Rapid, sensitive, and low-cost detection of Escherichia coli bacteria in contaminated water samples using a phage-based assay.

Inadequate drinking water quality is among the major causes of preventable mortality, predominantly in young children. Identifying contaminated water sources remains a significant challenge, especially where resources are limited. The current methods for measuring Escherichia coli (E. coli), the WHO preferred indicator for measuring fecal contamination of water, involve overnight incubation and require specialized training. In 2016, UNICEF released a Target Product Profile (TPP) to incentivize product innovations to detect low levels of viable E. coli in water samples in the field in less than 6 h. Driven by this challenge, we developed a phage-based assay to detect and semi-quantify E. coli. We formulated a phage cocktail containing a total of 8 phages selected against an extensive bacterial strain library and recombined with the sensitive NanoLuc luciferase reporter. The assay was optimized to be processed in a microfluidic chip designed in-house and was tested against locally sourced sewage samples and on drinking water sources in Nairobi, Kenya. With this assay, combined with the microfluidic chip platform, we propose a complete automated solution to detect and semi-quantify E. coli at less than 10 MPN/100 mL in 5.5 h by minimally trained personnel.

Automated liquid handling robot for rapid lateral flow assay development.

The lateral flow assay (LFA) is one of the most popular technologies on the point-of-care diagnostics market due to its low cost and ease of use, with applications ranging from pregnancy to environmental toxins to infectious disease. While the use of these tests is relatively straightforward, significant development time and effort are required to create tests that are both sensitive and specific. Workflows to guide the LFA development process exist but moving from target selection to an LFA that is ready for field testing can be labor intensive, resource heavy, and time consuming. To reduce the cost and the duration of the LFA development process, we introduce a novel development platform centered on the flexibility, speed, and throughput of an automated robotic liquid handling system. The system comprises LFA-specific hardware and software that enable large optimization experiments with discrete and continuous variables such as antibody pair selection or reagent concentration. Initial validation of the platform was demonstrated during development of a malaria LFA but was readily expanded to encompass development of SARS-CoV-2 and Mycobacterium tuberculosis LFAs. The validity of the platform, where optimization experiments are run directly on LFAs rather than in solution, was based on a direct comparison between the robotic system and a more traditional ELISA-like method. By minimizing hands-on time, maximizing experiment size, and enabling improved reproducibility, the robotic system improved the quality and quantity of LFA assay development efforts.