Over the past few years, infections caused by airborne pathogens have spread worldwide, infecting several people and becoming an increasingly severe threat to public health. Therefore, there is an urgent need for developing airborne pathogen monitoring technology for use in confined environments to enable epidemic prevention. In this study, we designed a colorimetry-based bacterial detection platform that uses a clustered regularly interspaced short palindromic repeat-associated protein 12a system to amplify signals and a urease enzyme to induce color changes. Furthermore, we have developed a smartphone application that can distinguish colors under different illumination conditions based on the HSV model and detect three types of disease-causing bacteria. Even synthetic oligomers of a few picomoles of concentration and genomic DNA of airborne bacteria smaller than several nanograms can be detected with the naked eye and using color analysis systems. Furthermore, in the air capture model system, the bacterial sample generated approximately a 2-fold signal difference compared with that in the control group. This colorimetric detection method can be widely applied for public safety because it is easy to use and does not require complex equipment.
Keywords: Bacterial detection; Colorimetry; Mobile; Pathogen; Point-of-care sensing.
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