Identification of antigenic linear peptides in the soil-transmitted helminth and Schistosoma mansoni proteome

土源性蠕虫和曼氏血吸虫蛋白质组中抗原线性肽的鉴定

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作者:Johnny Vlaminck, Ole Lagatie, Daniel Dana, Zeleke Mekonnen, Peter Geldhof, Bruno Levecke, Lieven J Stuyver

Abstract

The scientific community identified non stool-based biomarkers as the way forward to support soil-transmitted helminth (STH; Ascaris lumbricoides, Trichuris trichiura and the hookworms Ancylostoma duodenale and Necator americanus) and schistosome (S. mansoni and S. haematobium) deworming programs. This support is needed in making the decision of whether or not to stop preventive chemotherapy intervention efforts and to ultimately transition towards a post-intervention surveillance phase. We applied a two-step micro-array approach to identify antigenic linear epitopes in the STH and S. mansoni proteomes. In a first experiment, we identified antigenic peptides by applying sera from 24 STH and/or S. mansoni infected Ethiopian children on a high-density peptide microarray containing 3.3 million peptides derived from the complete STH and S. mansoni proteomes. A second array experiment with 170,185 peptides that were recognized in the first array was designed to identify non-specific antibody reactivity by applying sera from 24 healthy individuals from Belgium (a non-endemic country). From this array testing cascade, several peptides were identified for STH but none of them appeared to be unique for one species. We therefore concluded that for STH, none of the peptides revealed to be sufficiently sensitive or species specific. For S. mansoni, some promising peptides were identified prompting future investigation. Based on these results, it is unlikely that linear epitopes would be highly useful in detecting species-specific antibody responses to STH in endemic communities. For S. mansoni, one particular peptide of the micro-exon gene 12 (MEG-12) protein deserves further research. In addition, this study emphasizes the need of well-characterized biobanks for biomarker discovery, particularly when the integration of multiple disease programs is envisioned.

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