Literature DB >> 27225413

A Computationally Designed Serological Assay for Porcine Epidemic Diarrhea Virus.

Yunfeng Song1, Pankaj Singh2, Eric Nelson3, Sheela Ramamoorthy4.   

Abstract

The periodic emergence of new infectious agents and the genetic and antigenic evolution of existing agents necessitate the improvement of technology for the rapid development of diagnostic assays. The porcine epidemic diarrhea virus (PEDV) emerged in the United States in 2013, causing severe economic damage to the pork industry. The primary goal of this study was to develop methods to reduce the lead time for serological assay development. An approach involving the computational prediction of diagnostic targets, followed by a rapid synthesis of antigens, was adopted to achieve this objective. To avoid cross-reactivity with other closely related swine coronaviruses, the N protein sequences of PEDV were analyzed to identify sequences unique to PEDV. The potential antigenicity of the identified sequence was predicted computationally using the Jameson-Wolf method. A sequence with a high antigenic index was rapidly synthesized using an in vitro transcription and translation system to yield the diagnostic antigen. The computationally designed enzyme-linked immunosorbent assay (ELISA) was validated using 169 field sera, whose statuses were determined by a PEDV-specific immunofluorescence assay. Comparison of the computationally designed ELISA to a conventionally developed ELISA, using bacterially expressed N protein, and to the immunofluorescence assay showed a high degree of agreement among the three tests (mean kappa statistic, 0.842). The sensitivity and specificity, compared to the conventionally developed assay, were 90.62 and 95.18, respectively. Therefore, the described approach is useful in reducing the development time for serological assays in the face of an infectious disease outbreak.
Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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Year:  2016        PMID: 27225413      PMCID: PMC4963506          DOI: 10.1128/JCM.00460-16

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


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6.  Monitoring SARS-CoV-2 decontamination by dry heat and ultraviolet treatment with a swine coronavirus as a surrogate.

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