Nanobody-based strategy for rapid and accurate pathogen detection: A case of COVID-19 testing.

Antibody pairs-based immunoassay platforms served as essential and effective tools in the field of pathogen detection. However, the cumbersome preparation and limited detection sensitivity of antibody pairs challenge in establishment of a highly sensitive detection platform. In this study, using COVID-19 testing as a case, we utilized readily accessible nanobodies as detection antibodies and further proposed an accurate design concept with a more scientific and efficient screening strategy to obtain ultrasensitive antibody pairs. We employed nanobodies capable of binding different antigenic epitopes of the nucleocapsid (NP) or receptor-binding domain (RBD) antigens sandwich as substitutes for monoclonal antibodies (mAbs) sandwich in fast detection formats and utilized time-resolved fluorescence (TRF) microspheres as the signal probe. Consequently, we developed a multi-epitope nanobody sandwich-based fluorescence lateral flow immunoassay (FLFA) strip. Our results suggest that the NP antigen had a detection limit of 12.01pg/mL, while the RBD antigen had a limit of 6.51 pg/mL using our FLFA strip. Based on double mAb sandwiches, the values presented herein demonstrated 4 to 32-fold enhancements in sensitivity, and 32 to 256-fold enhancements compared to commercially available antigen lateral flow assay kits. Furthermore, we demonstrated the excellent characteristics of the proposed test strip, including its specificity, stability, accuracy, and repeatability, which underscores its the prospective utility. Indeed, these findings indicate that our established screening strategy along with the multi-epitope nanobody sandwich mode provides an optimized strategy in the field of pathogen detection.
Competing Interests: Declaration of competing interest The authors 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. Published by Elsevier B.V.)