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Associations of antimicrobial use with antimicrobial resistance in Campylobacter coli from grow-finish pigs in Japan
Preventive Veterinary Medicine 106 (2012) 295–300
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Preventive Veterinary Medicine journal homepage: www.elsevier.com/locate/prevetmed
Associations of antimicrobial use with antimicrobial resistance in Campylobacter coli from grow-finish pigs in Japan M. Ozawa a,∗ , K. Makita b , Y. Tamura b , T. Asai a a b
National Veterinary Assay Laboratory, Ministry of Agriculture, Forestry and Fisheries, Tokyo, Japan Department of Veterinary Hygiene and Environmental Sciences, School of Veterinary Medicine, Rakuno Gakuen University, Hokkaido, Japan
a r t i c l e
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Article history: Received 7 September 2011 Received in revised form 17 March 2012 Accepted 23 March 2012 Keywords: Antibiotic resistance Campylobacteriosis
a b s t r a c t To determine associations between antimicrobial use and antimicrobial resistance in Campylobacter coli, 155 isolates were obtained from the feces of apparently healthy growfinish pigs in Japan. In addition, data on the use of antibiotics collected through the national antimicrobial resistance monitoring system in Japan were used for the analysis. Logistic regression was used to identify risk factors to antimicrobial resistance in C. coli in pigs for the following antimicrobials: ampicillin, dihydrostreptomycin, erythromycin, oxytetracycline, chloramphenicol, and enrofloxacin. The data suggested the involvement of several different mechanisms of resistance selection. The statistical relationships were suggestive of co-selection; use of macrolides was associated with enrofloxacin resistance (OR = 2.94; CI95% : 0.997, 8.68) and use of tetracyclines was associated with chloramphenicol resistance (OR = 2.37; CI95% : 1.08, 5.19). The statistical relationships were suggestive of cross-resistance: use of macrolides was associated with erythromycin resistance (OR = 9.36; CI95% : 2.96, 29.62) and the use of phenicols was associated with chloramphenicol resistance (OR = 11.83; CI95% : 1.41, 99.44). These data showed that the use of antimicrobials in pigs selects for resistance in C. coli within and between classes of antimicrobials. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Campylobacteriosis is the most commonly reported bacterial food-borne disease in Japan (National Institute of Infectious Diseases and Tuberculosis and Infectious Diseases Control Division, 2010). Campylobacter jejuni causes >90% of human infections and Campylobacter coli is responsible for the remainder exclusively. However, recent studies emphasized the importance of C. coli as an important human pathogen due to resistance to an increasing number of antimicrobials (Saenz et al., 2000; Tam et al., 2003).
∗ Corresponding author at: National Veterinary Assay Laboratory, Ministry of Agriculture, Forestry and Fisheries, 1-15-1 Tokura, Kokubunji, Tokyo, 185-8511 Japan. Tel.: +81 42 321 1841; fax: +81 42 321 1769. E-mail address: [email protected] (M. Ozawa). 0167-5877/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.prevetmed.2012.03.013
C. coli is most frequently isolated from pigs. The treatment of pig diseases mainly involves the use of approved antimicrobials, such as -lactams, aminoglycosides, tetracyclines, phenicols, antifolates (for example, sulfonamide and trimethoprim), macrolides, and fluoroquinolones. In Japan, tetracyclines are most frequently used to treat pigs followed by sulfonamides, -lactams and macrolides (Koike et al., 2008). As a consequence of these treatments, a high proportion of C. coli strains from pigs have become resistant to most of these antimicrobials (Saenz et al., 2000; Ishihara et al., 2004; Varela et al., 2007; Qin et al., 2011). Many factors can influence the selection of antimicrobial resistance; especially the selective pressure imposed by antimicrobial use plays a remarkable role in the development of antimicrobial resistance. Several studies have reported a causal link between antimicrobial use and the emergence of resistance in Campylobacter isolated from pigs. Rosengren et al. (2009) showed a dose–response
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relationship between macrolide use and macrolide resistance. Further, Taylor et al. (2009) reported that the use of fluoroquinolone was the most important factor associated with emergence of fluoroquinolone-resistant Campylobacter. Antimicrobial use as a risk factor for resistance should be considered in accordance with the particular situation found in each individual country, as the factors that participate in the associations between the usage of antimicrobials and the emergence of antimicrobial resistance are different. As a response to emerging resistance, the Japanese Veterinary Antimicrobial Resistance Monitoring System (JVARM) was established in 1999 (Tamura, 2003) and has continued to monitor the changes in antimicrobialresistant bacteria from food-producing animals (National Veterinary Assay Laboratory, 2009) and to collect information on the use of veterinary antimicrobials in each farm (Koike et al., 2008). However, the relationship between antimicrobial use and resistance in C. coli has not yet been described for swine farms. The present study presents possible antimicrobial-associated risk factors for the prevalence of antimicrobial resistant C. coli in pig farms in Japan. 2. Materials and methods 2.1. Sample collection and administration of a questionnaire A total of 327 fecal samples were collected from apparently healthy pigs from 42 of 47 Japanese prefectures between 2004 and 2007 under the JVARM scheme (National Veterinary Assay Laboratory, 2009). Surveyed farms (up to 12 farms in each prefecture) were randomly selected without regard of the number of farms in each prefecture and one fecal sample per farm was collected. Data on the recent use of veterinary antimicrobial products within the six months prior to the day of survey were collected from interviews with farmers based on records of veterinary antimicrobials use at each of the farms that participated in the JVARM program. A structured questionnaire administered by veterinarians in the prefectural livestock hygiene service centers was used (Koike et al., 2008). Antimicrobial use was categorized into seven classes: (i) aminoglycosides, (ii) beta-lactams, (iii) macrolides (including lincosamides), (iv) sulfonamides, (v) tetracyclines, (vi) phenicols, and (vii) fluoroquinolones.
chlorampheniol, and enrofloxacin for C. coli isolates were determined by an agar dilution method, in accordance with the Clinical Laboratory Standards Institute guidelines (Clinical and Laboratory Standards Institute, 2008). C. jejuni ATCC 33560 was used for quality control. The breakpoint for erythromycin complied with the CLSI guidelines, whereas the breakpoints for other antimicrobials were microbiologically defined. 2.3. Statistical analysis The association between antimicrobial use and resistance was carried out using either Chi-square test, or Fisher’s exact test when at least one of the expected frequency in four cells was less than five. Potential risk factors of which P-values were <0.2 in these tests were served for multivariable analysis. In the selection of the explanatory variables, the use of antimicrobial that falls into the same antimicrobial class with the outcome (resistance) was retained in the multivariable model, regardless of the Pvalue in the univariate analysis. To avoid collinearity in the analysis, all pairs of variables were checked for correlation. If there was a strong association for any combination of these variables (r > 0.8), one of the two variables of interest was selected. As at most two Campylobacter isolates per fecal sample per farm were investigated for antimicrobial resistance, these two isolates from a same farm are clustered due to intra-class correlation at the pig/farm level. To control this clustering issue (Berge et al., 2005), robust variance estimation was performed for multivariable analysis using Generalized Estimating Equations (GEE) with binomial errors in statistic software R version 2.12.2. Step-wise model simplification was performed, removing the variable with the highest pwald value. After removal of each variable, the updated model was compared with the previous model by the likelihood-ratio test (P-value of likelihood-ratio test to enter <0.05, to remove >0.1). For this final model, two-way interactions between the remaining factors were investigated. The fit of the model was assessed using the Hosmer–Lemeshow goodness-of-fit test. 3. Results 3.1. Prevalence of Campylobacter and antimicrobial susceptibility
2.2. Isolation and susceptibility testing of C. coli Isolation of bacteria was performed by direct inoculation on Campylobacter blood-free selective agar (no. CM0739) with supplement (no. SR155) (Oxoid, Cambridge, UK). Typical Campylobacter colonies were selected from each sample and subcultured on Mueller–Hinton agar (Oxoid) supplemented with 5% defibrinated horse blood. The isolates were identified as C. coli by polymerase chain reaction (Linton et al., 1997). Two Campylobacter isolates per sample where available were served for further investigation on the resistance against antibiotics. The minimum inhibitory concentrations of ampicillin, dihydrostreptomycin, erythromycin, oxytetracycline,
In total, 215 C. coli isolates were isolated from 125 of 327 fecal samples collected. Up to two isolates per sample were selected for antimicrobial susceptibility testing. When the two isolates from the same sample showed the same resistance pattern, one of the two isolates was excluded from the statistical analysis and 155 isolates remained. The frequency of resistance to the antimicrobials studied among 155 C. coli isolates ranged from 5.8 to 88.4% (Table 1). The highest prevalence of resistance was to oxytetracycline, followed by dihydrostreptomycin. Antimicrobial resistance patterns are shown in Table 2. One hundred and twenty nine (83.2%) of the C. coli isolates were resistant to two or more drugs.
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Table 1 Prevalence of resistance in C. coli isolated from grow-finish pigs in Japan (n = 155). Antimicrobial
Resistant isolates (No.)
Prevalence (%)
ABPC DSM EM OTC CP CRFX
9 95 76 137 51 59
5.8 61.3 49.0 88.4 32.9 38.1
95% CI 2.7–10.7 53.1–69.0 40.9–57.2 82.3–93.0 25.6–41.0 30.4–46.2
Break point (g/mL) 32 32 32 16 16 2
ABPC, ampicillin; DSM, dihydrostreptomycin; EM, erythromycin; OTC, oxytetracycline; CP, chloramphenicol; ERFX, enrofloxacin; CI; confidence interval.
3.2. Exposure to each antimicrobial The number of strains exposed to aminoglycosides, beta-lactams, macrolides (including lincosamides), sulfonamides, tetracyclines, phenicols, and fluoroquinolones were 5 (3.2%), 13 (8.4%), 22 (14.2%), 22 (14.2%), 27 (17.4%), 7 (4.5%), and 7 (4.5%), respectively (n = 155). 3.3. Prevalence of co-resistance A high prevalence of co-resistance to oxytetracycline was observed among the considered antimicrobials (enrofloxacin, erythromycin, and chloramphenicol) (Table 3). Co-resistance to both enrofloxacin and erythromycin was observed in 35 (22.6%) of the isolates. 3.4. Risk factors associated with antimicrobial resistance In the univariate analysis, three resistance outcomes (enrofloxacin, erythromycin, and chloramphenicol) met the criteria for entry into the multivariable models. Table 2 Frequency of the antimicrobial resistance phenotypes observed in C. coli isolated from grow-finish pigs in Japan (n = 155). Resistance phenotype
No.
%
DSM OTC EM ABPC, OTC ABPC, EM DSM, OTC DSM, EM EM, OTC OTC, CP DSM, OTC, CP DSM, EM, OTC OTC, ERFX EM, OTC, CP ABPC, OTC, ERFX DSM, OTC, ERFX DSM, EM, OTC, CP EM, OTC, ERFX OTC, CP, ERFX ABPC, DSM, EM, OTC, CP DSM, EM, OTC, ERFX DSM, OTC, CP, ERFX EM, OTC, CP, ERFX ABPC, EM, OTC, CP, ERFX DSM, EM, OTC, CP, ERFX ABPC, DSM, EM, OTC, CP, ERFX Susceptible
13 10 1 3 1 13 1 13 5 10 13 6 2 1 8 8 7 4 1 12 4 4 1 10 2 2
8.4 6.5 0.6 1.9 0.6 8.4 0.6 8.4 3.2 6.5 8.4 3.9 1.3 0.6 5.2 5.2 4.5 2.6 0.6 7.7 2.6 2.6 0.6 6.5 1.3 1.3
ABPC, ampicillin; DSM, dihydrostreptomycin; EM, erythromycin; OTC, oxytetracycline; CP, chloramphenicol; ERFX, enrofloxacin.
Univariate odds ratios for the association between the use of antimicrobials and resistance are shown in Table 4. Use of -lactams, fluoroquinolones, and macrolides were selected as explanatory variables for the multivariable analysis of resistance against enrofloxacin. Similarly, use of -lactams, macrolides, sulfonamides, and tetracyclines were selected for the analysis of resistance against erythromycin, and use of macrolides, phenicols, and tetracyclines for chloramphenicol (variables with asterisk in Table 4). The final GEE models revealed the three drugs for which resistance was associated with use of antimicrobials (Table 5). Two of these types of resistance were associated with exposure to the drugs in the same antimicrobial class; resistance to erythromycin was associated with exposure to macrolides and resistance to chloramphenicol was associated with phenicol use. In contrast, resistance to enrofloxacin was not associated with fluoroquinolone use but the relationship between the use of macrolides and resistance against enrofloxacin was suggestive. No significant two-way interaction was observed for resistance against any drug. The Hosmer–Lemeshow goodness-of-fit tests for the model of chloramphenicol resistance were proven to be not statistically significant (P > 0.05), suggesting that the data fit the models. 4. Discussion The current study aimed to investigate the link between antimicrobial use and resistance of C. coli isolated from pigs. Risk factors were identified for resistance to enrofloxacin, erythromycin, and chloramphenicol. The relationship between the use of macrolides and resistance against enrofloxacin was suggestive. In Campylobacter, the main mechanism of resistance to fluoroquinolones has been reported to be attributed to a mutation at amino acid 86 of GyrA (Zirnstein et al., 2000). On the other hand, the main mechanism of resistance against macrolides has been reported to be attributed to mutations at positions 2074 and 2075 of the 23S rRNA genes in clinical strains of C. coli (Harada et al., 2006). Therefore, there is no common mechanism for resistance to both fluoroquinolones and macrolides but coresistance to both fluoroquinolones and macrolides has been reported. Ishihara et al. (2004) found that 17.2% of C. coli from pigs in Japan were co-resistant to fluoroquinolones and macrolides among isolates collected in different years through the JVARM program in Japan. Furthermore, 80.6% of the pig isolates from a study performed by Saenz et al. (Saenz et al., 2000) were also co-resistant to
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Table 3 Prevelence of co-resistance in C. coli isolated from grow-finish pigs in Japan (n = 155). No. (%) of isolates resistance to
ERFX EM CP
ABPC
DSM
EM
OTC
CP
ERFX
4(2.6) 5(3.2) 4(2.6)
36(23.2) 47(30.3) 35(28.6)
36(23.2) – 28(18.1)
58(37.4) 73(47.1) 51(32.9)
25(16.1) 28(18.1) –
– 36(23.2) 25(16.1)
ABPC, ampicillin; DSM, dihydrostreptomycin; EM, erythromycin; OTC, oxytetracycline; CP, chloramphenicol; ERFX, enrofloxacin. Table 4 The results of univariate analyses of variables for the occurrence of antimicrobial resistance to enrofloxacin, erythromycin and chloramphenicol (n = 155). Resistance outcome
Enrofloxacin
Erythromycin
Chloramphenicol
Antimicrobial use variables
Aminoglycosides Beta-lactams* Fluoroquinolones* Macrolides* Phenicols Sulfonamides Tetracyclines Aminoglycosides Beta-lactams* Fluoroquinolones Macrolides* Phenicols Sulfonamides* Tetracyclines* Aminoglycosides Beta-lactams Fluoroquinolones Macrolides* Phenicols* Sulfonamides Tetracyclines*
No. exposed
No. not exposed
R+
R−
R+
R−
5 8 4 13 2 10 12 4 9 4 19 3 15 17 1 3 0 12 6 9 14
0 5 3 9 5 12 15 1 4 3 3 4 7 10 4 10 7 10 1 13 13
54 51 55 46 57 49 47 72 67 72 57 73 61 59 50 48 51 39 45 42 37
96 91 93 87 91 84 81 78 75 76 76 75 72 69 100 94 97 94 103 91 91
P
Odds ratio (95% CI)
– 0.08 0.428 0.028 0.709 0.441 0.452 0.204 0.155 0.716 0 1 0.052 0.111 1 0.547 – 0.02 0.005 0.388 0.021
– 2.85 (0.89, 9.19) 2.25 (0.49, 10.45) 2.73 (1.09, 6.87) 0.64 (0.12, 3.4) 1.43 (0.57, 3.55) 1.38 (0.6, 3.19) 4.33 (0.47, 39.68) 2.52 (0.74, 8.56) 1.41 (0.3, 6.51) 8.44 (2.38, 29.92) 0.77 (0.17, 3.56) 2.53 (0.97, 6.6) 1.99 (0.85, 4.67) 0.5 (0.05, 4.59) 0.59 (0.15, 2.24) – 2.89 (1.15, 7.25) 13.73 (1.61, 117.4) 1.5 (0.59, 3.78) 2.65 (1.14, 6.17)
R+, number of isolates positive for resistance to each antimicrobial; R−, number of isolates negative for resistance to each antimicrobial; CI, confidence interval. * The variables entered in the multivariable model.
fluoroquinolones and macrolides. In the present study, 23.2% of C. coli strains were co-resistant to enrofloxacin and erythromycin. Juntunen et al. (2010) reported that the frequency of resistance to ciprofloxacin and erythromycin was significantly higher in C. coli isolates from tylosin-treated pigs than those from untreated pigs. Moreover, the C. coli strains co-resistant to ciprofloxacin and erythromycin were isolated from tylosin-treated pigs. These findings support our data that the use of macrolides may be a risk factor for fluoroquinolone resistance. It is assumed that the coselection (antimicrobial use selecting for resistance to an antimicrobial in another class) imposed by macrolide usage might occur for fluoroquinolone resistance.
Campylobacter strains are well-known for the ability to acquire exogenous DNA by natural transformation (Wang and Taylor, 1990b) that may be an important mechanism for the transfer of chromosomally encoded resistance. Point mutations responsible for fluoroquinolone and macrolide resistance have been reported to be transferred to Campylobacter by natural transformation (Wilson et al., 2003; Kim et al., 2006). The Campylobacter strains which acquired co-resistance to fluoroquinolone and macrolide may be selected by the use of both fluoroquinolone and macrolide. Taylor et al. (2009) suggested that the use of fluoroquinolone was the most important factor associated with fluoroquinolone-resistant Campylobacter. The present
Table 5 Final multivariable generalized estimating equation model for the occurrence of antimicrobial resistance to enrofloxacin, erythromycin and chloramphenicol. Resistance outcome
Antimicrobial use variables
Coefficient
SE
Enrofloxacin
Macrolides
1.079
0.552
0.051
2.94 (0.997, 8.68)
Erythromycin
Macrolides
2.236
0.588
<0.001
9.36 (2.96, 29.62)
Chloramphenicol
Phenicols Tetracyclines
2.471 0.862
1.086 0.400
0.023 0.031
11.83 (1.41,99.44) 2.37 (1.08, 5.19)
CI, confidence interval.
P (Wald’s)
Odds ratio (95% CI)
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study found that the use of fluoroquinolone was not associated with resistances to both fluoroquinolone and macrolide. These data may be attributed to the relatively small number of farms that had used fluoroquinolones. Additionally, Asai et al. (2007) reported that fluoroquinolone-resistant C. coli were isolated from the farms with no history of fluoroquinolone usage. It is possible that several factors other than fluoroquinolone use such as biosecurity account for the presence of fluoroquinoloneresistant Campylobacter (Taylor et al., 2009). Tetracycline is one of the most common antimicrobial classes used in Japanese pig production (Asai et al., 2005). In fact, tetracycline resistance was that most prevalent form of resistance in C. coli (88.4%) found in the present study. A higher prevalence of to enrofloxacin–oxytetracycline co-resistance and erythromycin–oxytetracycline was observed than for enrofloxacin–erythromycin, however, tetracycline use was not identified as a risk factor for enrofloxacin and erythromycin resistance. The frequencies of resistance in tetracycline-exposed isolates and non-tetracyclineexposed isolates against enrofloxacin and erythromycin were not significantly different for each antimicrobial (data not shown). Thus, tetracycline use was not associated with co-resistance. Similarly, tetracyline use was not statistically associated with tetracycline resistance. The number of animals already colonized antimicrobial-resisitant isolates (cononization pressure) may be an important factor involved in the spread of resistant isolates (Bonten et al., 1998). It is suggested that under the situation of high prevalence of tetracycline resistance, the frequency of resistance may be maintained by the colonization pressure despite the use of tetracycline. Therefore, the selection pressure imposed by the use of tetracycline may not influence to direct selection. All chloramphenicol-resistant C. coli in this study were also resistant to tetracycline. Chloramphenicol resistance in C. coli is induced by the chloramphenicol acetyltransferase (CAT) (Wang and Taylor, 1990a) and resistance to tetracycline in C. coli is conferred by the tet(O) gene, which encodes a ribosomal protection protein (Manavathu et al., 1988). Therefore, co-resistance to chloramphenicol and oxytetracycline is possibly due to plasmids or mobile genetic elements, such as integrons, transposons and insertional sequences carrying both the cat gene and tet(O) gene. Although the mechanisms of co-resistance to chloramphenicol and oxytetracycline are currently unclear, the selective pressure imposed by the use of tetracyclines may contribute to the selection of chloramphenicol-resistant C. coli. The current study suggested that erythromycin resistance was selected by macrolide use, consistent with a study performed by Rosengren et al. (2009) that also suggested an association between macrolide exposure and resistance to macrolide in Campylobacter isolated from pigs. Resistance to erythromycin in C. coli isolated from pigs in Japan was relatively high (44.9–57.1%) between 1999 and 2003 (National Veterinary Assay Laboratory, 2009). Macrolides are the drugs of choice to treat severe Campylobacter infections in humans and thus, the emergence of macrolide-resistant Campylobacter in food-producing
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animals is a major concern for public health. Moreover, the use of macrolides for the treatment of bacterial infections in pigs has increased in recent years in Japan (Koike et al., 2008). Therefore, continued monitoring of the prevalence of macrolide resistance in C. coli isolated from pigs is needed. Chloramphenicol resistance was associated with the use of phenicols in animals. The use of chloramphenicol in food-producing animals was banned in 1998 in Japan; however, the percentage of chloramphenicol-resistant C. coli in pigs in Japan has been maintained at approximately 20–40% in recent years (data not shown). Therefore, chloramphenicol resistance in C. coli isolated from pigs is likely to have been maintained by the routine use of phenicols, such as thiamphenicol or florfenicol. There are limitations in our study. The causality between antimicrobial use and antimicrobial resistance is yet to be determined because the present study is crosssectional. The time precedence of drug use to the selection of resistance could not be determined unless it is confirmed by a cohort or intervention study. 5. Conclusions Use of antimicrobials on studied farms may select antimicrobial-resistant C. coli isolates by cross-resistance or co-selection. A history of the use of macrolides was identified as a risk factor for the development of macrolide resistance and the relationship between the use of macrolides and fluoroquinolone resistance was suggestive. The emergence of fluoroquinolone and macrolide resistance in Campylobacter isolates from food-producing animals presents a threat to human health. These findings stress the importance of prudent use of antimicrobials in the swine production. Acknowledgments We are grateful to the farmers that participated in this study and the staff of the Livestock Hygiene Service Centers across the country for providing C. coli strains. References Asai, T., Kojima, A., Harada, K., Ishihara, K., Takahashi, T., Tamura, Y., 2005. Correlation between the usage volume of veterinary therapeutic antimicrobials and resistance in Escherichia coli isolated from the feces of food-producing animals in Japan. Jpn. J. Infect. Dis. 58, 369–372. Asai, T., Harada, K., Ishihara, K., Kojima, A., Sameshima, T., Tamura, Y., Takahashi, T., 2007. Association of antimicrobial resistance in Campylobacter isolated from food-producing animals with antimicrobial use on farms. Jpn. J. Infect. Dis. 60, 290–294. Berge, A.C.B., Epperson, W.B., Pritchard, R.H., 2005. Assessing the effect of a single dose florfenicol treatment in feedlot cattle on the antimicrobial resistance patterns in faecal Escherichia coli. Vet. Res. 36, 723–734. Bonten, M.J., Slaughter, S., Ambergen, A.W., Hayden, M.K., van Voorhis, J., Nathan, C., Weinstein, R.A., 1998. The role of “colonization pressure” in the spread of vancomycin-resistant enterococci: an important infection control variable. Arch. Intern. Med. 158, 1127–1132. Clinical and Laboratory Standards Institute, 2008. Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals; Approved Standard-Third Edition. M31-A3, vol. 28, no. 8. Clinical and Laboratory Standards Institute, Wayne, PA, USA.
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Preventive Veterinary Medicine journal homepage: www.elsevier.com/locate/prevetmed
Associations of antimicrobial use with antimicrobial resistance in Campylobacter coli from grow-finish pigs in Japan M. Ozawa a,∗ , K. Makita b , Y. Tamura b , T. Asai a a b
National Veterinary Assay Laboratory, Ministry of Agriculture, Forestry and Fisheries, Tokyo, Japan Department of Veterinary Hygiene and Environmental Sciences, School of Veterinary Medicine, Rakuno Gakuen University, Hokkaido, Japan
a r t i c l e
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Article history: Received 7 September 2011 Received in revised form 17 March 2012 Accepted 23 March 2012 Keywords: Antibiotic resistance Campylobacteriosis
a b s t r a c t To determine associations between antimicrobial use and antimicrobial resistance in Campylobacter coli, 155 isolates were obtained from the feces of apparently healthy growfinish pigs in Japan. In addition, data on the use of antibiotics collected through the national antimicrobial resistance monitoring system in Japan were used for the analysis. Logistic regression was used to identify risk factors to antimicrobial resistance in C. coli in pigs for the following antimicrobials: ampicillin, dihydrostreptomycin, erythromycin, oxytetracycline, chloramphenicol, and enrofloxacin. The data suggested the involvement of several different mechanisms of resistance selection. The statistical relationships were suggestive of co-selection; use of macrolides was associated with enrofloxacin resistance (OR = 2.94; CI95% : 0.997, 8.68) and use of tetracyclines was associated with chloramphenicol resistance (OR = 2.37; CI95% : 1.08, 5.19). The statistical relationships were suggestive of cross-resistance: use of macrolides was associated with erythromycin resistance (OR = 9.36; CI95% : 2.96, 29.62) and the use of phenicols was associated with chloramphenicol resistance (OR = 11.83; CI95% : 1.41, 99.44). These data showed that the use of antimicrobials in pigs selects for resistance in C. coli within and between classes of antimicrobials. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Campylobacteriosis is the most commonly reported bacterial food-borne disease in Japan (National Institute of Infectious Diseases and Tuberculosis and Infectious Diseases Control Division, 2010). Campylobacter jejuni causes >90% of human infections and Campylobacter coli is responsible for the remainder exclusively. However, recent studies emphasized the importance of C. coli as an important human pathogen due to resistance to an increasing number of antimicrobials (Saenz et al., 2000; Tam et al., 2003).
∗ Corresponding author at: National Veterinary Assay Laboratory, Ministry of Agriculture, Forestry and Fisheries, 1-15-1 Tokura, Kokubunji, Tokyo, 185-8511 Japan. Tel.: +81 42 321 1841; fax: +81 42 321 1769. E-mail address: [email protected] (M. Ozawa). 0167-5877/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.prevetmed.2012.03.013
C. coli is most frequently isolated from pigs. The treatment of pig diseases mainly involves the use of approved antimicrobials, such as -lactams, aminoglycosides, tetracyclines, phenicols, antifolates (for example, sulfonamide and trimethoprim), macrolides, and fluoroquinolones. In Japan, tetracyclines are most frequently used to treat pigs followed by sulfonamides, -lactams and macrolides (Koike et al., 2008). As a consequence of these treatments, a high proportion of C. coli strains from pigs have become resistant to most of these antimicrobials (Saenz et al., 2000; Ishihara et al., 2004; Varela et al., 2007; Qin et al., 2011). Many factors can influence the selection of antimicrobial resistance; especially the selective pressure imposed by antimicrobial use plays a remarkable role in the development of antimicrobial resistance. Several studies have reported a causal link between antimicrobial use and the emergence of resistance in Campylobacter isolated from pigs. Rosengren et al. (2009) showed a dose–response
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relationship between macrolide use and macrolide resistance. Further, Taylor et al. (2009) reported that the use of fluoroquinolone was the most important factor associated with emergence of fluoroquinolone-resistant Campylobacter. Antimicrobial use as a risk factor for resistance should be considered in accordance with the particular situation found in each individual country, as the factors that participate in the associations between the usage of antimicrobials and the emergence of antimicrobial resistance are different. As a response to emerging resistance, the Japanese Veterinary Antimicrobial Resistance Monitoring System (JVARM) was established in 1999 (Tamura, 2003) and has continued to monitor the changes in antimicrobialresistant bacteria from food-producing animals (National Veterinary Assay Laboratory, 2009) and to collect information on the use of veterinary antimicrobials in each farm (Koike et al., 2008). However, the relationship between antimicrobial use and resistance in C. coli has not yet been described for swine farms. The present study presents possible antimicrobial-associated risk factors for the prevalence of antimicrobial resistant C. coli in pig farms in Japan. 2. Materials and methods 2.1. Sample collection and administration of a questionnaire A total of 327 fecal samples were collected from apparently healthy pigs from 42 of 47 Japanese prefectures between 2004 and 2007 under the JVARM scheme (National Veterinary Assay Laboratory, 2009). Surveyed farms (up to 12 farms in each prefecture) were randomly selected without regard of the number of farms in each prefecture and one fecal sample per farm was collected. Data on the recent use of veterinary antimicrobial products within the six months prior to the day of survey were collected from interviews with farmers based on records of veterinary antimicrobials use at each of the farms that participated in the JVARM program. A structured questionnaire administered by veterinarians in the prefectural livestock hygiene service centers was used (Koike et al., 2008). Antimicrobial use was categorized into seven classes: (i) aminoglycosides, (ii) beta-lactams, (iii) macrolides (including lincosamides), (iv) sulfonamides, (v) tetracyclines, (vi) phenicols, and (vii) fluoroquinolones.
chlorampheniol, and enrofloxacin for C. coli isolates were determined by an agar dilution method, in accordance with the Clinical Laboratory Standards Institute guidelines (Clinical and Laboratory Standards Institute, 2008). C. jejuni ATCC 33560 was used for quality control. The breakpoint for erythromycin complied with the CLSI guidelines, whereas the breakpoints for other antimicrobials were microbiologically defined. 2.3. Statistical analysis The association between antimicrobial use and resistance was carried out using either Chi-square test, or Fisher’s exact test when at least one of the expected frequency in four cells was less than five. Potential risk factors of which P-values were <0.2 in these tests were served for multivariable analysis. In the selection of the explanatory variables, the use of antimicrobial that falls into the same antimicrobial class with the outcome (resistance) was retained in the multivariable model, regardless of the Pvalue in the univariate analysis. To avoid collinearity in the analysis, all pairs of variables were checked for correlation. If there was a strong association for any combination of these variables (r > 0.8), one of the two variables of interest was selected. As at most two Campylobacter isolates per fecal sample per farm were investigated for antimicrobial resistance, these two isolates from a same farm are clustered due to intra-class correlation at the pig/farm level. To control this clustering issue (Berge et al., 2005), robust variance estimation was performed for multivariable analysis using Generalized Estimating Equations (GEE) with binomial errors in statistic software R version 2.12.2. Step-wise model simplification was performed, removing the variable with the highest pwald value. After removal of each variable, the updated model was compared with the previous model by the likelihood-ratio test (P-value of likelihood-ratio test to enter <0.05, to remove >0.1). For this final model, two-way interactions between the remaining factors were investigated. The fit of the model was assessed using the Hosmer–Lemeshow goodness-of-fit test. 3. Results 3.1. Prevalence of Campylobacter and antimicrobial susceptibility
2.2. Isolation and susceptibility testing of C. coli Isolation of bacteria was performed by direct inoculation on Campylobacter blood-free selective agar (no. CM0739) with supplement (no. SR155) (Oxoid, Cambridge, UK). Typical Campylobacter colonies were selected from each sample and subcultured on Mueller–Hinton agar (Oxoid) supplemented with 5% defibrinated horse blood. The isolates were identified as C. coli by polymerase chain reaction (Linton et al., 1997). Two Campylobacter isolates per sample where available were served for further investigation on the resistance against antibiotics. The minimum inhibitory concentrations of ampicillin, dihydrostreptomycin, erythromycin, oxytetracycline,
In total, 215 C. coli isolates were isolated from 125 of 327 fecal samples collected. Up to two isolates per sample were selected for antimicrobial susceptibility testing. When the two isolates from the same sample showed the same resistance pattern, one of the two isolates was excluded from the statistical analysis and 155 isolates remained. The frequency of resistance to the antimicrobials studied among 155 C. coli isolates ranged from 5.8 to 88.4% (Table 1). The highest prevalence of resistance was to oxytetracycline, followed by dihydrostreptomycin. Antimicrobial resistance patterns are shown in Table 2. One hundred and twenty nine (83.2%) of the C. coli isolates were resistant to two or more drugs.
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Table 1 Prevalence of resistance in C. coli isolated from grow-finish pigs in Japan (n = 155). Antimicrobial
Resistant isolates (No.)
Prevalence (%)
ABPC DSM EM OTC CP CRFX
9 95 76 137 51 59
5.8 61.3 49.0 88.4 32.9 38.1
95% CI 2.7–10.7 53.1–69.0 40.9–57.2 82.3–93.0 25.6–41.0 30.4–46.2
Break point (g/mL) 32 32 32 16 16 2
ABPC, ampicillin; DSM, dihydrostreptomycin; EM, erythromycin; OTC, oxytetracycline; CP, chloramphenicol; ERFX, enrofloxacin; CI; confidence interval.
3.2. Exposure to each antimicrobial The number of strains exposed to aminoglycosides, beta-lactams, macrolides (including lincosamides), sulfonamides, tetracyclines, phenicols, and fluoroquinolones were 5 (3.2%), 13 (8.4%), 22 (14.2%), 22 (14.2%), 27 (17.4%), 7 (4.5%), and 7 (4.5%), respectively (n = 155). 3.3. Prevalence of co-resistance A high prevalence of co-resistance to oxytetracycline was observed among the considered antimicrobials (enrofloxacin, erythromycin, and chloramphenicol) (Table 3). Co-resistance to both enrofloxacin and erythromycin was observed in 35 (22.6%) of the isolates. 3.4. Risk factors associated with antimicrobial resistance In the univariate analysis, three resistance outcomes (enrofloxacin, erythromycin, and chloramphenicol) met the criteria for entry into the multivariable models. Table 2 Frequency of the antimicrobial resistance phenotypes observed in C. coli isolated from grow-finish pigs in Japan (n = 155). Resistance phenotype
No.
%
DSM OTC EM ABPC, OTC ABPC, EM DSM, OTC DSM, EM EM, OTC OTC, CP DSM, OTC, CP DSM, EM, OTC OTC, ERFX EM, OTC, CP ABPC, OTC, ERFX DSM, OTC, ERFX DSM, EM, OTC, CP EM, OTC, ERFX OTC, CP, ERFX ABPC, DSM, EM, OTC, CP DSM, EM, OTC, ERFX DSM, OTC, CP, ERFX EM, OTC, CP, ERFX ABPC, EM, OTC, CP, ERFX DSM, EM, OTC, CP, ERFX ABPC, DSM, EM, OTC, CP, ERFX Susceptible
13 10 1 3 1 13 1 13 5 10 13 6 2 1 8 8 7 4 1 12 4 4 1 10 2 2
8.4 6.5 0.6 1.9 0.6 8.4 0.6 8.4 3.2 6.5 8.4 3.9 1.3 0.6 5.2 5.2 4.5 2.6 0.6 7.7 2.6 2.6 0.6 6.5 1.3 1.3
ABPC, ampicillin; DSM, dihydrostreptomycin; EM, erythromycin; OTC, oxytetracycline; CP, chloramphenicol; ERFX, enrofloxacin.
Univariate odds ratios for the association between the use of antimicrobials and resistance are shown in Table 4. Use of -lactams, fluoroquinolones, and macrolides were selected as explanatory variables for the multivariable analysis of resistance against enrofloxacin. Similarly, use of -lactams, macrolides, sulfonamides, and tetracyclines were selected for the analysis of resistance against erythromycin, and use of macrolides, phenicols, and tetracyclines for chloramphenicol (variables with asterisk in Table 4). The final GEE models revealed the three drugs for which resistance was associated with use of antimicrobials (Table 5). Two of these types of resistance were associated with exposure to the drugs in the same antimicrobial class; resistance to erythromycin was associated with exposure to macrolides and resistance to chloramphenicol was associated with phenicol use. In contrast, resistance to enrofloxacin was not associated with fluoroquinolone use but the relationship between the use of macrolides and resistance against enrofloxacin was suggestive. No significant two-way interaction was observed for resistance against any drug. The Hosmer–Lemeshow goodness-of-fit tests for the model of chloramphenicol resistance were proven to be not statistically significant (P > 0.05), suggesting that the data fit the models. 4. Discussion The current study aimed to investigate the link between antimicrobial use and resistance of C. coli isolated from pigs. Risk factors were identified for resistance to enrofloxacin, erythromycin, and chloramphenicol. The relationship between the use of macrolides and resistance against enrofloxacin was suggestive. In Campylobacter, the main mechanism of resistance to fluoroquinolones has been reported to be attributed to a mutation at amino acid 86 of GyrA (Zirnstein et al., 2000). On the other hand, the main mechanism of resistance against macrolides has been reported to be attributed to mutations at positions 2074 and 2075 of the 23S rRNA genes in clinical strains of C. coli (Harada et al., 2006). Therefore, there is no common mechanism for resistance to both fluoroquinolones and macrolides but coresistance to both fluoroquinolones and macrolides has been reported. Ishihara et al. (2004) found that 17.2% of C. coli from pigs in Japan were co-resistant to fluoroquinolones and macrolides among isolates collected in different years through the JVARM program in Japan. Furthermore, 80.6% of the pig isolates from a study performed by Saenz et al. (Saenz et al., 2000) were also co-resistant to
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Table 3 Prevelence of co-resistance in C. coli isolated from grow-finish pigs in Japan (n = 155). No. (%) of isolates resistance to
ERFX EM CP
ABPC
DSM
EM
OTC
CP
ERFX
4(2.6) 5(3.2) 4(2.6)
36(23.2) 47(30.3) 35(28.6)
36(23.2) – 28(18.1)
58(37.4) 73(47.1) 51(32.9)
25(16.1) 28(18.1) –
– 36(23.2) 25(16.1)
ABPC, ampicillin; DSM, dihydrostreptomycin; EM, erythromycin; OTC, oxytetracycline; CP, chloramphenicol; ERFX, enrofloxacin. Table 4 The results of univariate analyses of variables for the occurrence of antimicrobial resistance to enrofloxacin, erythromycin and chloramphenicol (n = 155). Resistance outcome
Enrofloxacin
Erythromycin
Chloramphenicol
Antimicrobial use variables
Aminoglycosides Beta-lactams* Fluoroquinolones* Macrolides* Phenicols Sulfonamides Tetracyclines Aminoglycosides Beta-lactams* Fluoroquinolones Macrolides* Phenicols Sulfonamides* Tetracyclines* Aminoglycosides Beta-lactams Fluoroquinolones Macrolides* Phenicols* Sulfonamides Tetracyclines*
No. exposed
No. not exposed
R+
R−
R+
R−
5 8 4 13 2 10 12 4 9 4 19 3 15 17 1 3 0 12 6 9 14
0 5 3 9 5 12 15 1 4 3 3 4 7 10 4 10 7 10 1 13 13
54 51 55 46 57 49 47 72 67 72 57 73 61 59 50 48 51 39 45 42 37
96 91 93 87 91 84 81 78 75 76 76 75 72 69 100 94 97 94 103 91 91
P
Odds ratio (95% CI)
– 0.08 0.428 0.028 0.709 0.441 0.452 0.204 0.155 0.716 0 1 0.052 0.111 1 0.547 – 0.02 0.005 0.388 0.021
– 2.85 (0.89, 9.19) 2.25 (0.49, 10.45) 2.73 (1.09, 6.87) 0.64 (0.12, 3.4) 1.43 (0.57, 3.55) 1.38 (0.6, 3.19) 4.33 (0.47, 39.68) 2.52 (0.74, 8.56) 1.41 (0.3, 6.51) 8.44 (2.38, 29.92) 0.77 (0.17, 3.56) 2.53 (0.97, 6.6) 1.99 (0.85, 4.67) 0.5 (0.05, 4.59) 0.59 (0.15, 2.24) – 2.89 (1.15, 7.25) 13.73 (1.61, 117.4) 1.5 (0.59, 3.78) 2.65 (1.14, 6.17)
R+, number of isolates positive for resistance to each antimicrobial; R−, number of isolates negative for resistance to each antimicrobial; CI, confidence interval. * The variables entered in the multivariable model.
fluoroquinolones and macrolides. In the present study, 23.2% of C. coli strains were co-resistant to enrofloxacin and erythromycin. Juntunen et al. (2010) reported that the frequency of resistance to ciprofloxacin and erythromycin was significantly higher in C. coli isolates from tylosin-treated pigs than those from untreated pigs. Moreover, the C. coli strains co-resistant to ciprofloxacin and erythromycin were isolated from tylosin-treated pigs. These findings support our data that the use of macrolides may be a risk factor for fluoroquinolone resistance. It is assumed that the coselection (antimicrobial use selecting for resistance to an antimicrobial in another class) imposed by macrolide usage might occur for fluoroquinolone resistance.
Campylobacter strains are well-known for the ability to acquire exogenous DNA by natural transformation (Wang and Taylor, 1990b) that may be an important mechanism for the transfer of chromosomally encoded resistance. Point mutations responsible for fluoroquinolone and macrolide resistance have been reported to be transferred to Campylobacter by natural transformation (Wilson et al., 2003; Kim et al., 2006). The Campylobacter strains which acquired co-resistance to fluoroquinolone and macrolide may be selected by the use of both fluoroquinolone and macrolide. Taylor et al. (2009) suggested that the use of fluoroquinolone was the most important factor associated with fluoroquinolone-resistant Campylobacter. The present
Table 5 Final multivariable generalized estimating equation model for the occurrence of antimicrobial resistance to enrofloxacin, erythromycin and chloramphenicol. Resistance outcome
Antimicrobial use variables
Coefficient
SE
Enrofloxacin
Macrolides
1.079
0.552
0.051
2.94 (0.997, 8.68)
Erythromycin
Macrolides
2.236
0.588
<0.001
9.36 (2.96, 29.62)
Chloramphenicol
Phenicols Tetracyclines
2.471 0.862
1.086 0.400
0.023 0.031
11.83 (1.41,99.44) 2.37 (1.08, 5.19)
CI, confidence interval.
P (Wald’s)
Odds ratio (95% CI)
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study found that the use of fluoroquinolone was not associated with resistances to both fluoroquinolone and macrolide. These data may be attributed to the relatively small number of farms that had used fluoroquinolones. Additionally, Asai et al. (2007) reported that fluoroquinolone-resistant C. coli were isolated from the farms with no history of fluoroquinolone usage. It is possible that several factors other than fluoroquinolone use such as biosecurity account for the presence of fluoroquinoloneresistant Campylobacter (Taylor et al., 2009). Tetracycline is one of the most common antimicrobial classes used in Japanese pig production (Asai et al., 2005). In fact, tetracycline resistance was that most prevalent form of resistance in C. coli (88.4%) found in the present study. A higher prevalence of to enrofloxacin–oxytetracycline co-resistance and erythromycin–oxytetracycline was observed than for enrofloxacin–erythromycin, however, tetracycline use was not identified as a risk factor for enrofloxacin and erythromycin resistance. The frequencies of resistance in tetracycline-exposed isolates and non-tetracyclineexposed isolates against enrofloxacin and erythromycin were not significantly different for each antimicrobial (data not shown). Thus, tetracycline use was not associated with co-resistance. Similarly, tetracyline use was not statistically associated with tetracycline resistance. The number of animals already colonized antimicrobial-resisitant isolates (cononization pressure) may be an important factor involved in the spread of resistant isolates (Bonten et al., 1998). It is suggested that under the situation of high prevalence of tetracycline resistance, the frequency of resistance may be maintained by the colonization pressure despite the use of tetracycline. Therefore, the selection pressure imposed by the use of tetracycline may not influence to direct selection. All chloramphenicol-resistant C. coli in this study were also resistant to tetracycline. Chloramphenicol resistance in C. coli is induced by the chloramphenicol acetyltransferase (CAT) (Wang and Taylor, 1990a) and resistance to tetracycline in C. coli is conferred by the tet(O) gene, which encodes a ribosomal protection protein (Manavathu et al., 1988). Therefore, co-resistance to chloramphenicol and oxytetracycline is possibly due to plasmids or mobile genetic elements, such as integrons, transposons and insertional sequences carrying both the cat gene and tet(O) gene. Although the mechanisms of co-resistance to chloramphenicol and oxytetracycline are currently unclear, the selective pressure imposed by the use of tetracyclines may contribute to the selection of chloramphenicol-resistant C. coli. The current study suggested that erythromycin resistance was selected by macrolide use, consistent with a study performed by Rosengren et al. (2009) that also suggested an association between macrolide exposure and resistance to macrolide in Campylobacter isolated from pigs. Resistance to erythromycin in C. coli isolated from pigs in Japan was relatively high (44.9–57.1%) between 1999 and 2003 (National Veterinary Assay Laboratory, 2009). Macrolides are the drugs of choice to treat severe Campylobacter infections in humans and thus, the emergence of macrolide-resistant Campylobacter in food-producing
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animals is a major concern for public health. Moreover, the use of macrolides for the treatment of bacterial infections in pigs has increased in recent years in Japan (Koike et al., 2008). Therefore, continued monitoring of the prevalence of macrolide resistance in C. coli isolated from pigs is needed. Chloramphenicol resistance was associated with the use of phenicols in animals. The use of chloramphenicol in food-producing animals was banned in 1998 in Japan; however, the percentage of chloramphenicol-resistant C. coli in pigs in Japan has been maintained at approximately 20–40% in recent years (data not shown). Therefore, chloramphenicol resistance in C. coli isolated from pigs is likely to have been maintained by the routine use of phenicols, such as thiamphenicol or florfenicol. There are limitations in our study. The causality between antimicrobial use and antimicrobial resistance is yet to be determined because the present study is crosssectional. The time precedence of drug use to the selection of resistance could not be determined unless it is confirmed by a cohort or intervention study. 5. Conclusions Use of antimicrobials on studied farms may select antimicrobial-resistant C. coli isolates by cross-resistance or co-selection. A history of the use of macrolides was identified as a risk factor for the development of macrolide resistance and the relationship between the use of macrolides and fluoroquinolone resistance was suggestive. The emergence of fluoroquinolone and macrolide resistance in Campylobacter isolates from food-producing animals presents a threat to human health. These findings stress the importance of prudent use of antimicrobials in the swine production. Acknowledgments We are grateful to the farmers that participated in this study and the staff of the Livestock Hygiene Service Centers across the country for providing C. coli strains. References Asai, T., Kojima, A., Harada, K., Ishihara, K., Takahashi, T., Tamura, Y., 2005. Correlation between the usage volume of veterinary therapeutic antimicrobials and resistance in Escherichia coli isolated from the feces of food-producing animals in Japan. Jpn. J. Infect. Dis. 58, 369–372. Asai, T., Harada, K., Ishihara, K., Kojima, A., Sameshima, T., Tamura, Y., Takahashi, T., 2007. Association of antimicrobial resistance in Campylobacter isolated from food-producing animals with antimicrobial use on farms. Jpn. J. Infect. Dis. 60, 290–294. Berge, A.C.B., Epperson, W.B., Pritchard, R.H., 2005. Assessing the effect of a single dose florfenicol treatment in feedlot cattle on the antimicrobial resistance patterns in faecal Escherichia coli. Vet. Res. 36, 723–734. Bonten, M.J., Slaughter, S., Ambergen, A.W., Hayden, M.K., van Voorhis, J., Nathan, C., Weinstein, R.A., 1998. The role of “colonization pressure” in the spread of vancomycin-resistant enterococci: an important infection control variable. Arch. Intern. Med. 158, 1127–1132. Clinical and Laboratory Standards Institute, 2008. Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals; Approved Standard-Third Edition. M31-A3, vol. 28, no. 8. Clinical and Laboratory Standards Institute, Wayne, PA, USA.
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