Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants

Abstract

Complete characterization of antibody specificities associated to natural infections is expected to provide a rich source of serologic biomarkers with potential applications in molecular diagnosis, follow-up of chemotherapeutic treatments, and prioritization of targets for vaccine development. Here, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than 175,000 overlapping 15mer peptides derived from T. cruzi proteins. Peptides were synthesized in situ on microarray slides, spanning the complete length of 457 parasite proteins with fully overlapped 15mers (1 residue shift). Screening of these slides with antibodies purified from infected patients and healthy donors demonstrated both a high technical reproducibility as well as epitope mapping consistency when compared with earlier low-throughput technologies. Using a conservative signal threshold to classify positive (reactive) peptides we identified 2,031 disease-specific peptides and 97 novel parasite antigens, effectively doubling the number of known antigens and providing a 10-fold increase in the number of fine mapped antigenic determinants for this disease. Finally, further analysis of the chip data showed that optimizing the amount of sequence overlap of displayed peptides can increase the protein space covered in a single chip by at least ∼threefold without sacrificing sensitivity. In conclusion, we show the power of high-density peptide chips for the discovery of pathogen-specific linear B-cell epitopes from clinical samples, thus setting the stage for high-throughput biomarker discovery screenings and proteome-wide studies of immune responses against pathogens.

Current tools for predicting cancer-specific T cell immunity

“…21 A promising perspective is pMHC multimer arrays allowing detection of hundreds of T cell specificities in one sample. 94 In view of the rapid progress in microfluidic multiplexing technologies the number of T cells that can be enumerated and analyzed is likely to increase dramatically in the near future.…”

“…In view of recent progress in peptide microarray technology it may become possible to rapidly screen very high numbers of peptides binding to MHC II and perhaps also MHC I molecules. 63,64,94 Alternatively, MS immune-peptidome analysis may be combined with UV irradiation induced exchange of conditional MHC ligands with libraries of predicted peptides. 49,50,70 A powerful strategy of epitope discovery and T cell analysis consist in using peptide exchange combined with combinatorial multimer flow cytometry analysis of patient's TIL or PBMC.…”

Optimal threshold estimation for binary classifiers using game theory

“…However, to our knowledge, skew-indifference has not been exploited for optimal threshold estimation. Furthermore, the operating point of a classifier is often chosen by balancing sensitivity and specificity, without reference to the rationale behind 7 . Our game theory analysis shows that this empirical practice can be understood as a maximization of classifier robustness.…”

Neglected Tropical Diseases in the Post-Genomic Era

“…Using T. cruzi as an example, we recently designed high-density tiling peptide chips spanning the full-length of 500 parasite proteins from the deduced proteome [122]. These peptide arrays have been screened with sera from Chagasic patients (and healthy controls), and this led to the simultaneous identification and mapping of hundreds of novel parasite B cell antigens/epitopes.…”