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Development of an ELISA-Based Pulldown Approach for Functional Analysis of Antigen-Specific Antibodies

Steventon, R.; Stolle, L.; Gregory, R.; Gaetani, L.; Carnell, G. W.; McInally, C.; Jarvis, L.; Temperton, N.; Thompson, C. P.

2026-02-20 immunology
10.64898/2026.02.19.706726 bioRxiv
Show abstract

The identification of antigen-specific neutralising antibodies is essential for vaccine development and therapeutic discovery, yet current methods either lack functional readouts or are impractical for polyclonal sera from large cohorts. Here, we describe an ELISA-based pulldown methodology that isolates functional antibodies from serum samples while preserving their neutralising activity for downstream applications. We optimised elution conditions using 3M MgCl2 in HEPES buffer, which effectively disrupts antibody-antigen interactions without dislodging immobilised antigen or impairing antibody function. The assay demonstrated 100% specificity and 77.78% sensitivity for detecting known positive samples. Compatibility with pseudotype neutralisation assays was established, with maximum tolerable MgCl2 concentrations defined for direct use without dialysis. As proof-of-concept, we applied the method to identify domain-specific neutralising antibodies against the influenza virus haemagglutinin, distinguishing head-targeting from stem-targeting responses in human sera. This methodology provides a scalable platform for dissecting functional antibody responses with epitope-level resolution. HighlightsO_LIAdapted ELISA pulldown isolates functional antigen-specific antibodies C_LIO_LI3M MgCl2 elution preserves antibody functionality C_LIO_LICompatible with Influenza pseudotype neutralisation assays C_LIO_LIAllows for the identification of region-specific antibodies C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/706726v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1ab9bforg.highwire.dtl.DTLVardef@98e20borg.highwire.dtl.DTLVardef@120687dorg.highwire.dtl.DTLVardef@abf267_HPS_FORMAT_FIGEXP M_FIG C_FIG

Published in Journal of Virological Methods (predicted rank #2) · training set

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