Increased SERS Detection Efficiency for Characterizing Rare Events

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Analytical Chemistry

Increased SERS Detection Efficiency For Characterizing Rare Events In Flow Kevin T. Jacobs and Zachary D. Schultz* University of Notre Dame, Department of Chemistry and Biochemistry, Notre Dame, IN, 46556, USA *email of corresponding author: [email protected]

Abstract: Improved SERS measurements of a flowing aqueous sample are accomplished by combining line focus optics with sheath-flow SERS detection. The straightforward introduction of a cylindrical lens into the optical path of the Raman excitation laser increases the efficiency of SERS detection and the reproducibility of SERS signals at low concentrations. The width of the line focus is matched to the width of the sample capillary from which the analyte elutes under hydrodynamic focusing conditions, allowing for increased collection across the SERS substrate while maintaining the power density below the damage threshold at any specific point. We show that a 4x increase in power spread across the line increases the signal to noise ratio by a factor of 2 for a variety of analytes, such as rhodamine 6G, amino acids, and lipid vesicles, without any detectable photodamage. COMSOL simulations and Raman maps elucidate the hydrodynamic focusing properties of the flow cell, providing a clearer picture of the confinement effects at the surface where the sample exits the capillary. The lipid vesicle results suggest that the combination of hydrodynamic focusing and increased optical collection enables the reproducible detection of rare events, in this case individual lipid vesicles.

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Introduction. Biomedical diagnostics rely on sensitive, selective, and rapid identification of chemical species.1 Absorption and fluorescence detection platforms offer simple methods for a variety of diagnostics but are limited by the amount of chemical identification information they provide. Mass spectrometry offers exquisite chemical identification, but the necessary instrumentation is typically confined to large core facilities. Surface-enhanced Raman scattering (SERS) can address these issues in a cost-effective manner. SERS has been used for detection of analytes in aqueous solutions in a variety of detection platforms, which has enabled improved detection of bacteria, drugs of abuse, and other chemicals.2-8 Innovative approaches have been reported for detection in flow. Plasmonic nanodome arrays have been developed and implemented into a flow cell for monitoring drugs in IV tubing.9,10 An innovative SERS substrate was created by directly evaporating silver onto a PDMS channel and then etching with O2 to create a nanostructured surface.11 SERS detection can be challenging due to the need for analytes to interact with the enhancing nanostructure within the laser focus.12,13 SERS detection in fluids offers additional challenges arising from limited interaction times and possibilities for the analytes to diffuse away from the nanostructures, all of which is further complicated in a dynamic, flowing system. Recently, hydrodynamic focusing was shown to confine analytes near a SERS substrate in flow and improve detection efficiency.14 This initial work placed a small sample capillary inside a larger sheath-flow channel, such that the sheath flow confines the sample, exiting from a smaller capillary, in close proximity to the SERS-active substrate. The confinement makes diffusion to the surface an effective mode of transport, where the analyte is reversibly adsorbed during detection. Adsorption to the surface has been reported to be necessary for obtaining a


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strong SERS signal in solution.12 Using a planar SERS substrate for detection improves the reproducibility of the SERS spectrum by maintaining a consistent plasmonic environment. While nanoparticle aggregates have shown promise, spectral reproducibility is challenging. Segmented microdroplet experiments have shown heterogeneity within nanoparticle aggregates.15 Sheath-flow SERS provides increased interactions and a consistent enhancement for repeated detection. Coupled with capillary electrophoresis separations, the sheath-flow SERS detection has been demonstrated for the on-line detection of dyes,16 amino acids,17 and small peptides.18 For detection in flow, the confined analyte region should be matched to the laser excitation to ensure dilute species interact in the laser focus. Using large spot sizes degrades spectral resolution as the slit on the spectrograph has to be increased to capture all the scattered photons. One solution to this challenge, commonly used in imaging, is to shape the focus into a line.19-21 Because the line is then diffraction limited in width, a narrow monochromator slit can be used to retain the spectral resolution that is key for molecular identification. Another approach is raster orbital scanning implemented by Snowy Range Instruments.22 In flow, the residence time at the SERS substrate is typically on the timescale of milliseconds. Thus increasing the detection area provides a means to maximize the number of molecules giving rise to the signal and improving the signal to noise ratio (SNR). At high concentrations, this is less critical; however, it increases reproducibility for low concentration detection. Rare events are challenging in regards to detection as not all molecules in the sample are detected by SERS. This was evident in previous experiments performed in the lab as the injection time of the sample was longer than the detected SERS signal duration.16 Larger particles and cells adsorb more readily to surfaces. SERS has been shown to distinguish cell



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types23,24 and to detect rare species, such as circulating tumor cells, offering tremendous diagnostic potential. In the current work, we have added line focus excitation to improve the abilities of the sheath-flow SERS detector. The straightforward addition of a cylindrical lens to the path of the Raman excitation laser creates a ‘line’ focused detection spot. By matching the line focus to the width of the sample capillary, increased detection efficiency is achieved. By dispersing the laser intensity throughout the line, increased SNR is obtained without increased photodamage. Photodamage to a sample is a known problem in laser-based analyses due to photothermal and photochemical effects.25 This increase in SNR also results in improved reproducibility of the SERS signal from dilute samples such as lipid vesicles.

Experimental. An extended description of the materials and methods used are provided in the electronic supporting information. Materials. Rhodamine 6G (R6G, ~95%), 4-mercaptobenzoic acid (4-MBA), thiophenol, methionine, serine, arginine, sodium hydroxide, and ethanol were purchased from Sigma-Aldrich (St. Louis, MO). Di-palmitoyl-phosphotidyl choline was purchased from Avanti Polar Lipids (Alabaster, AL). Ultrapure water (18.2 MΩ cm) was obtained from a Barnstead Nanopure filtration system. Fused silica capillary was purchased from Polymicro Technologies (Phoenix, AZ).


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Line Focus Raman Detection. Measurements were performed using a previously described home-built system with some modifications.26 A 40x water-immersion objective (NA = 0.80) was used to focus a 660 nm (Laser Quantum, San Jose, CA) laser onto the substrate in the flow cell. Raman scattering was collected through this objective lens and directed to the spectrograph (Princeton Instruments, Trenton, NJ). The Raman scattering was focused onto a 50 µm slit using a 4x microscope objective (NA = 0.10). The power for all measurements was collected at the sample. Line focusing of the laser was achieved by placing a cylindrical lens (f=500 mm) into the beam path approximately one focal length away from the sample as shown in Figure 1. The lens was rotated until the line shape of the laser was normal to the capillary on the substrate as viewed through the eyepiece of the microscope. A Renishaw InVia Raman microscope (Renishaw, Inc) with 632.8 nm HeNe laser excitation was used for the Raman mapping experiments. Sheath Flow SERS Detector. Sheath flow SERS detection was performed using the flow cell27 and SERS substrate26 described previously. A fused silica capillary, i.d. 72 um, o.d. 143 um, was affixed to the substrate to be roughly centered in the sheath-flow channel. Data Processing. All spectra were processed using Matlab 2012a (Mathworks) with the PLS toolbox and Igor Pro (WaveMetrics).

Results and Discussion. The change from point to line laser shape was first validated by comparing the SERS signals obtained from both line and point focusing. The spectroscopically dispersed signal from both point and line focus experiments of a thiophenol SAM on a SERS substrate was imaged



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onto the CCD as shown in Figures 2A and 2B. The large detection region is clearly evident in Figure 2B by the broader spectroscopic features. The laser power was increased to approximately 4 mW for the line, which at the highest intensity pixel generates the same signal as 1 mW for the point focused image (Fig. 2C). This shows that the highest intensity pixel, or spot on the surface, is at the same power density as in the spot focus. The 4 mW of power is spread throughout the line focus, spreading laser intensity across a larger sample area. As long as the increase in laser power is spread over a larger area, thus not increasing the power density, there is no risk for any additional photodamage to the surface. The width of a Gaussian fit to the peak in Figure 2C can be used to estimate the length of the line focus laser. The imaged line measures 17 pixels full width half maximum (FWHM) and 31 pixels at 90% of the maximum (FWTM). Based on the 8x magnification and the 16 µm pixel size, this corresponds a excitation line 34 µm at the FWHM and 62 µm at the FWTM. When the line focus length is the width of the capillary in the flow cell, this increase in laser power over a larger area should generate an increase in signal. Because the line focus is still diffraction limited in width, there is no loss in intensity or spectral resolution when imaged onto the spectrometer slit. The improved spectroscopic detection was validated with R6G samples, generating a better SNR from analytes in flow. Figure 3 shows the spectra obtained from point and line focus geometries for different concentrations of R6G solutions. R6G was flowed through the capillary onto a bare silver SERS substrate, collected in rapid 200 ms acquisitions. Figure 3A compares the SERS spectra of 10-6 M R6G collected using line (a) and point (b) foci. The use of the line focus generates a stronger SNR than the point focus, 38.6 to 16.5 respectively. This 2x increase in SNR is consistent with the 4x increase in power, which


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corresponds to a 4x increase in scattered photons. The line focused laser spot is able to capture a larger surface area to which molecules exit the capillary and interact with the surface. To verify that no signal is lost upon collecting the scatter from the line focus, the signal from a 1 mW spot focus was compared to the signal from a 1 mW line focus. This experiment was conducted on R6G in flow and a monolayer of thiophenol, where both line and point focus measurements were done with full vertical binning on the CCD detector. The spectra acquired in this fashion were the same. Thus adding a cylindrical lens does not affect the collection efficiency, as there is no significant change in total detected photons. In Figure 3B, 10-7 M R6G was flowed through the capillary and detected on the silver SERS substrate. The line focused laser at 4 mW, again generates a stronger SNR than point focused at 1 mW, 16.2 to 8.27, respectively, a two-fold increase. This is consistent with the results from the thiophenol monolayer noted above. The improvement in SNR was also verified using an amino acid mixture, as shown in Figure S-1. In our previous work,14 there was a strong signal dependence related to the position of the focus in the confined sample stream. The effect of the line focus on signal collection was investigated by collecting SERS spectra from different points along the sample capillary output. Figure S-2 plots the SERS intensity of R6G at 1360 cm-1 as measured from both the line and a point focus as they are translated across the sample stream. At a central position the powernormalized intensity from the line and point focus are closely matched. Moving to positions off the center of the capillary, the line focus (Fig. S-2A) is still able to detect an increased fraction of the molecules exiting the capillary while the point focused signal (Fig. S-2B) decreases more rapidly. This demonstrates the importance, when using a laser focused to a spot, of ensuring the



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focus is directly in the middle of the sample stream exiting capillary, any deviation can lead to a great loss in signal. The line focus allows some deviation from the center while capturing a broader cross-section of analytes in the flow stream and still generating substantial signal. To further assess the focusing effect on the SERS substrate, a SAM of 4-MBA was investigated, shown in Figure S-3. The Raman spectrum of 4-MBA has a COO- vibrational band at 1372 cm-1 that shows pH dependent change in intensity relative to other peaks in the spectrum, such as the 1588 cm-1 mode used in our study. This distinct pH dependence exhibits high intensity at basic pH and low intensity in acidic pH.28,29 The intensity of the 1372 cm-1 mode was mapped in a basic sheath flow (Fig. S-3A) and with an acidic solution eluting from the sample capillary (Fig. S-3B). This change in intensity provides a signal that correlates with the hydrodynamic confinement region. A range of pH solutions were flowed from the sample capillary in the flow cell, and the intensity at 1372 cm-1 was compared to the intensity obtained from the SERS substrate in each pH solution without flow (Fig S-3C). The observed change in the vibrational spectrum is consistent across measurements done both in flow as well as in fixed pH solutions. The pH dependent SERS signals provide direct visualization of the confinement region at the surface. The observed confinement is consistent with our previous fluorescence images and the COMSOL calculation.14 This further supports our claim that a line focus will collect more of the molecules interacting with the surface, better than a point focus, improving the SNR for analyte detection. The improved SNR associated with the line focus was used to detect a lipid vesicle sample purified by capillary electrophoresis. The flow cell channel and capillary in the flow cell were filled with 15 mM borate buffer, and the sheath fluid flow rate was lowered to 10 µL/min to match the slower electrokinetic flow from the sample capillary. 400 nm diameter lipid vesicles


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were loaded into the capillary through a 2s pressure injection (130 nL). High voltage, 300 V/cm, was applied and transported the vesicles through the capillary. Using a point focus, the observed signals lack reproducibility, sometimes being detected, often not. We attribute this observation to vesicles exiting the sample capillary and not interacting with the SERS substrate in the laser focus. Figure 4A shows the heat map and rapid on and off SERS signal that the lipids produced. Figure 4B shows the corresponding Raman signal of one 250 ms acquisition of a run of lipids through capillary electrophoresis. The observed peaks are consistent with the Raman spectrum of DPPC.12 The SNR of the SERS signal of the lipid vesicles isolated by CE was 15.8 and 55.0 for the CC stretch (1065 cm-1) and choline stretch (715 cm-1), respectively. Previously reported data of a similarly sized vesicle freely diffusing around the surface showed a SNR of 7 using the C-C stretch of the DPPC vesicle.12 Comparing the hydrodynamic confinement with line focusing detection to free diffusion with point detection, the SNR for our current result is greater; however, it includes a longer signal acquisition time. Correcting for the acquisition time, the SNR is nominally the same. In the previous work, the signal correlated to a single vesicle, which suggests the signal observed in our current work also arises from a single vesicle. Because the confinement resulting from hydrodynamic focusing is still larger than the diffusion layer, many of the vesicles in our sample travel through the beam path but do not interact with the silver nanostructures to generate SERS signal. The signal width for the CE-SERS spectra in the Figure 4A inset is 800 ms compared to an expected transit time of 300-400 ms, interpolating the data for a similarly sized vesicle freely diffusing from previous work.12 This increase in width indicates that either the vesicle is more strongly retained at the surface or we are sequentially detecting



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more than 1 vesicle. The narrow peaks in the SERS electropherogram are consistent with CELIF detection of individual organelles that similarly show narrow migration peaks.30 Interestingly, the detection time on the heat map shows that the lipids were detected for approximately 800 milliseconds; the actual migration time for the lipids is expected to correlate to the 2 s injection. Previous work claims that peak narrowing results from a Langmuir type adsorption mechanism.18 We estimate that 40,000 lipid vesicles are loaded into the capillary for SERS detection. Models suggest that the height of the confinement regions is still larger than the diffusion layer by an order of magnitude.14 This further indicates that the line focus increases the lateral capture area, but only a fraction of molecules loaded into the capillary are confined close enough to the surface to be detected by SERS. Future studies will investigate additional ways to improve the confinement and optimize the SERS signal. In conclusion, we have demonstrated a simple increase in SNR with the addition of line focusing a SERS detection platform utilizing hydrodynamic focusing. The SNR increase was evident across multiple different analytes. The SNR gain was due to the increase in detection area of the laser while maintaining the power density at the central point in the beam path. This power density was controlled to ensure there was no increase in risk of photodamage to the analytes. The line focusing allowed for reproducible lipid vesicle detection, which was not observed with the point focus. The ability to detect structures like lipid vesicles opens new possibilities to detect differences in microvesicles and exosomes in circulation that are associated with diseases such as cancer.31 The ability to obtain chemical specific detection of individual lipid vesicles suggests a powerful new method for biomarker detection.


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Acknowledgement: The authors acknowledge support from the National Institutes of Health Award R21GM107893, a Cottrell Scholar Award to ZDS from Research Corporation for Science Advancement, the Walther Cancer Foundation, and the University of Notre Dame. Supporting Information Available. Additional experimental details and Figures S-1, S-2, and S-3 are available in supporting information. This information is available free of charge via the Internet at http://pubs.acs.org/



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Figure 1.

Figure 1. Diagram of the laser path. The distance from the cylindrical lens to the back aperture of the objective matches the focal length of the cylindrical lens, 500 mm.


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Figure 2

Figure 2. Heat map the SERS signal of thiophenol SAM on a silver SERS-active substrate collected as an image on the CCD using the point (A) and line (B) configurations. The 1580 cm-1 Raman shift of thiophenol plotted demonstrating the intensity differences of the point (blue) and line (red) spread across the CCD.



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Figure 3

Figure 3. Raman spectra of R6G acquired in 200 ms acquisitions. 10-6 M (A) and 10-7 M (B) R6G comparing the signal intensity differences collected using the line (a) and point (b) focused laser.


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Figure 4

Figure 4. (A) The SERS electropherogram showing the intensity change at each Raman shift as a function of time for a sample of 0.4 µm DPPC lipid vesicles collected in 250 ms acquisitions with line focus detection for the sheath-flow SERS flow cell. Inset: the intensity of the choline band at 715 cm-1 demonstrating the rapid on then off signal. (B) The SERS spectrum from the most intense spectrum collected in the migration band of the SERS electropherogram.



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Increased SERS Detection Efficiency for Characterizing Rare Events

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