UC Davis

Single domain heavychain binders (nanobodies) obtained from camelid antibody libraries hold a great promise for immunoassay development. However, there is no simple method to select the most valuable nanobodies from the crowd of positive clones obtained after the initial screening. In this paper, we describe a novel nanobody-based platform that allows comparison of the reactivity of hundreds of clones with the labeled antigen, and identifies the best nanobody pairs for two-site immunoassay development. The output clones are biotinylated in vivo in 96-well culture blocks and then used to saturate the biotin binding capacity of avidin coated wells. This standardizes the amount of captured antibody allowing their sorting by ranking their reactivity with the labeled antigen. Using human soluble epoxide hydrolase (sEH) as a model antigen, we were able to classify 96 clones in four families and confirm this classification by sequencing. This provided a criterion to select a restricted panel of five capturing antibodies and to test each of them against the rest of the 96 clones. The method constitutes a powerful tool for epitope binning, and in our case allowed development of a sandwich ELISA for sEH with a detection limit of 63 pg/mL and four log dynamic range, which performed with excellent recovery in different tissue extracts. This strategy provides a systematic way to test nanobody pairwise combinations and would have a broad utility for the development of highly sensitive sandwich immunoassays.