Dataset Information

Development of ssDNA Aptamers for Diagnosis and Inhibition of the Highly Pathogenic Avian Influenza Virus Subtype H5N1.

ABSTRACT: Avian influenza (AI) has severely affected the poultry industry worldwide and has caused the deaths of millions of birds. Highly pathogenic avian influenza virus is characterized by high mortality and the ability to transmit from birds to humans. Early diagnosis is difficult because of the variation in pathogenicity and the genetic diversity between virus subtypes. Therefore, development of a sensitive and accurate diagnostic system is an urgent priority. We developed ssDNA aptamer probes to detect AI viruses. Through seven rounds of SELEX to search for a probe specific to the highly pathogenic AI virus subtype H5N1, we identified 16 binding aptamers and selected two with the highest binding frequency. These two aptamers had strong binding affinities and low detection limits. We found that they could bind more specifically to H5N1, as compared to other subtypes. Furthermore, these aptamers inhibited hemagglutination, which is caused by the virus surface protein hemagglutinin. Our results indicate that our screened aptamers are effective molecular probes for diagnosing H5N1 and can be used as therapeutic agents to inhibit viral surface proteins. Sensitive diagnosis and suppression of avian influenza will help maintain a stable and healthy livestock industry, as well as protect human health.

SUBMITTER: Kim SH

PROVIDER: S-EPMC7465229 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Development of ssDNA Aptamers for Diagnosis and Inhibition of the Highly Pathogenic Avian Influenza Virus Subtype H5N1.

Kim Sang-Heon SH Choi Jae-Woo JW Kim A-Ru AR Lee Sang-Choon SC Yoon Moon-Young MY

Biomolecules 20200728 8

Avian influenza (AI) has severely affected the poultry industry worldwide and has caused the deaths of millions of birds. Highly pathogenic avian influenza virus is characterized by high mortality and the ability to transmit from birds to humans. Early diagnosis is difficult because of the variation in pathogenicity and the genetic diversity between virus subtypes. Therefore, development of a sensitive and accurate diagnostic system is an urgent priority. We developed ssDNA aptamer probes to det ...[more]

PMID: 32731467

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Project description:BACKGROUND: The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. METHODOLOGY/PRINCIPAL FINDINGS: An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007-2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. CONCLUSIONS/SIGNIFICANCE: The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh.

Dataset Information

Development of ssDNA Aptamers for Diagnosis and Inhibition of the Highly Pathogenic Avian Influenza Virus Subtype H5N1.

Publications

Development of ssDNA Aptamers for Diagnosis and Inhibition of the Highly Pathogenic Avian Influenza Virus Subtype H5N1.

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