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

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.

Multiple assays in a real-time RT-PCR SARS-CoV-2 panel can mitigate the risk of loss of sensitivity by new genomic variants during the COVID-19 outbreak.

OBJECTIVES: In this study, five SARS-CoV-2 PCR assay panels were evaluated against the accumulated genetic variability of the virus to assess the effect on sensitivity of the individual assays. DESIGN OR METHODS: As of week 21, 2020, the complete set of available SARS-CoV-2 genomes from GISAID and GenBank databases were used in this study. SARS-CoV-2 primer sequences from publicly available panels (WHO, CDC, NMDC, and HKU) and QIAstat-Dx were included in the alignment, and accumulated genetic variability affecting any oligonucleotide annealing was annotated. RESULTS: A total of 11,627 (34.38%) genomes included single mutations affecting annealing of any PCR assay. Variations in 8,773 (25.94%) genomes were considered as high risk, whereas additional 2,854 (8.43%) genomes presented low frequent single mutations and were predicted to yield no impact on sensitivity. In case of the QIAstat-Dx SARS-CoV-2 Panel, 99.11% of the genomes matched with a 100% coverage all oligonucleotides, and critical variations were tested in vitro corroborating no loss of sensitivity. CONCLUSIONS: This analysis stresses the importance of targeting more than one region in the viral genome for SARS-CoV-2 detection to mitigate the risk of loss of sensitivity due to the unknown mutation rate during this SARS-CoV-2 outbreak.

The osmoregulatory and the amino acid-regulated responses of system A are mediated by different signal transduction pathways.

The osmotic response of system A for neutral amino acid transport has been related to the adaptive response of this transport system to amino acid starvation. In a previous study (Ruiz-Montasell, B., M. Gómez-Angelats, F.J. Casado, A. Felipe, J.D. McGivan, and M. Pastor-Anglada. 1994. Proc. Natl. Acad. Sci. USA. 91:9569-9573), a model was proposed in which both responses were mediated by different mechanisms. The recent cloning of several isoforms of system A as well as the elucidation of a variety of signal transduction pathways involved in stress responses allow to test this model. SAT2 mRNA levels increased after amino acid deprivation but not after hyperosmotic shock. Inhibition of p38 activity or transfection with a dominant negative p38 did not alter the response to amino acid starvation but partially blocked the hypertonicity response. Inhibition of the ERK pathway resulted in full inhibition of the adaptive response of system A and no increase in SAT2 mRNA levels, without modifying the response to hyperosmolarity. Similar results were obtained after transfection with a dominant negative JNK1. The CDK2 inhibitor peptide-II decreased the osmotic response in a dose-dependent manner but did not have any effect on the adaptive response of system A. In summary, the previously proposed model of up-regulation of system A after hypertonic shock or after amino acid starvation by separate mechanisms is now confirmed and the two signal transduction pathways have been identified. The involvement of a CDK-cyclin complex in the osmotic response of system A links the activity of this transporter to the increase in cell volume previous to the entry in a new cell division cycle.