Population heterogeneity in bacterial phenotypes, particularly antibiotic resistance, is increasingly recognized as a major medical concern1. One specific form of phenotypic heterogeneity, known as heteroresistance (HR), refers to the presence of small subpopulations of resistant bacterial cells within a larger, otherwise susceptible population2. During antibiotic treatment, these rare resistant subpopulations can survive and proliferate, often leading to treatment failure and persistent infections. HR is clinically significant yet remains underdiagnosed because standard antibiotic susceptibility testing (AST) methods lack the sensitivity to detect resistant subpopulations that exist at very low frequencies, typically between 1 in 1,000,000 and 1 in 100,000 cells.
To address this diagnostic challenge, we have developed a 3D-printed droplet microfluidics-based platform combined with a texture-based image analysis tool to detect rare resistant subpopulations with frequencies as low as 10⁻⁶. The microfluidic chip consists of two main sections: (i) a droplet generation unit featuring a T-junction where an oil phase and an aqueous phase (containing bacteria in Mueller-Hinton broth mixed with antibiotics) to form discrete droplets (Fig. 1a), and (ii) an incubation chamber capable of housing approximately 2000–3500 droplets. In our multiplex design (Fig. 1b), multiple droplet generators and corresponding incubation zones are integrated to enable high-throughput screening. Each droplet typically encapsulates 1000–5000 bacterial cells, depending on parameters such as droplet volume, bacterial concentration (CFU/mL), the antibiotic used, and the expected frequency of resistant cells. If resistant cells are present, they can proliferate inside the droplets under antibiotic stress, altering the internal texture patterns. These changes can be quantified using image texture analysis, particularly through reduced homogeneity and correlation. Using this approach, we successfully detect HR in clinical isolates of Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Staphylococcus aureus against various antibiotics.
2025.