Deciphering epitope specificities within polyserum using affinity selection of random peptides and a novel algorithm based on pattern recognition theory

Denisov, D. A.; Denisova, Galina; Lelic, Alina; Loeb, Mark; Bramson, Jonathan L.

doi:10.1016/j.molimm.2008.10.013

Cited by 8 publications

(10 citation statements)

References 37 publications

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“…We have been investigating methods that employ affinity-selection of random peptides to provide an unbiased approach to epitope characterization. We have previously demonstrated that this method can be used to characterize the target epitopes of monoclonal antibodies [6], [7], [8], [9], [10], [11], [12], [13], [14] and, more recently, we have also applied this technology to polyclonal serum [15]. Manipulation and identification of random peptides is facilitated by the use of phage-display [16] where the random peptides presented on the phage surface serve as peptidomimetics of conformational and discontinuous antibody epitopes [17], [18] referred to commonly as “mimotopes”.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Complex Polysera Produced by Antigen-Specific Immunization through the Use of Affinity-Selected Mimotopes

et al. 2009

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BackgroundAntigen-based (as opposed to whole organism) vaccines are actively being pursued for numerous indications. Even though different formulations may produce similar levels of total antigen-specific antibody, the composition of the antibody response can be quite distinct resulting in different levels of therapeutic activity.Methodology/Principal FindingsUsing plasmid-based immunization against the proto-oncogene HER-2 as a model, we have demonstrated that affinity-selected epitope mimetics (mimotopes) can provide a defined signature of a polyclonal antibody response. Further, using novel computer algorithms that we have developed, these mimotopes can be used to predict epitope targets.Conclusions/SignificanceBy combining our novel strategy with existing methods of epitope prediction based on physical properties of an individual protein, we believe that this method offers a robust method for characterizing the breadth of epitope-specificity within a specific polyserum. This strategy is useful as a tool for monitoring immunity following vaccination and can also be used to define relevant epitopes for the creation of novel vaccines.

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Section: Introductionmentioning

confidence: 99%

Characterizing Complex Polysera Produced by Antigen-Specific Immunization through the Use of Affinity-Selected Mimotopes

et al. 2009

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“…Many different methods including solid phase peptide libraries and phage displayed peptide libraries [5,6] have been used to screen for linear epitopes. Although peptide display systems offer high-throughput identification of linear mimotopes [7] they have biases with regard to certain sequence populations and selection steps [6,8,9].…”

Section: Introductionmentioning

confidence: 99%

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

et al. 2017

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Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity.B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, high-resolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such large-scale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.

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“…To deal with the complexity of large collections of conformational mimotopes, we have developed a novel method based on pattern recognition theory [45-47] (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

“…The signs we employ are amino acid pairs chosen from different positions within an epitope sequence; unique signs can be identified which are specific to individual epitopes. Such signs can also be identified by direct analysis of theoretically predicted epitopes [45,48]. During the identification phase, mimotopes selected using patient polyserum are interrogated for the presence of the epitope specific signs found during the learning phase.…”

Section: Introductionmentioning

confidence: 99%

“…Using statistical methods, mimotopes are subsequently identified based on their signs and assigned to specific epitopes. We recently published a report describing the use of this approach for characterizing the epitope specificity of polysera from West Nile virus patients [45]. To accomplish this goal, we discovered signs during the learning step using a recently catalogued database of peptides that were affinity-selected using monoclonal antibodies specific for the West Nile virus E protein [31].…”

Section: Introductionmentioning

confidence: 99%

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Applying bioinformatics for antibody epitope prediction using affinity-selected mimotopes – relevance for vaccine design

2010

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To properly characterize protective polyclonal antibody responses, it is necessary to examine epitope specificity. Most antibody epitopes are conformational in nature and, thus, cannot be identified using synthetic linear peptides. Cyclic peptides can function as mimetics of conformational epitopes (termed mimotopes), thereby providing targets, which can be selected by immunoaffinity purification. However, the management of large collections of random cyclic peptides is cumbersome. Filamentous bacteriophage provides a useful scaffold for the expression of random peptides (termed phage display) facilitating both the production and manipulation of complex peptide libraries. Immunoaffinity selection of phage displaying random cyclic peptides is an effective strategy for isolating mimotopes with specificity for a given antiserum. Further epitope prediction based on mimotope sequence is not trivial since mimotopes generally display only small homologies with the target protein. Large numbers of unique mimotopes are required to provide sufficient sequence coverage to elucidate the target epitope. We have developed a method based on pattern recognition theory to deal with the complexity of large collections of conformational mimotopes. The analysis consists of two phases: 1) The learning phase where a large collection of epitope-specific mimotopes is analyzed to identify epitope specific “signs” and 2) The identification phase where immunoaffinity-selected mimotopes are interrogated for the presence of the epitope specific “signs” and assigned to specific epitopes. We are currently using computational methods to define epitope “signs” without the need for prior knowledge of specific mimotopes. This technology provides an important tool for characterizing the breadth of antibody specificities within polyclonal antisera.

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Deciphering epitope specificities within polyserum using affinity selection of random peptides and a novel algorithm based on pattern recognition theory

Cited by 8 publications

References 37 publications

Characterizing Complex Polysera Produced by Antigen-Specific Immunization through the Use of Affinity-Selected Mimotopes

Characterizing Complex Polysera Produced by Antigen-Specific Immunization through the Use of Affinity-Selected Mimotopes

ArrayPitope: Automated Analysis of Amino Acid Substitutions for Peptide Microarray-Based Antibody Epitope Mapping

Applying bioinformatics for antibody epitope prediction using affinity-selected mimotopes – relevance for vaccine design

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