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Using ecological coexistence theory to understand antibiotic resistance and microbial competition

Nature Ecology & Evolution volume 5, pages 431–441 (2021)Cite this article

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Abstract

Tackling antibiotic resistance necessitates deep understanding of how resource competition within and between species modulates the fitness of resistant microbes. Recent advances in ecological coexistence theory offer a powerful framework to probe the mechanisms regulating intra- and interspecific competition, but the significance of this body of theory to the problem of antibiotic resistance has been largely overlooked. In this Perspective, we draw on emerging ecological theory to illustrate how changes in resource niche overlap can be equally important as changes in competitive ability for understanding costs of resistance and the persistence of resistant pathogens in microbial communities. We then show how different temporal patterns of resource and antibiotic supply, alongside trade-offs in competitive ability at high and low resource concentrations, can have diametrically opposing consequences for the coexistence and exclusion of resistant and susceptible strains. These insights highlight numerous opportunities for innovative experimental and theoretical research into the ecological dimensions of antibiotic resistance.

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Fig. 1: Partitioning costs of resistance mediated by constraints on resource uptake into competitive ability differences and niche overlap.
Fig. 2: Partitioning costs of resistance mediated by constraints on resource uptake into competitive ability differences and niche overlap.
Fig. 3: The effect of constant versus pulsed delivery of a growth-inhibiting antibiotic on coexistence between a susceptible strain (blue) and a resistant mutant (green).
Fig. 4: Coexistence and exclusion of a susceptible and resistant strain across antibiotic pulse intervals of increasing length but the same time-averaged concentration, and decreasing costs of resistance.
Fig. 5: Simulation results illustrating the interactive effects of antibiotic pulsing, resource pulse interval length and resource pulse size on competitive outcomes under different resource-uptake-associated costs of resistance (maximum growth trade-off in left panel; R* trade-off in right panel).

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References

  1. Levy, S. B. & Marshall, B. Antibacterial resistance worldwide: causes, challenges and responses. Nat. Med. 10, S122–S129 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Raymond, B. Five rules for resistance management in the antibiotic apocalypse, a road map for integrated microbial management. Evol. Appl. 12, 1079–1091 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  3. Perron, G. G., Inglis, R. F., Pennings, P. S. & Cobey, S. Fighting microbial drug resistance: a primer on the role of evolutionary biology in public health. Evol. Appl. 8, 211–222 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Andersen, S. B., Shapiro, B. J., Vandenbroucke-Grauls, C. & de Vos, M. G. J. Microbial evolutionary medicine: from theory to clinical practice. Lancet Infect. Dis. 19, e273–e283 (2019).

    Article  PubMed  Google Scholar 

  5. Gilbert, J. A. & Lynch, S. V. Community ecology as a framework for human microbiome research. Nat. Med. 25, 884–889 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Huijben, S., Chan, B. H. K., Nelson, W. A. & Read, A. F. The impact of within-host ecology on the fitness of a drug-resistant parasite. Evol. Med. Public Health 2018, 127–137 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Klümper, U. et al. Selection for antimicrobial resistance is reduced when embedded in a natural microbial community. ISME J. 13, 2927–2937 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  9. Hall, A. R., Angst, D. C., Schiessl, K. T. & Ackermann, M. Costs of antibiotic resistance - separating trait effects and selective effects. Evol. Appl. 8, 261–272 (2015).

    Article  PubMed  Google Scholar 

  10. Lehtinen, S. et al. Evolution of antibiotic resistance is linked to any genetic mechanism affecting bacterial duration of carriage. Proc. Natl Acad. Sci. USA 114, 1075–1080 (2017).

    Article  CAS  PubMed  Google Scholar 

  11. Colijn, C. et al. What is the mechanism for persistent coexistence of drug-susceptible and drug-resistant strains of Streptococcus pneumoniae? J. R. Soc. Interface 7, 905–919 (2010).

    Article  PubMed  Google Scholar 

  12. Blanquart, F., Lehtinen, S. & Fraser, C. An evolutionary model to predict the frequency of antibiotic resistance under seasonal antibiotic use, and an application to streptococcus pneumoniae. Proc. R. Soc. B 284, 20170679 (2017).

    Article  PubMed  Google Scholar 

  13. Holmes, A. H. et al. Understanding the mechanisms and drivers of antimicrobial resistance. Lancet 387, 176–187 (2016).

    Article  CAS  PubMed  Google Scholar 

  14. Blanquart, F. Evolutionary epidemiology models to predict the dynamics of antibiotic resistance. Evol. Appl. 12, 365–383 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Davies, N. G., Flasche, S., Jit, M. & Atkins, K. E. Within-host dynamics shape antibiotic resistance in commensal bacteria. Nat. Ecol. Evol. 3, 440–449 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Melnyk, A. H., Wong, A. & Kassen, R. The fitness costs of antibiotic resistance mutations. Evol. Appl. 8, 273–283 (2015).

    Article  PubMed  Google Scholar 

  17. Bjourkman, 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  Google Scholar 

  18. Petersen, A., Aarestrup, F. M. & Olsen, J. E. The in vitro fitness cost of antimicrobial resistance in Escherichia coli varies with the growth conditions. FEMS Microbiol. Lett. 299, 53–59 (2009).

    Article  CAS  PubMed  Google Scholar 

  19. Paulander, W., Maisnier-Patin, S. & Andersson, D. I. The fitness cost of streptomycin resistance depends on rpsL mutation, carbon source and RpoS (σS). Genetics 183, 539–546 (2009).

    Article  PubMed Central  Google Scholar 

  20. Hall, A. R., Iles, J. C. & MacLean, R. C. The fitness cost of rifampicin resistance in Pseudomonas aeruginosa depends on demand for RNA polymerase. Genetics 187, 817–822 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Trindade, S., Sousa, A. & Gordo, I. Antibiotic resistance and stress in the light of Fisher’s model. Evolution 66, 3815–3824 (2012).

    Article  PubMed  Google Scholar 

  22. Tilman, D. Resource Competition and Community Structure (Princeton Univ. Press, 1982).

  23. Chesson, P. Mechanisms of maintenance of species diversity. Annu. Rev. Ecol. Syst. 31, 343–366 (2000).

    Article  Google Scholar 

  24. Chase, J. & Leibold, M. Ecological Niches: Linking Classical and Contemporary Approaches (Univ. Chicago Press, 2003).

  25. Adler, P. B., Hillerislambers, J. & Levine, J. M. A niche for neutrality. Ecol. Lett. 10, 95–104 (2007).

    Article  PubMed  Google Scholar 

  26. HilleRisLambers, J., Adler, P. B., Harpole, W., Levine, J. M. & Mayfield, M. Rethinking community assembly through the lens of coexistence theory. Annu. Rev. Ecol. Evol. Syst. 43, 227–248 (2012).

    Article  Google Scholar 

  27. Letten, A. D., Ke, P.-J. & Fukami, T. Linking modern coexistence theory and contemporary niche theory. Ecol. Monogr. 87, 161–177 (2017).

    Article  Google Scholar 

  28. Barabás, G., D’Andrea, R. & Stump, S. M. Chesson’s coexistence theory. Ecol. Monogr. 88, 277–303 (2018).

    Article  Google Scholar 

  29. Chesson, P. Updates on mechanisms of maintenance of species diversity. J. Ecol. 106, 1773–1794 (2018).

    Article  Google Scholar 

  30. Ellner, S. P., Snyder, R. E., Adler, P. B. & Hooker, G. An expanded modern coexistence theory for empirical applications. Ecol. Lett. 22, 3–18 (2019).

    Article  PubMed  Google Scholar 

  31. Chesson, P. Multispecies competition in variable environments. Theor. Popul. Biol. 45, 227–276 (1994).

    Article  Google Scholar 

  32. Adler, P. B., HilleRisLambers, J., Kyriakidis, P. C., Guan, Q. & Levine, J. M. Climate variability has a stabilizing effect on the coexistence of prairie grasses. Proc. Natl Acad. Sci. USA 103, 12793–12798 (2006).

    Article  CAS  PubMed  Google Scholar 

  33. Yuan, C. & Chesson, P. The relative importance of relative nonlinearity and the storage effect in the lottery model. Theor. Popul. Biol. 105, 39–52 (2015).

    Article  PubMed  Google Scholar 

  34. Wale, N., Sim, D. G. & Read, A. F. A nutrient mediates intraspecific competition between rodent malaria parasites in vivo. Proc. R. Soc. B 284, 20171067 (2017).

    Article  PubMed  Google Scholar 

  35. Pereira, F. C. & Berry, D. Microbial nutrient niches in the gut. Environ. Microbiol. 19, 1366–1378 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Hester, E. R., Jetten, M. S. M., Welte, C. U. & Lücker, S. Metabolic overlap in environmentally diverse microbial communities. Front. Genet. 10, 989 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Smith, V. H. & Holt, R. D. Resource competition and within-host disease dynamics. Trends Ecol. Evol. 11, 386–389 (1996).

    Article  CAS  PubMed  Google Scholar 

  38. Hurtado, P. J., Hall, S. R. & Ellner, S. P. Infectious disease in consumer populations: dynamic consequences of resource-mediated transmission and infectiousness. Theor. Ecol. 7, 163–179 (2014).

    Article  Google Scholar 

  39. Cressler, C. E., Nelson, W. A., Day, T. & McCauley, E. Disentangling the interaction among host resources, the immune system and pathogens. Ecol. Lett. 17, 284–293 (2014).

    Article  PubMed  Google Scholar 

  40. Smith, V. H., Holt, R. D., Smith, M. S., Niu, Y. & Barfield, M. Resources, mortality, and disease ecology: importance of positive feedbacks between host growth rate and pathogen dynamics. Isr. J. Ecol. Evol. 61, 37–49 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Alonso, A. et al. Overexpression of the multidrug efflux pump SmeDEF impairs Stenotrophomonas maltophilia physiology. J. Antimicrob. Chemother. 53, 432–434 (2004).

    Article  CAS  PubMed  Google Scholar 

  42. Perkins, A. E. & Nicholson, W. L. Uncovering new metabolic capabilities of Bacillus subtilis using phenotype profiling of rifampin-resistant rpoB mutants. J. Bacteriol. 190, 807–814 (2008).

    Article  CAS  PubMed  Google Scholar 

  43. Martínez, J. L. & Rojo, F. Metabolic regulation of antibiotic resistance. FEMS Microbiol. Rev. 35, 768–789 (2011).

    Article  PubMed  Google Scholar 

  44. Zampieri, M. et al. Metabolic constraints on the evolution of antibiotic resistance. Mol. Syst. Biol. 13, 917 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Dunphy, L. J., Yen, P. & Papin, J. A. Integrated experimental and computational analyses reveal differential metabolic functionality in antibiotic-resistant Pseudomonas aeruginosa. Cell Syst. 8, 3-14.e3 (2019).

    PubMed  PubMed Central  Google Scholar 

  46. Webber, M. A. & Piddock, L. J. V. The importance of efflux pumps in bacterial antibiotic resistance. J. Antimicrob. Chemother. 51, 9–11 (2003).

    Article  CAS  PubMed  Google Scholar 

  47. Fitzsimmons, J. M., Schoustra, S. E., Kerr, J. T. & Kassen, R. Population consequences of mutational events: effects of antibiotic resistance on the r/K trade-off. Evol. Ecol. 24, 227–236 (2010).

    Article  Google Scholar 

  48. Baltrus, D. A. Exploring the costs of horizontal gene transfer. Trends Ecol. Evol. 28, 489–495 (2013).

    Article  PubMed  Google Scholar 

  49. San Millan, A. & MacLean, R. C. Fitness costs of plasmids: a limit to plasmid transmission. Microbiol. Spectrum 5, 65–79 (2017).

    Article  Google Scholar 

  50. Dennis, J. J. The evolution of IncP catabolic plasmids. Curr. Opin. Biotechnol. 16, 291–298 (2005).

    Article  CAS  PubMed  Google Scholar 

  51. Shintani, M. et al. Response of the Pseudomonas host chromosomal transcriptome to carriage of the IncP-7 plasmid pCAR1. Environ. Microbiol. 12, 1413–1426 (2009).

    PubMed  Google Scholar 

  52. San Millan, A. et al. Integrative analysis of fitness and metabolic effects of plasmids in Pseudomonas aeruginosa PAO1. ISME J. 12, 3014–3024 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Schlüter, A. et al. The 64508 bp IncP-1β antibiotic multiresistance plasmid pB10 isolated from a waste-water treatment plant provides evidence for recombination between members of different branches of the IncP-1β group. Microbiology 149, 3139–3153 (2003).

    Article  PubMed  Google Scholar 

  54. Chen, K. et al. Comparison of four Comamonas catabolic plasmids reveals the evolution of pBHB to catabolize haloaromatics. Appl. Environ. Microbiol. 82, 1401–1411 (2016).

    Article  CAS  PubMed Central  Google Scholar 

  55. Douglas, A. E. Fundamentals of Microbiome Science: How Microbes Shape Animal Biology (Princeton Univ. Press, 2018).

  56. Ibrahim, K. H., Gunderson, B. W., Hermsen, E. D., Hovde, L. B. & Rotschafer, J. C. Pharmacodynamics of pulse dosing versus standard dosing: in vitro metronidazole activity against Bacteroides fragilis and Bacteroides thetaiotaomicron. Antimicrob. Agents Chemother. 48, 4195–4199 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Peña-Miller, R., Lähnemann, D., Schulenburg, H., Ackermann, M. & Beardmore, R. Selecting against antibiotic-resistant pathogens: optimal treatments in the presence of commensal bacteria. Bull. Math. Biol. 74, 908–934 (2012).

    Article  PubMed  Google Scholar 

  58. Lin, W.-H. & Kussell, E. Complex interplay of physiology and selection in the emergence of antibiotic resistance. Curr. Biol. 26, 1486–1493 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Bauer, M., Graf, I. R., Ngampruetikorn, V., Stephens, G. J. & Frey, E. Exploiting ecology in drug pulse sequences in favour of population reduction. PLoS Comput. Biol. 13, e1005747 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Baker, C. M., Ferrari, M. J. & Shea, K. Beyond dose: pulsed antibiotic treatment schedules can maintain individual benefit while reducing resistance. Sci. Rep. 8, 5866 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Nev, O. A., Jepson, A., Beardmore, R. E. & Gudelj, I. Predicting community dynamics of antibiotic-sensitive and -resistant species in fluctuating environments. J. R. Soc. Interface 17, 20190776 (2020).

    Article  PubMed  Google Scholar 

  62. Kouyos, R. D. et al. The path of least resistance: aggressive or moderate treatment? Proc. R. Soc. B 281, 20140566 (2014).

    Article  PubMed  Google Scholar 

  63. Day, T. & Read, A. F. Does high-dose antimicrobial chemotherapy prevent the evolution of resistance? PLoS Comput. Biol. 12, e1004689 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Alexander, H. K. & MacLean, R. C. Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells. Proc. Natl Acad. Sci. USA 117, 19455–19464 (2020).

    Article  CAS  PubMed  Google Scholar 

  65. Zarrinpar, A., Chaix, A., Yooseph, S. & Panda, S. Diet and feeding pattern affect the diurnal dynamics of the gut microbiome. Cell Metab. 20, 1006–1017 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Thaiss, C. A., Zeevi, D., Levy, M., Segal, E. & Elinav, E. A day in the life of the meta-organism: diurnal rhythms of the intestinal microbiome and its host. Gut Microbes 6, 137–142 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Kaczmarek, J. L., Thompson, S. V. & Holscher, H. D. Complex interactions of circadian rhythms, eating behaviors, and the gastrointestinal microbiota and their potential impact on health. Nutr. Rev. 75, 673–682 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Turnbaugh, P. J. et al. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci. Transl. Med. 1, 6ra14 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Wu, G. D. et al. Linking long-term dietary patterns with gut microbial enterotypes. Science 334, 105–108 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).

    Article  CAS  PubMed  Google Scholar 

  71. Venable, E. B. et al. Effects of feeding management on the equine cecal microbiota. J. Equine Vet. Sci. 49, 113–121 (2017).

    Article  Google Scholar 

  72. Parris, D. J., Morgan, M. M. & Stewart, F. J. Feeding rapidly alters microbiome composition and gene transcription in the clownfish gut. Appl. Environ. Microbiol. 85, e02479-18 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Chesson, P. & Huntly, N. The roles of harsh and fluctuating conditions in the dynamics of ecological communities. Am. Nat. 150, 519–553 (1997).

    Article  CAS  PubMed  Google Scholar 

  74. Chesson, P. Quantifying and testing coexistence mechanisms arising from recruitment fluctuations. Theor. Popul. Biol. 64, 345–357 (2003).

    Article  PubMed  Google Scholar 

  75. Watson, S. P., Clements, M. O. & Foster, S. J. Characterization of the starvation-survival response of Staphylococcus aureus. J. Bacteriol. 180, 1750–1758 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Grover, J. Resource Competition Vol. 19 (Springer Science & Business Media, 1997).

  77. Letten, A. D., Dhami, M. K., Ke, P.-J. & Fukami, T. Species coexistence through simultaneous fluctuation-dependent mechanisms. Proc. Natl Acad. Sci. USA 115, 6745–6750 (2018).

    Article  CAS  PubMed  Google Scholar 

  78. Levison, M. E. & Levison, J. H. Pharmacokinetics and pharmacodynamics of antibacterial agents. Infect. Dis. Clin. N. Am. 23, 791–815 (2009).

    Article  Google Scholar 

  79. Maharjan, R. & Ferenci, T. The fitness costs and benefits of antibiotic resistance in drug-free microenvironments encountered in the human body. Environ. Microbiol. Rep. 9, 635–641 (2017).

    Article  CAS  PubMed  Google Scholar 

  80. Silva, A. S. et al. Evolutionary approaches to prolong progression-free survival in breast cancer. Cancer Res. 72, 6362–6370 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Song, T. et al. Fitness costs of rifampicin resistance in Mycobacterium tuberculosis are amplified under conditions of nutrient starvation and compensated by mutation in the β subunit of RNA polymerase. Mol. Microbiol. 91, 1106–1119 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Hart, S. P., Schreiber, S. J. & Levine, J. M. How variation between individuals affects species coexistence. Ecol. Lett. 19, 825–838 (2016).

    Article  PubMed  Google Scholar 

  83. Schreiber, S. J., Levine, J. M., Godoy, O., Kraft, N. J. & Hart, S. P. Does deterministic coexistence theory matter in a finite world? Insights from serpentine annual plants. Preprint at bioRxiv https://doi.org/10.1101/290882 (2020).

  84. Data from the ECDC Surveillance Atlas - Antimicrobial Resistance (European Centre for Disease Prevention and Control, 2020); http://go.nature.com/3oLrjOG

  85. Matteo, M. J., Granados, G., Olmos, M., Wonaga, A. & Catalano, M. Helicobacter pylori amoxicillin heteroresistance due to point mutations in PBP-1A in isogenic isolates. J. Antimicrob. Chemother. 61, 474–477 (2008).

    Article  CAS  PubMed  Google Scholar 

  86. Mongkolrattanothai, K. et al. Simultaneous carriage of multiple genotypes of Staphylococcus aureus in children. J. Med. Microbiol. 60, 317–322 (2011).

    Article  CAS  PubMed  Google Scholar 

  87. Folkvardsen, D. B. et al. Rifampin heteroresistance in Mycobacterium tuberculosis cultures as detected by phenotypic and genotypic drug susceptibility test methods. J. Clin. Microbiol. 51, 4220–4222 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  88. Kamng’ona, A. W. et al. High multiple carriage and emergence of Streptococcus pneumoniae vaccine serotype variants in Malawian children. BMC Infect. Dis. 15, 234 (2015).

  89. Andersson, D. I., Nicoloff, H. & Hjort, K. Mechanisms and clinical relevance of bacterial heteroresistance. Nat. Rev. Microbiol. 17, 479–496 (2019).

    Article  CAS  PubMed  Google Scholar 

  90. Chesson, P. & Kuang, J. J. The interaction between predation and competition. Nature 456, 235–238 (2008).

    Article  CAS  PubMed  Google Scholar 

  91. Gonze, D., Coyte, K. Z., Lahti, L. & Faust, K. Microbial communities as dynamical systems. Curr. Opin. Microbiol. 44, 41–49 (2018).

    Article  PubMed  Google Scholar 

  92. Godoy, O., Kraft, N. J. B. & Levine, J. M. Phylogenetic relatedness and the determinants of competitive outcomes. Ecol. Lett. 17, 836–844 (2014).

    Article  PubMed  Google Scholar 

  93. Kraft, N. J. B., Godoy, O. & Levine, J. M. Plant functional traits and the multidimensional nature of species coexistence. Proc. Natl. Acad. Sci. USA 112, 797–802 (2015).

    Article  CAS  PubMed  Google Scholar 

  94. Hart, S. P., Freckleton, R. P. & Levine, J. M. How to quantify competitive ability. J. Ecol. 106, 1902–1909 (2018).

    Article  Google Scholar 

  95. Hallinen, K. M., Karslake, J. & Wood, K. B. Delayed antibiotic exposure induces population collapse in enterococcal communities with drug-resistant subpopulations. eLife 9, e52813 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Gould, A. L. et al. Microbiome interactions shape host fitness. Proc. Natl Acad. Sci. USA 115, E11951–E11960 (2018).

    Article  CAS  PubMed  Google Scholar 

  97. Torres-Barceló, C. & Hochberg, M. E. Evolutionary rationale for phages as complements of antibiotics. Trends Microbiol. 24, 249–256 (2016).

    Article  PubMed  Google Scholar 

  98. Burmeister, A. R. et al. Pleiotropy complicates a trade-off between phage resistance and antibiotic resistance. Proc. Natl Acad. Sci. USA 117, 11207–11216 (2020).

    Article  CAS  PubMed  Google Scholar 

  99. Butler, S. & O’Dwyer, J. P. Stability criteria for complex microbial communities. Nat. Commun. 9, 2970 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  100. Estrela, S. & Brown, S. P. Community interactions and spatial structure shape selection on antibiotic resistant lineages. PLoS Comput. Biol. 14, e1006179 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank D. McLeod, S. Bonhoeffer and the Pathogen Ecology group at ETH for thoughtful discussions and comments on an earlier draft of this manuscript. This project received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skodowska-Curie grant agreement no. 750779.

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  1. School of Biological Sciences, University of Queensland, Brisbane, Queensland, Australia

    Andrew D. Letten

  2. Department of Environmental Systems Science, Institute of Integrative Biology, ETH Zürich, Zürich, Switzerland

    Andrew D. Letten & Alex R. Hall

  3. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA

    Jonathan M. Levine

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A.D.L., A.R.H. and J.M.L. conceived the study. A.D.L. performed simulations and analysis. A.D.L., A.R.H. and J.M.L. wrote the manuscript.

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Correspondence to Andrew D. Letten.

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Letten, A.D., Hall, A.R. & Levine, J.M. Using ecological coexistence theory to understand antibiotic resistance and microbial competition. Nat Ecol Evol 5, 431–441 (2021). https://doi.org/10.1038/s41559-020-01385-w

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