Molecular detection and characterization of avian infectious bursitis virus (AIBV) in poultry farms of Northeast Mexico

The detection and characterization of the avian infectious bursitis virus (AIBV) genetic type circulating in flocks of a specific geographic areas is a basic tool for its monitoring, control and eradication. In this work, the reverse transcriptase-polymerase chain reaction technique (RT-PCR), coupled with restriction enzyme analysis (REA) of the hyper variable region of viral protein 2 (VP2) in AIBV was adapted for the detection and molecular characterization of the different strains. The goal was to have available this methodology for the fast and precise diagnosis and identification of the virus present in the area. The utilization of PCR primers previously reported and newly designed for this study was compared. Primers 9 and 10r produced the expected 447 base pair (bp) DNA fragment, whereas our primers (IBDV-818 and IBDV-1420r) amplified a 602 bp product. PCR products were detected in vaccine virus (strain Bursine (TM) 2 and S706) used as positive controls, as well as in a six week old flock vaccinated with the strain S706 at the 1th and 8th day of birth. Birds of 1, 2 and 3 weeks of age vaccinated with the same strain and vaccination scheme gave negative results with the RT-PCR test. Amplified fragments were subjected to previously reported REA in order to detect different strains with varied degrees of virulence. The REA profiles obtained corresponded to the expected vaccine strains used. In both cases the amplified fragments were recognized with enzymes BstN I and Taq alpha I; however, an additional restriction site was detected with enzyme BstN I in fragments amplified with IBDV-818 and IBDV-1420r primers, which improved the interpretation of results. Our conclusion was that it is possible to do the molecular detection and characterization of AIBV in Fabricius bursa samples. However, it is advisable to include in the study strains with a high to moderate degree of virulence in order to validate the obtained results.