Screening and Identification of ssDNA Aptamers against HN Protein for Detection of Bovine Parainfluenza Virus Type 3 Antibodies in Serum

Author(s): Jie Cheng, Jiawei Wang, Ying Liu, Qingmin Wu*, Zhen Wang*.

Journal Name: Current Pharmaceutical Biotechnology

Volume 19 , Issue 11 , 2018

Become EABM
Become Reviewer

Graphical Abstract:


Background: Bovine Parainfluenza Virus type 3 (BPIV3) is a major but often overlooked pathogen that causes respiratory disease in cattle, especially during transportation and in feedlot situations. There is a demand for the rapid detection and serological diagnosis of BPIV3 to monitor the presence of the virus and its antibodies in cattle, which is critical in designing suitable interventions and control.

Methods: In the present study, ssDNA aptamers with high affinity and specificity against the HN protein of BPIV3 were selected using microplates as the matrix.

Results: After eleven rounds selection, thirty-four different DNA sequences were obtained in total, wherein w-32, w-33, and w-34 were repeated seven, eleven, and nine times, and with Kd values of 56.57 ± 2.7 nM, 24.64 ± 2.84 nM, and 31.3 ± 3.32 nM, respectively. Two-dimensional structural analysis showed that the three aptamers had several loop structures that were probably more energetically favorable for target binding. Of the three candidates, aptamer w-33 showed the best affinity in an indirect enzyme-linked aptamer assay (ELAA). The percent inhibition cutoff value of the ELAA, assessed using twenty negative sera, was 31%.

Conclusion: In a comparative study with commercial ELISA kits, the positive detection rate of the ELAA was slightly higher than that of the commercial ELISA kits, and the coincidence rate of ELAA and ELISA was 88%. Further optimization of the ELAA method with more serums is needed.

Keywords: Bovine parainfluenza virus type 3, aptamers, indirect competitive ELAA, Paramyxoviridae, SELEX selection procedure, Chinese cattle.

Rights & PermissionsPrintExport Cite as

Article Details

Year: 2018
Page: [896 - 901]
Pages: 6
DOI: 10.2174/1389201019666181031154046
Price: $65

Article Metrics

PDF: 15