Development of a Peptide ELISA for the Diagnosis of Aleutian Mink Disease

PLoS One. 2016 Nov 1;11(11):e0165793. doi: 10.1371/journal.pone.0165793. eCollection 2016.

Abstract

Aleutian disease (AD) is a common immunosuppressive disease in mink farms world-wide. Since the 1980s, counterimmunoelectrophoresis (CIEP) has been the main detection method for infection with the Aleutian Mink Disease Virus (AMDV). In this study, six peptides derived from the AMDV structural protein VP2 were designed, synthesized, and used as ELISA antigens to detect anti-AMDV antibodies in the sera of infected minks. Serum samples were collected from 764 minks in farms from five different provinces, and analyzed by both CIEP (a gold standard) and peptide ELISA. A peptide designated P1 (415 aa-433 aa) exhibited good antigenicity. A novel ELISA was developed using ovalbumin-linked peptide P1 to detect anti-AMDV antibodies in mink sera. The sensitivity and specificity of the peptide ELISA was 98.0% and 97.5%, respectively. Moreover, the ELISA also detected 342 early-stage infected samples (negative by CIEP and positive by PCR), of which 43.6% (149/342) were true positives. These results showed that the peptide ELISA had better sensitivity compared with CIEP, and therefore could be preferable over CIEP for detecting anti-AMDV antibodies in serological screening.

MeSH terms

  • Aleutian Mink Disease / diagnosis*
  • Animals
  • Capsid Proteins / chemistry
  • Capsid Proteins / immunology
  • Computational Biology
  • Enzyme-Linked Immunosorbent Assay / methods*
  • Epitopes, B-Lymphocyte / immunology
  • Limit of Detection
  • Mink / virology
  • Models, Molecular
  • Peptide Fragments / chemistry
  • Peptide Fragments / immunology
  • Peptide Fragments / metabolism*
  • Protein Conformation

Substances

  • Capsid Proteins
  • Epitopes, B-Lymphocyte
  • Peptide Fragments
  • VP2 protein, Aleutian mink disease virus

Grants and funding

This study was funded by the Jilin Province Science and Technology Program (20140204074NY). The funder is Zhang Lei, who has taken part in study design, data collection and analysis, and the decision to publish.