Abstract
Small molecules such as neurotransmitters are critical for biochemical functions in living systems. While conventional ultraviolet–visible spectroscopy and mass spectrometry lack portability and are unsuitable for time-resolved measurements in situ, techniques such as amperometry and traditional field-effect detection require a large ensemble of molecules to reach detectable signal levels. Here we demonstrate the potential of carbon-nanotube-based single-molecule field-effect transistors (smFETs), which can detect the charge on a single molecule, as a new platform for recognizing and assaying small molecules. smFETs are formed by the covalent attachment of a probe molecule, in our case a DNA aptamer, to a carbon nanotube. Conformation changes on binding are manifest as discrete changes in the nanotube electrical conductance. By monitoring the kinetics of conformational changes in a binding aptamer, we show that smFETs can detect and quantify serotonin at the single-molecule level, providing unique insights into the dynamics of the aptamer–ligand system. In particular, we show the involvement of G-quadruplex formation and the disruption of the native hairpin structure in the conformational changes of the serotonin–aptamer complex. The smFET is a label-free approach to analysing molecular interactions at the single-molecule level with high temporal resolution, providing additional insights into complex biological processes.
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Data availability
Source data for all figures are provided with this paper. The measured raw data for all smFET devices are published on https://doi.org/10.5281/zenodo.10161590. Source data are provided with this paper.
Code availability
Custom data analysis toolchain and HMM fitting algorithms for the smFET analysis can be accessed at https://github.com/klshepard/traceAnalysisTool.
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Acknowledgements
We thank Columbia Nano-Initiative (CNI) and CUNY Advanced Science Research Center (ASRC) for device fabrication. J.B. thanks J. Jadwisczek for helpful discussions on experiment design. K.L.S. acknowledges funding supported by the Defense Advanced Research Projects Agency (DARPA) under Cooperative Agreement Number D20AC00004. Y.L. acknowledges funding supported by the National Research Foundation of Korea by the Korean government (MSIT) (NRF-2022R1A2C1092050).
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Contributions
Y.L., E.F.Y., B.H. and K.L.S. conceived the study and the experiments. Y.L., E.F.Y. and D.L. fabricated the devices. Y.L. and D.L. conducted the smFET experiments. J.B. and Y.L. evaluated the smFET data with the help of K.Y., B.H., B.P. and M.N.S., and B.H. conducted smFRET experiments. K.Y. and B.H. conducted ThT assay experiments. J.B. employed analysis tools and modelling. Y.L., J.B. and K.L.S. wrote the manuscript with contributions from all authors. K.L.S. and S.S. provided financial support for the research. K.L.S. supervised the research.
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K.L.S. and E.F.Y. are involved in the commercialization of smFET devices for molecular diagnostic applications through Quicksilver Biosciences, Inc. The other authors declare no competing interests.
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Extended data
Extended Data Fig. 1 SEM images and transfer characteristics of two types of CNT FET fabrications used in the study.
The number of CNTs crossing the source–drain electrode pair is counted on the SEM images. Conducting FET devices transiting a single CNT are screened by back-gate transfer characteristics using a semiconductor parameter analyser (Agilent 4155 C). The back-gate voltage (VBG) is applied to the heavily doped p + + silicon substrate and swept from −10 to +10 V with a step size of 500 mV. Constant source–drain voltage (VSD) of 100 mV is applied to the devices, and the current at each VBG is measured. a) The representative SEM images of a CNT FET produced by a CVD method. CNT nucleation features (4 μm by 4 μm) containing iron nanoparticles are patterned on the top of silicon substrates by electron beam lithography. CNTs with controlled density and length are grown from the sites by the CVD method (left). The Ti electrode pairs with a 2 μm gap are deposited on the defined CNT growth sites (right). Each chip (11 mm by 10 mm) contains 79 pairs of source–drain electrical contacts. b) The two representative SEM images of CNT FETs fabricated by spin-casting. After spin-coating the CNT solution (250 μg/ml) on the four-inch wafer, Ti electrode pairs with source–drain separation of 0.5 μm are patterned on top. Each chip (11 mm by 10 mm) contains 280 pairs of source–drain electrical contacts. c) The representative transfer curves of 22 CNT FETs, including a single-crossing CNT produced by the CVD-grown method. d) The transfer curves of 26 single-crossing spin-cast CNT FETs. Devices that have a single CNT bridge and exceed threshold ID values of 1 nA at −10 V of VBG are used in the subsequent experiments.
Extended Data Fig. 2 Electrically controlled diazonium chemistry for single-point CNT functionalization.
a) The example of ID–t trace (black line) displaying serial single sp3 defect generations by aryl-diazonium salt at a fixed liquid gate potential (VDS = 30 mV, VLG = –200 mV, red line). Discrete downward current steps are detected (Inset, red arrows), and the ID level is rapidly reduced after introducing 4-formylbenzene diazonium hexafluorophosphate (FBDP) solution (shaded in blue). b) The representative ID–t trace (from Device A, which is discussed in the main text) displays controlled diazonium chemistry (VDS = 50 mV). At –500 mV of VLG, the downward current steps are not observed in the FBDP solution. The discrete current steps are detected when the VLG is tuned to –300 mV. The two ID steps cause a resistance change of 4.7 kΩ and 5.1 kΩ, respectively. c) The diazonium cation is reduced by electrons supplied from CNT; subsequently, aryl-radical is coupled with CNT. The VLG is then turned down to –0.5 V to reduce the electron density in CNT, halting the reaction. d) Examples of transfer curves of Device A before (grey squares) and after the controlled diazonium reaction (red circles) and after DNA aptamer conjugation (blue triangles). All transfer curves are obtained in the phosphate buffer. Error bars represent a standard deviation of the mean current value for three measurements. The measurement VLG point (100 mV) for temporal dynamic serotonin sensing is chosen from the curve. After the functionalization, the average conductance is decreased, indicating that permanent DNA-CNT couplings are created on the sp3 defect site on CNT.
Extended Data Fig. 3 The temporal electric signals originated from the single-molecule binding events observed on serotonin-specific aptamer-functionalized smFET devices.
a-f) 30-s-length ID-t traces displaying single-molecule events (displayed in the increasing order of liquid gate potentials). The right panel shows the ID distributions of each time trace, and two Gaussian fits with peak values μ1 and μ2. (a) Device A, VLG = 200 mV, VDS = 50 mV. (b) Device B, VLG = 100 mV, VDS = 50 mV. (c) Device C, VLG = 300 mV, VDS = 25 mV. (d) Device D, VLG = 400 mV, VDS = 50 mV. (e) Device E, VLG = –200 mV, VDS = 50 mV. (f) Device F, VLG = 0 mV, VDS = 200 mV. g) Measured SNR values for six devices \(\left({SNR}=\left({\mu }_{1}-{\mu }_{2}\right)/\sqrt{0.5\left({\sigma }_{1}^{2}{+\sigma }_{2}^{2}\right)}\right)\).
Extended Data Fig. 4 Concentration dependence for the fraction of time spent in the lower conductance state (PLOW) of Device B (a) and Device F (b).
The plots of PLOW are fitted into Langmuir isotherm function (black line). Data points are the mean probability of the low conductance state calculated from all dwell times by bootstrapping (Nboot = 2,000). Error bars represent the 90% confidence interval from bootstrapped mean value of PLOW.
Extended Data Fig. 5 Histograms showing temporal conductance profiles of smFET device in response to the target and non-target introduction.
a) The experimental sequence of introducing serotonin (5-HT) and dopamine solutions to the device (Device D used for the experiments). b) Histograms of ID distributions before target introduction. c-i) Histograms of ID distributions displayed chronologically after each sample is introduced. 600-s of ID-t trace was sampled at each recording point. 400 mV of VLG was applied during the experiment. The data recording time after introducing blank PBS buffer (b), serotonin (c-f), and dopamine-diluted PBS solution (g-i) is indicated in each graph.
Extended Data Fig. 6 Control experiments on the aptamer-conjugated smFET devices.
ID–t traces measured on serotonin-specific aptamer-functionalized CNT FET (Device B) measured in the presence of pure buffer, dopamine (100 nM), and serotonin solution (50 nM), respectively.
Extended Data Fig. 7 Control experiments on the unfunctionalized CNT FET.
a) ID–t trace of an unmodified CNT FET (Device G), measured in presence of pure buffer solution. b) Response of the device to a 10 nM serotonin solution in the buffer. c) Device response at a higher concentration of 50 nM serotonin in the buffer. d) Graph showing the average ID values measured over 10 minutes at varying serotonin concentrations displaying the extent of the non-specific charge adsorption. Standard deviations of the ID measurements are represented by error bars.
Extended Data Fig. 8 Normalized dwell time distributions and concentration dependency of the high and low conductance states.
The semi-logarithmic dwell time histograms for the low conductance state (left column) and high conductance state (right column) at various serotonin concentrations are shown. The counts are presented per second to account for variations in measurement time between experiments. a, b) Normalized dwell time distributions for the low and high conductance states obtained from Device A (a) and Device B (b). The histograms are overlaid with single-exponential (red lines) and double-exponential decay (orange lines) functions. The double-exponential fits reveal two distinct populations characterized by fast and slow rates, represented by orange dotted lines. c) Concentration-dependent number of counts of smFET transitions for Device A (left) and Device B (right). The plot illustrates the relationship between the number of counts per second and the serotonin concentration, addressing the concentration dependency of the smFET transitions for each device.
Extended Data Fig. 9 The rate constants determined by HMM analysis.
a) The dwell time analysis with HMM showing single-exponential distribution (data from Device A, 50 nM of [5-HT]). b) The HMM includes eight interconversion rates. c) The two rate constants (on-rate: pink, off-rate: green) calculated from the HMM at each pathway are plotted as a function of serotonin concentrations. The smFET data of Device B are used. Data points are calculated from fitting dwell-time distributions for each state transition to a single-exponential distribution. The error bars indicate the one-sigma confidence interval of the model fit.
Supplementary information
Supplementary Information
Supplementary Discussion, Figs. 1–18, Tables 1–3 and references.
Source data
Source Data Fig. 1
Current–time traces. Idealized conductance state fit. Histograms of current-time trace. Fraction of trace in low conductance state vs. concentration and respective Langmuir isotherm fit. ChemDraw elements used in Fig. 1a.
Source Data Fig. 1
Current–time traces. Idealized conductance state fit. Histograms of current-time trace. Fraction of trace in low conductance state vs. concentration and respective Langmuir isotherm fit. ChemDraw elements used in Fig. 1a.
Source Data Fig. 1
Current–time traces. Idealized conductance state fit. Histograms of current-time trace. Fraction of trace in low conductance state vs. concentration and respective Langmuir isotherm fit. ChemDraw elements used in Fig. 1a.
Source Data Fig. 2
Current–time traces. Dwell time distribution of low and high conductance state on semi log scale including model fit for single and double-exponential. Extracted rate constants vs. serotonin concentration.
Source Data Fig. 3
Estimated rate constants of each HMM path vs. serotonin concentration.
Source Data Fig. 4
State occupation vs. serotonin concentration. Estimated dissociation constants from Langmuir fitting in each condition.
Source Data Extended Data Fig. 1
Current vs. liquid gate voltage plots.
Source Data Extended Data Fig. 2
Current–time trace and histograms. Current vs. liquid gate voltage plots.
Source Data Extended Data Fig. 3
Current–time trace including current histogram with double Gaussian-distribution fit data.
Source Data Extended Data Fig. 4
Probability of a low conductance state vs. serotonin concentration. Langmuir isotherm fitting to low conductance state.
Source Data Extended Data Fig. 5
Histograms of measured smFET current.
Source Data Extended Data Fig. 6
Current–time trace.
Source Data Extended Data Fig. 7
Current–time trace. Mean and standard deviation of measured currents.
Source Data Extended Data Fig. 8
Histograms of dwell time distributions of high and low conductance states at different concentrations including fitting. Counts per second at the respective concentrations.
Source Data Extended Data Fig. 9
Histograms of dwell time distribution of each kinetic path including fitting. Estimated rate constants at the respective concentrations in each path.
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Lee, Y., Buchheim, J., Hellenkamp, B. et al. Carbon-nanotube field-effect transistors for resolving single-molecule aptamer–ligand binding kinetics. Nat. Nanotechnol. (2024). https://doi.org/10.1038/s41565-023-01591-0
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DOI: https://doi.org/10.1038/s41565-023-01591-0
