Revealing the genetic changes responsible for antibiotic resistance can be critical for developing novel antibiotic therapies. However, systematic studies correlating genotype to phenotype in the context of antibiotic resistance have been missing. In order to fill in this gap, we evolved 88 isogenic Escherichia coli populations against 22 antibiotics for 3 weeks. For every drug, two populations were evolved under strong selection and two populations were evolved under mild selection. By quantifying evolved populations’ resistances against all 22 drugs, we constructed two separate cross-resistance networks for strongly and mildly selected populations. Subsequently, we sequenced representative colonies isolated from evolved populations for revealing the genetic basis for novel phenotypes. Bacterial populations that evolved resistance against antibiotics under strong selection acquired high levels of cross-resistance against several antibiotics, whereas other bacterial populations evolved under milder selection acquired relatively weaker cross-resistance. In addition, we found that strongly selected strains against aminoglycosides became more susceptible to five other drug classes compared with their wild-type ancestor as a result of a point mutation on TrkH, an ion transporter protein. Our findings suggest that selection strength is an important parameter contributing to the complexity of antibiotic resistance problem and use of high doses of antibiotics to clear infections has the potential to promote increase of cross-resistance in clinics.
We present a protocol for building and operating an automated fluidic system for continuous culture that we call the "morbidostat". The morbidostat is used to follow evolution of microbial drug resistance in real time. Instead of exposing bacteria to predetermined drug environments, the morbidostat constantly measures the growth rates of evolving microbial populations and dynamically adjusts drug concentrations inside culture vials in order to maintain a constant drug induced inhibition. The growth rate measurements are done using an optical detection system that is based on measuring the intensity of back-scattered light from bacterial cells suspended in the liquid culture. The morbidostat can additionally be used as a chemostat or a turbidostat. The whole system can be built from readily available components within two to three weeks, by biologists with some electronics experience or engineers familiar with basic microbiology.
Many key regulatory proteins in bacteria are present in too low numbers to be detected with conventional methods, which poses a particular challenge for single-cell analyses because such proteins can contribute greatly to phenotypic heterogeneity. Here we develop a microfluidics-based platform that enables single-molecule counting of low-abundance proteins by mechanically slowing-down their diffusion within the cytoplasm of live Escherichia coli (E. coli) cells. Our technique also allows for automated microscopy at high throughput with minimal perturbation to native physiology, as well as viable enrichment/retrieval. We illustrate the method by analysing the control of the master regulator of the E. coli stress response, RpoS, by its adapter protein, SprE (RssB). Quantification of SprE numbers shows that though SprE is necessary for RpoS degradation, it is expressed at levels as low as 3–4 molecules per average cell cycle, and fluctuations in SprE are approximately Poisson distributed during exponential phase with no sign of bursting.
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