Effect of Reductive Dithiothreitol and Trolox on Nitric Oxide Quenching

Nov 15, 2012 - Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, ...
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Effect of Reductive Dithiothreitol and Trolox on Nitric Oxide Quenching of Single-Walled Carbon Nanotubes Selda Sen,†,‡ Fatih Sen,†,‡ Ardemis A. Boghossian,† Jingqing Zhang,† and Michael S. Strano*,† †

Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States ‡ Department of Chemistry, Middle East Technical University, 06531 Ankara, Turkey S Supporting Information *

ABSTRACT: Semiconducting single-walled carbon nanotubes (SWCNTs) fluoresce in the near-infrared and are promising as optical sensors when functionalized to enable analyte recognition. SWCNT sensors with enhanced fluorescence emission have been hypothesized to have greater sensitivities, and reductive brightening reagents, such as dithiothreitol (DTT) and Trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid), enhance SWCNT brightness. We examine the effect of Trolox and DTT on the sensitivity of a nitric oxide (NO) sensor and report that the NO sensitivity is reduced. The NO adsorption rate decreases from 0.0007 ± 0.00003 to 0.000 3± 0.00003 and 0.0004 ± 0.0001 s−1 μM−1 upon pretreatment of 1 mM Trolox and 1 mM DTT, respectively. These results are consistent with a model where Trolox and DTT are competitive binding agents with NO, occupying one of a finite number of available SWCNT binding sites and altering the NO binding strength. In the use of brightening agents, a trade-off is predicted between signal intensity and analyte sensitivity.

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the largest quantum yield, were selected for analysis as they are hypothesized to have low defect densities and nonradiative relaxation rates that are primarily dominated by the intrinsic SWCNT processes. In a recent study by Krauss and co-workers,9 the brightness of DNA-wrapped nanotubes was monitored in the presence of reducing agents such as dithiothreitol (DTT) and Trolox (6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid). According to this study, these reducing agents increase the fluorescence intensity by donating electrons to trap sites along the nanotube sidewall, resulting in passivation of defective SWCNTs believed to be predominantly doped by holes. We ask, in this work, whether addition of such brightening agents would result in greater sensitivity toward single-molecule detection of a model analyte, NO. In theory, nanotubes with an increased number of available states for exciton formation and emission are brighter, demonstrating enhanced sensitivities toward binding analytes. On the other hand, nanotubes in the presence of external brightening reagents have an enhanced brightness that is attributed to the fact that these reagents essentially remove the potential nonradiative decay pathways upon excitation. Previous studies conducted by Duque and co-workers12 examined

he ubiquitous development of single-walled carbon nanotube (SWCNT)-based sensors is attributed to the favorable photophysical features of semiconducting nanotubes.1−4 In particular, the near-infrared fluorescence emissions of these nanotubes, which lie within the tissue transparency window, enable in vivo implementation of these sensors in the absence of tissue interference.1,5−7 This fluorescence is emitted by a monodisperse suspension of semiconducting SWCNTs, wherein individual nanotubes are wrapped with polymeric and surfactant coatings that enable suspension of the hydrophobic nanotubes in an aqueous environment.8−11 Since the fluorescence emission wavelengths and intensities are sensitive to the surrounding SWCNT environment,8,12−14 wrappings that induce charge transfer or undergo conformational changes in the presence of an analyte impart the nanotube with an optical sensing mechanism. Such a mechanism has been used in the development of sensors selective for glucose,15−17 deoxyribonucleic acid (DNA) polymorphism and hybridization,18,19 adenotriphosphate (ATP),20 and nitric oxide (NO).21 This approach has been extended to detect analytes down to the single-molecule level, where individual molecular binding events result in the stochastic fluctuation of a nanotube’s fluorescence.22,23 This platform has been applied to single-molecule sensors capable of detecting acidic and diazonium constructs,23 hydrogen peroxide (H2O2),24,25 glucose,17 nitroaromatics,26 and recently NO.27 In all of these studies, the brightest nanotubes, or nanotubes demonstrating © XXXX American Chemical Society

Received: April 10, 2012 Revised: November 4, 2012

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the high Trolox solubility in methanol, complete dissolution was obtained immediately upon mixing. During experimental runs, 25, 50, and 100 μL aliquots of this stock solution were subsequently added to the 2 mL of PBS buffer containing the DNA-SWCNT to yield final Trolox concentrations of 0.5, 1, and 2 mM, respectively. Similarly, DTT (purchased from Sigma Aldrich) solution was prepared to yield a final concentration of 1 mM upon addition to 2 mL of PBS buffer.

the effect of the brightness of surfactant/SWCNT assemblies on environmental sensitivity, reporting that for optimal sensitivity one must consider both the maximum photoluminscence (PL) intensity and the ability of the sensors to sense environmental changes. In this study we examine for the first time the sensitivity of polymer-wrapped or, more specifically, DNA-wrapped SWCNTs selective toward NO in the presence of external brightening reagents. This study shows that DNAwrapped SWCNTs with intrinsically higher emission intensities are more sensitive to NO addition. However, in the presence of brightening reagents such as Trolox and DTT, the brighter nanotubes are less sensitive than the bright, pristine nanotubes in the absence of Trolox and DTT.

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NO SOLUTION NO solution was prepared using a method similar to the one reported previously.27 Briefly, 3 mL of PBS was introduced into a 5 mL round-bottomed flask and sealed with a septum with two needles inserted, providing an inlet and an outlet. First, the system was purged with argon gas (Airgas) for 2 h to remove dissolved oxygen in the buffer. Next, NO gas (99.99%, Electronic Fluorocarbons, LLC) was introduced for 20 min at an outlet pressure of 2 psi. NO concentration was determined using the horseradish peroxidase assay.29,30

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DNA OLIGONUCLEOTIDE NANOTUBE SUSPENSION SWCNTs were wrapped with d(AT)15 oligonucleotide (Figure 1b) using a method described previously.18,27 Briefly, high-pressure carbon monoxide (HiPCO) SWCNTs purchased from Unidym were suspended with a 30-base (dAdT) sequence of singlestranded DNA (Integrated DNA Technologies) in a 2:1 DNA:SWCNT mass ratio in 0.1 M sodium chloride. The DNA concentration used in this study was 2 mg/mL. Samples were sonicated with a 3 mm probe tip (Cole-Parmer) for 10 min at a power of 10 W, followed by benchtop centrifugation for 180 min (Eppendorf Centrifuge 5415D) at 16 100 relative centrifugal force (RCF). After centrifugation, the supernatant was collected and the pellet was discarded. The resulting SWCNT lengths ranged from 0.25 to 2 μm with a mean length of 1 μm, as verified via atomic force microscopy (AFM) and single-particle tracking measurements in previous studies.27,28

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CALIBRATION OF THE SENSOR PLATFORM WITH AND WITHOUT TROLOX AND DTT d(AT)15-SWCNT sensor calibration with and without Trolox and DTT was carried out by exposing the sensor to different concentrations of NO solution, with concentrations ranging from 0.5 to 19.6 μM. A custom-written MATLAB program was used to analyze the data based on a birth-and-death Markov process.22,27 This program automatically selects the brightest diffraction-limited spots, with each spot representing a single SWCNT. It then monitors the fluorescence intensity of each nanotube over time, resulting in a set of intensity versus time traces for each experiment.27 Figure 1 illustrates the experimental setup used to measure and compare NO quenching of a fluorescent film of SWCNTs adsorbed to a microscope slide in the presence and absence of the reductive brightening agents, Trolox and DTT. Incubation and absorption measurements are conducted such that approximately 200−300 diffraction-limited fluorescent spots are visible for analysis. Histograms are used to compare the starting and ending intensity frequency distributions of SWCNTs in the absence of Trolox and NO (Figure 1c), in the presence of 1 mM Trolox (Figure 1d), and in the presence of 9.8 μM NO (Figure 1e). The figure also illustrates representative near-infrared fluorescence images of the individual d(AT)15-SWCNTs deposited on the glass-bottomed Petri dish in the absence of Trolox and NO (Figure 1f), in the presence of 1mM Trolox (Figure 1g), and in the presence of 9.8 μM NO (Figure 1h). When NO binds to the SWCNT surface, upon reaching equilibrium after approximately 200 s for the conditions used in this work, the distribution of intensities is reduced (Figure 1e and 1h). Alternatively, SWCNTs are brightened by a factor of approximately 2 upon addition of Trolox or DTT (Figure 1d and 1g) compared to the control (Figure 1c and 1f), consistent with previous reports from Krauss and co-workers.9 One hypothesis explored in this work is that brighter SWCNTs possessing fewer chemical and structural defects23 are more sensitive to changes or perturbations to their environment, and hence, they possess a lower NO detection limit on account of increased site availability. A birth-and-death Markov model was used to extract concentration-dependent apparent rate constants based on stochastic fluctuations in nanotube fluorescence due to singlemolecule binding events. A detailed description of the model

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MICROSCOPY AND DATA COLLECTION FOR SINGLE-MOLECULE DETECTION DNA-SWCNT films were synthesized according to previously published methods.27 Briefly, a 200 μL droplet of 10% (3-aminopropyl) triethoxysilane (APTES, 99%, Sigma) was added to a glass-bottomed Petri dish (Mattek P35G-1.5-14-C) for surface pretreatment, and the dish was subsequently rinsed 3 times with 1× phosphate buffer saline (PBS) buffer. After rinsing, 200 μL of the DNA oligonucleotide-SWCNT solution was added to the glass surface and incubated for 2−3 min. The solution was then removed, and the Petri dish was once more rinsed 3 times with buffer. The film was incubated for 5−10 min prior to addition of 2 mL of PBS buffer. In the single-molecule microscope measurements, d(AT)15-SWCNT samples were excited by a 658 nm laser (LDM-OPT-A6-13, Newport Corp.) with a 90 μm spot size at 33.8 mW, and their fluorescence intensities were monitored in real time through an Alpha PlanApo 100x/1.46 oil emersion objective for 400 s using an inverted microscope (Carl Zeiss, Axiovert 200) with a 2D InGaAs array detector (Princeton Instruments OMA 2D). A WinSpec data acquisition program (Princeton Instruments) was used to acquire the movies with an exposure time of 0.2 s/frame. Prior to NO and/or brightening agent addition, a control movie (with the same movie length as the experimental movie) was taken to ensure stable baseline measurements.

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TROLOX AND DTT SOLUTIONS Trolox solutions were prepared as described in previous studies.9 To summarize, a 50 mM Trolox solution was made by dissolving 0.125 g of Trolox in 10 mL of methanol. Provided B

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Figure 1. Fluorescent SWCNT array capable of detecting NO. (a) Schematic of the microscope setup shows that a 658 nm laser beam (red) excites the SWCNT array deposited on the glass-bottomed Petri dish. Emission (yellow) is collected by a near-infrared array detector through a 100× TIRF objective mounted on an inverted microscope. (b) In a sample configuration of the SWCNT array, individual d(AT)15-SWCNT complexes bind to a glass surface pretreated with APTES through electrostatic interactions. Histograms show the frequency distributions of starting and ending PL intensities (c) in the absence of Trolox and NO, (d) in the presence of 1 mM Trolox, and (e) in the presence of 9.8 μM NO. Representative nearinfrared fluorescence images of the individual d(AT)15-SWCNTs deposited on the glass-bottomed Petri dish are shown (f) in the absence of Trolox and NO, (g) in the presence of 1mM Trolox, and (h) in the presence of 9.8 μM NO.

can be found in our previous work.22,27,31 To summarize, the algorithm consists of three analytical steps: (1) extraction of fluorescence vs time traces from individual SWCNTs or collections of nanotubes which appear as diffraction-limited spots, (2) fitting of these experimental traces to idealized, denoised, multistep functions to identify transitions from noise, and (3) calculation of the apparent rate constants based on the frequency of these transitions. The calculated apparent rate

constants, which demonstrate a NO concentration dependency, can be used to extract the detection limit of the sensor array. In the first step, which is extraction of traces from individual SWCNTs, experimental fluorescence vs time data were collected using the setup shown in Figure 1a and fluorescence emissions were recorded for Petri dishes containing DNA-wrapped films (Figure 1b) over time. A sample image collected by the microscope is shown in Figure 2a. In the analysis, nanotubes were C

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Figure 2. Analysis of fluorescence images of DNA-wrapped SWCNT films. (a) Sample image of the first frame of a movie is shown, where the bright spots are the fluorescence emissions from individual SWCNTs. Pixel intensities were averaged over 2 × 2 pixelated regions for diffraction-limited SWCNT emissions. (b) Image shown in a was cropped such that SWCNTs located near the outer ring of the laser boundary are removed. (c) Location of the 100 brightest nanotubes within the cropped image in b were selected. Specific SWCNTs designated as X, Y, and Z are highlighted. (d) Intensity−time traces are shown for the individual SWCNTs or groups of SWCNTs highlighted in c. (e) Apparent rate constants for the d(AT)15-SWCNT sensor array were averaged over 50 time traces in the presence of various NO concentrations (square, St-weighted average of k′a,M). Calculated rate constants linearly increase with NO concentration.

located based on the first frame of the movie. Therefore, it is essential that the nanotubes remain stationary throughout the course of the movie. Since the diffraction-limited spots of individually fluorescent nanotubes result in 2 × 2 pixelated bright spots, the pixels in the first image of the movie were averaged over 2 × 2 pixelated regions. The fluorescence from the nanotubes located near the outer boundary of the illumination spot is susceptible to laser-induced fluctuations in intensity, resulting in step-like changes in the nanotube fluorescence intensity in the absence of analyte addition. To avoid this, the image was cropped to select only a region of interest (ROI) that excluded boundary SWCNTs (Figure 2b), as performed in previous studies.24,27 Nanotubes located within the ROI undergo negligible laserinduced fluctuations in intensity, as observed in the control traces shown in Figure 3a, with a negligible background rate constant of 0.0001 s−1.27 The 100 brightest 2 × 2 pixelated regions were subsequently selected from the pixels located within this ROI (Figure 2c). Representative intensity−time traces for selected individual SWCNTs (circled as X, Y, and Z in Figure 2c) in the presence of NO are provided in Figure 2d. Fluorescence traces exhibited step-like decreases in intensity that are reminiscent of those observed in previous studies27 and in contrast with the stable traces observed in the control (Figure 3a and Figure S1).

The quenching rate constant for NO adsorption to d(AT)15SWCNTs linearly increases with NO concentration (Figure 2e), consistent with previous findings.27 In the second step, once experimental intensity versus time traces were extracted, they were analyzed to identify stochastic, step-like intensity transitions from noise. A fitting algorithm was adopted from Kerssemakers and co-workers,32 which essentially fits the noise and transitions via a sequential errorminimization algorithm. This algorithm was run on all data sets and has been shown in previous studies to accurately recover stochastic fluctuations in intensity in the presence of experimental noise.22 Sample traces are shown in Figure 3, which plots the experimental traces (red) and resulting best-fit traces (black). For more traces, see Figure S2. Sample traces are provided for control films in the absence of Trolox, DTT, and NO (Figure 3a), in the presence of 9.8 μM NO (Figure 3b), in the presence of both 1 mM Trolox and 19.6 μM NO (Figure 3c), and in the presence of both 1 mM DTT and 19.6 μM NO (Figure 3d). In the last step, once the traces have been fit, the number and frequency of transitions were used to determine the concentrationbased apparent rate constant. Previous studies have shown that the rate constants are most accurately extracted using the birth-anddeath Markov model.22 A detailed discussion on the model D

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Figure 3. Experimental intensity traces with best-fit traces. Intensity vs time traces for the 5 brightest nanotubes were fit to ideal, denoised states. Experimental data are shown in red, and best-fit traces are shown in black. Traces shown are for those (a) in the absence of Trolox, DTT, and NO, (b) with addition of 9.8 μM NO at t = 0 s, (c) in the presence of 1 mM Trolox with addition of 19.6 μM NO, and (d) in the presence of 1 mM DTT with addition of 19.6 μM NO. The y axes are rescaled to elucidate the individual stochastic fluctuations.

derivation can be found elsewhere.22,27 To summarize, the birthand-death population model treats every quenching event as a “death” with a forward rate of kf and every dequenching event as a “birth” with a reverse rate of kr. Thus, the probability of a transition from an intensity level of It0 = i at a time t0 to an intensity level of It0+Δt = j at the next time, t0+Δt, is described by the following conditional probability expression

in the trace, t is total trace time, and St, which is the cumulative intensity of a trace over the time interval [0,t], is defined as St =

(eq 1)

where Imax is the maximum intensity of the trace. On the basis of maximization of the likelihood of the observed processes, expressions for the maximum likelihood estimator of kf and kr are kf =

kr =

Nquenched St

(eq 2)

Ndequenched Imaxt − St

t

Iu du

(eq 4)

where Iu is the total intensity at a time u. Thus, an apparent rate constant can be calculated for each trace directly based on the number of step increases and decreases in intensity. Due to the stochastic nature of these binding events and the variable number of possible intensity levels that can be occupied by each of the nanotubes, a distribution of rate constants is calculated for each data set. Histograms representing this distribution are shown in Figure 4. As before, this figure shows data for the control film in the absence of Trolox, DTT, and NO (Figure 4a and 4b), films in the presence of 9.8 μM NO (Figure 4c and 4d), films in the presence of 1 mM Trolox and 19.6 μM NO (Figure 4e and 4f), and films in the presence of 1 mM DTT and 19.6 μM NO (Figure 4g and 4h). To address the hypothesis of whether brightness, corresponding to a suppression of defects, decreases the detection limit, we specifically examine subpopulations of SWCNTs in each data set ranked by initial brightness. The histograms on the left represent the calculated rate constants for the brightest 50 nanotubes, and the histograms on the right represent the calculated rate constants for the second brightest 50 nanotubes. Shown in red are the average values of the calculated rate constants for the

P(It0+Δt = j|It0 = i) ⎧(Imax − i)k r Δt if j = i + 1 ⎪ ⎪ = ⎨1 − (Imax − i)k r Δt − ik f Δt if j = i ⎪ ⎪ ik Δt if j = i − 1 ⎩ f

∫0

(eq 3)

where Nquenched is the number of quenching transitions in the trace, Ndequenched is the number of dequenching transitions E

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Figure 4. Distribution of calculated rate constants. Histograms illustrate the distribution of rate constants calculated for each nanotube for each movie. Different movie conditions shown include the (a) first 50 brightest nanotubes and (b) second 50 brightest nanotubes in the absence of NO and additives, (c) first 50 brightest nanotubes and (d) second 50 brightest nanotubes with addition of 9.8 μM NO, (e) first 50 brightest nanotubes and (f) second 50 brightest nanotubes in the presence of 1 mM Trolox with addition of 19.6 μM NO, and (g) first 50 brightest nanotubes and (h) second 50 brightest nanotubes in the presence of 1 mM DTT with addition of 19.6 μM NO. Average rate constants for each distribution are shown in red. F

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entire film. As expected, the calculated rate constant is on average larger in the presence of NO (Figure 4c,d) than in the absence of NO (Figure 4a,b). In the presence of Trolox or DTT (Figure 4e,f and 4g,h respectively), the calculated rate constants are on average smaller than those obtained in the absence of Trolox or DTT (Figure 4a,b), even when the concentration of NO is larger in the presence of Trolox or DTT than in the absence (19.6 vs 9.8 μM). In the presence of NO, the average rate constant calculated for the 50 brightest nanotubes (left) is larger than that calculated for the second 50 brightest nanotubes (right). To quantify the detection limits of the sensors, the stochastic transitions in the single-molecule traces must be converted to concentration-dependent reaction rates. To do this, the singlemolecule traces shown in Figure 3 were analyzed using an adaptation of the classical birth-and-death Markov process to correlate the stochastic quenching events with NO concentrations.22,27 Consider a nanotube divided into multiple surface sites, where the empty sites are denoted as θ and the occupied sites are denoted as θ*. NO adsorption on the surface of the nanotube could be described as follows

In a plot of log(ka′) versus log([NO]), one can directly determine the intrinsic rate constant from the intercept, log(ka). The slope of this plot, b, is the apparent reaction order with respect to NO concentration. The apparent reaction order describes the sensitivity of the system with respect to NO concentration, with a larger slope indicative of a more sensitive system. Physically, a decrease in the apparent order of the reaction is consistent with diminished NO sensitivities that may occur on account of an increased number of defective SWCNT binding sites or the inhibitive or effectively competitive blocking of NO adsorption to the SWCNT surface. On the other hand, a decrease in the intercept, or intrinsic rate constant, signifies a decrease in NO binding affinity. Since the DNA strands occupy potential binding sites on the SWCNT surface, the DNA-SWCNT interactions can influence the adsorption behavior of NO, DTT, and Trolox. Adsorption agents, such as Trolox, DTT, and NO, may nonspecifically adsorb onto the DNA-wrapped SWCNT, or they may interfere with the DNA-SWCNT interaction and modify the DNA conformation. Both adsorption models have been discussed in the literature as mechanisms for modulating fluorescence changes, and their relative contributions can be assessed based on current studies that examine DNA-SWCNT interactions.33−43 A comparison of the calculated rate constants for the first 50 brightest SWCNTs (Figure 5a) to that of the next 50 brightest SWCNTs (Figure 5b) reveals that the resulting rate constant, ka, is invariable to initial nanotube intensity, indicating that the intrinsic single-site adsorption rate constant, or NO binding affinity, is the same across different sensors. On the other hand, changes in the slope, b, is indicative of a change in sensor sensitivity toward NO. The calibration curve for the dimmer SWCNTs has a smaller slope, alluding to a decrease in the apparent number of binding sites, which is characteristic of either decreased site availability due to analyte blocking or an enhanced number of defect sites that remain unresponsive to NO binding. Since addition of Trolox or DTT clearly brightens the SWCNTs, we investigated whether their presence would affect the sensitivity of the sensor toward NO (Figures 5c−f). As is the case for SWCNTs in the absence of Trolox, in the presence of Trolox or DTT, the next 50 brightest nanotubes undergo decreased sensitivities toward NO compared to the 50 brightest nanotubes. In both cases, addition of Trolox (Figure 5c and 5d) or DTT (Figure 5e and 5f) resulted in a decrease of both ka and b. Therefore, in addition to decreasing the apparent number of SWCNT binding sites, both Trolox and DTT also effectively decrease the binding affinity of NO to the SWCNT surface. These observations are consistent with a model where the Trolox or DTT may compete with NO for SWCNT surface binding sites. For example, consider a single SWCNT sensor divided into segments, each of which is approximately the size of the excitondiffusion length.23,44 At any instant, the following reaction occurs

ka

NO + θ ⇄ θ* kd

(reaction 1)

where ka is the intrinsic adsorption rate constant and kd is the intrinsic desorption rate constant. According to the law of mass action, the rate expression for reaction 1 is dθ = −(ka[NO])θ + kd(θ*) dt

(eq 5)

θ + θ* = N

(eq 6)

where N is the total number of sites on the SWCNT. In this study, since NO adsorption on the SWCNT surface has a negligible effect on the bulk NO concentration, bulk NO concentration is assumed to remain constant throughout each experimental run. Therefore, in eq 5, the bracketed portion containing the intrinsic adsorption rate constant and NO concentration can be grouped together to describe the apparent adsorption rate constant, k′a

ka′ = ka[NO]

(eq 7)

The birth-and-death Markov model calculates this apparent rate constant based on the frequency and dwell times of adsorption events throughout each fluorescence trace.22,27 Because fluorescence intensity is an indirect measurement of the number of vacant nanotube sites, when applied to fluorescence intensity traces, the birth-and-death Markov model calculates the apparent rate constant as the number of available nanotube sites varies over time. If we relax our original assumption that k′a obeys first-order NO kinetics and assume it obeys rate laws on the order of b, then the more general expression for the apparent rate constant becomes ka′ = ka[NO]b

(reaction 2)

NO + θ ↔ θ*

If NO is added after Trolox or DTT addition, then the possible reactions are ka

NO + θ ⇄ θ*

(reaction 1)

kd ka1

Trolox/DTT + θ ⇄ θ**

(eq 8)

kd1

or by taking the logarithm of both sides log(ka′) = log(ka) + b log([NO])

(reaction 2)

with an overall site balance θ + θ* + θ** = θtotal

(eq 9) G

(eq 10)

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Figure 5. NO calibration plots for the d(AT)15-SWCNT sensor array. Rate constants were calculated in the presence of varying NO concentrations for the (a) first 50 brightest nanotubes and (b) second 50 brightest nanotubes in the absence of additives, (c) first 50 brightest nanotubes and (d) second 50 brightest nanotubes after 1 mM Trolox addition, and (e) first 50 brightest nanotubes and (f) second 50 brightest nanotubes after 1 mM DTT addition. The effective background rate constant, k′a,M − k′a,M,C0, was calculated, where k′a,M is the St-weighted average rate constant from 50 time traces at various NO concentrations and k′a,M,C0 is the St-weighted average rate constant in the absence of NO. Experimental traces (blue squares) were fit using linear regression (red lines), and the best-fit intercept and slopes are shown.

where θ* and θ** refer to NO-occupied and Trolox- or DTToccupied SWCNTs, respectively, and ka1 and kd1 are the adsorption and desorption Trolox or DTT rate constants, respectively. According to mass action,

However, because NO adsorption results in a decrease in SWCNT fluorescence emission and Trolox and DTT adsorption results in an increase in emission, NO and Trolox (or DTT) adsorption and desorption will have opposing effects on SWCNT fluorescence emission. To differentiate between the analyte effects on site availability and on SWCNT fluorescence emission, we define a new variable, [θ]PL, to describe SWCNT PL

dθ = −ka[NO][θ ] + kd[θ*] − ka1[Trolox/DTT][θ ] + kd1[θ**] dt (eq 11)

[θ ] + [θ*] + [θ**] = N

(eq 12)

dθPL = −ka[NO][θ ] + kd[θ*] dt

Because NO and Trolox (or DTT) occupy vacant binding sites in an analogous manner, mathematically, their adsorption and desorption will have the same effect on site availability.

+ ka1[Trolox/DTT][θ ] − kd1[θ**] H

(eq 13)

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Notes

In the birth-and-death model, the lumped/apparent rate constant we calculated, ka′, is equivalent to ka′ = ka[NO] − ka1[Trolox/DTT] ⎛ k [Trolox/DTT] ⎞ = ka[NO]⎜1 − a1 ⎟ ka [NO] ⎠ ⎝

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors are grateful for funding from the National Science Foundation. F.S and S.S. thank TUBITAK for the 2211 and 2214-Research fellowship program and the METU-DPT-OYP program on the behalf of Yuzuncu Yil University. A.A.B. is grateful for support from the National Defense Science and Engineering Graduate (NDSEG) Fellowship.

(eq 14)

When Trolox or DTT bind to the surface, upon reaching equilibrium, the SWCNTs are brightened (Figure 1d and 1g), indicative of an upshift in the Fermi level of the SWCNTs and a modified intrinsic interaction between the SWCNT and NO. In fact, our data show that ka in the presence of Trolox or DTT is less than that in the absence of reducing agents, suggesting a decrease in NO adsorption kinetics in the presence of these reducing agents. In addition, the bound Trolox or DTT molecules occupy available nanotube sites, making it difficult for NO molecules to either displace the Trolox or DTT or modulate the SWCNT fluorescence in a manner that is similar to that observed in the absence of reductive additives. This difficulty is reflected in the observation of a decreased slope of b < 1. A comparison of the PL effects of the brightening agents (Figure 1d) and of the quenching NO (Figure 1e) reveals a more pronounced effect from the brightening agents. A comparison of the calibration plots shown in Figure 5 reveals that intrinsically brighter SWCNTs are more sensitive to NO adsorption. However, it appears that if brightness comes at the expense of competitive site occupation on the SWCNT surface, as is the case with pre-adsorbed reagents such as Trolox and DTT, then sensor sensitivity is effectively diminished. Future directions in the field would therefore include a reduction of the number of pre-existing defects from the SWCNT surface. Reductive brightening reagents such as DTT and Trolox enhance nanotube fluorescence brightness via passivation of defect sites, motivating their examination as promoters of SWCNT sensitivity as sensors. We examined the effect of the brightening agents, Trolox and DTT, on the sensitivity of a d(AT)15 DNA oligonucleotide-wrapped SWCNT sensor selective for NO, and we found that the reductive brightening agents clearly enhance the mean brightness of the d(AT)15-SWCNT construct by a factor of approximately 2. However, the resulting sensor sensitivity to NO was reduced. The NO adsorption rate constants decreased from 0.0007 ± 0.00003 to 0.0003 ± 0.00003 and 0.0004 ± 0.0001 s−1 μM−1 upon pretreatment of 1 mM of Trolox and 1 mM of DTT, respectively. The results are consistent with a model where Trolox and DTT behave as competitive binding agents with the analyte, NO, occupying one of a finite number of available SWCNT binding sites. Hence, a tradeoff between signal intensity and analyte sensitivity is predicted when using brightening agents such as Trolox and DTT to enhance molecular detection.

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ASSOCIATED CONTENT

S Supporting Information *

Additional experimental data are avaliable, including single-molecule fluorescence response time traces and control experiments showing the effect of different Trolox concentration addition, methanol and DTT additions. This information is available free of charge via the Internet at http://pubs.acs.org

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