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Generation of Q-bead against bone Gla protein with simplified preparation steps

Authors
Kim, J.-P.Kim, S.-H.Ueda, H.Jeong, H.-J.
Issue Date
1-May-2023
Publisher
Elsevier B.V.
Keywords
Bone Gla protein; Fluorescence sensor; On-bead assay; One-pot immunoassay; Quenchbody
Citation
Journal of Immunological Methods, v.516
Journal Title
Journal of Immunological Methods
Volume
516
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/31102
DOI
10.1016/j.jim.2023.113471
ISSN
0022-1759
1872-7905
Abstract
Quenchbody (Q-body)-based immunoassays enable the detection of antigen within a few minutes with high sensitivity and specificity, thereby revealing their applicability as biosensors for quantifying several biomolecules of interest; however, while producing a Q-body, it is necessary to eliminate the unconjugated dye after labeling to separate the Q-body from the capturing bead and to change the buffer using ultrafiltration, which is time-consuming and leads to yield reduction. In this study, we generated a recombinant single chain variable fragment against bone Gla protein as a model antibody. We labeled the antibody with a dye to generate a Q-body and subsequently added affinity beads to the Q-body mixture. After washing, we directly added antigen without extracting the Q-body from the bead and then measured the fluorescence intensity. As a result, the antigen-dependent fluorescence response was obtained from “Q-bead”, which was almost the same as that of the Q-body generated according to the conventional method. The Q-bead was generated within only 2.5 h, thus requiring an hour and two steps less than those required for the generation of the traditional Q-body. No expensive Flag peptide was required to recover the total antibody from beads. Moreover, the ultra-filtration step was eliminated in this bead-based method, leading to improved convenience and cost- and time-saving attributes. The Q-bead-based assay can be used as a standard protocol for simple and rapid analysis of antibody-based molecular detection. © 2023 Elsevier B.V.
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