2,605 research outputs found

    CD4+ Th immunogenicity of the Ascaris spp. secreted products

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    Ascaris spp. is a major health problem of humans and animals alike, and understanding the immunogenicity of its antigens is required for developing urgently needed vaccines. The parasite-secreted products represent the most relevant, yet complex (>250 proteins) antigens of Ascaris spp. as defining the pathogen-host interplay. We applied an in vitro antigen processing system coupled to quantitative proteomics to identify potential CD4+ Th cell epitopes in Ascaris-secreted products. This approach considerably restricts the theoretical list of epitopes using conventional CD4+ Th cell epitope prediction tools. We demonstrate the specificity and utility of our approach on two sets of candidate lists, allowing us identifying hits excluded by either one or both computational methods. More importantly, one of the candidates identified experimentally, clearly demonstrates the presence of pathogen-reactive T cells in healthy human individuals against these antigens. Thus, our work pipeline identifies the first human T cell epitope against Ascaris spp. and represents an easily adaptable platform for characterization of complex antigens, in particular for those pathogens that are not easily amenable for in vivo experimental validation

    Prediction of the binding affinities of peptides to class II MHC using a regularized thermodynamic model

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    <p>Abstract</p> <p>Background</p> <p>The binding of peptide fragments of extracellular peptides to class II MHC is a crucial event in the adaptive immune response. Each MHC allotype generally binds a distinct subset of peptides and the enormous number of possible peptide epitopes prevents their complete experimental characterization. Computational methods can utilize the limited experimental data to predict the binding affinities of peptides to class II MHC.</p> <p>Results</p> <p>We have developed the Regularized Thermodynamic Average, or RTA, method for predicting the affinities of peptides binding to class II MHC. RTA accounts for all possible peptide binding conformations using a thermodynamic average and includes a parameter constraint for regularization to improve accuracy on novel data. RTA was shown to achieve higher accuracy, as measured by AUC, than SMM-align on the same data for all 17 MHC allotypes examined. RTA also gave the highest accuracy on all but three allotypes when compared with results from 9 different prediction methods applied to the same data. In addition, the method correctly predicted the peptide binding register of 17 out of 18 peptide-MHC complexes. Finally, we found that suboptimal peptide binding registers, which are often ignored in other prediction methods, made significant contributions of at least 50% of the total binding energy for approximately 20% of the peptides.</p> <p>Conclusions</p> <p>The RTA method accurately predicts peptide binding affinities to class II MHC and accounts for multiple peptide binding registers while reducing overfitting through regularization. The method has potential applications in vaccine design and in understanding autoimmune disorders. A web server implementing the RTA prediction method is available at <url>http://bordnerlab.org/RTA/</url>.</p

    MHCherryPan, a novel model to predict the binding affinity of pan-specific class I HLA-peptide

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    The human leukocyte antigen (HLA) system or complex plays an essential role in regulating the immune system in humans. Accurate prediction of peptide binding with HLA can efficiently help to identify those neoantigens, which potentially make a big difference in immune drug development. HLA is one of the most polymorphic genetic systems in humans, and thousands of HLA allelic versions exist. Due to the high polymorphism of HLA complex, it is still pretty difficult to accurately predict the binding affinity. In this thesis, we presented a new algorithm to combine convolutional neural network and long short-term memory to solve this problem. Compared with other current popular algorithms, our model achieved the state-of-the-art results

    Decellularized Matrices Effect on the Adaptive Immune Response

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    Decellularized extracellular matrices have been a growing area of interest in the biomedical engineering fields of tissue engineering and regenerative medicine.As these materials move toward clinical applications, the immune response to these materials will be a driving force toward their success in clinical approaches. Fully digested decellularized matrix constructs derived from porcine liver, muscle and lung were created to test the adaptive immune response. Hydrogel characterization ensured that the materials had relatively similar stiffness levels to reduce variability, and in vitro studies were conducted. Each individual construct as well as a gelatin control were plated with a co-culture of macrophages and T-cells to measure T-cell proliferation. In addition standard markers of inflammation through qPCR were measured in the macrophage group. Constructs were then placed into animals for 3 and 7 days in addition to a second group that received constructs for 21 days before secondary constructs were placed. These groups were then sacrificed following 3, 7 and 14 days to measure the residual and memory-like response of the constructs. Our results showed that t-cell proliferation was increased with decellularized constructs, particularly in tissue with higher DNA content. In vivo, animals with secondary treatments showed extended inflammatory response, driven by Th1 and Th17 polarization suggesting a memory-like response due to recognition of peptides in the constructs from secondary placements

    Selection and Demography Drive Range-Wide Patterns of Mhc Variation in Mule Deer (odocoileus Hemionus)

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    Variation at functional genes involved in immune response is of increasing concern as wildlife diseases continue to emerge and threaten populations. The amount of standing genetic variation in a population is directly associated with its potential for rapid adaptation to novel environments. For genes in the major histocompatibility complex (MHC), which are crucial in activating the immune response and which have extremely high levels of polymorphism, the genetic variation has been shown to be influenced by both parasite-mediated selection and historical population demography. To better understand the relative roles of parasite-mediated selection and demography on MHC evolution in large populations, I analyzed geographic patterns of variation at the MHC DRB class II locus in mule deer (Odocoileus hemionus). I identified 31 new MHC-DRB alleles which were phylogenetically similar to other cervid MHC alleles, and I found 1 allele that was shared with white-tailed deer (Odocoileus virginianus). I found evidence for selection on the MHC based on high dN/dS ratios, positive neutrality tests, deviations from Hardy-Weinberg Equilibrium (HWE) and greater isolation-by-distance (IBD) than expected under neutrality. However, I also saw evidence that historical demography is important in shaping variation at the MHC, in the similar variation structures between MHC and microsatellites and the lack of significant environmental drivers of variation at either locus. These results show that both natural selection and historical demography are important drivers in the evolution of the MHC in mule deer and may aid in predicting how future adaptation is shaped when this species is confronted with environmental challenges

    High-Throughput Engineering and Analysis of Class II Mhc/Peptide Binding by Yeast Co-Display

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    Polymorphisms of major histocompatibility complex (MHC) and molecular mechanisms of their antigen-presenting specificity and promiscuity have great impact on T cell-mediated immune responses and related diseases. Challenges in elucidating the characteristics of antigenic peptide binding by MHC motivate the development of high throughput experimental tools to quantitatively analyze interactions between hundreds of MHC allelic proteins and various peptide sequences. We demonstrated such a method by co-displaying target peptides and class II MHC (MHC-II) on the yeast surface in an intracellular association-dependent manner. The optimized yeast co-display system enabled quantitative mapping of side-chain preferences and general motifs for peptides binding to MHC-II by site-directed mutagenesis or peptide library screening, and also allowed rapid tailoring of MHC-II peptide binding specificity by directed evolution approaches, which derived MHC-II allelic mutants with altered peptide binding specificity or hyper-promiscuity. Comparison of these experimentally engineered mutants with naturally discovered MHC-II proteins recovered valuable information about structure-function relationship in the evolutionary mechanisms for polymorphic MHC-II molecules, which could direct future immunotherapeutic innovation
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