Re-engineering aptamers to support reagentless, self-reporting electrochemical sensors.
Re-engineering aptamers to support reagentless, self-reporting electrochemical sensors.
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DOI:
10.1039/b921253a
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发表时间:
2010-03
期刊:
影响因子:
--
通讯作者:
Plaxco KW
中科院分区:
文献类型:
--
作者:
White RJ;Rowe AA;Plaxco KW
Electrochemical aptamer-based (E-AB) sensors have emerged as a promising and versatile new biosensor platform. Combining the generality and specificity of aptamer–ligand interactions with the selectivity and convenience of electrochemical readouts, this approach affords the detection of a wide variety of targets directly in complex, contaminant-ridden samples, such as whole blood, foodstuffs and crude soil extracts, without the need for exogenous reagents or washing steps. Signaling in this class of sensors is predicated on target-induced changes in the conformation of an electrode-bound probe aptamer that, in turn, changes the efficiency with which a covalently attached redox tag exchanges electrons with the interrogating electrode. Aptamer selection strategies, however, typically do not select for the conformation-switching architectures, and as such several approaches have been reported to date by which aptamers can be re-engineered such that they undergo the binding-induced switching required to support efficient E-AB signaling. Here, we systematically compare the merits of these re-engineering approaches using representative aptamers specific to the small molecule adenosine triphosphate and the protein human immunoglobulin E. We find that, while many aptamer architectures support E-AB signaling, the observed signal gain (relative change in signal upon target binding) varies by more than two orders of magnitude across the various constructs we have investigated (e.g., ranging from −10% to 200% for our ATP sensors). Optimization of the switching architecture is thus an important element in achieving maximum E-AB signal gain and we find that this optimal geometry is specific to the aptamer sequence upon which the sensor is built.
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影响因子:
16.6
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Xiao, Y;Lubin, AA;Plaxco, KW
通讯作者:
Plaxco, KW
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通讯作者:
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