Research ArticleAntibiotics

Use of Collateral Sensitivity Networks to Design Drug Cycling Protocols That Avoid Resistance Development

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Science Translational Medicine  25 Sep 2013:
Vol. 5, Issue 204, pp. 204ra132
DOI: 10.1126/scitranslmed.3006609
  • Fig. 1. Collateral sensitivity and its application in drug cycling.

    (A to C) Determination of drug susceptibility profiles is based on the growth of a WT (black line) and resistant strain (green line) as a function of varying drug concentrations. (A) Collateral resistance. As the concentration of drug 1 increases, a resistant strain with collateral resistance to this drug will outcompete the WT (orange shade). (B) No change in susceptibility. As the concentration of drug 2 increases, the resistant strain will perform the same as the WT. (C) Collateral sensitivity. When the concentration of drug 3 increases, the WT will outcompete the resistant strain (blue shade). (D) A general model illustrating the principle of collateral sensitivity cycling showing eradication of resistant strains when drugs with reciprocal collateral sensitivity profiles (A and B) are rotated. Consider that treatment of a WT disease-causing cell population (black circles) starts with drug A (violet arrow) at time t0. Over time in the presence of drug A, resistance to drug A develops (violet circles), and eventually, drug A becomes ineffective (t1). Then, treatment is switched to drug B (green arrow), to which drug A–resistant cells had become collaterally sensitive (t2). This treatment will lead to an eradication of the drug A–resistant cells and selection for cells with WT resistance levels (MICWT). Eventually, resistance to drug B (green circles) develops (t3) and treatment is switched back to drug A, to which drug B–resistant cells had become collaterally sensitive, resulting in an elimination of drug B–resistant cells (t0). Thus, through the rational cycling between drugs A and B, drug resistance—and possibly treatment failure—can be selected against.

  • Fig. 2. Collateral sensitivity profiles of drug-resistant E. coli strains.

    (A) A heat map showing drug susceptibility profiles of drug-resistant E. coli strains relative to the WT. Susceptibility profiles were defined on the basis of MIC inhibition curves (fig. S1). (B) Distribution of drug collateral sensitivity and collateral resistance for 23 drug-resistant E. coli strains (drugs from the same class are excluded). Throughout the figure, blue coloring refers to collateral sensitivity, orange coloring refers to collateral resistance, and white coloring refers to no change in susceptibility relative to WT. Drug abbreviations are shown in Table 1.

  • Fig. 3. Collateral sensitivity cycles.

    (A) Collateral sensitivity network of E. coli. Nodes of the network are the drugs, and the edges of the network represent collateral sensitivities resulting from resistance acquired to those drugs (Table 1). For example, if E. coli has evolved resistance to rifampicin (RIF), it displays collateral sensitivity to tetracycline (TET), minocycline (MIN), tigecycline (TGC), and trimethoprim (TRI). The color coding of the nodes (orange to blue) is proportional to the number of edges proceeding from a particular node and represents the number of drugs with collateral sensitivity. (B) Distribution of the number of potential collateral sensitivity cycles as a function of the number of drugs included in the cycle. (C) Drug pairs with reciprocal collateral sensitivity. The color coding of the nodes (orange to blue) is proportional to the number of collateral sensitivity pairs of which a given drug is a part (Table 1).

  • Fig. 4. Selective elimination of resistant E. coli strains by collateral sensitivity cycling.

    (A and B) Survival of WT E. coli strains and strains resistant to gentamicin or cefuroxime within a mixed population at various concentrations of (A) cefuroxime or (B) gentamicin. Colony-forming units (CFU) indicate the proportion of the mutant and WT cells in the mixed population. Results are means of three replicates ± SD. (C) Collateral sensitivity cycling of gentamicin and cefuroxime. A CFP-labeled WT population was exposed to gentamicin over a period of 8 days until a 32-fold increase in MICWT was achieved. At this point, the CFP-labeled gentamicin-resistant population was mixed with a YFP-labeled WT population, and treatment was switched to cefuroxime (4 μg/ml), resulting in the complete eradication of the CFP-labeled population. The surviving YFP-labeled population was then exposed to cefuroxime over an 8-day period until a 128-fold increase in MICWT was achieved. At this point, the YFP-labeled cefuroxime-resistant population was mixed with a CFP-labeled WT population and exposed to gentamicin (1 μg/ml), resulting in the eradication of the YFP-labeled cefuroxime-resistant population. The data were consistent across three replicates. Green color refers to treatment with gentamicin, and violet refers to treatment with cefuroxime. In the bottom panel, the proportion of the population that is CFP-labeled (green) or YFP-labeled (violet) is represented during the 17-day drug exposure period.

  • Fig. 5. Alteration of the killing dynamic and mutant selection window of resistant E. coli strains by collateral sensitivity.

    (A and B) In the presence of a drug to which resistant strains are collaterally sensitive, both gentamicin- and cefuroxime-resistant strains were eradicated faster than the WT. Results are means of three replicates ± SD. (C) Strains resistant to gentamicin or cefuroxime also had a lower MPC relative to WT when exposed to drugs to which they were collaterally sensitive.

  • Fig. 6. Collateral sensitivity profiles for E. coli clinical isolates.

    A heat map showing drug susceptibility profiles of two resistant E. coli pathogenic isolates (EC3770 and EC3856) and the MG1655 strain, which evolved resistance to eight drugs. Susceptibility profiles were defined on the basis of MIC inhibition curves for the resistant strains and WT (figs. S1, S4, and S5). Blue coloring refers to collateral sensitivity, orange coloring refers to collateral resistance, and white coloring refers to no change in susceptibility relative to WT. Drug abbreviations are listed in Table 1.

  • Table 1 List of antibiotics used in the study.
    AntibioticAbbreviationClassTarget
    AmikacinAMIAminoglycosideProtein synthesis, 30S
    GentamicinGENAminoglycosideProtein synthesis, 30S
    KanamycinKANAminoglycosideProtein synthesis, 30S
    StreptomycinSTRAminoglycosideProtein synthesis, 30S
    AmpicillinAMPβ-LactamCell wall
    AmoxicillinAMXβ-LactamCell wall
    PiperacillinPIPβ-LactamCell wall
    CefuroximeCFXβ-LactamCell wall
    CefepimeCFPβ-LactamCell wall
    Nalidixic acidNALQuinoloneDNA gyrase
    CiprofloxacinCIPQuinoloneDNA gyrase
    LevofloxacinLEVQuinoloneDNA gyrase
    TetracyclineTETTetracyclineProtein synthesis, 30S
    MinocyclineMINTetracyclineProtein synthesis, 30S
    TigecyclineTGCTetracyclineProtein synthesis, 30S
    ChloramphenicolCHLAmphenicolProtein synthesis, 50S
    AzithromycinAZYMacrolideProtein synthesis, 50S
    ColistinCOLPolymyxinLipopolysaccharide
    Polymyxin BPOLPolymyxinLipopolysaccharide
    FosfomycinFOSFosfomycinCell wall biogenesis
    RifampicinRIFRifamycinRNA polymerase
    NitrofurantoinNITNitrofuranMultiple
    TrimethoprimTRIDihydrofolate reductase inhibitorFolic acid biosynthesis

Supplementary Materials

  • www.sciencetranslationalmedicine.org/cgi/content/full/5/204/204ra132/DC1

    Table S1. Drug adaptation level and clinical breakpoints.

    Table S2. Drug common use.

    Table S3. List of possible collateral sensitivity cycles.

    Fig. S1. MIC inhibition curves for E. coli MG1655 resistant strains and WT.

    Fig. S2. Competition assay.

    Fig. S3. Collateral sensitivity and collateral resistance distribution.

    Fig. S4. MIC inhibition curves for E. coli EC3770 resistant strains and WT.

    Fig. S5. MIC inhibition curves for E. coli EC3856 resistant strains and WT.

  • Supplementary Material for:

    Use of Collateral Sensitivity Networks to Design Drug Cycling Protocols That Avoid Resistance Development

    Lejla Imamovic and Morten O. A. Sommer*

    *Corresponding author. E-mail: msom@bio.dtu.dk

    Published 25 September 2013, Sci. Transl. Med. 5, 204ra132 (2013)
    DOI: 10.1126/scitranslmed.3006609

    This PDF file includes:

    • Table S1. Drug adaptation level and clinical breakpoints.
    • Table S2. Drug common use.
    • Table S3. List of possible collateral sensitivity cycles.
    • Fig. S1. MIC inhibition curves for E. coli MG1655 resistant strains and WT.
    • Fig. S2. Competition assay.
    • Fig. S3. Collateral sensitivity and collateral resistance distribution.
    • Fig. S4. MIC inhibition curves for E. coli EC3770 resistant strains and WT.
    • Fig. S5. MIC inhibition curves for E. coli EC3856 resistant strains and WT.

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