Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Opinion
  • Published:

Predicting antibiotic resistance

Abstract

The treatment of bacterial infections is increasingly complicated because microorganisms can develop resistance to antimicrobial agents. This article discusses the information that is required to predict when antibiotic resistance is likely to emerge in a bacterial population. Indeed, the development of the conceptual and methodological tools required for this type of prediction represents an important goal for microbiological research. To this end, we propose the establishment of methodological guidelines that will allow researchers to predict the emergence of resistance to a new antibiotic before its clinical introduction.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Conceptual framework for predicting antibiotic resistance in a bacterial population.
Figure 2: Evolutionary trajectories in the emergence of resistance.
Figure 3: Understanding antibiotic resistance as a colonization factor.

Similar content being viewed by others

References

  1. Albert, T. J. et al. Mutation discovery in bacterial genomes: metronidazole resistance in Helicobacter pylori. Nature Methods 2, 951–953 (2005).

    Article  CAS  PubMed  Google Scholar 

  2. Chen, J. Y., Yan, Z., Shen, C., Fitzpatrick, D. P. & Wang, M. A systems biology approach to the study of Cisplatin drug resistance in ovarian cancers. J. Bioinform. Comput. Biol. 5, 383–405 (2007).

    Article  PubMed  Google Scholar 

  3. Burger, R. & Lande, R. On the distribution of the mean and variance of a quantitative trait under mutation-selection-drift balance. Genetics 138, 901–912 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Baquero, F. From pieces to patterns: evolutionary engineering in bacterial pathogens. Nature Rev. Microbiol. 2, 510–518 (2004).

    Article  CAS  Google Scholar 

  5. Baquero, F. Low-level antibacterial resistance: a gateway to clinical resistance. Drug Resist. Updat. 4, 93–105 (2001).

    Article  CAS  PubMed  Google Scholar 

  6. Luo, N. et al. Enhanced in vivo fitness of fluoroquinolone-resistant Campylobacter jejuni in the absence of antibiotic selection pressure. Proc. Natl Acad. Sci. USA 102, 541–546 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Andersson, D. I. & Levin, B. R. The biological cost of antibiotic resistance. Curr. Opin. Microbiol. 2, 489–493 (1999).

    Article  CAS  PubMed  Google Scholar 

  8. World Health Organization. World Health Organization Report in Infectious Diseases 2000 — Overcoming Antibiotic Resistance [online], (2000).

  9. Martinez, J. L. & Baquero, F. Interactions among strategies associated with bacterial infection: pathogenicity, epidemicity, and antibiotic resistance. Clin. Microbiol. Rev. 15, 647–679 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  10. Martinez, J. L. & Baquero, F. Mutation frequencies and antibiotic resistance. Antimicrob. Agents Chemother. 44, 1771–1777 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Olliver, A., Valle, M., Chaslus-Dancla, E. & Cloeckaert, A. Overexpression of the multidrug efflux operon acrEF by insertional activation with IS1 or IS10 elements in Salmonella enterica serovar typhimurium DT204 acrB mutants selected with fluoroquinolones. Antimicrob. Agents Chemother. 49, 289–301 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Davies, J. E. Origins, acquisition and dissemination of antibiotic resistance determinants. Ciba Found. Symp. 207, 15–35 (1997).

    CAS  PubMed  Google Scholar 

  13. Wright, G. D. The antibiotic resistome: the nexus of chemical and genetic diversity. Nature Rev. Microbiol. 5, 175–186 (2007).

    Article  CAS  Google Scholar 

  14. D'Acosta, V. M., McGrann, K. M., Hughes, D. W. & Wright, G. D. Sampling the antibiotic resistome. Science 311, 374–377 (2006).

    Article  Google Scholar 

  15. Xu, J. Microbial ecology in the age of genomics and metagenomics: concepts, tools, and recent advances. Mol. Ecol. 15, 1713–1731 (2006).

    Article  CAS  PubMed  Google Scholar 

  16. Remington, K. A., Heidelberg, K. & Venter, J. C. Taking metagenomic studies in context. Trends Microbiol. 13, 404 (2005).

    Article  CAS  PubMed  Google Scholar 

  17. Handelsman, J. Metagenomics: application of genomics to uncultured microorganisms. Microbiol. Mol. Biol. Rev. 68, 669–685 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Stoczko, M., Frere, J. M., Rossolini, G. M. & Docquier, J. D. Postgenomic scan of metallo-β-lactamase homologues in rhizobacteria: identification and characterization of BJP-1, a subclass B3 ortholog from Bradyrhizobium japonicum. Antimicrob. Agents Chemother. 50, 1973–1981 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Gomez, M. J. & Neyfakh, A. A. Genes involved in intrinsic antibiotic resistance of Acinetobacter baylyi. Antimicrob. Agents Chemother. 50, 3562–3567 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Salipante, S. J., Barlow, M. & Hall, B. G. GeneHunter, a transposon tool for identification and isolation of cryptic antibiotic resistance genes. Antimicrob. Agents Chemother. 47, 3840–3845 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Hall, B. G. Predicting the evolution of antibiotic resistance genes. Nature Rev. Microbiol. 2, 430–435 (2004).

    Article  CAS  Google Scholar 

  22. Barlow, M. & Hall, B. G. Experimental prediction of the evolution of cefepime resistance from the CMY-2 AmpC β-lactamase. Genetics 164, 23–29 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Barlow, M. & Hall, B. G. Experimental prediction of the natural evolution of antibiotic resistance. Genetics 163, 1237–1241 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Hall, B. G. & Barlow, M. Evolution of the serine β-lactamases: past, present and future. Drug Resist. Updat. 7, 111–123 (2004).

    Article  CAS  PubMed  Google Scholar 

  25. Galan, J. C., Morosini, M. I., Baquero, M. R., Reig, M. & Baquero, F. Haemophilus influenzae bla(ROB-1) mutations in hypermutagenic δampC Escherichia coli conferring resistance to cefotaxime and β-lactamase inhibitors and increased susceptibility to cefaclor. Antimicrob. Agents Chemother. 47, 2551–2557 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Negri, M. C., Lipsitch, M., Blazquez, J., Levin, B. R. & Baquero, F. Concentration-dependent selection of small phenotypic differences in TEM β-lactamase-mediated antibiotic resistance. Antimicrob. Agents Chemother. 44, 2485–2491 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Barlow, M. & Hall, B. G. Predicting evolutionary potential: in vitro evolution accurately reproduces natural evolution of the TEM β-lactamase. Genetics 160, 823–832 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Hall, B. G. Predicting evolution by in vitro evolution requires determining evolutionary pathways. Antimicrob. Agents Chemother. 46, 3035–3038 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Blazquez, J., Morosini, M. I., Negri, M. C. & Baquero, F. Selection of naturally occurring extended-spectrum TEM β-lactamase variants by fluctuating β-lactam pressure. Antimicrob. Agents Chemother. 44, 2182–2184 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Macia, M. D. et al. Efficacy and potential for resistance selection of antipseudomonal treatments in a mouse model of lung infection by hypermutable Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 50, 975–983 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Robicsek, A. et al. Fluoroquinolone-modifying enzyme: a new adaptation of a common aminoglycoside acetyltransferase. Nature Med. 12, 83–88 (2006).

    Article  CAS  PubMed  Google Scholar 

  32. Park, C. H., Robicsek, A., Jacoby, G. A., Sahm, D. & Hooper, D. C. Prevalence in the United States of aac(6)-Ib-cr encoding a ciprofloxacin-modifying enzyme. Antimicrob. Agents Chemother. 50, 3953–3955 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Martinez-Suarez, J. V. et al. Acquisition of antibiotic resistance plasmids in vivo by extraintestinal Salmonella spp. J. Antimicrob. Chemother. 20, 452–453 (1987).

    Article  CAS  PubMed  Google Scholar 

  34. Tomasz, A. & Munoz, R. β-Lactam antibiotic resistance in gram-positive bacterial pathogens of the upper respiratory tract: a brief overview of mechanisms. Microb. Drug Resist. 1, 103–109 (1995).

    Article  CAS  PubMed  Google Scholar 

  35. Spratt, B. G., Bowler, L. D., Zhang, Q. Y., Zhou, J. & Smith, J. M. Role of interspecies transfer of chromosomal genes in the evolution of penicillin resistance in pathogenic and commensal Neisseria species. J. Mol. Evol. 34, 115–125 (1992).

    Article  CAS  PubMed  Google Scholar 

  36. Baquero, M. R. et al. Polymorphic mutation frequencies in Escherichia coli: emergence of weak mutators in clinical isolates. J. Bacteriol. 186, 5538–5542 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Bjorkholm, B. et al. Mutation frequency and biological cost of antibiotic resistance in Helicobacter pylori. Proc. Natl Acad. Sci. USA 98, 14607–14612 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. LeClerc, J. E., Li, B., Payne, W. L. & Cebula, T. A. High mutation frequencies among Escherichia coli and Salmonella pathogens. Science 274, 1208–1211 (1996).

    CAS  PubMed  Google Scholar 

  39. Matic, I. et al. Highly variable mutation rates in commensal and pathogenic Escherichia coli. Science 277, 1833–1834 (1997).

    CAS  PubMed  Google Scholar 

  40. Oliver, A., Canton, R., Campo, P., Baquero, F. & Blazquez, J. High frequency of hypermutable Pseudomonas aeruginosa in cystic fibrosis lung infection. Science 288, 1251–1254 (2000).

    CAS  PubMed  Google Scholar 

  41. Macia, M. D. et al. Hypermutation is a key factor in development of multiple-antimicrobial resistance in Pseudomonas aeruginosa strains causing chronic lung infections. Antimicrob. Agents Chemother. 49, 3382–3386 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Macia, M. D., Borrell, N., Perez, J. L. & Oliver, A. Detection and susceptibility testing of hypermutable Pseudomonas aeruginosa strains with the Etest and disk diffusion. Antimicrob. Agents Chemother. 48, 2665–2672 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Galan, J. C. et al. Fosfomycin and rifampin disk diffusion tests for detection of Escherichia coli mutator strains. J. Clin. Microbiol. 42, 4310–4312 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Saint-Ruf, C. & Matic, I. Environmental tuning of mutation rates. Environ. Microbiol. 8, 193–199 (2006).

    Article  CAS  PubMed  Google Scholar 

  45. Gomez-Gomez, J. M., Blazquez, J., Baquero, F. & Martinez, J. L. H-NS and RpoS regulate emergence of Lac Ara+ mutants of Escherichia coli MCS2. J. Bacteriol. 179, 4620–4622 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Bjedov, I. et al. Stress-induced mutagenesis in bacteria. Science 300, 1404–1409 (2003).

    Article  CAS  PubMed  Google Scholar 

  47. McKenzie, G. J., Harris, R. S., Lee, P. L. & Rosenberg, S. M. The SOS response regulates adaptive mutation. Proc. Natl Acad. Sci. USA 97, 6646–6651 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Martinez, J. L. et al. Resistance to β-lactam/clavulanate. Lancet 2, 1473 (1987).

    Article  CAS  PubMed  Google Scholar 

  49. Kugelberg, E., Kofoid, E., Reams, A. B., Andersson, D. I. & Roth, J. R. Multiple pathways of selected gene amplification during adaptive mutation. Proc. Natl Acad. Sci. USA 103, 17319–17324 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Roth, J. R., Kugelberg, E., Reams, A. B., Kofoid, E. & Andersson, D. I. Origin of mutations under selection: the adaptive mutation controversy. Annu. Rev. Microbiol. 60, 477–501 (2006).

    Article  CAS  PubMed  Google Scholar 

  51. Bjorkman, J., Nagaev, I., Berg, O. G., Hughes, D. & Andersson, D. I. Effects of environment on compensatory mutations to ameliorate costs of antibiotic resistance. Science 287, 1479–1482 (2000).

    Article  CAS  PubMed  Google Scholar 

  52. Walsh, T. R. Combinatorial genetic evolution of multiresistance. Curr. Opin. Microbiol. 9, 476–482 (2006).

    Article  CAS  PubMed  Google Scholar 

  53. Beaber, J. W., Hochhut, B. & Waldor, M. K. SOS response promotes horizontal dissemination of antibiotic resistance genes. Nature 427, 72–74 (2004).

    Article  CAS  PubMed  Google Scholar 

  54. Alonso, A., Sanchez, P. & Martinez, J. L. Environmental selection of antibiotic resistance genes. Environ. Microbiol. 3, 1–9 (2001).

    Article  CAS  PubMed  Google Scholar 

  55. Wisplinghoff, H. et al. Related clones containing SCCmec type IV predominate among clinically significant Staphylococcus epidermidis isolates. Antimicrob. Agents Chemother. 47, 3574–3579 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Sherley, M., Gordon, D. M. & Collignon, P. J. Evolution of multi-resistance plasmids in Australian clinical isolates of Escherichia coli. Microbiology 150, 1539–1546 (2004).

    Article  CAS  PubMed  Google Scholar 

  57. Sherley, M., Gordon, D. M. & Collignon, P. J. Species differences in plasmid carriage in the Enterobacteriaceae. Plasmid 49, 79–85 (2003).

    Article  CAS  PubMed  Google Scholar 

  58. Escobar-Paramo, P. et al. Identification of forces shaping the commensal Escherichia coli genetic structure by comparing animal and human isolates. Environ. Microbiol. 8, 1975–1984 (2006).

    Article  CAS  PubMed  Google Scholar 

  59. Souza, V. & Eguiarte, L. E. Bacteria gone native vs. bacteria gone awry? plasmidic transfer and bacterial evolution. Proc. Natl Acad. Sci. USA 94, 5501–5503 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Datta, N. & Hughes, V. M. Plasmids of the same Inc groups in Enterobacteria before and after the medical use of antibiotics. Nature 306, 616–617 (1983).

    Article  CAS  PubMed  Google Scholar 

  61. Force, A. et al. The origin of subfunctions and modular gene regulation. Genetics 170, 433–446 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Shapiro, J. A. A 21st century view of evolution: genome system architecture, repetitive DNA, and natural genetic engineering. Gene 345, 91–100 (2005).

    Article  CAS  PubMed  Google Scholar 

  63. Lenski, R. E., Ofria, C., Pennock, R. T. & Adami, C. The evolutionary origin of complex features. Nature 423, 139–144 (2003).

    Article  CAS  PubMed  Google Scholar 

  64. Kashtan, N. & Alon, U. Spontaneous evolution of modularity and network motifs. Proc. Natl Acad. Sci. USA 102, 13773–13778 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Petri, R. & Schmidt-Dannert, C. Dealing with complexity: evolutionary engineering and genome shuffling. Curr. Opin. Biotechnol. 15, 298–304 (2004).

    Article  CAS  PubMed  Google Scholar 

  66. Di Ventura, B., Lemerle, C., Michalodimitrakis, K. & Serrano, L. From in vivo to in silico biology and back. Nature 443, 527–533 (2006).

    Article  CAS  PubMed  Google Scholar 

  67. Toussaint, A. & Merlin, C. Mobile elements as a combination of functional modules. Plasmid 47, 26–35 (2002).

    Article  CAS  PubMed  Google Scholar 

  68. Pepper, J. W. The evolution of evolvability in genetic linkage patterns. Biosystems 69, 115–126 (2003).

    Article  CAS  PubMed  Google Scholar 

  69. von Mering, C. et al. Genome evolution reveals biochemical networks and functional modules. Proc. Natl Acad. Sci. USA 100, 15428–15433 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Ettema, T., van der Oost, J. & Huynen, M. Modularity in the gain and loss of genes: applications for function prediction. Trends Genet. 17, 485–487 (2001).

    Article  CAS  PubMed  Google Scholar 

  71. Brent, R. & Bruck, J. 2020 computing: can computers help to explain biology? Nature 440, 416–417 (2006).

    Article  CAS  PubMed  Google Scholar 

  72. Stadler, B. M., Stadler, P. F., Wagner, G. P. & Fontana, W. The topology of the possible: formal spaces underlying patterns of evolutionary change. J. Theor. Biol. 213, 241–274 (2001).

    Article  CAS  PubMed  Google Scholar 

  73. Danchin, A. The bag or the spindle: the cell factory at the time of systems' biology. Microb. Cell Fact. 3, 13 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Andrianantoandro, E., Basu, S., Karig, D. K. & Weiss, R. Synthetic biology: new engineering rules for an emerging discipline. Mol. Syst. Biol. 2, 2006 0028 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Navarre, W. W. et al. Selective silencing of foreign DNA with low GC content by the H-NS protein in Salmonella. Science 313, 236–238 (2006).

    Article  CAS  PubMed  Google Scholar 

  76. Enne, V. I., Delsol, A. A., Roe, J. M. & Bennett, P. M. Evidence of antibiotic resistance gene silencing in Escherichia coli. Antimicrob. Agents Chemother. 50, 3003–3010 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Dieckmann, U. & Metz, J. A. Surprising evolutionary predictions from enhanced ecological realism. Theor. Popul. Biol. 69, 263–281 (2006).

    Article  PubMed  Google Scholar 

  78. Andersson, D. I. The biological cost of mutational antibiotic resistance: any practical conclusions? Curr. Opin. Microbiol. 9, 461–465 (2006).

    Article  CAS  PubMed  Google Scholar 

  79. Andersson, D. I. Persistence of antibiotic resistant bacteria. Curr. Opin. Microbiol. 6, 452–456 (2003).

    Article  CAS  PubMed  Google Scholar 

  80. Handel, A., Regoes, R. R. & Antia, R. The role of compensatory mutations in the emergence of drug resistance. PLoS Comput. Biol. 2, e137 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  81. O'Neill, A. J., Huovinen, T., Fishwick, C. W. & Chopra, I. Molecular genetic and structural modeling studies of Staphylococcus aureus RNA polymerase and the fitness of rifampin resistance genotypes in relation to clinical prevalence. Antimicrob. Agents Chemother. 50, 298–309 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Hurdle, J. G., O'Neill, A. J., Ingham, E., Fishwick, C. & Chopra, I. Analysis of mupirocin resistance and fitness in Staphylococcus aureus by molecular genetic and structural modeling techniques. Antimicrob. Agents Chemother. 48, 4366–4376 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Kussell, E., Kishony, R., Balaban, N. Q. & Leibler, S. Bacterial persistence: a model of survival in changing environments. Genetics 169, 1807–1814 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Levin, B. R. & Rozen, D. E. Non-inherited antibiotic resistance. Nature Rev. Microbiol. 4, 556–562 (2006).

    Article  CAS  Google Scholar 

  85. Ernande, B. & Dieckmann, U. The evolution of phenotypic plasticity in spatially structured environments: implications of intraspecific competition, plasticity costs and environmental characteristics. J. Evol. Biol. 17, 613–628 (2004).

    Article  CAS  PubMed  Google Scholar 

  86. von Gotz, F. et al. Expression analysis of a highly adherent and cytotoxic small colony variant of Pseudomonas aeruginosa isolated from a lung of a patient with cystic fibrosis. J. Bacteriol. 186, 3837–3847 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Wiuff, C. & Andersson, D. I. Antibiotic treatment in vitro of phenotypically tolerant bacterial populations. J. Antimicrob. Chemother. 59, 254–263 (2006).

    Article  CAS  PubMed  Google Scholar 

  88. Stewart, P. S. & Costerton, J. W. Antibiotic resistance of bacteria in biofilms. Lancet 358, 135–138 (2001).

    Article  CAS  PubMed  Google Scholar 

  89. Fux, C. A., Costerton, J. W., Stewart, P. S. & Stoodley, P. Survival strategies of infectious biofilms. Trends Microbiol. 13, 34–40 (2005).

    Article  CAS  PubMed  Google Scholar 

  90. Costerton, J. W., Stewart, P. S. & Greenberg, E. P. Bacterial biofilms: a common cause of persistent infections. Science 284, 1318–1322 (1999).

    Article  CAS  PubMed  Google Scholar 

  91. Ceri, H. et al. The Calgary Biofilm Device: new technology for rapid determination of antibiotic susceptibilities of bacterial biofilms. J. Clin. Microbiol. 37, 1771–1776 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Wiedemann, B., Pfeifle, D., Wiegand, I. & Janas, E. β-Lactamase induction and cell wall recycling in gram-negative bacteria. Drug Resist. Updat. 1, 223–226 (1998).

    Article  CAS  PubMed  Google Scholar 

  93. Reguera, J. A., Baquero, F., Berenguer, J., Martinez-Ferrer, M. & Martinez, J. L. β-Lactam-fosfomycin antagonism involving modification of penicillin-binding protein 3 in Pseudomonas aeruginosa. Antimicrob. Agents Chemother. 34, 2093–2096 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Dunne, W. M. Jr, & Hardin, D. J. Use of several inducer and substrate antibiotic combinations in a disk approximation assay format to screen for AmpC induction in patient isolates of Pseudomonas aeruginosa, Enterobacter spp., Citrobacter spp., and Serratia spp. J. Clin. Microbiol. 43, 5945–5949 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Ma, D. et al. Genes acrA and acrB encode a stress-induced efflux system of Escherichia coli. Mol. Microbiol. 16, 45–55 (1995).

    Article  CAS  PubMed  Google Scholar 

  96. Prouty, A. M., Brodsky, THAT IS, Falkow, S. & Gunn, J. S. Bile-salt-mediated induction of antimicrobial and bile resistance in Salmonella typhimurium. Microbiology 150, 775–783 (2004).

    Article  CAS  PubMed  Google Scholar 

  97. Grkovic, S., Brown, M. H. & Skurray, R. A. Regulation of bacterial drug export systems. Microbiol. Mol. Biol. Rev. 66, 671–701 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Lucchini, S. et al. H-NS Mediates the silencing of laterally acquired genes in bacteria. PLoS Pathog. 2, e81 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  99. Dorman, C. J. H-NS: a universal regulator for a dynamic genome. Nature Rev. Microbiol. 2, 391–400 (2004).

    Article  CAS  Google Scholar 

  100. Gomez-Gomez, J. M., Blazquez, J., Baquero, F. & Martinez, J. L. HNS mutant unveils the presence of a latent haemolytic activity in Escherichia coli K-12. Mol. Microbiol. 19, 909–910 (1996).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Thanks are given to F. Rojo, J. Pérez-Martín and B. Sánchez for comments on draft versions of this Perspective. J.L.M. was supported by grants LSHM-CT-2005-518152, LSHM-CT-2005-018705 and BIO2005-04278. F.B. was supported by grants LSHM-CT-2005-518152 and LSHM-CT-2005-018705. D.I.A. was supported by grants from the Swedish Research Council, LSHM-CT-2005-51852 and Uppsala University, Sweden.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to José L. Martínez.

Supplementary information

Related links

Related links

FURTHER INFORMATION

José Martínez's homepage

DATABASES

Entrez-Gene

Streptococcus pneumoniae

Neisseria gonorrhoeae

Escherichia coli

Glossary

Evolutionary trajectories

All the steps in evolution that are required to produce a given phenotype. Evolutionary trajectories depend on mutation, selection, drift, migration, ecological constraints and the previous history of the organism.

Evolvability

The ability of an organism or a gene to evolve and change its genotype and, consequently, the phenotype it encodes.

Fitness

The capability of an individual to survive and reproduce in a given ecosystem. Reproductive fitness is often measured as growth rate. Fitness is measured in comparison to other potential competitors.

Hypermutation

A mutation rate that is significantly higher than that observed for most members of a bacterial species.

Integron

A gene-capture unit that is present in plasmids, chromosomes and transposons. It contains an integrase that allows the capture of gene cassettes flanked by conserved repetitive sequences, an integration site and a strong promoter that allows expression of the genes that are present in the cassettes.

Metagenomics

Methodologies developed to describe all of the genetic elements that are present in a given ecosystem. Typically these methodologies are based on non-culture procedures.

Modularity

An attribute of a system that can be decomposed into a set of repeated, conserved cohesive entities that are loosely coupled.

Persistence

A non-inherited trait that is exhibited by a subpopulation of bacteria, characterized by slow growth coupled with an ability to survive antibiotic treatment.

Phenotypic resistance

Resistance that is not the consequence of a genetic event (mutation, horizontal gene transfer), but rather that is caused by the cells being in a particular physiological state.

SOS response

A specific response to DNA damage that involves the blocking of DNA replication and cell division as well as the induction of genes that are involved in DNA repair, recombination and mutation.

Synthetic biology

An area of research that is based on the combination of biological modules to build-up novel biological functions and systems. In some aspects it is complementary to systems biology.

System biology

The study of the interactions between the components (modules) of biological systems that has the aim of understanding these systems as a whole, using quantitative models.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Martínez, J., Baquero, F. & Andersson, D. Predicting antibiotic resistance. Nat Rev Microbiol 5, 958–965 (2007). https://doi.org/10.1038/nrmicro1796

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrmicro1796

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing