Technical Note pubs.acs.org/ac
Integrating Biochemiluminescence Detection on Smartphones: Mobile Chemistry Platform for Point-of-Need Analysis Aldo Roda,*,†,‡ Elisa Michelini,†,‡ Luca Cevenini,† Donato Calabria,†,§ Maria Maddalena Calabretta,‡ and Patrizia Simoni∥ †
Department of Chemistry “G. Ciamician”, University of Bologna, Via Selmi 2, Bologna, 40126, Italy INBB, Istituto Nazionale di Biostrutture e Biosistemi, Viale delle Medaglie d’Oro, Roma, 305, Italy § Health Sciences and TechnologiesInterdepartmental Center for Industrial Research (HST−ICIR), University of Bologna, Via Tolara di Sopra, 50 Ozzano dell’Emilia, 40064, Italy ∥ Department of Medical and Surgical Sciences, University of Bologna, Via Massarenti 9, Bologna, 40138, Italy ‡
S Supporting Information *
ABSTRACT: In this paper, we report, for the first time, the use of a smartphone to image and quantify biochemiluminescence coupled biospecific enzymatic reactions to detect analytes in biological fluids. Using low-cost three-dimensional (3D) printing technology, we fabricated a smartphone accessory and a minicartridge for hosting biospecific reactions. As a proof-of-principle, we report two assays: a bioluminescence assay for total bile acids using 3α-hydroxyl steroid dehydrogenase coimmobilized with bacterial luciferase system and a chemiluminescence assay for total cholesterol using cholesterol esterase/cholesterol oxidase coupled with the luminol−H2O2−horseradish peroxidase system. These assays can be performed within 3 min in a very straightforward manner and provided adequate analytical performance for the analysis of total cholesterol in serum (limit of detection (LOD) = 20 mg/dL) and total bile acid in serum and oral fluid (LOD = 0.5 μmol/L) with a reasonable accuracy and precision. Smartphone-based biochemiluminescence detection could be thus applied to a variety of clinical chemistry assays.
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Several examples have been recently reported showing the actual feasibility of using smartphone-based platforms to detect biomarkers and analytes of clinical interest in bodily fluids including sweat, blood, and saliva.3,4 The smartphone camera has been previously used exploiting detection principles such as colorimetric measurements,5−7 fluorescence,8 and label-free formats.9 To the best of our knowledge, biochemiluminescence (BL-CL) has not yet been implemented as detection principle for smartphone-based biosensing. BL-CL is one of the most sensitive tools to improve the analytical performance of bioassays, allowing one to measure down to 10−15−10−18 moles of the target analyte in a small volume or spot.10 We have recently demonstrated the suitability of a portable and compact device, based on the use of a cooled charge-coupled device (CCD), for the detection of proteins down to attomole levels and nucleic acids at femtomole levels. 11 Although their sensitivity is still lower than cooled CCDs,12 back-illuminated complementary metaloxide semiconductors (BI-CMOS) integrated into smartphones
martphones, thanks to their multifunction capabilities, imaging, and computing power, are increasingly playing a pivotal role in recreational activities and healthcare delivery. The built-in functions of smartphones can be further extended through the addition of accessories that enable the smartphone to sense different types of information. Besides, hundreds of new applications (apps) are made available everyday, to respond to the rising needs of end-users. The extensive distribution of smartphones and tablets, together with cloud services ensuring pervasive connectivity, creates an incredible market, largely untapped, especially in the field of healthcare self-management.1 Smartphones can be considered as the natural evolution of point-of-care (POC) analytical devices. As POC devices, smartphones could perform tests outside clinical laboratories, even in low resource settings for critical and emergency medicine. The main advantage in comparison to existing biosensor technologies is the possibility to have an “all-in-one device” that fully exploits the multiple smartphone capabilities. This would eliminate the need for separate devices and, after running the analytical test, processed data could be stored, or sent by E-mail to a physician to properly manage the diagnosis and follow-up, thus facilitating the new approach of “personalized medicine”.2 © 2014 American Chemical Society
Received: June 10, 2014 Accepted: July 14, 2014 Published: July 14, 2014 7299
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Figure 1. (a) Picture of the accessory, (b) picture of the minicartridge, and (c) picture of the accessory snapped into the smartphone. (d) Schematic cutaway drawings of the minicartridge showing the integration of the various components. The transparent ABS optical window (200 μm) of 4 mm diameter allows imaging of biochemiluminescent reaction. (e) Introduction of the minicartridge into the accessory and (f) picture of a representative CL acquisition with the smartphone.
biological fluids such as blood and oral fluid. Using low-cost 3D printing technology17 we fabricated a smartphone accessory and a minicartridge for hosting biospecific reactions. As a proofof-principle we report two assays: an assay for total bile acids (BA) in oral fluid and serum using 3α-hydroxyl steroid dehydrogenase (3α-HSD) co-immobilized with bacterial luciferase system and an assay for serum total cholesterol using cholesterol esterase/cholesterol oxidase in which the produced H2O2 is detected using the CL of the luminol− H2O2−HRP system.
could be suitable for the measurement of analytes present at medium-abundant concentrations (e.g., at micromolar levels) using BL-CL detection. Besides the use of BI-CMOS as luminometer/luminograph does not require any hardware modification, thus being available to a wide range of users. Coupled BL-CL enzymatic reactions have been previously used to increase the sensitivity in comparison to conventional colorimetric substrates. One of the most used CL systems involves the use of oxidase enzymes such as glucose oxidase, cholesterol oxidase, urate oxidase that produce hydrogen peroxide, which, in turn, can be detected by the CL reaction with luminol and enhancers, catalyzed by horseradish peroxidase (HRP).13 As an alternative, dehydrogenases such as glucose, ethanol, and lactate dehydrogenases can been used: the NAD(P) cofactor generates NAD(P)H that will be detected with the bacterial luciferase BL system composed by NADH/FMN oxidoreductase/bacterial luciferase (lux) enzymes.14 In the past, these two coupled enzymatic BL-CL systems have been extensively applied using different analytical configurations spanning from single batch assays to coimmobilized enzymes with flow injection analysis (FIA) or other flow system formats.15,16 In this paper, we report, for the first time, the use of a smartphone to image and quantify biochemiluminescence coupled biospecific enzymatic reactions to detect analytes in
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EXPERIMENTAL SECTION Materials and Chemicals. Peroxidase type VI-A from horseradish 1080 units/mg, 3α-HSD, recombinant cholesterol oxidase from Brevibacterium sp. 50 units/mg protein, cholesterol esterase from Pseudomonas fluorescens (∼20% protein), hydrogen peroxide, NAD, FMN, decanal, dithiothreitol (DTT), and all other chemicals were supplied from Sigma−Aldrich (St. Louis, MO, USA). Lyophilized recombinant bacterial luciferase (EC1.14.14.3) from Photobacterium phosphoreum and lyophilized bacterial recombinant FMNreductase (EC1.5.1.29) were obtained from Novocib (Lyon, France). Sepharose 4B was from Pharmacia (Uppsala, Sweden). Super Signal West Dura Extended Duration substrate was obtained from Thermo Scientific (Waltham, MA, USA). Blood and saliva separation membranes LF1 and Whatman No.1 filter
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(4 mm diameter), while a reagents’ reservoir contains the CL reagent (15 μL). A volume of 15 μL of blood is inserted into the minicartridge from the back inlet by touching the exposed pad. Within 2 min, the serum is directed toward the reaction chamber, where enzymatic reactions take place. CL reaction is triggered 3 min after sample injection with a simple flick in order to drive the CL reagent from the reservoir to the reaction chamber. The minicartridge is then inserted into the smartphone mini darkbox accessory and the light signal measured by the smartphone camera for 30 s using LongExpo app (Eyetap Soft LLC). Quantitative analysis of the CL images were performed using ImageJ software v.1.46 (National Institutes of Health, Bethesda, MD). Regions of interest (ROIs) corresponding to the detection chamber and background were selected and light emissions quantified as raw integrated densities. GraphPad Prism (GraphPad Software, Inc., La Jolla, CA) was used to plot CL signal as a function of total serum cholesterol concentration. Cholesterol Trinder assay (FAR Diagnostics, Verona, Italy) was used to evaluate accuracy of SmartChol. The standard solution of 200 mg/dL cholesterol contained in the kit was concentrated via rotary evaporation to obtain cholesterol solutions in the range of 140−386 mg/dL that were added to charcoal-stripped serum. Total Bile Acid Smartphone-Based Assay (SmartBA). Principle: 3α-HSD catalyzes the conversion of the BA 3αhydroxyl group to an oxo group. NADH is produced and, in the presence of NADH:FMN oxidoreductase, it converts FMN to its reduced form. The latter, in the presence of bacterial luciferase, reacts with decanal and oxygen to produce FMN, decanoic acid, and light. The light intensity is proportional to BA concentration in the initial reaction. The three enzymes were co-immobilized on Sepharose 4B beads as previously described by Ford et al.18 Briefly, 1 mL of the coupling solution containing 3 mg of the 3α-HSD (8U/ mg), 12 mg of luciferase, and 2 mg (10U/mL) of NADH:FMN oxidoreductase was reacted with 500 mg of activated Sepharose 4B. Sepharose-bound enzymes were stored for several days in phosphate buffer (0.1 M, pH 7.0) containing BSA (2.0 g/L), DTT (0.1 mM), and sodium azide (0.2 g/L). The composition of the solution absorbed on the cellulose disk is 1 × 10−5 % decanal, FMN 30 μmol/L, NAD 25 μmol/L in phosphate buffer 0.1 M, pH 7.0. A 10-μL volume of this solution and 5.0 μL of the suspended Sepharose 4B beads were adsorbed and dried on the cellulose disk. For the assay, 50 μL of oral fluid or 15 μL of serum were introduced in the minicartridge and diluted 1:5 v/v with 0.1 M sodium phosphate buffer pH 7.0 in the microfluidic channel inside the cartridge and delivered to the disk starting the BL reaction. The light emission was collected for 3 min. Evaluation of Analytical Performance of SmartChol and SmartBA Assays. Standard curves were constructed using dilutions of cholesterol (range = 140−3860 mg/dL) and BA samples using glycocholic acid as a standard (range 0.5− 100 μM) in phosphate buffer (0.1 M, pH 7.0). Each standard was assayed using three different minicartridges. To evaluate the accuracy of the assays, cholesterol, and total BA, where measured in 10 serum samples at known concentration obtained by standard validated methods. The reproducibility of the two methods was assessed by analyzing three serum samples at low, medium, and high concentrations of analyte using six different minicartridges. Within-run precision was calculated by measuring the same sample using six different minicartridges prepared the same day with the same batch of
paper were purchased from Whatman International, Ltd. (Maidstone, England). Smartphone Camera Characterization. An Iphone 5S (Apple, Cupertino, CA, USA) with a BI-CMOS sensor and 8megapixel (8MP) camera was used. A comparative study has been performed by analyzing standard solutions of H2O2 by CL reaction with the smartphone camera and a thermoelectrically cooled MZ-2PRO CCD camera (MagZero, Pordenone, Italy) equipped with a Sony ICX285 image sensor (1360 × 1024 pixels, pixel size = 6.45 μm × 6.45 μm) that has been previously reported by us.11 Briefly, a series of standard solutions of the system H2O2/luminol/enhancer/HRP with a concentration of hydrogen peroxide ranging from 0.01 μM to 10 mM where the reagents are adsorbed on a disk 4 mm in diameter were analyzed and the images collected with the two instrumentations (Figure S1 in the Supporting Information). The images have been elaborated with ImageJ software to quantify the signal over the sample spot area and expressed as relative light units (RLUs). 3D-Printed Smartphone Accessory Device Fabrication. The minicartridge and the mini darkbox smartphone accessory were fabricated using a dual-extrusion 3D printer Replicator 2X (Makerbot, Boston, MA, USA), using a thermoplastic black acrylonitrile butadiene styrene polymer. Three-dimensional (3D) models were created using the opensource Tinkercad browser-based 3D design platform (Autodesk, Inc.). MakerWare v.2.4 software, which uses an algorithm that slices digital files (exported as .stl files) into thin layers for 3D printing, was used to define printing options and settings. The device consists of two main parts: a phone adapter comprising the darkbox and lens holder and a cartridge for the bioassays (Figure 1). The depicted accessory was designed for the Iphone 5S to hold a plano-convex lens 6 mm in diameter (Edmund Optics, York, U.K.) in contact with the phone objective and housing a mini-cartridge (3.5 cm length, 1.2 cm width, and 5 mm thickness) with an optical window of 4 mm diameter, made by a thin layer (200 μm) of transparent acrylnitrile butadiene styrene (ABS, from Amazon.co.uk) deposited exploiting the dual-extrusion printing option. The disposable mini-cartridge contains a blood separator pad holder, with a LF1 glass fiber filter, connected to a reaction chamber where a 4 mm nitrocellulose disk supporting the specific enzymes is placed. A separate 15 μL reservoir for BL/ CL reagents is connected via microfluidics to the reaction chamber at 200 μm height in order to prevent premature mixing. The minicartridge was printed in two separate pieces, which are then glued together, in order to insert the specific supports and solutions. Sample Collection. Microsafe collection and dispensing tubes (with preset volume of 15 μL) were used for fingerprick sampling and dispensing of whole blood into the minicartridge. Oral fluid samples were collected with Salivette cotton swabs (Sarstedt, Germany). Total Cholesterol Smartphone-Based Assay (SmartChol). Principle: the assay is based on coupled enzymatic reactions in two steps: (1) esterified cholesterol hydrolysis by cholesterol esterase and cholesterol oxidation by cholesterol oxidase, and (2) CL detection of the produced hydrogen peroxide using Super Signal West Dura Luminol/ Enhancer solution in the presence of HRP as a catalyst. The optimized assay conditions are the followings: the enzymes (1U cholesterol oxidase, 0.5U cholesterol esterase, and 0.05U HRP) have been coabsorbed on the nitrocellulose disk 7301
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resolution. ABS, which becomes moldable at 220−230 °C, was selected as printing material. It enabled one to build a robust accessory that can be easily attached to the smartphone and a microfluidic minicartridge that supports the integration of other components. We chose to use an affordable yet versatile 3D printer that allows one to print objects with two different colors or materials in order to develop more-sophisticated devices with less printing steps. This feature was exploited to create a 200μm thin transparent ABS-based window over the minicartridge reaction chamber allowing the acquisition of BL/CL signals while preventing any leakage. The constructed smartphone accessory device can be easily snapped to the smartphone, providing a minidarkbox for the minicartridge. This adapter could be designed ad hoc for smartphones or tablets of different brands, allowing modification and adaptability to the continuous development of new models. Total Cholesterol Smartphone-Based Assay (SmartChol). The developed assay quantifies the total cholesterol in 15 μL of whole blood by exploiting cholesterol esterase and cholesterol oxidase that produces cholest-4-en-3one and H2O2, which is measured with the CL reaction with luminol, enhancers, and HRP as a catalyst. The minicartridge holds a pad for one-step serum separation from whole blood, a nitrocellulose disk in which the enzymes, i.e., cholesterol esterase, cholesterol oxidase, and HRP, are coadsorbed and a reservoir containing Super Signal West Dura for CL reaction. Thanks to ABS hydrophobicity and channel width, no accidental release of the reagents occurs, even turning the minicartridge upside down. In order to achieve the highest CL signal with a reasonably stable kinetics, different conditions were optimized including pH and concentrations of enzymes and reagents. Under the optimized conditions, reported in the Experimental section, the CL signal is proportional to the cholesterol concentration in the sample with a linear range from 20 mg/dL to 386 mg/dL and a limit of detection (LOD) of 20 mg/dL. Figure 2 shows CL images acquired with the smartphone and quantitative analysis of physiologically relevant cholesterol concentration range. The accuracy of the smartphone total cholesterol assay was characterized by quantifying cholesterol levels in serum samples in the range of 140−386 mg/dL and comparing them to results obtained using a commercial kit. At each concentration, six minicartridges were used and the within-run coefficient of variation was 5% for the sample containing 240 mg/dL cholesterol. Figure 3 shows the correlation between SmartChol and Trinder method obtained analyzing 10 serum samples of unknown cholesterol concentration (r2 = 0.996, p < 0.0001). The smartphone-based CL test allowed the discrimination and quantification of total cholesterol over the entire range of physiological values. Physiological desirable serum cholesterol levels (240 mg/ dL). These results show that the reported SmartChol assay has similar analytical performance when compared to a recently reported cholesterol biosensor relying on electrochemiluminescence detection (linear range from 0.83 mM to 2.62 mM, detection limit = 0.28 μM).19 Despite the reported assay having a higher LOD than other amperometric biosensors,20,21 it has the non-negligible advantage of requiring only a smartphone, thus eliminating the need to have additional detectors or devices for the test with a cost of ∼3−5 euros per assay
reagents; between-run precision was calculated by assaying the same sample with 6 minicartridges prepared in different days, each of them stored at least for 2 days at +4 °C. For SmartBA assay, total BA was measured in serum and oral fluid of 12 healthy subjects in fasting and post-prandial state (2 h after a standard meal) previously analyzed by HPLC-ES-MS/ MS.
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RESULTS AND DISCUSSION The simple accessory developed in this work was designed with the aim of using the smartphone camera as a luminometer, to measure the light produced by BL and CL systems coupled with analyte specific enzymatic reactions. Smartphone Camera Analytical Performance. New generation smartphones use BI-CMOS photodiodes as light sensors to increase light collection with reduced size. Compared to the conventional front-illuminated light sensors, this architecture allows one to reduce the pixel pitch and increase the optical efficiency,12 making mobile devices suitable to detect very weak light signals, such as those produced by BLCL reactions, with reasonable exposure time (e.g., few seconds, minutes). Since one of the main limitations for BL-CL detection is the instrumental thermal noise, cooled CCDs seem to be the most appropriate sensors; however, for the detection of analytes present at concentrations from the micromolar level to the millimolar level, BI-CMOS could offer adequate analytical performance, with the advantage of being integrated in a smartphone. A comparative study using a lensless cooled CCD camera, previously reported by us,11 and an iPhone 5S, showed that the BI-CMOS is less sensitive but still adequate to measure the photons produced by BL and CL reactions. For this purpose, a series of standards solutions of the system H2O2/luminol/enhancer/HRP with a concentration of hydrogen peroxide ranging from 0.01 μM to 10 mM were analyzed and the images collected with the two instrumentations (see Figure S1 in the Supporting Information). In terms of resolution, the images obtained with the smartphone camera show better performance thanks to the inclusion of a planoconvex lens to focus the image. In this configuration, two spots of 4 mm diameter at a distance of 1 mm can be simultaneously imaged without cross-talk, fitting the smartphone display size. This could be particularly useful to implement multiplexed assays (i.e., allowing to simultaneously measure more analytes using the same cartridge) into smartphone-based devices. Concerning detectability, even if the cooled CCD is able to image and quantify a concentration of H2O2 three decades lower, the BI-CMOS detector is suitable for detecting analytes present in biological fluids at micromolar levels, as the majority of common biomarkers of clinical interest. 3D-Printed Accessory Device. We developed a compact smartphone accessory and a minicartridge for specific enzymatic reactions using a desktop 3D printer. The use of 3D printing technology allowed us to rapidly obtain several prototypes without the need of fabricating for each one a master, such as with polydimethylsiloxane (PDMS) protocols. In addition, physical 3D models were quickly and affordably generated with a printing time of ∼10 min for the minicartridge and 30 min for the accessory. 3D models were easily generated using computer-aided design (CAD) programs, converted to Stereo Lithography (.stl) file format and elaborated with a slicer software that allows the 3D object to be printed as subsequent layers of thermoplastic material at a defined horizontal 7302
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including manufacturing and reagents. The availability of this simple and minimally invasive tool to measure blood cholesterol could be of clinical utility for several diagnostic needs such as the monitoring of subjects with ischemic stroke high risk, post-menopausal women, diabetic children, and, more generally, to monitor a patient’s metabolic status. Oral Fluid and Serum Total Bile Acid SmartphoneBased Assay (SmartBA). As we previously reported, for this coupled assay the use of co-immobilized enzymes is fundamental, in terms of optimal enzymatic activity, signal kinetics, and enzyme stability.22 Since the pH of 3αHSD enzymatic reaction is compatible with that of the indicator systems, the three enzymes have been first chemically co-immobilized on Sepharose beads and then absorbed on a 4-mm-diameter cellulose disk. In the smartphone-based optimized conditions, the light emission acquired for 30 s correlates well with the NADH concentration in the range from 10−7−10−4 M (data not shown). The minicartridge holds a pad for one-step serum separation from whole blood as for the cholesterol assay. The relative concentration of the indicator enzymes and substrates have been selected to linearly measure NADH in a concentration ranging from 10 pmol/L to 50 nmol/L and to prevent the autoxidation of FMNH2. The highest light emission has been achieved with a protein ratio of 2:3 and a final concentration of 10 μmol/mL. The assay is specific for 3α-hydroxy BA and has a detection limit of 0.5 μmol/L, with a linear range of 0.5−100 μmol/L, as reported in Figure 4, using glycocholic acid as a representative standard. Three serum samples at low, medium, and high BA concentrations were tested using six minicartridges for each sample and a CV% ranging from 9% to 12% was calculated for the same sample tested with six different minicartridges prepared with the same batch of reagents while a CV% from 13% to 16% was determined by assaying the same sample with six minicartridges with different batches of reagents and stored at least 24 h at 4 °C (see Table S1 in the Supporting Information). In the 12 healthy subjects, the mean total BA concentration in fasting state was 12.2 ± 3.5 μmol/L (range of 6.1−14.3 μmol/L), with an increase after meal to a mean value of 29.3 ± 2.8 μmol/L (range of 16.1−36.3 μmol/L). The oral fluids total BA values are usually 6−12 times lower than the corresponding serum values (Figure 4). In the fasting state, the mean values were 1.5 μmol/L (range of 0−2.3 μmol/L), which increase after meal to 3.4 μmol/L (range 1.1−4.6 μmol/L). The values were in agreement with those measured with HPLC-ES-MS/ MS in both oral fluid and serum (Table S1 in the Supporting Information). These data suggest that this device can be successfully used to perform frequent and noninvasive BA monitoring in patients with different hepatobiliary diseases.23
Figure 2. (a) Raw BL images of six charcoal-stripped human serum samples spiked with cholesterol measured by the smartphone camera, using the LongExpo app (30 s) showing low, medium, and high cholesterol concentrations. (b) Quantitative analysis of the same samples measured with SmartChol. Data represent the mean values ± the standard deviation (SD) obtained using three different minicartridges.
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CONCLUSION In this technical note, we demonstrated, for the first time, that the smartphone camera can be used to image and quantify the light produced by biochemiluminescence reactions used to amplify analyte-specific enzymatic reactions. A simple and compact smartphone accessory has been prototyped and fabricated using facile and cost-effective three-dimensional (3D) printing. This accessory has the dual role of acting as a darkbox for shedding from ambient light and hosting the minicartridge, which can be customized according to the target chemical reactions and diagnostic needs.
Figure 3. (a) Correlation between SmartChol and Trinder method obtained analyzing 10 serum samples of unknown cholesterol concentration (r2 = 0.996, p < 0.0001). (b) Physiological desirable cholesterol levels (240 mg/ dL).
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biochemiluminescence detection on smartphones for point-ofcare and point-of-need analysis.
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ASSOCIATED CONTENT
* Supporting Information S
Additional information as noted in the text. This material is available free of charge via the Internet at http://pubs.acs.org.
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AUTHOR INFORMATION
Corresponding Author
*Tel.:/Fax +39 051343398. E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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REFERENCES
(1) Vashist, S. K.; Mudanyali, O.; Schneider, E. M.; Zengerle, R.; Ozcan, A. Anal. Bioanal. Chem. 2014, 406, 3263−3277. (2) Boulos, M. N.; Wheeler, S.; Tavares, C.; Jones, R. Biomed. Eng. Online 2011, 10, 24. (3) Lee, S.; Oncescu, V.; Mancuso, M.; Mehta, S.; Erickson, D. Lab Chip 2014, 14, 1437−1442. (4) Oncescu, V.; O’Dell, D.; Erickson, D. Lab Chip 2013, 13, 3232− 3338. (5) Shen, L.; Hagen, J. A.; Papautsky, I. Lab Chip 2012, 12, 4240− 4243. (6) Oncescu, V.; Mancuso, M.; Erickson, D. Lab Chip 2014, 14, 759−763. (7) Byoung-Yong, C. Bull. Korean Chem. Soc. 2012, 33 (2), 549. (8) Petryayeva, E.; Algar, W. R. Anal. Chem. 2014, 86, 3195−3202. (9) Gallegos, D.; Long, K. D.; Yu, H.; Clark, P. P.; Lin, Y.; George, S.; Nath, P.; Cunningham, B. T. Lab Chip 2013, 13, 2124−2132. (10) Roda, A.; Pasini, P.; Mirasoli, M.; Michelini, E.; Guardigli, M. Trends Biotechnol. 2004, 22, 295−303. (11) Roda, A.; Mirasoli, M.; Dolci, L. S.; Buragina, A.; Bonvicini, F.; Simoni, P.; Guardigli, M. Anal. Chem. 2011, 83, 3178−3185. (12) Watanabe, N.; Tsunoda, I.; Takao, T.; Tanaka , K.; Asano, T. Jpn. J. Appl. Phys. 2010, 49, 04DB01. DOI: 10.1143/JJAP.49.04DB01. (13) Ryan, O.; Smyth, M. R.; Fágáin, C. O. Essays Biochem. 1994, 28, 129−146. (14) Roda, A.; Kricka, L. J.; DeLuca, M.; Hofmann, A.F. J. Lipid Res. 1982, 23, 1354−1361. (15) Blum, L. J.; Gautier, S. M.; Coulet, P. R. J. Biotechnol. 1993, 31, 357−368. (16) Roda, A.; Girotti, S.; Ghini, S.; Grigolo, B.; Carrea, G.; Bovara, R. Clin. Chem. 1984, 30, 206−210. (17) Gross, B. C.; Erkal, J. L.; Lockwood, S. Y.; Chen, C.; Spence, D. Anal. Chem. 2014, 86, 3240−3253. (18) Ford, J.; De Luca, M. Anal. Biochem. 1981, 110, 43−48. (19) Zhang, J.; Chen, S.; Tan, X.; Zhong, X.; Yuan, D.; Cheng, Y. Biotechnol. Lett. 2014, in press (DOI: 10.1007/s10529-014-1547-9). (20) Soylemez, S.; Kanik, F. E.; Ileri, M.; Hacioglu, S. O.; Toppare, L. Talanta 2014, 118, 84−89. (21) Ruecha, N.; Rangkupan, R.; Rodthongkum, N.; Chailapakul, O. Biosens. Bioelectron. 2014, 52, 13−19. (22) Jablonski, E.; DeLuca, M. Proc. Natl. Acad. Sci. U. S. A. 1976, 73, 3848−51. (23) Festi, D.; Morselli, A. M.; Roda, A.; Bazzoli, F.; Frabboni, R.; Rucci, P.; Tavoni, F.; Aldini, R.; Roda, E.; Barbara, L. Hepatology 1983, 5, 707−713. (24) Vinci, S. R.; Rifas-Shiman, S. L.; Cheng, J. K.; Mannix, R. C.; Gillman, M. W.; de Ferranti, S. D. JAMA 2014, 311, 1804−1807. (25) Schlesinger, D. P.; Rubin, S. I. Can. Vet. J. 1993, 34, 215−220.
Figure 4. (a) Calibration curve with glycocholic acid used as a representative standard showing a linear range from 0.5 to 100 μmol/ L. Insets show raw BL images obtained with 0.5 μmol/L and 100 μmol/L glycocholic concentrations. (b) Correlation between concentration of serum and oral fluid BA of 12 samples calculated with SmartBA.
The suitability of this accessory was demonstrated with two assays, SmartChol and SmartBA, for measuring cholesterol and total BA in serum and oral fluid. These assays can be performed within 3 min in a very straightforward manner with just few easy actions: snap the accessory onto the smartphone, add sample (e.g., 15 μL of blood or 50 μL oral fluid) to analytespecific minicartridge, introduce the minicartridge in the accessory and flick it, wait 3 min, and get results. The SmartChol could find relevant applications in the monitoring of cholesterol levels in children at risk with the possibility to perform the assay in pediatric outpatient clinic, helping the management of childhood obesity.24 Concerning the SmartBA, it is well know the increase of BA in liver disease and particularly during cholestatic liver disease. Therefore, potential future applications span from monitoring of pregnancy with cholestasis, to infants with cholestatic jaundice, patients with duodenum gastric reflux, to pharmacological therapy monitoring. In addition, another interesting application of the smartphone accessory could be in veterinary medicine, where the measurement of serum BA allows the rapid evaluation of hepatic functions in pets such as dogs and cats.25 The extreme simplicity of the device widens it applicability and makes it suitable for the detection of many analytes of clinical interest, for instance any NAD(P)H dehydrogenases or H2O2 producing oxidases such as those specific for glucose, lactate, and ethanol. Therefore, SmartChol and SmartBA could be considered as the forerunners of the integration 7304
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