The unconstrained evolution of fast and efficient antibiotic-resistant bacterial genomes


Evolutionary trajectories are constrained by trade-offs when mutations that benefit one life history trait incur fitness costs in other traits. As resistance to tetracycline antibiotics by increased efflux can be associated with an increase in length of the Escherichia coli chromosome of 10% or more, we sought costs of resistance associated with doxycycline. However, it was difficult to identify any because the growth rate (r), carrying capacity (K) and drug efflux rate of E. coli increased during evolutionary experiments where the species was exposed to doxycycline. Moreover, these improvements remained following drug withdrawal. We sought mechanisms for this seemingly unconstrained adaptation, particularly as these traits ought to trade-off according to rK selection theory. Using prokaryote and eukaryote microorganisms, including clinical pathogens, we show that r and K can trade-off, but need not, because of ‘rK trade-ups’. r and K trade-off only in sufficiently carbon-rich environments where growth is inefficient. We then used E. coli ribosomal RNA (rRNA) knockouts to determine specific mutations, namely changes in rRNA operon (rrn) copy number, than can simultaneously maximize r and K. The optimal genome has fewer operons, and therefore fewer functional ribosomes, than the ancestral strain. It is, therefore, unsurprising for r-adaptation in the presence of a ribosome-inhibiting antibiotic, doxycycline, to also increase population size. We found two costs for this improvement: an elongated lag phase and the loss of stress protection genes.

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Figure 1: Collated rK data sets are best explained by unimodal data fits; K, r and yield data sets in fungi and bacteria are explained by equations (2)–(7).
Figure 2: Empirical and theoretic rK and r-yield relationships.
Figure 3: A demonstration that rrn operon copy number controls r and K by mediating yield: to turn K into yield, divide by 2 mg ml−1 glucose.
Figure 4: Determining the rrn operon copy number that maximizes growth rate of the E. coli rrn mutants.
Figure 5: E. coli K12(MG1655) rrn knockout strains Δ3 and Δ4 optimize population size, K, when glucose is high in concentration without paying a growth rate cost.
Figure 6: Simultaneous rK-adaptation from an antibiotic challenge where drug resistance also increased.
Figure 7: A DNA coverage plot for E. coli K12(AG100) following 60 generations (96 h) of growth in the presence and absence of doxycycline.


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The rrn knockout strains derived from E. coli MG1655 were gifted by T. Bollenbach, strain AG100 was provided by S. Levy and Candida strains were a gift from S. Bates, who are sincerely thanked for their help.

Author information

R.B., I.G., M.H. and C.R.R. proposed research questions and hypotheses, and subsequently designed the experiments; R.B., C.R.R., F.G. and M.H. designed and wrote computer codes to analyse the data; C.R.R., M.H. and S.D. performed the experiments; and R.B., C.R.R. and I.G. wrote the manuscript.

Correspondence to Robert Beardmore.

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Supplementary Figures 1–15; Supplementary Tables 1,2 (PDF 1191 kb)

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Reding-Roman, C., Hewlett, M., Duxbury, S. et al. The unconstrained evolution of fast and efficient antibiotic-resistant bacterial genomes. Nat Ecol Evol 1, 0050 (2017).

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