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Ultrasensitive and Selective Protein Recognition with Nanobody-Functionalized Synthetic Nanopores

Duznovic, Ivana ; Gräwe, Alexander ; Weber, Wadim ; Müller, Lena K. ; Ali, Mubarak ; Ensinger, Wolfgang ; Tietze, Alesia ; Stein, Viktor (2021)
Ultrasensitive and Selective Protein Recognition with Nanobody-Functionalized Synthetic Nanopores.
In: Small (Weinheim an der Bergstrasse, Germany)
doi: 10.1002/smll.202101066
Article, Bibliographie

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Abstract

The development of flexible and reconfigurable sensors that can be readily tailored toward different molecular analytes constitutes a key goal and formidable challenge in biosensing. In this regard, synthetic nanopores have emerged as potent physical transducers to convert molecular interactions into electrical signals. Yet, systematic strategies to functionalize their surfaces with receptor proteins for the selective detection of molecular analytes remain scarce. Addressing these limitations, a general strategy is presented to immobilize nanobodies in a directional fashion onto the surface of track-etched nanopores exploiting copper-free click reactions and site-specific protein conjugation systems. The functional immobilization of three different nanobodies is demonstrated in ligand binding experiments with green fluorescent protein, mCherry, and α-amylase (α-Amy) serving as molecular analytes. Ligand binding is resolved using a combination of optical and electrical recordings displaying quantitative dose-response curves. Furthermore, a change in surface charge density is identified as the predominant molecular factor that underlies quantitative dose-responses for the three different protein analytes in nanoconfined geometries. The devised strategy should pave the way for the systematic functionalization of nanopore surfaces with biological receptors and their ability to detect a variety of analytes for diagnostic purposes.

Item Type: Article
Erschienen: 2021
Creators: Duznovic, Ivana ; Gräwe, Alexander ; Weber, Wadim ; Müller, Lena K. ; Ali, Mubarak ; Ensinger, Wolfgang ; Tietze, Alesia ; Stein, Viktor
Type of entry: Bibliographie
Title: Ultrasensitive and Selective Protein Recognition with Nanobody-Functionalized Synthetic Nanopores
Language: English
Date: 3 July 2021
Journal or Publication Title: Small (Weinheim an der Bergstrasse, Germany)
DOI: 10.1002/smll.202101066
Corresponding Links:
Abstract:

The development of flexible and reconfigurable sensors that can be readily tailored toward different molecular analytes constitutes a key goal and formidable challenge in biosensing. In this regard, synthetic nanopores have emerged as potent physical transducers to convert molecular interactions into electrical signals. Yet, systematic strategies to functionalize their surfaces with receptor proteins for the selective detection of molecular analytes remain scarce. Addressing these limitations, a general strategy is presented to immobilize nanobodies in a directional fashion onto the surface of track-etched nanopores exploiting copper-free click reactions and site-specific protein conjugation systems. The functional immobilization of three different nanobodies is demonstrated in ligand binding experiments with green fluorescent protein, mCherry, and α-amylase (α-Amy) serving as molecular analytes. Ligand binding is resolved using a combination of optical and electrical recordings displaying quantitative dose-response curves. Furthermore, a change in surface charge density is identified as the predominant molecular factor that underlies quantitative dose-responses for the three different protein analytes in nanoconfined geometries. The devised strategy should pave the way for the systematic functionalization of nanopore surfaces with biological receptors and their ability to detect a variety of analytes for diagnostic purposes.

Identification Number: pmid:34216425
Additional Information:

Artikel-Nr. e2101066

Divisions: 10 Department of Biology
10 Department of Biology > Protein Engineering of Ion Conducting Nanopores
Date Deposited: 05 Jul 2021 11:42
Last Modified: 28 Dec 2023 07:34
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