Investigation of respiratory disease outbreaks of poultry in Bangladesh using two real-time PCR-based simultaneous detection assays.
Front Vet Sci
; 9: 1036757, 2022.
Article
em En
| MEDLINE
| ID: mdl-36583036
ABSTRACT
For rapid and sensitive pathogen screening from field outbreaks, molecular techniques such as qPCR-based simultaneous detections are efficient. Respiratory diseases are the most detrimental diseases to the poultry industry and need to be addressed because of their major economic losses. In the current study, we have applied two different detection assays one for simultaneous detection of avian influenza virus (AIV; M gene) and subtyping (H5, N1, H9, N2) using TaqMan probe chemistry (TaqMan multitarget) and another for simultaneous detection of Newcastle disease virus (NDV), infectious bronchitis virus (IBV), and infectious laryngotracheitis virus (ILTV) using SYBR Green chemistry (SYBR Green multitarget). Two individual qPCRs were conducted for the detection of four pathogens. Surveillance of tissue (n = 158) and oropharyngeal swab (206) samples from multiple poultry flocks during the years April 2020-July 2022 applying the TaqMan and SYBR Green multitarget qPCRs revealed that 48.9% of samples were positive for respiratory infections, of which 17.2% were positive for NDV, 25.5% were positive for AIV, 9.9% were positive for IBV, and only a single positive (0.3%) for ILTV. Among the AIV, 35% were highly pathogenic subtype H5N1 and 65% were low pathogenic subtype H9N2. Co-infections of 2-3 respiratory viruses were also accurately detected. Respiratory viral pathogens are quite common in Bangladeshi poultry and can be successfully detected using multitarget simultaneous real-time quantitative polymerase chain reaction (RT-qPCR) assays like those adopted in the current study. Increased mass surveillance, along with the molecular characterization of the circulating respiratory viruses, is crucial to control the epidemic and subsequently save the Bangladeshi poultry industry.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
Idioma:
En
Revista:
Front Vet Sci
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Bangladesh