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  4. Paper-based diagnostics in the antigen-depletion regime: High-density immobilization of rcSso7d-cellulose-binding domain fusion proteins for efficient target capture

Paper-based diagnostics in the antigen-depletion regime: High-density immobilization of rcSso7d-cellulose-binding domain fusion proteins for efficient target capture

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sword-2019-09-11T17:00:56.original.xml (130 B)
Original SWORD entry document
Author(s)
Miller, Eric A
•
Baniya, Subha
•
Osorio, Daniel
•
Al Maalouf, Yara Jabbour
•
Sikes, Hadley D
Date Issued
2018
Journal
Biosensors and Bioelectronics
Publisher
Elsevier BV
Version
Author's final manuscript
Abstract
© 2017 Elsevier B.V. In this work, we report the development of a general strategy for enhancing the efficiency of target capture in immunoassays, using a bifunctional fusion protein construct which incorporates a substrate-anchoring moiety for the high-abundance immobilization of an antigen-binding domain. This approach was informed by the development of a pseudo first-order rate constant model, and tested in a paper-based assay format using a fusion construct consisting of an rcSso7d binding module and a cellulose-binding domain. These rcSso7d-CBD fusion proteins were solubly expressed and purified from bacteria in high molar yields, and enable oriented, high-density adsorption of the rcSso7d binding species to unmodified cellulose within a 30-second incubation period. These findings were validated using two distinct, antigen-specific rcSso7d variants, which were isolated from a yeast surface display library via flow cytometry. Up to 1.6 micromoles of rcSso7d-CBD was found to adsorb per gram of cellulose, yielding a volume-averaged binder concentration of up to 760 μM within the resulting active material. At this molar abundance, the target antigen is captured from solution with nearly 100% efficiency, maximizing the attainable sensitivity for any given diagnostic system.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/134939
DOI of Published Version
https://doi.org/10.1016/J.BIOS.2017.11.050
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