Catch-and-Display Immunoassay as an Accessible Platform for Digital Biomarker Detection
Digital immunoassays provide exceptional analytical sensitivity for detecting low-abundance biomarkers, but their broad adoption is limited by practical barriers. Commercial platforms are prohibitively expensive for routine use by individual laboratories, and laboratory-scale concepts typically describe specialized biosensors and sophisticated workflows. Here, we introduce a nanomembrane-based Catch-and-Display Immunoassay (CAD-IA) as an accessible digital immunoassay for common laboratory settings. In CAD-IA, fluorescent nanoparticles are "captured" by the nanoscale pores of ultrathin silicon nitride membranes through a pipette powered filtration. The captured nanoparticles serve as optically isolated 'hotspots' for fluorescent immunocomplex formation when target antigen is present. Co-localization of the fluorescent particles and fluorescent immunocomplexes are then "displayed" and quantified by standard confocal microscopy to generate digital signals. CAD-IA is implemented using the μSiM-DX (<b>micro</b>fluidic device featuring an ultrathin <b>si</b>licon <b>m</b>embrane for <b>diagnostics</b>) platform, which is manually assembled from mass produced, cost-effective components. Using the traumatic brain injury (TBI) biomarker S100B as a model, we demonstrate that CAD-IA provides consistent digital outputs and linear quantification with a dynamic range of at least two orders of magnitude when digital and analog analysis are combined on the same image sets. We further demonstrate that the assay maintains linearity in serum matrices and achieves suitable sensitivity (LoD = 0.02 μg/mL) for clinically relevant diagnostic with the addition of tyramide signal amplification (TSA). While further optimization of CAD-IA is possible, these results constitute a proof-of-concept demonstration of a novel digital immunoassay that is accessible to most laboratory environments.
Authors
- Michel Godin
- Michael E. Klaczko
- Yuxuan Liu (ORCID: https://orcid.org/0009-0001-6678-5408)
- Benjamin H. Singer (ORCID: https://orcid.org/0000-0002-4721-6920)
- Samuel N. Walker
- Jonathan Flax
- James L. McGrath
- Vincent Tabard-Cossa
Institutions
- University of Ottawa (CA)
- University of Michigan (US)
- University of Rochester Medical Center (US)
- University of Rochester (US)
Publication Details
- Journal
- bioRxiv (Cold Spring Harbor Laboratory)
- Published
- 2026-01-30
- DOI
- https://doi.org/10.64898/2026.01.27.702166
- Primary Topic
- Biosensors and Analytical Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Rochester
- National Institutes of Health