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Drug interactions and the evolution of antibiotic resistance

Abstract

Large-scale, systems biology approaches now allow us to systematically map synergistic and antagonistic interactions between drugs. Consequently, drug antagonism is emerging as a powerful tool to study biological function and relatedness between cellular components as well as to uncover mechanisms of drug action. Furthermore, theoretical models and new experiments suggest that antagonistic interactions between antibiotics can counteract the evolution of drug resistance.

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Figure 1: A functional relationship between pathways can be revealed by the direct epistasis link between them and by the similarity of their epistasis interaction patterns with other pathways.
Figure 2: Suppressive drug combinations can reverse selection for resistance.
Figure 3: Drug interactions affect the mutant selection window.
Figure 4: Evolution in various antibiotic combinations reveals an accelerated rate of adaptation in synergistic drug pairs.

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References

  1. Hickman, M. & Cairns, J. The centenary of the one-gene one-enzyme hypothesis. Genetics 163, 839–841 (2003).

    PubMed  PubMed Central  Google Scholar 

  2. Loewe, S. Die quantitation probleme der pharmakologie. Ergeb. Physiol. 27, 47–187 (1928).

    Article  Google Scholar 

  3. Bliss, C. I. The toxicity of poisons applied jointly. Ann. Appl. Biol. 26, 585–615 (1939).

    Article  CAS  Google Scholar 

  4. Greco, W. R., Bravo, G. & Parsons, J. C. The search for synergy: a critical review from a response surface perspective. Pharmacol. Rev. 47, 331–385 (1995).

    CAS  PubMed  Google Scholar 

  5. Frankel, W. N. & Schork, N. J. Who's afraid of epistasis? Nature Genet. 14, 371–373 (1996).

    Article  CAS  Google Scholar 

  6. Phillips, P. C. The language of gene interaction. Genetics 149, 1167–1171 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Phillips, P. C., Otto, S. P. & Whitlock, M. C. in Epistasis and the Evolutionary Process (Oxford Univ. Press, New York, 2000).

    Google Scholar 

  8. Brodie, E. D. III. in Epistasis and the Evolutionary Process (Oxford Univ. Press, New York, 2000).

    Google Scholar 

  9. Mani, R., Onge, R. P. S., Hartman, J. L., Giaever, G. & Roth, F. P. Defining genetic interaction. Proc. Natl Acad. Sci. USA 105, 3461–3466 (2008).

    Article  CAS  Google Scholar 

  10. Chait, R., Craney, A. & Kishony, R. Antibiotic interactions that select against resistance. Nature 446, 668–671 (2007).

    Article  CAS  Google Scholar 

  11. Hegreness, M., Shoresh, N., Damian, D., Hartl, D. & Kishony, R. Accelerated evolution of resistance in multidrug environments. Proc. Natl Acad. Sci. USA 105, 13977–13981 (2008).

    Article  CAS  Google Scholar 

  12. Michel, J.-B., Yeh, P., Chait, R., Moellering, R. C. & Kishony, R. Drug interactions modulate the potential for evolution of resistance. Proc. Natl Acad. Sci. USA 105, 14918–14923 (2008).

    Article  CAS  Google Scholar 

  13. Tong, A. H. Y. et al. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294, 2364–2368 (2001).

    Article  CAS  Google Scholar 

  14. Tong, A. H. Y. et al. Global mapping of the yeast genetic interaction network. Science 303, 808–813 (2004).

    Article  CAS  Google Scholar 

  15. Pan, X. W. et al. A DNA integrity network in the yeast Saccharomyces cerevisiae. Cell 124, 1069–1081 (2006).

    Article  CAS  Google Scholar 

  16. Lehner, B., Crombie, C., Tischler, J., Fortunato, A. & Fraser, A. G. Systematic mapping of genetic interactions in Caenorhabditis elegans identifies common modifiers of diverse signaling pathways. Nature Genet. 38, 896–903 (2006).

    Article  CAS  Google Scholar 

  17. Tischler, J., Lehner, B. & Fraser, A. G. Evolutionary plasticity of genetic interaction networks. Nature Genet. 40, 390–391 (2008).

    Article  CAS  Google Scholar 

  18. Ye, P. et al. Gene function prediction from congruent synthetic lethal interactions in yeast. Mol. Syst. Biol. 1, 2005.0026 (2005).

  19. Ooi, S. L. et al. Global synthetic-lethality analysis and yeast functional profiling. Trends Genet. 22, 56–63 (2006).

    Article  CAS  Google Scholar 

  20. Meluh, P. B. et al. Analysis of genetic interactions on a genome-wide scale in budding yeast: diploid-based synthetic lethality analysis by microarray. Methods Mol. Biol. 416, 221–247 (2008).

    Article  CAS  Google Scholar 

  21. Sanjuan, R., Moya, A. & Elena, S. F. The contribution of epistasis to the architecture of fitness in an RNA virus. Proc. Natl Acad. Sci. USA 101, 15376–15379 (2004).

    Article  CAS  Google Scholar 

  22. Drees, B. L. et al. Derivation of genetic interaction networks from quantitative phenotype data. Genome Biol. 6, R38 (2005).

    Article  Google Scholar 

  23. Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–519 (2005).

    Article  CAS  Google Scholar 

  24. Collins, S. R., Schuldiner, M., Krogan, N. J. & Weissman, J. S. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 7, R63 (2006).

    Article  Google Scholar 

  25. St Onge, R. P. et al. Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions. Nature Genet. 39, 199–206 (2007).

    Article  CAS  Google Scholar 

  26. Jasnos, L. & Korona, R. Epistatic buffering of fitness loss in yeast double deletion strains. Nature Genet. 39, 550–554 (2007).

    Article  CAS  Google Scholar 

  27. Typas, A. et al. High-throughput, quantitative analyses of genetic interactions in E. coli. Nature Methods 5, 781–787 (2008).

    Article  CAS  Google Scholar 

  28. Roguev, A. et al. Conservation and rewiring of functional modules revealed by an epistasis map in fission yeast. Science 322, 405–410 (2008).

    Article  CAS  Google Scholar 

  29. Collins, S. R. et al. Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map. Nature 446, 806–810 (2007).

    Article  CAS  Google Scholar 

  30. Roguev, A., Wiren, M., Weissman, J. S. & Krogan, N. J. High-throughput genetic interaction mapping in the fission yeast Schizosaccharomyces pombe. Nature Methods 4, 861–866 (2007).

    Article  CAS  Google Scholar 

  31. DeLuna, A. et al. Exposing the fitness contribution of duplicated genes. Nature Genet. 40, 676–681 (2008).

    Article  CAS  Google Scholar 

  32. Breslow, D. K. et al. A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nature Methods 5, 711–718 (2008).

    Article  CAS  Google Scholar 

  33. Segre, D., DeLuna, A., Church, G. M. & Kishony, R. Modular epistasis in yeast metabolism. Nature Genet. 37, 77–83 (2005).

    Article  CAS  Google Scholar 

  34. Bandyopadhyay, S., Kelley, R., Krogan, N. J. & Ideker, T. Functional maps of protein complexes from quantitative genetic interaction data. PloS Comput. Biol. 4, e1000065 (2008).

    Article  Google Scholar 

  35. Yeh, P., Tschumi, A. I. & Kishony, R. Functional classification of drugs by properties of their pairwise interactions. Nature Genet. 38, 489–494 (2006).

    Article  CAS  Google Scholar 

  36. Lehar, J. et al. Chemical combination effects predict connectivity in biological systems. Mol. Syst. Biol. 3, 80 (2007).

    Article  Google Scholar 

  37. Yeh, P. & Kishony, R. Networks from drug–drug surfaces. Mol. Syst. Biol. 3, 85 (2007).

    Article  Google Scholar 

  38. Pillai, S. K., Moellering, R. C. & Eliopoulos, G. M. in Antibiotics in Laboratory Medicine (ed. Lorian, V.) 365–440 (Lippincott Williams & Wilkins, Philadelphia, 2005).

    Google Scholar 

  39. Fraser, T. R. The antagonism between the actions of active substances. Br. Med. J. 2, 485–487 (1872).

    Article  CAS  Google Scholar 

  40. Eagle, H. & Musselman, A. D. The rate of bactericidal action of penicillin in vitro as a function of its concentration, and its paradoxically reduced activity at high concentrations against certain organisms. J. Exp. Med. 88, 99–131 (1948).

    Article  CAS  Google Scholar 

  41. Smith, J. T. The mode of action of 4-quinolones and possible mechanisms of resistance. J. Antimicrob. Chemother. 18, 21–29 (1986).

    Article  CAS  Google Scholar 

  42. Lewin, C. S., Morrissey, I. & Smith, J. T. The mode of action of quinolones: the paradox in activity of low and high concentrations and activity in the anaerobic environment. Eur. J. Clin. Microbiol. Infect. Dis. 10, 240–248 (1991).

    Article  CAS  Google Scholar 

  43. Baquero, F. Resistance to quinolones in gram-negative micororganisms: mechanisms and prevention. Eur. Urol. 17, 3–12 (1990).

    Article  Google Scholar 

  44. Baquero, F. & Negri, M. C. Strategies to minimize the development of antibiotic resistance. J. Chemother. 9, 29–37 (1997).

    CAS  PubMed  Google Scholar 

  45. Dong, Y. Z., Zhao, X. L., Domagala, J. & Drlica, K. Effect of fluoroquinolone concentration on selection of resistant mutants of Mycobacterium bovis BCG and Staphylococcus aureus. Antimicrob. Agents. Chemother. 43, 1756–1758 (1999).

    Article  CAS  Google Scholar 

  46. Drlica, K. The mutant selection window and antimicrobial resistance. J. Antimicrob. Chemother. 52, 11–17 (2003).

    Article  CAS  Google Scholar 

  47. Dong, Y. Z., Zhao, X. L., Kreiswirth, B. N. & Drlica, K. Mutant prevention concentration as a measure of antibiotic potency: studies with clinical isolates of Mycobacterium tuberculosis. Antimicrob. Agents Chemother. 44, 2581–2584 (2000).

    Article  CAS  Google Scholar 

  48. Blondeau, J. M., Zhao, X. L., Hansen, G. & Drlica, K. Mutant prevention concentrations of fluoroquinolones for clinical isolates of Streptococcus pneumoniae. Antimicrob. Agents Chemother. 45, 433–438 (2001).

    Article  CAS  Google Scholar 

  49. Zhao, X. L. & Drlica, K. Restricting the selection of antibiotic-resistant mutant bacteria: measurement and potential use of the mutant selection window. J. Infect. Dis. 185, 561–565 (2002).

    Article  Google Scholar 

  50. Randall, L. P., Cooles, S. W., Piddock, L. J. V. & Woodward, M. J. Mutant prevention concentrations of ciprofloxacin and enrofloxacin for Salmonella enterica. J. Antimicrob. Chemother. 54, 688–691 (2004).

    Article  CAS  Google Scholar 

  51. Metzler, K. et al. Comparison of minimal inhibitory and mutant prevention drug concentrations of 4 fluoroquinolones against clinical isolates of methicillin-susceptible and -resistant Staphylococcus aureus. Int. J. Antimicrob. Agents 24, 161–167 (2004).

    Article  CAS  Google Scholar 

  52. Linde, H. J. & Lehn, N. Mutant prevention concentration of nalidixic acid, ciprofloxacin, clinafloxacin, levofloxacin, norfloxacin, ofloxacin, sparfloxacin or trovafloxacin for Escherichia coli under different growth conditions. J. Antimicrob. Chemother. 53, 252–257 (2004).

    Article  CAS  Google Scholar 

  53. Li, X. Y., Mariano, N., Rahal, J. J., Urban, C. M. & Drlica, K. Quinolone-resistant Haemophilus influenzae: determination of mutant selection window for ciprofloxacin, garenoxacin, levofloxacin, and moxifloxacin. Antimicrob. Agents Chemother. 48, 4460–4462 (2004).

    Article  CAS  Google Scholar 

  54. Marcusson, L. L., Olofsson, S. K., Lindgren, P. K., Cars, O. & Hughes, D. Mutant prevention concentrations of ciprofloxacin for urinary tract infection isolates of Escherichia coli. J. Antimicrob. Chemother. 55, 938–943 (2005).

    Article  CAS  Google Scholar 

  55. Rodriguez-Martinez, J. M. et al. Mutant prevention concentrations of fluoroquinolones for Enterobacteriaceae expressing the plasmid-carried quinolone resistance determinant qnrA1. Antimicrob. Agents Chemother. 51, 2236–2239 (2007).

    Article  CAS  Google Scholar 

  56. Firsov, A. A. et al. In vitro pharmacodynamic evaluation of the mutant selection window hypothesis using four fluoroquinolones against Staphylococcus aureus. Antimicrob. Agents Chemother. 47, 1604–1613 (2003).

    Article  CAS  Google Scholar 

  57. Firsov, A. A., Lubenko, I. Y., Smirnova, M. V., Strukova, E. N. & Zinner, S. H. Enrichment of fluoroquinolone-resistant Staphylococcus aureus: oscillating ciprofloxacin concentrations simulated at the upper and lower portions of the mutant selection window. Antimicrob. Agents Chemother. 52, 1924–1928 (2008).

    Article  CAS  Google Scholar 

  58. Zhanel, G. G., Mayer, M., Laing, N. & Adam, H. J. Mutant prevention concentrations of levofloxacin alone and in combination with azithromycin, ceftazidime, colistin (polymyxin E), meropenem, piperacillin-tazobactam, and tobramycin against Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 50, 2228–2230 (2006).

    Article  CAS  Google Scholar 

  59. Deeks, S. G. Treatment of anti retroviral-drug-resistant HIV-1 infection. Lancet 362, 2002–2011 (2003).

    Article  CAS  Google Scholar 

  60. Nosten, F. & Brasseur, P. Combination therapy for malaria: the way forward? Drugs 62, 1315–1329 (2002).

    Article  CAS  Google Scholar 

  61. Klein, M. & Schorr, S. E. The role of bacterial resistance in antibiotic synergism and antagonism. J. Bacteriol. 65, 454–465 (1953).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Jawetz, E. Infectious diseases: problems of antimicrobial therapy. Ann. Rev. Med. 5, 1–26 (1954).

    Article  CAS  Google Scholar 

  63. Lipsitch, M. & Levin, B. R. The population dynamics of antimicrobial chemotherapy. Antimicrob. Agents Chemother. 41, 363–373 (1997).

    Article  CAS  Google Scholar 

  64. Lepper, M. H. & Dowling, H. F. Treatment of pneumococcic meningitis with penicillin compared with penicillin plus aureomycin; studies including observations on an apparent antagonism between penicillin and aureomycin. AMA Arch. Intern. Med. 88, 489–494 (1951).

    Article  CAS  Google Scholar 

  65. Kishony, R. & Leibler, S. Environmental stresses can alleviate the average deleterious effect of mutations. J. Biol. 2, 14 (2003).

    Article  Google Scholar 

  66. Blagosklonny, M. V. Drug-resistance enables selective killing of resistant leukemia cells: exploiting of drug resistance instead of reversal. Leukemia 13, 2031–2035 (1999).

    Article  CAS  Google Scholar 

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Acknowledgements

We thank A. DeLuna, J.-B. Michel, R. Chait, N. Shoresh and T. Bollenbach for helpful discussion and comments on the manuscript. R. Chait contributed many of the figures for Box 1. This work was supported in part by a National Institutes of Health postdoctoral fellowship to P.J.Y., by National Science Foundation and National Defense Science and Engineering graduate fellowships to A.P.A. and by National Institutes of Health Grant R01GM081617 to R.K.

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Correspondence to Roy Kishony.

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Yeh, P., Hegreness, M., Aiden, A. et al. Drug interactions and the evolution of antibiotic resistance. Nat Rev Microbiol 7, 460–466 (2009). https://doi.org/10.1038/nrmicro2133

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