We need to find ways of enhancing the potency of existing antibiotics, and, with this in mind, we begin with an unusual question: how low can antibiotic dosages be and yet bacterial clearance still be observed? Seeking to optimise the simultaneous use of two antibiotics, we use the minimal dose at which clearance is observed in an in vitro experimental model of antibiotic treatment as a criterion to distinguish the best and worst treatments of a bacterium, Escherichia coli. Our aim is to compare a combination treatment consisting of two synergistic antibiotics to so-called sequential treatments in which the choice of antibiotic to administer can change with each round of treatment. Using mathematical predictions validated by the E. coli treatment model, we show that clearance of the bacterium can be achieved using sequential treatments at antibiotic dosages so low that the equivalent two-drug combination treatments are ineffective. Seeking to treat the bacterium in testing circumstances, we purposefully study an E. coli strain that has a multidrug pump encoded in its chromosome that effluxes both antibiotics. Genomic amplifications that increase the number of pumps expressed per cell can cause the failure of high-dose combination treatments, yet, as we show, sequentially treated populations can still collapse. However, dual resistance due to the pump means that the antibiotics must be carefully deployed and not all sublethal sequential treatments succeed. A screen of 136 96-h-long sequential treatments determined five of these that could clear the bacterium at sublethal dosages in all replicate populations, even though none had done so by 24 h. These successes can be attributed to a collateral sensitivity whereby cross-resistance due to the duplicated pump proves insufficient to stop a reduction in E. coli growth rate following drug exchanges, a reduction that proves large enough for appropriately chosen drug switches to clear the bacterium.

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...

In May 1993, an outbreak of methicillin-resistant Staphylococcus aureus (MRSA) was identified at our tertiary care teaching center. The epidemic MRSA strain was transmitted efficiently in the hospital environment. Subsequent investigations indicated that the strain had been introduced into western Canada by a patient who had recently been hospitalized for 3 months in the Punjab, India, and had been admitted to a hospital in rural British Columbia shortly after his arrival in Canada. Transfer of the patient to a hospital in Vancouver and subsequent transfer of a colonized patient contact to a hospital in Winnipeg, Manitoba, resulted in major outbreaks of MRSA at these two large tertiary care centers within 6 weeks of the arrival of the index case in Canada. Epidemiological typing of the S. aureus coagulase gene with use of a polymerase chain reaction method and pulsed-field gel electrophoresis documented clonality of this strain. These outbreaks again illustrate both the propensity of certain strains of S. aureus to produce epidemic disease, including rapid spread within the institutional setting, and the global nature of problems with antimicrobial resistance.