Open Access

Antimicrobial resistance patterns of Staphylococcus species isolated from cats presented at a veterinary academic hospital in South Africa

BMC Veterinary ResearchBMC series – open, inclusive and trusted201713:286

https://doi.org/10.1186/s12917-017-1204-3

Received: 6 March 2017

Accepted: 1 September 2017

Published: 15 September 2017

Abstract

Background

Antimicrobial resistance is becoming increasingly important in both human and veterinary medicine. This study investigated the proportion of antimicrobial resistant samples and resistance patterns of Staphylococcus isolates from cats presented at a veterinary teaching hospital in South Africa. Records of 216 samples from cats that were submitted to the bacteriology laboratory of the University of Pretoria academic veterinary hospital between 2007 and 2012 were evaluated. Isolates were subjected to antimicrobial susceptibility testing against a panel of 15 drugs using the disc diffusion method. Chi square and Fisher’s exact tests were used to assess simple associations between antimicrobial resistance and age group, sex, breed and specimen type. Additionally, associations between Staphylococcus infection and age group, breed, sex and specimen type were assessed using logistic regression.

Results

Staphylococcus spp. isolates were identified in 17.6% (38/216) of the samples submitted and 4.6% (10/216) of these were unspeciated. The majority (61.1%,11/18) of the isolates were from skin samples, followed by otitis media (34.5%, 10/29). Coagulase Positive Staphylococcus (CoPS) comprised 11.1% (24/216) of the samples of which 7.9% (17/216) were S. intermedius group and 3.2% (7/216) were S. aureus. Among the Coagulase Negative Staphylococcus (CoNS) (1.9%, 4/216), S. felis and S. simulans each constituted 0.9% (2/216). There was a significant association between Staphylococcus spp. infection and specimen type with odds of infection being higher for ear canal and skin compared to urine specimens. There were higher proportions of samples resistant to clindamycin 34.2% (13/25), ampicillin 32.4% (2/26), lincospectin 31.6% (12/26) and penicillin-G 29.0% (11/27). Sixty three percent (24/38) of Staphylococcus spp. were resistant to one antimicrobial agent and 15.8% were multidrug resistant (MDR). MDR was more common among S. aureus 28.6% (2/7) than S. intermedius group isolates 11.8% (2/17). One S. intermedius group isolate was resistant to all β-lactam antimicrobial agents tested.

Conclusion

S. intermedius group was the most common cause of skin infections and antimicrobial resistance was not wide spread among cats presented at the veterinary academic hospital in South Africa. However, the presence of MDR-Staphylococcus spp. and isolates resistant to all β-lactams is of both public health and animal health concern.

Keywords

Staphylococcus spp. Antimicrobial resistance Veterinary hospital Cats South Africa

Background

Although Staphylococcus are commensals of the skin, mucous membranes, alimentary and urogenital tracts of a diverse group of mammals and birds, they have been implicated in clinical infections of humans and animals [13]. Transmission of Staphylococcus between animals and humans are known to occur [1, 4]. Cats have been reported as carriers of both Coagulase positive (CoPS) and coagulase negative Staphylococcus species (CoNS) [2, 3, 57]. However, coagulase positive Staphylococcus species infections seem to be more prominent in feline medicine than CoNS infections [1]. Among the CoPS species in cats, S. pseudintermedius are the most common followed by S. aureus [5, 8]. These infections have been associated with pyoderma, postoperative wound infections and otitis [9]. In addition, S. felis, is a cause of urinary tract infections [10].

Although resistance to β-lactam antimicrobials among Staphylococcus isolates from cats has been reported [6, 8], other antimicrobial agents such as gentamycin, enrofloxacin and doxycycline have been reported to be effective against Staphylococcus infections in cats [5, 11, 12]. However, information on the proportion of antimicrobial resistant isolates and resistance patterns of Staphylococcus species in clinical cases of cats in developing economies in general and South Africa in particular is very limited. Therefore, the objective of this study was to investigate the proportion of antimicrobial resistant isolates and resistance patterns among Staphylococcus species isolates from cat samples submitted to a veterinary academic hospital in South Africa between 2007 and 2012.

Methods

Data collection

Data containing records of cat samples submitted to the University of Pretoria Bacteriology Laboratory at the Veterinary Teaching Hospital in South Africa between January 2007 and December 2012 for routine diagnostic tests were evaluated. The following variables were captured: breed, age, sex, specimen type, staphylococcus species isolated, antimicrobial included in the antimicrobial susceptibility test panel and the susceptibility profile of the isolates.

Staphylococcus identification and antimicrobial susceptibility testing

Culture of samples was done using sheep blood agar incubated at 37 °C for at least 24 h. All media used were quality controlled using S. aureus ATCC 25923. Suspected Staphylococcus colonies were identified based on phenotypic characteristics including colony characteristics, catalase, D-mannitol, maltose, deoxyribonuclease (DNase) tests, polymyxin-B and Gram-staining as described by Quinn [13]. S. intermedius and S. delphini were classified as S. intermedius group (SIG) as described by Sasaki et al. [14].

Isolates were subjected to antimicrobial susceptibility testing against a panel of 15 drugs using the disc diffusion method (discs supplied by Oxoid) [15]. Included in the panel were the following drugs: 30 μg amikacin (AK), 30 μg doxycycline (DOX30), 5 μg enrofloxacin (ENR), 10 μg gentamicin (CN), 10 μg penicillin G (P), 25 μg sulpha-trimethroprim (SXT), 30 μg chloramphenicol (C), 30 μg cephalothin/lexin (KF), 30 μg kanamycin (K), 2 μg clindamycin/lincomycin (MY), 100 μg lincospectin (Espectinomycine-lincomycine) (LS100), 5 μg orbifloxacin (OBX5), 20/10 μg synulox (Amoxicillin-Clavulanic acid) (AMC20/10) and 15 μg tylosin (TY). The results, based on the diameter of the inhibition zones, were classified as sensitive, intermediate or resistant in accordance with the Clinical and Laboratory Standards Institute [15]. For the purposes of the study, intermediate susceptibility was considered as susceptible. Multidrug resistance (MDR) was defined as resistance to at least one antimicrobial agent in three or more antimicrobial categories [16].

Data analysis

All the statistical analyses were performed using SAS 9.4 (SAS Institute Inc., Cary, NC, USA) statistical package. The dataset was assessed for missing data and inconsistencies such as improbable values. Shapiro-Wilk test of normality was used for evaluation of distributions of age that was found to be non-normally distributed and hence median and interquartile ranges were reported. Age was also categorised into two categories: <2 years and ≥2 years. The frequencies and proportions of all categorical variables were calculated and presented in a table. Associations between antimicrobial resistance of Staphylococcus spp. isolates and a number of host factors (breed, age, sex, specimen type) and other categorical variables were assessed using the Chi-square and Fisher’s Exact tests. Statistical significant was assessed using a critical p-value of 0.05. The variables specimen type and breed had too many categories to include in the model in their original form and hence they were re-coded (Table 1).
Table 1

Distribution of Staphylococcus isolates among cat specimens tested at an academic veterinary hospital laboratory, 2007–2012

  

Number of cats tested

Staphylococcus positive

Variable

Category

Frequency

Percent

Frequency

Percent

Breed (n = 212)

 

Domestic Short Hair

132

62.3

24

18.2

 

Persian

21

9.9

4

19.1

 

Siamese

15

7.1

1

6.7

 

Domestic Long Hair

12

5.7

3

25.0

 

All others

32

15.1

6

18.8

Sex (n = 205)

 

Male

122

59.5

17

13.9

 

Female

83

40.5

20

24.1

Specimen type (n = 215)

 

Urine

95

44.2

3

3.2

 

Ear canal swab

29

13.5

10

34.5

 

Skin

18

8.4

11

61.1

 

All others

73

34.0

14

19.2

Age (n = 216)

 

≥2 years

123

56.9

21

17.1

 

<2 years

93

43.1

17

18.3

Univariable and multivariable models

Investigation of the predictors of Staphylococcus spp. infections was done in two steps. In the first step, univariable logistic regression model was fit to assess the relationships between sex, age, specimen type and breed, and the outcome variable, Staphylococcus status. The potential predictors of Staphylococcus spp. infection at this stage were identified using a relaxed α ≤ 0.20. Thus variables with p ≤ 0.20 in the univariable model were considered for inclusion in the multivariable model in the 2nd step. Therefore, the 2nd step involved fitting a multivariable logistic regression model using manual backwards selection method with the significance set at α ≤ 0.05.

Confounding was assessed by comparing the change in model coefficients with and without the suspected confounders. If the removal of a suspected confounding variable resulted in a 20% or greater change in another model coefficient, the removed variable was considered a confounder and retained in the model regardless of its statistical significance. In addition, two-way interaction terms between variable in the final main effects model were assessed.

Odds ratios (ORs) and their 95% confidence intervals were computed for variables included in the final model. The differences between categories of statistically significant predictors for Staphylococcus spp. were also assessed by changing the reference categories of the predictors. Hosmer-Lemeshow goodness-of-fit test was used to assess model fit.

Results

A total of 216 samples were submitted to the bacteriology lab during the study period, of which, 17.6% (38/216) tested positive for Staphylococcus spp. each of which had single isolates (i.e. no mixed infections were identified).The majority of samples tested were urine (44.2%, 95/215), followed by ear canal swab (13.5%, 29/215) and skin samples (8.4%, 18/215). Significantly (p = 0.0065) more samples originated from males (59.5%, 122/205) than female cats (40.5, 83/205). Similarly, a significantly (p = 0.0412) higher proportion of samples came from cats ≥2 years (56.9%, 123/216) compared to cats <2 years (43.1%, 93/216). The majority of samples were obtained from the domestic short hair breed (DSH) (62.3%, 132/212), followed by Persian breed (9.9%, 21/212) (Table 1).

Staphylococcus species were isolated from several cat breeds including domestic long hair (25.0% 3/12), domestic short hair (18.2%, 24/132) and persian breed (19.1%, 4/21). Skin samples yielded the highest (61.1%,11/18) percentage of staphylococcus isolates followed by ear swabs (34.5%,10/29).

Significantly (p = 0.02) more CoPS (11.1%, 24/216) were isolated compared to CoNS (1.9%, 4/216). Among the CoPS, S. intermedius group was most predominant (7.9%, 17/216) followed by S. aureus (3,2%, 7/216). Equal percentage of S. felis (0.9%, 2/216) and S. simulans (0.9%; 2/216) were observed among the CoNS. Five percent (4.6%, 10/216) of the Staphylococcus isolates identified were not characterized (Table 2).
Table 2

Distribution of Staphylococcus species isolated from clinical specimens from cats presented at an academic veterinary hospital between 2007 and 2012 (n = 216)

 

Isolate

Frequency

Percent (%)

CoPS n = 24 (11.1%)

S. intermedius group (SIG)

17

7.9

S. aureus

7

3.2

CoNS n = 4 (1.9%)

S. felis

2

0.9

S. simulans

2

0.9

Unspeciated

S. spp.

10

4.6

Negative

172

82.4

 

Total

216

100

Staphylococcus isolates exhibited relatively high levels of resistance towards ampicillin (32.4%, 12/26), penicillin-G (29.0%, 11/27), clindamycin (34.2%,13/25) and lincospectin (31.6%, 12/26) (Table 3). Overall, 63.2% (24/38) of Staphylococcus spp. were resistant to at least one antimicrobial agent and 21.1% (8/38) were multidrug resistant (MDR). S. aureus (85.7%, 6/7) had the highest level of resistance to at least one antimicrobial agent followed by S. intermedius group (52.9%, 9/17). Similarly, S. aureus (42.9%, 3/7) had a higher level of MDR than S. intermedius group (12.5%, 2/16). One S. intermedius group isolate was resistant to all β-lactam antimicrobial agents tested. This isolate was also resistant to 9 out of the 15 antimicrobial agents tested. Three S. intermedius group isolates were resistant to both clindamycin and lincosamides. Among the S. aureus isolates, one was resistant to five antimicrobial agents and two to four antimicrobial agents (Table 4).
Table 3

Antimicrobial resistance profile of Staphylococcus isolates to antimicrobial agents from samples tested at an academic veterinary laboratory, 2007–2012

Group

Drug

Frequency

Percent (n/N) b

β-lactam

 

26

28.9 (26/90)

 Penicillin

PenicillinG

11

29.0 (11/27)

 

Ampicillin

12

32.4 (12/26)

 Cephalosporin

Cephalothin

1

2.7 (1/37)

 

Ceftiofur

1

2.7 (1/37)

 Combination

Amoxicillin/Clavulanic acid

1

2.7 (1/37)

Tetracycline

Doxycycline

1

2.7 (1/37)

Fluoroquinolone

 

6

8.6 (6/70)

 

Enrofloxacin

3

7.9 (3/35)

 

Orbifloxacin

3

7.9 (3/35)

Aminoglycoside

 

4

3.6 (4/110)

 

Gentamicin

1

2.7 (1/37)

 

Amikacin

1

2.7 (1/37)

 

Kanamycin

2

5.3 (2/36)

Potentiated sulfonamide

Sulfamethoxazole/trimethoprim

4

10.5 (4/34)

Amphenicols

Chloramphenicol

2

5.2 (2/36)

Lincosamides

Clindamycin

13

34.2 (13/25)

Aminoglycoside-lincosamide

Lincospectin

12

31.6 (12/26)

Macrolide

Tylosin

2

5.3 (2/36)

b = n is the number resistant, N is number tested

Table 4

Antimicrobial resistance patterns identified in Staphylococcus isolates from cat specimens tested at an academic veterinary hospital laboratory, 2007–2012

 

Antimicrobial Resistance

Multidrug Resistance

B-Lactam resistance

Resistance patterns

Species

Percent (n/N)

Percent (n/N)

Percent (n/N)

 

S. aureus

85.7 (6/7)

42.9 (3/7)

0

AMP (1), AMP PEN (1), AMP PEN LIN (1), AMP PEN CLI LIN (1), AMP PEN CHL LIN (1), AMP SP KAN CLI LIN (1)

S. felis

0 (0/2)

0

0

 

S. intermedius group

52.9 (9/17)

11.8 (2/17)

5.9 (1/17)

PEN (1), KAN (1), CLI LIN (3), SP LIN (1), AMP PEN SP (1), ENR LIN OR TYL (1), AMP CEF GEN PEN SP CEF KAN OR SU (1)

S. simulans

0 (0/2)

0

0

 

S. spp.

90.0 (9/10)

30.0 (3/10)

0

CLI (2), LIN (1), CHL CLI (1), AMP PEN (1), CLI LIN OR (1), AMP AMP DOX ENR PEN CLI (1), AMP PEN CLI (1), AMP ENR PEN CLI LIN TYL (1),

n number of resistant samples, N number of samples tested, AMP ampicillin, CEF Ceftiofur, ENR Enrofloxacin, GEN Gentamicin, PEN PenicillinG, SP Sulpha/Trimethroprim, CHL Chloramphenicol, KAN Kanamycin, CLI Clindamycin/Lincomycin, AMI Amikacin, DOX Doxycycline, LIN Lincospectin, ORB Orbifloxacin, SU Amoxicillin/Clavulanic acid, TYL Tylosin

Predictors of staphylococcus infections

Based on the univariable logistic model, only sex and specimen type stood out as potential predictors of Staphylococcus spp. infection based on a liberal α ≤ 0.20 (Table 5). Thus, only these two variables were assessed in the multivariable model. In the final model only specimen type was significantly associated with staphylococcus species infection based on α ≤ 0.05. The odds of testing positive for Staphylococcus spp. infections were significantly higher among ear canal (p = 0.0002) and skin samples (p < 0.0001) than urine samples (Table 6). However, there was no significant differences in the odds of Staphylococcus spp. infection between skin and ear canal samples (Table 7).
Table 5

Results of the univariable logistic model showing predictors of Staphylococcus spp. infection among cats tested at an academic veterinary hospital laboratory, 2007–2012

Variable

ORa

95% CIb

p-value

Breed

 Domestic Long Hair

1.4

0.3

7.0

0.368

 Domestic Short Hair

0.9

0.4

2.6

0.707

 Persian

1.0

0.3

4.2

0.723

 Siamese

0.3

0.03

2.8

0.237

 All others

Ref

.

.

.

Sex

 Female

1.9

0.9

4.0

0.066

 Male

Ref

.

.

.

Specimen type

 Ear canal swab

16.1

4.1

64.2

<0.0001

 Skin

48.2

10.9

213.7

<0.0001

 All others

7.3

2.0

26.4

0.003

 Urine

Ref

.

.

.

Age

  < 2 years

1.1

0.5

2.2

0.818

  > = 2 years

Ref

.

.

.

aOdds ratio

b95% Confidence Interval

Table 6

Multivariable logistic model showing predictors of Staphylococcus spp. infection among cats tested at an academic veterinary hospital laboratory, 2007–2012

Variable

OR1

95% CI2

p-value

Sex

 Female

1.9

0.8

4.3

0.117

 Male

Ref

.

.

.

Specimen type

 Ear canal swab

14.8

3.6

60.5

0.0002

 Skin

52.1

11.3

240.3

<.0001

 All others

8.4

2.3

30.7

0.001

 Urine

Ref

.

.

.

Table 7

Final multivariable logistic model showing the results of changing reference categories of specimen type

Variable

OR1

95% CI2

p-value

Specimen type

 Skin

3.519

0.969

12.78

0.0559

 Urine

0.068

0.017

0.276

0.0002

 All others

0.564

0.208

1.531

0.2611

 Ear canal swab

Ref

.

.

.

 Ear canal swab

0.284

0.078

1.032

0.0559

 Urine

0.019

0.004

0.089

<.0001

 All others

0.16

0.05

0.517

0.0022

 Skin

Ref

.

.

.

 Ear canal swab

1.773

0.653

4.81

0.2611

 Skin

6.237

1.933

20.131

0.0022

 Urine

0.12

0.033

0.439

0.0014

 All others

Ref

.

.

.

Discussion

The aim of this study was to investigate the proportion of antimicrobial resistant isolates and resistance patterns of Staphylococcus spp. isolates from clinical samples obtained from cats admitted to a veterinary academic hospital in South Africa. The proportion of Staphylococcus spp. isolated from cat samples in this study was relatively low (17.6%). This is not directly comparable to findings from other previous studies on cats due to differences in isolation methods (use of enrichment media in particular), and differences in study designs. In the current study, we investigated Staphylococcus infections in hospitalised clinical cases only. However, the majority of similar published studies of Staphylococcus in cats have largely focused on methicillin resistance rather than Staphylococcus infections in general. In addition, past studies have focused on carriage rather than infections [8, 17].

Similar to findings from other studies [8, 17], in this study we observed that skin and ear canal samples had significantly higher odds of testing positive for Staphylococcus spp. than other samples. These results seem to suggest that Staphylococcus spp. are a major cause of skin related infections in cats [1820]. Although there tended to be a higher proportion of Staphylococcus spp. isolated from the domestic short hair breeds, the final model indicated no significant association between breed and odds of Staphylococcus spp. infection. However, the lack of significant association might be due to small sample size involved in this study. It is worth noting that, there is evidence that certain diseases are more common in certain breeds of cats and we suspect that this might be the case with Staphylococcus infections [17, 21].

Consistent with other studies [3, 5, 17, 19], we observed a higher percentage of CoPS than CoNS. This is mainly due to the observed higher percentage of S. intermedius group, which are CoPS, isolated in this study. On the contrary, Abraham et al. [7] reported nearly equal proportions of S. aureus and S. pseudintermedius isolates from asymptomatic cats. Consistent with our study, a Brazilian study by Lilenbaum et al. [8] reported a higher percentage of S. intermedius group (S. pseudintermedius) in cats compared to other Staphylococcus species. This may be related to the fact that SIG especially S. pseudintermedius is well adapted to the skin surface of dogs and cats than S. aureus [2225].

The observed higher percentage of resistance towards β-lactam and lincosamide antimicrobial agents among the Staphylococcus isolates in cats has previously been reported [6, 8, 23]. Of particular concern is one S. intermedius group isolate that was resistant to all β-lactam antimicrobial agents tested in this study. Moreover, MRSA have an intrinsic resistance to β-lactams by virtue of newly acquired low-affinity penicillin-binding protein 2A (PBP2A). Therefore, it is possible that this isolate was MRSA [26, 27]. Unforunately, we could not assess this since the lab that supplied the data used in this study did not test for methicillin resistance. Almost 16 % (15.8%) of Staphylococcus isolates in this study were MDR. This is close to the 14.8% reported by Gandolfi-Decristophoris et al. [23] in Switzerland.

Since this is a retrospective study, these findings should be interpreted with caution. The history of previous use of antimicrobial agents was not included in the analysis and this could have affected the recovery rates of Staphylococcus species. The study also suffers from low samples size which impacted the precision of some of the estimates. Nonetheless, the results provide a useful preliminary indication of the burden and antimicrobial resistance patterns of Staphylococcus spp. infections in cats presented to the academic veterinary hospital in South Africa.

Conclusions

As has been observed in other studies, this study suggests that S. intermedius group is the most common cause of skin infections in cats investigated in this study. It also suggests that antimicrobial resistance is not so wide spread among cats presented at the veterinary academic hospital in South Africa. Considering the risk of cross-transmission of resistant organisms between cats and humans, the levels of resistance to β-lactams is of great concern from both a public health and animal health point of view. However, given the limited scope of this study, there is need for larger and more detailed primary base studies to specifically assess the extent of antimicrobial resistant infections in cats in South Africa and their role in the spread of antimicrobial drug resistance to humans.

Abbreviations

AMR: 

Antimicrobial resistance

CoNS: 

Coagulase negative staphylococci species

CoPS: 

Coagulase Positive Staphylococcus

DSH: 

Domestic Short Hair breed

MDR: 

Multidrug resistant resistance

SAS: 

Statistical Analysis System

Declarations

Acknowledgements

The authors would like to thank the Department of Tropical Diseases and Companion Animal Clinical Studies for providing access to the records used in this study. We are also grateful to Ms. S Nxumalo and Mr. W Mbethe for helping with data entry and validation.

Funding

Not applicable.

Availability of data and materials

The data that support the findings of this study are available from the bacteriology laboratory of the University of Pretoria that has legal ownership of the data. The data are not publicly available and should be requested and obtained from the above legal owner.

Authors’ contributions

DNQ was involved in study design and data management and performed all statistical analyses and interpretation as well as preparation of the manuscript draft. AO was involved in study design, data analysis and interpretation as well as extensive editing of the manuscript. JWO was involved in study design and editing of the manuscript. DS was involved in data collection and interpretation of results of the manuscript. All authors read and approved the final manuscript.

Ethics approval

The study was approved by the University of Pretoria Ethics Committee (reference number S4285–15).

Consent for publication

The study does not involve human subjects and therefore no consent was required. However, the lab that supplied the study data provided consent for study results to be published.

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
University of Pretoria, Faculty of Veterinary Science, Department of Paraclinical Sciences, SectionVeterinary Public Health
(2)
University of South Africa, College of Agriculture and Environmental Sciences, Department of Agriculture and Animal Health
(3)
University of Tennessee, College of Veterinary Medicine, Department of Biomedical and Diagnostic Sciences

References

  1. Morris DO, Mauldin EA, O’Shea K, Shofer FS, Rankin SC. Clinical, microbiological, and molecular characterization of methicillin-resistant Staphylococcus Aureus infections of cats. Am J Vet Res. 2006;67:1421–5.View ArticlePubMedGoogle Scholar
  2. Hanselman BA, Kruth SA, Rousseau J, Weese JS. Coagulase positive staphylococcal colonization of humans and their household pets. Can Vet J. 2009;50:954–8.PubMedPubMed CentralGoogle Scholar
  3. Rich M. Staphylococci in animals: prevalence, identification and antimicrobial susceptibility, with an emphasis on methicillin-resistant Staphylococcus Aureus. Br J Biomed Sci. 2005;62:98–105.View ArticlePubMedGoogle Scholar
  4. Duquette RA, Nuttall TJ. Methicillin-resistant Staphylococcus Aureus in dogs and cats: an emerging problem? J Small Anim Pract. Blackwell Publishing Ltd. 2004;45:591–7.View ArticleGoogle Scholar
  5. Beça N, Bessa LJ, Mendes Â, Santos J, Leite-Martins L, Matos AJF, et al. Coagulase-positive staphylococcus: prevalence and antimicrobial resistance. J Am Anim Hosp Assoc. 2015;51:365–71.View ArticlePubMedGoogle Scholar
  6. Bierowiec K, Płoneczka-Janeczko K, Rypuła K. Is the colonisation of Staphylococcus Aureus in pets associated with their close contact with owners? PLoS One. 2016;11:e0156052.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Abraham J, Morris D, Griffeth G, Shofer F, Rankin S. Surveillance of healthy cats and cats with inflammatory skin disease for colonization of the skin by methicillin-resistant coagulase-positive staphylococci and staphylococcus schleiferi ssp. schleiferi. Dermatology. 2007;18:252–9.Google Scholar
  8. Lilenbaum W, Nunes EL, Azeredo MA. Prevalence and antimicrobial susceptibility of staphylococci isolated from the skin surface of clinically normal cats. Lett Appl Microbiol. 1998;27:224–8.View ArticlePubMedGoogle Scholar
  9. Bannoehr J, Guardabassi L. Staphylococcus pseudintermedius in the dog: taxonomy, diagnostics, ecology, epidemiology and pathogenicity. Vet Dermatol. 2012;23:253–66.View ArticlePubMedGoogle Scholar
  10. Litster A, Moss SSM, Honnery M, Rees B, Trott DJD. Prevalence of bacterial species in cats with clinical signs of lower urinary tract disease: recognition of Staphylococcus Felis as a possible feline urinary tract pathogen. Vet Microbiol. 2007;121:182–8.View ArticlePubMedGoogle Scholar
  11. Ganiere JP, Medaille C, Mangion C. Antimicrobial drug susceptibility of Staphylococcus Intermedius clinical isolates from canine pyoderma. J Vet Med B Infect Dis Vet Public Health. 2005;52:25–31.View ArticlePubMedGoogle Scholar
  12. Lilenbaum W, Esteves AL, Souza GN. Prevalence and antimicrobial susceptibility of staphylococci isolated from saliva of clinically normal cats. Lett Appl Microbiol. Blackwell Science Ltd. 1999;28:448–52.View ArticleGoogle Scholar
  13. Quinn PJ, Carter ME, Markey B, Carter GR. Clinical veterinary microbiology. Edinburgh: Mosby Wolfe; 1994.Google Scholar
  14. Sasaki T, Kikuchi K, Tanaka Y, Takahashi N, Kamata S, Hiramatsu K. Reclassification of phenotypically identified Staphylococcus Intermedius strains. J Clin Microbiol. 2007;45:2770–8.View ArticlePubMedPubMed CentralGoogle Scholar
  15. Clinical Institute Laboratory Standards. Performance standards for antimicrobial disk and dilution susceptibility tests for bacteria isolated from animals; approved standard -- fourth edition. CLSI document VET01-A. 2013.Google Scholar
  16. Magiorakos AP, Srinivasan A, Carey RB, Carmeli Y, Falagas ME, Giske CG, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18:268–81.View ArticlePubMedGoogle Scholar
  17. Loeffler A, Boag AK, Sung J, Lindsay JA, Guardabassi L, Dalsgaard A, et al. Prevalence of methicillin-resistant Staphylococcus Aureus among staff and pets in a small animal referral hospital in the UK. J Antimicrob Chemother. 2005;56:692–7.View ArticlePubMedGoogle Scholar
  18. Scott DW, Paradis M. A survey of canine and feline skin disorders seen in a university practice: small animal clinic, University of Montréal, Saint-Hyacinthe, Québec (1987-1988). Can Vet J. 1990;31:830–5.PubMedPubMed CentralGoogle Scholar
  19. Devriese LA, Nzuambe D, Godard C. Identification and characteristics of staphylococci isolated from lesions and normal skin of horses. Vet Microbiol. 1985;10:269–77.View ArticlePubMedGoogle Scholar
  20. Biberstein EL, Jang SS, Hirsh DC. Species distribution of coagulase-positive staphylococci in animals. J Clin Microbiol. 1984;19:610–5.PubMedPubMed CentralGoogle Scholar
  21. Lekcharoensuk C, Osborne CA, Lulich JP. Epidemiologic study of risk factors for lower urinary tract diseases in cats. J Am Vet Med Assoc. 2001;218:1429–35.View ArticlePubMedGoogle Scholar
  22. Kawakami T, Shibata S, Murayama N, Nagata M, Nishifuji K, Iwasaki T, et al. Antimicrobial susceptibility and methicillin resistance in staphylococcus pseudintermedius and staphylococcus schleiferi subsp. coagulans isolated from dogs with pyoderma in Japan. J Vet Med Sci. 2010;72:1615–9.View ArticlePubMedGoogle Scholar
  23. Gandolfi-Decristophoris P, Regula G, Petrini O, Zinsstag J, Schelling E. Prevalence and risk factors for carriage of multi-drug resistant staphylococci in healthy cats and dogs. J Vet Sci. 2013;14:449–56.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Schmidt VM, Williams NJ, Pinchbeck G, Corless CE, Shaw S, McEwan N, et al. Antimicrobial resistance and characterisation of staphylococci isolated from healthy Labrador retrievers in the United Kingdom. BMC Vet Res. 2014;10:17.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Paul NC, Bärgman SC, Moodley A, Nielsen SS, Guardabassi L. Staphylococcus pseudintermedius colonization patterns and strain diversity in healthy dogs: a cross-sectional and longitudinal study. Vet Microbiol. 2012;160:420–7.View ArticlePubMedGoogle Scholar
  26. Guignard B, Entenza JM, Moreillon P. β-Lactams against methicillin-resistant Staphylococcus Aureus. Curr Opin Pharmacol. 2005;5:479–89.View ArticlePubMedGoogle Scholar
  27. Lim D, Strynadka NCJ. Structural basis for the beta lactam resistance of PBP2a from methicillin-resistant Staphylococcus Aureus. Nat Struct Biol. 2002;9:870–6.PubMedGoogle Scholar

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