Bacteria with increased mutation frequency and antibiotic resistance are enriched in the commensal flora of patients with high antibiotic usage

Ingegerd Gustafsson1, Maria Sjölund1, Erik Torell2, Marie Johannesson3, Lars Engstrand1,4, Otto Cars1,4 and Dan I. Andersson4,*

1 Antibiotic Research Unit, Department of Medical Sciences, Section of Clinical Bacteriology, 2 Section of Infectious Diseases and 3 Uppsala CF Center, Department of Womens’ and Childrens’ Health, Uppsala University Hospital, Uppsala; 4 Swedish Institute for Infectious Disease Control, Department of Bacteriology, SE-171 82 Solna, Sweden

Received 26 May 2003; returned 30 June 2003; revised 13 July 2003; accepted 23 July 2003


    Abstract
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Background: We examined how prolonged antibiotic treatment affected the resistance and mutation frequency of human microflora isolated from intestine (Escherichia coli, enterococci spp.), pharynx ({alpha}-streptococci) and nostril (coagulase-negative staphylococci, CoNS).

Methods: Samples were collected from patients at the Center of Cystic Fibrosis (n = 18) and the haematology ward (n = 18) of the University Hospital, Uppsala, Sweden. The individually used amount of antibiotics for 1 year was recorded as the defined daily dose (DDD). Primary health care patients (n = 30), with no antibiotic treatment for 1 year before sampling, were used as controls. Three isolates of each bacterium from each patient were examined. Antibiotic susceptibilities were determined by disc diffusion. Mutation frequencies to rifampicin resistance were measured on 30 independent cultures of each bacterial species from each individual by plating on rifampicin agar plates. For {alpha}-streptococci the mutation frequency to streptomycin resistance was also determined.

Results: Isolates from patients with high antibiotic use showed a pronounced shift towards increased resistance and a small but significant increase in the mutation frequency compared with isolates from the controls. For E. coli, enterococci and CoNS the increase in geometric mean mutation frequency in the patient group was 3-, 1.8- and 1.5-fold, respectively (P values 0.0001, 0.016 and 0.012). For {alpha}-streptococci there was a significant difference in geometric mean mutation frequency between patient and control groups for streptomycin resistance (P = 0.024) but not for rifampicin resistance (P = 0.74).

Conclusions: High antibiotic use selected for commensals with highly increased resistance and a slight increase in mutation frequency.

Keywords: human microflora, antibiotic treatment, selection, mutators


    Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
The human microflora constitutes a complex ecological system that plays an important role in human health, for example, by stimulating the immune response, aiding in the digestion of food and helping prevent pathogens from colonizing epithelial surfaces. Antimicrobial agents are known to influence the microflora and the extent of disturbance depends on a variety of factors, including drug dosage, route of administration and the pharmacokinetic/dynamic properties of the agent.1 Even though the microflora may return to normal rapidly after completion of a treatment, long-term persistence (several years) of selected resistant commensal bacteria has been reported.2 Such persistence and the natural exchange of genes between bacteria make the microflora a reservoir of resistance genes for potential spread to pathogens.

Bacteria with increased mutation rate, so-called mutators, have been found among pathogenic isolates of several bacterial species.3,4 For example, in Escherichia coli, Salmonella typhimurium, Helicobacter pylori and Pseudomonas aeruginosa between 1% and 36% of clinical isolates are mutators.58 Several types of mutators have been described and their increase in mutation rates might vary between five- and 5000-fold.9,10 Whether an increased mutation rate is deleterious or beneficial depends on several factors, including the stability of the environment. Under constant conditions mutators are generally at a disadvantage because they generate deleterious mutations at a higher rate than a non-mutator.11 In contrast, in a rapidly changing environment mutators might be selected because they have a higher probability of generating a beneficial mutation.12 Thus, mutators are enriched because of the genetic linkage to the adaptive mutations they generate rather than as a direct result of their higher mutation rate.11 Selection for mutators in pathogenic bacteria might occur because mutators increase the rate of, for example, antigenic surface variation or acquisition of antibiotic resistance.13 Even though under laboratory conditions14 and in animal models12 selection for antibiotic resistance can rapidly enrich for mutators, it remains unclear whether clinical use of antibiotics is an important selector for strains with an increased mutation frequency. Recent work by Oliver et al.6 showed that 36% of P. aeruginosa lung isolates from cystic fibrosis patients were mutators. Furthermore, there was a positive correlation between mutation rate and antibiotic resistance, suggesting that antibiotic use and associated selection for antibiotic resistance caused mutator enrichment. However, an alternative selective force that could have caused enrichment for mutators in this particular type of chronic infection was the continuous deterioration of the lung environment and the reiterated challenges by the host’s immune system.

Thus, to examine a situation where the host environment is unaltered, and not directly affected by a current infectious pathogenesis, we examined whether extensive, high antibiotic use enriched for commensal bacteria with increased mutation frequency. The mutation frequency and resistance patterns were studied in E. coli, enterococci, {alpha}-streptococci and coagulase-negative staphylococci (CoNS) isolated from patient groups with high antibiotic use and a control group with no antibiotic exposure for the previous year.


    Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Subjects

Samples from nostril, pharynx and faeces were collected from patients at the Center of Cystic Fibrosis (n = 18), and Department of Haematology (n = 18) of the University Hospital, Uppsala, Sweden, subcultured within 24 h and then frozen at –70°C. Each patient’s use of antibiotics during 1 year was recorded as the defined daily dose (DDD).15 Primary health care patients (n = 30) with no antibiotic treatment for 1 year before sampling were used as controls. The age range, median and mean for the patients and controls were 2–77, 32 and 37 years and 33–77, 52 and 53 years, respectively. The ethics committee of the Faculty of Medicine at Uppsala University approved the study.

Bacteria

Three isolates of each bacterium were randomly chosen and verified. Faecal E. coli were isolated on CLED agar (cysteine lactose electrolyte deficient, brolacin agar; Merck, Darmstadt, Germany), incubated at 35°C, and verified by negative Voges-Proskauer test, urea and H2S, and positive indole reactions. Faecal enterococci were isolated on M-Enterococcus agar (Difco) as purple colonies and verified by positive aesculin (BBL Microbiology Systems) reactions. The {alpha}-streptococci from pharynx and CoNS from nostrils were isolated on blood agar plates (Columbia agar base with 5% horse blood; Acumedia Manufactures Inc., Baltimore, MD, USA) and incubated at 35°C in 5% CO2. {alpha}-Streptococci were verified by green haemolysis, negative optochin (Oxoid) and negative aesculin (BBL) tests. The CoNS were verified by a negative DNase test (Acumedia).

Susceptibilities and MIC

Antibiotic susceptibilities were determined by disc diffusion (Oxoid) on IsoSensitest agar (Oxoid) according to recommendations by the Swedish Reference Group for Antibiotics (available at www.srga.org). The antibiotics where chosen to represent the major classes. For those antibiotic–bacteria combinations lacking breakpoints the inhibition zone diameters were registered. MICs were determined by Etest (AB Biodisk, Solna, Sweden) on IsoSensitest agar according to the manufacturer’s instructions.

Mutation frequency to rifampicin resistance

The mutation frequency to rifampicin resistance was calculated from 30 independent cultures (10 from each of the three isolates from each patient/control). The cultures were inoculated with 103 bacteria, from fresh broth preculture, in 0.4 mL Todd–Hewitt broth (Difco). The pre-cultures were controlled for pre-existing mutants by plating 104 bacteria on blood agar plates containing rifampicin (Duchefa, Haarlem, The Netherlands) at a concentration of 50 mg/L for E. coli and enterococci, and 0.1 mg/L for {alpha}-streptococci and CoNS. If pre-existing mutants were found the test cultures were discarded (this was the case for one E. coli and two CoNS isolates). The cultures were incubated overnight at 35°C, giving 108–109 cfu/mL. The number of bacteria was determined by viable counts in 20 strains of E. coli, enterococci and CoNS, respectively. The optical density was also measured at 540 nm on all cultures. For the additional strains, the optical density was used to ensure that the cultures had reached maximal turbidity. To estimate the total number of bacteria the mean cfu/mL of the 20 viable counts were used. The number of {alpha}-streptococci was determined by viable count. Each culture was spread on a rifampicin-containing blood agar plate (50 mg/L for E. coli and enterococci or 0.1 mg/L for {alpha}-streptococci and CoNS). Different concentrations of rifampicin were used because of differences in intrinsic resistance between the bacteria. Plates were dried and incubated for 24 h and then colonies were counted. The mutation frequency for each isolate was determined from the median number of resistant mutants from the 10 cultures divided by the number of bacterial cells applied on the agar plates, and the geometric mean of the mutation frequency for the three isolates was calculated.

Mutation frequency to streptomycin resistance

The {alpha}-streptococci were also analysed for their mutation frequency to streptomycin resistance. Five independent cultures of one strain from each patient (n = 14) and controls (n = 17) were included. The remaining strains were excluded because of high initial MICs of streptomycin. Todd–Hewitt broth (50 mL) was inoculated with 103 bacteria from a fresh broth culture and incubated overnight at 35°C in 5% CO2. The number of bacteria was determined by viable count from one culture for each strain. The bacteria were concentrated by centrifugation and the resuspended pellet, ~1010 bacteria, was applied to blood agar plates containing 120 mg/L streptomycin (Duchefa) and then colonies were counted after 24 h.

Sequencing of the rpoB gene

The rpoB gene from four independent rifampicin-resistant colonies of enterococci, {alpha}-streptococci and CoNS was sequenced to verify that the resistant mutants had mutations in the rpoB gene. In E. coli rifampicin resistance is caused by rpoB mutations.16 Primers for the ß-subunit of rpoB were designed using Streptococcus pyogenes (GenBank accession number AJ295718) and Staphylococcus warneri (GenBank accession number AF325895) sequences. DNA was prepared with Dneasy Tissue kit (Qiagen). Five microlitres of sample was added to 45 µL PCR mixture, consisting of PCR buffer (Amersham Bioscience), 0.2 mmol/L deoxynucleostide triphosphate, 1 U Taq polymerase (Amersham Bioscience), and 2 pmol/µL of each primer. Amplification was performed in a thermal cycler (GeneAmp PCR system 9700; Applied Biosystems) with an initial denaturing step of 94°C for 5 min followed by 30 cycles of 94°C for 30 s, 55°C for 30 s and 72°C for 30 s. An additional extension step of 72°C for 7 min completed the PCR. Negative controls were included and the reactions were evaluated in 1% agarose gel electrophoresis. The PCR products were sequenced by using ABI Prism BigDye terminator cycle sequencing ready reaction kit analysed in 310 Genetic Analyzer (Applied Biosystems) and compared with the original strains. All mutations were located within cluster I in the rpoB site as described in E. coli.16 The enterococci had the substitutions Gly-522->Asp (GGT->GAT) or His-526->Arg (CAT->CGT). The {alpha}-streptococci showed similar point mutations at three sites in cluster I: Asp-516->Asn (GAC->AAC), Ser-522->Leu (TCA->TTA) or His-526->Tyr/Asn (CAC->TAC/AAC). In CoNS, two mutations were identified within cluster I: His-526->Tyr (CAC->TAC) and Ser-531->Phe (TCT->TTT).

Sequencing of the rpsL gene in {alpha}-streptococci

The rpsL gene from three independent streptomycin-resistant colonies of {alpha}-streptococci was sequenced to verify that the resistant mutants contained mutations in the rpsL gene, as has been shown in, for example, E. coli.17 Primers were constructed from the rpsL gene of S. pyogenes (GenBank accession number AE006493). PCR and sequencing was performed as described above. All three strains had an A->T mutation that resulted in a Lys->Ile substitution at a position corresponding to codon 42 in E. coli.17

Statistical analysis

The statistical significance of the difference in mutation frequency was determined from the geometrical mean by Mann–Whitney test in Statistical Analyzing System version 8. Further comparison of mutation frequencies and total DDD was performed with Microsoft Excel.


    Results
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 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Distribution of antibiotic usage and antibiotic susceptibilities

The cystic fibrosis and haematology patients had a very high use of antibiotics during 1 year: on average 382 (range 36–1187) and 163 (range 30–535) DDDs, respectively (Figure 1). If neutropenic, the haematology patients received ciprofloxacin treatment, which reduced the probability of recovering E. coli from faeces. Thus, only five of 18 haematology patients had E. coli, whereas among cystic fibrosis patients 15/18 had E. coli. The number of strains from patients and controls are presented in Figure 2. A clear shift towards increased resistance was seen among isolates from antibiotic-treated patients for practically all types of resistances examined (Figure 2). For example, the frequency of ciprofloxacin resistance in enterococci and CoNS was 63% and 67%, respectively, as compared with 0% in the controls. Similarly, the frequency of erythromycin-resistant CoNS was 52% in the patient group and 0% in the controls. Resistance to tobramycin was uncommon in E. coli and CoNS, in spite of a rather high use of tobramycin. Finally, vancomycin and imipenem resistance was not detected at all in the patient group, but these drugs were also the least used.



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Figure 1. Distribution of antibiotic use for the two patient groups.

 


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Figure 2. Susceptibility pattern for (a) E. coli, (b) enterococci, (c) {alpha}-streptococci and (d) CoNS. S, I and R indicate susceptible, intermediate and resistant breakpoints according to the Swedish reference group for antibiotics. The numbers indicate inhibition zone diameters (mm) divided into major groups where no breakpoints were available.

 
Mutation frequency

The frequency at which rifampicin-resistant mutants appear in vitro is often used as an indicator of the overall mutation frequency in bacteria.8,12 Rifampicin resistance in, for example, E. coli is caused by a limited number of mutations in the rpoB gene. We confirmed that this was the case also for the other commensals examined (see Materials and methods). The experimentally determined mutation frequencies to rifampicin resistance for each species are shown in Figure 3 (see Materials and methods). When comparing all isolates the mutation frequency to rifampicin resistance varied between 10–9 and 10–6, and for each species there was a 10- to 100-fold range of frequencies. When comparing the patients and controls a significant difference in mutation frequency was noted for E. coli, enterococci and CoNS. Thus, the patients had commensal bacteria with a 3-, 1.8- and 1.5-fold higher mutation frequency as compared with the controls (P = 0.0001, 0.016 and 0.012, respectively). For {alpha}-streptococci, no significant difference (P = 0.74) in mutation frequency to rifampicin resistance between the controls and patients was evident. To further assess whether {alpha}-streptococci from patients had an increased mutation frequency, we also measured the mutation frequency to streptomycin resistance for this group of bacteria. The mutation frequency was 4.7 x 10–10 and 1.5 x 10–10 for patients and controls, respectively (P = 0.024), suggesting that strains with an increased mutation frequency might be enriched also in the {alpha}-streptococci. Why this difference was only seen for streptomycin resistance and not rifampicin is unclear, but might be related to which types of base pair substitutions cause resistance to the two antibiotics.



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Figure 3. Mutation frequencies to rifampicin resistance for four species of bacteria isolated from patients and controls. Each data point represents the mutation frequency of one bacterial species from one patient or control. The overall geometric mean mutation frequency for each bacterial species for the whole patient and control group is indicated by a line.

 
Mutation frequency in relation to the level of resistance to different antibiotic classes and DDD

We examined whether there was a correlation between the level of resistance to different antibiotic classes and the mutation frequency. For aminoglycosides, ß-lactams, macrolides and trimethoprim–sulfamethoxazole no correlation was observed (not shown). In contrast, when comparing ciprofloxacin-resistant and -susceptible isolates of E. coli within the patient group, the mutation frequencies differed significantly. Thus, ciprofloxacin-resistant E. coli showed a higher mutation frequency than the susceptible isolates (P = 0.036). Because of this observation the MICs of ciprofloxacin were determined for all strains of E. coli and enterococci from patients and controls. The MICs of ciprofloxacin for E. coli varied between 0.006 and >32 mg/L for patients and 0.004 and 0.016 mg/L for controls, and this difference was highly significant (P = 0.002). Similarly, the corresponding MICs of ciprofloxacin for enterococci were 0.38–>32 mg/L for patients and 0.25–3 mg/L for controls (P = 0.0006). Furthermore, we examined whether antibiotic exposure (DDDs) was correlated with level of resistance or mutation frequency using linear regression. There was no correlation between total DDD of antibiotics and mutation frequency, nor between DDD of fluoroquinolones and ciprofloxacin resistance or mutation frequency. Finally, within each patient there was no correlation between the mutation frequencies for the different bacterial species.


    Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
Theoretical considerations and experimental studies12,14,18 show that mutators may be enriched when bacteria are exposed to a changing environment, e.g. repeated challenges of antibiotics, host immune responses or tissue damage caused by pathogenesis. Previous studies have concerned pathogenic bacteria. We wanted to study the impact of antibiotic use on the enrichment of mutators in the commensal microflora in order to reduce the likelihood that changes in the environmental conditions due to disease pathogenesis were the cause of selection for mutators. Thus, with regard to the microflora, antibiotic use was the primary selective parameter expected to vary between the patient and control groups. However, it should be noted that some of the haematology patients received cytostatic drugs that might disturb, for example, the local environment of the microflora or the host’s immune response. When comparing bacterial isolates from the two groups studied, a significant increase of the geometric mean mutation frequency (two- to three-fold) was observed for E. coli, enterococci and CoNS isolated from the antibiotic use group. When examining the correlation between increased mutation frequency and resistance for each individual class of antibiotics, a significant correlation could only be seen for ciprofloxacin resistance where the resistant E. coli showed a higher mutation frequency than the susceptible isolates. A potential explanation for why only the faecal commensals showed this correlation could be that the faecal flora might be differently exposed to the drug than the pharynx and skin flora. Selection for resistant mutants requires a concentration interval ‘selective window’19, where the concentration is high enough to prevent growth of the susceptible strain but low enough to allow growth of the resistant mutants. A substantial part of the fluoroquinolones in faeces is bound to various compounds, resulting in lower concentrations of active drug.20 Furthermore, high free levels of fluoroquinolones have been found in sweat.21 Thus, it is possible that in faeces there is a stronger selection for resistance (and mutators) than in sweat because the bacteria are exposed to the ‘selective window’ for a longer time period.22,23

Even though the increased mutation frequency in the patient group was significant, the magnitude of the increase was small. These increases could be caused by mutations of small effect in any of the processes that affect the mutation frequency in a bacterium (e.g. DNA polymerase, mismatch repair, excision repair, etc.). Unexpectedly, at least in the light of previous studies where frequencies of strong mutators were 1.2–36%6,7, only one such mutator (an E. coli from the patient group) was found among the 193 commensal isolates examined. One explanation for the rarity of strong mutators could be that for these investigated bacterial species, mutators are impaired for growth in the commensal flora of hosts, thereby preventing them increasing to a high frequency.12 A second potential explanation is that putative mutator genes were removed by recombination after resistance was acquired.24 Finally, a third possibility, and the one we find most likely, is that most of the antibiotics given to these patients are poor selectors of mutators. Thus, it is predicted that mutators are mainly enriched when the resistance is conferred by a chromosomal mutation (e.g. gyrA) that is formed at a higher rate in the mutator than the non-mutator. Most of the resistances in the examined bacteria result from genes that are located on horizontally transferred genetic elements (e.g. plasmids) and a mutator is not expected to increase the rate of plasmid transfer. The only exception is fluoroquinolone resistance, which is caused by sequential chromosomal mutations that confer stepwise increases in resistance.25 Thus, acquiring high-level fluoroquinolone resistance is predicted to enrich for mutators. Support for this idea comes from the finding that a significant correlation between resistance and increased mutation frequency was only seen for ciprofloxacin.

The shift towards increased resistance among the patient isolates was pronounced.26,27 We cannot say whether the resistant clones were pre-existing in the individuals, selected de novo during treatment or acquired from other sources during hospitalization, but it is clear that the resistant strains were enriched during treatment to eventually dominate the microflora. It is likely that the selection and persistence of resistant commensal strains with an increased mutation rate constitutes a risk factor for additional resistance development, transfer of resistance to pathogens24 and the occurrence of difficult-to-treat endogenous infections.


    Acknowledgements
 
We thank Anna Johnson and Elisabeth Nääs at the Cystic Fibrosis Center and Sissi Lundgren at Infectious Diseases for valuable contributions, and Kasia Gabrowska at Swedish Institute for Infectious Disease Control for statistical analysis. This work was supported by the Swedish Institute for Infectious Disease Control, the Swedish Research Council and the AFA Research Fund.


    Footnotes
 
* Corresponding author. Tel: +46-8-4572432; Fax: +46-8-301797; E-mail: dan.andersson{at}smi.ki.se Back


    References
 Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 
1 . Sullivan, A., Edlund, C. & Nord, C. E. (2001). Effect of antimicrobial agents on the ecological balance of human microflora. Lancet Infectious Diseases 1, 101–14.[CrossRef][Medline]

2 . Sjölund, M., Wreiber, K., Andersson, D. I. et al. (2003). Long-term persistence of resistant Enterococcus species after antibiotic treatment to eliminate Helicobacter pylori. Annals of Internal Medicine, in press.

3 . Matic, I., Radman, M., Taddei, F. et al. (1997). Highly variable mutation rates in commensal and pathogenic Escherichia coli. Science 277, 1833–4.[Free Full Text]

4 . Giraud, A., Radman, M., Matic, I. et al. (2001). The rise and fall of mutator bacteria. Current Opinion in Microbiology 4, 582–5.[CrossRef][ISI][Medline]

5 . LeClerc, J. E., Li, B., Payne, W. L. et al. (1996). High mutation frequencies among Escherichia coli and Salmonella pathogens. Science 274, 1208–11.[Abstract/Free Full Text]

6 . Oliver, A., Canton, R., Campo, P. et al. (2000). High frequency of hypermutable Pseudomonas aeruginosa in cystic fibrosis lung infection. Science 288, 1251–4.[Abstract/Free Full Text]

7 . Denamur, E., Bonacorsi, S., Giraud, A. et al. (2002). High frequency of mutator strains among human uropathogenic Escherichia coli isolates. Journal of Bacteriology 184, 605–9.[Abstract/Free Full Text]

8 . Björkholm, B., Sjölund, M., Falk, P. G. et al. (2001). Mutation frequency and biological cost of antibiotic resistance in Helicobacter pylori. Proceedings of the National Academy of Sciences, USA 98, 14607–12.[Abstract/Free Full Text]

9 . Miller, J. H. (1998). Mutators in Escherichia coli. Mutation Research 409, 99–106.[ISI][Medline]

10 . Oliver, A., Baquero, F. & Blazquez, J. (2002). The mismatch repair system (mutS, mutL and uvrD genes) in Pseudomonas aeruginosa: molecular characterization of naturally occurring mutants. Molecular Microbiology 43, 1641–50.[CrossRef][ISI][Medline]

11 . Taddei, F., Radman, M., Maynard-Smith, J. et al. (1997). Role of mutator alleles in adaptive evolution. Nature 387, 700–2.[CrossRef][ISI][Medline]

12 . Giraud, A., Matic, I., Tenaillon, O. et al. (2001). Costs and benefits of high mutation rates: adaptive evolution of bacteria in the mouse gut. Science 291, 2606–8.[Abstract/Free Full Text]

13 . Tanabe, K., Kondo, T., Onodera, Y. et al. (1999). A conspicuous adaptability to antibiotics in the Escherichia coli mutator strain, dnaQ49. FEMS Microbiology Letters 176, 191–6.[CrossRef][ISI][Medline]

14 . Mao, E. F., Lane, L., Lee, J. et al. (1997). Proliferation of mutators in a cell population. Journal of Bacteriology 179, 417–22.[Abstract]

15 . World Health Organization. (2001). WHO Collaborating Centre for Drug Statistics Methodology. ATC Index with DDD. WHO, Oslo, Norway.

16 . Jin, D. J. & Gross, C. A. (1988). Mapping and sequencing of mutations in the Escherichia coli rpoB gene that lead to rifampicin resistance. Journal of Molecular Biology 202, 45–58.[ISI][Medline]

17 . Timms, A. R., Steingrimsdottir, H., Lehmann, A. R. et al. (1992). Mutant sequences in the rpsL gene of Escherichia coli B/r: mechanistic implications for spontaneous and ultraviolet light mutagenesis. Molecular and General Genetics 232, 89–96.[Medline]

18 . Giraud, A., Matic, I., Radman, M. et al. (2002). Mutator bacteria as a risk factor in treatment of infectious diseases. Antimicrobial Agents and Chemotherapy 46, 863–5.[Abstract/Free Full Text]

19 . Negri, M. C., Lipsitch, M., Blazquez, J. et al. (2000). Concentration-dependent selection of small phenotypic differences in TEM beta-lactamase-mediated antibiotic resistance. Antimicrobial Agents and Chemotherapy 44, 2485–91.[Abstract/Free Full Text]

20 . Edlund, C., Lindqvist, L. & Nord, C. E. (1988). Norfloxacin binds to human fecal material. Antimicrobial Agents and Chemotherapy 32, 1869–74.[ISI][Medline]

21 . Hoiby, N., Jarlov, J. O., Kemp, M. et al. (1997). Excretion of ciprofloxacin in sweat and multiresistant Staphylococcus epidermidis. Lancet 349, 167–9.[CrossRef][ISI][Medline]

22 . Zhao, X. & Drlica, K. (2001). Restricting the selection of antibiotic-resistant mutants: a general strategy derived from fluoroquinolone studies. Clinical Infectious Diseases 33, Suppl. 3, S147–56.[CrossRef][ISI][Medline]

23 . Martinez, J. L. & Baquero, F. (2000). Mutation frequencies and antibiotic resistance. Antimicrobial Agents and Chemotherapy 44, 1771–7.[Free Full Text]

24 . Denamur, E., Lecointre, G., Darlu, P. et al. (2000). Evolutionary implications of the frequent horizontal transfer of mismatch repair genes. Cell 103, 711–21.[ISI][Medline]

25 . Drlica, K. & Zhao, X. (1997). DNA gyrase, topoisomerase IV, and the 4-quinolones. Microbiology and Molecular Biology Reviews 61, 377–92.[Abstract]

26 . Levy, S. B., Marshall, B., Schluederberg, S. et al. (1988). High frequency of antimicrobial resistance in human fecal flora. Antimicrobial Agents and Chemotherapy 32, 1801–6.[ISI][Medline]

27 . Lang, A., De Fina, G., Meyer, R. et al. (2001). Comparison of antimicrobial use and resistance of bacterial isolates in a haematology ward and an intensive care unit. European Journal of Clinical Microbiology and Infectious Diseases 20, 657–60.[ISI][Medline]