Norovirus infections are the leading cause of non-bacterial gastroenteritis and result in about 21 million new cases and $2 billion in costs per year in the United States. Existing diagnostics have limited feasibility for point-of-care applications, so there is a clear need for more reliable, rapid, and simple-to-use diagnostic tools in order to contain outbreaks and prevent inappropriate treatments. In this study, a combination of phage display technology, deep sequencing and computational analysis was used to identify 12-mer peptides with specific binding to norovirus genotype GI.1 virus-like particles (VLPs). After biopanning, phage populations were sequenced and analyzed to identify a consensus peptide motif-YRSWXP. Two 12-mer peptides containing this sequence, NV-O-R5-3 and NV-O-R5-6, were further characterized to evaluate the motif's functional ability to detect VLPs and virus. Results indicated that these peptides effectively detect GI.1 VLPs in solid-phase peptide arrays, ELISAs and dot blots. Further, their specificity for the S-domain of the major capsid protein enables them to detect a wide range of GI and GII norovirus genotypes. Both peptides were able to detect virus in norovirus-positive clinical stool samples. Overall, the work reported here demonstrates the application of phage display coupled with next generation sequencing and computational analysis to uncover peptides with specific binding ability to a target protein for diagnostic applications. Further, the reagents characterized here can be integrated into existing diagnostic formats to detect clinically relevant genotypes of norovirus in stool.
Keywords: diagnostics; informatics; norovirus; peptide; phage display.
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