Influenza Other Respir Viruses. 2019 Oct 13. doi: 10.1111/irv.12683. [Epub ahead of print] FluChip-8G Insight: HA and NA subtyping of potentially pandemic influenza A viruses in a single assay.
Toth E1, Dawson ED1, Taylor AW1, Stoughton RS1, Blair RH1, Johnson JE Jr1, Slinskey A1, Fessler R1, Smith CB2, Talbot S2, Rowlen K1.
Author information
1 InDevR, Inc., Boulder, CO, USA. 2 Influenza Division, the Centers for Disease Control and Prevention, Atlanta, GA, USA.
Abstract
BACKGROUND:
Global influenza surveillance in humans and animals is a critical component of pandemic preparedness. The FluChip-8G Insight assay was developed to subtype both seasonal and potentially pandemic influenza viruses in a single assay with a same day result. FluChip-8G Insight uses whole gene segment RT-PCR-based amplification to provide robustness against genetic drift and subsequent microarray detection with artificial neural network-based data interpretation.
OBJECTIVES:
The objective of this study was to verify and validate the performance of the FluChip-8G Insight assay for the detection and positive identification of human and animal origin non-seasonal influenza A specimens.
METHODS:
We evaluated the ability of the FluChip-8G Insight technology to type and HA and NA subtype a sample set consisting of 297 results from 180 unique non-seasonal influenza A strains (49 unique subtypes).
RESULTS:
FluChip-8G Insight demonstrated a positive percent agreement ≥93% for 5 targeted HA and 5 targeted NA subtypes except for H9 (88%), and negative percent agreement exceeding 95% for all targeted subtypes.
CONCLUSIONS:
The FluChip-8G Insight neural network-based algorithm used for virus identification performed well over a data set of 297 na?ve sample results, and can be easily updated to improve performance on emerging strains without changing the underlying assay chemistry.
? 2019 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.
KEYWORDS:
influenza; multiplex PCR; neural networks; oligonucleotide microarrays; pandemics; validation studies
PMID: 31608599 DOI: 10.1111/irv.12683