For and , drug resistance is sometimes due to the pre-existence of genetic polymorphisms that bypass the mode of action of the drug, thus conferring a long-term survival benefit. In other cases, resistance is acquired via the evolution of de novo genetic polymorphisms. There is evidence that possess a drug tolerance response which “buys time” for individuals to evolve beneficial mutations. Our goal here is to characterize this poorly understood epigenetic cytoprotective program at the single cell molecular level.


We developed a nano-litre droplet based single cell sequencing platform capable of transcriptionally profiling several thousand individual cells in an efficient manner. We exploit this platform to profile both untreated and drug exposed (incl. fluconazole, caspofungin and nystatin) populations at early time points post-treatment (tolerance) and late time points (resistance) in order to understand survival trajectories. The profile are compared with the matched sequenced genomes.


We show that untreated populations exhibit “bet hedging”, stochastically expressing cytoprotective transcriptional programs, and drug tolerant individuals partition into distinct subpopulations, each with a unique survival strategy involving different transcriptional programs. We observe a burst of chromosomal aberrations at two days post-treatment that differ between survivor subpopulation.


Our single cell approach highlights that survivor subpopulations pass through a tolerance phase that involves a multivariate transcriptional response including upregulation of efflux pumps, chaperones and transport mechanisms, and cell wall maintenance. Together this suggests that targeting the tolerance response concomitantly with standard therapies could represent an efficient approach to ablating clinical persistence.

  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.

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