Analysis of Multiplexed Nanosensor Arrays Based on Near-Infrared

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Analysis of Multiplexed Nanosensor Arrays Based on Near Infrared Fluorescent Single Walled Carbon Nanotubes Juyao Dong, Daniel P. Salem, Jessica H. Sun, and Michael S. Strano ACS Nano, Just Accepted Manuscript • DOI: 10.1021/acsnano.8b00980 • Publication Date (Web): 03 Apr 2018 Downloaded from http://pubs.acs.org on April 3, 2018

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Analysis of Multiplexed Nanosensor Arrays Based on Near Infrared Fluorescent Single Walled Carbon Nanotubes Juyao Dong, Daniel P. Salem, Jessica H. Sun, and Michael S. Strano∗ Department of Chemical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139 E-mail: [email protected] Abstract The high-throughput, label-free detection of biomolecules remains an important challenge in analytical chemistry with the potential of nanosensors to significantly increase the ability to multiplex such assays. In this work, we develop an optical sensor array, printable from a single walled carbon nanotube/chitosan ink and functionalized to enable a divalent ion based proximity quenching mechanism for transducing binding between a capture protein or an antibody with the target analyte. Arrays of 5×6, 200 µm near infrared (nIR) spots at a density of ≈ 300 spots/cm2 are conjugated with immunoglobulin-binding proteins (Protein A, G and L) for the detection of Human IgG, Mouse IgM, Rat IgG2a and Human IgD. Binding kinetics are measured in a parallel, multiplexed fashion from each sensor spot using a custom laser scanning imaging configuration with an nIR photomultiplier tube detector. These arrays are used to examine cross-reactivity, competitive and non-specific binding of analyte mixtures. We find that Protein G and Protein L functionalized sensors report selective responses to Mouse IgM on the latter, as anticipated. Optically addressable platforms such as

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the one examined in this work have potential to significantly advance the real-time, multiplexed biomolecular detection of complex mixtures.

Keywords: single walled carbon nanotubes, label-free detection, microarray, kinetic analysis, nanosensor

The high-throughput, label-free detection of protein biomolecules remains an important challenge in analytical chemistry. 1–3 Fluorescent and chemiluminescent labeling methods, 4,5 such as the enzyme-linked immunosorbent assay (ELISA), enable the production of largescale multiplexed microarrays, but also inhibit the collection of transient data due to the additional processing steps including post treatments, and may also alter the structure of the analyte. It is generally accepted that label-free detection is desired and several schemes have been proposed including mechanical, 6–10 electrical 11–13 and optical 14–16 signal transduction. Specific examples include electrochemical impedance spectroscopy, 17 field emission transistor sensors, 16,18 microcantilevers, 6,8 surface plasmon resonance spectroscopy, 19–23 and voltammetric sensors. 24,25 Label-free optical microarrays stand out as a powerful category that can perform real-time, continuous detection and binding interaction kinetic analyses. 1,14 In pursuit of label-free detection, nanosensors generally provide the benefits of high throughput, high sensitivity and the potential to massively multiplex arrays of miniature sensors, 2,3,11,18 all evident in the ample research studies published in recent years. 2,3,8,11,13,18,24–28 Label-free nanosensor microarrays for protein detection were studied in early work using field-effect transistor devices from silicon nanowires, where Lieber et al. examined multiple sensor devices in an array for cancer biomarker (the prostate specific antigen) detection. 11 Health et al. fabricated a silicon nanowire array for such purposes at an ultrahigh density of 1018 cm – 3 . 29 Field-effect transistors based on metal oxide semiconductors were later achieved by Fahmy and Reed et al., reporting prostate specific antigen and CA15.3 detection in whole blood. 13,30,31 Nanotransistor devices generally require complex, cleanroom fabrication that limits their multiplexing applications and their access as a general research tool. On the other 2


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hand, optical, label-free nanosensor microarrays were developed by employing noble metal films with periodic nanoholes that generate strong local plasmonic field when in resonance with the incident light. The platform has been applied to examine the biotin-streptavidin binding, to distinguish antibodies from different species, as well as to quantify the CD24 and EpCAM expressions on exosomes. 28,32,33 The top-down patterning process of the nanoholes hinders the integration of different recognition sites, thus multiplexing was mainly achieved by segregating nanoholes with microchannels. 28,33 Another plasmonic technique, the localized surface plasmon resonance using nanoparticles, has also been adapted to microarrays for neutravidin and antibody detection. 26,34 However, because the signal readout relies on the absorption spectra of nanoparticles, its microarray design requires a hyperspectral imaging system and has limited temporal resolutions. For a comprehensive review of label-free detection methods, please refer to reports from Rayet al. and Syahir et al. 2,3 In this study, we endeavor to develop an optical sensing microarray that not only is easy to prepare and multiplex like the traditional sandwich assays, but also combines the benefits of label-free platforms, performing real-time, continuous detection and binding interaction kinetic analyses. We develop a sensor array based on a single walled carbon nanotube(SWNT)/chitosan ink, functionalized to allow a divalent ion to quench the intrinsic near infrared (nIR) fluorescence of SWNTs (Figure 1). A capture protein or antibody possessing a hexa-histidine tag can then bind to the ion and transduce its binding with the target analyte by modulating the nIR emission of SWNTs. In contrast with conventional fluorophores that have constant fluorescence and require post processing to generate distinguishable signals, the nanotube sensors have intrinsic signal transduction upon the binding of target molecules, therefore allows real-time, in situ detection. The ink can be used in a standard microarray printer to create variable dimensions of sensor arrays with spots ≈ 200 µm in diameter at ≈ 300 spots/cm2 density. A 5×6 array is used for this study. We conjugate the sensors with immunoglobulin-binding proteins (Protein A, G and L) and examine antibodies including Human IgG, Mouse IgM, Rat IgG2a and Human IgD. In addition to the

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real-time, continuous detection, this platform allows us to measure binding kinetics in parallel for each sensor spot. Moreover, we have investigated the cross-reactivity, competitive and non-specific binding of analytes, demonstrating the recognition of Mouse IgM in multiplexed microarrays.

Results/Discussion Nanosensor construction The sensing of target biomolecules is transduced using the near IR fluorescence of semiconductor SWNTs. 35–42 Here, SWNTs are non-covalently modified with the immunoglobulinbinding proteins, Protein A, G and L. The Cu2+ ions are chelated to the complex to serve both as a bridge to bind the capture proteins and as proximity quenchers to modulate the SWNT fluorescence (Figure 1b). 43 More specifically, (6,5) chirality enriched SWNTs were first suspended in water by wrapping with the biopolymer chitosan through sonication and ultracentrifuge, resulting in a stable colloidal solution. The amine groups on chitosan reacts with succinic anhydride to expose carboxylic acid groups, which are subsequently conjugated with the Nα , Nα -bis(carboxymethyl)-L-lysine hydrate. The resulted terminal nitrilotriacetic acid (NTA) groups readily chelate with divalent Cu2+ ions. After the chelation, the metal ions were left with two vacant ligand sites and chelated strongly with the hexa histidine-tags on the recombinant Protein A, G and L. 44–46 The Cu2+ ions are slightly stretched away from the SWNT surfaces upon the binding of the analytes, reducing their quenching effect and enhancing the near IR emission of SWNTs. The design of the Cu-NTA chelating chemistry with the histidine-tag is intended to provide a universal method to integrate a variety of capture proteins in the same sensor microarray for multiplexed detection. The as-prepared SWNT/chitosan ink solution was characterized by visible-nIR absorption spectrum and single particle tracking. As shown in Figure 2a, the absorption spectrum of the SWNT solution shows distinct and sharp absorption peaks, indicating the successful 4


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Figure 1: The detection mechanism of label-free sensor arrays, based on the near infrared fluorescent SWNTs. (a) An optical micrograph of two 10×10 printed SWNT sensor arrays next to a ruler under ambient lighting. (b), The mechanism of label-free detection using a versatile chelating chemistry to integrate capture proteins into the SWNT microarray spots. Nanotubes are wrapped in chitosan polymer and non-covalently bonded to Cu2+ ions, which readily chelate with recombinant his-tagged capture proteins and serve as proximity quenchers of the SWNT near IR fluorescence. The binding between the capture protein and the target analyte modulates the distance between Cu2+ ions and SWNTs, changing the exciton quenching efficiency, resulting in variable emission intensities. In this study, immunoglobulin-binding proteins (Protein A, G and L) are used as the recognition sites to detect antibodies including Human IgG, Mouse IgM, Rat IgG2a and Human IgD. (c), The optical configuration of a custom-built microarray scanner, where the excitation laser at 560 nm is directed by two perpendicular galvo mirrors to scan the sensor array area on the substrate glass slide. The reflected near IR emission of each spot is filtered and sequentially recorded by an nIR photomultiplier tube (PMT) detector for image reconstruction.

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isolation of individual carbon nanotubes. The absorption peaks at 578 nm and 995 nm correlate to the E22 and E11 transitions between the valence bands and the conduction bands in (6, 5) nanotubes. 47 Moreover, the distribution of nanotube lengths in the colloidal solution was characterized by dark-field scattering microscopy, where individual nanotubes are tracked and analyzed (Figure 2b). The hydrodynamic diameters for most of nanotubes are between 125 nm (10 percentile) and 400 nm (90 percentile), with the average around 230 nm. (The hydrodynamic diameter is extracted from the particle scatterings based on an algorithm for spherical particles. Nevertheless, it serves as a good approximation of the nanotube length distribution.) The measured SWNTs have a concentration around 5 mg/L, diluted from the sensor ink used for printing. In addition, the Raman spectrum of the nanotubes was collected too, where we observe the radial breathing modes, the D-band, the G-band, and the G’-band. Since the surface modification was carried out non-covalently on the SWNTs, the Raman spectrum remains the same after the chemical conversion of the amines of chitosan to NTA groups. (See Supporting Info.)

Figure 2: Nanosensor characterization. (a), Visible-nIR absorption spectrum of the chitosan suspended SWNT colloidal solution, showing the E22 and E11 transitions at 578 nm and 995 nm. (b), Nanotube hydrodynamic diameter distribution collected by single-particle darkfield scattering microscopy. Most have a hydrodynamic diameter between 125 nm and 400 nm and the average is around 230 nm. (c), Fluorescence emission spectra of SWNT nanosensor spots modified with capture protein, his-tag protein A, before (black curve) and after adding 250 µg/mL Human IgG (red curve). The near IR fluorescence between 950 and 1100 nm originates from the (6,5) enriched nanotubes and shows a strong increase after adding the analyte, indicating the recognition of Human IgG. For our initial proof-of-concept, we modified the SWNTs with the immunoglobulinbinding protein, histidine-tagged recombinant protein A, in order to recognize the antibody, 6


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Human IgG. The (6,5) chirality nanotube sensors were excited by a 785 nm laser and their emission was collected by a near IR detector after passing a spectrometer. The spectra were recorded continuously as the analyte, 250 µg/mL of Human IgG, was added (Figure 2c). We observe about 10 % fluorescence intensity increase of the E11 transitions at around 1000 nm after adding the analyte, indicating that the binding between the Human IgG with protein A has pulled the Cu2+ ions further away from the SWNTs and has reduced the quenching effect of the metal ions. In the control group, where only phosphate-buffered saline (PBS) was added, there is no intensity increase (see Supporting Info), suggesting that the observed fluorescence change is induced by the specific binding interactions between protein A and the analyte Human IgG.

Sensor microarray In order to integrate multiple recognition sites, the SWNT/chitosan ink solution was dispensed onto a glass substrate by a microarray printer (MicroSys, Digilab, Inc.). Electrostatic interactions between the positively charged chitosan polymer and the negatively charged glass surface immobilize the SWNTs. The array dimension is tunable, and a 5×6 sensor array is employed, where each spot is 1 nL of the SWNT ink and contains pico grams of nanotube materials (Figure 3a), with a size around 210 ± 10 µm and a spot height about 45 - 50 nm, collected by the optical profilometer and the atomic force microscopy (Figure 3c-e). The non-covalent modification of SWNTs was then carried out on the glass surface, converting the amine groups of chitosan to NTA groups to chelate the Cu2+ ions. (Extra reagents in each steps of modification were rinsed away with water or PBS.) The capture protein solutions were printed onto the NTA modified SWNT array using the original coordinates. A custom-made glass slide holder was used to secure the same slide position in the holder.

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Figure 3: Nanosensor microarray characterization. (a), A near IR fluorescence image of a 6×7 carbon nanotube sensor microarray, collected by the home-built scanning imaging system. The grey scale is proportional to the emission intensity. The sensor responses of the spots inside the white square are shown in (b), which are examples of sensor spots responding to 250 µg/mL Human IgG (blue dot curves), with Protein A as the capture protein. The emission increases are fitted with a reversible binding model described in Equation (4) (red line curves). The relative fluorescence change of each spot ((δI − I0 )/I0 ) is plotted as a function of time, where the analyte was added at around 60 s. (c), The height profile map of a single spot characterized by a scanning optical profilometer, indicating that the spot height is around 40 -50 nm. The profile of the horizontal line is shown at top and that of the vertical line is shown on the right. (d), The optical diffraction image of the microarray. The spot size is measured as 210 ± 10 µm. (e), The atomic force microscopy image of the edge of one sensor spot, showing the absorption of nanoparticles on the glass slide and the measured the spot height is around 45 nm, similar to the results from the optical profilometer. (f), Near IR images and responses of arrays when different (continue on next page) 8


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Figure 3: (Continued) nanotube concentrations were used for printing. From left to right, the nanotube solution concentration increases from 15 mg/L to 60 mg/L. The concentration at 30 mg/L showed similar brightness as the 45 and 60 mg/L arrays, together with the highest response magnitude. The color scales are the same and shown on the right, in the unit of percentage. Scale bars: (a) 500 µm, (d) 200 µm, (e) 2 µm.

In order to optimize the printing procedure of the microarray, we have thoroughly examined different immobilization parameters, including 1) different concentrations of nanotube solutions, 2) electrostatic absorption versus covalent bonding of nanotubes, and 3) non-contact versus contact printing. The conclusion is that the contact printing with electrostatic absorbed SWNT at 30 mg/L produces the most homogenous spots and the optimal sensor response. For example, Figure 3f shows the near IR images and sensor responses of 4 arrays, where nanotube concentrations were tuned from 15 to 60 mg/L for printing. The lowest concentration results in an array that is less bright than the others. The concentration at 30 mg/L showed similar brightness as the 45 and 60 mg/L arrays, together with the highest response magnitude. This concentration is used for all following array preparations. Results of the other immobilization conditions are shown in Supporting Info., together with the optimization of signal analysis parameters. In order to continuously collect the near IR fluorescence of the microarray for analyte detection, we built a laser scanning imaging system, taking advantage of the high sensitivity of a photomultiplier tube detector and the large field of view provided by raster scanning. The excitation laser at 560 nm - in resonance of the (6,5) nanotube absorption - was directed by two galvo mirrors to scan the microarray area on the substrate glass slide. The reflected emission of the nanotubes passed a dichromic mirror, a long-pass filter at 950 nm and a short-pass filter at 1100 nm, and was collected by the single channel near IR PMT detector (Figure 1c). The generated voltage signal was amplified and recorded in a sequence corresponding to the order that the array was scanned. Using a Matlab code, the data sequence was organized to reconstruct the microarray emission image (Figure 3a). The fluorescence image was collected at a frequency of one frame per second over 5-6 min, where the first 9


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1 min was the baseline and real-time array responses were monitored continuously for another 4-5 min. This time scale is decided by the interaction of the analyte molecules with the capture proteins on nanotube surfaces, which is much shorter than previous sandwich assays and other optical microarrays that need several hours for data collection. 14 To illustrate the sensor microarray’s response, we used the recombinant his-tagged protein A as the capture protein and examined the recognition of Human IgG as the analyte. After the binding of Protein A, the microarray was covered with 10 µL PBS buffer and 10 µL Human IgG solution at 500 µg/mL was introduced. As shown in Figure 3b, where a portion of the microarray responses are plotted, upon the addition of the analyte, the near IR fluorescence of the spots increases following a negative exponential decay (blue dot curves). The interaction between the Protein A and Human IgG drives the sensor response and could be quantitatively fitted by a reversible binding model (red line curves) described by the following equations.

kon

CP + A CP − A

(1)

d[CP − A] = kon [CP ][A] − kof f [CP − A] dt

(2)

∵ kof f = kon KD

(3)

I − I0 (β − 1)[A] = [1 − exp(−(kon [A] + kon KD )t)], I0 [A] + KD

(4)

kof f

where CP is the capture protein; A is the analyte; CP − A is the binding complex formed between the capture protein and the analyte; I is the fluorescence intensity of the spot; I0 is the initial fluorescence intensity; β − 1 is the relative intensity change; kon is the association rate; kof f is the dissociation rate and KD is the dissociation constant. All the terms in parentheses represent the concentrations of corresponding species. (see Supporting Info.).

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Figure 4: Quantitative detection using the SWNT sensor microarray. (a), Variable capture protein concentrations result in different sensor responses towards the same amount of Human IgG (10 µL, 500 µg/mL). The optimized Protein A concentration is 250 µg/mL. The responses of sensor spots in one microarray are plotted in the box plot with the statistical labels. The corresponding response images of arrays are shown below the chart. The color scale has the same unit as in the box plot. (b), Increasing the analyte - Human IgG - concentration leads to a linear increase of the nanotube emission change (dashed line), demonstrating that the platform detect analytes quantitatively. Microarray response images are shown below. (c), Sensor array without the capture protein modification did not show fluorescence intensity change when antibody analyte was added. The unit of color scale is percentage.

Quantitative detection Following the recognition of the target analyte, we further investigated the capacity of the sensors for quantitative detection. We first examined how the sensor response is related to the amount of capture proteins. Different concentrations of Protein A (from 125 to 500 µg/mL) were used to functionalize the arrays. When treated with Human IgG at the same concentration, the maximum sensor response correlates to a Protein A concentration at 250 µg/mL. Both the lower and higher concentrations hinder the sensor response amplitude. 11


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The lower concentration is likely to generate less functional sensors, and the higher concentrations cause more steric repulsions and limit the access of Human IgG to the Protein A (Figure 4a). As a control, we examined the sensor responses in the absence of the capture protein. To two arrays that are either treated with Protein L or not, analyte Mouse IgM at 100 µg/mL was introduced. Only the array that has capture protein modification showed turn-on responses, confirming that the specific recognition of the antibody results from its binding with the capture protein. Using the optimized capture protein concentration, the sensor arrays were treated with different concentrations of analyte Human IgG. In the concentration region between 125 500 µg/mL, the sensor response amplitude is linearly related to the analyte concentrations (Figure 4b). Thus, we can quantitatively analyze the protein concentrations according to the sensor response magnitude. The sensors have shown responses as low concentration as low as 25 µg/mL, although it is not in the linear response region. Although the sensitivity of the array is not ideal compared to other optical methods previous reported, 14 it has large space of improvement and is not limited by the chemistry of nanotubes, but by the detector that is needed to accommodate a relatively large field of view. When a microscope with a 5x magnification objective was used to image part of the array, the detection limit is at least an order lower (See Supporting Info.). The sensitivity can be further increased with higher magnification imaging, as we have demonstrated single molecular sensitivity of nanotubes in previous reports, 27 although at the cost of much less sensor spots that can be imaged at the same time. The standard deviations of sensor spots in the same array correspond to 0.8 - 1.2 % response differences in the capture protein optimization and 1.1 - 1.4 % in the analyte quantification, comparable with the technical variations that are reported in other microarray methods. 48–51 The examination of variation sources and the demonstration of array reproducibility are detailed in the Supporting Info.

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Figure 5: Binding kinetic analysis and sensing specificity. (a), The association rates of the analyte binding to the capture proteins can be extracted from the sensor response curves. The blue curve plots one sensor spot emission intensity change after Human IgG was recognized by the immobilized Protein A. The arrow points at the time when the analyte was added. The first 10 data points after the analyte was introduced are fitted with a linear equation (Equation (6), the orange line and the inset), for the purpose of extracting the association rate (kon value) for this interaction. (b-d), Different capture protein modified sensors demonstrate different association rates with the same analyte, thus the platform can serve to distinguish the target molecules. Protein L functionalized sensors exhibit larger kon values with the analyte Mouse IgM (b) and Human IgD (c), consistent with the results collected by the biolayer interferometry (purple up triangles in the same plot). (d), For Rat IgG2a, forward binding reaction proceeds faster with Protein A sensors when compared with those modified with Protein G and Protein L. The association rates are collected based on the method shown in (a) and results from the same microarray treated with the same analyte are plotted in one cluster. kon values of the arrays are shown below the plots, where the color scale is on the right, of the same unit as in the plots.

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Kinetic analysis and sensing specificity Because the platform monitors the real-time nanosensor responses to the analyte, we have the advantage of examining the interaction kinetics between the target biomolecule and the capture protein. As we have discussed before, the binding reaction of Human IgG with Protein A on the sensor surface can be fitted with Equation (4), as shown in Figure 3b. At the initial stage of binding interaction, ample analytes react with the capture protein, thus the reaction in Equation (1) is almost completely forward. The rate of intensity change is controlled by the association rate, kon , and can be mathematically expressed using a derivation of Equation (4), as dI = kon (I0 β − 1)[A] − (I − I0 )(kon [A] + kon KD ). dt

(5)

Because at the initial stage, I ≈ I0 and the analyte concentration is close to its original concentration [A0 ], the above equation can be simplified to dI/I0 = kon (βmax − 1)[A0 ], dt

(6)

where βmax corresponds to the maximum relative intensity and can be calculated from the steady state of the binding interaction. (See Supporting Info. for the detailed derivation process.) The sensor response curve is smoothed by an exponential filter (α = 0.5) and a moving average filter (width = 9) to remove the noise. We then linearly fit the initial responses (10-15 data points after adding the analyte) with the above equation and extract the kon values for each sensor spot (Figure 5a). The resulting association rates of different spots in the same array are plotted together in a cluster in Figure 5b-d. Using this method, we examined the binding kinetics between the immunoglobulinbinding proteins and a group of antibodies (including Mouse IgM, Human IgD and Rat IgG2a). We find distinct association rates of different capture proteins when they bind to

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Table 1: kon results Protein A

Mouse IgM (×105 M −1 s−1 ) Human IgD (×104 M −1 s−1 )

Protein G

Protein L

SWNTs

BLI

SWNTs

BLI

SWNTs

BLI

1.11 ± 0.20

1.56 ± 0.02

2.36 ± 0.11

2.83 ± 0.06

4.18 ± 0.37

4.82 ± 0.12

2.03 ± 0.22

1.86 ± 0.05

1.98 ± 0.26

1.79 ± 0.03

4.99 ± 0.40

4.67 ± 0.07

the same analyte. In addition to Protein A, two other immunoglobulin-binding proteins, Protein G and Protein L, were used to modify the sensor arrays. When treated with the same analyte Mouse IgM, the microarray functionalized with Protein L exhibits much faster binding kinetics, resulting in an association rate of 4.18 ×105 M −1 s−1 , much larger than that of Protein A (1.11 ×105 M −1 s−1 ) and Protein G (2.36 ×105 M −1 s−1 ), in agreement with its higher binding affinity reported for affinity purification assays. In addition, the kon values extracted from the binding curves are comparable with the results collected by another kinetic analysis method (Table 1 and Figure 5), biolayer interferometry (BLI), validating the kinetic analysis results of our nanosensor platform. Similar to Mouse IgM, the binding between Human IgD and Protein L has an associate rate around 4.99 ×105 M −1 s−1 , compared to 2.03 ×105 M −1 s−1 for Protein A and 1.98 ×105 M −1 s−1 for Protein G. On the other hand, Rat IgG2a shows faster binding kinetics with Protein A (Figure 5d). Therefore, the distinct binding interactions between the analyte and different capture proteins could serve to detect the target analyte orthogonally and specifically. The ease of kinetic analysis of molecular level interactions is our main advantage compared to other conventional microassays.

Multiplexed detection We then examined the ability of this platform to integrate multiple capture proteins into the same microarray for parallel and orthogonal detection of multiple analytes. As an initial test, a microarray of separate parts was first printed, where the two components were modified

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Figure 6: Multiplexed microarray for real-time detection and kinetic analysis. (a), A microarray has two parts modified with either Protein G or Protein L, and only the Protein L spots responded to Human IgM. (b), Different capture proteins are integrated in alternative columns of an array to perform multiplexed detection. Protein G and Protein L are fluorescently labelled with Alexa Fluor 633 and Alexa Fluor 532, respectively and dispersed onto different columns. After washing, the residual fluorescence of the array is characterized by a two-channel visible microarray scanner, confirming the docking of capture proteins and the absence of crosstalk between spots. The partial quenching of the green emission is due to the overlap of the absorption of (6, 5) nanotubes and the emission of Alexa Flour 532 at around 560 nm. (c), Only the Protein L functionalized sensor spots showed large intensity change upon the adding of Mouse IgM, excluding the Protein G modified sensors. The first image on the left shows the initial near IR image of the microarray with two capture proteins. Blue shade boxes circle the sensor spots that are modified with Protein G and the other columns are with Protein L. The two colormaps in the middle and on the right exhibit the near IR intensity changes compared to the initial baseline, at the times before and after the analyte were added. (d), The binding kinetics of the analyte with the two capture proteins could be examined in parallel, based on the real-time sensor responses. (continue on next page) 16


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Figure 6: (Continued) The resulted kon values of the binding between Protein G and Protein L with the analyte Mouse IgM are similar to the previous results in Figure 5. Panel (b) and (c) are of the same scale and the scale bar is 1 mm.

with either Protein G or Protein L. When Human IgM (at 50 µg/mL) was introduced, only the Protein L functionalized sensors showed turn-on responses, confirming the independent responses of different sensors (Figure 6a). The two capture proteins - Protein G and Protein L - were then printed onto the alternative columns of the sensor array (Figure 6c). Successful capture protein functionalization was confirmed using fluorescent labeling of Protein G and Protein L with fluorophore Alexa Fluor 633 and Alexa Fluor 532, respectively. After extensive washing, the residual fluorescence of each spot was collected by a two-channel visible microarray scanner (Agilent G2565 microarray scanner). The two capture proteins are successfully bonded onto the sensor spots in the alternative columns with a minimum amount of crosstalk observed (Figure 6b). Due to the overlap of the absorption of the (6,5) SWNTs and the emission of the Alexa Fluor 532, the green emission is partially quenched in the center of spots, but less so at the edge of spots. To examine the detection performance, the functionalized microarray was treated with Mouse IgM at 250 µg/mL and the sensor responses were compared between columns (Figure 6c). After the baseline subtraction, the emission intensity change is plotted as a colormap of the spots. After the analyte addition, only spots that are modified with Protein L show substantial intensity increases, excluding the Protein G modified spots, showing minimal cross reactivity. The results suggest that such sensor spots in the multiplexed array specifically recognize the target analyte. Kinetic analyses of the real-time, parallel sensor responses yield kon values that are similar to previous results (Figure 6d), validating the platform for both the specific detection as well as the label-free kinetic analysis.

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Conclusions In summary, we have constructed a label-free, multiplexed microarray platform for real-time biomolecular detection, using fluorescent single walled carbon nanotubes. Nanotubes are non-covalently conjugated with immunoglobulin-binding proteins as the molecular recognition sites, to quantitatively detect antibody molecules, including Human IgD, Mouse IgM and Rat IgG2a. By examining the continuous sensor responses, arrays modified with different capture proteins exhibit distinct binding kinetics with the same analyte, where the collected association rates are consistent with those from biolayer interferometry. In addition, when both Protein G and Protein L are integrated into the same microarray, only the sensor spots modified with Protein L demonstrate substantial binding with the analyte Mouse IgM, confirming the specific recognition in the multiplexed microarray. Compared to conventional sandwich and other optical microarrays, our platform allows for real-time monitoring of binding interactions in a multiplexed array, together with facile kinetic analysis, which has the potential of analyzing reversible and transient binding reactions. It also has the advantage of easy preparation that does not require clean room fabrications or array initial calibrations, as in the case of other label-free detection methods. The future work will focus on expanding the microarrays with other capture proteins for orthogonal recognition in a mixture. This facile optical label-free detection platform will benefit bioanalytics for various applications.

Methods/Experimental Material Chitosan (medium molecular weight, Aldrich), N -(3-Dimethylaminopropyl)-N 0 -thylcarbodiimide hydrochloride (EDC, commercial grade, Aldrich), N -Hydroxysuccinimide (NHS, 97 %, Aldrich), Copper(II) chloride dihydrate (99.0 %, Aldrich), acetic acid (99 %, Aldrich), Nα , Nα -Bis(carboxymethyl)-

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L-lysine hydrate (97.0 %, Aldrich), phosphate buffered saline (PBS, 25×, pH 7.6, Spring Bioscience), phosphate buffered saline (1×, pH 7.4, Thermo Fisher scientific), succinic anhydride (99 %, Alfa Aesa), glass slide (H-slide, SCHOTT Nexterion), recombinant Protein A (Abcam, ab52953), recombinant Protein G (Abcam, ab49807), recombinant Protein L (Abcam ,ab155706), Mouse IgM isotype control (Thermo Fisher scientific, 02-6800), natural Human IgD (Abcam, ab91022), natural Human IgG (Abcam, ab91102), Rat IgG2a (Thermo Fisher scientific, 02-9688), BupHTM MES buffered Saline Packs (Thermo Fisher scientific, 28390), single wall carbon nanotube (SWNTs, (6,5) chirality, carbon 93-95 %, Aldrich), sodium hydroxide (pellets, 98 %, Aldrich) and HEPES solution (1 M, pH 7.5, Teknova) were used. All chemicals are reagent grade and used without further purification or modification.

Characterization The microarrays were printed using a microarray dispense system (Digilab Inc., MicroSys system). The volume for each spot was 1 nL and the spot-to-spot distance was 0.6 mm. The ultracentrifuge was carried out using a Beckman Coutler with an SW32 Ti rotor. The near infrared image and sensor responses of the microarray were collected by a custom-built near IR microarray scanner. A 560 nm laser (MPB communications Inc. maximum power: 1 W) was used as the excitation source. The laser beam was directed by a pair of galvo mirrors (Throlabs, Inc.) to raster scan the microarray area on the glass slide. The emission of the nanotubes passes a dichroic mirror and a set of filters to eliminate the excitation light, before being collected by a near IR photo-multiplier tube detector (PMT, Hamamatsu H10330A-25). The absorption spectrum of the carbon nanotube solution was collected by a UV-visNIR spectrophotometer (Agilent Technologies, Cary 5000). The near IR emission spectra were recorded by a home-built near infrared fluorescence spectrometer. A Zeiss AxioVision inverted microscope was coupled with a nitrogen-cooled InGaAs detector (Princeton Instruments InGaAs OMA V) through a PI Acton SP2500 spectrometer. The nanotubes were 19


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excited by a 785 nm photodiode laser, 450 mW at the source and 150 mW at the sample plane. The high resolution near IR image of the sensor spot was collected by a Zeiss AxioVision inverted microscope coupled to a nitrogen-cooled InGaAs 2D detector (Princeton Instruments), excited by a 785 nm laser excitation (InvictusTM , Kaiser Optical Systems), through a 20× objective. The Raman spectra were collected by a confocal Raman spectrometer HR-800 system (Horiba JY LabRAM) using a 532 nm excitation laser, a 10× objective lens and an 1800 lines/mm grating. The particle size analysis was carried out by a dark-field scattering microscopy by Malven Instruments Ltd. (NanoSight LM10) with a 405 nm laser. The exposure time for each collection was 60 s and the results were averaged over 5 exposures. The optical profilometer was collected on a 3D laser scanning microscope with a 50× objective (Keyence VK-X100). The atomic force microscope image was collected in a tapping mode on an Asylum Research MFP-3D AFM instrument on the glass slide with the microarray.

Preparation of functionalized SWNT microarrays The hydrophobic carbon nanotubes were wrapped with chitosan polymers by mixing 5 mg of (6,5) SWNTs with 15 mL chitosan solution, which was made by dissolving 40 mg of chitosan in 100 mL of water with 2.5% of acetic acid. The nanotube and water mixture was sonicated by a probe sonicator with a 6 mm probe tip at 10 W for 40 min. The resulting solution was ultracentrifuged at 35000 rpm for 4 h to remove the unsuspended or bundled particles. The visible-NIR absorption spectrum of the collected supernatant solution was recorded, and the SWNT colloidal solution concentration was calculated. Various concentrations of SWNT solutions were examined before choosing 30 mg/L for printing (Figure 3). As-prepared SWNT solution was dispensed by the microarray printer onto the glass slide, following the programed printing pattern. The volume for each spot is 1 nL. Compared to non-contact printing, contact printing produced more consistent spots, hence it was used. Both activated and deactivated H-slides were examined. When the N-hydroxysuccinimide 20


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(NHS) groups on the H-slide are deactivated, SWNTs absorb onto the slide due to electrostatic interactions between the chitosan amine groups and the carboxylate groups. When the NHS groups are present, the amine groups of chitosan reacts with the N-hydroxysuccinimide groups to covalently bond onto the glass surface. Except the testing of these two immobilization schemes, all other arrays present were electrostatically absorbed. A customized slide holder with a string on the edge was used to maintain the position of the glass slide for all the printing. After the printing, the slide was placed in an incubator at 38 ◦ C for 45 min to facilitate the immobilization of the SWNTs onto the glass slide. The microarrays were then washed with water for twice to remove non-absorbed SWNTs. To functionalize the chitosan SWNTs with the chelating group, the arrays were first reacted with succinic anhydride solution (0.05 M in 25× PBS buffer) at room temperature overnight, in order to convert the amine groups on chitosan to carboxylic acid groups. The resulting slide was rinsed with water for three times to remove unreacted reagents. Following the washing, the microarrays were covered with NHS/EDC solution in MES buffer (NHS: 0.52 M, EDC: 0.10 M) at room temperature for 2 h, followed by washing. Copper (II) chloride dihydrate (0.102 M) reacted with Nα ,Nα ,bis(carboxymethyl)-L-lysine (0.014 M) in 8 ml of water containing 162 µL of 1 M HEPES buffer. The solution pH was tuned to 7.5 with 3 M of NaOH, to chelate the Cu2+ ions with the NTA groups. The extra Cu2+ ions precipitated out upon the pH change and were removed by centrifuge. The supernatant Cu-NTA solution was used to react with the NHS groups on the chitosan SWNTs prepared in the last step. The conjugation reaction of the NHS groups with the amine groups on lysine was carried out overnight at room temperature. His-tag recombinant Protein A, G and L were used as the capture proteins. After reacting with the Cu-NTA solutions, the microarrays were rinsed with PBS buffer (pH 7.4) and placed back into the microarray printer to print the capture proteins. The volume for each spot was 1 nL, same as the SWNT printing procedure. The concentrations of capture protein solutions were from 125 - 500 µg/mL depending on the procedure. The arrays were rinsed

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with PBS buffer to remove the extra immunoglobulin-binding proteins.

Sensor array responses to the antibody analytes The functionalized SWNT microarrays are used for antibody detection and binding kinetic analyses. For this purpose, the microarray was first covered with 10 µL of PBS and placed on the stage in the home-built microarray scanner. The near IR emission of the microarray was monitored for 2-5 minutes as the baseline before the analyte was added. The fluorescence intensity of the microarray was continuously monitored for 8-10 min for the whole process. The near IR image of the microarray was reconstructed, and the fluorescence intensity change of individual sensor spot was calculated and plotted as shown in Figure 3b. The relative intensity change of the spots was used for quantitative comparison, and the initial intensity change upon adding the analyte was used for the association kinetic analysis. For the preparation of the multiplexed microarray, the printing of SWNTs and the capture proteins were carried out similarly. The differences are: for SWNT printing, instead of a regular rectangular array, certain spots were omitted in order to generate an array in which the alternative columns have either a 2-spot sequence or a 3-spot sequence, as shown in Figure 6c; correspondingly, the capture proteins were printed on the alternative columns Protein G on the 3-spot sequence column and Protein L on the 2-spot sequence column. The antibody detection using the microarray scanner and the following analysis were carried out using the same procedure as the regular arrays.

Acknowledgments This work was supported by the Abdul Latif Jameel World Water and Food Security Lab (J-WAFS), and GlaxoSmithKline plc.

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References 1. Yu, X.; Xu, D.; Cheng, Q. Label-Free Detection Methods for Protein Microarrays. Proteomics 2006, 6, 5493–5503. 2. Ray, S.; Mehta, G.; Srivastava, S. Label-Free Detection Techniques for Protein Microarrays: Prospects, Merits and Challenges. Proteomics 2010, 10, 731–748. 3. Syahir, A.; Usui, K.; Tomizaki, K.-y.; Kajikawa, K.; Mihara, H. Label and Label-Free Detection Techniques for Protein Microarrays. Microarrays 2015, 4, 228–244. 4. Woodbury, R. L.; Varnum, S. M.; Zangar, R. C. Elevated HGF Levels in Sera from Breast Cancer Patients Detected Using a Protein Microarray ELISA. J. Proteome Res. 2002, 1, 233–237. 5. Yao, J.; Schachermeyer, S.; Yin, Y.; Zhong, W. Cation Exchange in ZnSe Nanocrystals for Signal Amplification in Bioassays. Anal. Chem. 2011, 83, 402–408. 6. Braun, T.; Ghatkesar, M. K.; Backmann, N.; Grange, W.; Boulanger, P.; Letellier, L.; Lang, H.-P.; Bietsch, A.; Gerber, C.; Hegner, M. Quantitative Time-Resolved Measurement of Membrane Protein–ligand Interactions Using Microcantilever Array Sensors. Nat. Nanotechnol. 2009, 4, 179–185. 7. Wu, G.; Datar, R. H.; Hansen, K. M.; Thundat, T.; Cote, R. J.; Majumdar, A. Bioassay of Prostate-Specific Antigen (PSA) Using Microcantilevers. Nat Biotech 2001, 19, 856– 860. 8. McKendry, R.; Zhang, J.; Arntz, Y.; Strunz, T.; Hegner, M.; Lang, H. P.; Baller, M. K.; Certa, U.; Meyer, E.; Güntherodt, H.-J.; Gerber, C. Multiple Label-Free Biodetection and Quantitative DNA-Binding Assays on a Nanomechanical Cantilever Array. Proc. Natl. Acad. Sci. U. S. A. 2002, 99, 9783–9788.

23


ACS Nano 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

9. Shu, W.; Laurenson, S.; Knowles, T. P. J.; Ko Ferrigno, P.; Seshia, A. A. Highly Specific Label-Free Protein Detection from Lysed Cells Using Internally Referenced Microcantilever Sensors. Biosens. Bioelectron 2008, 24, 233–237. 10. Wee, K. W.; Kang, G. Y.; Park, J.; Kang, J. Y.; Yoon, D. S.; Park, J. H.; Kim, T. S. Novel Electrical Detection of Label-Free Disease Marker Proteins Using Piezoresistive Self-Sensing Micro-Cantilevers. Biosens. Bioelectron 2005, 20, 1932–1938. 11. Zheng, G.; Patolsky, F.; Cui, Y.; Wang, W. U.; Lieber, C. M. Multiplexed Electrical Detection of Cancer Markers with Nanowire Sensor Arrays. Nat. Biotechnol. 2005, 23, 1294–1301. 12. Luo, X.; J. Davis, J. Electrical Biosensors and the Label Free Detection of Protein Disease Biomarkers. Chem. Soc. Rev. 2013, 42, 5944–5962. 13. Stern, E.; Klemic, J. F.; Routenberg, D. A.; Wyrembak, P. N.; Turner-Evans, D. B.; Hamilton, A. D.; LaVan, D. A.; Fahmy, T. M.; Reed, M. A. Label-Free Immunodetection with CMOS-Compatible Semiconducting Nanowires. Nature 2007, 445, 519–522. 14. Özkumur, E.; Needham, J. W.; Bergstein, D. A.; Gonzalez, R.; Cabodi, M.; Gershoni, J. M.; Goldberg, B. B.; Ünlü, M. S. Label-Free and Dynamic Detection of Biomolecular Interactions for High-Throughput Microarray Applications. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 7988–7992. 15. Marusov, G.; Sweatt, A.; Pietrosimone, K.; Benson, D.; Geary, S. J.; Silbart, L. K.; Challa, S.; Lagoy, J.; Lawrence, D. A.; Lynes, M. A. A Microarray Biosensor for Multiplexed Detection of Microbes Using Grating-Coupled Surface Plasmon Resonance Imaging. Environ. Sci. Technol. 2012, 46, 348–359. 16. Chen, Z.; Tabakman, S. M.; Goodwin, A. P.; Kattah, M. G.; Daranciang, D.; Wang, X.; Zhang, G.; Li, X.; Liu, Z.; Utz, P. J.; Jiang, K.; Fan, S.; Dai, H. Protein Microarrays with Carbon Nanotubes as Multicolor Raman Labels. Nat. Biotechnol. 2008, 26, 1285–1292. 24


Page 24 of 30

Page 25 of 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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17. Evans, D.; Johnson, S.; Laurenson, S.; Davies, A. G.; Ko Ferrigno, P.; Wälti, C. Electrical Protein Detection in Cell Lysates Using High-Density Peptide-Aptamer Microarrays. J. Biol. 2008, 7, 3. 18. Vacic, A.; Criscione, J. M.; Stern, E.; Rajan, N. K.; Fahmy, T.; Reed, M. A. Multiplexed SOI BioFETs. Biosens. Bioelectron. 2011, 28, 239–242. 19. Patching, S. G. Surface Plasmon Resonance Spectroscopy for Characterisation of Membrane Protein–ligand Interactions and Its Potential for Drug Discovery. Biochim. Biophys. Acta 2014, 1838, 43–55. 20. Grosjean, L.; Cherif, B.; Mercey, E.; Roget, A.; Levy, Y.; Marche, P. N.; Villiers, M.-B.; Livache, T. A Polypyrrole Protein Microarray for Antibody–antigen Interaction Studies Using a Label-Free Detection Process. Anal. Chem. 2005, 347, 193–200. 21. Yoshikawa, H.; Murahashi, M.; Saito, M.; Jiang, S.; Iga, M.; Tamiya, E. Parallelized Label-Free Detection of Protein Interactions Using a Hyper-Spectral Imaging System. Anal. Methods 2015, 7, 5157–5161. 22. Lausted, C.; Hu, Z.; Hood, L.; Campbell, C. T. SPR Imaging for High Throughput, Label-Free Interaction Analysis. Comb. Chem. High Throughput Screening 2009, 12, 741–751. 23. Taylor, J. D.; Linman, M. J.; Wilkop, T.; Cheng, Q. Regenerable Tethered Bilayer Lipid Membrane Arrays for Multiplexed Label-Free Analysis of Lipid-Protein Interactions on Poly(Dimethylsiloxane) Microchips Using SPR Imaging. Anal. Chem. 2009, 81, 1146– 1153. 24. Eissa, S.; Zourob, M. Aptamer- Based Label-Free Electrochemical Biosensor Array for the Detection of Total and Glycated Hemoglobin in Human Whole Blood. Sci. Rep. 2017, 7, 1016.

25


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25. Okuno, J.; Maehashi, K.; Kerman, K.; Takamura, Y.; Matsumoto, K.; Tamiya, E. LabelFree Immunosensor for Prostate-Specific Antigen Based on Single-Walled Carbon Nanotube Array-Modified Microelectrodes. Biosens. Bioelectron 2007, 22, 2377–2381. 26. Endo, T.; Kerman, K.; Nagatani, N.; Hiepa, H. M.; Kim, D.-K.; Yonezawa, Y.; Nakano, K.; Tamiya, E. Multiple Label-Free Detection of Antigen-Antibody Reaction Using Localized Surface Plasmon Resonance-Based Core-Shell Structured Nanoparticle Layer Nanochip. Anal. Chem. 2006, 78, 6465–6475. 27. Landry, M. P.; Ando, H.; Chen, A. Y.; Cao, J.; Kottadiel, V. I.; Chio, L.; Yang, D.; Dong, J.; Lu, T. K.; Strano, M. S. Single-Molecule Detection of Protein Efflux from Microorganisms using Fluorescent Single-Walled Carbon Nanotube Sensor Arrays. Nat. Nanotechnol. 2017, 12, 368–377. 28. Im, H.; Lesuffleur, A.; Lindquist, N. C.; Oh, S.-H. Plasmonic Nanoholes in a Multichannel Microarray Format for Parallel Kinetic Assays and Differential Sensing. Anal. Chem. 2009, 81, 2854–2859. 29. Wang, D.; Sheriff, B. A.; Heath, J. R. Silicon P-FETs from Ultrahigh Density Nanowire Arrays. Nano Lett. 2006, 6, 1096–1100. 30. Stern, E.; Vacic, A.; Rajan, N. K.; Criscione, J. M.; Park, J.; Ilic, B. R.; Mooney, D. J.; Reed, M. A.; Fahmy, T. M. Label-Free Biomarker Detection from Whole Blood. Nat. Nanotechnol. 2010, 5, 138–142. 31. Stern, E.; Steenblock, E. R.; Reed, M. A.; Fahmy, T. M. Label-Free Electronic Detection of the Antigen-Specific T-Cell Immune Response. Nano Lett. 2008, 8, 3310–3314. 32. Chang, T.-Y.; Huang, M.; Ali Yanik, A.; Tsai, H.-Y.; Shi, P.; Aksu, S.; Fatih Yanik, M.; Altug, H. Large-Scale Plasmonic Microarrays for Label-Free High-Throughput Screening. Lab Chip 2011, 11, 3596–3602.

26


Page 26 of 30

Page 27 of 30 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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33. Im, H.; Shao, H.; Park, Y. I.; Peterson, V. M.; Castro, C. M.; Weissleder, R.; Lee, H. Label-Free Detection and Molecular Profiling of Exosomes with a Nano-Plasmonic Sensor. Nat Biotech 2014, 32, 490–495. 34. Raphael, M. P.; Christodoulides, J. A.; Mulvaney, S. P.; Miller, M. M.; Long, J. P.; Byers, J. M. A New Methodology for Quantitative LSPR Biosensing and Imaging. Anal. Chem. 2012, 84, 1367–1373. 35. Ahn, J.-H.; Kim, J.-H.; Reuel, N. F.; Barone, P. W.; Boghossian, A. A.; Zhang, J.; Yoon, H.; Chang, A. C.; Hilmer, A. J.; Strano, M. S. Label-Free, Single Protein Detection on a Near-Infrared Fluorescent Single-Walled Carbon Nanotube/Protein Microarray Fabricated by Cell-Free Synthesis. Nano Lett. 2011, 11, 2743–2752. 36. Bisker, G.; Ahn, J.; Kruss, S.; Ulissi, Z. W.; Salem, D. P.; Strano, M. S. A Mathematical Formulation and Solution of the CoPhMoRe Inverse Problem for Helically Wrapping Polymer Corona Phases on Cylindrical Substrates. J. Phys. Chem. C 2015, 119, 13876– 13886. 37. Bisker, G.; Dong, J.; Park, H. D.; Iverson, N. M.; Ahn, J.; Nelson, J. T.; Landry, M. P.; Kruss, S.; Strano, M. S. Protein-Targeted Corona Phase Molecular Recognition. Nat. Commun. 2016, 7, 10241. 38. Nelson, J. T.; Kim, S.; Reuel, N. F.; Salem, D. P.; Bisker, G.; Landry, M. P.; Kruss, S.; Barone, P. W.; Kwak, S.; Strano, M. S. Mechanism of Immobilized Protein A Binding to Immunoglobulin G on Nanosensor Array Surfaces. Anal. Chem. 2015, 87, 8186–8193. 39. Iverson, N. M.; Bisker, G.; Farias, E.; Ivanov, V.; Ahn, J.; Wogan, G. N.; Strano, M. S. Quantitative Tissue Spectroscopy of Near Infrared Fluorescent Nanosensor Implants. J. Biomed. Nanotechnol. 2016, 12, 1035–1047. 40. Landry, M. P.; Vukovic, L.; Kruss, S.; Bisker, G.; Landry, A. M.; Islam, S.; Jain, R.; Schulten, K.; Strano, M. S. Comparative Dynamics and Sequence Dependence of DNA 27


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and RNA Binding to Single Walled Carbon Nanotubes. J. Phys. Chem. C 2015, 119, 10048–10058. 41. Landry, M. P.; Kruss, S.; Nelson, J. T.; Bisker, G.; Iverson, N. M.; Reuel, N. F.; Strano, M. S. Experimental Tools to Study Molecular Recognition within the Nanoparticle Corona. Sensors 2014, 14, 16196–16211. 42. Salem, D. P.; Landry, M. P.; Bisker, G.; Ahn, J.; Kruss, S.; Strano, M. S. Chirality Dependent Corona Phase Molecular Recognition of DNA-Wrapped Carbon Nanotubes. Carbon 2016, 97, 147–153. 43. Brege, J. J.; Gallaway, C.; Barron, A. R. Fluorescence Quenching of Single-Walled Carbon Nanotubes with Transition-Metal Ions. J. Phys. Chem. C 2009, 113, 4270–4276. 44. Hainfeld, J. F.; Liu, W.; Halsey, C. M. R.; Freimuth, P.; Powell, R. D. Ni–NTA–Gold Clusters Target His-Tagged Proteins. J. Struct. Biol. 1999, 127, 185–198. 45. Reuel, N. F.; Ahn, J.-H.; Kim, J.-H.; Zhang, J.; Boghossian, A. A.; Mahal, L. K.; Strano, M. S. Transduction of Glycan–Lectin Binding Using Near-Infrared Fluorescent Single-Walled Carbon Nanotubes for Glycan Profiling. J. Am. Chem. Soc 2011, 133, 17923–17933. 46. Zhang, D.; He, H.; Liu, M.; Meng, Z.; Guo, S. A Novel Assay for Screening Inhibitors Targeting HIV-1 Integrase Dimerization Based on Ni-NTA Magnetic Agarose Beads. Sci. Rep. 2016, 6, 25375. 47. Bachilo, S. M. Structure-Assigned Optical Spectra of Single-Walled Carbon Nanotubes. Science 2002, 298, 2361–2366. 48. Zakharkin, S. O.; Kim, K.; Mehta, T.; Chen, L.; Barnes, S.; Scheirer, K. E.; Parrish, R. S.; Allison, D. B.; Page, G. P. Sources of Variation in Affymetrix Microarray Experiments. BMC Bioinf. 2005, 6, 214. 28


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49. Bryant, P. A.; Smyth, G. K.; Robins-Browne, R.; Curtis, N. Technical Variability Is Greater than Biological Variability in a Microarray Experiment but Both Are Outweighed by Changes Induced by Stimulation. PLoS One 2011, 6, e19556. 50. Coombes, K. R.; Highsmith, W. E.; Krogmann, T. A.; Baggerly, K. A.; Stivers, D. N.; Abruzzo, L. V. Identifying and Quantifying Sources of Variation in Microarray Data Using High-Density cDNA Membrane Arrays. J. Comput. Biol. 2002, 9, 655–669. 51. Bakay, M.; Chen, Y.-W.; Borup, R.; Zhao, P.; Nagaraju, K.; Hoffman, E. P. Sources of Variability and Effect of Experimental Approach on Expression Profiling Data Interpretation. BMC Bioinf. 2002, 3, 4.

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Analysis of Multiplexed Nanosensor Arrays Based on Near-Infrared

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