An integrated approach to epitope analysis II: A system for proteomic-scale prediction of immunological characteristics

Immunome Research, Dec 2010

Background Improving our understanding of the immune response is fundamental to developing strategies to combat a wide range of diseases. We describe an integrated epitope analysis system which is based on principal component analysis of sequences of amino acids, using a multilayer perceptron neural net to conduct QSAR regression predictions for peptide binding affinities to 35 MHC-I and 14 MHC-II alleles. Results The approach described allows rapid processing of single proteins, entire proteomes or subsets thereof, as well as multiple strains of the same organism. It enables consideration of the interface of diversity of both microorganisms and of host immunogenetics. Patterns of binding affinity are linked to topological features, such as extracellular or intramembrane location, and integrated into a graphical display which facilitates conceptual understanding of the interplay of B-cell and T-cell mediated immunity. Patterns which emerge from application of this approach include the correlations between peptides showing high affinity binding to MHC-I and to MHC-II, and also with predicted B-cell epitopes. These are characterized as coincident epitope groups (CEGs). Also evident are long range patterns across proteins which identify regions of high affinity binding for a permuted population of diverse and heterozygous HLA alleles, as well as subtle differences in reactions with MHCs of individual HLA alleles, which may be important in disease susceptibility, and in vaccine and clinical trial design. Comparisons are shown of predicted epitope mapping derived from application of the QSAR approach with experimentally derived epitope maps from a diverse multi-species dataset, from Staphylococcus aureus, and from vaccinia virus. Conclusions A desktop application with interactive graphic capability is shown to be a useful platform for development of prediction and visualization tools for epitope mapping at scales ranging from individual proteins to proteomes from multiple strains of an organism. The possible functional implications of the patterns of peptide epitopes observed are discussed, including their implications for B-cell and T-cell cooperation and cross presentation.

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An integrated approach to epitope analysis II: A system for proteomic-scale prediction of immunological characteristics

Immunome Research An integrated approach to epitope analysis II: A system for proteomic-scale prediction of immunological characteristics Robert D Bremel E Jane Homan 0 ioGenetics LLC , 3591 Anderson Street, Madison, WI 53704 , USA Background: Improving our understanding of the immune response is fundamental to developing strategies to combat a wide range of diseases. We describe an integrated epitope analysis system which is based on principal component analysis of sequences of amino acids, using a multilayer perceptron neural net to conduct QSAR regression predictions for peptide binding affinities to 35 MHC-I and 14 MHC-II alleles. Results: The approach described allows rapid processing of single proteins, entire proteomes or subsets thereof, as well as multiple strains of the same organism. It enables consideration of the interface of diversity of both microorganisms and of host immunogenetics. Patterns of binding affinity are linked to topological features, such as extracellular or intramembrane location, and integrated into a graphical display which facilitates conceptual understanding of the interplay of B-cell and T-cell mediated immunity. Patterns which emerge from application of this approach include the correlations between peptides showing high affinity binding to MHC-I and to MHC-II, and also with predicted B-cell epitopes. These are characterized as coincident epitope groups (CEGs). Also evident are long range patterns across proteins which identify regions of high affinity binding for a permuted population of diverse and heterozygous HLA alleles, as well as subtle differences in reactions with MHCs of individual HLA alleles, which may be important in disease susceptibility, and in vaccine and clinical trial design. Comparisons are shown of predicted epitope mapping derived from application of the QSAR approach with experimentally derived epitope maps from a diverse multi-species dataset, from Staphylococcus aureus, and from vaccinia virus. Conclusions: A desktop application with interactive graphic capability is shown to be a useful platform for development of prediction and visualization tools for epitope mapping at scales ranging from individual proteins to proteomes from multiple strains of an organism. The possible functional implications of the patterns of peptide epitopes observed are discussed, including their implications for B-cell and T-cell cooperation and cross presentation. - Background The availability of proteomic information is increasing exponentially. This is especially true for pathogenic microorganisms. Integration and interpretation of vast amounts of data from the analysis of proteomic information, so that it may be useful to bench scientists and clinicians is a growing challenge. Achieving this goal is essential if bioinformatic analysis is to lead to improved vaccines and antibody therapies and to a better understanding of patient and population responses to infections, cancers, autoimmune epitopes, and allergens. Experimental approaches to definition of epitopes are time consuming and expensive; predictive methods can provide maps which could reduce the effort needed in experimental characterization. Current Challenges in Epitope Analysis In reviewing approaches to epitope characterization described in the literature, both experimentally and through the use of computer-based analysis, three broad shortcomings become apparent. First, literature reports of experimental approaches to epitope characterization have often been narrow in scope, based on the response of individual patients, cells from a few individual donors or single strains of mice, or focused on isolated peptides. This has generated valid data, but which is specific to the narrow set of circumstances and not reflective of the broader host or organism population. Discovering binding affinity for an MHC molecule of a single HLA haplotype will not necessarily be predictive for a population of diverse heterozygotic individuals. Many literature reports claim Tcell epitope characterization but fail to report the MHC restriction (mouse) or HLA of cells used. By limiting consideration to isolated peptides, an important feature of cell biology is overlooked. Binding to MHC-I and MHC-II molecules is a competitive and dynamic process [1,2]. MHC molecules bind to peptides selected from among all those competitors which result from the proteolysis of the whole organism. Predictive determinations of preferential epitope binding can thus only be made when considered in the context of the whole proteome, or, at very least, the whole protein, but not for isolated peptides. Second, from an epidemiologic perspective the outcome of infection is dependent on the interface between a population of heterozygous hosts and a diverse array of microbial strains. Many possible interactions of individual and strain are possible. Depending on the context, the challenge in vaccine design may be to choose the best combination of (...truncated)


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Robert D Bremel, E Jane Homan. An integrated approach to epitope analysis II: A system for proteomic-scale prediction of immunological characteristics, Immunome Research, 2010, pp. 8, Volume 6, Issue 1, DOI: 10.1186/1745-7580-6-8