Dataset Information

Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness.

ABSTRACT: Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS-CoV-2 panel is the double target approach for Influenza A detection of seasonal strains affecting humans using a generic Influenza A assay plus the three specific human subtype assays. This work explores the potential use of this double target approach in the QIAstat-Dx Respiratory SARS-Co-V-2 Panel as a tool to detect zoonotic Influenza A strains. A set of recently recorded H9 and H1 spillover strains and the G4 EA Influenza A strains as example of recent zoonotic Flu A strains were subjected to detection prediction with QIAstat-Dx Respiratory SARS-CoV-2 Panel using commercial synthetic dsDNA sequences. In addition, a large set of available commercial human and non-human influenza A strains were also tested using QIAstat-Dx Respiratory SARS-CoV-2 Panel for a better understanding of detection and discrimination of Influenza A strains. Results show that QIAstat-Dx Respiratory SARS-CoV-2 Panel generic Influenza A assay detects all the recently recorded H9, H5 and H1 zoonotic spillover strains and all the G4 EA Influenza A strains. Additionally, these strains yielded negative results for the three-human seasonal IAV (H1, H3 and H1N1 pandemic) assays. Additional non-human strains corroborated those results of Flu A detection with no subtype discrimination, whereas human Influenza strains were positively discriminated. These results indicate that QIAstat-Dx Respiratory SARS-CoV-2 Panel could be a useful tool to diagnose zoonotic Influenza A strains and differentiate them from the seasonal strains commonly affecting humans.

SUBMITTER: Penarrubia L

PROVIDER: S-EPMC9936110 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

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Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness.

Peñarrubia Luis L Rao Sonia N SN Porco Roberto R Varo Marta M Muñoz-Torrero Patricia P Ortiz-Martinez Fernando F Pareja Josep J López-Fontanals Marta M Manissero Davide D

Scientific reports 20230217 1

Recent reports from the World Health Organization regarding Influenza A cases of zoonotic origin in humans (H1v and H9N2) and publications describing emergence swine Influenza A cases in humans together with "G4" Eurasian avian-like H1N1 Influenza A virus have drawn global attention to Influenza A pandemic threat. Additionally, the current COVID-19 epidemic has stressed the importance of surveillance and preparedness to prevent potential outbreaks. One feature of the QIAstat-Dx Respiratory SARS- ...[more]

PMID: 36807577

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Project description:Syndromic multiplex panel testing enables simultaneous detection of multiple respiratory pathogens, but limited data is available on the comparative diagnostic performance of different testing systems. In this multicenter prospective study, we aimed to compare the QIAstat-Dx Respiratory Panel 2.0 (QIAstat-Dx-RP2.0) with the widely used BioFire-RP2.1, using 269 respiratory clinical specimens. Concordant test results were obtained in 232 (86.3%) cases. Discordant test results included 33 BioFire-RP2.1(+)/QIAstat-Dx-RP2.0(-) and 4 BioFire-RP2.1(-)/QIAstat-Dx-RP2.0(+) results. Discordant samples showed significantly lower pathogen loads than concordant ones (p < 0.01). Overall, the QIAstat-Dx-RP2.0 showed an analytical sensitivity of 50%-100% depending on the respiratory target, with an analytical specificity ≥ 99.0%. Most significant differences were found for the detection of adenovirus, human coronaviruses, respiratory syncytial virus, human rhinovirus/enterovirus and SARS-CoV-2 (kappa-score: 0.67-0.91). Co-detections of respiratory pathogens were identified in 47 cases by BioFire-RP2.1 and 29 by QIAstat-Dx-RP2.0. Agreement rates between the two multiplex panel tests decreased from 91.8% for single pathogen detections to 65.0% and 42.9% for co-detecting two and three pathogens, respectively. Pathogen loads were significantly lower in co-detections compared to single pathogen detections (p < 0.01), potentially explaining the lower detection rates with the QIAstat-Dx-RP2.0 in cases of multiple pathogens. In conclusion, our prospective multicenter evaluation showed good diagnostic performance of the QIAstat-Dx-RP2.0 assay, but lower detection rates for some respiratory targets compared to BioFire-RP2.1. As QIAstat-Dx-RP2.0 offers advantages in handling, noise emission, cost effectiveness, and provides semi-quantitative results compared to BioFire-RP2.1 an updated version with enhanced analytical sensitivity would be a viable alternative syndromic testing system for detecting respiratory pathogens.

Dataset Information

Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness.

Publications

Detecting zoonotic Influenza A using QIAstat-Dx Respiratory SARS-CoV-2 panel for pandemic preparedness.

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