Detection of respiratory virus antigens and viral genomes by using arrays in wells
Session III – Hyypia, T.
Title of Contribution: Detection of respiratory virus antigens and viral genomes by using arrays in wells
Author(s): Timo Hyypia1, Petri Saviranta2, Petri Susi1, Liisa Hattara2, Harri Siitari2 and Matti Waris1
Affiliation(s): 1Department of Virology, University of Turku and 2VTT Medical Biotechnology Centre, Turku, Finland
Abstract:
We have developed a multiplexed virus antigen detection assay using microarrays printed in the wells of 96-well microtitration plates. The format was tested for the detection of seven important respiratory viruses: adenoviruses, influenza A and B viruses, parainfluenzavirus types 1 to 3, and respiratory syncytial virus. Capturing antibodies were first printed on the bottom of the wells. Multiplexed sandwich immunoassays were performed by incubating samples together with a mixture of labeled virus-specific antibodies in the wells. To record the results, the microarray was read through the bottom of the well with a confocal laser scanner. When the results were compared to those obtained with time-resolved fluoroimmunoassay (TR-FIA) titration of standard virus preparations indicated that the array assay had a higher sensitivity than TR-FIA. Detection of viruses in nasopharyngeal specimens showed an overall agreement of 88% between the methods. This array system is a promising tool for improved antigen detection in high-throughput respiratory virus diagnostics.
A straightforward assay for rapid typing of enteroviruses using oligonucleotide arrays in microtiter wells was also developed. Viral nucleic acids are concomitantly amplified and labeled during RT-PCR, and unpurified PCR products are used for hybridization. The microarray hybridization reactions are performed in standard 96-well microtiter plates, that makes the method easily adaptable to high throughput analysis. The assay identified correctly ten common enterovirus types. Overall, the assay involves several features aiming at easy performance, robustness, and applicability to large scale studies.
