A Mem-dELISA platform for dual color and ultrasensitive digital detection of colocalized proteins on extracellular vesicles.

Accurate, multiplex, and ultrasensitive measurement of different colocalized protein markers on individual tumor-derived extracellular vesicles (EVs) and dimerized proteins with multiple epitopes could provide insights into cancer heterogeneity, therapy management and early diagnostics that cannot be extracted from bulk methods. However, current digital protein assays lack certain features to enable robust colocalization, including multi-color detection capability, large dynamic range, and selectivity against background proteins. Here, we report a lithography-free, inexpensive (< $0.1) and ultrasensitive dual-color Membrane Digital ELISA (Mem-dELISA) platform by using track-etched polycarbonate (PCTE) membranes to overcome these shortcomings. Their through-pores remove air bubbles through wicking before they are sealed on one side by adhesion to form microwells. Immunomagnetic bead-analyte complexes and substrate solution are then loaded into the microwells from the opposite side, with >80% loading efficiency, before sealing with oil. This enables duplex digital protein colorimetric assay with beta galactosidase and alkaline phosphatase enzymes. The platform achieves 5 logs of dynamic range with a limit of detection of 10 aM for both Biotinylated β-galactosidase (B-βG) and Biotin Alkaline Phosphatase Conjugated (B-ALP) proteins. We demonstrate its potential by showing that a higher dosage of paclitaxel suppresses EpCAM-positive EVs but not GPC-1 positive EVs from breast cancer cells, a decline in chemo-resistance that cannot be detected with Western blot analysis of cell lysate. The Mem-dELISA is poised to empower researchers to conduct ultrasensitive, high throughput protein colocalization studies for disease diagnostics, treatment monitoring and biomarker discovery.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Himani Sharma, Vivek Yadav, Satyajyoti Senapati and Hsueh-Chia Chang has patent #Application No 63/516,620 pending to University of Notre Dame du Lac. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier B.V. All rights reserved.)