Smartphone biosensors – Nanosensors Group

Since their introduction in 1997, “smart” mobile phones with internet connectivity, high-resolution cameras, touchscreen displays, and powerful CPUs have gained rapid market acceptance. It is estimated that, of the ~7.5 billion mobile phones that are currently in use, 51% of them can be classified as smartphones, with an expected rise to ~76% by 2022 (Ericsson Mobility Report, 2017). The rapid acceptance of smartphones is driven by a combination of falling prices and increasingly sophisticated features. In addition, there is a growing ecosystem of applications that take advantage of the phone’s sensors, display, and connection to powerful computing and cloud-based data storage capabilities. The built-in capabilities of smartphones can be further extended through the addition of accessories that enable the phone to sense different types of information, with uses in many different point-of-care testing applications (POCT). Recent examples include attachments that enable smartphones to serve as stethoscopes, ultrasound probes, microscopes, fluorescent microscopes, and label-free biosensor detection instruments. POCT is broadly applicable across industries ranging from medical diagnostics, food safety, food processing quality control, water quality monitoring, animal diagnostics, and pathogen detection.

Further incorporation of traditionally laboratory-based biosensing into smartphone platforms has much potential, as it opens the door for testing in situations not currently feasible and by a much broader range of users. Such developments may help to facilitate the goal of “personalized medicine,” in which home-based tests may be used to diagnose a medical condition but with a system that automatically communicates results to a cloud-based monitoring system that alerts the physician when warranted. Low-cost portable biosensor systems integrated with smartphones also may enable diagnostic technology that can be translated to resource-poor regions of the world for pathogen detection, disease diagnosis, and monitoring of nutritional status. Such a system, deployed widely, would be capable of rapidly monitoring for the presence of environmental contaminants over large areas, or tracking the development of a medical condition throughout a large population. Of all the label-free detection approaches that have been demonstrated, those based upon optical phenomena have been most commercially accepted due to a combination of sensitivity, sensor cost, detection system robustness, and high throughput. Adsorption of biomolecules, viral particles, bacteria, or cells on the surface of an optical biosensor transducer results in a shift in the conditions of optimal optical coupling, which can be measured by illuminating the transducer surface and subsequently measuring a property of the reflected or transmitted light. Such a detection approach is extremely robust and has become economically advantageous due to the advent of low-cost light-emitting diodes, semiconductor lasers, and miniature spectrometers. For example, surface plasmon resonance (SPR)-based and photonic crystal (PC) optical biosensors are capable of detecting broad classes of biological analytes through their intrinsic dielectric permittivity. Each approach has been successfully implemented in the form of large laboratory instruments and miniaturized (shoebox-sized) systems. Our lab seeks to take such optical sensors and shrink them to handheld detachments, with our initial successes being in both the PC-based label-free sensing and Enzyme Linked Immunosorbent Assays (ELISA).

Figure 1. A student uses the smartphone application to compare wavelength shifts in two samples (foreground, left), measured with a PC-based biosensor (foreground, right). Representative spectra, as observed by the smartphone showing changes in reflected bands, is indicative of biological absorption onto a PC surface (background).

Our developed technology uses a cradle-based attachment to allow the onboard camera of a smartphone to function as a spectrometer. The dispersion of light resulting from transmission through a diffraction grating allows transmitted light to be spatially differentiated along one dimension of the CMOS sensor. Changes in wavelength resultant from biological absorption to a PC surface, analogous to the PC-based bench top apparatuses used throughout the Nanosensors Group, can be measured with minimal modification to methodologies. Proof of concept has been demonstrated with both regular layers of polymer deposited on PCs as well as a basic biological absorption of Protein A and porcine IgG antibodies.

Similarly, ELISA procedures can be modified to be read on the smartphone system. Since its introduction, it has become one of the most widely adaptable tools for biological assays, allowing for the rapid quantification of proteins and antibodies for diseases ranging from HIV to cancer, yielding over 40,000 new articles involving the technology annually. An ELISA test is completed by immobilizing antibodies that possess an affinity for a specific biomolecule of interest onto a standard format 96-well microtiter plate and then passing over a series of liquids, exploiting the high specificity of the antibody-antigen interaction to eventually yield a colorometric change of the liquid sample based upon the cleavage of a chromogen moiety by an enzyme. When the optical absorptions of standards at known concentrations are used to obtain a calibration curve, the concentrations of an analyte within a test sample may be accurately determined via interpolation. Similarly, other color-specific absorption tests can be modified and read on the system. So far, we have demonstrated the success of such tests using both IL-6, a useful cancer biomarker, and Ara h 1, a biomarker responsible for peanut allergies, at physiologically relevant concentrations.

Figure 2. Steps of an ELISA Procedure. Primary antibodies are attached to the bottom of a 96-well microtiter plate. Next, molecules of interest are incubated on the sensing surface and attach to exposed antibodies. Secondary antibodies bound to enzymes capable of catalysing chromogenic reactions are incubated and attach specifically to the immobilized molecules of interest. Finally, chromogenic compounds are exposed to the sensor and are catalysed by any bound enzymes generating a color change that can then be quantified using the smartphone system.

The smartphone biosensor is also capable of conducting fluorescence applications. Light emitters operate via a variety of optical mechanisms that include fluorescence, chemoluminescence, and semiconductor quantum dot-excited electron relaxation. Among these approaches, those that utilize the Förster Resonance Energy Transfer (FRET) as a mechanism for observing changes in the quenching efficiency between matched donor-acceptor pairs are effective methods for diagnostics applications, because single-step assays are performed in liquid, without complex mixing-washing steps. For FRET assays, the ability to measure the spectrum of fluorescent emission is especially useful, as the combined contributions of donor and acceptor fluorophores can be measured independently, while wavelength-selective filters are not necessary. By using the function of the smartphone fluorimeter, which can disperse and analyze the incident optical signal, a sensitive molecular-beacon FRET assay for a specific microRNA sequence can be performed. Our results show that smartphone-based spectroscopic fluorimetry is a route towards portable biomolecular assays for viral/bacterial pathogens and toxins. The resulting capability may find applications that include point-of-care detection/analysis of pathogens, specific nanoparticle detection, human/animal diagnostics, and food safety.

Spectral bands on the smarphone screen — Figure 3. (a) Spectral bands on the smartphone screen before the target miR-21 is introduced (top; target miRNA (T): 0 μM), and after addition of the target that is a complementary match to the probe (bottom; T: 1 μM). (b) Normalized fluorescence intensity distributions. Inset shows magnified spectra that corresponds to the dashed area. (c) Normalized total intensities according to various T-miRNA concentrations. The intensity over the wavelength range of 560-580 nm was integrated to derive a single intensity value for each concentration. Inset shows enlarged region of the area encompassed by the dashed box.

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