Design and application of a portable luminometer for bioluminescence detection.

The silicon photomultiplier (SiPM) for low light detection has many advantages when compared to existing photon counting detectors, such as high sensitivity, low cost, robustness, and compact hardware. To facilitate the use of SiPM as a portable, field deployable device, an electrical circuit was designed consisting of an amplifier, comparator, and microcontroller. In addition, a 3D printing was used to create a portable cradle for housing the SiPM. To evaluate its detection ability, a laser experiment and bioluminescent experiments, including Pseudomonas fluorescens M3A detection, E. coli O157:H7 PhiV10nluc lysogen detection, and a luminescence-based detection of E. coli O157:H7 in ground meat using the engineered luminescent-based reporter phage PhiV10nluc, were conducted. In the same experimental setting, our previously developed smartphone-based luminometer called the bioluminescent-based analyte quantitation by smartphone and a conventional photomultiplier tube-based benchtop luminometer were used to compare detection levels and applicability for supporting luminescent phage-based pathogen detection. Results showed that the SiPM provides better performance in terms of time to detection and SNR and could be used as the light detection component of the PhiV10nluc phage-based detection format.

Smartphone-based lateral flow imaging system for detection of food-borne bacteria E.coli O157:H7.

We report an application for the smartphone as an accurate and unbiased reading platform of a lateral flow immunoassays for food safety application. In particular, this report focuses on detection of food-borne bacteria in samples extracted from food matrices such as ground beef and spinach. The lateral flow assay is a widely accepted methodology owing to its on-site results, low-cost analysis, and ease of use with minimum user inputs, even though sensitivity is not quite equivalent to that of standard laboratory equipment. An antibody-antigen relationship is transduced into a color change on a nitrocellulose pad while visual interpretation of this color change can result in uncertainty, particularly near the detection limit of the assay. Employing the high resolution integrated camera, constant illumination from light source, and computing power of a smartphone, we provide an objective and accurate method to determine the bacterial cell concentration in a food matrix based on the regression model from the color intensity of test lines. A 3D-printed sample holder was designed for representative commercial lateral flow assays and an in-house application was developed in Android Studio to solve the inverse problem to provide cell concentration information from the color intensity. Test results with E.coli O157:H7 as a model organism suggests that smartphone-based reader can detect 104-105 CFU/ml from ground beef and spinach food matrices.

Smartphone-based low light detection for bioluminescence application.

We report a smartphone-based device and associated imaging-processing algorithm to maximize the sensitivity of standard smartphone cameras, that can detect the presence of single-digit pW of radiant flux intensity. The proposed hardware and software, called bioluminescent-based analyte quantitation by smartphone (BAQS), provides an opportunity for onsite analysis and quantitation of luminescent signals from biological and non-biological sensing elements which emit photons in response to an analyte. A simple cradle that houses the smartphone, sample tube, and collection lens supports the measuring platform, while noise reduction by ensemble averaging simultaneously lowers the background and enhances the signal from emitted photons. Five different types of smartphones, both Android and iOS devices, were tested, and the top two candidates were used to evaluate luminescence from the bioluminescent reporter Pseudomonas fluorescens M3A. The best results were achieved by OnePlus One (android), which was able to detect luminescence from ~106 CFU/mL of the bio-reporter, which corresponds to ~107 photons/s with 180 seconds of integration time.

Smartphone-based colorimetric analysis for detection of saliva alcohol concentration.

A simple device and associated analytical methods are reported. We provide objective and accurate determination of saliva alcohol concentrations using smartphone-based colorimetric imaging. The device utilizes any smartphone with a miniature attachment that positions the sample and provides constant illumination for sample imaging. Analyses of histograms based on channel imaging of red-green-blue (RGB) and hue-saturation-value (HSV) color space provide unambiguous determination of blood alcohol concentration from color changes on sample pads. A smartphone-based sample analysis by colorimetry was developed and tested with blind samples that matched with the training sets. This technology can be adapted to any smartphone and used to conduct color change assays.