Rapid Waterborne Pathogen Detection with Mobile Electronics

Label-free detection and enumeration of Giardia cysts in agitated suspensions using in situ microscopy

Laboratory procedures performed in water treatment studies frequently require the characterization of (oo)cyst suspensions. Standard methods commonly used are laborious, expensive and time-consuming, besides requiring well-trained personnel to prepare samples with fluorescent staining and perform analysis under fluorescence microscopy. In this study, an easy cost-effective in situ microscope was assessed to acquire images of Giardia cysts directly from agitated suspensions without using any chemical labels or sample preparation steps. An image analysis algorithm analyzes the acquired images, and automatically enumerates and provides morphological information of cysts within 10 min. The proposed system was evaluated at different cyst concentrations, achieving a limit of detection of ~30 cysts/mL. The proposed system overcomes cost, time and labor demands by standard methods and has the potential to be an alternative technique for the characterization of Giardia cyst suspensions in resource-limited facilities, since it is independent of experts and free of consumables.

Detection of cholera toxin with surface plasmon field-enhanced fluorescent spectroscopy

In this work, a biosensor based on surface plasmon field-enhanced florescence spectroscopy (SPFS) method was successfully constructed to detect the truncated form of cholera toxin, that is, its beta subunit (CTX-B). CTX-B is a relatively small molecule (12 kDa) and it was chosen as model analyte for the detection of protein toxins originated from waterborne pathogens. Recognition layer was prepared on gold-coated LaSFN9 glasses modified with 11-mercaptoundecanoic acid (11-MUA). Biotin-conjugated anti-CTX-B polyclonal antibody (B-Ab) was immobilized on streptavidin (SA) layer constructed on the 11-MUA-modified surface. CTX-B amount was determined with direct assay using B-Ab in surface plasmon resonance (SPR) mode and with sandwich assay in SPFS mode using Cy5-conjugated anti-CTX-B polyclonal antibody. Minimum detected CTX-B concentrations were 10 and 0.01 μg/ml with SPR and SPFS, respectively, showing the sensitivity of the SPFS system over the conventional one. The detection was done in 2-6 h, which was faster than both culture and polymerase chain reaction (PCR)-based methods. Stability tests were performed with SA-coated sensors (excluding B-Ab). In this form, the layer was stable after 30 days of storage in phosphate-buffered saline (PBS; 0.01 M, pH = 7.4) at +4°C. B-Ab layer was formed immediately on them before each measurement.

A smartphone-based particle diffusometry platform for sub-attomolar detection of Vibrio cholerae in environmental water

Each year, 3.4 million people die from waterborne diseases worldwide. Development of a rapid and portable platform for detecting and monitoring waterborne pathogens would significantly aid in reducing the incidence and spread of infectious diseases. By combining optical methods and smartphone technology with molecular assays, the sensitivity required to detect exceedingly low concentrations of waterborne pathogens can readily be achieved. Here, we implement smartphone-based particle diffusometry (PD) detection of loop-mediated isothermal amplification (LAMP) targeting the waterborne pathogen Vibrio cholerae (V. cholerae). By measuring the diffusion of 400 nm streptavidin-coated fluorescent nanoparticles imaged at 68X magnification on a smartphone, we can detect as few as 6 V. cholerae cells per reaction (0.66 aM) in just 35 minutes. In a double-blinded study with 132 pond water samples, we establish a 91.8% sensitivity, 95.2% specificity, and 94.3% accuracy of the smartphone-based PD platform for detection of V. cholerae. Together, these results demonstrate the utility of this smartphone-based PD platform for rapid and sensitive detection of V. cholerae at the point of use.

A Rapid and Low-Cost Pathogen Detection Platform by Using a Molecular Agglutination Assay

Rapid and low-cost pathogen diagnostic approaches are critical for clinical decision-making procedures. Cultivating bacteria often takes days to identify pathogens and provide antimicrobial susceptibilities. The delay in diagnosis may result in compromised treatment and inappropriate antibiotic use. Over the past decades, molecular-based techniques have significantly shortened pathogen identification turnaround time with high accuracy. However, these assays often use complex fluorescent labeling and nucleic acid amplification processes, which limit their use in resource-limited settings. In this work, we demonstrate a wash-free molecular agglutination assay with a straightforward mixing and incubation step that significantly simplifies procedures of molecular testing. By targeting the 16S rRNA gene of pathogens, we perform a rapid pathogen identification within 30 min on a dark-field imaging microfluidic cytometry platform. The dark-field images with low background noise can be obtained using a narrow beam scanning technique with off-the-shelf complementary metal oxide semiconductor (CMOS) imagers such as smartphone cameras. We utilize a machine learning algorithm to deconvolute topological features of agglutinated clusters and thus quantify the abundance of bacteria. Consequently, we unambiguously distinguish Escherichia coli positive from other E. coli negative among 50 clinical urinary tract infection samples with 96% sensitivity and 100% specificity. Furthermore, we also apply this quantitative detection approach to achieve rapid antimicrobial susceptibility testing within 3 h. This work exhibits easy-to-use protocols, high sensitivity, and short turnaround time for point-of-care testing uses.