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ARS Home » Midwest Area » Ames, Iowa » National Animal Disease Center » Ruminant Diseases and Immunology Research » Research » Publications at this Location » Publication #374889

Research Project: Identification of Disease Mechanisms and Control Strategies for Viral Respiratory Pathogens of Ruminants

Location: Ruminant Diseases and Immunology Research

Title: Multivariate analysis as a method to evaluate antigenic relationships between BVDV vaccine and field strains

Author
item MOSENA, ANA - Universidade Federal Do Rio Grande Do Norte
item Falkenberg, Shollie
item Ma, Hao
item Casas, Eduardo
item Dassanayake, Rohana
item WATZ, PAUL - Auburn University
item CANAL, CLAUDIO - Universidade Federal Do Rio Grande Do Norte
item Neill, John

Submitted to: Vaccine
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/6/2020
Publication Date: 7/18/2020
Citation: Mosena, A.C., Falkenberg, S.M., Ma, H., Casas, E., Dassanayake, R.P., Watz, P., Canal, C., Neill, J.D. 2020. Multivariate analysis as a method to evaluate antigenic relationships between BVDV vaccine and field strains. Vaccine. 38(36):5764-5772. https://doi.org/10.1016/j.vaccine.2020.07.010.
DOI: https://doi.org/10.1016/j.vaccine.2020.07.010

Interpretive Summary: Providing protection against bovine viral diarrhea virus (BVDV) is challenging due to the antigenic diversity among BVDV strains and ability of BVDV to infect the fetus, therefore complicating vaccine design and composition to confer fetal protection. Typically, virus neutralization (VN) is used determine antigenic difference among BVDV isolates, but interpretation of the data can be difficult. Data from this study utilized an analysis that generates graphical scatter plots for visualization of VN results to determine antigenic relationships between vaccine strains and BVDV field isolates. Calves were exposed to six BVDV strains currently contained in vaccine formulations, and serum was obtained from these calves and used for VN to measure the neutralizing antibody titers against 15 BVDV field isolates characterized as prevalent and divergent isolates in the USA. The results demonstrated spatial patterns in the graphs that were suggestive of antigenic differences among the BVDV isolates used in the assay. Some BVDV isolates had very distinct spatial patterns in the graphs that could suggest extremely antigenically divergent isolates. This analysis and graphs provides an alternative and more efficient means to analyze large VN datasets to visualize antigenic relationships between BVDV isolates.

Technical Abstract: Bovine viral diarrhea virus is comprised of two species, BVDV-1 and BVDV-2, but given the genetic diversity among pestiviruses, at least 21 subgenotypes are described for BVDV-1 and 4 for BVDV-2, with the most prevalent subgenotypes worldwide being BVDV-1a, 1b and 2a. Genetic characterization can be achieved through complete or partial sequencing and phylogeny, but antigenic characterization can be difficult to determine due to the antigenic diversity and cross-neutralization that exists among isolates. The traditional method for characterizing antigenic relationships between pestivirus isolates is the virus neutralization (VN) assay, but interpretation of the data can be difficult due to antigenic differences. Data from this study utilized a multivariate analysis for visualization of VN results to analyze the antigenic relationships between vaccine strains and multiple field isolates. Polyclonal sera were generated against 6 BVDV strains currently contained in vaccine formulations, and each serum was used in VN’s to measure the neutralizing antibody titers against 15 BVDV field isolates characterized as prevalent and divergent subgenotypes in the USA. Principal component analysis (PCA) were performed on the VN assay datasets, and results were interpreted from PCA clustering and scatter plot with accumulated proportion of variance ranging from 89.56 percent to 98.25 percent. The results demonstrated spatial patterns among isolates that differ in VN titers, suggestive of antigenic differences. While expected, the greatest spatial distribution among isolates was observed between the BVDV-1 and 2 isolates. In addition, other BVDV isolates had distinct spatial patterns suggesting antigenically divergent isolates. This analysis provides an alternative and more efficient means to analyze large VN datasets to visualize antigenic relationships between pestivirus isolates. This analysis could be beneficial for vaccine development and evaluation of efficacy, since most vaccines cannot fully protect animals from the broad range diversity of BVDV viruses.