Emergence of Antibiotic Resistance from Single Cells
Stochastic switches that control antibiotic resistance genes are prevalent in bacterial genomes. We developed a model system to track the emergence and dynamics of antibiotic resistance in single cells.
To observe stochastic switching dynamics of antibiotic resistance, we used the agn43 promoter to drive tetracycline resistance and a fluorescent reporter in E. coli.
Using the agn43 stochastic switch to control tetracycline resistance. Ref: Lin & Kussell, Current Biology, 26:1486 (2016).
This video shows E. coli cells expressing the stochastic switch growing in the chemoflux device under pulses of tetracycline. When a cell turns ‘green’ the antibiotic resistance gene is expressed, and a selective sweep ensues. Because switching occurs stochastically without sensing, some populations do not develop resistance and go extinct.
Experiments by Wei-Hsiang Lin
We developed image analysis algorithms to quantify the dynamics of growth rate variation over 48-hour experiments that track hundreds of populations simultaneously in fluctuating conditions.
Dynamics of stochastic resistance emergence in six populations. Gray bars indicate tetracycline exposure periods.
By varying the period of antibiotic pulse duration, we discovered that emergence of resistance is minimized when the pulse period is comparable to the cell division time.
Distribution of resistance frequency over populations at different tetracycline pulse periods.
Tracking single cell elongation dynamics during antibiotic pulsing revealed that non-resistant E. coli cells can adapt physiologically to specific pulse periods, which minimizes selection for resistance.
Single cell elongation, division, and size dynamics for non-resistant cells under tetracycline pulses (gray bars).