The field of microbiology is entering a new era in which quantitative single cell data is required to understand the complex molecular pathways of antimicrobial-resistance. The synergy of biology, microfluidics and artificial intelligence is emerging, and makes it possible interrogate thousands of single cells. We have designed and developed a microfluidic system to isolate and monitor 1000+ single bacteria that are exposed to antibiotics. We are studying the phenomenon of antibiotic-induced mutagenesis, using time lapse fluorescence microscopy to gather quantitative data on individual cells.
The goal of this project is to develop a system to measure the phenotypes of a large variety of resistance mutations, both strong and weak, and imparting both high and low fitness. In contrast to traditional techniques, this system isolates each bacterium thereby preventing competition that would otherwise allow only the strongest and healthiest mutation to survive. The offspring of individual bacteria is monitored while they are being exposed to antibiotics. These bacteria are equipped with plasmids that produce fluorescent proteins once the genetic promoters of interest are activated. Their induced resistance phenotype is then monitored overnight, with fluorescent microscopy and time lapse techniques. We will use these data to reconstruct the first antibiotic fitness landscapes measured using single cells. This will map the range of effects that are produced by resistance-conferring mutations and will give new insight into antibiotic-induced resistance.