The chemical dynamics of nanosensors capable of single-molecule detection

Abstract

Recent advances in nanotechnology have produced the first sensor transducers capable of resolving the adsorption and desorption of single molecules. Examples include near infrared fluorescent single-walled carbon nanotubes that report single-molecule binding via stochastic quenching. A central question for the theory of such sensors is how to analyze stochastic adsorption events and extract the local concentration or flux of the analyte near the sensor. In this work, we compare algorithms of varying complexity for accomplishing this by first constructing a kinetic Monte Carlo model of molecular binding and unbinding to the sensor substrate and simulating the dynamics over wide ranges of forward and reverse rate constants. Methods involving single-site probability calculations, first and second moment analysis, and birth-and-death population modeling are compared for their accuracy in reconstructing model parameters in the presence and absence of noise over a large dynamic range. Overall, birth-and-death population modeling was the most robust in recovering the forward rate constants, with the first and second order moment analysis very efficient when the forward rate is large (>10(-3) s(-1)). The precision decreases with increasing noise, which we show masks the existence of underlying states. Precision is also diminished with very large forward rate constants, since the sensor surface quickly and persistently saturates.

Spatiotemporal Intracellular Nitric Oxide Signaling Captured Using Internalized, Near-Infrared Fluorescent Carbon Nanotube Nanosensors

“…The local nitric oxide concentration at each sensor location can be calculated by considering the reversible interaction of NO with an unoccupied site on the SWCNT surface, forming the NO-SWNCT complex that results in a quenched emission state at that site, as we have shown previously in the case of single molecule detection 45 of NO. The adsorption and desorption of nitric oxide can be described by a first order reversible process, leading to the rate expressionwhere k f , k r are the forward and backward rate constants, respectively, and calculated from previous in vitro single-SWCNT experiments 23 to be k f = 8.68 × 10 –4 (μM s) −1 and k r = 3.18 × 10 –3 s –1 (see Supporting Information Note 5).…”

Estimation of local concentration from measurements of stochastic adsorption dynamics using carbon nanotube-based sensors

“…For time-varying concentration in (6), the analytical solution (15) can be obtained by applying the integrating factor. However, the general solution of (15) is fairly complex to evaluate, with an integral appearing within an integral.…”

“…2 shows the SWNT sensor array composed of single-stranded d(AT) 15 DNA oligonucleotide wrapped SWNTs (AT 15 -SWNTs) detecting nitric oxide molecules selectively. An individual suspension of AT 15 -SWNTs in the array can be detected by atomic force microscopy (AFM, Fig. 2(a)) and its ideal system can be depicted as an evenly distributed sensor array on a two-dimensional field (Fig.…”

“…The analytical form of the solution makes possible an efficient estimation of parameters appearing in the CME. Based on this idea, maximum likelihood estimation (MLE) of the adsorption rate constant for the SWNT sensor system has been proposed [15][16][17].…”

Stochastic mapping of first order reaction networks: A systematic comparison of the stochastic and deterministic kinetic approaches

“…Practical interest is also increasing in these processes due to improvements in single molecule detection. [30][31][32][33][34][35] Therefore, the objective of this article is to develop stochastic maps for first order reaction networks. General strategies toward building these maps will be illustrated by a number of specific examples involving particularly important reaction schemes.…”