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Development of a Rapid Fluorescent Diagnostic System to Detect Subtype H9 Influenza A Virus in Chicken Feces.

ABSTRACT: The circulation of the H9N2 virus results in significant economic losses in the poultry industry, and its zoonotic transmission highlights the need for a highly sensitive and rapid diagnostic and detection system for this virus. In this study, the performance of lateral flow test strips for a fluorescent immunochromatographic test (FICT) was optimized for the diagnosis of H9N2 virus-infected animal samples. The novel monoclonal antibodies (McAbs) against influenza A H9 viruses were developed, and two categories of McAbs with linear and conformational epitopes were compared for the performance of rapid diagnostic performance in the presence of feces sample at different time points (2, 4, and 6 days) post-infection (dpi). The limit of detection (LOD) of FICT and Kd values were comparable between linear and conformational epitope McAbs. However, superior performance of linear epitope McAbs pairs were confirmed by two animal studies, showing the better diagnostic performance showing 100% relative sensitivity in fecal samples at 6 dpi although it showed less than 80% sensitivity in early infection. Our results imply that the comparable performance of the linear epitope McAbs can potentially improve the diagnostic performance of FICT for H9N2 detection in feces samples. This highly sensitive rapid diagnostic method can be utilized in field studies of broiler poultry and wild birds.

SUBMITTER: Tuong HT

PROVIDER: S-EPMC8396311 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The poultry sector contributes four percent to the national GDP of Nepal. However, this sector is under threat with periodic outbreaks of Avian Influenza (AI) subtypes H5 and H9 since 2009. This has been both a public health threat and an economic issue. Since the past few years, outbreaks of AI subtype H9 have caused huge economic losses in major poultry producing areas of Nepal. However, the risk factors associated with these outbreaks have not been assessed. A retrospective case-control study was conducted from April 2018 to May 2019 to understand the risk factors associated with AI subtype H9 outbreaks in Kathmandu valley. Out of 100 farms selected, 50 were "case" farms, confirmed positive to H9 at Central Veterinary Laboratory, Kathmandu, and another 50 farms were "control" farms, matched for farm size and locality within a radius of three km from the case farm. Each farm was visited to collect information using a semi-structured questionnaire. Twelve potential risk factors were included in the questionnaire under the broad categories: birds and farm characteristics, and management and biosecurity status of the farms. Univariable and multivariable logistic regression analysis was conducted and corresponding odds ratios were calculated. Risk factors, associated with AI subtype H9 outbreaks in Kathmandu valley, identified in the final multivariable model were: "farms that have flock size greater than median flock size of study farms (>1500)" (OR = 4.41, 95% CI: 1.53-12.71, p = 0.006), "farms that did not apply rules to wear boots for visitors inside the farms" (OR = 4.32, 95% CI: 1.52-12.29, p = 0.006) and "other commercial farms located within one km periphery" (OR = 10, 95% CI: 1.8-50, p = 0.007). This study showed that outbreaks of AI subtype H9 in Kathmandu valley were associated with a higher population of birds in the farm, poor management practices, and weak biosecurity measures in poultry farms. We suggest improving management practices and increase biosecurity in the farms to reduce incidences of AI subtype H9 outbreaks in Kathmandu valley.

Dataset Information

Development of a Rapid Fluorescent Diagnostic System to Detect Subtype H9 Influenza A Virus in Chicken Feces.

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