Speckle imaging offers sensitive detection of bacterial growth in microdroplet antibiotic susceptibility testing assays

Abstract

Detection and quantification of bacterial populations in droplets is a fundamental prerequisite for the application of droplet microfluidic technology in antibiotic susceptibility assays, paving the way for single-cell profiling and quantifying hetero-resistance. While several label-free detection approaches have been proposed, limited detection sensitivity and the ability to quantify bacterial populations in droplets accurately remain challenging. Furthermore, these approaches are prone to a high number of false positives resulting in low accuracy and requiring highly monodisperse droplets. This study presents a speckle image-based detection technique for the quantification of the bacterial population in droplets. Speckles are generated by scattering laser light from bacteria-loaded droplets in a flow cytometric approach. Spatial segregation of the scattering signal from the droplet surface as well as its contents allows the detection of encapsulated bacteria with a high signal-to-noise ratio. This results in a detection sensitivity of ⁓100 CFU/droplet, the highest achieved by any label-free detection technique in a flow format thus far. It also allows the identification of false-positive signals, thereby increasing the accuracy of detection and enabling operation with polydisperse droplets (diameter: 10–500 µm). The properties of the speckle image generated from droplets, such as speckle grain size and density, can be used to quantify the population of bacteria in droplets. This detection approach applies to a wide range of bacteria species of clinical and industrial importance, creating avenues for innovation in bacteria analysis using droplet microfluidics.