HIGH-THROUGHPUT EPITOPE DISCOVERY: USE OF NEXT-GENERATION PEPTIDE CHIPS FOR FAST IDENTIFICATION AND FINE MAPPING OF DIAGNOSTIC AND PROGNOSTIC MARKERS FOR CHAGAS DISEASE

点击翻译按钮获取中文摘要

 DESCRIPTION (provided by applicant): Trypanosoma cruzi is a parasite responsible for an important human disease, Chagas Disease, which is endemic in the Americas. The parasite is transmitted by the bite of an insect, or by blood transfusion or organ transplants. The current drugs available for treatment are able to cure the disease in its acute phase, and provide benefits to patients in the chronic stage, but certification of cure is difficult to achieve. Management and surveillance of this disease rests heavily on the use of diagnostic tools, which are based on the detection of circulating antibodies against parasite proteins or protein fragments. However, in spite of the availability of a few diagnostic tests for screening blood banks, and for diagnosing the disease, there are major unmet needs in this area. There are currently no biomarkers that can differentially diagnose infections by different parasite strains (which could be linked to drug sensitivity and disease prognosis). Also, there are no tests that provide an early indication of therapeutic treatment success or failure, which constitutes a major obstacle in current drug trials. A constant stream of new biomarkers is required to explore their potential to develop new diagnostic tools. One of the most promising developments in recent years is the ability to produce high-density peptide microarrays, which allow the production of tiling displays of essentially complete pathogen proteomes. The goal of this application is to study the complexity of the human antibody response against this parasite, and to identify thousands of novel serology markers for further characterization. Using high-density peptide microarrays covering the complete Trypanosoma cruzi proteome we will screen sera from diverse Chagas Disease patient populations to identify all antibody- binding protein fragments recognized by these immune responses. This will provide a comprehensive set of novel biomarkers. We will complement this strategy with two comparative studies in which we will seek to define biomarkers that i) are able to differentiate infection by different parasite lineage, and ii) are able to predict treatment success/failure. These studies will feed a pipeline of downstream experiments which will validate these biomarkers for the development of new diagnostic tools.