Quantitative Characterization of Individual Microdroplets using Surface

Article pubs.acs.org/ac

Quantitative Characterization of Individual Microdroplets using Surface-Enhanced Resonance Raman Scattering Spectroscopy Christopher D. Syme, Chiara Martino, Rama Yusvana, Narayana M. S. Sirimuthu, and Jonathan M. Cooper* Advanced Medical Diagnostics group, School of Engineering, University of Glasgow, Glasgow, G12 8LT, Scotland, U.K. S Supporting Information *

ABSTRACT: Surface-enhanced resonance Raman scattering (SERRS) spectroscopy is a highly sensitive optical technique capable of detecting multiple analytes rapidly and simultaneously. There is significant interest in SERRS detection in micro- and nanotechnologies, as it can be used to detect extremely low analyte concentrations in small volumes of fluids, particularly in microfluidic systems. There is also rapidly growing interest in the field of microdroplets, which promises to offer the analyst many potential advantages over existing technologies for both design and control of microfluidic assays. While there have been rapid advances in both fields in recent years, the literature on SERRS-based detection of individual microdroplets remains lacking. In this paper, we demonstrate the ability to quantitatively detect multiple variable analyte concentrations from within individual microdroplets in real time using SERRS spectroscopy. We also demonstrate the use of a programmable pump control algorithm to generate concentration gradients across a chain of droplets.

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multiplexed optical detection is internal standardization, which relies upon the ability to detect an analyte and a reference probe simultaneously.35 Internal standardization of this kind requires the detection of two or more optical markers at different concentrations within individual microdroplets. Preferably, in the context of microdroplets, such measurements would be made in a high-throughput format. In this paper, we take the next step on from work that has previously combined SERRS detection and microdroplets and demonstrate for the first time the quantitative real-time spectral characterization of variable analyte mixtures within individual microdroplets using SERRS multiplexing spectroscopy.

urface-enhanced resonance Raman scattering (SERRS) spectroscopy1,2 is an increasingly important and versatile optical detection technique capable of generating informationrich data from extremely low concentrations of analyte such as those typically encountered in microfluidic systems3 and in microdroplets.4 Due to its sensitivity and ability to readily discriminate multiple components simultaneously, SERRS spectroscopy is a flexible technique for a wide range of analytical and bioanalytical applications.5,6 SERRS detection is of particular interest for use with microfluidic systems such as microdroplets,7−11 cell-trapping arrays,12 and flow-cells,13 and also in combination with novel nanoparticle and nanostructured surfaces.14 Considerable work has also been done on SERRS multiplexing.14−20 Several recent studies address the stability of SERRS probes,21 quantitation of data from SERRS experiments,7,22 and the analysis of multiplexed SERRS data.23 SERRS detection of functionalized nanosensors is increasingly being used in assays of significant biomedical interest, such as cancer tumor detection,24 immunoassays,25 and DNA detection,26,27 as well as in forensic applications such as drug screening.28 SERRS detection has also been applied to assays that previously used fluorescence detection, such as intracellular protein determination,29 and has found recent application in microfluidic channels,30 not least as it has been shown that signal enhancement may occur as a consequence of the advantages afforded by miniaturization.31 Droplets or microemulsions have recently shown significant opportunities in low-volume, high-throughput analysis.32 There is also significant interest in exploring barcoding with microdroplet systems33,34 using optical markers for multiplexed detection. Another particularly important application for © 2011 American Chemical Society

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EXPERIMENTAL SECTION Microfluidic Device Preparation. The upper part of the device was made from poly(dimethylsiloxane) (PDMS) (Sylgard 184, Dow Corning) cast on a silicon master, fabricated using photolithography, etch mask deposition, lift-off, and dry etching. A positive photoresist (AZ4562) layer was spin-coated on to a silicon wafer at 1000 rpm for 1 min, baked for 4 min at 90 °C, exposed for 15 s to UV light at 7.2 mW cm−2 with a Karl Suss MA6 mask aligner, developed in a 1:4 ratio of an AZ400K developer/water mixture, postbaked at 120 °C for 1 h, dryetched in an STS-ICP system, and washed with acetone for the photoresist removal. The master was then silanized with trichloro-(1H,1H,2H,2H-perfluorooctyl)silane (448931, Sigma) to prepare it for PDMS casting. The PDMS, in a mixture of Received: October 12, 2011 Accepted: December 16, 2011 Published: December 16, 2011 1491

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Figure 1. (A) Schematic diagram of microfluidic device layout. The device has three inlets, one for oil and two for aqueous analytes. Droplet formation occurs at the junction between the two inlet channels, and droplets flow toward the storage area via the Raman detection point. (B) Photograph of the device (top) and brightfield image of droplet formation on the device at a flow rate of 0.5 μL/min oil and analytes (lower).

of roughly 67 nm which yields a particle concentration of ∼1010 particles/mL. Colloidal aggregation state was monitored by UV−vis spectroscopy to ensure that aggregation did not change significantly during analysis (see Supporting Information Figure SI-1). It is known that large changes in the aggregation state of the colloid can lead to significant variation in the SERRS enhancement and hence SERRS signal for a given concentration of analyte.37 Solutions of SERRS dyes crystal violet (CV) and rhodamine 6G (R6G) were prepared as stock solutions (5 × 10−4 and 3 × 10−5 M, respectively). Initial analyte concentrations were selected so as to yield roughly equivalent Raman signal intensities in the spectral region being monitored (∼1500−1700 cm−1) under the experimental conditions being used. An amount of 1 mL of analyte was added to 1 mL of colloidal solution prior to introduction in the microfluidic device, yielding final analyte concentrations within the syringe pump in the nanomolar range. SERRS dyes were loaded onto the microfluidic device at a flow rate of between 0 and 0.5 mL/min, and droplets with an approximately volume of ∼500 pL were produced, such that each droplet contained roughly 10 amol of analyte. Instrumental Control. Pump control was performed by an algorithm created using the LabVIEW 8.5 graphical programming language (National Instruments Ltd.) The program also provides basic control of the instrument acquisition. The front panel of the software is shown in Supporting Information Figure SI-2 and describes the basic functions of the pump control algorithm. Liquid flows are delivered to the microdroplet device via high-quality and high-accuracy laboratory syringes (Hamilton). One syringe contained oil for the continuous phase, and two syringes were required (one per analyte) for the analyte−colloid mixtures. All syringes were controlled by NE-500 series syringe pumps (New Era Pump Systems Inc.). Raman Microspectroscopy Measurements. All Raman spectra were acquired with a LabRam inverted microscope spectrometer, manufactured by Jobin Yvon Ltd. The spectrometer was equipped with a 533 nm laser (the power

monomer and catalyst in the ratio 10:1, was poured on the silicon wafer and degassed in a desiccator chamber to remove air bubbles. This was followed by a curing step at 70 °C for 12 h, prior to release from the master. Fluidic inlets were mechanically formed, and the chip was bonded to a glass slide and treated with a hydrophobic reagent (Aquapel). The microchannel connections from the chip were made using small glass capillaries (TSP 320450, Polymicro Technologies) 1.5 cm in length inserted in poly(tetrafluoroethylene) (PTFE) tubing (06417−11, Cole-Parmer) and directly connected to 1 mL syringes. Droplet Generation. Droplet formation in the microfluidic channels used independently controlled flows of two immiscible liquids from syringes pumps, imposing constant volumetric flow rates for both liquid phases. The geometry of the microchannel junction and the relative flow rates of the two phases create a competition between capillary and surface forces, which determines the rate of droplet generation at the point where the two immiscible phases meet. The oil used for the continuous phase was FC40 (3M) with 2% (w/w) surfactant (RainDance Technologies, Inc.). As stated, the droplet-based microfluidic device was designed and fabricated using soft lithographic techniques. A technical drawing of the device is presented in Figure 1A. Channel 1 is used for the delivery of the oil phase while channels 2 and 3 were used for the delivery of the analytes (in this case, two different SERRS dyes premixed with a silver colloid solution). Each channel contains a filter that traps small debris which could otherwise obstruct the channels. Detail of the T-junction where the droplets are formed is also shown in Figure 1A. The T-junction is made by two perpendicular channels 60 and 70 μm wide and 50 μm high. The volume of the microdroplets depends on the flow rates used as well as the dimensions of the channels, and in this case, droplet volume was calculated to be approximately 500 pL. Nanoparticle Preparation. Silver colloids were prepared using a method described by Leopold and Lendl,36 generating colloidal nanoparticle suspensions with an average particle size 1492

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at the sample was ca. 5 mW), true confocal optics, a holographic transmission grating, and a charge-coupled device (CCD) detector. The instrument included a precision motorized x, y, z sample stage for automated mapping at spatial resolution better than 1 μm in the x, y plane and ∼2 μm depth resolution. LabSpec 5 was used for all data processing. In this study, a 100× objective lens (N.A. = 1.25) was used (U Plan FL, Nikon, Japan). This objective lens was mounted on a PI721.10 piezo actuator (Physik Instrumente, Germany). A grating with 600 grooves mm−1, a confocal aperture of 300 μm, and an entrance slit of 150 μm were selected for all experiments. The Raman spectrometer wavelength range was calibrated using the center frequency of the silicon band from a silicon sample (520.2 cm−1). LabSpec 5’s “Swift” mapping algorithm was employed to execute acquisition times required to collect SERRS spectra from moving microdroplets. Polynomial line fitting correction was used to remove the baseline from the spectra.

Figure 2. Chemical structure and Raman (SERRS) spectra of reporter molecules rhodamine 6G (R6G) and crystal violet (CV). Characteristic marker peaks for each analyte are marked (see Supporting Information Figure SI-3 for full spectra).

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RESULTS AND DISCUSSION Sensor Platform Design and Operation. The sensor platform comprises a microdroplet device (Figure 1) with two analyte inlets, each connected to a pump operating under LabVIEW (National Instruments Ltd.) control. Microdroplets were interrogated by Raman microscopy, generating highthroughput, real-time data from the platform. As stated, the flow rate of both pumps was controlled by a programmable pump control algorithm created using the commercially available software utility, LabVIEW, allowing for the generation of a gradient of concentrations between successive droplets. The software developed here (described in Supporting Information Figure SI-2) provides automated control to simulate typical conditions of analyte mixing processes involving liquid flows, such as titrations. Computer-controlled microfluidic platforms such as that demonstrated here improve the reliability of data acquisition and create scalable test environments. Figure 1A (top section) is a schematic diagram of the microfluidic device, comprising three inlets, one for the carrier oil (continuous phase) required for droplet formation (channel 1) and two for the analytes which form the aqueous contents of the microdroplets. The two analyte channels merge and connect with the oil flow channel at a T-junction (Figure 1A, lower section), where the microdroplets form with dimensions and at a rate dependent on the selected flow rates of the oil and the combined analyte flows. Figure 1B shows an example of the devices used in this work (top) and a brightfield microscope image of microdroplet formation in the main channel of the device. Droplets are approximately 100 μm in length and are generated at a rate of ∼4 droplets/s. The microdroplets generated in the channel subsequently flow into a droplet storage area on the device where they remain stable for several hours.38 The basic functions of the pump control software are presented in the Supporting Information. The software allows for up to two individual syringe pumps to be controlled simultaneously. The flow rate of each pump can be changed by a defined amount over a defined time period, allowing for the generation of gradients. Real-Time SERRS Detection in Microdroplets. Figure 2 shows the chemical structure and characteristic Raman spectra of two strongly SERRS-active dyes, CV and R6G, used in this work. The Raman band at 1653 cm−1 is used to identify R6G in

multiplexed spectra, whereas the Raman band at 1617 cm−1 is used to identify CV within mixtures. Figure 3 shows the result of fast SERRS detection of flowing microdroplets containing R6G-labeled silver (Ag) colloidal

Figure 3. Real-time SERRS detection of flowing microdroplets. The top portion of the figure shows detail from the SERRS real-time acquisition. Each pixel represents one SERRS acquisition of 20 ms each. Each droplet may be profiled 5−10 times, and the gaps between drops are clearly resolved. The lower portion of the figure shows summed spectra revealing the contents of individual microdroplets, in this case silver colloid labeled with rhodamine 6G dye (red). Gaps between droplets show no SERRS signal (black).

nanoparticles in real time. Figure 3 shows the result of real-time SERRS detection of passing microdroplets. The bar at the top of Figure 3 represents a 1 s segment from the real-time acquisition and clearly shows both the individual droplets (red) and the gaps between them (black). Each pixel in the map represents a single acquisition and shows the SERRS intensity at 1653 cm−1, the marker peak for R6G as shown in Figure 2. The flow rate of the analyte was selected at 0.5 μL/min in order to produce a new droplet (ca. 500 pL) approximately every quarter of a second, such that approximately four microdroplets were detected per second. The spectra shown in the lower portion of Figure 3 are the averaged SERRS spectra from the sum window within an individual droplet (red trace) and from a gap between droplets (black trace). 1493

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Multiplexed Gradient Detection in Individual Microdroplets. Figure 4 shows the SERRS spectra obtained from a

Figure 4. SERRS spectra obtained from droplets during the titration experiment performed on-chip over time. The concentration of rhodamine 6G (red) is gradually increased over time while the concentration of crystal violet (blue) falls. The intensity at ∼1617 cm−1 (from crystal violet) is strong in earlier droplets and decreases over time, while the intensity at ∼1653 cm−1 (rhodamine 6G) increases steadily and is most evident in later droplets.

Figure 5. SERRS measurements of individual microdroplets revealing the changing composition of the analyte mixture over time. Left: SERRS maps of individual droplets were measured at different time points throughout the titration. Each droplet was samples ca. eight times. Each pixel represents a single SERRS acquisition. Right: the averaged SERRS spectrum from each droplet.

train of successive droplets where the concentration of two analytes is varied incrementally over time, creating a gradient. As stated, CV and R6G were premixed with surface-enhancing silver (Ag) colloid solution. These dyes were used because they give very strong Raman signals, even at the very low concentrations and in the very short time periods required for real-time microdroplet Raman measurements (in this case, ca. 20 ms per acquisition). Microdroplets were sampled ∼1 mm downstream of the droplet formation region (see Figure 1) to ensure that individual droplets were fully formed and that the analytes were properly mixed inside the droplets before SERRS detection.39 The flow rate of CV was initially 0.5 μL/min and gradually lowered to almost zero (±0.01 μL per 6 s), whereas R6G was initially almost zero and gradually raised to 0.5 μL/ min at precisely the same rate. The combined flow rate of both pumps was held constant at ca. 0.5 μL/min to ensure a stable microdroplet generation rate (see Supporting Information Figure SI-4). Over the course of the titration, the signal from R6G (at 1653 cm−1) was observed to increase, whereas the intensity at 1617 cm−1 reduced at the same rate. Figure 4 shows the actual Raman (SERRS) spectra collected from the individual microdroplets sampled at different time intervals. Figure 5 shows the SERRS maps obtained from individual microdroplets at various time points throughout the titration. Each pixel in the SERRS maps represents a single Raman acquisition. Both reporter peaks are being detected simultaneously, with the 1617 cm−1 peak (of CV) contributing to the blue color of each pixel and the 1653 cm−1 (of R6G) responsible for the red color. As the gradient forms inside the droplets, the hue of the pixels changes from predominantly blue, through purple (a mixture of both hues), and finally toward predominantly red, indicating that the concentration of each dye is gradually changing over time and that this gradient of SERRS dyes can be simultaneously detected inside individual droplets in real time. The averaged SERRS spectrum from each individual droplet is shown on the right for clarity. Figure 6 shows the measured SERRS intensities of both SERRS dyes (CV and R6G) at various times throughout the

Figure 6. SERRS gradient across a succession of microdroplets. CV was monitored by observing the intensity of the 1617 cm−1 Raman band (blue circles/lines). R6G was monitored by observing the 1653 cm−1 Raman band (red circles/lines). Separate intensity scales are used for clarity.

continuous monitoring over the duration of approximately 5 min. The blue circles denote the SERRS intensity of the 1617 cm−1 Raman band, indicating the presence of CV, whereas the red circles and line denote the SERRS intensity of the 1653 cm−1 Raman band, indicating the presence of R6G. At the outset, only CV is detected, but as the flow rates are varied to create a gradient, the intensity of the CV peak is seen to reduce to virtually zero (although some residual signals are visible), whereas the intensity of the R6G peak increases to a maximum by the end of the titration.

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CONCLUSION

We have demonstrated the ability to create and control SERRSdetectable titrations in a high-throughput, microfluidic platform and to monitor variable concentrations of multiple SERRS species in real time within discrete microdroplets. We have demonstrated a novel combination of SERRS multiplexing and 1494

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real-time microdroplet detection. This novel combination of emerging technologies promises a host of useful possible applications in analytical and bioanalytical assays in the future and is of particular usefulness in calibration and standardization of SERRS-based assays. This work represents a novel combination of a variety of techniques, e.g., real-time detection, SERRS multiplexing, and computer-controlled gradient formation inside microdroplets, providing the first complete example of individual microdroplet characterization by SERRS spectroscopy.

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ASSOCIATED CONTENT

S Supporting Information *

Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone: +44 (0)141 330 4931. Fax: +44 (0)141 330 4907. Email: [email protected].

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ACKNOWLEDGMENTS The authors thank Dr. Michele Zagnoni (University of Strathclyde) and Dr. Gurman Pall and Dr. Andrew Glidle (University of Glasgow) for their helpful contributions to this work. This work was funded by RCUK Basic Technology Grant EP/E032745/1. We also acknowledge The School of Engineering for the finding of Ms. Martino.

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