Antibiotic Susceptibility of Bacterial Infections in Arizona Companion Animal Species from January 2015 to December 2016

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1 Antibiotic Susceptibility of Bacterial Infections in Arizona Companion Animal Species from January 2015 to December 2016 Item Type text; Electronic Thesis Authors Hefferman, Sarah Marie Publisher The University of Arizona. Rights Copyright is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. Download date 11/07/ :05:48 Link to Item

2 ANTIBIOTIC SUSCEPTIBILITY OF BACTERIAL INFECTIONS IN ARIZONA COMPANION ANIMAL SPECIES FROM JANUARY 2015 TO DECEMBER 2016 By SARAH MARIE HEFFERAN A Thesis Submitted to The Honors College In Partial Fulfillment of the Bachelors degree With Honors in Physiology THE UNIVERSITY OF ARIZONA M A Y Approved by: Dr. Peder Cuneo Department of Animal & Comparative Biomedical Sciences

3 Table of Contents Abstract Introduction Background...1 Statement of Purpose....3 Statement of Relevance Methods.3 Results...4 Discussion Considerations Future Directions References Appendix.31

4 ABSTRACT Antibiotic resistance is a problem of growing importance in veterinary medicine. In order to ensure that antibiotics are used appropriately, antibiograms are generated to monitor bacterial susceptibility to antibiotics. The computer program Biomic was used to generate antibiograms for bacterial isolates from canine, feline, and equine samples sent to the Arizona Veterinary Diagnostic Laboratory between January 1st, 2015 and December 31st, The most common specimen types were urine (n=125), ear cultures (n=92), wounds (n=63), and skin cultures (n=30) for canines, uterine cultures (n=44) and wounds (n=41) for equines, and urine (n=16) and wounds (n=17) from felines. Of the canine isolates, the most common urine isolate E. coli was most susceptible to amikacin and chloramphenicol (92%), the most common ear isolate P. aeruginosa was most susceptible to amikacin (74%), the most common skin isolate Staphylococcus coagulase-negative was most susceptible to marbofloxacin, amikacin, amoxicillin-clavulanate, and cephalothin (60%), and the most common wound isolate E. coli was most susceptible to trimethoprim-sulfamethoxazole (100%). Of the equine isolates, the most common uterine isolate S. equi spp zooepidemicus was most susceptible to penicillin G (92%) and the most common wound isolate S. equi spp zooepidemicus were most susceptible to penicillin G (100%). INTRODUCTION Background Antibiotics can have a variety of cellular targets, as shown to the left in Figure 1 [1]. For example, beta lactam antibiotics function by targeting bacterial cell wall synthesis, while other antibiotics inhibit the 30S or 50S subunits of the bacterial ribosome and thus interfere with protein synthesis [1]. Although the cellular targets of antibiotics vary, they all act to disrupt the machinery and normal functioning of bacteria. 1

5 The ubiquitous nature of antibiotics in society and their misuse can potentially lead to the development of antimicrobial resistance in some bacterial strains [3]. There are many mechanisms through which bacteria may achieve antimicrobial resistance, as shown below in Figure 2 [1]. Each of these mechanisms acts to render the antibiotic ineffective in its normal functioning. For example, streptomycin normally inhibits bacterial protein synthesis by preventing binding of the trna to the 30S ribosomal subunit. As shown in Figure 2, the mechanism of antibiotic resistance to streptomycin results from the drug being exported from the cell before it reaches its intracellular ribosomal target [1]. Although antibiotic resistance may begin with only a few bacteria in a colony having the biochemical characteristics to evade the activity of antibiotics, these resistant bacteria can go on to proliferate and thus perpetuate their antibiotic resistance. Genes that govern antimicrobial resistance can also be transferred from one bacterium to another, growing the population of resistant bacteria [3]. In order to mitigate problems related to antimicrobial resistance, it is necessary to monitor the susceptibility of bacteria to antibiotics. This surveillance is especially important in the veterinary field as it relates to the concept of One Health. The idea of One Health is that the health of humans is related to both the health of animals and to that of the environment. One of the primary avenues through which the health of animals is directly related to the health of humans is through agriculture [2]. Government organizations such as the United States Department of Agriculture (USDA) have implemented action plans to enumerate ways in which surveillance, research, and education can aid in the mission to mitigate problems related to antimicrobial resistance in agriculture and thus in humans. Additionally, companion animals (felines, canines) have a close connection to their human counterparts. Appropriate treatment of pets is therefore pertinent in the prevention of the zoonotic transmission of antimicrobialresistant bacterial strains. One of the main tools used to monitor the susceptibility of bacteria to antibiotics is an antibiogram. Antibiograms are data profiles that can be generated using computer software to describe the susceptibility of certain bacterial species to a panel of antibiotics. These are especially useful in a diagnostic laboratory or hospital setting due to their high volume of specimens. In the realm of companion animal medicine, antibiograms can be used to inform 2

6 clinicians of trends in antibiotic susceptibility of local bacterial strains in order to best treat their patients. Statement of Purpose The goal of this project is to generate antibiograms for the most common specimen types submitted to the Arizona Veterinary Diagnostic Laboratory in companion animal species (canines, felines) and equines from January 1 st, 2015 to December 31 st, These antibiograms will provide a resource for local veterinarians to consult while developing treatment plans for their patients. Statement of Relevance Monitoring trends in the antibiotic susceptibility of local bacterial isolates is important to ensure the appropriate administration of antibiotics to animals during veterinary treatment. An inappropriate use of antibiotics, if significant, can potentially contribute to the growth of antibiotic-resistant strains of bacteria. Therefore, it is pertinent both to monitor these trends to know if susceptibility is changing over time, and to select antibiotics for treatment based upon current susceptibility trends in the area. METHODS Bacterial Isolation Once the specimen is collected by a veterinarian and received at the laboratory, it is assigned a case number. Next, it is necessary to isolate any bacterial species present in the sample. This involves isolating colonies based upon morphology and performing biochemical testing and staining in order to identify the bacteria. If a sample yields no growth, it does not advance past this stage. Antibiotic Sensitivity Testing Once the isolates are identified, Kirby-Bauer Disc Diffusion testing is performed to analyze the isolates susceptibility to a panel of antibiotics. The panel of antibiotics is typically selected from pre-defined panels at the laboratory depending on one or both of the following parameters: (1) the species the specimen came from and (2) the gram type of the bacterium. This testing involves incubating the bacterial plate with antibiotic-infused discs. The computer program Biomic was used to read the plate once testing was complete. This includes generating the Minimum Inhibitory Concentration (MIC) and evaluating the susceptibility of the isolate to each antibiotic. This information is automatically input into the computer into the according sample file based upon its assigned case number. Data Input and Organization 3

7 Next, patient and specimen information was updated in the computer in order to complete the online documentation. This required reading back through paper copies of each specimen submission that was included in this analysis and extracting pertinent information to include in the electronic file in Biomic. Relevant information included patient species and specimen type (e.g. urine, wound). During data entry, the number of each specimen type (according to species and isolated bacteria) was recorded in an excel sheet. This process was performed retroactively between August 2016 and March Generating Antibiograms The generation of antibiograms in Biomic was completed using the Cumulative Susceptibility Chart feature in the Epidemiology Reports section of the program. The generation of the chart is automated by the program after selecting the parameters for the antibiogram report (including report type, date of specimen receipt, location of specimen collection, specimen type, organism, antibiotics, species, etc.). An antibiogram was run for each species (canine, equine, feline) for any specimen type that had over 30 specimens for horses and dogs between 2015 and 2016, and over 15 specimens total for cats between 2015 and

8 Count RESULTS Figure 1.1 Distribution of Bacterial Isolates from Canine Urine Samples Canine Urine Isolates Bacteria 5

9 Percent Susceptibility (%) Figure 1.2 Antibiotic Susceptibility of Bacterial Isolates from Canine Urine Samples 100 Canine Urine Isolate Antibiotic Susceptibility E. coli P. mirabilis 50 Proteus indole-negative Staphylococcus coagulase-positive Staphylococcus coagulase-negative Streptococcus sp. Enterococcus sp AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ Antibiotic 6

10 Figure 1.3 Antibiotic Susceptibility of Bacterial Isolates from Canine Urine Samples Canine Urine Isolates AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ Acientobacter sp. % susceptible E. coli % susceptible count Klebsiella sp. % susceptible Proteus sp. % susceptible count P. mirabilis % susceptible count Proteus indole-negative % susceptible count P. aeruginosa % susceptible count Staphylococcus sp. % susceptible count S. aureus % susceptible count Staphylococcus coagulase-positive % susceptible count Staphylococcus coagulase-negative % susceptible count Streptococcus sp. % susceptible count S. canis % susceptible count Enterococcus sp. % susceptible count E. faecalis % susceptible

11 Count O. anthropi % susceptible count Figure 2.1 Distribution of Bacterial Isolates from Canine Ear Samples 20 Canine Ear Isolates Bacteria 8

12 Percent Susceptibility (%) Figure 2.2 Antibiotic Susceptibility of Bacterial Isolates from Canine Ear Samples 100 Canine Ear Isolate Antibiotic Susceptibility P. aeruginosa Corynebacterium sp. Staphylococcus sp. S. aureus Staphylococcus coagulase-positive Staphylococcus coagulase-negative Streptococcus sp. S. canis AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ Antibiotic Figure 2.3 Antibiotic Susceptibility of Bacterial Isolates from Canine Ear Samples Canine Ear Isolates AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ E. coli % susceptible count

13 Klebsiella sp. % susceptible Proteus sp. % susceptible count P. mirabilis % susceptible count Proteus Indole-negative % susceptible Pseudomonas sp. % susceptible count P. aeruginosa % susceptible count Corynebacterium sp. % susceptible count Staphylococcus sp. % susceptible count S. aureus % susceptible count Staphylococcus coagulase-positive % susceptible count Staphylococcus coagulase-negative % susceptible count S. hominis % susceptible Streptococcus sp. % susceptible count S. canis % susceptible count B. cereus % susceptible

14 Percent Susceptibilty (%) Count Figure 3.1 Distribution of Bacterial Isolates from Canine Skin Samples Canine Skin Isolates Bacteria Figure 3.2 Antibiotic Susceptibility of Bacterial Isolates from Canine Skin Samples Canine Skin Isolate Antibiotic Susceptibility Antibiotic Staphylococcus coagulase-positive Staphylococcus coagulase-negative 11

15 Figure 3.3 Antibiotic Susceptibility of Bacterial Isolates from Canine Skin Samples Canine Skin Isolates AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ R. terrigena % susceptible Proteus Indole-negative % susceptible Pseudomonas sp. % susceptible count Corynebacterium sp. % susceptible count Staphylococcus sp. % susceptible S. aureus % susceptible count Staphylococcus coagulase-positive % susceptible count Staphylococcus coagulase-negative % susceptible count Streptococcus sp. % susceptible count S. canis % susceptible count

16 Count Figure 4.1 Distribution of Bacterial Isolates from Canine Wound Samples Canine Wound Isolates Bacteria 13

17 Percent Susceptibility (%) Figure 4.2 Antibiotic Susceptibility of Bacterial Isolates from Canine Wound Samples 100 Canine Wound Isolate Antibiotic Susceptibility E. coli Staphylococcus sp. S. aureus Staphylococcus coagulase-positive Staphylococcus coagulase-negative Streptococcus sp. S. canis 10 0 Antibiotic 14

18 Figure 4.3 Antibiotic Susceptibility of Bacterial Isolates from Canine Wound Samples Canine Wound Isolates AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ Acinetobacter sp. % susceptible count Enterobacter sp. % susceptible E. cloacae % susceptible count E. coli % susceptible count Pasteurella sp. % susceptible P. multocida % susceptible Proteus sp. % susceptible Proteus Indole-negative % susceptible Pseudomonas sp. % susceptible count P. aeruginosa % susceptible count Serratia sp. % susceptible S. marcescens % susceptible count Corynebacterium sp. % susceptible count Staphylococcus sp. % susceptible count S. aureus % susceptible count

19 Count Staphylococcus coagulase-positive % susceptible count Staphylococcus coagulase-negative % susceptible count Streptococcus sp. % susceptible count S. canis % susceptible count Enterococcus sp. % susceptible E. faecalis % susceptible Figure 5.1 Distribution of Bacterial Isolates from Equine Uterine Samples Equine Uterine Isolates Bacteria 16

20 Percent Susceptibiltiy (%) Figure 5.2 Antibiotic Susceptibility of Bacterial Isolates from Equine Uterine Samples Equine Uterine Isolate Antibiotic Susceptibilty E. coli Streptococcus sp. S. equi spp zooepidemicus ENRO GENT PENG RFPN TETR TMSZ CTIO Antibiotic 17

21 Figure 5.3 Antibiotic Susceptibility of Bacterial Isolates from Equine Uterine Samples Horse Uterine Isolates ENRO GENT PENG RFPN TETR TMSZ CTIO Gram - coccobacillus % susceptibility count Acinetobacter sp. % susceptibility count E. coli % susceptibility count P. mirabilis % susceptibility count P. aeruginosa % susceptibility count P. oryzihabitans % susceptibility count Corynebacterium sp. % susceptibility count Staphylococcus coagulasepositive % susceptibility count Staphylococcus coagulasenegative % susceptibility count Streptococcus sp. % susceptibility count Streptococcus dysgalactiae % susceptibility count S. equi spp zooepidemicus % susceptibility count

22 Count Figure 6.1 Distribution of Bacterial Isolates from Equine Wound Samples 10 Equine Wound Isolates Etiology 19

23 Percent Suscepbitiliy (%) Figure 6.2 Antibiotic Susceptibility of Bacterial Isolates from Equine Wound Samples Equine Wound Isolate Antibiotic Susceptibility Staphylococcus coagulase-negative S. equi spp zooepidemicus ENRO GENT PENG RFPN TETR TMSZ CTIO Antibiotic 20

24 Figure 6.3 Antibiotic Susceptibility of Bacterial Isolates from Equine Wound Samples Horse Wound Isolates ENRO GENT PENG RFPN TETR TMSZ CTIO Gram - coccobacillus % susceptible count Citrobacter sp. % susceptible count E. coli % susceptible count K. pneumoniae % susceptible count Pasteurella sp. % susceptible count P. aeruginosa % susceptible count Corynebacterium sp. % susceptible count C. pseudotuberculosis % susceptible count S. aureus % susceptible count Staphylococcus coagulasepositive % susceptible count Staphylococcus coagulasenegative % susceptible count Streptococcus sp. % susceptible count S. equi spp zooepidemicus % susceptible count S. equi % susceptible count

25 Count Figure 7.1 Distribution of Bacterial Isolates from Feline Urine Samples Feline Urine Isolates 0 Escherichia coli Enterococcus faecium Proteus mirabilis Staphylococcus coag-negative Staphylococcus sp. Streptococcus sp. Bacteria 22

26 Percent Susceptibility (%) Figure 7.2 Antibiotic Susceptibility of Bacterial Isolates from Feline Urine Samples Feline Urine Isolate Antibiotic Susceptibility E. coli Streptococcus sp. Antibiotic Figure 7.3 Antibiotic Susceptibility of Bacterial Isolates from Feline Urine Samples Feline Urine Isolates AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ E. coli % susceptible count P. mirabilis % susceptible Staphylococcus coagulase-negative % susceptible count Streptococcus sp. % susceptible count E. faecium % susceptible

27 Count Figure 8.1 Distribution of Bacterial Isolates from Feline Wound Samples 6 Feline Wound Isolates Bacteria 24

28 Figure 8.2 Antibiotic Susceptibility of Bacterial Isolates from Feline Wound Samples Feline Wound Isolates AMIK AMCL AMPI CZOL VEC CFOX CEFD CEPH CLOR CLND ENRO GENT MARB PENG TETR TMSZ E. coli % susceptibility Pasteurella sp. % susceptibility P. pneumotropica/mannheimia % susceptibility Corynebacterium sp. % susceptibility C. argentoratense % susceptibility S. aureus % susceptibility Staphylococcus coagulasepositive % susceptibility count Staphylococcus coagulasenegative % susceptibility count Streptococcus sp. % susceptibility count S. canis % susceptibility Streptococcus group G % susceptibility count

29 Figure 9 Antibiotic Panels Used in Species-Specific Antibiotic Susceptibility Testing Amikacin (AMIK) Amoxicillin-clavulanate (AMCL) Ampicillin (AMPI) Cefazolin (CZOL) Cefovecin (VEC) Cefoxitin (CFOX) Cefpodoxime (CEFD) Ceftiofur (CTIO) Cephalothin (CEPH) Chloramphenicol (CLOR) Clindamycin (CLND) Enrofloxacin (ENRO) Gentamicin (GENT) Marbofloxacin (MARB) Penicillin G (PENG) Rifampin (RFPN) Tetracycline (TETR) Trimethoprim-sulfamethoxazole (TMSZ) Equine Companion Animal (Canine/Feline) Gram + Gram - 26

30 DISCUSSION In total, there were 690 bacteria isolated from canine samples, 210 isolated from equine samples, and 105 isolated from feline samples submitted to the laboratory from January 1 st, 2015 to December 31 st, Antibiograms were generated for any specimen type that had at least 30 samples submitted to the laboratory. Canine antibiograms were generated for urine isolates (n=125), ear isolates (n=92), wound isolates (n=63), and skin isolates (n=30). Equine antibiograms were generated for uterine isolates (n=44) and wound isolates (n=41). Feline sample submissions were far fewer than canine and equine submissions, so no specimen type exceeded the n=30 criteria for generating an antibiogram. Therefore, an antibiogram was generated for the two most common specimen types, urine isolates (n=16) and wound isolates (n=17). Canine Urine Samples A total of 125 bacterial isolates were obtained from canine urine samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and Collection methods of these urine samples include cystocentesis and free-catch. These 125 isolates included 18 bacterial etiologies. The most common isolates included Escherichia coli (n=51) and Staphylococcus coagulase-negative (n=22), as shown in Figure 1.1. The antibiotic susceptibility of the most common isolates is shown in Figure 1.3. Overall, the E. coli isolates were most sensitive to amikacin (n=49, 92% susceptible), chloramphenicol (n=51, 92% susceptible), gentamicin (n=49, 88% susceptible), and trimethoprim-sulfamethoxazole (n=50, 88% susceptible). The Staphylococcus coagulase-negative isolates were most sensitive to amoxicillin-clavulanate (n=22, 82% susceptible), amikacin (n=22, 77% susceptible), and gentamicin (n=22, 77% susceptible). Canine Ear Samples A total of 92 bacterial isolates were obtained from canine ear samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and These 92 isolates included 17 bacterial etiologies. The most common isolates included Pseudomonas aeruginosa (n=19) and Staphylococcus coagulase-negative (n=16), as shown in Figure 2.1. The antibiotic susceptibility of the most common isolates is shown in Figure 2.3. Overall, the P. aeruginosa isolates were most sensitive to amikacin (n=19, 74% susceptible). The P. aeruginosa isolates were 0% susceptible to 8 out of the 12 tested antibiotics. The Staphylococcus coagulase-negative isolates were most susceptible to cephalexin (n=16, 88% susceptible) and amoxicillinclavulanate (n=16, 81% susceptible). Canine Skin Samples A total of 30 bacterial isolates were obtained from canine skin samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and These 30 isolates included 11 bacterial etiologies. The most common isolates included Staphylococcus coagulase-negative 27

31 (n=10) and Staphylococcus coagulase-positive (n=5), as shown in Figure 3.1. The antibiotic susceptibility of the most common isolates is shown in Figure 3.3. Overall, the Staphylococcus coagulase-negative isolates were most sensitive to marbofloxacin (n=10, 60% susceptible), amikacin (n=10, 60% susceptible), amoxicillin-clavulanate (n=10, 60% susceptible), and cephalothin (n=10, 60% susceptible). The Staphylococcus coagulase-positive isolates were most susceptible to marbofloxacin (n=5, 80% susceptible), amikacin (n=5, 80% susceptible), gentamicin (n=5, 80% susceptible), and cephalothin (n=5, 80% susceptible). Canine Wound Samples A total of 63 bacterial isolates were obtained from canine wound samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and These 63 isolates included 22 bacterial etiologies. The most common isolates included E. coli (n=9), Staphylococcus coagulase-negative (n=9), and Streptococcus sp. (n=6), as shown in Figure 4.1. The antibiotic susceptibility of the most common isolates is shown in Figure 4.3. Overall, the E. coli isolates were most susceptible to amikacin (n=9, 89% susceptible), cefoxitin (n=9, 89% susceptible), chloramphenicol (n=9, 89% susceptible), and trimethoprim-sulfamethoxazole (n=9, 100% susceptible). The Staphylococcus coagulase-negative isolates were most susceptible to amikacin (n=9, 78% susceptible) and amoxicillin-clavulanate (n=9, 78% susceptible). The Streptococcus sp. Isolates were most susceptible to amoxicillin-clavulanate (n=6, 67% susceptible), cefpodoxime (n=6, 67% susceptible), cephalothin (n=6, 67% susceptible), and tetracycline (n=6, 67% susceptible). Equine Uterine Samples A total of 44 bacterial isolates were obtained from equine uterine samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and These 44 isolates included 13 bacterial etiologies. The most common isolates included S. equi spp zooepidemicus (n=12) and E. coli (n=10), as shown in Figure 5.1. The antibiotic susceptibility of the most common isolates is shown in Figure 5.3. Overall, the S. equi isolates were most sensitive to penicillin G (n=12, 92% susceptible) and ceftiofur (n=11, 91% susceptible). The E. coli isolates were most sensitive to tetracycline (n=10, 100% susceptible), enrofloxacin (n=10, 90% susceptible), and gentamicin (n=10, 90% susceptible). Equine Wound Samples A total of 41 bacterial isolates were obtained from equine wound samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and These 41 isolates included 15 bacterial etiologies. The most common isolates included Staphylococcus coagulase-negative (n=6) and S. equi spp zooepidemicus (n=8), as shown in Figure 6.1. The antibiotic susceptibility of the most common isolates is shown in Figure 6.3. Overall, the Staphylococcus coagulasenegative isolates were most sensitive to tetracycline (n=6, 83 % susceptible), penicillin G (n=6, 28

32 83% susceptible), and rifampin (n=5, 80% susceptible). The S. equi spp zooepidemicus isolates were most sensitive to penicillin G (n=8, 100% susceptible) and ceftiofur (n=8, 75% susceptible). Feline Urine Samples A total of 16 bacterial isolates were obtained from feline urine samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and Collection methods of these urine samples include cystocentesis and free-catch. These 16 isolates included 5 bacterial etiologies. The most common isolates included E. coli (n=7) and Streptococcus sp. (n=5), as shown in Figure 7.1. The antibiotic susceptibility of the most common isolates is shown in Figure 7.3. Overall, the E. coli isolates were most sensitive to chloramphenicol (n=7, 100% susceptible), marbofloxacin (n=7, 100% susceptible), and trimethoprim-sulfamethoxazole (n=7, 100%). The Streptococcus sp. Isolates were most sensitive to amoxicillin-clavulanate (n=5, 40% susceptible) and cephatlothin (n=5, 40% susceptible). Feline Wound Samples A total of 17 bacterial isolates were obtained from feline wound samples submitted to the laboratory for antibiotic sensitivity testing during 2015 and These 17 isolates included 11 bacterial etiologies. The most common isolates included Streptococcus sp. (n=4) and Staphylococcus coagulase-negative (n=3), as shown in Figure 8.1. Overall, the Streptococcus sp. Isolates were most sensitive to cephalothin (n=4, 100% susceptible) and amoxicillin-clavulanate (n=4, 75% susceptible). The Staphylococcus coagulase-negative isolates were most sensitive to amikacin (n=3, 67% susceptible). CONSIDERATIONS With all submitted samples, it is important to note that the integrity of the sample can in no way be verified by the Arizona Veterinary Diagnostic Laboratory. Although a certain strain of bacteria may be isolated by the lab from a wound sample, it is possible that this strain was simply a contaminant as a result of the sample collection by the veterinary personnel at the clinic where the sample was taken. For instance, the wound samples are spread about a wide array of bacterial species. However, it is difficult to discern whether or not these microbes are truly contributing to the wound infection or if they are simply a contaminant. It is important for clinicians to keep this in mind when reviewing this data as a resource. Once challenge of this project was categorizing the sample as one of the predefined specimen types used in this project (e.g. wound vs. skin culture). The most accurate assignment of the specimen type would require actually examining the patient. However, due to the nature of a diagnostic laboratory, this was not possible. Instead, an assignment of specimen type was performed using this information in the sheet that is submitted along with the specimen. 29

33 One problem with this is project is the low number of samples from which this data was derived. Although there is a large number of total isolates for each of the three species, once divided by bacterial isolate and specimen type within a species, the sample sizes decrease pointedly. Limited information can be gleaned from the antibiotic susceptibility of bacterial isolates once the sample size decreases. This is especially brings into question the validity of the numbers describing the antibiotic sensitivity of the feline urine and wound samples. As previously stated, this information can potentially be used as a resource for local veterinarians. However, ordering a culture and sensitivity at a diagnostic laboratory for the specific infection being treated is the best option to ensure that an appropriate antibiotic is used. In addition, many other things are factored into the decision of which antibiotic to use for a patient (including cost, contraindications, etc.). It would be necessary to select an antibiotic on a case by case basis with all factors considered to make the appropriate choice for that specific patient. Future Directions Because antibiotic sensitivity can change over time with the development of antibiotic resistance, it would be important to track antibiotic susceptibility changes over time. A static picture of the antibiotic sensitivity can only provide so much information. Tracking changes over time gives a much more realistic picture of how local bacterial strains are evolving and if they are indeed developing antibiotic resistance. REFERENCES 1 Chen, Qin. "Antibiotics." Introduction to Pharmacology. Lecture. 2 Landers, Timothy F., Bevin Cohen, Thomas E. Wittum, and Elaine L. Larson. "A Review of Antibiotic Use in Food Animals: Perspective, Policy, and Potential." Public Health Reports (2012): US National Library of Medicine. Web. 3 Ventola, Lee. "The Antibiotic Resistance Crisis." Pharmacy and Therapeutics 40.4 (2015): US National Library of Medicine. Web 30

34 APPENDIX Table 1 - Distribution of Bacterial Isolates from Equine Samples Bacteria abscess anal brain draining tract ear culture eye culture intestine liver lung lymph node mammary gland nasal culture oral swab skin culture stool synovial fluid tendon urine uterine culture wound placenta TOTAL Aeromonas salmonicida 1 1 Acinetobacter sp. 1 1 B. cereus Bacillus sp. 1 1 Bacteroides sp. 1 1 Citrobacter sp. 1 1 Corynebacterium pseudotuberculosis Corynebacterium sp Cronobacter sakazakii 1 1 E. coli Enterobacter sp Enterococcus sp. 1 1 gram negative coccobacillus gram negative rod 1 1 gram positive rod 1 1 Klebsiella pneuomoniae 1 1 Klebsiella sp. 1 1 Pasteurella sp. 1 1 Proteus mirabilis 2 2 Pseudomonas aeruginosa Pseudomonas fluorescens/putida 1 1 Pseudomonas oryzihabitans 1 1 Salmonella sp. 1 1 Staphylococcus aureus Staphylococcus coag-negative Staphylococcus coag-positive Staphylococcus sp Strep group A beta-hemolytic 1 1 Streptococcus dysgalactiae 1 1 Streptococcus equi

35 Streptococcus equisimilis 1 1 Streptococcus sp Streptococcus zooepidemicus TOTAL Table 2 - Distribution of Bacterial Isolates from Feline Samples draining tract ear culture intestine liver lung lymph node nasal culture skin culture spleen urine wound TOTAL Bacteria abscess bladder pancreas Cellulomonas spp/microbacterium spp 1 1 Corynebacterium argentoratense 1 1 Corynebacterium sp Enterobacter cloacae 1 1 Escherichia coli Enterococcus faecium Enterococcus sp. 1 1 Klebsiella pneumoniae 1 1 Micrococcus sp Pasteurella multocida Pasteurella pneumotropica/haemolytica 1 1 Pasteurella sp Proteus mirabilis 2 2 Pseudomonas aeruginosa 1 1 Staphylococcus aureus 1 1 Staphylococcus coagnegative Staphylococcus coagpositive Staphylococcus sp Streptococcus canis Streptococcus sp Serratia marcescens 1 1 TOTAL Table 3 - Distribution of Bacterial Isolates from Canine Samples 32

36 abdo men absc ess anal cult ure blad der blad der ston e bo ne br ain drai ning tract ear cult ure eye cult ure intes tine kid ney liv er Bacteria Acinetobacte r baumannii 1 1 Acinetobacte r sp Aeromonas sp. 1 1 Bacillus cereus Cellulomonas spp/microba cterium spp 1 1 Citrobacter freundii 1 1 Corynebacter ium propinquum 1 1 Corynebacter ium sp Corynebacter ium striatum E. coli E. faecium 1 1 Enterobacter cloacae Enterobacter sp Enterococcus faecalis Enterococcus sp Gemella morbillorum 1 1 Gram negative rods Gram NF 2 2 Klebsiella pneumoniae 1 1 Klebsiella sp Ochrobactru m anthropi 1 1 Pasteurella dagmatis 1 1 Pasteurella multocida Pasteurella sp Proteus Indole-neg lu ng lym ph no de m as s mu scle nas al cult ure perito neal fluid skin cult ure spl een st oo l syno vial fluid thr oat to ot h uri ne uter ine cult ure wo und TO TAL

37 Proteus mirabilis Proteus sp Providencia alcalifaciens/ rustigianii 1 1 Pseudomona s aeuriginosa Pseudomona s fluorescens/ putida Pseudomona s sp Raoultella terrigena Salmonella sp. 1 1 Serratia marcescens 1 1 Serratia sp Staphylococc us aureus Staphylococc us coagnegative Staphylococc us coagpositive Staphylococc us hominis 1 1 Staphylococc us sp Streptococcu s agalactiae 1 1 Streptococcu s canis Streptococcu s dysgalactiae spp. equisim 1 1 Streptococcu s sp TOTAL

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