The spread of antibiotic resistance, a major threat to human health, is poorly understood. Simple population-level models of bacterial transmission predict that above a certain rate of antibiotic consumption in a population, resistant bacteria should completely eliminate non-resistant strains, while below this threshold they should be unable to persist at all. This prediction stands at odds with empirical evidence showing that resistant and non-resistant strains coexist stably over a wide range of antibiotic consumption rates. Not knowing what drives this long-term coexistence is a barrier to developing evidence-based strategies for managing the spread of resistance. Here, we argue that competition between resistant and sensitive pathogens within individual hosts gives resistant pathogens a relative fitness benefit when they are rare, promoting coexistence between strains at the population level. To test this hypothesis, we embed mechanistically explicit within-host dynamics in a structurally neutral pathogen transmission model. Doing so allows us to reproduce patterns of resistance observed in the opportunistic pathogens Escherichia coli and Streptococcus pneumoniae across European countries and to identify factors that may shape resistance evolution in bacteria by modulating the intensity and outcomes of within-host competition.
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C++ code for the individual-based model is available at https://github.com/nicholasdavies/tinyhost.
Goossens, H., Ferech, M., Vander Stichele, R. & Elseviers, M. Outpatient antibiotic use in Europe and association with resistance: a cross-national database study. Lancet 365, 579–587 (2005).
Antimicrobial Consumption Database (ESAC-Net) (European Centre for Disease Prevention and Control, 2018); http://ecdc.europa.eu/en/healthtopics/antimicrobial_resistance/esac-net-database/Pages/Antimicrobial-consumption-rates-by-country.aspx
Data from the ECDC Surveillance Atlas—Antimicrobial Resistance (European Centre for Disease Prevention and Control, 2016); https://ecdc.europa.eu/en/antimicrobial-resistance/surveillance-and-disease-data/data-ecdc
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).
Hardin, G. The competitive exclusion principle. Science 131, 1292–1297 (1960).
Cobey, S. et al. Host population structure and treatment frequency maintain balancing selection on drug resistance. J. R. Soc. Interface 14, 20170295 (2017).
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).
Austin, D. J., Kristinsson, K. G. & Anderson, R. M. The relationship between the volume of antimicrobial consumption in human communities and the frequency of resistance. Proc. Natl Acad. Sci. USA 96, 1152–1156 (1999).
United Nations High-Level Meeting on Antimicrobial Resistance (World Health Organization, 2016); http://www.who.int/mediacentre/events/2016/antimicrobial-resistance/en/%5Cn http://www.who.int/antimicrobial-resistance/events/UNGA-meeting-amr-sept2016/en/
O’Neill, J. Tackling Drug-Resistant Infections Globally: Final Report and Recommendations https://amr-review.org (2016).
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).
Turner, P. et al. Improved detection of nasopharyngeal cocolonization by multiple pneumococcal serotypes by use of latex agglutination or molecular serotyping by microarray. J. Clin. Microbiol. 49, 1784–1789 (2011).
Martinez-Medina, M. et al. Molecular diversity of Escherichia coli in the human gut: new ecological evidence supporting the role of adherent-invasive E. coli (AIEC) in Crohn’s disease. Inflamm. Bowel Dis. 15, 872–882 (2009).
Mongkolrattanothai, K. et al. Simultaneous carriage of multiple genotypes of Staphylococcus aureus in children. J. Med. Microbiol. 60, 317–322 (2011).
Gordon, D. M., O’Brien, C. L. & Pavli, P. Escherichia coli diversity in the lower intestinal tract of humans. Environ. Microbiol. Rep. 7, 642–648 (2015).
Chaban, B. et al. Characterization of the upper respiratory tract microbiomes of patients with pandemic H1N1 influenza. PLoS ONE 8, e69559 (2013).
Ederveen, T. H. A. et al. Haemophilus is overrepresented in the nasopharynx of infants hospitalized with RSV infection and associated with increased viral load and enhanced mucosal CXCL8 responses. Microbiome 6, 10 (2018).
Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).
Negri, M. C., Lipsitch, M., Blázquez, J., Levin, B. R. & Baquero, F. Concentration-dependent selection of small phenotypic differences in TEM beta-lactamase-mediated antibiotic resistance. Antimicrob. Agents Chemother. 44, 2485–2491 (2000).
Wargo, A. R., Huijben, S., de Roode, J. C., Shepherd, J. & Read, A. F. Competitive release and facilitation of drug-resistant parasites after therapeutic chemotherapy in a rodent malaria model. Proc. Natl Acad. Sci. USA 104, 19914–19919 (2007).
Melnyk, A. H., Wong, A. & Kassen, R. The fitness costs of antibiotic resistance mutations. Evol. Appl. 8, 273–283 (2015).
Smani, Y. et al. In vitro and in vivo reduced fitness and virulence in ciprofloxacin-resistant Acinetobacter baumannii. Clin. Microbiol. Infect. 18, 1–4 (2012).
Birch, L. C. The meanings of competition. Am. Nat. 91, 5–18 (1957).
Hastings, I. M. Complex dynamics and stability of resistance to antimalarial drugs. Parasitology 132, 615–624 (2006).
Ayala, F. J. Competition between species: frequency dependence. Science 171, 820–824 (1971).
Ayala, F. J. & Campbell, C. A. Frequency-dependent selection. Annu. Rev. Ecol. Syst. 5, 115–138 (1974).
Cobey, S. & Lipsitch, M. Niche and neutral effects of acquired immunity permit coexistence of pneumococcal serotypes. Science 335, 1376–1380 (2012).
Lipsitch, M., Colijn, C., Cohen, T., Hanage, W. P. & Fraser, C. No coexistence for free: neutral null models for multistrain pathogens. Epidemics 1, 2–13 (2009).
Sinervo, B. & Lively, C. M. The rock–paper–scissors game and the evolution of alternative male strategies. Nature 380, 240–243 (1996).
Gigord, L. D. B., Macnair, M. R. & Smithson, A. Negative frequency-dependent selection maintains a dramatic flower color polymorphism in the rewardless orchid Dactylorhiza sambucina (L.) Soò. Proc. Natl Acad. Sci. USA 98, 6253–6255 (2001).
Rainey, P. B. & Travisano, M. Adaptive radiation in a heterogeneous environment. Nature 394, 69–72 (1998).
Wale, N. et al. Resource limitation prevents the emergence of drug resistance by intensifying within-host competition.Proc. Natl Acad. Sci. USA 114, 13774–13779 (2017).
Lewnard, J. A. et al. Impact of antimicrobial treatment for acute otitis media on carriage dynamics of penicillin-susceptible and penicillin–non-susceptible Streptococcus pneumoniae. J. Infect. Dis. 218, 1356–1366 (2018).
Andersson, D. I. The biological cost of mutational antibiotic resistance: any practical conclusions? Curr. Opin. Microbiol. 9, 461–465 (2006).
Andersson, D. I. & Hughes, D. Antibiotic resistance and its cost: is it possible to reverse resistance? Nat. Rev. Microbiol. 8, 260–271 (2010).
Flasche, S. et al. The impact of specific and non-specific immunity on the ecology of Streptococcus pneumoniae and the implications for vaccination. Proc. R. Soc. B 280, 20131939 (2013).
MacFadden, D. R., McGough, S. F., Fisman, D., Santillana, M. & Brownstein, J. S. Antibiotic resistance increases with local temperature. Nat. Clim. Change 8, 510–514 (2018).
Dietz, K. Epidemiologic interference of virus populations. J. Math. Biol. 8, 291–300 (1979).
Gupta, S., Swinton, J. & Anderson, R. M. Theoretical studies of the effects of heterogeneity in the parasite population on the transmission dynamics of malaria. Proc. R. Soc. B 256, 231–238 (1994).
Lipsitch, M. Vaccination against colonizing bacteria with multiple serotypes. Proc. Natl Acad. Sci. USA 94, 6571–6576 (1997).
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).
Colijn, C. & Cohen, T. How competition governs whether moderate or aggressive treatment minimizes antibiotic resistance. eLife 4, e10559 (2015).
Smith, E. E. et al. Genetic adaptation by Pseudomonas aeruginosa to the airways of cystic fibrosis patients. Proc. Natl Acad. Sci. USA 103, 8487–8492 (2006).
Yang, L. et al. Evolutionary dynamics of bacteria in a human host environment. Proc. Natl Acad. Sci. USA 108, 7481–7486 (2011).
Lehtinen, S. et al. Mechanisms that maintain coexistence of antibiotic sensitivity and resistance also promote high frequencies of multidrug resistance. Preprint at https://www.biorxiv.org/content/early/2017/12/14/233957 (2017).
Atkins, K. E. et al. Use of mathematical modelling to assess the impact of vaccines on antibiotic resistance.Lancet Infect. Dis. 18, e204–e213 (2018).
Goossens, M. C., Catry, B. & Verhaegen, J. Antimicrobial resistance to benzylpenicillin in invasive pneumococcal disease in Belgium, 2003–2010: the effect of altering clinical breakpoints. Epidemiol. Infect. 141, 490–495 (2013).
Ter Braak, C. A Markov chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces. Stat. Comput. 16, 239–249 (2006).
Bogaert, D. et al. Colonisation by Streptococcus pneumoniae and Staphylococcus aureus in healthy children. Lancet 363, 1871–1872 (2004).
Chewapreecha, C. et al. Dense genomic sampling identifies highways of pneumococcal recombination. Nat. Genet. 46, 305–309 (2014).
We thank M. Davies and A. Levy for assistance and S. Lehtinen, C. Colijn and M. Lipsitch for discussion. N.G.D., M.J. and K.E.A. were funded by the National Institute for Health Research Health Protection Research Unit in Immunisation at the London School of Hygiene and Tropical Medicine in partnership with Public Health England. The views expressed are those of the authors and not necessarily those of the NHS, National Institute for Health Research, Department of Health or Public Health England. For part of this work, S.F. was supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and Royal Society (grant number 208812/Z/17/Z).
The authors declare no competing interests.
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Davies, N.G., Flasche, S., Jit, M. et al. Within-host dynamics shape antibiotic resistance in commensal bacteria. Nat Ecol Evol 3, 440–449 (2019). https://doi.org/10.1038/s41559-018-0786-x
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