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Antimicrobial Agents and Chemotherapy, January 2004, p. 23-29, Vol. 48, No. 1
0066-4804/04/$08.00+0 DOI: 10.1128/AAC.48.1.23-29.2004
Copyright © 2004, American Society for Microbiology. All Rights Reserved.
Antimicrobial Research Centre and Division of Microbiology, School of Biochemistry and Molecular Biology, University of Leeds, Leeds LS2 9JT, United Kingdom
Received 13 March 2003/ Returned for modification 3 July 2003/ Accepted 30 August 2003
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Leu) and cefotaxime resistance resulted from loss of outer membrane porin OmpF. The mechanisms of gentamicin resistance could not be defined, but resistance did not result from mutations in ribosomal protein L6 (rplF). Although similar mechanisms of low-level antibiotic resistance probably arise in these strains, mutators are a risk factor because the increased generation of mutants with low-level resistance enhances the opportunity for subsequent emergence of high-level resistance. |
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In the presence of antibiotics, mutators are predicted to benefit the populations in which they occur, since resistant variants can be rapidly selected (9, 17). Indeed, in some cases the frequencies of mutations for high-level antibiotic resistance are 1,000-fold higher in mutators than normal strains, indicating the increased adaptability of these strains (9, 21). Generation of multiple chromosomal mutations, which occurs more readily in mutators, may also assist development of high-level resistance when stepwise acquisition of several mutations is required (23). Mutators also have increased potential to generate mutants expressing low-level antibiotic resistance. These mutants may persist long enough to acquire subsequent resistance mechanisms via horizontal gene transfer (4). In addition, MMR-deficient strains present reduced barriers to interspecies genetic exchange (9) and therefore may be important in the acquisition of mobile resistance determinants. In view of their superior mutability and enhanced gene acquisition properties, mutators could therefore have an important role in the emergence and spread of antibiotic resistance within bacterial populations.
The likelihood that mutators are indeed a risk factor in the treatment of infectious diseases is suggested by the correlation between high mutation frequency and antibiotic resistance in P. aeruginosa recovered from the lungs of cystic fibrosis patients (26). Nevertheless, the response of mutators to antibiotics at the concentrations therapeutically achievable in humans has not been determined. In this paper we report on the effects of antibiotics used for the treatment of human urinary tract (UT) infections (UTIs) on E. coli mutators, focusing on mutational responses to pharmacokinetic peak antibiotic concentrations (Cmaxs) and trough antibiotic concentrations (Cmins). Our studies provide a relevant model of the in vivo behavior of mutators because E. coli is the primary UT pathogen in humans (34) and E. coli mutators occur at a high frequency among human uropathogenic isolates (10). We conclude that mutators can present an enhanced risk for emergence of antibiotic resistance during therapy of UTIs caused by E. coli.
(Portions of this work were presented at the 42nd Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, Calif., 27 to 30 September 2002 [K. Miller, A. J. O'Neill, and I. Chopra, Abstr. 40th Intersci. Conf. Antimicrob. Agents Chemother., abstr. C1-965, 2002].)
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TABLE 1. E. coli strains used in this study
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Determination of susceptibilities to antibiotics and chemicals. The MICs of cefotaxime (CTX), CIP, gentamicin (GEN), nitrofurantoin (NIT), tetracycline (TET), cetyltrimethylammonium bromide (CTAB), and ethidium bromide (EB) were determined by serially diluting the antibiotics twofold in MHA and inoculating the dilutions on MHB at 104 CFU/spot. For TMP, MHA and MHB were replaced by ISA and ISB, respectively. The plates were incubated aerobically or anaerobically (GasPak 150 anaerobic jar system; Becton Dickinson, Oxford, United Kingdom) for 18 h at 37°C, and the MIC was defined as the lowest concentration of inhibitor that allowed no visible growth.
Determination of MPCs.
The mutant prevention concentration (MPC) is the lowest drug concentration that prevents bacterial colony formation from a culture containing
1010 CFU (38). Accordingly, to determine MPCs, late-logarithmic-phase cultures of E. coli growing in either MHB or ISB were harvested by centrifugation (6,000 x g, 10 min) and resuspended in fresh growth medium at a final concentration of 1011 CFU/ml. Aliquots (100 µl) were incorporated into MHA plates or ISA plates (for TMP) containing serial twofold drug dilutions in the range of 0.5 to 64 times the MIC of each drug. MPCs were determined following aerobic or anaerobic incubation at 37°C for 72 h.
Determination of frequencies of mutation to antibiotic resistance. The frequencies of mutation to antibiotic resistance were determined as described previously (21) with Mueller-Hinton or Iso-Sensitest growth media. Following aerobic or anaerobic incubation, the mutation frequencies were expressed as the number of resistant mutants recovered as a fraction of the total number of viable bacteria (21).
PCR amplification and sequencing of the mar (multiple antibiotic resistance) regulon, folA, and rplF. Preparation of chromosomal DNA and PCR amplifications were performed as described previously (32). Oligonucleotide primers designed with the Oligo (version 6.0) program (Molecular Biology Insights, Cascade, Colo.) were used to amplify the resistance-determining (25) regions of the marR and marO genes of the mar regulon (5'-AGCCTTGCATCGCATTGAA and 5'-GCGTCAGTATTGCGTCTGG); the folA gene, including the promoter (5'-GAACCGGAAACGAAACC and 5'-CTTCATCCACCGACTTCAC); and rplF (5'-TGTACCACCAGGCGAGTT and 5'-GGGTCTGGGTATCGCAGTTGT). PCR products were purified by using Microcon PCR Centrifugal Filter Devices (Millipore, Watford, United Kingdom) according to the instructions of the manufacturer. DNA sequencing was performed by Lark Technologies (Saffron Walden, United Kingdom).
Fluorometric determination of intracellular EB. The level of accumulation of EB was measured as described previously (6), with the exception that the cells were washed twice in uptake buffer and lysed with BugBuster reagent (Novagen, Madison, Wis.).
Determination of protein concentration. Protein concentrations were determined by the method of Bradford (5).
Outer membrane preparation and analysis of proteins. Outer membranes were prepared essentially as described previously (30). Outer membrane proteins (OMPs) were analyzed on sodium dodecyl sulfate-polyacrylamide gels (8%) containing 6 M urea to achieve optimum resolution of the porin proteins (30). Gels were stained with Coomassie brilliant blue. The identities of the OMPs were determined by N-terminal sequencing and comparison of the sequence data with those available in the SWISS-PROT database.
Crude DHFR preparation. The method used for the preparation of crude dihydrofolate reductase (DHFR) was adapted from the method of Adrian and Klugman (1). Sonication was replaced by chemical lysis with the BugBuster protein reagent, followed by exchange of the BugBuster reagent for reaction buffer (50 mM sodium phosphate buffer [pH 7.4]) containing 10 mM ß-mercaptoethanol and 1 mM EDTA and concentration fivefold with a Centricon Plus-20 centrifugal filter device (Millipore).
TMP IC50 determination. The 50% inhibitory concentrations (IC50s) of TMP were determined by using an adaptation of the DHFR assay described by Thillet et al. (36). Reactions were carried out with 200-µl volumes of a reaction mixture comprising 50 µM dihydrofolate, 100 µM NADPH, 100 mM potassium phosphate (pH 7), 100 mM potassium chloride, and 20 µg of the whole soluble protein fraction containing DHFR, which was added last to start the reaction. The reaction mixture was added to various concentrations of TMP in a 96-well microtiter tray. The activity of DHFR (and therefore the susceptibility of DHFR to TMP) was measured by determination of the drop in absorbance at 340 nm after 3 min with a SpectraMax Plus 384 microplate reader (Molecular Devices, Sunnyvale, Calif.). IC50s were established by determination of the concentration of TMP required to bring about a 50% reduction of DHFR activity relative to that for the untreated control.
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MPCs have not been determined for mutators. We therefore used E. coli mutators as a model system and studied their responses to the antibiotics commonly used for the treatment of UTIs. The UT is invaded predominantly by aerobic bacteria in the course of an infection (34). However, anaerobes can also be recovered from patients with UTIs (3, 33), indicating that anaerobic sites exist within the UT. It was therefore relevant to determine MPCs for E. coli under aerobic and anaerobic conditions. To our knowledge MPCs have not previously been reported for anaerobes or facultative organisms under anaerobic conditions.
Mutant selection windows and selection indices were therefore experimentally defined for E. coli mutators by determination under aerobic and anaerobic conditions of the MICs and MPCs (Table 2) of a set of antimicrobial drugs used as single agents for the treatment of UTIs (16, 22). The majority of studies were performed with strains 1411, 1412, 1413, and 1417 (Table 1). However, since these strains contain a gyrA (Ser83
Leu) mutation (21), they were not used for further work with CIP. Consequently, MIC and MPC data for CIP were generated with CIP-sensitive mutator strain CSH115 (mutS) and its parent, CSH109 (Table 1).
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TABLE 2. MICs and MPCs for parent and mutator strains under aerobic and anaerobic conditions
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MPCs, pharmacokinetic parameters of anti-UTI drugs, and prediction of resistance emergence. Measurement of the MPC is useful for predicting the in vivo emergence of drug resistance when the MPC is considered along with the pharmacokinetic data for antimicrobial agents (38). During chemotherapy it may be impossible to maintain drug concentrations above the MPC, particularly as Cmin is approached. Consequently, when MPCs exceed achievable drug concentrations at any point in the dosing schedule, there is the potential for selection of drug-resistant mutants in vivo.
Pharmacokinetic data for anti-UTI drugs (Table 3) were compared with the MPCs (Table 2) to predict the likelihood of mutant selection in vivo for both mutator and parent E. coli strains during treatment of UTIs. The pharmacokinetic data that we considered were Cmaxs and Cmins in the urine of both healthy patients and renal failure patients and Cmaxs and Cmins in the serum of healthy patients after application of standard therapeutic regimens for the treatment of UTIs. Renal failure can be due to a number of causes. However, the pharmacokinetic data accessible from the literature (Table 3) do not address drug levels in relation to specific renal symptoms. Concentrations in serum are surrogates of concentrations in renal tissue for patients without renal failure (12).
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TABLE 3. Pharmacokinetic parameters for anti-UTI drugs in humans
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Mutation frequencies for resistance at drug concentrations below the MPC. The data presented above predict the emergence of resistance to GEN, TMP, and CTX in E. coli during therapy for UTIs. However, since the MPCs of these drugs were no greater for mutators than for the parent strain, the mutants were expected to express similar levels of antibiotic resistance, probably reflecting similar genotypes. Indeed, the MICs of individual drugs for the mutants, whether they were derived from mutator or normal hosts, were similar and no greater than twice the concentrations initially used for mutant selection (data not shown).
Although the types of mutations arising in mutators and normal strains may be similar, the frequency at which resistant mutants arise in mutators may be considerably elevated for certain antibiotics (21). We therefore examined the frequencies of mutations for resistance to GEN, TMP, and CTX under appropriate aerobic or anaerobic conditions at those pharmacokinetic Cmaxs or Cmins of the drugs in the UT that fell below the MPCs of these agents (Table 4). Apart from selection for resistance with the Cmin of GEN in urine (16 µg/ml) under anaerobic conditions (Table 4), mutators gave rise to resistant mutants at frequencies 10- to 100-fold greater than those for their parents (Table 4).
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TABLE 4. Mutation frequencies under aerobic and anaerobic conditions at concentrations of TMP, GEN, and CTX expected in vivo
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Two TMP-resistant mutants derived from each of the starting strains 1411, 1412, 1413, and 1417 were selected at random for further analysis. KM13 and KM14 were derived from strain 1411, KM15 and KM16 were derived from 1412, KM17 and KM18 were derived from 1413, and KM19 and KM20 were derived from 1417. The folA genes and their promoter regions of mutants KM13 to KM20 and their parents were sequenced following PCR amplification of folA. All mutants carried a single point mutation in folA (Ile94
Leu). In vitro TMP inhibition of DHFR from mutator strain 1412 (TMP IC50, 0.156 µg/ml) and one of the TMP-resistant mutants (KM15; TMP IC50, 4.7 µg/ml) confirmed that resistance was mediated by the altered DHFR.
Two CTX-resistant mutants derived from each of the starting strains 1411, 1412, 1413, and 1417 were selected at random for analysis of resistance mechanisms. KM21 and KM22 were derived from strain 1411, KM23 and KM24 were derived from strain 1412, KM25 and KM26 were derived from strain 1413, and KM27 and KM28 were derived from strain 1417. The chromosomally encoded mar locus in E. coli determines low-level resistance to a number of chemically unrelated antimicrobial agents, including ß-lactam antibiotics (2). Mutations within mar, at either marO or marR, lead to increased levels of expression of mar-specific transcripts, which cause decreased levels of expression of the porin OmpF and increased levels of expression of the AcrAB efflux pump (25). However, sequencing of marOR of CTX mutants KM21 to KM28 revealed no marOR mutations (data not shown).
EB is a substrate for many multidrug resistance (MDR) efflux pumps in E. coli, including AcrAB (35); and accumulation of this agent, determined fluorometrically, indicates MDR activity. Steady-state accumulation of EB was enhanced in acrAB-knockout strain SM1411 and decreased in marOR mutant AG112 (Fig. 1). However, EB accumulation levels were not altered in a representative CTX-resistant mutant, KM21 (Fig. 1). In addition, the MICs of EB and CTAB for mutants KM21 to KM27 were inconsistent with the MIC profiles of the MDR mutants characterized (35). Representative data for mutant KM21 and the MDR mutants are shown in Table 5. The data indicate that the susceptibilities to EB and CTAB are unaltered in mutant KM21 but that the susceptibilities of mutants SM1411 and AG112 differ from those of their parent strains.
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FIG. 1. Accumulation of EB by various E. coli strains. Fluorescence data have been normalized relative to the fluorescence for strain 1411 and are the means of at least four determinations. Bars represent standard deviations.
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TABLE 5. Susceptibilities of E. coli strains to EB and CTAB
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FIG. 2. Outer membrane protein profiles of KM21, KM23, KM25, and KM27 and their parent strains (strains 1411, 1412, 1413, and 1417, respectively).
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Concluding remarks. Mutators with defects in MMR appear to be an important clinical source of drug-resistant bacteria (9, 21, 26). Using a model for the in vivo behavior of E. coli mutators during exposure to anti-UTI drugs, we demonstrated that they have the potential to generate mutants with low-level resistance to TMP, GEN, and CTX during standard schedules of dosing with these drugs. Although the types of mutations arising in mutators and normal strains appear to be similar, the increased frequency at which resistance arises in mutators is cause for concern. Since bacterial populations in excess of 1010 organisms can occur in patients with UTIs (3), E. coli mutators are indeed a likely source of low-level antibiotic-resistant mutants in vivo.
The emergence of mutant populations possessing low-level antibiotic resistance increases the chance of survival of the bacterial population in the host during chemotherapy and provides an important platform for the development of high-level antibiotic resistance (4). We therefore conclude that E. coli mutators present an enhanced risk for the emergence of antibiotic resistance during treatment for UTIs. Our results agree with those of Oliver et al. (26), who suggested that mutators are also risk factors in the treatment of P. aeruginosa infections. Whether mutators of other clinical species pose a similar threat has yet to be established.
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