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. 2017 Jun 27;61(7):e00086-17. doi: 10.1128/AAC.00086-17

In Vitro Resistance Selection in Shigella flexneri by Azithromycin, Ceftriaxone, Ciprofloxacin, Levofloxacin, and Moxifloxacin

George P Allen 1,✉, Kayla A Harris 1
PMCID: PMC5487670  PMID: 28483960

ABSTRACT

Shigella flexneri continues to be a major cause of diarrhea-associated illness, and increasing resistance to first-line antimicrobials complicates the treatment of infections caused by this pathogen. We investigated the pharmacodynamics of current antimicrobial treatments for shigellosis to determine the likelihood of resistance promotion with continued global antimicrobial use. The mutant prevention concentration (MPC) and mutant selection window (MSW) were determined for azithromycin, ceftriaxone, ciprofloxacin, levofloxacin, and moxifloxacin against a wild-type strain of S. flexneri (ATCC 12022) and an isogenic gyrA mutant (m-12022). Time-kill assays were performed to determine antimicrobial killing. Concentrations of approved doses of ciprofloxacin, levofloxacin, and moxifloxacin are predicted to surpass the MPC for a majority of the dosage interval against ATCC 12022. However, against m-12022, concentrations of all fluoroquinolones are predicted to fall below the MPC and remain in the MSW for a majority of the dosage interval. Concentrations of ceftriaxone fall within the MSW for the majority of the dosage interval for both strains. All agents other than azithromycin displayed bactericidal activity in time-kill assays. Results of pharmacodynamic analyses suggest that all tested fluoroquinolones would achieve a favorable area under the concentration-time curve (AUC)/MPC ratio for ATCC 12022 and would restrict selective enrichment of mutants but that mutant selection in m-12022 would be likely if ciprofloxacin were used. Based on pharmacodynamic analyses, azithromycin and ceftriaxone are predicted to promote mutant selection in both strains. Confirmation of these findings and examination of novel treatment regimens using in vivo studies are warranted.

KEYWORDS: Shigella flexneri, mutant prevention concentration, mutant selection window

INTRODUCTION

The pathogenic bacterium Shigella flexneri is a major cause of dysentery and related morbidity and mortality worldwide, particularly in children less than 5 years of age in developing countries and travelers returning from tropical areas. In the 1990s, the number of annual cases of shigellosis worldwide was approximately 164.7 million, with 1.1 million resulting in death (1). Data from 2014 demonstrated an average of 5.81 cases per 100,000 individuals in the United States (2). The treatment of shigellosis has been complicated by the emergence of strains of S. flexneri that are resistant to many antimicrobials, including former first-line treatment options such as ampicillin, chloramphenicol, tetracyclines, and trimethoprim-sulfamethoxazole (SXT) (1). Current treatment guidelines for infectious diarrhea from the Infectious Diseases Society of America, published in 2001, recommend SXT, a fluoroquinolone (ofloxacin, norfloxacin, or ciprofloxacin), ceftriaxone, or azithromycin (3). In guidelines published by the WHO in 2005, ciprofloxacin was considered the first-line treatment for shigellosis, with ceftriaxone and azithromycin considered to be alternative therapies (4). However, the number of reported cases of reduced susceptibility to third-generation cephalosporins has been increasing (5, 6). Resistance to azithromycin has also been noted, and resistance was observed in 4.7% of Shigella isolates in the United States in 2014 (7). With the widespread use of ciprofloxacin to treat shigellosis, resistance to ciprofloxacin and other fluoroquinolones has been observed (8). Thus, the development of novel antimicrobial agents for shigellosis is needed. However, even if novel agents are discovered, it is important to reevaluate antimicrobial dosing to target strategies that restrict the emergence of resistant mutants.

The MIC is the standard measure of antimicrobial susceptibility. The mutant prevention concentration (MPC) is a susceptibility parameter that measures the minimum concentration that would block growth of the least susceptible bacterium present within a heterogeneous population (9, 10). The mutant selection window (MSW) is bordered by the MIC and MPC for a given bacterium exposed to an antimicrobial; it describes the range of concentrations that would inhibit growth of susceptible cells while selecting the growth of nonsusceptible cells. Thus, resistance is thought to be promoted when antimicrobial concentrations fall within the MSW (11). This has been shown using in vitro studies and studies in animals (12–23).

We determined the likelihood of resistance selection and the relative levels of antibacterial killing by azithromycin, ceftriaxone, ciprofloxacin, levofloxacin, and moxifloxacin against S. flexneri. We performed MSW testing to evaluate the likelihood of mutant selection by all agents and used time-kill assays to determine relative levels of bactericidal activity against a fully susceptible strain of S. flexneri and an isogenic gyrA mutant selected through levofloxacin exposure.

(Portions of this work were presented at ASM Microbe 2016, Boston, MA, June 2016, and the 55th Interscience Conference on Antimicrobial Agents and Chemotherapy, San Diego, CA, September 2015.)

RESULTS

Susceptibility testing and MPC determinations.

MIC and MPC values are shown in Table 1; MPC values were the same at 48 h and 72 h. According to CLSI interpretive standards, both ATCC 12022 and m-12022 are susceptible to ceftriaxone, ciprofloxacin, and levofloxacin (24). CLSI has not published interpretive standards for moxifloxacin against Enterobactericeae spp. According to European Committee on Antimicrobial Susceptibility Testing (EUCAST) susceptibility criteria, both ATCC 12022 and m-12022 are susceptible to moxifloxacin (25). No published susceptibility breakpoint is available for azithromycin.

TABLE 1.

MIC and MPC results

Antimicrobial ATCC 12022
 m-12022
MIC (mg/liter) MPC (mg/liter) MIC (mg/liter) MPC (mg/liter)
Azithromycin 4 >64 8 >64
Ceftriaxone 0.0625 0.5 0.125 2
Ciprofloxacin 0.03125 0.25 0.25 2
Levofloxacin 0.0625 0.5 0.25 2
Moxifloxacin 0.0625 0.5 0.5 2
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PD analysis.

Results of pharmacodynamic (PD) analyses (of the percentage of time during which concentrations were within the MSW [%TMSW], percentage of time during which concentrations were greater than the MPC [%T>MPC], and area under the concentration-time curve [AUC]/MPC ratio) are shown in Table 2. Azithromycin was the only antimicrobial tested that failed to achieve concentrations above the MIC; thus, its concentrations never entered the MSW for either strain. Concentrations of ceftriaxone are predicted to fall within the MSW for 69% of the dosage interval for ATCC-12022 and 98% of the dosage interval for m-12022. Ciprofloxacin and moxifloxacin concentrations exceeded the MPC for 100% of the dosage interval in testing against ATCC-12022, whereas levofloxacin concentrations exceeded the MPC for 87% of the dosage interval. Concentrations of all three fluoroquinolones fell below the MPC and within the MSW for the majority of the dosage interval in testing against m-12022.

TABLE 2.

Pharmacodynamic analyses

Antimicrobial ATCC 12022
 m-12022
%T>MPC %TMSW AUC/MPC %T>MPC %TMSW AUC/MPC
Azithromycin 0 0 <0.1 0 0 <0.1
Ceftriaxone 31 69 NAa 0 98 NA
Ciprofloxacin 100 0 77 2 98 10
Levofloxacin 87 13 66 28 72 16
Moxifloxacin 100 0 58 22 78 14
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a

NA, not applicable.

Time-kill assays.

Ceftriaxone, ciprofloxacin, levofloxacin, and moxifloxacin achieved bactericidal activity against both ATCC 12022 (Fig. 1) and m-12022 (Fig. 2), while azithromycin achieved bacteriostatic activity only. For ATCC 12022, colony count reductions recorded at the 4-h time point were as follows: azithromycin, −1.2 log10 CFU/ml; ceftriaxone, 2.2 log10 CFU/ml; ciprofloxacin, 2.4 log10 CFU/ml; levofloxacin, 2.7 log10 CFU/ml; moxifloxacin, 3.6 log10 CFU/ml. For m-12022, colony count reductions recorded at the 4-h time point were as follows: azithromycin, −0.7 log10 CFU/ml; ceftriaxone, 2.5 log10 CFU/ml; ciprofloxacin, 4.2 log10 CFU/ml; levofloxacin, 3.7 log10 CFU/ml; moxifloxacin, 4.0 log10 CFU/ml. The rank order of agents with respect to colony count reductions of ATCC 12022 was moxifloxacin > levofloxacin > ciprofloxacin > ceftriaxone > azithromycin. For m-12022, the rank order was ciprofloxacin > moxifloxacin > levofloxacin > ceftriaxone > azithromycin.

FIG 1.

FIG 1

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Activity of all antimicrobials against ATCC 12022. The data are shown as follows: filled circle, growth control; open circle, azithromycin (0.28 mg/liter); filled square, ceftriaxone (0.95 mg/liter); open square, ciprofloxacin (2.08 mg/liter); filled triangle, levofloxacin (3.93 mg/liter); open triangle, moxifloxacin (2.7 mg/liter). The dotted line indicates the lower limit of detection for bacterial quantification, 2 log10 CFU/ml. Error bars reflect the results of two replicate experiments.

FIG 2.

FIG 2

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Activity of all antimicrobials against m-12022. The data are shown as follows: filled circle, growth control; open circle, azithromycin (0.28 mg/liter); filled square, ceftriaxone (0.95 mg/liter); open square, ciprofloxacin (2.08 mg/liter); filled triangle, levofloxacin (3.93 mg/liter); open triangle, moxifloxacin (2.7 mg/liter). The dotted line indicates the lower limit of detection for bacterial quantification, 2 log10 CFU/ml. Error bars reflect the results of two replicate experiments.

DISCUSSION

S. flexneri continues to serve as a major contributor to diarrhea-associated morbidity and mortality and enhances the burden of diarrheal illnesses worldwide. Resistance to first-line antimicrobials continues to rise and threatens the efficacy of current treatment options for shigellosis. We performed a pilot study using a limited number of bacterial isolates in order to investigate the extent to which current treatment options for shigellosis may induce further resistance development with continued use. To our knowledge, this is the first study to have examined the risk of resistance promotion in S. flexneri using the MPC and MSW.

Although rehydration and nutritional support are important aspects of the treatment of shigellosis, treatment with antibiotics is known to quicken recovery and decrease disease-related complications and mortality (26). Ampicillin and SXT were at one time considered drugs of choice for the treatment of Shigella infections. However, since the 1980s, widespread resistance to both agents has emerged, and neither antimicrobial is currently recommended for empirical therapy (1). After resistance to ampicillin and SXT became widespread, nalidixic acid became a frequent choice for the treatment of shigellosis. However, in 2004 the WHO removed nalidixic acid as a treatment option for shigellosis due to the emergence of significant levels of resistance in Asia and Africa and increasing resistance in Europe and America (1). It is unclear whether the emergence of nalidixic acid resistance may have predisposed strains to later resistance to other fluoroquinolones, such as ciprofloxacin. It has been shown that nalidixic acid resistance in Enterobacteriaceae is linked primarily to a single amino acid substitution at position 83 or 87 of the gyrA gene, while resistance to ciprofloxacin requires at least one additional amino acid substitution in gyrA (27). According to the current WHO guidelines, ciprofloxacin is the preferred agent for shigellosis, despite the fact that some cross-resistance between nalidixic acid and ciprofloxacin has been noted (4). Moreover, the increased use of ciprofloxacin in the treatment of Shigella infections has caused increased resistance development, especially in areas of the world with a high incidence of infection. For instance, rates of ciprofloxacin resistance in India rose from 0% to 48% in a period of 5 years (28). Increasing ciprofloxacin resistance has also been noted in the United States, with resistance observed in 2.4% of isolates in 2014 (7). Isolates with resistance to both fluoroquinolones and cephalosporins have also been noted (29).

In the WHO guidelines for the treatment of shigellosis, azithromycin is considered a second-line option, and guidelines published by the American Academy of Pediatrics designate azithromycin a treatment option for children infected with multidrug-resistant Shigella (4, 30). However, resistance to azithromycin has increased globally. For example, in tests of isolates obtained in India between 2006 and 2011, 48% were resistant to azithromycin (27). In the United States, reduced susceptibility to azithromycin was first reported in 2013 and has been extensively reported in men who have sex with men (MSM) (31, 32).

Ceftriaxone is another second-line option in the treatment for shigellosis and is also recommended as a treatment option by the American Academy of Pediatrics (4, 30). Resistance to ceftriaxone has been noted during outbreaks of Shigella infection in India and Vietnam, and cephalosporin-resistant isolates have been shown to produce extended-spectrum beta lactamases (28, 33, 34).

Much of the work examining the relationship between antimicrobial exposure, the MPC/MSW, and the selection of antimicrobial resistance has been performed using fluoroquinolones. It has been shown that fluoroquinolone concentrations within the MSW select mutant growth, although the placement of concentrations within the MSW also may determine mutant selection. For example, in Staphylococcus aureus, average ciprofloxacin concentrations slightly above the MIC, intermediate between the MIC and MPC, and close to the MPC selected mutants that differed in their mechanisms of resistance and susceptibility changes (35). The relationship between TMSW and the emergence of resistance also appears to be related to the magnitude of T>MPC (36).

Several studies have demonstrated a relationship between AUC/MPC values and the emergence of resistant mutants. It was shown in one study that achieving an AUC/MPC ratio of ≥22 prevented the emergence of resistance to ciprofloxacin in a fully susceptible strain of Escherichia coli, whereas an AUC/MPC ratio of 11 prevented further resistance in a gyrA mutant (37). In a second study, AUC/MPC ratios of 35 and 14 were shown to prevent ciprofloxacin resistance development in a susceptible strain of E. coli and a gyrA mutant, respectively (38). In studies of Gram-positive bacteria, AUC/MPC ratios that prevent fluoroquinolone resistance have ranged from 18 to 69 (39). Considering the susceptible strain, ATCC 12022, concentrations of all fluoroquinolones fall above the MPC for a majority of the dosage interval, and all fluoroquinolones achieve AUC/MPC values that would predict a low likelihood of resistance development. However, with respect to the gyrA mutant, concentrations of all fluoroquinolones fall below the MPC and within the MSW for a significant percentage of the dosage interval, and only levofloxacin and moxifloxacin achieve AUC/MPC values that would be predicted to prevent resistance development. Considering the pharmacokinetics (PK) associated with a levofloxacin dose of 750 mg administered orally every 24 h, an AUC/MPC ratio of 125 or 31 would be achieved for ATCC 12022 or m-12022, respectively, suggesting an even lower risk of resistance selection in either strain. Thus, evaluation of this regimen for shigellosis may be warranted.

The relationships among beta-lactam exposure, the MPC/MSW, and the selection of resistance have not been extensively studied. It has been shown that the relevant pharmacokinetic/pharmacodynamic (PK/PD) parameter that predicts the activity of beta-lactams is the T>MIC (40). In a piglet tissue-cage model of the cephalosporin cefquinome, doses that achieved a T>MIC99 that was ≤25% of the dosage interval or a T>MPC that was ≥50% of the dosage interval were not associated with mutant enrichment in E. coli (22). On the basis of our data, we predict increased resistance selection with the continued use of ceftriaxone to treat S. flexneri, as ceftriaxone concentrations fall within the MSW for a majority of the dosage interval for both ATCC and m-12022 and concentrations fail to exceed the MPC for ≥50% of the dosage interval; ceftriaxone concentrations fail to exceed the MPC completely for m-12022.

The impact of the relationship between macrolide concentrations and the MPC and/or MSW has not been studied. It has been shown that the relevant PK/PD parameter that correlates with macrolide antibacterial activity is the AUC/MIC ratio (41). However, the relationship between macrolide concentrations, the MPC or MSW, and the emergence of resistance has not been studied. Since the AUC/MPC ratio has been shown to correlate with mutant enrichment for fluoroquinolones, it is possible that the same would be true for macrolides; however, this has not been studied, and a threshold AUC/MPC value that would prevent selective enrichment of mutants has not been determined. Our results indicate that azithromycin concentrations fall below the MIC and MPC for the entire dosage interval for both ATCC 12022 and m-12022, a result of the low extracellular concentrations achieved by this agent. In E. coli and Salmonella enterica, sub-MIC concentrations of ciprofloxacin, streptomycin, and tetracycline have been shown to enrich mutant growth and select de novo mutants (42). Blondeau et al. hypothesized that the high prevalence of azithromycin resistance in Streptococcus pneumoniae may be explained by the low AUC/MPC values attained by this agent; clarithromycin and erythromycin were shown to achieve higher AUC/MPC values (43). On the basis of the low AUC/MPC values attained by azithromycin against the S. flexneri strains evaluated in this study, we predict that resistance to azithromycin will continue to emerge if this agent is used to treat infections caused by this organism, and alternative macrolides, such as clarithromycin, should be studied. Of note, azithromycin was the only agent that failed to achieve bactericidal activity in time-kill assays.

Limitations of this study include the analysis of only two strains of S. flexneri and a lack of inclusion of other species of Shigella, such as Shigella sonnei. The examination of additional strains of Shigella that are biologically variant is necessary to confirm our findings. Nonetheless, we consider our pilot study to have been an important preliminary study in this area. A second limitation is the fact that our time-kill assays did not measure the emergence of resistant mutants but merely assessed killing by each antimicrobial.

A third limitation relates to our ability to draw conclusions regarding the relationship between the concentrations of the tested antimicrobials and the selection of resistant mutants. While it has been shown that the emergence of resistant mutants after fluoroquinolone exposure is related to %TMSW, %T>MPC, and the AUC/MPC ratio, the relationship between fluoroquinolone PK/PD parameters and mutant selection has not been studied specifically in Shigella species. Thus, we used findings from in vitro studies of other bacteria, including E. coli; confirmation of the relationship between fluoroquinolone concentrations and the emergence of resistance in S. flexneri is required to validate our conclusions. A single study has evaluated the relationship between cephalosporin concentrations, the MPC/MSW, and mutant selection, and the results showed that T>MIC or T>MPC was correlated with mutant selection in E. coli (22). We used these parameters (as well as TMSW) in our analyses of the risk of mutant selection by ceftriaxone. No published studies have evaluated the relationship between macrolide concentrations, the MPC/MSW, and the restriction of mutant growth. Thus, we used the established relevant PK/PD index (the AUC/MIC ratio) in drawing conclusions regarding the risk of mutant selection in S. flexneri by azithromycin. Nonetheless, the results of our study suggest that continued use of certain current first-line antimicrobials against S. flexneri may promote resistance selection and thus limit their long-term usefulness in the treatment of shigellosis. Examination of alternative antimicrobials and more-stringent dosing strategies that are targeted to mutant restriction in Shigella are warranted.

MATERIALS AND METHODS

Bacterial strains.

ATCC 12022 was obtained from Microbiologics, Inc., Saint Cloud, MN. A gyrA mutant (Ser 83 Leu) strain, m-12022, with reduced fluoroquinolone susceptibility was isolated by culturing approximately 1010 CFU/ml of ATCC 12022 on agar medium containing 0.25 mg/liter of levofloxacin. Analysis of the quinolone resistance-determining region of gyrA in m-12022 was performed using PCR parameters described by Pu et al. (44).

Antimicrobial agents.

Analysis-grade powders of azithromycin, ceftriaxone, ciprofloxacin, levofloxacin, and moxifloxacin were obtained from Sigma Chemical Co., St. Louis, MO. Stock solutions of each antimicrobial were prepared on the day of use.

Medium.

Mueller-Hinton broth (MHB; Difco Laboratories, Detroit, MI) supplemented with 12.5% magnesium and 25% calcium (SMHB) was used for the preparation of bacterial inocula during MPC testing and in time-kill assays. Mueller-Hinton agar (MHA; Difco) was used in MIC and MPC determinations and in quantification of bacterial counts.

Susceptibility testing.

MICs were determined using the Etest methodology (bioMérieux, AB Biodisk, Solna, Sweden) with an inoculum of 5 × 105 CFU/ml. MICs were determined after incubation for 18 to 24 h at 35°C in 0.5% CO2 according to Clinical and Laboratory Standards Institute (CLSI) guidelines (24).

MPC determinations.

MPC determinations were adapted from the methodology described by Blondeau et al. (45). A total of 10 MHA plates were inoculated with either ATCC 12022 or m-12022 using a sterile swab in order to form a confluent lawn of growth on each plate after incubation for 24 h at 35°C in 0.5% CO2. All resulting bacterial growth after incubation was collected and transferred to 500 ml of SMHB and incubated for an additional 24 h. The resulting suspension was centrifuged (5,000 × g for 15 min), the supernatant was discarded, and bacterial cells were resuspended in SMHB to yield a final inoculum with a concentration of 1010 CFU/ml. Finally, 100 μl of this suspension was applied to each of 10 MHA plates containing antimicrobial concentrations increasing 2-fold above each antimicrobial's MIC. Inoculated plates were incubated for 72 h and screened for growth at 48 h and 72 h. The lowest antimicrobial concentration seen to inhibit all visible growth was deemed the MPC. MIC testing of recovered colonies was performed to ensure the presence of resistance.

Pharmacodynamic analysis.

Steady-state extracellular pharmacokinetic parameters (Cmax, half-life [t1/2], and AUC over 24 h at the steady state) achieved after dosing in adult patients were used in pharmacodynamic analyses (46–48). The free (unbound; ƒ) Cmax and AUC values were calculated using protein binding values of 51%, 95%, 30%, 31%, and 40% for azithromycin, ceftriaxone, ciprofloxacin, levofloxacin, and moxifloxacin, respectively. These pharmacokinetic parameters were used to calculate the %TMSW (the percentage of each dosage interval during which concentrations fall within the MSW), %T>MPC (the percentage of the dosage interval during which concentrations exceed the MPC), and AUC/MPC ratio for each antimicrobial. Pharmacokinetic parameters attained by azithromycin at 500 mg orally every 24 h (ƒCmax, 0.28 mg/liter; t1/2, 68 h; AUC, 1.27 mg · h/liter), ceftriaxone at 250 mg intramuscularly ×1 (ƒCmax, 0.95 mg/liter; t1/2, 8 h), ciprofloxacin at 500 mg orally every 12 h (ƒCmax, 2.08 mg/liter; t1/2, 4 h; AUC, 19.18 mg · h/liter), levofloxacin at 500 mg orally every 24 h (ƒCmax, 3.93 mg/liter; t1/2, 7 h; AUC, 32.78 mg · h/liter), and moxifloxacin at 400 mg orally every 24 h (ƒCmax, 2.7 mg/liter; t1/2, 12 h; AUC, 28.8 mg · h/liter) were used in all pharmacodynamic analyses.

Time-kill assays.

A time-kill methodology was used to test the activity of concentrations of each antimicrobial equal to the extracellular ƒCmax against approximately 106–7 CFU/ml. All time-kill studies were performed using a final volume of 2 ml of SMHB. Samples were obtained at 0, 4, 8, and 24 h and were serially diluted in cold 0.9% saline solution; samples were diluted to achieve an antimicrobial concentration below the MIC for that agent to prevent the effects of antimicrobial carryover. Quantification of bacterial growth was performed by plating triplicate 20-μl aliquots of diluted samples on MHA and incubating for 24 h. Time-kill curves were created by plotting bacterial counts (log10 CFU counts per ml) versus time; the lower limit of quantification was 2 log10 CFU/ml. Bactericidal activity was defined as a 3 log10 reduction in CFU/ml. Time-kill assays were performed in duplicate.

ACKNOWLEDGMENTS

We thank Daniel Brazeau for his assistance in characterizing isolate m-12022.

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

REFERENCES

  • 1.Klontz KC, Singh N. 2015. Treatment of drug-resistant Shigella infections. Expert Rev Anti Infect Ther 13:69–80. doi: 10.1586/14787210.2015.983902. [DOI] [PubMed] [Google Scholar]
  • 2.Crim SM, Griffin PM, Tauxe R, Marder EP, Gilliss D, Cronquist AB, Cartter M, Tobin-D'Angelo M, Blythe D, Smith K, Lathrop S, Zansky S, Cieslak PR, Dunn J, Holt KG, Wolpert B, Henao OL. 2015. Preliminary incidence and trends of infection with pathogens transmitted commonly through food—Foodborne Diseases Active Surveillance Network, 10 U.S. sites, 2006–2014. MMWR Morb Mortal Wkly Rep 64:495–499. [PMC free article] [PubMed] [Google Scholar]
  • 3.Guerrant RL, Van Gilder T, Steiner TS, Thielman NM, Slutsker L, Tauxe RV, Hennessy T, Griffin PM, DuPont H, Sack RB, Tarr P, Neill M, Nachamkin I, Reller LB, Osterholm MT, Bennish ML, Pickering LK. 2001. Practice guidelines for the management of infectious diarrhea. Clin Infect Dis 32:331–351. doi: 10.1086/318514. [DOI] [PubMed] [Google Scholar]
  • 4.WHO. 2005. Guidelines for the control of shigellosis, Including epidemics due to Shigella dysenteriae type 1, 2005. World Health Organization, Geneva, Switzerland. [Google Scholar]
  • 5.Bhattacharya D, Purushottaman SA, Bhattacharjee H, Thamizhmani R, Sudharama SD, Manimunda SP, Bharadwaj AP, Singhania M, Roy S. 2011. Rapid emergence of third-generation cephalosporin resistance in Shigella sp. isolated in Andaman and Nicobar Islands, India. Microb Drug Resist 17:329–332. doi: 10.1089/mdr.2010.0084. [DOI] [PubMed] [Google Scholar]
  • 6.Zhang CL, Liu QZ, Wang J, Chu X, Shen LM, Guo YY. 2014. Epidemic and virulence characteristic of Shigella spp. with extended-spectrum cephalosporin resistance in Xiaoshan District, Hangzhou, China. BMC Infect Dis 14:260. doi: 10.1186/1471-2334-14-260. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.CDC. 2016. National antimicrobial resistance monitoring system for enteric bacteria (NARMS): human isolates surveillance report for 2014 (final report), 2016. Centers for Disease Control and Prevention, Atlanta, GA. [Google Scholar]
  • 8.Klontz EH, Das SK, Ahmed D, Ahmed S, Chisti MJ, Malek MA, Faruque AS, Klontz KC. 2014. Long-term comparison of antibiotic resistance in Vibrio cholerae O1 and Shigella species between urban and rural Bangladesh. Clin Infect Dis 58:e133–e136. doi: 10.1093/cid/ciu040. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Dong Y, Zhao X, Domagala J, Drlica K. 1999. Effect of fluoroquinolone concentration on selection of resistant mutants of Mycobacterium bovis BCG and Staphylococcus aureus. Antimicrob Agents Chemother 43:1756–1758. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Zhao X, Drlica K. 2001. Restricting the selection of antibiotic-resistant mutants: a general strategy derived from fluoroquinolone studies. Clin Infect Dis 33(Suppl 3):S147–S156. doi: 10.1086/321841. [DOI] [PubMed] [Google Scholar]
  • 11.Blondeau JM. 2009. New concepts in antimicrobial susceptibility testing: the mutant prevention concentration and mutant selection window approach. Vet Dermatol 20:383–396. doi: 10.1111/j.1365-3164.2009.00856.x. [DOI] [PubMed] [Google Scholar]
  • 12.Almeida D, Nuermberger E, Tyagi S, Bishai WR, Grosset J. 2007. In vivo validation of the mutant selection window hypothesis with moxifloxacin in a murine model of tuberculosis. Antimicrob Agents Chemother 51:4261–4266. doi: 10.1128/AAC.01123-07. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Croisier D, Etienne M, Bergoin E, Charles PE, Lequeu C, Piroth L, Portier H, Chavanet P. 2004. Mutant selection window in levofloxacin and moxifloxacin treatments of experimental pneumococcal pneumonia in a rabbit model of human therapy. Antimicrob Agents Chemother 48:1699–1707. doi: 10.1128/AAC.48.5.1699-1707.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Croisier D, Etienne M, Piroth L, Bergoin E, Lequeu C, Portier H, Chavanet P. 2004. In vivo pharmacodynamic efficacy of gatifloxacin against Streptococcus pneumoniae in an experimental model of pneumonia: impact of the low levels of fluoroquinolone resistance on the enrichment of resistant mutants. J Antimicrob Chemother 5:640–647. doi: 10.1093/jac/dkh393. [DOI] [PubMed] [Google Scholar]
  • 15.Cui J, Liu Y, Wang R, Tong W, Drlica K, Zhao X. 2006. The mutant selection window in rabbits infected with Staphylococcus aureus. J Infect Dis 194:1601–1608. doi: 10.1086/508752. [DOI] [PubMed] [Google Scholar]
  • 16.Etienne M, Croisier D, Charles PE, Lequeu C, Piroth L, Portier H, Drlica K, Chavanet P. 2004. Effect of low-level resistance on subsequent enrichment of fluoroquinolone-resistant Streptococcus pneumoniae in rabbits. J Infect Dis 190:1472–1475. doi: 10.1086/423853. [DOI] [PubMed] [Google Scholar]
  • 17.Ferran AA, Kesteman AS, Toutain PL, Bousquet-Mélou A. 2009. Pharmacokinetic/pharmacodynamic analysis of the influence of inoculum size on the selection of resistance in Escherichia coli by a quinolone in a mouse thigh bacterial infection model. Antimicrob Agents Chemother 53:3384–3390. doi: 10.1128/AAC.01347-08. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Firsov AA, Vostrov SN, Lubenko IY, Drlica K, Portnoy YA, Zinner SH. 2003. In vitro pharmacodynamic evaluation of the mutant selection window hypothesis using four fluoroquinolones against Staphylococcus aureus. Antimicrob Agents Chemother 47:1604–1613. doi: 10.1128/AAC.47.5.1604-1613.2003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Mei Q, Ye Y, Zhu YL, Cheng J, Chang X, Liu YY, Li HR, Li JB. 2015. Testing the mutant selection window hypothesis in vitro and in vivo with Staphylococcus aureus exposed to fosfomycin. Eur J Clin Microbiol Infect Dis 34:737–744. doi: 10.1007/s10096-014-2285-6. [DOI] [PubMed] [Google Scholar]
  • 20.Ni W, Song X, Cui J. 2014. Testing the mutant selection window hypothesis with Escherichia coli exposed to levofloxacin in a rabbit tissue cage infection model. Eur J Clin Microbiol Infect Dis 33:385–389. doi: 10.1007/s10096-013-1968-8. [DOI] [PubMed] [Google Scholar]
  • 21.Xiong M, Wu X, Ye X, Zhang L, Zeng S, Huang Z, Wu Y, Sun J, Ding H. 2016. Relationship between cefquinome PK/PD parameters and emergence of resistance of Staphylococcus aureus in rabbit tissue-cage infection model. Front Microbiol 7:874. doi: 10.3389/fmicb.2016.00874. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Zhang B, Gu X, Li Y, Li X, Gu M, Zhang N, Shen X, Ding H. 2014. In vivo evaluation of mutant selection window of cefquinome against Escherichia coli in piglet tissue-cage model. BMC Vet Res 10:297. doi: 10.1186/s12917-014-0297-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Zhu YL, Hu LF, Mei Q, Cheng J, Liu YY, Ye Y, Li JB. 2012. Testing the mutant selection window in rabbits infected with methicillin-resistant Staphylococcus aureus exposed to vancomycin. J Antimicrob Chemother 67:2700–2706. doi: 10.1093/jac/dks280. [DOI] [PubMed] [Google Scholar]
  • 24.Clinical and Laboratory Standards Institute. 2016. M100-S26. Performance standards for antimicrobial susceptibility testing: 26th informational supplement. Clinical and Laboratory Standards Institute, Wayne, PA. [Google Scholar]
  • 25.EUCAST. 2017. Breakpoint tables for interpretation of MICs and zone diameters. Version 7.0, January 2017. http://www.eucast.org/clinical_breakpoints/ Accessed January 2017.
  • 26.Das JK, Salam RA, Bhutta ZA. 2014. Global burden of childhood diarrhea and interventions. Curr Opin Infect Dis 27:451–458. doi: 10.1097/QCO.0000000000000096. [DOI] [PubMed] [Google Scholar]
  • 27.Bhattacharya D, Bhattacharya H, Thamizhmani R, Sayi DS, Reesu R, Anwesh M, Kartick C, Bharadwaj AP, Singhania M, Sugunan AP, Roy S. 2014. Shigellosis in Bay of Bengal Islands, India: clinical and seasonal patterns, surveillance of antibiotic susceptibility patterns, and molecular characterization of multidrug-resistant Shigella strains isolated during a 6-year period from 2006 to 2011. Eur J Clin Microbiol Infect Dis 33:157–170. doi: 10.1007/s10096-013-1937-2. [DOI] [PubMed] [Google Scholar]
  • 28.Srinivasa H, Baijayanti M, Raksha Y. 2009. Magnitude of drug resistant shigellosis: a report from Bangalore. Indian J Med Microbiol 27:358–360. doi: 10.4103/0255-0857.55460. [DOI] [PubMed] [Google Scholar]
  • 29.Jue S, Hardee R, Overman M, Mays E, Bowen A, Whichard J, Greene K, Pecic G, Taylor E. 2010. Emergence of Shigella flexneri 2a resistant to ceftriaxone and ciprofloxacin—South Carolina, October 2010. MMWR Morb Mortal Wkly Rep 59:1619. [PubMed] [Google Scholar]
  • 30.Committee on Infectious Diseases, American Academy of Pediatrics. 2015. Shigella infections, p 706–709. In Kimberlin DW, Brady MT, Jackson MA, Long SS (ed), Red book: 2015 report of the Committee on Infectious Diseases. American Academy of Pediatrics, Elk Grove Village, IL. [Google Scholar]
  • 31.Baker KS, Dallman TJ, Ashton PM, Day M, Hughes G, Crook PD, Gilbart VL, Zittermann S, Allen VG, Howden BP, Tomita T, Valcanis M, Harris SR, Connor TR, Sintchenko V, Howard P, Brown JD, Petty NK, Gouali M, Thanh DP, Keddy KH, Smith AM, Talukder KA, Faruque SM, Parkhill J, Baker S, Weill FX, Jenkins C, Thomson NR. 2015. Intercontinental dissemination of azithromycin-resistant shigellosis through sexual transmission: a cross-sectional study. Lancet Infect Dis 15:913–921. doi: 10.1016/S1473-3099(15)00002-X. [DOI] [PubMed] [Google Scholar]
  • 32.Sjölund Karlsson M, Bowen A, Reporter R, Folster JP, Grass JE, Howie RL, Taylor J, Whichard JM. 2013. Outbreak of infections caused by Shigella sonnei with reduced susceptibility to azithromycin in the United States. Antimicrob Agents Chemother 57:1559–1560. doi: 10.1128/AAC.02360-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Mandal J, Mondal N, Mahadevan S, Parija SC. 2010. Emergence of resistance to third-generation cephalosporin in Shigella–a case report. J Trop Pediatr 56:278–279. doi: 10.1093/tropej/fmp118. [DOI] [PubMed] [Google Scholar]
  • 34.Vinh H, Baker S, Campbell J, Hoang NV, Loan HT, Chinh MT, Anh VT, Diep TS, Phuong le T, Schultsz C, Farrar J. 2009. Rapid emergence of third generation cephalosporin resistant Shigella spp. in southern Vietnam. J Med Microbiol 58:281–283. doi: 10.1099/jmm.0.002949-0. [DOI] [PubMed] [Google Scholar]
  • 35.Campion JJ, McNamara PJ, Evans ME. 2004. Evolution of ciprofloxacin-resistant Staphylococcus aureus in in vitro pharmacokinetic environments. Antimicrob Agents Chemother 48:4733–4744. doi: 10.1128/AAC.48.12.4733-4744.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Firsov AA, Portnoy YA, Strukova EN, Shlykova DS, Zinner SH. 2014. Predicting bacterial resistance using the time within the mutant selection window: possibilities and limitations. Int J Antimicrob Agents 44:301–305. doi: 10.1016/j.ijantimicag.2014.06.013. [DOI] [PubMed] [Google Scholar]
  • 37.Olofsson SK, Marcusson LL, Lindgren PK, Hughes D, Cars O. 2006. Selection of ciprofloxacin resistance in Escherichia coli in an in vitro kinetic model: relation between drug exposure and mutant prevention concentration. J Antimicrob Chemother 57:1116–1121. doi: 10.1093/jac/dkl135. [DOI] [PubMed] [Google Scholar]
  • 38.Olofsson SK, Marcusson LL, Stromback A, Hughes D, Cars O. 2007. Dose-related selection of fluoroquinolone-resistant Escherichia coli. J Antimicrob Chemother 60:795–801. doi: 10.1093/jac/dkm265. [DOI] [PubMed] [Google Scholar]
  • 39.Drlica K, Zhao X. 2007. Mutant selection window hypothesis updated. Clin Infect Dis 44:681–688. doi: 10.1086/511642. [DOI] [PubMed] [Google Scholar]
  • 40.Sinnollareddy MG, Roberts MS, Lipman J, Roberts JA. 2012. Beta-lactam pharmacokinetics and pharmacodynamics in critically ill patients and strategies for dose optimization: a structured review. Clin Exp Pharmacol Physiol 39:489–496. doi: 10.1111/j.1440-1681.2012.05715.x. [DOI] [PubMed] [Google Scholar]
  • 41.Craig WA. 1998. Pharmacokinetic/pharmacodynamic rationale for antibacterial dosing of mice and men. Clin Infect Dis 26:1–12. doi: 10.1086/516284. [DOI] [PubMed] [Google Scholar]
  • 42.Gullberg E, Cao S, Berg OG, Ilbäck C, Sandegren L, Hughes D, Andersson DI. 2011. Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathog 7:e1002158. doi: 10.1371/journal.ppat.1002158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Metzler K, Drlica K, Blondeau JM. 2013. Minimal inhibitory and mutant prevention concentrations of azithromycin, clarithromycin and erythromycin for clinical isolates of Streptococcus pneumoniae. J Antimicrob Chemother 68:631–635. doi: 10.1093/jac/dks461. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Pu XY, Zhang Q, Pan J-C, Shen Z, Zhang W. 2013. Spontaneous mutation frequency and molecular mechanisms of Shigella flexneri fluoroquinolone resistance under antibiotic selective stress. World J Microbiol Biotechnol 29:365–371. doi: 10.1007/s11274-012-1190-3. [DOI] [PubMed] [Google Scholar]
  • 45.Blondeau JM, Zhao X, Hansen G, Drlica K. 2001. Mutant prevention concentrations of fluoroquinolones for clinical isolates of Streptococcus pneumoniae. Antimicrob Agents Chemother 45:433–438. doi: 10.1128/AAC.45.2.433-438.2001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Aminimanizani A, Beringer P, Jelliffe R. 2001. Comparative pharmacokinetics and pharmacodynamics of the newer fluoroquinolone antibacterials. Clin Pharmacokinet 40:169–187. doi: 10.2165/00003088-200140030-00003. [DOI] [PubMed] [Google Scholar]
  • 47.Lamb HM, Ormrod D, Scott LJ, Figgitt DP. 2002. Ceftriaxone: an update of its use in the management of community-acquired and nosocomial infections. Drugs 62:1041–1089. doi: 10.2165/00003495-200262070-00005. [DOI] [PubMed] [Google Scholar]
  • 48.Zuckerman JM, Qamar F, Bono BR. 2009. Macrolides, ketolides, and glycylcyclines: azithromycin, clarithromycin, telithromycin, tigecycline. Infect Dis Clin North Am 23:997–1026. doi: 10.1016/j.idc.2009.06.013. [DOI] [PubMed] [Google Scholar]

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