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Record W2164203391 · doi:10.1093/infdis/jis281

Fluoroquinolone Resistance in Neisseria gonorrhoeae: Fitness Cost or Benefit?

2012· letter· en· W2164203391 on OpenAlexaff
J A Dillon, Rajinder P. Parti

Bibliographic record

VenueThe Journal of Infectious Diseases · 2012
Typeletter
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsNeisseria gonorrhoeaeGonorrheaNeisseriaResistance (ecology)MicrobiologyAntibiotic resistanceNeisseriaceaeBiologyMedicineVirologyBacteriaAntibioticsGeneticsEcology

Abstract

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(See the article by Kunz et al, on pages 1821–9.) The successful treatment of gonorrhea, presently the second most prevalent bacterial sexually transmitted infection worldwide, has historically taken full advantage of the introduction of successive new categories of antimicrobial agents to successfully eliminate the microorganism causing this disease, Neisseria gonorrhoeae. New antibiotics have replaced older ones for treatment because N. gonorrhoeae has progressively developed resistance to each class introduced; first to sulphonamides, then to penicillins, tetracyclines, and then quinolones and macrolides [1, 2]. While the last class of antimicrobial effective for the treatment of gonorrhea is the third-generation cephalosporins, more and more reports are emerging of in vitro decreased susceptibility and treatment failures to the oral cephalosporins, such as cefixime, coupled with recent reports of strains with high-level resistance to ceftriaxone [3–5]. The strains with high-level resistance to cephalosporins also exhibited resistance or reduced susceptibility to several other antibiotics. Thus, there is a great concern that gonorrhea has become an untreatable superbug in certain instances, and the search for effective alternative treatment strategies and therapies, possibly a combination of antibiotics, is urgent [5, 6]. The emergence of resistance to some classes of antimicrobial has been so rapid and sustained that a basic understanding of the factors underscoring the ability of N. gonorrhoeae isolates to survive in potentially lethal antimicrobial environments, a measure of fitness, is lacking. The report by Kunz et al in this issue of the Journal of Infectious Diseases describes fluoroquinolone resistance in N. gonorrhoeae as it relates to microbial fitness. Fluoroquinolones were introduced for the treatment of gonorrhea infections in the late 1980s following the rise and worldwide dissemination of both plasmid-mediated and chromosomal resistance to penicillins and tetracyclines [1, 2]. However, the introduction of fluoroquinolones, such as ciprofloxacin, for treatment was quickly followed by reports of resistance, first in Asia and subsequently worldwide [7, 8]. Once resistance to fluoroquinolones reached 5% of the N. gonorrhoeae isolates tested in any region, the accepted cutoff where it is recommended that treatment be changed, the third-generation cephalosporins were then recommended as the primary antibiotics to treat gonorrhea infections [9, 10]. Interestingly, some countries reported almost 100% resistance of N. gonorrhoeae isolates to fluoroquinolones [11], and this high percentage of resistance has not diminished appreciably. In other countries, despite some diminution of total percentages of resistant isolates, fluoroquinolone resistance persists at levels higher than 5% despite the withdrawal of these antimicrobials for the treatment of gonorrhea [11, 12]. The withdrawal of antibiotics can result in some modest diminution of resistance levels, possibly because antibiotic resistant isolates may have less survival advantage, or be less fit, than susceptible isolates [13]. However, given the maintenance of high percentages of ciprofloxacin resistant N. gonorrhoeae, it seems that, in some circumstances, antibiotic-resistant N. gonorrhoeae isolates may have a fitness advantage and not a fitness deficit. Bacterial fitness has been broadly described as the ability of a particular strain to survive and reproduce [13]. Fitness, often measured by growth rate and generation time, is frequently adversely affected by the development of antibiotic resistance. Most models used for bacterial fitness analysis involve in vitro and in vivo competition assays [13], and a mathematical model with high predictive value that associates fitness costs with drug-resistant bacteria has been reported [14]. Overall, the challenge in measuring bacterial fitness in antimicrobial environments is to choose a set of assays in the context of different bacterial environmental niches, genetic variation and virulence, making the fitness studies as clinically relevant as possible [13]. Numerous reports have noted effects of antimicrobial resistance on bacterial fitness with antibiotics as diverse as penicillins, tetracyclines, sulfonamides, and quinolones [13, 15, 16]. For example, a 100-fold increase in minimum inhibitory concentrations (MICs) to penicillin in Streptococcus gordonii resulted in a fitness cost, as determined by in vitro competition growth and viability assays [17]. The effect of antibiotic resistance on bacterial fitness without antibiotics was evident when tetracycline-susceptible isolates of Escherichia coli outnumbered resistant isolates after the human infantile colon was simultaneously colonized by equal numbers of resistant and susceptible strains [15]. In contrast, pairwise growth competition assays attributed the fitness benefit of a drug resistant E. coli isolate to the presence of a sulphonamide resistance plasmid [18]. Fluoroquinolones are broad spectrum antibacterial agents that inhibit bacteria by targeting the bacterial-specific enzymes DNA gyrase and topoisomerase IV, subunits of which are encoded by gyrA and parC, respectively. Resistance to fluoroquinolones is mainly attributed to mutations in gyrase and topoisomerase genes and/or genes encoding drug efflux pumps [19]. The effect of such mutations on bacterial fitness has been studied in bacteria such as E. coli and Campylobacter jejuni [16, 19, 20]. Equal numbers of fluoroquinolone-resistant and susceptible strains of C. jejuni were coinoculated into a chicken infection model with the result that more resistant than susceptible isolates were recovered. This enhanced fitness of fluoroquinolone-resistant C. jejuni was linked directly to a resistance-conferring single point mutation in gyrA [20]. Recently, using in vitro methods as well as a urinary tract mouse infection model, a detailed analysis reported the relationships between isogenic strains carrying various mutations contributing to ciprofloxacin resistance and E. coli fitness [19]. Increased resistance to fluoroquinolones could be obtained even in the absence of antibiotic exposure, and a positive relationship between reduced susceptibility to ciprofloxacin and increased E. coli fitness was demonstrated [19]. Ciprofloxacin-resistant N. gonorrhoeae isolates carry a number of different mutations in gyrA and parC, especially at codons Ser91 and Asp 95 in GyrA or Asp 86 in ParC [11, 21]. It is not known how these mutations might affect gonococcal fitness, and this is the subject of the article reported in this issue. It should be noted that N. gonorrhoeae is an obligate human pathogen, and, aside from the chimpanzee, an animal model to study infection eluded researchers in the field for some time [22]. More recently, however, a 17β-estradiol-treated BALB/c mouse female genital tract infection model has been developed to study N. gonorrhoeae genital tract infections [23]. Kunz et al report on the fitness benefit in N. gonorrhoeae due to the fluoroquinolone intermediate-level resistance-conferring substitutions Ser91Phe and Asp95Asn in GyrA (referred to as gyrA91/95). Interestingly, an additional Asp86Asn substitution in ParC (parC86), which increased the MIC to a clinically significant level, curbed this fitness benefit which, however, was again restored by compensatory mutations [ie, mutation(s) at another site that restores or improves fitness]. The authors analyzed the effects of individual mutations using isogenic strains in a combination of in vitro assays and a competitive murine infection model. When Ser91Phe and Asp95Asn substitutions were made in the gyrA subunit, the fluoroquinolone-sensitive strain N. gonorrhoeae FA19 acquired intermediate ciprofloxacin resistance, and in vitro growth rate showed a slight growth disadvantage. However, this same mutant had a fitness benefit over the isogenic parent strain in the competitive mouse female genital tract infection model. In contrast, a gyrA91/95, parC86 mutant strain displayed high ciprofloxacin resistance but reduced fitness in the mouse, as well as reduced growth in vitro, when compared to the isogenic parent strain. Kunz et al propose that the intermediately resistant gyrA91/95 mutant, which has an in vivo fitness benefit, can serve as a reservoir for the development of highly-resistant isolates, as the single parC86 mutation was all that was needed to confer high level ciprofloxacin resistance (MIC 6 µg/mL). The authors also affirm that other adaptive mutations that contribute to resistance may have different effects on fitness. Nevertheless, the importance of studying the effects of specific resistance mutations in vivo is clear. Earlier investigations reported on the contribution of MtrCDE, the multidrug resistance efflux pump in N. gonorrhoeae, on gonococcal fitness in a mouse vaginal infection model [1, 23]. In N. gonorrhoeae, the MtrCDE efflux pump, transcriptionally regulated by mtrR (repressor) and mtrA (activator), expels macrolides, penicillins, and host-derived antimicrobials (ie, antimicrobial peptides, bile salts), thus conferring nonspecific antibiotic resistance. MtrCDE-deficient gonococci and mtrA mutants showed a fitness loss, whereas mtrR mutants with high antibiotic resistance had a fitness advantage in murine experiments, as compared to wild-type bacteria [23, 24]. Interestingly, a spontaneous compensatory mutation in the mtrR locus in a fitness-deficient mtrA mutant restored the fitness to wild-type levels during murine infection [24]. Extending these observations to fluoroquinolone resistance, Kunz and colleagues described the fitness effects of gyrA91/95 and parC86 substitutions on a macrolide-resistant mtrR-79 mutant (this strain has a deletion in the promoter upstream of mtrR). The gyrA91/95 mutation conferred an in vivo fitness benefit to mtrR-79–mutant gonococci, while the gyrA91/95, parC86, mtrR-79 mutant displayed a distinct fitness loss. However, the study becomes all the more interesting, as the authors observed spontaneous fitness cost–compensatory mutations in the gyrA91/95, parC86, mtrR-79 mutant, which caused repair of mtrR-79 and alteration of the gyrA91/95 mutation during infection. As the mtrR-79 mutation by itself promotes fitness, its repair compensating for fitness loss in the gyrA91/95, parC86, mtrR-79 mutant is interesting. It is clear from this study that compensatory mutations have an important effect on the fitness of N. gonorrhoeae isolates resistant to ciprofloxacin and that the assessment of other such mutations may better explain the emergence and maintenance of gonococcal resistance to antibiotics. In conclusion, it appears that high percentages of ciprofloxacin-resistant isolates can be maintained because of the fitness advantage provided by mutations in gyrA. Although this advantage could be abrogated by a mutation in parC, which confers a high level of resistance, compensatory mutations in mtrR and gyrA can restore gonococcal fitness. This helps explain why the antimicrobial susceptibility of N. gonorrhoeae isolates to ciprofloxacin may not be restored to under 5% of isolates tested despite the withdrawal of the antibiotic for the treatment of gonorrhea. In addition, the continued use of ciprofloxacin for other disease conditions may also contribute to the selection and maintenance of strains with mutations that contribute to fluoroquinolone resistance and improved gonococcal fitness. Potential conflicts of interest. All authors: No reported conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0150.009
Insufficient payload (model declined to judge)0.0060.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.290
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations11
Published2012
Admission routes1
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