Automated Imaging and Analysis of the Hemagglutination Inhibition Assay
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The hemagglutination inhibition (HAI) assay quantifies the level of strain-specific influenza virus antibody present in serum and is the standard by which influenza vaccine immunogenicity is measured. The HAI assay endpoint requires real-time monitoring of rapidly evolving red blood cell (RBC) patterns for signs of agglutination at a rate of potentially thousands of patterns per day to meet the throughput needs for clinical testing. This analysis is typically performed manually through visual inspection by highly trained individuals. However, concordant HAI results across different labs are challenging to demonstrate due to analyst bias and variability in analysis methods. To address these issues, we have developed a bench-top, standalone, high-throughput imaging solution that automatically determines the agglutination states of up to 9600 HAI assay wells per hour and assigns HAI titers to 400 samples in a single unattended 30-min run. Images of the tilted plates are acquired as a function of time and analyzed using algorithms that were developed through comprehensive examination of manual classifications. Concordance testing of the imaging system with eight different influenza antigens demonstrates 100% agreement between automated and manual titer determination with a percent difference of ≤3.4% for all cases.
Microfluidic chip designs and their application for E antigen typing on red blood cells.
Maraming P, Shean Aye N, Panyakakaew P, Tippayawat P, Daduang S, Choowongkomon K RSC Adv. 2025; 15(8):6077-6088.
PMID: 39995458 PMC: 11848836. DOI: 10.1039/d4ra08321k.
Scheim D Int J Mol Sci. 2022; 23(5).
PMID: 35269703 PMC: 8910562. DOI: 10.3390/ijms23052558.
Antigenic characterization of influenza and SARS-CoV-2 viruses.
Wang Y, Tang C, Wan X Anal Bioanal Chem. 2021; 414(9):2841-2881.
PMID: 34905077 PMC: 8669429. DOI: 10.1007/s00216-021-03806-6.
Han Q, Wen X, Wang L, Han X, Shen Y, Cao J J Clin Lab Anal. 2020; 34(5):e23191.
PMID: 31901184 PMC: 7246361. DOI: 10.1002/jcla.23191.
Yang H, Zhang P, Xu X, Chen X, Liu Q, Jiang C Biosci Rep. 2019; 39(5).
PMID: 30971500 PMC: 6500895. DOI: 10.1042/BSR20190224.