Smartphone-Based Methods for Detection of Various Bacteria Species and Proteins

Abstract

The smartphone platform offers a unique tool by combining low-cost components that can be used as an optical reader device. With the widespread adoption of smartphones, these platforms have potential functions in a variety of biosensing applications. One such application is the employment of a smartphone and other low-cost components for detection of bacterial species on laboratory surfaces via autofluorescence. With the combination of a smartphone, a 405 nm light emitting diode (LED) as an excitation source, and an acrylic film as an optical bandpass filter, the autofluorescent signals from the bacterial species can be detected directly on the laboratory surface. ImageJ analysis was utilized to process the images and obtain average intensity of the autofluorescent signal from Escherichia coli, Salmonella Typhimurium, and Staphylococcus aureus. With a limit of detection (LOD) of 104 CFU/cm2, a decreasing trend in the fluorescent signal was observed with decreasing concentration of each bacterial species. This imaging setup also had the capability to distinguish bacterial species from a variety of controls such as tap water and bovine serum albumin (BSA). In addition to such applications, detection of SARS-CoV-2 antibodies from clinical saline gargle samples using this smartphone platform was also possible. An antibody assay for SARS-CoV-2 antibodies can be beneficial in tracking vaccine efficacy, its diminished effect over time, and an individual’s immune status after infection. However, due to low concentrations of SARS-CoV-2 antibodies in the clinical saline gargle samples, the need for an invasive blood sample has been the gold standard for detection of these antibodies. To avoid this, we developed a competitive particle immunoassay on a paper microfluidic chip. This competitive particle immunoassay requires pre-loading of fluorescent particle conjugated receptor-binding domain (RBD) antigens and salivary SARS-CoV-2 antibodies. Following the loading of the sample, a smartphone fluorescent microscope images the captured fluorescent particles which can then be counted through an ImageJ batch code analysis. An LOD of 1-5ng/mL was obtained from 10% and 1% saliva. A statistical difference was observed in the 10-fold diluted virus negative and virus positive samples from the clinical saline gargle samples. The high sensitivity of this assay demonstrated the ability to detect SARS-CoV-2 antibodies, even in the early stages of infection, while using a less invasive and more cost-effective method. Continuing with a smartphone and microfluidic paper platform, a flow velocity measurement was used for detecting extracellular nicotinamide phosphoribosyltransferase (eNAMPT) in 10% and 1% plasma and clinical samples. The flow velocity detection requires a video to be captured with a smartphone as the samples are loaded into each microfluidic channel where this video will be analyzed with a custom Python code running on Google Collaboratory. A LOD of 1-10 pg/mL was obtained from 1% and 10% plasma samples. Finally, using this same flow velocity method of detection, differences in flow velocities of different DNA target amplicon lengths were measured. Gel electrophoresis is run after polymerase chain reaction (PCR) to determine successful amplification of the target DNA. This method requires an additional 1-2 hours where the use of our paper microfluidic assay would take around five minutes to run potentially reducing the time needed to determine successful amplification after PCR. This method successfully distinguished the different lengths of amplified products. Overall, smartphone platforms offer the possibility to detect various bacterial species, virus pathogens, disease markers, and PCR products while being low-cost, user-friendly, and portable.