A1 Refereed original research article in a scientific journal
Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2
Authors: Pietiäinen Vilja, Polso Minttu, Migh Ede, Guckelsberger Christian, Harmati Maria, Diosdi Akos, Turunen Laura, Hassinen Antti, Potdar Swapnil, Koponen Annika, Sebestyen Edina Gyukity, Kovacs Ferenc, Kriston Andras, Hollandi Reka, Burian Katalin, Terhes Gabriella, Visnyovszki Adam, Fodor Eszter, Lacza Zsombor, Kantele Anu, Kolehmainen Pekka, Kakkola Laura, Strandin Tomas, Levanov Lev, Kallioniemi Olli, Kemeny Lajos, Julkunen Ilkka, Vapalahti Olli, Buzas Krisztina, Paavolainen Lassi, Horvath Peter, Hepojoki Jussi
Publisher: Cell Press
Publication year: 2023
Journal: Cell reports : methods
Journal name in source: Cell reports methods
Journal acronym: Cell Rep Methods
Article number: 100565
Volume: 3
Issue: 8
ISSN: 2667-2375
eISSN: 2667-2375
DOI: https://doi.org/10.1016/j.crmeth.2023.100565
Web address : https://doi.org/10.1016/j.crmeth.2023.100565
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/181158460
We present a miniaturized immunofluorescence assay (mini-IFA) for measuring antibody response in patient blood samples. The method utilizes machine learning-guided image analysis and enables simultaneous measurement of immunoglobulin M (IgM), IgA, and IgG responses against different viral antigens in an automated and high-throughput manner. The assay relies on antigens expressed through transfection, enabling use at a low biosafety level and fast adaptation to emerging pathogens. Using severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the model pathogen, we demonstrate that this method allows differentiation between vaccine-induced and infection-induced antibody responses. Additionally, we established a dedicated web page for quantitative visualization of sample-specific results and their distribution, comparing them with controls and other samples. Our results provide a proof of concept for the approach, demonstrating fast and accurate measurement of antibody responses in a research setup with prospects for clinical diagnostics.
Downloadable publication This is an electronic reprint of the original article. |