Lab on a Chip PAPER
Cite this: Lab Chip, 2013, 13, 4832
Smartphone quantifies Salmonella from paper microfluidics† Tu San Park, Wenyue Li, Katherine E. McCracken and Jeong-Yeol Yoon* Smartphone-based optical detection is a potentially easy-to-use, handheld, true point-of-care diagnostic tool for the early and rapid detection of pathogens. Paper microfluidics is a low-cost, field-deployable, and easy-to-use alternative to conventional microfluidic devices. Most paper-based microfluidic assays typically utilize dyes or enzyme–substrate binding, while bacterial detection on paper microfluidics is rare. We demonstrate a novel application of smartphone-based detection of Salmonella on paper microfluidics. Each paper microfluidic channel was pre-loaded with anti-Salmonella Typhimurium and anti-Escherichia coli conjugated submicroparticles. Dipping the paper microfluidic device into the Salmonella solutions led to the antibody-conjugated particles that were still confined within the paper fibers to immunoagglutinate. The extent of immunoagglutination was quantified by evaluat-
Received 25th August 2013, Accepted 2nd October 2013 DOI: 10.1039/c3lc50976a www.rsc.org/loc
ing Mie scattering from the digital images taken at an optimized angle and distance with a smartphone. A smartphone application was designed and programmed to allow the user to position the smartphone at an optimized angle and distance from the paper microfluidic device, and a simple image processing algorithm was implemented to calculate and display the bacterial concentration on the smartphone. The detection limit was single-cell-level and the total assay time was less than one minute.
Introduction Optical detection of chemical and biological assays has become very popular due to its superior sensitivity. It requires a light source and a light detector, and is typically performed with a spectrophotometer (including a fluorometer), often in conjunction with the use of optical fibers.1 Modern smartphones do possess both a light source (a “white” LED used as a camera flash) and a light detector (a digital camera). The white LEDs in many smartphones are very bright, offering sufficient light intensity for use as a light source for optical detection. The resolution and sensitivity of the smartphone's digital camera have already surpassed those of stand-alone, compact digital cameras. Since the smartphone serves as the primary user interface for detection, the overall time for someone to become familiar with the experimental setup is minimized, and the total cost of the system is greatly reduced from that of current detection methods. In addition, utilizing a smartphone as the primary sensing element allows it to serve as a true point-of-care diagnostic tool for the early and rapid detection of pathogens.2–6
Department of Agricultural & Biosystems Engineering, The University of Arizona, Tucson, AZ 85721, USA. E-mail:
[email protected]; Tel: +1 520 62103587 † Electronic supplementary information (ESI) available. See DOI: 10.1039/ c3lc50976a
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Paper microfluidics has gained great popularity in recent years due to its potential as a low-cost, field-deployable, and easy-to-use alternative to conventional microfluidic devices. Pattern transfer has been greatly simplified over the conventional photo- or soft lithographic techniques, utilizing either photoresists7 or wax printing.8 Many different chemical and biological assays have been performed using paper microfluidics. Paper microfluidics has been used for detecting glucose,8–11 protein (albumin),8,9 cholesterol,8,11 lactate,11 alcohol,11 enzymes (transaminase12 and galactosidase13), and heavy metals,10 and they have also been used as a platform for ELISA.14 Most of those applications were based on optical8,9,12–14 and electrochemical10,11 detection methods, which rely on chemiluminescent and enzymatic redox reactions. Although these results can be considered promising, colorimetric (or sometimes electrochemical) signals from these assays can be interfered with by inhomogeneous paper fibers, leading to inferior specificity and sensitivity. More sophisticated paper microfluidic devices have recently emerged, such as a galvanic cell-integrated self-powered system13 or 3-D paper microfluidics.15–17 However, the use of paper microfluidics for antibody-based identification/ quantification of pathogens is rare. Bacteria and viruses are much larger and more complex than most analytes tested using paper microfluidics.8–14 In addition, the sample matrices for such pathogenic detection, including human blood, food samples, and tissue culture media, can create substantial background signals (noise) in both optical and electrochemical
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Lab on a Chip detection. When these complicated analytes and sample matrices are assayed on paper, which is essentially a nonhomogeneous medium of cellulose fibers, detection becomes even more challenging. The use of smartphones, however, may suppress this nonhomogeneity issue with the paper medium, since its light detector (digital camera) is an imaging device. Non-uniform optical signals from non-homogeneous cellulose fibers can be averaged out over a substantial area. In addition, the signal fluctuations over a range of wavelengths can also be averaged out when a white LED or white ambient light is used, which is not possible with conventional spectrophotometric analyses. To benefit from this, we should utilize neither fluorescent nor chemiluminescent detection, which are highly wavelength- (or color-) dependent. Higher sensitivity in detection is possible with Mie scatter detection, which is less dependent on wavelength compared with fluorescence or chemiluminescence. To this end, we propose to use Mie scattering as our detection modality, which is highly angle-dependent but less wavelength-dependent than other optical detection methods. Light scattering from the particles follows the Mie solution to Maxwell's equations when the particle size is comparable or larger than the wavelength of incident light. Mie scattering assumes that a single particle can scatter from multiple points, and that these different scattering centers can both constructively and destructively interfere with each other, leading to non-symmetric angular dependence of the scattered intensity for large particles.18 When the Mie scattering intensity is plotted against the scattering angle (from 0° to 180°), multiple sharp peaks can be observed.18 Since the locations of those peaks vary by the materials used, it becomes possible to distinguish the scattering signal of the target from those of surrounding material (directly reflected light, background scatter, etc.) at a certain optimized angle of detection. To further improve the sensitivity, one can use submicron latex particles that emit “white” scattering, which are covalently conjugated with the antibodies corresponding to the pathogens. Antibody–antigen binding in paper microfluidics will trigger the immunoagglutination of the latex particles,18–20 which will greatly augment the extent of Mie scattering at a certain specific angle of detection.21–23 In this work, we will develop single-channel and multichannel paper microfluidic devices, pre-loaded with antibodyconjugated latex particles and subsequently dry them out before the assays. Dipping the paper microfluidic device into the serially diluted solutions of Salmonella will trigger the capillary flow of the sample solution through the channels. We will aim to maximize the effects of filtration (for big bacterial colonies and sample matrices) and the confinement of latex particles by the paper fibers. Other physical and chemical parameters of papers and reagents will be evaluated as well. Mie scattering detection will be initially made using the “bench-top” apparatus, consisting of micro-positioning stages, an LED light source (monochromatic), a miniature spectrometer, and a pair of optical fibers, to determine the
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Paper optimum angle and scattering detection. These experiments will be repeated using smartphones, to find out whether a “white” LED flash and a digital camera can replace the monochromatic LED light source and the miniature spectrometer in quantifying the extent of Mie scatter. Multichannel paper microfluidics will also be tested, especially for multiplex assays or specificity assessments. Finally, a smartphone application will be programmed and tested, to allow the user to position the smartphone at an optimized angle and distance from the paper microfluidic device, eliminating the need for micro-positioning stages, and to display the bacterial concentration on its display through the implementation of a simple image processing algorithm. We aim to demonstrate an extremely low detection limit, preferably at the singlecell-level, and a wide linear range of the assay (5–6 orders of magnitude).
Materials and methods Salmonella and E. coli samples Salmonella Typhimurium Z005 strain (ZeptoMetrix, NY, USA) and Escherichia coli K12 lyophilized cell powder (Sigma-Aldrich, MO, USA) were incubated with 25 mg mL−1 brain heart infusion broth (Remel, KS, USA) for 12 hours at 37 °C. These fully cultured bacteria samples (108 CFU mL−1) were serially diluted in 0.5 mM pH 7.4 phosphate buffered saline (PBS). A 1% solution of Tween 80 was added to each diluted solution to lyse the bacterial membrane, and samples were then refrigerated. All deionized water used in this study was processed with a Simplicity® water purification system (EMD Millipore Corp., Billerica, MA, USA), with 18 MΩ cm resistivity. Antibody conjugated polystyrene submicroparticles Highly carboxylated polystyrene latex particles with a diameter of 920 nm (Bangs Laboratories, IN, USA) were used as the agglutination substrate.24,25 The particles were first washed twice with activation buffer, 50 mM 2-(N-morpholino)ethanesulfonic acid (MES; Sigma-Aldrich) at pH 6.0. A centrifuge (VWR, PA, USA) was used for all washing processes for 15 minutes at 9900g. The particles were then mixed with water-soluble carbodiimide (Sigma-Aldrich) at room temperature for 15 minutes and washed twice with coupling buffer, 50 mM pH 7.4 PBS. Rabbit polyclonal antibodies to the Salmonella Typhimurium antigens (Abcam, MA, USA) and goat polyclonal antibodies to the E. coli antigens (Meridian Life Sciences, ME, USA) were added to each separate suspension at an appropriate concentration to yield 100% surface coverage of antibodies on the particles.24 The resulting solutions were slowly rocked overnight at 4 °C, and were then washed three times with PBS, followed by mixing with a quenching solution of 40 mM hydroxylamine (Sigma-Aldrich). Finally, particles were stored in a storage buffer, PBS–BN (PBS at pH 7.4 with 1% bovine serum albumin, BSA, and 0.05% sodium azide). For a negative control, the particles were conjugated with BSA according to the same aforementioned protocol with 33%
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Paper coverage of the particle surface.21 Particles were refrigerated until use. Fabrication of paper microfluidics Paper microfluidic channels were fabricated on cellulose chromatography paper (GE Healthcare, Springfield Mill, UK) using SU-8 negative photoresist (Microchem, MA, USA), diluted with negative resist thinner I (Sigma-Aldrich) in 2 to 1 ratio. A mask having a rectangular sample inlet, a 10 mm long channel, and a round absorbent pad (Fig. 1a) was printed on transparency film using a laser printer. The paper was first saturated with the photoresist solution, and was then dried above a hot plate at 85 °C and UV-exposed for 3 minutes on each side using the aforementioned mask. Sequential acetone and isopropyl alcohol rinsing stages were used for developing the pattern.7 The resulting channel was SU-8-free and hydrophilic, allowing the sample to spontaneously flow by capillary action. A benchtop system for optimizing Mie scatter detection Positioning stages (Edmund Optics, NJ, USA) with a pair of optical fibers (Ocean Optics, FL, USA) were designed and assembled to expose the paper microfluidic device at varying angles of incident and detection light.2 A static optical fiber attached to a LED light source (LS-450, Ocean Optics) (λ = 475 nm) irradiated the paper microfluidic device. An ultraviolet–visible miniature fiber optic spectrometer (USB4000, Ocean Optics) measured light intensities between 20° and 90° from the paper microfluidic channel, while the paper microfluidic device was rotated between 90° and 150° from the incident light, in 5° intervals of each angle. AntiSalmonella conjugated polystyrene submicroparticles were loaded at the center of the paper microfluidic channel
Lab on a Chip (Fig. 1a), and deionized water was provided at the sample inlet to keep the channel wet. The light scatter intensities were measured from the paper microfluidic device and this signal was compared with that from the same experiment without the particles loaded on the paper microfluidic device. Mobility of submicroparticles and Salmonella through the paper microfluidic channels To investigate the mobility of submicroparticles through the paper microfluidic channels, the particles were conjugated with methylthymol blue dye (Sigma-Aldrich), using the same protocol used to conjugate antibodies to them. These particles were loaded at the center of a paper channel and deionized water was loaded at the sample inlet. The movement of blue colored particles was observed as soon as the water sample passed through the site of particle loading. Additionally, scanning electron microscopy (Inspect-S Scanning Electron Microscope, FEI, OR, USA) was used to track the movement of particles from the initial loading point at the paper channel. A LIVE/DEAD® cell viability assay reagent (Life Technologies, NY, USA) was added to 105 CFU mL−1 Salmonella sample before it was loaded at the sample inlet of the paper microfluidic device. Confocal fluorescence microscopy (Eclipse C1si Confocal, Nikon Instrument, Tokyo, Japan) was used to track the mobility of the cells. In addition, a Bradford protein assay (Bio-Rad, CA, USA) was conducted using BSA solutions as model antigens, to verify the mobility of antigens through the paper channel. Evaluation of background scatter The uniformity of the chromatography paper, used for fabricating paper microfluidics, was analyzed since it might affect the scatter signals from the background. The effects of dried PBS and dried Tween 80 were also analyzed towards light scatter signals. Plain, PBS-loaded and Tween 80-loaded paper microfluidic devices were mounted on the benchtop system with the optimized Mie scattering angle, and scatter intensities were measured throughout the entire channel. SEM was also used to characterize these paper microfluidic devices under different treatment conditions. Salmonella detection on a spectrometric benchtop system
Fig. 1 Optimization of Mie scatter detection using a spectrometric benchtop system. (a) Photograph of a single-channel paper microfluidic device. (b) Benchtop apparatus for optimizing the angles for Mie scatter detection from paper microfluidics. (c) Definition of the angles for light irradiation and scattering detection. (d) Contour plot of difference in scatter intensities with and without particles vs. the angles of light irradiation and scattering detection.
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Each different Salmonella sample (101–105 CFU mL−1) or deionized water (as control) was mixed with anti-Salmonella conjugated particles and loaded at the center of the paper microfluidic channel. This is “pre-mixing”, indicating that immunoagglutination occurs before loading into the paper microfluidic device. The light scatter intensity from each target concentration was analyzed on the benchtop system with the spectrometer at the optimized Mie scatter angle. These results were examined and compared to Mie scattering simulations, which used the following parameters: the particle diameter, the refractive index of the medium (in this case, the cellulose fiber of paper), the real and imaginary refractive
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Lab on a Chip indices of particles, the wavelength of the incident light, and the concentration of the suspension.24,26 A standard curve of measurements for known Salmonella concentrations was produced using the spectrometer on the benchtop system. These were prepared by loading 3 μL and 4.5 μL of anti-Salmonella conjugated particles at the center of paper microfluidic channels for low- and high-concentration measurements, respectively. Serially diluted Salmonella samples and deionized water (as a negative control) were used for assays. After particles were loaded, the dried paper microfluidic device was mounted on the benchtop system and SpectraSuite software (Ocean Optics) was used to record the light scatter intensity at 475 nm wavelength from the center of the paper microfluidic channel. Before the sample solution reached the central zone where the particles were loaded, the scatter intensity was recorded (“background” signal). The scatter intensity dropped substantially upon the arrival of the sample solution, and the plateau signal was recorded (“sample” signal). The “sample” signal was divided by the “background” signal to cancel out the difference between paper microfluidics (normalized scatter intensity or I). The same experiments were performed with the negative control solution (normalized negative control scatter intensity, or I0). A series of I/I0 against varying concentrations of Salmonella were obtained to construct a standard curve. All ambient light was turned off during these experiments. Salmonella detection on a smartphone benchtop system To find out whether a “white” light source and a digital camera can replace the monochromatic LED and the spectrometer for Mie scatter detection, two iPhone 4 (Apple, CA, USA) smartphones were mounted to the same benchtop system, where the flash of one smartphone was used as a continuous, “white” light source and the digital camera of the other was used as an image detector. Supports for precisely attaching each smartphone to the benchtop system were designed using AutoCAD 2000i (Autodesk, CA, USA) and were then stereo-lithographically printed using an uPrint 3D printer (Stratasys, MN, USA). Using this benchtop system with smartphones, standard curves were again constructed using the same method described in the previous section. Measurements of scatter intensities were replaced with taking digital images 30 seconds after the sample was loaded at the sample inlet of the paper microfluidic device. All images were taken in auto-exposure/ auto-focus mode. These images were then analyzed using a program coded in MATLAB R2010a (MathWorks, MA, USA). The code algorithm converted the color image to a green image, recognized the channel region, divided the channel area into three sections along the direction of flow, and finally calculated the average intensity of the second (central) region. I/I0 and the standard curve were evaluated in the same manner as described in the previous section. Crossreactivity of Salmonella to anti-E. coli conjugated particles was also tested with this system for low (102 CFU mL−1) and high (105 CFU mL−1) concentrations of Salmonella samples.
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Paper Direct detection under ambient light with smartphone application The final system was designed to use a single smartphone and a multi-channel paper microfluidic device under ambient light, without the need for micro-positioning stages. To this end, a smartphone application was programmed using Xcode (Apple, CA, USA), to allow the user to position the smartphone at an optimized angle and distance from the paper microfluidic device (eliminating the need for micropositioning stages) and to display the bacterial concentration on its display through implementing a simple image processing algorithm. A five-channel paper microfluidic device was fabricated, where each channel corresponded to low and high concentrations of Salmonella measurements, low and high concentrations of E. coli measurements, and a negative control. 3 or 4.5 μL of each anti-Salmonella or anti-E. coli-conjugated particles was loaded into each channel. To eliminate the need for a separate negative control (deionized water), BSA conjugated particles were loaded into the negative control channel, which should not immunoagglutinate upon mixing with Salmonella solutions.
Results and discussion Can we detect submicroparticles on paper? Fig. 1a shows the shape and dimensions of a microfluidic channel fabricated on paper. Antibody- or BSA-conjugated particles were loaded at the center of each channel. The absorbent pad is a circular area that allows the sample to flow continuously from the inlet and through the channel until the absorbent pad is filled. Without this absorbent pad, a sample would cease to flow as soon as the channel was filled with the sample, and the channel would need to be substantially longer. Fig. 1b shows a benchtop system for optimizing Mie scatter detection. Light scatter intensities were measured while changing the angle of incident light to paper (angle a in Fig. 1c) and the angle of light scatter from paper (angle b in Fig. 1c). Both angles were modified through adjusting the positions of a paper microfluidic device and an optical fiber for scatter detection, while the optical fiber for incident light was stationary. Light scatter intensities were evaluated at each angle combination, using the paper microfluidic device, with and without particles. This was used to determine the optimum detection angles that would provide maximum scatter signal from the submicroparticles and minimum signal from the paper background. Fig. 1d presents these results as a contour plot, where each data point represents the scatter intensity difference between the wet paper microfluidic device with and without particles. Maximum differences in scatter intensities were found at a = 125° and b = 60°, followed by a = 125° and b = 30°. The peak at a = 125° and b = 30° is very sharp, indicating that this angle combination may be very vulnerable to the small shift in angles. The other peak at a = 125° and b = 60°, which we determined as the optimum angles to be used, is more gradual and broader.
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Paper Can submicroparticles and Salmonella cells travel through the paper microfluidic device? Methylthymol blue-conjugated submicroparticles were loaded on the paper microfluidic device and deionized water was provided at the sample inlet to generate the capillary flow. As shown in Fig. 2a, the dye-conjugated particles (blue color) showed no evidence of traveling through the channel. Scanning electron microscopy (SEM) was additionally performed to further confirm this relative “confinement” of submicroparticles, as well as their ability to immunoagglutinate within paper fibers. Fig. 2b shows the boundary between the paper channel (left) and the photoresist layer (right), in which the pores between the cellulose fibers have been filled with photoresist materials. Fig. 2c and d show the SEM images around the particleloaded channel. Many particles, mostly immunoagglutinated, could be found where the particles were initially loaded (Fig. 2d), whereas almost none could be seen right above that zone (Fig. 2c). Cellulose fibers in paper were assumed to not only function as a barrier to the movement of submicroparticles but also provide sufficient space for antigen–antibody binding to occur, thus leading to immunoagglutination. In this
Lab on a Chip manner, particles were not lost during the laminar flow and they were available for immunoagglutination. Next, a LIVE/DEAD® cell viability assay reagent was added to the paper microfluidic device, where 105 CFU mL−1 (colony forming units per mL) of Salmonella Typhimurium sample was loaded to its sample inlet, to track cell mobility through paper fibers. A confocal fluorescence microscopic image (Fig. 2e) was taken at the border of the sample inlet and the channel after the sample filled the channel. The bright green area of the image shows where live cells are located in the sample inlet, indicating that bacterial cells and colonies have some difficulty in moving through the paper. This difficulty may not be of importance, provided that the antigens from bacteria can travel through the paper, since immunoagglutination is caused largely by free antigens and cell fragments.19 To this end, bovine serum albumin (BSA) solutions stained with the Bradford assay reagent (blue color) were loaded at the sample inlets of the paper microfluidic device. Four different concentrations (1000, 500, 75, and 25 μg mL−1) of stained BSA were tested. As shown in Fig. 2f, BSA was able to fill the channel rapidly (in 1 minute), indicating that free antigens would travel through the paper without any difficulty. Since the Tween 80 surfactant was added to Salmonella solutions before the experiments, most bacteria were lysed into cell fragments or free antigens, and thus were able to travel through the paper channel and immunoagglutinate with antibody-conjugated particles.
Effects of paper inhomogeneity, PBS, and Tween 80 Paper inhomogeneity may affect light scatter intensity on a location-to-location and paper-to-paper basis. Therefore, the scatter intensities across the entire paper channel were analyzed (Fig. 3a) using the benchtop system (Fig. 1b). The average signal standard deviation throughout each channel was
Fig. 2 Behavior of submicroparticles, cells and proteins on paper microfluidics. (a) SEM images of the border between the photoresist layer and the paper channel. (b) Image of the paper microfluidic device loaded with the dye-conjugated particles at the center of the channel, with deionized water loaded at the bottom sample inlet. Almost no antibody-conjugated particles were found away from the central particle loading point (c), while immunoagglutinated particles were found to be con® fined at this loading point (d). (e) Confocal microscopic image of LIVE/DEAD cell viability assay for Salmonella on paper microfluidics. (f) A photograph of the paper microfluidic device loaded with Bradford-stained BSA (concentrations of 1000, 500, −1 75, and 25 μg mL , from left to right) for validating the flow of proteins through paper microfluidic channels.
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Fig. 3 Factors affecting light scatter intensities from paper microfluidics. Light scatter intensities were measured throughout the dried paper microfluidic channels after loading with (a) deionized water, (b) different concentrations of PBS, and (c) different concentrations of Tween 80 solutions. (d) SEM images of paper channels loaded with 1) deionized water, 2) 50 mM of PBS, 3) and 1% Tween 80 solution.
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Lab on a Chip 5% of their mean values, but the chip-to-chip variation was much higher. Therefore, all light scatter intensities were divided by the “background” signal from each channel to compensate for this chip-to-chip variation. Next, the effects of crystallization of solutes on light scattering were examined along the paper fibers. Anti-Salmonella conjugated particles were suspended in a 50 mM phosphate buffered saline (PBS) solution at the final step of the conjugation process. This particle suspension was loaded on the paper channels and dried. Upon drying, PBS tended to form crystals on the paper fibers. Channel regions a, b, and c in Fig. 3b were loaded with 0.5, 5, and 50 mM PBS solutions, respectively, and dried. Higher concentrations of PBS corresponded to more light scattering (b = 7% and c = 14% higher than a) with bigger fluctuations. This increase and fluctuation in scatter intensity may lead to false-positive results and/or compromise the sensitivity of the assay. The effect of Tween 80 was also tested. Tween 80 was added to the Salmonella samples to lyse the bacterial cell membranes to facilitate the movement of target antigens through the paper channel. Tween 80 can also be added to antibody-conjugated particles to stabilize the particle suspension and facilitate chemical agitation.21 However, since the particle suspension must be dried on the paper, Tween 80 may undergo the same problem as that of PBS. Fig. 3c indicates the regions where 0.1, 0.2, and 1% Tween 80 solutions were loaded and dried. Huge fluctuations in light scatter intensities were observed: the average signal standard deviation was 13% of their mean values, indicating substantial signal fluctuation in overall scatter intensity. This signal variance would also contribute to the higher level of background noise, in much the same way as PBS. SEM was used for visualizing the structural differences between dried PBS and dried Tween 80 on paper. Fig. 3d presents these images of a paper channel with dried distilled water (d1), dried 50 mM PBS (d2), and dried 1% Tween 80 (d3). In Fig. 3d2, crystals of PBS are seen around the paper fibers. In Fig. 3d3, small kernels of Tween 80 are seen on the surface of the paper fibers. Signal variances with dried PBS (14%) and dried Tween 80 (13%) were much greater than that with deionized water (5%). Since light scatter data from the dried channel were required for background normalization, neither PBS nor Tween 80 should be pre-loaded on the paper channel. Therefore, during the final step of preparing antibodyconjugated particles, deionized water was used for washing and storing. Tween 80 was still added to the Salmonella samples before the assay, but not for the pre-loaded particles on the paper channel. Salmonella detection on a spectrometric benchtop system Initially, the assays were performed by premixing an equal volume of anti-Salmonella-conjugated microparticle suspension in deionized water and each serially diluted Salmonella sample, without pre-loading and drying the particles on the
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Paper paper microfluidic device, for the purpose of simplification. 10 μL of each mixture was applied to the paper microfluidic channel. The light scatter intensities before and after such loading were measured using the spectrometric benchtop system (Fig. 1b). As the target molecules were mixed with the antibody-conjugated particles, immunoagglutination occurred, leading to an increase in the effective diameter and the change in the morphology of the particles. These changes lead to the changes in light scatter intensities. Fig. 4a presents the normalized light scatter intensities over the Salmonella concentrations. The produced curve shows an increase to maximum intensity at 10 CFU mL−1 followed by a dip at 102 CFU mL−1, and a further increase to 104 CFU mL−1 followed by saturation. For all data points, 95% confidence intervals (= mean ± 1.96 × standard error) are all higher than 1, indicating that the lower limit of detection is 10 CFU mL−1. This dip in scattering intensity is purely an optical phenomenon, characteristic of Mie scatter, as has been previously investigated by Mie scatter simulation and subsequent experimental validations (Fig. 4b).24,25 This dip in the standard curve causes a problem in correctly estimating the target concentration. Our approach is to extend the initial linear range (0–101 CFU mL−1 in Fig. 4a) by reducing the amount of antibody-conjugated particles, and shift the second linear range (102–104 CFU mL−1) to a higher concentration range by increasing the amount of antibody-conjugated particles. This approach requires two different sets of experiments. Therefore, a multi-channel microfluidic device was chosen as a solution, with different amounts of particles loaded in separate
Fig. 4 Salmonella detection with a spectrometric benchtop system with premixing (a) or microfluidic mixing (c and d). (a) Normalized light scatter intensities over Salmonella target concentrations using the benchtop apparatus, where the pre-mixed solution of Salmonella and antibody-conjugated particles were loaded directly into each channel. (b) Simulated light scatter characteristics as the effective particle size grows through immunoagglutination. (c) Standard curve of the normalized light scatter intensities over the Salmonella target concentrations using the benchtop apparatus optimized for the low concentrations of Salmonella, where the antibody-conjugated particles were pre-loaded into each channel and subsequently dried, followed by introducing Salmonella solutions into the bottom inlet. (d) The same experiment optimized for the high concentrations of Salmonella. All data points are the average of three different experiments (each time with a different paper microfluidic device). Error bars are standard errors.
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Paper channels. 3 and 4.5 μL were experimentally selected for low and high concentrations of the target, respectively. This time, the paper microfluidic device was pre-loaded with the particles in each channel, and subsequently dried, followed by the introduction of Salmonella solution to the sample inlet. A standard curve was produced for each channel. The standard curve of the low-range concentration of the target (Fig. 4c) had an increase in signal from 0 to 103 CFU mL−1, and then started to decrease according to the aforementioned optical dip, extending the linear range by one order of magnitude. This time, the lower limit of detection is 102 CFU mL−1, presumably due to the reduced amount of antibodies. Considering the sample volume, 10 μL, this is equivalent to single-cell-level detection. The standard curve of the high-range concentration of the target (Fig. 4d) showed no significant increase in signal up to 103 CFU mL−1, followed by a steep increase towards 105 CFU mL−1. In both cases, the signals (I/I0) were much larger (~1.4 in Fig. 4c and ~1.8 in Fig. 4d) than those with pre-mixed samples (~1.13 in Fig. 4a). This trend is similar to our previous work:23 the microfluidic mixing of the separately-loaded sample and particle suspension resulted in a much higher change in scatter intensities, while the pre-mixed sample and particles generated a very small change in scatter intensities. Correct measurement was possible from 101 to 105 CFU mL−1 of Salmonella Typhimurium. Salmonella detection on a smartphone benchtop system The standard curve was produced again, this time using two smartphones (iPhone 4) on a benchtop system, one as a light source (utilizing its white LED flash) and the other as a detector (utilizing its digital camera) (Fig. 5a). This setup is obviously an intermediate version between the previous spectrometric benchtop system and the final direct detection with smartphone application. We wanted to make sure
Lab on a Chip whether the changes in light source (from the monochromatic LED to the white LED flash) and light detector (from the spectrometer at 16-bit resolution at a fixed wavelength to the digital camera at 8-bit resolution of one color over a range of wavelengths) did not compromise Salmonella detection under the identical micro-positioning stage setup. The orientation angles of each component relative to the paper channel were the same as found using the spectrometric benchtop system, which were a = 125° and b = 60°. A paper microfluidic device pre-loaded with anti-Salmonella submicroparticles was prepared using the same method described previously. Images of the dried paper channel were taken in auto-exposure/auto-focus mode before and 30 seconds after a target sample was loaded at the sample inlet. The images were transferred to a personal computer and analyzed using a program coded in MATLAB. The resulting standard curve is shown in Fig. 5b and c, from the low- and high-target concentration channels, respectively. The lower limit of detection is once again 102 CFU mL−1, or single-cell-level considering the sample volume of 10 μL. The standard curve produced from smartphone detection was similar to that produced using a spectrometer, but with a smaller change in scatter intensities up to 1.06, compared to those of a spectrometer up to 1.8. This difference is derived from the unavoidable characteristics of the white LED flash and digital camera of a smartphone, where light irradiation and detection are made not at an optimized wavelength but over a range of wavelengths. However, the error bars are smaller, leading to the same level of linear range and sensitivity as those of spectrometric detection. These smaller error bars can be attributed to the fact that the light scatter intensities were averaged over a substantial area through image detection. In fact, the lower endpoint of 95% confidence interval for 10 CFU mL−1 (Fig. 5b) is barely below 1, potentially indicating the superiority of smartphone-based detection. Cross-reactivity of Salmonella to anti-E. coli was also tested using the same system. Fig. 5d presents the results of measuring Salmonella concentrations of 102 and 105 CFU mL−1, using the channels loaded with both anti-Salmonella conjugated particles and anti-E. coli conjugated particles. The average signal intensity produced by the Salmonella target in the anti-E. coli channel was around 40% of that produced by Salmonella in the anti-Salmonella channel, which is typical of cross-reactivity between Salmonella and anti-E. coli. Through testing the sample with both anti-Salmonella and anti-E. coli, it is possible to distinguish between Salmonella and E. coli, or any other combination of pathogen/antibody that may cross-react. Smartphone application for direct Salmonella detection
Fig. 5 Smartphone detection of Salmonella and cross-reactivity to anti-E. coli. (a) Two smartphones replace the blue LED light source and the spectrometer of the benchtop apparatus. (b–c) Standard curves using dual smartphone detection with the low- and high-concentration channels. (d) Normalized light scatter intensities for evaluating the cross-reactivity of Salmonella to anti-E. coli.
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A smartphone software application was developed to further simplify the above smartphone benchtop system and enable on-board data analysis from a multi-channel paper microfluidic device. The application provided a trapezoidshaped box on the camera screen, prompting the user to fit
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Lab on a Chip the on-screen image of the rectangular paper microfluidic device into the trapezoid box (Fig. 6b). This would position the camera at 65° relative to the paper microfluidic device, which was an optimized angle for Mie scatter detection (angle a − b = 125° − 60° = 65°; from Fig. 1c). Fig. 7a shows the images of the multi-channel paper microfluidic device taken from different angles at the same distance, indicating how the change in detection angle could affect the shapes of trapezoids. Auto-focus and auto-exposure were automatically locked for the paper microfluidic device by pressing the first button on the screen (Fig. 6c). Then, the user was prompted to take the first (reference) image before the assay (Fig. 6d), and the second (signal) image 30 seconds after the sample was loaded (Fig. 6e). As soon as the second image was taken, the application automatically found the detection region of each channel, and calculated the normalized light scatter intensity from the detection site. Using the pre-stored standard curve, the application printed out the target concentration on the smartphone screen (Fig. 6f). The algorithm of this data processing was summarized in the ESI.† Direct Salmonella detection under ambient light with smartphone application Direct Salmonella detection was conducted from a multichannel paper microfluidic device using the developed smartphone application, without using micro-positioning stages or a separate personal computer. After each particle
Paper
Fig. 7 (a) Photographs of the five-channel paper microfluidic device taken at three different angles at the same lateral distance of detection. (b) A standard curve was constructed from the readout of three separate channels using the smartphone application under ambient light.
suspension was loaded on the corresponding channel and dried, assays were conducted to construct a standard curve by using the smartphone application. Fluorescent lamps on the laboratory ceiling (ambient light) were the only light sources used for image acquisition from the paper microfluidic device. Fig. 7b presents the normalized scatter signal plotted over Salmonella concentration from low and high concentration channels. Specifically, 0 CFU mL−1 data were from the control channel, 101 and 102 CFU mL−1 data were from the low concentration channel, and 103, 104 and 105 CFU mL−1 data were from the high concentration channel; all data were plotted into a single graph. The scatter intensity signals were similar to the smartphone benchtop system. The combination of this application and a multi-channel paper microfluidic device will provide cheap, easy, sensitive, and fast detection/quantification of bacteria. Compared to other smartphone-based optical detection techniques,2–6 this system has an advantage in that it does not require any holder for the phone or for the sensor.
Conclusion
Fig. 6 Smartphone application for Salmonella detection from a multi-channel microfluidic device. (a) Launching the application. (b) The user positions the smartphone to fit the image of the paper microfluidic device into the trapezoid box shown on the application screen. (c) Pressing the first button will lock the autofocus/auto-exposure. (d) Taking the reference image. (e) Adding samples to the paper microfluidic device. (f) After taking the signal image, the application will print out the assay result on the screen.
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Smartphone-based detection of Salmonella was successfully demonstrated with a multi-channel paper microfluidic device. The angles of light irradiation and scatter detection with respect to the paper were optimized to maximize the Mie scattering from immunoagglutinated particles and to minimize the background scatter of paper fibers, using the spectrometric benchtop system. Factors interfering with light scattering (inhomogeneous structure of paper, crystallization of PBS and Tween 80) were found, and appropriately compensated for or eliminated. The dip in a standard curve (at 102 CFU mL−1), which is due to light scattering phenomena, was overcome by using a multi-channel paper microfluidic device with different amounts of antibodyconjugated particles loaded to each channel. The detection platform was changed from the monochromatic LED light source and the miniature spectrometer to the white LED flash and the digital camera of a smartphone, and similar results could be obtained. Finally, a smartphone application was developed to eliminate the need for micro-positioning stages (positioning the smartphone at the optimized angle
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Paper and distance was achieved entirely by software) and to analyze the images on-board. The detection limit of the smartphone-based assay on paper microfluidics was 102 CFU mL−1 with a linear range up to 105 CFU mL−1 Salmonella Typhimurium. Considering the volume of the Salmonella solutions used in this study (10 μL), this detection limit corresponds to single-cell-level detection. This is still possible, since this assay detects the presence of free antigens but not the viable cells or its colonies. This impressive performance was made possible simply by dipping the paper microfluidic device into a sample solution followed by photographing with a smartphone, at an optimized angle and distance. No additional equipment is necessary, other than the multi-channel paper microfluidic device (with the reagents pre-loaded and dried) and the application-installed smartphone. Scattering measurements were made right before the assay and 30 seconds after the sample loading, indicating that the total assay time would be less than one minute. This smartphone-based bacterial assay only requires dipping the paper microfluidic device into a sample solution, followed by photographing, with the detection limit being sub-single-cell-level and the total assay time being less than one minute. Although the multi-channel device was used only for specificity assessment, it can be easily adapted for multiplex assays, i.e., assaying for similar strains or groups of bacteria, or even viruses. In fact, the proposed method can be utilized for a wide variety of applications, including food safety, environmental, medical, and veterinary diagnostics, by simply changing the antibodies and re-optimizing the physical and chemical parameters of paper microfluidics. Cellulose fibers in paper can serve as an excellent medium to filter out “big” molecules (e.g. soil particles, tissue fragments, big bacterial colonies, blood cells, etc.) from the sample matrices (e.g. wash water from food, wastewater, whole blood, blood serum, tissue sample, urine, etc.)
Acknowledgements We thank everyone at the Biosensors Laboratory at the University of Arizona, especially Dustin Harshman for engaging in a series of discussions over problems faced during this research, Christopher Fronczek and Scott Angus for training and sharing experiences associated with this work, Jessica Gamboa and Samir Mohandes for SEM imaging, Lily Walsh for experimental assistance, and Soumya Srivastava for the smartphone application programming. This research was supported by a postdoctoral fellowship grant to Tu San Park, from the National Research Foundation of Korea (NRF-2011-357-D00295), and a research grant from the Animal and Plant Quarantine Agency, Korea (C-AD14-2006-11-0). Katherine E. McCracken also acknowledges the partial support from Undergraduate Biology Research Program at the University of Arizona. Scanning electron microscopy and confocal fluorescence microscopy were performed at the W. M. Keck Center for Surface and Interface Imaging Facility at the University of Arizona.
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Notes and references 1 J.-Y. Yoon, Introduction to Biosensors: From Electric Circuits to Immunosensor, Springer, New York, 2013. 2 D. J. You, T. S. Park and J.-Y. Yoon, Biosens. Bioelectron., 2013, 40, 180. 3 O. Mudanyali, S. Dimitrov, U. Sikora, S. Padmanabhan, I. Navruz and A. Ozcan, Lab Chip, 2012, 12, 2678. 4 A. F. Coskun, J. Wong, D. Khodadadi, R. Nagi, A. Tey and A. Ozcan, Lab Chip, 2013, 13, 636. 5 H. Zhu, I. Sencan, J. Wong, S. Dimitrov, D. Tseng, K. Nagashima and A. Ozcan, Lab Chip, 2013, 13, 1282. 6 H. Zhu, U. Sikora and A. Ozcan, Analyst, 2012, 137, 2541. 7 A. W. Martinez, S. T. Phillips, B. J. Wiley, M. Gupta and G. M. Whitesides, Lab Chip, 2008, 8, 2146. 8 E. Carrilho, A. W. Martinez and G. M. Whitesides, Anal. Chem., 2009, 81, 7091. 9 A. W. Martinez, S. T. Phillips, E. Carrilho, S. W. Thomas III, H. Sindi and G. M. Whitesides, Anal. Chem., 2008, 80, 3699. 10 Z. Nie, C. A. Nijhuis, J. Gong, X. Chen, A. Kumachev, A. W. Martinez, M. Narovlyansky and G. M. Whitesides, Lab Chip, 2010, 10, 477. 11 Z. Nie, F. Deiss, X. Liu, O. Akbulut and G. M. Whitesides, Lab Chip, 2010, 10, 3163. 12 N. R. Pollock, J. P. Rollan, S. Kumar, P. D. Beattie, S. Jain, F. Noubary, V. L. Wong, R. A. Pohlmann, U. S. Ryan and G. M. Whitesides, Sci. Transl. Med., 2012, 4, 152ra129. 13 N. K. Thom, K. Yeung, M. B. Pillion and S. T. Phillips, Lab Chip, 2012, 12, 1768. 14 C.-M. Cheng, A. W. Martinez, J. Gong, C. R. Mace, S. T. Phillips, E. Carrilho, K. A. Mirica and G. M. Whitesides, Angew. Chem., Int. Ed., 2010, 122, 4881. 15 A. W. Martinez, S. T. Phillips and G. M. Whitesides, Proc. Natl. Acad. Sci. U. S. A., 2008, 105, 19606. 16 G. G. Lewis, M. J. DiTucci, M. S. Baker and S. T. Phillips, Lab Chip, 2012, 12, 2630. 17 A. W. Martinez, S. T. Philips, E. Carrilho and G. M. Whitesides, Anal. Chem., 2010, 82, 3. 18 S. V. Angus, H.-J. Kwon and J.-Y. Yoon, J. Environ. Monit., 2012, 14, 3295. 19 J.-H. Han, B. C. Heinze and J.-Y. Yoon, Biosens. Bioelectron., 2008, 23, 1303. 20 L. J. Lucas, J.-H. Han and J.-Y. Yoon, Colloids Surf. B, 2006, 49, 106. 21 C. F. Fronczek, D. J. You and J.-Y. Yoon, Biosens. Bioelectron., 2013, 40, 342. 22 D. J. You, K. J. Geshell and J.-Y. Yoon, Biosens. Bioelectron., 2011, 28, 399. 23 B. C. Heinze, J. R. Gamboa, K. Kim, J.-Y. Song and J.-Y. Yoon, Anal. Bioanal. Chem., 2010, 398, 2693. 24 B. C. Heinze and J.-Y. Yoon, Colloids Surf. B, 2011, 85, 168. 25 Bangs Laboratories, Technical Note #204: Adsorption to Microspheres, Bangs Laboratories: Fishers, 2008, (http://www. bangslabs.com/sites/default/files/bangs/docs/pdf/204.pdf). 26 S. Prahl, Mie Scattering Calculator, Oregon Medical Laser Center: Beaverton, 2007, (http://omlc.ogi.edu/calc/mie_calc.html).
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