Spectrally and Spatially Multiplexed Serological Array-in-Well Assay Utilizing Two-Color Upconversion Luminescence Imaging

Autor: Vishal Kale, Nina Sirkka, Annika Lyytikäinen, Ilkka Julkunen, Sheikh M. Talha, Anna Ahomaa, Anna Kutsaya, Jiri Vainio, Matti Waris, Henna Päkkilä, Tero Soukka
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Analytical Chemistry. 88(8):4470-4477
ISSN: 0003-2700
DOI: 10.1021/acs.analchem.6b00337
Popis: We demonstrate a simple dual-mode multiplexed array-in-well immunoassay for simultaneous classification and detection of serum IgG and IgM antibodies against influenza A and human adenoviruses based on the color and position of the upconversion luminescence on the array. Biotinylated influenza A/H1N1 and A/H5N1 as well as adenovirus serotype 2 and 5 hexon antigens along with positive and negative controls were printed in an array format onto the bottom of streptavidin-coated microtiter wells. The anti-influenza A and antiadenovirus antibodies present in the sample were captured to the array and detected with antihuman antibody-coated upconverting nanophosphors (UCNPs). The green emitting UCNPs (NaYF4:Yb(3+),Er(3+)) coated with antihuman IgG and blue emitting UCNPs (NaYF4:Yb(3+),Tm(3+)) coated with antihuman IgM were used to detect human IgG and IgM antibodies, respectively. The emission of the bound UCNPs was imaged free of autofluorescence with anti-Stokes photoluminescence microwell imager. No spectral cross-talk was observed between green and blue emitting UCNPs. Also the cross-reactivities between UCNP-conjugates and immobilized human IgG and IgM antibodies were negligible. Position of the signal on the array defined the antigen specificity and the antibody class was defined by the color of the upconversion luminescence. This technology could be used for differentiation between acute infection from past infection and immunity. Additionally, the class of the antibody response can be used for the differentiation between primary and secondary infections, hence, facilitating epidemiological seroprevalence studies.
Databáze: OpenAIRE