a James H. Quillen Veterans Affairs Medical Center, Mountain Home, TN 37684; b Department of Internal Medicine, PO Box 70622, c Department of Biological Sciences, PO Box 70703 and d Department of Medical Education, PO Box 70574, Quillen College of Medicine, East Tennessee State University, Johnson City, TN 37614, USA
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Abstract |
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Introduction |
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Population analysis of susceptibility to antibiotics provides a means of detecting trends and potential mechanisms of resistance.1115 Detailed analyses of single populations can provide insight into the mechanisms and rates of acquisition of resistance factors, and estimates of the capacity of a pathogenic species for developing and/or increasing levels of resistance. For example, if isolate identities can be deduced, a temporal series of samples can aid in distinguishing spread of resistance by clonal expansion from spread by horizontal exchange.13,16 In a most extreme scenario, a rapid sweep of resistance determinants through a population, especially via clonal expansion, may cause reductions in genetic diversity, which may limit responses to antibiotics other than those imposing selection. Further, the incremental loss of susceptibility to an antibiotic in bacterial populations may constitute a pathway to resistance, but, as Baquero has stated, "the detection of such evolutionary trends needs many years of observation".11 As a preliminary step toward understanding the genetic and evolutionary processes governing antimicrobial susceptibility in M. catarrhalis, a retrospective study was conducted to assess patterns of variation in a single population.
The availability of a long-term, comprehensive collection of M. catarrhalis from a single veterans medical centre provides an opportunity to assess inter-isolate variation and temporal trends in susceptibility among isolates recovered from a single host population. By restricting samples to one veterans medical centre, any variation caused by regional prescribing practices and diverse patient populations is minimized.16 The collection spans 19841994, and encompasses the early years of ß-lactamase expansion in the population. We show how samples from a single population can serve as a model for using temporal trends and phenotypic correlations among isolates as indicators of the underlying mechanisms leading to the spread of resistance in populations.
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Materials and methods |
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From July 1984 until June 1994, virtually all isolates of M. catarrhalis (>1000) recovered by the Mountain Home Veteran's Affairs Medical Center (VAMC) clinical laboratory in Johnson City, Tennessee, USA, were archived into a curated collection and stored at 70°C. Collection year designations begin in June and span calendar years; to simplify reporting, 19841985 will be referred to as either 1985 or sample year 1, 19851986 as 1986 or sample year 2, and so on to 19931994 as sample year 10. The patient or host population from which the bacterial isolates were recovered was drawn from a local and geographically defined region encompassing an approximate 240 km radius around Johnson City. Greater than 95% of the isolates were recovered from sputum. The number of isolates recovered per year peaked in year 5. Isolates for testing were randomly selected from the collection, with 50 isolates per year for the year 5 peak and the two prior and two subsequent flanking years, and 25 isolates per year for all other years. A total of 375 isolates were tested.
Antimicrobial agents and MIC determinations
MICs of the following antimicrobial agents were determined by a Sensititre broth microdilution method with MuellerHinton broth: amoxycillin/clavulanate (2:1, SmithKline Beecham, Philadelphia, PA, USA), cefamandole (Eli Lilly & Co., Indianapolis, IN, USA), ceftriaxone (HoffmanLaRoche, Nutley, NJ, USA), ciprofloxacin (Miles Laboratory, Elkhart, IN, USA), clarithromycin (Abbott Laboratories, Abbott Park, IL, USA), imipenem (Merck & Co., Rahway, NJ, USA), trimethoprim/sulphamethoxazole (1:19, HoffmanLaRoche, Nutley, NJ, USA), penicillin G and tetracycline (Sigma Chemical Co., St Louis, MO, USA). For clarity of data presentation, MICs of 2:1 amoxycillin/clavulanate will be reported using the amoxycillin concentration; similarly, MICs of 1:19 trimethoprim/sulphamethoxazole will be reported using the sulphamethoxazole concentration. A final inoculum of 105 cfu/mL was used; plates were incubated for 18 h at 37°C. Three replicate MIC determinations were conducted for each isolate. ß-Lactamase production was determined by a nitrocefin disc method.
Population variation
A nested ANOVA was used to test for differences in population mean MICs among years and among isolates within years. One-way ANOVA was used to test for differences in MICs between ß-lactamase producing and non-producing isolates. ANOVAs were conducted using the PROC GLM procedure of the SAS Institute.17
Temporal trends
Temporal trends in resistance to each of the nine antimicrobial agents were assessed by regressing geometric mean MICs on years using the PROC REG procedure of the SAS Institute.17 For those antimicrobials showing significant temporal increases, ß-lactamase-producing and non-producing groups were analysed separately to provide insight into whether the spread of a single ß-lactamase gene could explain observed trends. If increases in the population frequency of a single form of ß-lactamase caused the temporal trend, regressions would not be expected to be significant within either ß-lactamase-producing or nonproducing subsamples. A significant trend within the producing isolates could arise from several sources including the presence of multiple forms of the ß-lactamase enzyme, differences in rates of production of the enzyme or additional resistance factors.
Correlations among antimicrobial MICs
A correlation analysis was conducted in which pairwise partial correlation coefficients were computed (adjusting for year effects) with the expectation that MICs of antimicrobials with similar modes of action would be correlated. To provide insight into potential resistance determinants, partial correlations were computed separately for ß-lactamase-producing and non-producing isolates using the PROC CORR procedure of the SAS Institute.17 A significant correlation among non-producing isolates would suggest that the population harbours resistance factors other than ß-lactamase.
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Results |
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There was a marked increase in the proportion of isolates producing ß-lactamase between sample years 1 and 2, and by year 10 the population consisted of 96% ß-lactamaseproducing isolates (Figure 1). The rapid sweep toward ß-lactamase production in the local population paralleled global trends.18 Although regression analysis of ß-lactamase production proportion on year explained 33% of the sample variation, the regression was not significant (P = 0.08).
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There were significant differences in MICs among yearly population means for seven (P < 0.0001 for each ANOVA) of the nine antimicrobials (all except tetracycline and clarithromycin) and significant differences among isolates within years for eight (P < 0.01 for each ANOVA) antimicrobials (all except clarithromycin). These observations indicate individual and yearly population variability for susceptibility to all of the ß-lactam antimicrobials, the folate inhibitor combination of trimethoprim/sulphamethoxazole and the quinolone ciprofloxacin. Mean MICs of each of the five ß-lactam antimicrobials for ß-lactamase-producing isolates were significantly greater than for non-producing isolates (Table I). An unexpected finding was significantly higher MICs of trimethoprim/sulphamethoxazole for ß-lactamase-producing isolates compared with nonproducing isolates (Table I
).
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Significant trends toward decreased susceptibility were observed for four ß-lactam agents: amoxycillin/clavulanate, ceftriaxone, imipenem and penicillin (Table I). The pattern and rates of decreasing susceptibility were similar for penicillin and ceftriaxone in contrast to a slower rate of decreasing susceptibility for amoxycillin/clavulanate (Figure 2
). In contrast, MICs of the ß-lactam agent cefamandole did not show decreasing susceptibility (Table I
). When ß-lactamase-producing and non-producing isolates were analysed separately, there was no significant trend for either penicillin (Figure 3
) or ceftriaxone, but the temporal trend remained significant for both imipenem and amoxycillin/clavulanate (Table I
). Significant temporal reductions in susceptibility to clarithromycin occurred only within the ß-lactamase-producing isolatesan unexpected result for a non-ß-lactam antimicrobial (Figure 3
). Yearly mean MICs of trimethoprim/sulphamethoxazole increased from 2.86 mg/L in 1985 to 6.72 mg/L in 1992, then dropped below 4.2 mg/L in the final two sample years.
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The six pairwise correlations involving MICs of four ß-lactam agents (amoxycillin/clavulanate, imipenem, ceftriaxone, penicillin) were all significant and relatively high in both ß-lactamase-producing and non-producing isolates (Table II). Cefamandole showed significant correlations with ceftriaxone and penicillin within ß-lactamase-producing isolates, and a correlation with amoxycillin/clavulanate restricted to non-producing isolates (Table II
). Susceptibility to trimethoprim/sulphamethoxazole was correlated with susceptibility to each of four ß-lactam antimicrobials, but for three of these pairs, significant correlations were restricted to isolates producing ß-lactamase (Table II
). A total of five pairwise correlations were restricted to isolates producing ß-lactam, all involving either cefamandole and/or trimethoprim/sulphamethoxazole (Table II
). A correlation was revealed between ciprofloxacin and tetracycline in non-ß-lactamase-producing isolates.
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Penicillin is the only test antibiotic for which clinical resistance was found in the test sample, with 99% of ß-lactamase producing and 10% of non-producing isolates at or above the NCCLS breakpoint of 0.25 mg/L.19 The penicillin MIC90 in 1989 was 8 mg/L, and was constant at 16 mg/L for all remaining years. The penicillin MIC50 increased from 0.12 in 1985 to 2 mg/L in 1986, followed by a reduction to 1 mg/L for 5 years, and an increase to 2 mg/L in 1992, to 4 mg/L in 1993 and to 8 mg/L in 1994. The MIC of cefamandole for ß-lactamase-producing isolates was 8 mg/L, which defines the upper limit of susceptibility by NCCLS guidelines. The yearly mean MICs of cefamandole for ß-lactamase-producing isolates decreased from a high of 3.49 mg/L in 1989 to 2.19 mg/L by 1994. Cefamandole MIC90 remained constant at 4 mg/L throughout the study period; the cefamandole MIC50 was 2 mg/L in all years except 1986 and 1992, when it was 0.5 mg/L and 4 mg/L, respectively.
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Discussion |
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An increase in mean MIC in a population of organisms may occur either by an increase in the frequency of isolates carrying a resistance determinant or by increases in the magnitude of resistance among those carrying resistance determinants. Regression analyses conducted separately for all isolates and for the subset of ß-lactamase-producing isolates were used to distinguish between these potential mechanisms underlying observed temporal trends. Both ceftriaxone and penicillin, two antimicrobials for which significant temporal increases were noted, failed to show temporal trends when ß-lactamase-producing isolates were analysed separately. For these two antibiotics, the absence of progressive MIC increases within the ß-lactamaseproducing isolates suggests that the population trend toward decreased susceptibility was caused by an increase in the relative abundance of ß-lactamase-producing isolates rather than by increases in the prevalence of isolates producing a more active ß-lactamase. In contrast, the observation of a significant temporal decrease in susceptibility to two other ß-lactam antimicrobials (amoxycillin/ clavulanate and imipenem) within the ß-lactamaseproducing subset of isolates demonstrates that the simple presence or absence of a single form of ß-lactamase is not sufficient to explain the long-term trend.
Increased mean MICs against the ß-lactamase-producing isolates could occur if there was variation in ß-lactamases and if the proportion of producing isolates with a more active enzyme increased over time. Two forms of BRO ß-lactamases and the genes that encode them have been characterized; M. catarrhalis BRO-1 alleles confer higher MICs compared with BRO-2 alleles.4,20 This difference in MICs has been attributed to the production of more enzyme as a consequence of higher transcriptional activity of BRO-1.20 In the current study, MICs of penicillin displayed a clear trimodal pattern (Figure 4). Trimodal distributions to ß-lactam antimicrobials in M. catarrhalis have been reported previously, with peaks in the low, mid and high ranges interpreted as corresponding to non-ß-lactamase, BRO-2 and BRO-1 isolates, respectively.1,11 If BRO variants are the cause of trimodality in penicillin MICs, identical samples of isolates may be expected to show a similar MIC distribution to other ß-lactam agents. However, trimodal distributions were not evident for any of the four remaining ß-lactam agents in the current study (Figures 4 and 5
), or for either amoxycillin/clavulanate or ceftriaxone in a previous study.1 The stability of non-penicillin ß-lactam antimicrobials to BRO ß-lactamase may render differences between BRO forms insignificant. Moreover, differences in the MIC distributions between penicillin and other ß-lactam antimicrobials may arise from methodological sources; for instance, the customary two-fold antibiotic concentration intervals may be too broadly spaced to detect differential responses. Alternatively, observed variation to ß-lactam agents may not arise from BRO-1BRO-2 differences.
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Correlations in resistance phenotypes among antibiotics can provide additional insight into underlying causes of reduced susceptibility. Pairs of agents that make up the suite of five ß-lactam antimicrobials were expected to show MIC correlations within ß-lactamase-producing isolates if the variation was caused by different forms of the ß- lactamase or by ß-lactamase-dependent modifiers. This expected correlation was observed for four of the agents. The exception, cefamandole, showed no correlation with two ß-lactam antimicrobials and correlations involving cefamandole were generally lower in magnitude than those among other pairs of ß-lactam agents (Table II). The combination of long-term data from a single population and correlations among antimicrobials can provide clues to the underlying causes of the breakdown in the cefamandole correlations. The trend toward decreasing susceptibility to cefamandole paralleled that for other ß-lactam antimicrobials during the first seven sample years (19851991). A change in the VAMC formulary policy caused a dramatic decline in cefamandole usage in the medical centre in the mid-1980s, which may explain the observed increase in susceptibility to cefamandole during the final three study years. We hypothesize that relaxed selection for cefamandole resistance led to selection for antimicrobial-specific resistance determinants that retained or decreased susceptibility to ß-lactam antimicrobials other than cefamandole.
The effect of ß-lactamase on susceptibility to cephalosporins was not large, conferring four-fold higher MICs of cefamandole and three-fold higher MICs of ceftriaxone (Table I), which is consistent with the two- to four-fold differences found in previous studies.1,18 The mean MIC of penicillin among VAMC ß-lactamase-non-producing isolates (0.32 mg/L) was higher than that found in either US and European community-acquired isolates in a recent, multi-centre study (0.04 mg/L).1 Thus, the hospital-derived VAMC isolates appear to harbour non-ß-lactam mechanisms, such as altered penicillin-binding proteins, which are either more prevalent and/or more effective against penicillin than those possessed by community-acquired isolates. The decrease in susceptibility in ß-lactamase nonproducing isolates may reflect more widespread exposure to ß-lactam agents among hospital-acquired isolates.
Six pairs of ß-lactam antimicrobials showed significant correlations in both ß-lactamase-producing and nonproducing isolates (Table II). A pairwise correlation within isolates not producing ß-lactamase suggests that factors other than ß-lactamase contribute to reduced susceptibility, and the correlation within the ß-lactamase producing group suggests that there may be more than one form of the ß-lactamase or modifiers that regulate enzyme activity and/or production. Thus, decreases in mean population susceptibility appear to have been mediated, in part, by the increased proportion of ß-lactamase-producing isolates. However, the data suggest that two additional factors contributed to increases in resistance to ß-lactam antimicrobials: (i) selection for more efficient forms of ß- lactamases and/or more efficient production of a single ß-lactamase; (ii) selection for additional resistance determinants.
A trend to increased mean MICs of the macrolide clarithromycin was unexpectedly limited to ß-lactamase-producing isolates (Table I). Potential causes include the simultaneous expansion in the population of two independent characters, ß-lactamase production and a trait conferring reduced susceptibility to clarithromycin, each of which was independently subject to selection. Another possible explanation may be traced to the hitchhiking effect, where two traits tend to be inherited together by a physical linkage of genes.22 Alternatively, ß-lactamase-producing isolates may be characterized by alterations in outer membrane proteins that also affect the ability of the cell to take up clarithromycin. The observation of significant MIC correlations between some ß-lactam antimicrobials and trimethoprim/sulphamethoxazole also supports the inference of non-ß-lactamase resistance factors. In Streptococcus pneumoniae, increased resistance to penicillin has been shown to be correlated with increased resistance to diverse antimicrobials, including macrolides, tetracycline and trimethoprim/sulphamethoxazole, but not to fluoroquinolones.14
The long-term clinical significance of temporal trends to reduced ß-lactam susceptibility in M. catarrhalis is not clear. Genetic variants that confer small reductions in susceptibility have been described for TEM ß-lactamases, and these minor variants were effective targets of antimicrobial selection in laboratory studies.23 Genetic variants with small phenotypic effect that arise via mutation may be maintained at low cost to the bacteria and thus may be retained longer in a population in the absence of selection.24 Whether an accumulation of different variants, each with a small effect on susceptibility, can lead to treatment failure remains to be seen, but the importance of monitoring and reporting changes in susceptibility have been recognized.11,15
Surveillance studies of natural populations have demonstrated that antimicrobial susceptibility can decrease in circumstances in which clinical resistance is rare.13,25,26 Long-term surveillance of susceptibility of Neisseria gonorrhoeae to ciprofloxacin in a single medical centre revealed a temporal trend to reduced susceptibility,25 and surveillance of N. gonorrhoeae from a US metropolitan area showed trends in decreased susceptibility to penicillin, and a likely decline in the percentage of highly susceptible isolates, despite a decrease in the mean MICs.13 From our population analyses of antimicrobial susceptibility in a single location, we provide evidence that multiple sources of variation contribute to temporal trends to reduced susceptibility for four of nine antimicrobial agents. The gradual increase in mean MICs of cefamandole, followed by a decline subsequent to reduced local usage of cefamandole, suggest that reduced selection pressure and/or a fitness cost to reduced susceptibility may have limited further increases. A 3 year increase in mean MICs of trimethoprim/ sulphamethoxazole demonstrated the capacity of the population for reduced susceptibility, but it also suggests that additional environmental or biological factors limit fixation of the responsible trait in the population.
The current study has revealed long-term trends and correlations among antibiotics. More detailed genetic characterization of isolates may be necessary to distinguish among the potential mechanisms underlying the spread of resistance variants over time. For example, an efficient typing system for M. catarrhalis has recently been developed27 and detailed characterization of BRO alleles is now feasible.20 These typing methods may be used to uncover persistence patterns of isolates, to distinguish horizontal transfer from clonal expansion, and to ascertain the constancy of resistance phenotypes within genetically identical isolates.
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Acknowledgments |
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Notes |
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References |
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Received 23 March 1999; returned 30 August 1999; revised 15 September 1999; accepted 11 October 1999