National Public Health Service for Wales, Abton House, Wedal Road, Cardiff CF14 3QX, Wales, UK
Received 29 October 2004; returned 5 January 2005; revised 7 April 2005; accepted 1 June 2005
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Abstract |
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Methods: The model assumed that resistance in microbial ecologies changes slowly with changing selection pressure, at a rate proportional to the difference between the current resistance level and the resistance level that would be in equilibrium with current selection pressure. The maximum rate of increase in resistance during periods of increasing selection was assumed to be greater than the maximum rate of decrease during decreased selection.
Results: Under a simulated annual cyclic selection pressure variation of 40%, with maximum resistance rise and fall rates of 10 and 0.5%, respectively, resistance rose above the level expected from the mean selection pressure by small ratchet-like increments. Over 50 simulated years, resistance increased to 62%, rather than the 50% expected from the mean level of selection. Welsh community prescribing for a selection of antibiotics showed a seasonal cyclic variation of 1345%.
Conclusions: The intuitive assumption that cyclic selective pressure would produce resistance levels commensurate with the mean selection pressure was contradicted; rather resistance drifted towards a level commensurate with maximum selection pressure. If the ratchet effect exists in reality, it may produce unexpected excess resistance, particularly in the community for antibiotics used in respiratory infection, where cycling is pronounced, or in ITU antibiotic rotation. It should be most pronounced for resistance systems with strong asymmetry between rates of adaptation under rising and falling selection pressure. Non-linear dynamic systems in physics and ecology are notorious for producing counter-intuitive effects; resistance epidemiology may be similar.
Keywords: cyclic selection pressure , seasonal antibiotic prescribing , antibiotic resistance , ratchet effect
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Introduction |
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Methods |
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The model
A simple model (available as an Excel spreadsheet as Supplementary data at www.jac.oupjournals.org) was constructed based upon the following assumptions.
Significant cyclic variation in antibiotic selection pressure occurs. Table 1 illustrates the seasonal variation in community oral antibiotic prescribing. Prescribing in the JanuaryMarch financial quarter was 219% higher than mean quarterly prescribing and 125% lower in the JulySeptember quarter. Flucloxacillin was a notable exception where this pattern was reversed, with highest prescribing in the JulySeptember quarter.
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Resistance levels increase rapidly when selection pressure rises, but decrease slowly when selection pressure decreases. This is logical, as different processes are involved, which are likely to operate at different rates. Increased selection pressure has a double-hit mechanism; first, the greater selection removes susceptible organisms by direct bactericidal action, or by preventing reproduction; second, inhibition or death of susceptible organisms leaves nutritional resources and instances of the ecological niche available for growth of resistant variants. Conversely, falling selection pressure leaves a non-equilibrium level of resistant variants, and these are selected against by a single-hit mechanism; their only postulated disadvantage is that they may (or may not6) carry a metabolic overhead that reduces their competitive ability.
Evidence for a rapid rise in resistance under increased antibiotic selection is largely anecdotal, but rates of 515% per annum have been observed.7 The slow fall in resistance under decreased selection pressure is less well documented, but decreases at 0.5% per annum or less have been observed.8 Resistance genes can become fixed during prolonged in vitro selection, yielding strains that compete as well or better than the ancestral antibiotic-susceptible strain, and show low loss rates for resistance markers.6 It has been suggested that changes in the genetic background re-optimize metabolism and associate resistance genes with genes coding for essential products.6
The model assumes that equilibration with changing selective pressure proceeds with a rate of change that decreases as the system approaches equilibrium. Maximum rise and fall rates for resistance (rates attained when current resistance levels differ from selection equilibrium levels by 100%) were taken conservatively as 10 and 0.5% per annum, respectively. Other values yielded similarly shaped response curves to that illustrated (Figure 1, line A), provided that the rise rate was greater than the fall rate.
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Results and discussion |
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Changes in the maximum rate of fall in resistance over the range 20% per annum yielded closely similar results. Other assumptions on kinetics increased the rise. If the rate of equilibration was assumed to be proportional to the square root of the disequilibrium difference (difference between current resistance and the level that would be in equilibrium with current selection pressure), the rise over 50 years was 67.4%, and if the rate of change was assumed to be independent of the disequilibrium difference, resistance rose to 70% in 11 years. Discontinuous stepped cyclic changes in selection, such as might occur in ITU antibiotic rotation, produced ratchet-type changes similar to those illustrated for smooth sinusoidal variation in selection, unless the ratio between the durations of low and high selection approached the ratio of the rise to fall rates (set to 20:1).
The model makes predictions that could be tested. The ratchet phenomenon should be most marked for species/antibiotics that combine a particularly rapid rise with a particularly slow fall in response to, respectively, increasing or decreasing selection pressure. These characteristics are most likely to be found in highly evolved resistance systems, where resistant strains have a minimal competitive disadvantage, and ready, rapid inter-strain genetic transfer has been achieved, i.e. for antibiotics where long-standing, intense selection pressure has been applied and resistance is common. Wide cyclic variation in prescribing with a short cycle period is a prerequisite, and significantly increasing mean annual prescribing is desirable to avoid misinterpretation of a late pseudo-equilibrium state as a negative result. During periods when mean annual selection pressure is increasing, resistance levels should correlate slightly better with the maximum seasonal selection pressure than with mean selection pressure.
Conversely, where resistance is poorly evolved, unstable or has not evolved an effective transmission mechanism, and there is a large competitive disadvantage to carriage of resistance genes, the ratchet effect should be negligible. Figure 1, line B illustrates this case, with rise and fall adaptation rates set equal in the model. This may be the situation where the rates of forward and reverse mutation to resistance are similar, and there is little or no inter-strain transmission. A possible example is current fusidic acid resistance in methicillin-susceptible Staphylococcus aureus.9
It should be remembered that selection pressure may cycle widely and rapidly between doses in antibiotic treatment of individual patients. It seems unlikely that the ratchet mechanism might have a significant role in selection of resistant commensal or infecting flora in individual patients over average treatment periods of a few weeks, but some conditions require prolonged treatment. It may be interesting to explore this, and the possible longer-term broad ecological effects discussed here, in more sophisticated models.
Non-linear dynamic systems are notorious sources of unanticipated effects in physics, engineering and ecology. At the extreme, apparently simple systems can produce chaotic behaviour, leaving no possibility of definitive prediction of their state. It is well to remember that the epidemiology of resistance is essentially a problem in microbial ecology, and that early ventures into chaos theory included May's work on ecological models.10
The potential behaviour outlined here is not so extreme, yielding predictable consequences analogous to well-characterized hysteresis phenomena in electromagnetism and mechanics. The predictions that the model makes could be tested. However, whether or not the model is correct, in the sense that it predicts a real phenomenon, is not the main issue. What is important is that a plausible model has yielded predictions that are counter-intuitive, indicating complex behaviour that would not be anticipated by the average medical microbiologist. The resistance problem might well benefit from the attention of those who are trained in ecology or mathematics and familiar with the problems of prediction in dynamic systems.
Equally, the contrast between the behaviour in the two hypothetical examples given here illustrates the point that resistance may not be a single epidemiologically uniform phenomenon. There are considerable potential differences between the ecological behaviour of a resistance that is acquired readily by genetic transfer, and a resistance that results from high-frequency reversible mutation. It would not be surprising to find distinctive patterns of epidemiological behaviour amongst the wide range of species, resistance mechanisms, and prescribing patterns that exist. Despite nearly a century of antibiotic use, we are still struggling to define methods for gathering, validating and analysing resistance data. There may be many surprises to come from the infant science of resistance epidemiology.
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Transparency declaration |
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Supplementary data |
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Acknowledgements |
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References |
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9.
Mason BW, Howard AJ, Magee JT. Fusidic acid resistance in community isolates of methicillin-sensitive Staphylococcus aureus and fusidic acid prescribing. J Antimicrob Chemother 2003; 51: 10336.
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