domingo, 25 de diciembre de 2011

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection : Nature Genetics : Nature Publishing Group

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection

Journal name:
Nature Genetics
Year published:
Published online
Antibiotic resistance can evolve through the sequential accumulation of multiple mutations1. To study such gradual evolution, we developed a selection device, the 'morbidostat', that continuously monitors bacterial growth and dynamically regulates drug concentrations, such that the evolving population is constantly challenged2, 3, 4, 5. We analyzed the evolution of resistance in Escherichia coli under selection with single drugs, including chloramphenicol, doxycycline and trimethoprim. Over a period of ~20 days, resistance levels increased dramatically, with parallel populations showing similar phenotypic trajectories. Whole-genome sequencing of the evolved strains identified mutations both specific to resistance to a particular drug and shared in resistance to multiple drugs. Chloramphenicol and doxycycline resistance evolved smoothly through diverse combinations of mutations in genes involved in translation, transcription and transport3. In contrast, trimethoprim resistance evolved in a stepwise manner1, 6, through mutations restricted to the gene encoding the enzyme dihydrofolate reductase (DHFR)7, 8. Sequencing of DHFR over the time course of the experiment showed that parallel populations evolved similar mutations and acquired them in a similar order9.

Figures at a glance

  1. Figure 1: The morbidostat is a continuous-culture device that automatically tunes drug concentration to maintain constant growth inhibition.
    (a) The assay runs in cycles of growth periods (Δt = 11 min) and adds dilutions with either fresh medium (green) or drug solution (magenta). The population is diluted with antibiotic solution when the OD exceeds ODTHR (0.15) and the net growth over the complete cycle is positive (ΔOD > 0). (b) Representative bacterial growth in the morbidostat. OD is recorded at 1 Hz (plotted at 0.1 Hz, gray dots). The growth rate (r) within a growth period is calculated by fitting the exponential growth function (black lines). Magenta and green markers indicate dilutions with drug solution and fresh medium, respectively. Inset, parameters calculated at each growth cycle are shown. (c) Representative bacterial growth and inhibition in the morbidostat for an extended time period. For clarity, only final ODs within growth cycles are plotted. The grey rectangle delimits data shown in b. Magenta circles indicate the cycles after the addition of drug solution.
  2. Figure 2: Parallel populations attain high levels of drug resistance in similar adaptive trajectories.
    (a) Sample measurements of OD versus time (circles) and fitted growth rates (exponential fit; color represents normalized growth rate r/r0) of the ancestral strain in different trimethoprim concentrations. (b) Normalized growth rates of bacterial populations obtained from daily samples (x axis) of the evolving populations in a range of fixed drug concentrations (y axis). Day 0 corresponds to the ancestral strain before evolution. IC50 values are represented with black circles (r/r0 = 0.5). (ce) Resistance levels over time for parallel populations evolving under inhibition by trimethoprim (c), chloramphenicol (d) and doxycycline (e). Resistance increases by ~1,680, 870 and 10 fold, respectively. Trimethoprim resistance increases in a stepwise fashion. The resistance data for each of the 15 populations are derived from high-throughput phenotyping as shown in a (the TMP-1 population in c (black circles) is the one represented in b).
  3. Figure 3: Unique and common genetic changes identified by whole-genome sequencing.
    (a) SNPs identified by Illumina and Sanger sequencing. The horizontal arrow blocks and rectangles represent the coding and noncoding regions of genes, respectively. SNPs found in the 15 evolved populations are shown by different symbols, with colors indicating the drug applied during evolution (magenta, chloramphenicol; green, doxycycline; blue, trimethoprim). Note that SNPs found in multiple populations are shown with vertically stacked symbols appended to the genes. SNPs are localized to genes that fall into three major functional groups: (i) transcription and translation, (ii) folic acid biosynthesis and (iii) membrane transport. Arrow thickness reflects the frequency of mutations occurring within each functional group when the bacterial populations were challenged with the specified drugs. pDHFR, DHFR promoter; pcmr, cmr promoter. (b) Resistance levels (of Illumina-sequenced clones) to chloramphenicol, doxycycline and trimethoprim. Black dashed lines indicate minimum inhibitory concentration (MIC) for the ancestral strain. Panels with colored background show MIC values for the evolved strains for the drugs to which they evolved resistance. Strains evolved in the presence of chloramphenicol exhibit elevated doxycycline resistance and vice versa, whereas evolution in the presence of trimethoprim inhibition led to little or no cross-resistance for either doxycycline or chloramphenicol.
  4. Figure 4: Semi-ordered acquisition of trimethoprim resistance mutations.
    (a) Structure of E. coli DHFR enzyme (PDB 1RX2) bound to its substrate, dihydrofolate (black, arrow), with mutated residues shown in color. (b) IC50 values (gray lines) and time-resolved alterations in DHFR for each of the five replicate (TMP-1–TMP-5). For each day, alterations found in four randomly sampled clones are represented in a pie chart, with color indicating a specific alteration and shape of the chart indicating whether the alteration was a promoter mutation or amino acid substitution. The quadrants of the pie chart indicate the presence (filled) or absence (empty) of this alteration in each of the four sequenced clones (the correspondence between clones and quadrants is conserved across all mutations to indicate whether mutations are found in the same or different clones). Colors of the pie charts correspond to the colors of the mutated sites shown in a. Inset, additional colonies (TMP-4) were sequenced from bacteria isolated at days 8–10 to verify the disappearance of the W30C alteration. (c) Reproducibility of the order of fixation of mutations compared for the five parallel populations in the observed data (arrow) and when the order of mutations is randomly permuted (histogram bar). Only 0.2% of randomly permuted trajectories are equally or more reproducible than the trajectories observed in b.

Accession codes

Referenced accessions

Sequence Read Archive

Author information

  1. These authors contributed equally to this work.

    • Erdal Toprak &
    • Adrian Veres


  1. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA.

    • Erdal Toprak,
    • Jean-Baptiste Michel,
    • Remy Chait &
    • Roy Kishony
  2. Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts, USA.

    • Adrian Veres
  3. Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts, USA.

    • Jean-Baptiste Michel
  4. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA.

    • Daniel L Hartl
  5. School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.

    • Roy Kishony


E.T., A.V., R.C., D.L.H. and R.K. designed the project. E.T. and A.V. performed the experiments and E.T., A.V., J.-B.M. and R.K. analyzed the data. All authors contributed to preparing the manuscript.

Competing financial interests

The authors declare no competing financial interests.

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Supplementary information

PDF files

  1. Supplementary Text and Figures (3M)
    Supplementary Figures 1–4, Supplementary Tables 1–3 and Supplementary Note.

Evolutionary paths to antibiotic resistance under dynamically sustained drug selection : Nature Genetics : Nature Publishing Group

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