DNA aptamers have emerged as promising probes for challenging
analytes
that cannot be easily detected by conventional probes, including small-molecule
targets. Among the different signal transduction approaches, gold
nanoparticle (AuNP) aggregation assays have been widely used to generate
a colorimetric response from aptamer–target interactions. This
sensor design relies on the competition between the aptamer adsorbing
to the AuNP surface versus interacting with the target, whereby target
binding reduces the number of adsorbed aptamers that destabilizes
AuNPs toward salt-induced aggregation, thereby inducing a color change.
However, this thermodynamic framework overlooks the potential influence
of interaction kinetics of different aptamer conformations with AuNP
surfaces and with targets in solution or near surfaces. Here, we show
that aptamers become more strongly adsorbed on AuNPs over time, and
these trapped aptamers are less responsive toward the target analyte.
By varying the sequence of addition in sensing assays, we demonstrate
that these interaction kinetics have a significant effect on the sensor
response and thereby produce an effective sensor for methamphetamine
(meth) at biologically relevant levels in oral fluids. Along with
underpinning new tools for assay development, this new knowledge also
highlights the need for aptamer selection strategies that evolve aptamer
sequences based on the functionality that they need to exhibit in
an actual sensor.
Colorimetric gold-nanoparticle-based biosensors are an attractive platform for the detection of small-molecule analytes. Taking advantage of the adsorption of DNA aptamer probes on AuNPs, these sensors can be simple, rapid, sensitive, selective, and cost-effective. These properties are important for rapid detection of drugs like methamphetamine in biological matrices. Saliva is a highly desirable matrix for development of diagnostic tests because saliva sampling is minimally invasive and drug levels relate to recent use rather than accumulation from historical use. However, saliva is a complex fluid that presents a multitude of challenges when applying colorimetric aggregation assays. Here, we show that the contents of saliva interfere with the sensor in two main ways: (i) suppressing color change signals due to proteins nonspecifically adsorbing to nanoparticles and (ii) blocking aggregation and generating false signals due to specific electrolytes that induce aggregation. With this knowledge, we examine strategies to mitigate these effects, including sample collection and pretreatment procedures. These measures ultimately result in a sensor that can detect methamphetamine spiked into saliva samples and suggest immense promise for the feasibility of these platforms for on-site diagnostic applications.
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