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

Abstract

Evolutionary trajectories are constrained by tradeoffs 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 a 10%, or more, increase in length of the Escherichia coli chromosome, we sought costs of resistance associated with doxycycline. However, it was difficult to identify any because E.coli's growth rate (r), carrying capacity (K) and drug efflux rate increased during evolutionary experiments where E.coli 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 tradeoff according to rK selection theory. Using prokaryote and eukaryote microbes, including clinical pathogens, we therefore show r and K can tradeoff, but need not, because of 'rK trade-ups'. r and K only tradeoff in sufficiently carbon-rich environments where growth is inefficient.We then used E. coli ribosomal RNA (rrn) knockouts to determine specific mutations, namely changes in rrn operon copy number, than can simultaneously maximise 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. Although E. coli can evolve to grow faster and to larger population sizes in the presence of antibiotics when compared to their absence, we found two costs to this improvement: an elongated lag phase and the loss of stress protection genes. 1 IntroductionTradeoffs lie at the heart of a cross-kingdom research effort that seeks to explain how biodiversity is generated and maintained. [1][2][3][4][5] Two traits engage in an evolutionary tradeoff when beneficial mutations for one trait are deleterious for the other, and vice versa, and many theories agree 2,[6][7][8][9][10][11] that genetic polymorphisms are maintained when tradeoffs have an appropriate geometry. Less clear, however, are the physical, chemical and physiological forces that create tradeoffs in the first place 12 and tradeoffs needed for the theories to work can be difficult to isolate in practise. [13][14][15][16][17][18] It is essential for medicine that we understand tradeoffs. The term 'superbug' refers to a pathogenic microorganism that resists treatment by antibiotics with no apparent cost, or tradeoff, in terms of its pathogenicity. An evolutionary route to superbug status is thought to occur when a pathogen first adopts costly drug resistance mutations, a process that sees resistance traded against proliferation rate in antibiotic-free environments. Thereafter, other mutations compensate for those costs, yielding strains that are both drug resistant and capable of rapid proliferation. 19, 20 Tradeoffs are, however, sometimes observed in pathogens. A genomic study of a clinical pathogen using several antibiotic classes 21 showed res...

Plasmid carriage and the unorthodox use of fitness in microbial evolution

“…The distribution of non-transmissible plasmids with respect to their size is multimodal [12], and those around 5kb in size are the second most frequent type. pGW155B also harbours the tetracycline resistance gene tet (36), a ribosome-protection type resistance protein [37] that I used as advantageous, selectable trait. Importantly each construct is tagged with different fluorescence proteins, that I use to identify them in mixed culture conditions.…”

“…Despite their lower growth rate, the construct R, harbouring pGW155B, attained larger population sizes during the stationary phase compared to S. Optical density data reports similar dynamics ( Figure S1), so the larger population size is likely caused by an increase in cell number as Figure S2 illustrates. Thus, I used this parameter-population size in the equilibrium, K -to estimate the biomass yield (y) of both strains, a proxy for metabolic efficiency defined as y = K/glc [36,38], where glc is the supply of glucose. This metric suggests the construct R is more efficient than S, despite their slower growth rate (y S = 0.222 ± 0.004 normalised relative fluorescence units (nRFU) per mg of glucose in construct S, for y R = 0.305 ± 0.013 nRFU per mg of glucose in construct R; mean ± standard error with 8 replicates; Mann-Whitney U-test p = 3.108 × 10 −4 , ranksum = 37; Figure 1B).…”

“…Crucially, growth curves can provide insight into metabolic changes undergoing in bacteria. The transition between efficient and inefficient glucose metabolism, for example, can be detected by analysing them [36]. Therefore, to study the persistence of non-transmissible plasmids I sought changes in the growth curves of two strains of Escherichia coli MC4100 (see methods); one of which (R) bears the plasmid pGW155B [37].…”

“…I inoculated a 96-well microtitre plate containing 150µg/mL of supplemented M9 media with a mixture of two overnight cultures, one of E. coli GB(c) and another of E. coli Wyl ( Figure S2). The overnight culture for GB(c) was supplemented with 100ng/mL of tetracycline to preserve the plasmid pGW155B carrying tet (36) [59], centrifuged and removed prior adding to the microtitre plate. I incubated the plate at 30 o C in a commercial spectrophotometer and measured the optical density of each well at 600nm (OD 600 ), yellow florescence for the S strain (YFP excitation at 505nm, emission at 540nm), and cyan fluorescence for the R strain (CFP at 430nm/480nm) every 20min for 24h.…”

Stability ofβ-lactam antibiotics in bacterial growth media

“…When performing an MIC assay, one 5 assumes that the antibiotic does not degrade over the timescale of the assay. Antibiotic 6 stability is also assumed in a host of other bacterial growth assays that are used to 7 determine antibiotic mechanism of action [2][3][4][5], interactions between antibiotics [6-9], 8 and evolution of antibiotic resistance [10][11][12][13][14].…”