cause of cancer-related death worldwide. Inadequate screening tests largely account for presentation of advanced tumours and high mortality rates. Early detection of HCC amongst high-risk groups is paramount in improving prognosis. This research aimed to further characterise the previously described humoral immune response raised to tumour-associated antigens (TAAs) in the serum of patients with HCC.Methods: Serum from 96 patients with confirmed HCC, 96 healthy controls matched for age and sex, 78 patients with confirmed liver cirrhosis and 91 patients with confirmed chronic liver disease were analysed for the presence of IgG autoantibodies raised to 41 recombinant TAAs/antigen fragments by ELISA.Results: Varying autoantibody specificities (97–100%) and sensitivities (0–10%) were observed to individual TAAs. A 21-antigen panel achieved a specificity of 92% and sensitivity of 45% for the detection of HCC. This same panel identified 21% of 169 high-risk controls as having elevated autoantibody levels. A reproducible panel of 10 antigens achieved a specificity of 91% and sensitivity of 41% in HCC. 15% of 152 high-risk controls gave positive results with this panel.Conclusions: This minimally invasive blood test has the potential to offer advantages over currently available tools for the identification of HCC amongst pre-disposed patients. Results are comparable to current gold standards in HCC (Ultrasonography) and to similar tests in other cancers (EarlyCDT-Lung)

    JWST-TST DREAMS: Quartz Clouds in the Atmosphere of WASP-17b

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    Clouds are prevalent in many of the exoplanet atmospheres that have been observed to date. For transiting exoplanets, we know if clouds are present because they mute spectral features and cause wavelength-dependent scattering. While the exact composition of these clouds is largely unknown, this information is vital to understanding the chemistry and energy budget of planetary atmospheres. In this work, we observe one transit of the hot Jupiter WASP-17b with JWST's MIRI LRS and generate a transmission spectrum from 5-12 μ\rm{\mu}m. These wavelengths allow us to probe absorption due to the vibrational modes of various predicted cloud species. Our transmission spectrum shows additional opacity centered at 8.6 μ\rm{\mu}m, and detailed atmospheric modeling and retrievals identify this feature as SiO2_2(s) (quartz) clouds. The SiO2_2(s) clouds model is preferred at 3.5-4.2σ\sigma versus a cloud-free model and at 2.6σ\sigma versus a generic aerosol prescription. We find the SiO2_2(s) clouds are comprised of small 0.01{\sim}0.01 μ\rm{\mu}m particles, which extend to high altitudes in the atmosphere. The atmosphere also shows a depletion of H2_2O, a finding consistent with the formation of high-temperature aerosols from oxygen-rich species. This work is part of a series of studies by our JWST Telescope Scientist Team (JWST-TST), in which we will use Guaranteed Time Observations to perform Deep Reconnaissance of Exoplanet Atmospheres through Multi-instrument Spectroscopy (DREAMS).Comment: 19 pages, 7 figures, accepted for publication in ApJ

    Acupuncture and rehabilitation of the painful shoulder: study protocol of an ongoing multicentre randomised controlled clinical trial [ISRCTN28687220]

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    BACKGROUND: Although the painful shoulder is one of the most common dysfunctions of the locomotor apparatus, and is frequently treated both at primary healthcare centres and by specialists, little evidence has been reported to support or refute the effectiveness of the treatments most commonly applied. According to the bibliography reviewed, physiotherapy, which is the most common action taken to alleviate this problem, has not yet been proven to be effective, because of the small size of sample groups and the lack of methodological rigor in the papers published on the subject. No reviews have been made to assess the effectiveness of acupuncture in treating this complaint, but in recent years controlled randomised studies have been made and these demonstrate an increasing use of acupuncture to treat pathologies of the soft tissues of the shoulder. In this study, we seek to evaluate the effectiveness of physiotherapy applied jointly with acupuncture, compared with physiotherapy applied with a TENS-placebo, in the treatment of painful shoulder caused by subacromial syndrome (rotator cuff tendinitis and subacromial bursitis). METHODS/DESIGN: Randomised controlled multicentre study with blind evaluation by an independent observer and blind, independent analysis. A study will be made of 465 patients referred to the rehabilitation services at participating healthcare centres, belonging to the regional public health systems of Andalusia and Murcia, these patients presenting symptoms of painful shoulder and a diagnosis of subacromial syndrome (rotator cuff tendinitis and subacromial bursitis). The patients will be randomised into two groups: 1) experimental (acupuncture + physiotherapy); 2) control (TENS-placebo + physiotherapy); the administration of rescue medication will also be allowed. The treatment period will have a duration of three weeks. The main result variable will be the change produced on Constant's Shoulder Function Assessment (SFA) Scale; as secondary variables, we will record the changes in diurnal pain intensity on a visual analogue scale (VAS), nocturnal pain intensity on the VAS, doses of non-steroid anti-inflammatory drugs (NSAIDs) taken during the study period, credibility scale for the treatment, degree of improvement perceived by the patient and degree of improvement perceived by the evaluator. A follow up examination will be made at 3, 6 and 12 months after the study period has ended. Two types of population will be considered for analysis: per protocol and per intention to treat. DISCUSSION: The discussion will take into account the limitations of the study, together with considerations such as the choice of a simple, safe method to treat this shoulder complaint, the choice of the control group, and the blinding of the patients, evaluators and those responsible for carrying out the final analysis

    The unruptured intracranial aneurysm treatment score A multidisciplinary consensus

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    Objective: We endeavored to develop an unruptured intracranial aneurysm (UIA) treatment score (UIATS) model that includes and quantifies key factors involved in clinical decision-making in the management of UIAs and to assess agreement for this model among specialists in UIA management and research. Methods: An international multidisciplinary (neurosurgery, neuroradiology, neurology, clinical epidemiology) group of 69 specialists was convened to develop and validate the UIATS model using a Delphi consensus. For internal (39 panel members involved in identification of relevant features) and external validation (30 independent external reviewers), 30 selected UIA cases were used to analyze agreement with UIATS management recommendations based on a 5-point Likert scale (5 indicating strong agreement). Interrater agreement (IRA) was assessed with standardized coefficients of dispersion (v(r)*) (v(r)* 5 0 indicating excellent agreement and v(r)* = 1 indicating poor agreement). Results: The UIATS accounts for 29 key factors in UIA management. Agreement with UIATS (mean Likert scores) was 4.2 (95% confidence interval [CI] 4.1-4.3) per reviewer for both reviewer cohorts; agreement per case was 4.3 (95% CI 4.1-4.4) for panel members and 4.5 (95% CI 4.3-4.6) for external reviewers (p = 0.017). Mean Likert scores were 4.2 (95% CI 4.1-4.3) for interventional reviewers (n = 56) and 4.1 (95% CI 3.9-4.4) for noninterventional reviewers (n = 12) (p = 0.290). Overall IRA (v(r)*) for both cohorts was 0.026 (95% CI 0.019-0.033). Conclusions: This novel UIA decision guidance study captures an excellent consensus among highly informed individuals on UIA management, irrespective of their underlying specialty. Clinicians can use the UIATS as a comprehensive mechanism for indicating how a large group of specialists might manage an individual patient with a UIA.Peer reviewe

    MHC Class I Bound to an Immunodominant Theileria parva Epitope Demonstrates Unconventional Presentation to T Cell Receptors

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    T cell receptor (TCR) recognition of peptide-MHC class I (pMHC) complexes is a crucial event in the adaptive immune response to pathogens. Peptide epitopes often display a strong dominance hierarchy, resulting in focusing of the response on a limited number of the most dominant epitopes. Such T cell responses may be additionally restricted by particular MHC alleles in preference to others. We have studied this poorly understood phenomenon using Theileria parva, a protozoan parasite that causes an often fatal lymphoproliferative disease in cattle. Despite its antigenic complexity, CD8+ T cell responses induced by infection with the parasite show profound immunodominance, as exemplified by the Tp1214–224 epitope presented by the common and functionally important MHC class I allele N*01301. We present a high-resolution crystal structure of this pMHC complex, demonstrating that the peptide is presented in a distinctive raised conformation. Functional studies using CD8+ T cell clones show that this impacts significantly on TCR recognition. The unconventional structure is generated by a hydrophobic ridge within the MHC peptide binding groove, found in a set of cattle MHC alleles. Extremely rare in all other species, this feature is seen in a small group of mouse MHC class I molecules. The data generated in this analysis contribute to our understanding of the structural basis for T cell-dependent immune responses, providing insight into what determines a highly immunogenic p-MHC complex, and hence can be of value in prediction of antigenic epitopes and vaccine design
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