High prevalence of antimicrobial resistance and multidrug resistance among bacterial isolates from diseased pets: Retrospective laboratory data (2015–2017)

Nurul Asyiqin Haulisah; Latiffah Hassan; Saleh Mohammed Jajere; Nur Indah Ahmad; Siti Khairani Bejo

doi:10.1371/journal.pone.0277664

. 2022 Dec 7;17(12):e0277664. doi: 10.1371/journal.pone.0277664

High prevalence of antimicrobial resistance and multidrug resistance among bacterial isolates from diseased pets: Retrospective laboratory data (2015–2017)

Nurul Asyiqin Haulisah ¹, Latiffah Hassan ^1,^*, Saleh Mohammed Jajere ¹, Nur Indah Ahmad ¹, Siti Khairani Bejo ¹

Editor: Emmanuel Serrano²

PMCID: PMC9728933 PMID: 36477195

Abstract

Laboratory surveillance and the monitoring of antimicrobial resistance (AMR) trends and patterns among local isolates have been highly effective in providing comprehensive information for public health decision-making. A total of 396 cases along with 449 specimens were received for antibiotic susceptibility testing at a public university veterinary diagnostic laboratory in Malaysia between 2015 and 2017. Escherichia coli was the most frequently isolated (n = 101, 13%) bacteria, followed by Staphylococcus pseudintermedius (n = 97, 12%) and Streptococcus canis (n = 62, 8%). In cats, S. pseudintermedius isolates were highly resistant to azithromycin (90%), while the E. coli isolates were highly resistant to doxycycline (90%), tetracycline (81%), and cephalexin (75%). About 55% of S. pseudintermedius and 82% of E. coli were multi-drug resistant (MDR). In dogs, S. intermedius isolates were highly resistant to aminoglycosides neomycin (90.9%) and gentamicin (84.6%), and tetracycline (75%). Whereas the E. coli isolates were highly resistant to cephalexin (82.1%) and amoxicillin/clavulanic acid (76.5%). MDR was observed in 60% of S. intermedius and 72% of E. coli from dogs. Generally, the bacterial isolates from cats demonstrated higher levels of resistance to multiple antibiotics compared to those from dogs.

Introduction

Antimicrobial resistance (AMR) among bacterial isolates from pets has not received as much attention as AMR among bacteria in livestock. However, AMR among bacterial isolates such as MRSA and MDR E. coli and Klebsiella pneumoniae in pets is an emerging issue of veterinary and public health significance [1]. In addition to AMR complicating the treatment of sick pets, close relationships between pets and their human counterparts can result in the transmission of the resistant pathogens between the two [2, 3]. The transmission of antibiotic-resistant bacteria such as the zoonotic transmission of opportunistic pathogens like Staphylococcus spp. between dogs and their owners have been reported in many studies [4, 5]. In fact, several studies have reported that the AMR level is higher among animals living in close association with humans than the animals residing in remote areas [6]. Studies have found that pets may acquire resistant pathogens from their owners [7–9].

In the past decade, the use of antibiotics in animals reared for meat has been broadly scrutinized [10, 11]. Multiple reports have also established that the volume and frequency of antibiotics used in livestock production settings are reducing the effectiveness of the antibiotics when used for medicinal purposes in humans [12]. In fact, it is among the major drivers of the increasing level of AMR among bacterial pathogens [13, 14]. In contrast, there have been lesser attention paid to the use of antibiotics in pets and especially, the antibiotic resistance among bacteria from pets. Pets are normally exposed to antibiotics when they are treated for bacterial infections [15], or prevented from secondary bacterial infection during episodes of viral infections [16]. Antibiotic prescriptions often include critically important antibiotic groups used in human medicine including the heavy usage of broad-spectrum agents such as fluoroquinolones, cephalosporins, and penicillins [17]. These antibiotics are categorized as veterinary critically important antibiotics by the OIE [18] as well as critically important for human medicine by the WHO [19]. Veterinarians are often inclined to use broad-spectrum antibiotics as the first-line treatment for bacterial infection due to its convenience [20, 21] and as blanket coverage against a broad range of bacterial diseases. However, such usage increases selective pressure, leading to the development of multidrug resistance in bacteria such as Escherichia coli, Pseudomonas aeruginosa, and other commensal bacteria in pets [22–24].

Sporadic reports have suggested an increasing level of resistance in important pathogens in cats and dogs [25] and this situation escalates the complexity of treating bacterial infections such as urinary tract infections and cystitis in these species [26–28]. The findings from this study will highlight the significance of AMR among clinically important bacterial pathogens in small animal medicine. In line with Malaysia Strategic Action Plan for AMR (MyAP-AMR) [29] and Global Action Plan of AMR, this study aims to describe the antimicrobial resistance patterns of clinically important bacterial pathogens from diagnostic cases in pets. This study will also determine the differences in resistance profiles between isolates recovered from diseased cats and dogs between 2015 and 2017.

Material and methods

Source of data

The design of this study has been described in Haulisah et al., [30]. The data originated from the veterinary diagnostic cases that were received from various veterinary health premises and animal facilities in Peninsular Malaysia by the accredited Bacteriology Laboratory, Faculty of Veterinary Medicine of Universiti Putra Malaysia (UPM) Serdang, Selangor. Diagnostic reports (paper format) of cases from 1 January 2015 to 31 December 2017 were compiled and transferred into WHONET (vers 5.6, Boston, MA). Relevant data compiled included information concerning animal species, clinical history, sex, type of specimens (urine, wound swab, lavage fluid, etc.), clinical signs, isolated bacteria, and findings from antibiotic susceptibility testing (AST).

The laboratory performed culture and identification of received samples using standard microbiological procedures [31]. The antimicrobial sensitivity was performed using the Kirby Bauer’s disc diffusion on Mueller Hinton Agar (MHA) method following the Clinical Laboratory Standards Institute (CLSI) guidelines [32]. The AST data was grouped into three categories: Resistant (R), Intermediate (I), and Susceptible (S) using the established clinical breakpoints. The antimicrobial agent tested varied depending on the request of the clinician, type of the organism, and the availability of the antimicrobial agents.

Data received from the 396 cases by the laboratory were entered into Excel 2007 (Microsoft Office, 2007) and then transferred into WHONET 5.6 [33]. Data related to cats and dogs were analyzed separately. A total of 780 isolates were recovered from the various clinical samples of dogs and cats over a period of three years (2015–2017).

Data analysis

Descriptive data analysis was performed in WHONET 5.6 as described in WHO [34, 35]. Trends and patterns of tested antibiotics and the multidrug resistance (MDR) levels among the clinical isolates were analyzed based on the species of the pets followed by interspecies comparison. The difference in the level of resistance based on the antimicrobial agents for the 3-year study period was tested using the Chi-square test at 95% confidence intervals using SPSS 22 (IBM, Armonk, NY: IBM Corp.) at α = 0.05. Fisher’s exact test was applied when the expected numbers per cell were small. For the purpose of this analysis, the isolates categorized as ‘intermediate’ and ‘resistant’ were grouped as ‘non-susceptible’. In addition, an isolate was marked as ‘multi-drug resistant’ if it were resistant to at least one agent in three or more classes of antibiotics [36].

Results

Descriptive analysis of samples

Between 2015 and 2017, 396 cases with accompanying 449 specimens were received by the laboratory for antibiotic susceptibility testing (AST) (cats n = 271, 68.4% and dogs n = 125, 31.6%). A total of 780 isolates were obtained out of which more than half were recovered from cats (n = 467, 59.9%) and the rest from dogs (n = 313, 40.1%).

A total of 65 bacterial species were identified from the specimens. The most common species were Escherichia coli (n = 101, 13%), followed by Staphylococcus pseudintermedius (n = 97, 12%), and Streptococcus canis (n = 62, 8%). The majority of Enterococcus spp. were Enterococcus faecalis (n = 48, 72.7%) and the remaining 18 were non-faecalis Enterococcus spp. (Fig 1).

Fig 1 — Numbers inside brackets ‘()’ indicate the total number of bacterial isolates.

Antimicrobial resistance of clinical isolates from cats

A total of 289 clinical samples were received (Table 1) from which 467 isolates were recovered. Staphylococcus pseudintermedius was the most common bacteria from wounds/abscesses (61.2%) and ear infections (13.4%). Overall, S. pseudintermedius (n = 67, 14.3%), E. coli (n = 65, 13.9%), S. canis (n = 44, 9.4%), and K. pneumoniae (n = 37, 7.9%) were the most frequently isolated. Klebsiella pneumoniae was found to be more commonly isolated from urine (51.4%) while Escherichia coli, Staphylococcus pseudintermedius, and Streptococcus canis were most commonly isolated from wounds/abscess (Table 1). More than 75.8% (354/467) of the bacteria isolated were MDR out of which 20.6% (96/467) were resistant to one or two antibiotic classes and only 3.6% (17/467) were susceptible to all tested antibiotics.

Table 1. Species of bacteria isolated from diagnostic samples from diseased cats received by the Bacteriology Laboratory between 2015 and 2017.

Samples	N	%Staphylococcus pseudintermedius (n = 67)	%Escherichia coli (n = 65)	%Streptococcus canis (n = 44)	%Klebsiella pneumoniae (n = 37)	% Others^* (n = 254)
Wounds/abscess	157	41 (61.2%)	34 (52.3%)	31 (70.5%)	11 (29.7%)	148 (58.3%)
Ear	24	9 (13.4%)	4 (6.2%)	5 (11.4%)	1 (2.7%)	24 (9.4%)
Urinary tract	60	6 (9%)	16 (24.6%)	1 (2.3%)	19 (51.4%)	44 (17.3%)
Reproductive	11	3 (4.5)	5 (7.7%)	1 (2.3%)	0	6 (2.4%)
Post-mortem	9	1 (1.5%)	0	3 (6.8%)	5 (13.5%)	5 (2%)
Feces	5	1 (1.5%)	5 (7.7%)	0	1 (2.7%)	4 (1.6%)
Others	23	6 (9%)	1 (1.5%)	3 (6.8%)	0	23 (9.1%)
Total	289	67 (100%)	65 (100%)	44 (100%)	37 (100%)	254 (100%)

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N- Total number of clinical samples; n- Total number of bacterial isolates

*Others include blood, respiratory and eye infections

Antibiogram based on species of bacteria isolated from cats

Antibiogram of the bacteria isolated is presented in Figs 2–5. The MDR levels for the selected bacteria for 2015–2017 are shown in Fig 6.

Fig 2 — R–resistance; I-intermediate; S–susceptible; AMC–amoxicillin/clavulanic acid; AMX–amoxicillin; AZM–azithromycin; LEX–cephalexin; GEN–gentamicin; ENX–enrofloxacin; MBX–marbofloxacin; TET–tetracycline; SXT–trimethoprim-sulfamethoxazole. Numbers inside brackets ‘()’ indicate the total number of tested isolates for each antibiotic.

Fig 5 — R–resistance; I-intermediate; S–susceptible; AMC–amoxicillin/clavulanic acid; LEX–cephalexin; GEN–gentamicin; CRO–ceftriaxone; ENX–enrofloxacin; MBX–marbofloxacin; TET–tetracycline; SXT–trimethoprim-sulfamethoxazole. Numbers inside brackets ‘()’ indicate the total number of tested isolates for each antibiotic.

Fig 6 — Numbers inside brackets ‘()’ indicate the number of isolates detected; those on bars indicate percentage per organism; Non-MDR–Resistant to 1 or 2 classes; MDR–multi-drug-resistant, resistant to 3 or more classes.

Staphylococcus pseudintermedius

Fig 2 shows that the highest percentage of resistance was against azithromycin (90%; 95% CI = 54.1–99.5), followed by trimethoprim/sulfamethoxazole (57.1%; 95% CI = 29.6–81.2), and amoxicillin (53.3%; 95% CI = 27.4–77.7). There was no significant change in resistance trends for all tested antibiotics. More than 40.3% (27/67) of the S. pseudintermedius were resistant to multiple classes of antibiotics (MDR) (Fig 6).

Escherichia coli

The proportion of E. coli isolates resistant to doxycycline was 90% (95% CI = 54.1–99.5), 81% to tetracycline (95% CI = 57.5–93.7), and 75% to cephalexin (95% CI = 60.1–85.9) (Fig 3). There was no significant change in resistance level over the three-year study period. MDR (Fig 6) was observed among 70.8% (46/65) of E. coli isolates.

Fig 3 — R–resistance; I-intermediate; S–susceptible; AMC–amoxicillin/clavulanic acid; LEX–cephalexin; GEN–gentamicin; CRO–ceftriaxone; DOX–doxycycline; ENX–enrofloxacin; MBX–marbofloxacin; TET–tetracycline; SXT–trimethoprim-sulfamethoxazole. Numbers inside brackets ‘()’ indicate the total number of tested isolates for each antibiotic.

Streptococcus canis

Fig 4 shows that the resistance levels were high for gentamicin (66.7%; 95% CI = 35.5–88.7) and enrofloxacin (58.8%; 95% CI = 40.8–74.9). A significant increase in isolates grouped as ‘intermediate’ was observed for amoxicillin/clavulanic acid (p = 0.000, from 13.3% in 2015 to 22.2% in 2017). However, S. canis remained highly susceptible (90.7%) to amoxicillin/clavulanic acid over the three years. The MDR of S. canis (Fig 6) was relatively low at 9.1% (4/44).

Klebsiella pneumoniae

It was found that K. pneumoniae isolates were highly resistant to fluoroquinolones marbofloxacin (87.5%; 95% CI = 70.1–95.9), enrofloxacin (82.1; 95% CI = 62.4–93.2), and amoxicillin/clavulanic acid (81.1%; 95% CI = 64.3–91.5) (Fig 5). No significant change was observed in the resistance trends for all the tested antimicrobial agents over the three years. MDR was found in 86.5% of K. pneumoniae isolates from cats (86.5%, 32/37). None of the isolates was susceptible to all the classes of tested antimicrobial agents (Fig 6).

Antimicrobial resistance patterns of clinical isolates from dogs

Between 2015 and 2017, 160 clinical samples were analyzed from a total of 125 cases (Table 2). From these samples, 313 isolates were recovered. Staphylococcus intermedius (n = 37, 11.8%), Escherichia coli (n = 36, 11.5%), Proteus mirabilis (n = 31, 9.9%), and Staphylococcus pseudintermedius (n = 30, 9.58%) were the most frequently isolated bacterial species (Table 2). MDR was identified among 71.6% (224 /313) of the isolated bacteria.

Table 2. Species of bacteria isolated from diagnostic samples from diseased dogs received by the Bacteriology Laboratory between 2015 and 2017.

Samples	N	%Staphylococcus intermedius (n = 37)	%Escherichia coli (n = 36)	%Proteus mirabilis (n = 31)	%Staphylococcus pseudintermedius (n = 30)	%Others^* (n = 179)
Wounds/abscess	55	20 (54.1%)	15 (41.7%)	8 (25.8%)	8 (26.7%)	102 (57%)
Ear infection	45	13 (35.1%)	2 (5.6%)	14 (45.2%)	13 (43.3%)	47 (26.3%)
Urinary tract	36	2 (5.4%)	10 (27.8%)	8 (25.8%)	7 (23.3%)	15 (8.4%)
Reproductive	14	0	9 (25%)	0	0	5 (2.8%)
Post-mortem	2	0	0	0	0	2 (1.1%)
Others	8	2 (5.4%)	0	1 (3.2%)	2 (6.7%)	8 (4.5%)
Total	160	37 (100%)	36 (100%)	31 (100%)	30 (100%)	179 (100%)

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N- Total number of clinical samples; n- Total number of bacterial isolates.

*Others include blood, respiratory and eye infections

Antibiogram based on the species of bacteria isolated from dogs

Antibiogram of the bacteria isolated from dogs is presented in Figs 7–10. The MDR levels for the selected bacterial species (2015–2017) are shown in Fig 11.

Fig 7 — R–resistance; I-intermediate; S–susceptible; AMC–amoxicillin/clavulanic acid; LEX–cephalexin; GEN–gentamicin; ENX–enrofloxacin; MBX–marbofloxacin; NEO-neomycin; TET–tetracycline. Numbers inside brackets ‘()’ indicate the total number of tested isolates for each antibiotic.

Fig 10 — R–resistance; I-intermediate; S–susceptible; AMC–amoxicillin/clavulanic acid; LEX–cephalexin; ENX–enrofloxacin; MBX–marbofloxacin; TET–tetracycline. Numbers inside brackets ‘()’ indicate the total number of tested isolates for each antibiotic.

Fig 11 — Numbers inside brackets ‘()’ indicate number of isolates detected; those on bars indicate percentages per organism; Non-MDR–Resistant to 1 or 2 classes; MDR–multi-drug resistant, resistant to 3 or more classes.

Staphylococcus intermedius

The AST results for S. intermedius are presented in Fig 7. The highest resistance level was against neomycin (90.9%; 95% CI = 57.1–99.5), gentamicin (84.6%; 95% CI = 53.6–97.3), and tetracycline (75%; 95% CI = 47.4–91.7). It was also noted that about 60% (22/37) of the S. intermedius isolates were MDR (Fig 11). The resistance trend for the bacteria did not change significantly over time (2015–2017).

Escherichia coli

Fig 8 depicts the AMR levels of E. coli (2015–2017). The resistance was the highest for cephalexin (82.1%; 95% CI = 62.4–93.2) and amoxicillin/clavulanic acid (76.5%; 95% CI = 58.5–88.6). The resistance trend for E. coli did not change considerably over the study period. It was also noted that the proportion of MDR (Fig 11) among E. coli was 72.2% (26/36).

Proteus mirabilis

The frequency of AMR of P. mirabilis to all the tested antimicrobial agents (2015–2017) is presented in Fig 9. P. mirabilis isolates were completely resistant to tetracycline (100%; 95% CI = 59.8–100), followed by cephalexin (79.2%; 95% CI = 57.3–92.1), and trimethoprim/sulfamethoxazole (75%; 95% CI = 35.6–95.5). A significant decrease in resistance level was observed for marbofloxacin (p = 0.013, from 87.5% in 2015 to 36.4% in 2017). The MDR of P. mirabilis (Fig 11) was 51.6% (16/31).

Staphylococcus pseudintermedius

The resistance level was highest for tetracycline at 54.5% (95% CI = 24.5–81.8) (Fig 10). A significantly decreased resistance level to cephalexin (from 53.9% in 2015 to 0% in 2017) and to tetracycline (from 100% in 2015 to 0% in 2017) was observed over the three-year study period. Forty percent (12/30) of the S. pseudintermedius isolates were MDR (Fig 11).

Differences between the profile of resistances of isolates from cats and dogs

Staphylococcus pseudintermedius and Escherichia coli were the most commonly encountered bacterial species from both cats and dogs. In addition, most antibiotic classes used to treat E. coli and S. pseudintermedius infections are shared between these two species. Comparison of the AMR profiles among S. pseudintermedius and E. coli isolates are presented in Tables 3 and 4 respectively.

Table 3. Difference between E. coli isolates from diseased cats and dogs between 2015 and 2017.

Antimicrobial agents	Cat		Dog
Antimicrobial agents	Non-susceptible % (95% CI)	p-value	Non-susceptible % (95% CI)
Amoxicillin/clavulanic acid	96.9 (89.2–99.6)	0.338	91.2 (76.3–98.1)
Marbofloxacin	64.1 (51.1–75.7)	0.222	76.7 (57.7–90.1)
Cephalexin	100 (92.6–100)	0.368	96.4 (81.7.-99.9)
Enrofloxacin	80 (65.4–90.4)	0.624	84.4 (67.2–94.7)
Tetracycline ^*	95.2 (76.2–99.9)	0.031	64.7 (38.3–85.8)
Trimethoprim/sulfamethoxazole	58.3 (27.7–84.8)	0.371	83.3 (51.6–97.9)
Ceftriaxone	42.9 (17.7–71.1)	NA	NA
Doxycycline	100 (69.2–100)	NA	NA
Gentamicin	90 (55.5–99.7)	NA	NA

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NA- Not analyzed (data with isolates less than 10 were not analyzed);

*Significant difference between cats and dogs, P < 0.05.

Table 4. Differences between S. pseudintermedius isolates from diseased cats and dogs between 2015 and 2017.

Antimicrobial agents	Cat		Dog
Antimicrobial agents	Non-susceptible % (95% CI)	p-value	Non-susceptible % (95% CI)
Amoxicillin/clavulanic acid	65.7 (53.1–76.8)	0.517	58.6 (38.9–76.5)
Marbofloxacin	76.6 (64.3–86.2)	0.668	72.4 (52.8–87.3)
Cephalexin	57.7 (42.2–72.3)	0.560	50 (27.2–72.8)
Enrofloxacin	83.6 (71.2–92.2)	0.544	77 (56.4–91)
Tetracycline	75 (47.6–92.7)	1.000	81.8 (48.2–97.7)
Trimethoprim/sulfamethoxazole	78.5 (49.2–95.3)	NA	NA
Gentamicin	73.9 (51.6–89.8)	NA	NA
Amoxicillin	66.6 (38.4–88.2)	NA	NA
Azithromycin	100 (69.2–100)	NA	NA

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NA- Not Analyzed (data with isolates less than 10 were not analyzed)

Escherichia coli

E. coli isolates from dogs showed high levels of non-susceptibility towards all the tested antimicrobial agents with higher levels to trimethoprim/sulfamethoxazole, amoxicillin/clavulanic acid, and cephalexin. In contrast, E. coli isolates from cats showed high proportions of non-susceptibility towards tetracycline (95.2%). Significant differences were observed between the E. coli isolates from cats and dogs to tetracycline (95.2% versus 64.7%) (Table 3). It was observed that the frequency of MDR E. coli isolates from cats and dogs were similar (70.8% versus 72.2%; χ² = 0.024, p = 0.877).

Staphylococcus pseudintermedius

The resistance patterns of S. pseudintermedius isolates to commonly used antimicrobial agents were similar between dogs and cats (Table 4). The frequency of MDR also shared similarities between S. pseudintermedius isolates from cats and dogs (40.3% versus 40%; χ² = 0.001, p = 1.000).

Discussion

AMR is an ongoing global public health challenge that negatively impacts animals, humans as well as environmental health. Data from veterinary diagnostic laboratories provide vital information about trends and patterns of AMR among disease-causing agents circulating in the local animal population. In this study, the analyses of the data supplies important snapshot information on the AMR situation to shape treatment regime and to guide policy on the use of antibiotics in pets [37–39], consequently prolonging the usefulness of commonly prescribed antibiotics.

Our previous study reported a very high AMR prevalence among major disease-causing bacteria in livestock [30]. In this study, we report that S. pseudintermedius, E. coli, S. intermedius, P. mirabilis, K. pneumoniae, and S. canis, which are the most common pathogens isolated from diseased cats and dogs (2015–2017), have comparatively high levels of resistance to commonly used antibiotics for therapy. The resistance pattern against antibiotics for these pathogens underscores increasing challenges in treating common infections in cats and dogs as these bacterial species have also been identified as most clinically relevant in pets elsewhere [40]. Unfortunately, there are very few local or regional AMR information on pathogens causing diseases in pets to enable a more geographically contextual discussion. Therefore comparisons were made based on other available literatures.

Antimicrobial resistance of clinical isolates from cats

Overall, the trend did not change significantly over the study period for all the antibiotics tested. The majority of the S. canis isolates remained sensitive to amoxicillin/clavulanic acid. However, the increasing level of S. canis isolates grouped as ‘intermediate’ for amoxicillin/clavulanic acid from 13.3% in 2015 to 22.2% in 2017 is a note of concern. The level of susceptibility to this antibiotic is markedly higher than observed in a study by Awosile et al., [41], which reported a very low level (0.6%) of resistance from samples received over a ten-year study period at the Diagnostic Services Bacteriology Laboratory, Canada [41]. Additionally, in the study conducted by Ludwig et al., [42] across Europe, AMR was reported at 4% to amoxicillin/clavulanic acid over the entire study period.

Fluoroquinolones enrofloxacin and marbofloxacin are specific formulations for veterinary use [43, 44]. Marbofloxacin, a broad-spectrum antibiotic, is a drug of choice for the exclusive treatment of chronic bacterial infections affecting the urinary and respiratory tracts as well as skin and ear infections [45]. We observed high levels of resistance to enrofloxacin and marbofloxacin for K. pneumoniae (>80%) and E. coli (>40%) isolates recovered from cats. These findings corroborate with other similar studies conducted around the world. For instance, Marques et al., [46] reported a 72% resistance level of K. pneumoniae isolates recovered from urine samples of diseased cats and dogs in Lisbon. Other researchers report a lower resistance level (39.3%) of E. coli isolates against enrofloxacin in Poland [22]. In contrast, lower resistance levels (range: 0–5%) were observed for Enterobacteriaceae against marbofloxacin from stray cats between 2017 and 2018 in South Korea [47]. The observed high resistance level against fluoroquinolones antibiotics is not surprising as they are frequently prescribed in veterinary production and clinical practice [48]. Our finding should provide evidence for precautionary actions from the veterinary authority and other sectors to better strategize its usage to ensure the antibiotic’s continuing efficacy. Moreover, the overuse of fluoroquinolones in the veterinary application has been linked to cross-resistance with other fluoroquinolones such as ciprofloxacin and norfloxacin used for human therapy [19]. These are listed as critically important antimicrobials for humans and are often used for treating human bacterial infections [19, 49].

High resistance levels for S. pseudintermedius isolates from cats were recorded against azithromycin (90%). Azithromycin is a broad-spectrum macrolide used for bacterial, rickettsial, and parasitic infections [50, 51] and has been used in both veterinary and human medicine [19]. The resistance to this antibiotic is not commonly reported in pet animals. However, multiple reports of high-level resistance of azithromycin in animals are available amongst pathogens of public health significance in livestock [52] and human-specific pathogens such as Salmonella typhi [53] and Neiserria [54]. The high level of resistance points to the over-prescription of azithromycin and therefore must be re-examined as the antibiotic is preferred for treatment against rickettsial and hemotropica parasites [55–57].

In Finland [37] and Australia [58], the resistance levels for gentamicin and trimethoprim/sulfamethoxazole (30.8%-44.8%) for S. pseudintermedius isolates from cats were slightly lower than the findings of this study for the two antibiotics (>50%). Antibiotic-resistant S. pseudintermedius is an emerging veterinary clinical pathogen with some reports highlighting its increasing level of multi-drug resistance [59]. Although the zoonotic transmission of S. pseudintermedius remains rare [60], a few reports have linked infection from cats to their owners [61, 62].

Antimicrobial resistance of clinical isolates from dogs

The resistance trends for cephalexin and tetracycline in S. pseudintermedius and marbofloxacin in P. mirabilis isolates from dogs significantly declined between 2015 and 2017. P. mirabilis isolates were highly resistant to tetracycline (100%) and cephalexin (79.2%) which is concordant with the findings documented in Beijing [63] and Granada [64] where the isolates from dogs were 100% and 61.7% resistant against tetracycline, respectively. Auwaerter [65] reported the high resistance to tetracycline and cephalosporins by P. mirabilis isolates from dogs to be a common finding. Our findings of 79.2% resistance against cephalexin are higher than that reported in Canada (48.9%) by Awosile et al., [41]. The frequency of prescription of this antibiotic in small animal clinics [66] has been linked to the increasing level of resistance worldwide. Our study shows that more than half of S. intermedius and S. pseudintermedius isolates were resistant against tetracycline and is thus consistent with the findings from Kalhoro et al., [67] in sick dogs in China. A lower resistance level (less than 30%) of tetracycline by S. pseudintermedius isolates was reported from healthy dogs in Canada [68] and Australia [69].

E. coli isolates showing higher resistance levels against cephalexin (82.1%) and amoxicillin/clavulanic acid (76.5%) recorded in this study are similar to those reported among ESBL-E. coli isolates against amoxicillin/clavulanic acid (86.8%) from dogs and cats at the Veterinary Diagnostic Laboratory, United States [70]. Similar findings were also documented from dogs in Canada [41], Europe [71], the United States [72], and New Zealand [73]. Furthermore, in the present study, the E. coli isolates from dogs show high resistance levels against enrofloxacin, marbofloxacin, tetracycline, and trimethoprim/sulfamethoxazole, thus signifying an impending difficulty of treating E. coli infection in local dogs.

Comparison of antimicrobial resistance of clinical isolates from dogs and cats

E. coli and S. pseudintermedius are regarded as an excellent sentinel for AMR in a wide range of companion animals and as part of the their normal microbiota [1, 74]. These opportunistic bacteria can cause a wide range of infections. Hence, they are suitable candidates for comparing resistance profiles between cats and dogs. Our study shows interspecies variation in resistance patterns to tetracycline for E. coli isolates. E. coli isolates originating from cats had significantly higher resistance levels than those from dogs, which is consistent with the report from Australia [75]. However, more research is needed to explain this finding.

When we compare our findings on E. coli isolates from pets for the purpose of this study to that from local diseased livestock [30], we found that the level of resistance to tetracycline is very similar to that from diseased ruminants (cattle and goat) but significantly lower compared to that from diseased non-ruminants (chicken and pig). Our finding supports the conjecture relating to the key role of the environment and frequency of antibiotic usage in the trends of AMR. The finding for tetracycline resistance of E. coli is similar to that of diseased ruminants in Malaysia [30] that are raised extensively or semi-intensively with limited usage of antibiotics. Non-ruminants have a significantly higher level of resistance to tetracycline [30] as this antibiotic is one of the most commonly used as feed additives in intensive farming systems [76, 77]. In contrast, tetracycline is used only for treatment for conditions such as eye infection and bacterial gastrointestinal infection in cats and dogs [78].

Multi-drug resistance of clinical isolates from dogs and cats

Several bacteria are shared between companion animals and humans and this creates opportunities for interspecies transmission of AMR-bacteria [1]. In the current study, isolates from diseased dogs and cats exhibited high levels of MDR with the majority of the isolates being resistant to 3–4 antimicrobial agents. For example, we reported a high frequency of MDR among E. coli isolates from diseased dogs (72.2%) and cats (70.8%). We found a similar level of MDR among E. coli isolates from diseased livestock (both ruminant and non-ruminants) in our previous study [30]. However, with the exception of a study in Poland [22], which reported a 66.8% MDR among E. coli isolates from sick pets, many reports documented lower MDR levels. In the northern part of Peninsular Malaysia by Shahaza et al., [79] reported MDR E. coli isolates in only 0.58% of E. coli isolated from pets. Similarly, in Portugal [39] and Canada [41], a relatively lower MDR level (range: 13%–32%) was found among clinical E. coli isolates from sick cats and dogs presented to the Veterinary Diagnostic Laboratory. The level of MDR of other pathogens such as S. pseudintermedius from dogs and cats (>40%) is similar to those reported from a convenient sample of dogs (47.5% MDR) in the USA [80] but lower than that reported in another local study on S. pseudintermedius (n = 23) isolates from stray and pet dogs and cats (100% MDR) [81]. In contrast, Australia [59], France [25], and the United Kingdom [82] reported MDR levels of between 4.7% and 20.7%. The variations in the MDR levels could reflect the choice or preferences of some antimicrobials used for the treatment of bacterial diseases in pets [83] and also on the frequency of antimicrobial usage in livestock production settings as well as in human medicine within a locality or geographic region [84].

Limitations of the study

The present study shares similar inherent biases as stated by Hayer, et al., [85] about the study limitations using veterinary diagnostic laboratory data. The data used for this study are laboratory reports generated from diagnostics cases; therefore, the findings may not represent the AMR situation in the general pet population in peninsular Malaysia and may not reflect the overall picture of AMR levels among bacteria in healthy pets. Additionally, the samples received by the lab were from diseased pets which may have been treated with antibiotics prior to sample collection, thereby altering the antibiogram profiles. Unfortunately, the histories regarding their previous antimicrobial therapy were mostly not available. In addition, the bacteria isolated could be a part of the normal flora or contaminants rather than the disease-causing agent. Finally, the panels of antibiotics used in the analyses were not consistent because they were dependent on several factors such as the request by the clinician, availability of antibiotics in the laboratory, and the type of organism isolated.

Conclusion

This study presents a snapshot of the AMR among important bacterial pathogens such as Staphylococci (S. pseudintermedius and S. intermedius), E. coli, K. pneumoniae, P. mirabilis, and S. canis recovered from diseased pets. A similar AMR pattern was observed for S. pseudintermedius and E. coli isolates recovered from sick cats and dogs, except for their resistance to tetracycline—where E. coli isolates from cats show higher AMR levels than those from dogs. The majority of the aforementioned bacterial isolates also demonstrated high levels of MDR, thereby undermining or complicating treatment options for bacterial infections in pets. Despite the limitation in inferencing the findings of this study to larger populations, the high MDR levels observed alludes to the growing challenges concerning the treatment of pets with common bacterial infections. The findings from this study provide important baseline measurements for the ongoing AMR surveillance and provide a foundation to better frame the antimicrobial stewardship efforts in pets.

Acknowledgments

We thank the technical staff of the Bacteriology Laboratory, Faculty of Veterinary Medicine, UPM Serdang, Malaysia for their time and for sharing knowledge from the inception to the end of this research project.

Data Availability

All relevant data are within the paper.

Funding Statement

This research project was part of a Master’s research study undertaken in the Faculty of Veterinary Medicine, Universiti Putra Malaysia, and was funded by the UPM Research Grant number GP – IPB/2019/9676500, awarded to LH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0277664.r001

Decision Letter 0

Emmanuel Serrano

18 Aug 2022

PONE-D-22-09971High Prevalence of Antimicrobial Resistance and Multidrug Resistance Among Bacterial Isolates from Diseased Pets: Retrospective Laboratory Data (2015-2017)PLOS ONE

Dear Dr. Hassan,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. As you will see, the referee asks for some details that should be adressed in a further version of your work. Along the same lines, I think it would be recomedable to include some information about the situation of AMR in wildlife (e.g., One Health,11,2020,100198) that is turning into a serious animal health issue.

Please submit your revised manuscript by Oct 02 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

**********

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PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: GENERAL COMMENTS

• Overall, this is an interesting and timely paper on the evidence on the emerging Antimicrobial Resistance in companion animals in Malaysia.

• That being said there are several areas for clarification and elaboration that would strengthen the study.

• Scope:

o Although the aim of the paper was to analyze a retrospective data between 2015 to 2017 among companion animals presented to veterinary hospital, a significant gap is the lack of inclusion of data between 2017- 2022 missing accurate information on the current picture of AMR in the target population.

o Given that the prevalence of AMR is highly likely to be low in household-based setting compared to hospital setting as the case here, the authors need to clarify why this pertinent data was excluded.

o Related to the veracity of the confounding factors in some circumstances, the reported prevalence may not be specific, hence the lower proportion of these than expected. To establish this as evidence, the authors might make a correlation between antimicrobial use (AMU) in companions animals vs AMR to identify pathways of the drivers of AMR in Malaysia. Comparison of AMR between different settings (hospital as the case here vs household would further strengthen the impact of the paper.

Abstract

• Rationale

o My concern is that the brief of the rationale and the existing gaps has NOT been be briefly described.

o The authors presented retrospective data retrieved between 2015 – 2017 and up to date data missing great proportion of the totality of the evidence after 2017 [5 years].

MATERIALS & METHODS

Source of the data

o The appended below sentence (see line 90-94) should be shifted to results section as it is not related to the methodology.

� Fig 1 shows the distribution and percentages of bacterial species isolated during the study period. Escherichia coli was the most common isolate for Gram-negative bacteria followed by Proteus mirabilis and Klebsiella, whereas for Gram-positive bacteria, Staphylococcus pseudintermedius was the most common isolate followed by Streptococcus canis and Staphylococcus intermedius.

o Please clarify the following sentence:

� ‘For the purpose of this analysis, the isolates categorized as ‘intermediate’ and ‘resistant’ were grouped as ‘non-susceptible’.

• RESULTS

o Please define the acronym used in the fig 2-11. Please apply this change throughout.

o In Table 1: samples [postmortem, reproductive, urinary tract], please specify the nature of sample, and type of the organs rather than categorizing them as system-based classification.

o Please add a footnote to the table 1 and introduce the [others], etc.

o Please write as Fig 2-5 in line 145 and Table 3, 4 in line 293

o Rectify the footnote of Table 4; [*NA- should be written NOT Analyzed rather than Not Included to avoid confusion(see line 317).

• DISCUSSION

o The discussion section, even though should NOT be sub structured, remains superficial and not country specific. Comparisons are often made at global scale rather than regional and national levels missing crucial information about the epidemiology of AMR in the context of current research in Malaysia and the wider Southeast Asia.

o The author (s) should also discuss the strength of their study and how their manuscript contribute to the literature and fit within the context of current research or practice.

o The author (s) should also discuss the limitation of their study of using admitted cases as these that will overestimate of the prevalence of AMR, thus the call for a nationwide AMR prevalence study.

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Abdinasir Yusuf Osman

**********

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PLoS One. 2022 Dec 7;17(12):e0277664. doi: 10.1371/journal.pone.0277664.r002

Author response to Decision Letter 0

13 Sep 2022

Title: High Prevalence of Antimicrobial Resistance and Multidrug Resistance among Bacterial Isolates from Diseased Pets: Retrospective Laboratory Data (2015-2017)

Dear Reviewer,

We appreciate the constructive comments from the reviewer and believe that these comments have improved the overall quality and readability of the manuscript. Below are the point-by-point responses to the comments of the reviewer. We sincerely hope that this manuscript is now more acceptable for further review and publication in this journal.

NO. COMMENTS FROM THE REVIEWER RESPONSE AND CORRECTIONS MADE

A. SCOPE

1. Although the aim of the paper was to analyze a retrospective data between 2015 to 2017 among companion animals presented to veterinary hospital, a significant gap is the lack of inclusion of data between 2017-2022 missing accurate information on the current picture of AMR in the target population.

This project was part of a Master research project which started in 2018, therefore was scoped for the previous three-year retrospective lab report (2015-2017). We appreciate the suggestion of expanding the period of study however given the timeline of the Master’s programme, this was not possible.

However, since almost no information exists in the country and very few publications exists regionally or globally on the AMR of clinically important pathogens of small animals, we believe that this study has provided significant information on the overall picture of resistance pattern of pathogens that are important in causing illnesses in cats and dogs giving insight about the local trends of AMR at the national, regional, and global level.

2. Given that the prevalence of AMR is highly likely to be low in household-based setting compared to hospital setting as the case here, the authors need to clarify why this pertinent data was excluded.

The overall aim of this research is to address the knowledge gap and describe the situation of the AMR among clinical isolates through a retrospective examination of available diagnostic data. Most cases presented were from veterinary health premises and animal facilities received by the accredited diagnostic bacteriology laboratory at the university. We have made it explicit that data from this study does not necessarily represent the prevalence of AMR from pets in households or general cats and dogs populations in Peninsular Malaysia.

3. Related to the veracity of the confounding factors in some circumstances, the reported prevalence may not be specific, hence the lower proportion of these than expected. To establish this as evidence, the authors might make a correlation between antimicrobial use (AMU) in companions animals vs AMR to identify pathways of the drivers of AMR in Malaysia. Comparison of AMR between different settings (hospital as the case here vs household would further strengthen the impact of the paper.

Thank you for the comment. We fully recognized and acknowledged the inherent limitations of our findings and have addressed this in the original manuscript (Page 27). Unfortunately, the samples received by the diagnostic laboratory from pets were collected from diseased animals with incomplete history of antibiotic treatment(s). Thus, we cannot correlate between antimicrobial use (AMU) and antimicrobial resistance (AMR). In addition, as with many parts of the world, but especially reflective of the local and regional situation at the time of the study and remained true at present, the use of antibiotics in animals for both livestock and pets are poorly monitored. Monitoring and quantifying AMU is one of the strategy for the national AMR action plan for Malaysia that has been extended into the next action plan 2022-2027 due to the complexity and challenges of acquiring this type of information.

B. ABSTRACT (Rationale)

4. My concern is that the brief of the rationale and the existing gaps has NOT been being briefly described.

See No. 1

5. The authors presented retrospective data retrieved between 2015 – 2017 and up to date data missing great proportion of the totality of the evidence after 2017 [5 years].

See No. 1

C. MATERIALS AND METHODS (Source of the data)

6. The appended below sentence (see line 90-94) should be shifted to results section as it is not related to the methodology.

• Fig 1 shows the distribution … followed by Streptococcus canis and Staphylococcus intermedius.

Figure 1 has been shifted to the Results section in page 7.

Please clarify the following sentence:

• ‘For the purpose of this analysis, the isolates categorized as ‘intermediate’ and ‘resistant’ were grouped as ‘non-susceptible’. For the purpose of statistical analysis (Chi-square test), those isolates categorized as ‘intermediate’ from antibiotic susceptibility testing were not excluded from the study, instead were combined and grouped together with ‘resistant’ and named ‘non-susceptible’.

D. RESULTS

7. Please define the acronym used in the fig 2-11. Please apply this change throughout.

The acronyms were readily presented in the original manuscript.

8. In Table 1: samples [postmortem, reproductive, urinary tract], please specify the nature of sample, and type of the organs rather than categorizing them as system based classification.

The samples of the diseased animals presented to the bacteriology laboratory from various types of samples were combined and categorized as system-based increase data robustness for analysis because the number of isolates per type of samples varies widely and can be low.

9. Please add a footnote to the table 1 and introduce the [others], etc.

Footnote for table 1 and 2 has been added in page 9 and 14

10. Please write as Fig 2-5 in line 145 and Table 3, 4 in line 293.

Corrected in page 9 and 18

11. Rectify the footnote of Table 4; [*NA- should be written NOT Analyzed rather than Not Included to avoid confusion (see line 317).

Corrected in page 19 and 20

E. DISCUSSION

12. The discussion section, even though should NOT be sub structured, remains superficial and not country specific. Comparisons are often made at global scaler rather than regional and national levels missing crucial information about the epidemiology of AMR in the context of current research in Malaysia and the wider Southeast Asia.

Thank you for the comment and we acknowledge the limitation of available literature to discuss the findings of this study. Research and publication of AMR in the veterinary context and especially focusing on pathogens in pets is not extensive in Malaysia and in the region. We have addressed this issue in the Introduction and added a few lines in the Discussion (Page 21 Linen 383-385).

In Malaysia, there is only one publication by Shahaza et al., [79] which was included in the discussion part of this manuscript, that presented the analysis of E. coli of clinical isolates from various species. There is no publication about clinical isolates in pets at the regional level which was why most of the references and comparisons were from more extended populations of pets in Europe, Canada and Australia.

13. The author (s) should also discuss the strength of their study and how their manuscript contribute to the literature and fit within the context of current research or practice.

The strength of this study was discussed in Introduction, page 4, line 63 to 68.

14. The author (s) should also discuss the limitation of their study of using admitted cases as these that will overestimate of the prevalence of AMR, thus the call for a nationwide AMR prevalence study.

The limitation of the study was discussed in page 27.

Attachment

Submitted filename: List Of Correction PLOS ONE_Final.docx

Click here for additional data file.^{(24.8KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0277664.r003

Decision Letter 1

Emmanuel Serrano

10 Oct 2022

PONE-D-22-09971R1High Prevalence of Antimicrobial Resistance and Multidrug Resistance among Bacterial Isolates from Diseased Pets: Retrospective Laboratory Data (2015-2017)PLOS ONE

Dear Dr. Hassan,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Nov 24 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Emmanuel Serrano, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

**********

6. Review Comments to the Author

Reviewer #1: 1) The presented figures as a whole show poor quality and thus re-plotting probably using more sophisticated software to enhance their quality is highly recommended

2) The strength of the study should be written [re-highlighted] in the discussion section.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Abdinasir Yusuf Osman

**********

PLoS One. 2022 Dec 7;17(12):e0277664. doi: 10.1371/journal.pone.0277664.r004

Author response to Decision Letter 1

31 Oct 2022

Title: High Prevalence of Antimicrobial Resistance and Multidrug Resistance among Bacterial Isolates from Diseased Pets: Retrospective Laboratory Data (2015-2017)

Dear Reviewer,

NO. COMMENTS FROM THE REVIEWER RESPONSE AND CORRECTIONS MADE

A. REFERENCES

1. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

1) In text citation for:

• [1] (Page 2, Line 35)

• [1] (Page 26, Line 464)

• [22–24] (Page 4, Line 63)

• [1,74] (Page 25, Line 437) has been updated to the latest version.

2) Reference for:

24. Moyaert H, de Jong A, Simjee S, Rose M, Youala M, El Garch F, et al. Survey of antimicrobial susceptibility of bacterial pathogens isolated from dogs and cats with respiratory tract infections in Europe: ComPath results. J. Appl. Microbiol. 2019 April; 127(1): 29-46. https://doi.org/10.1111/jam.14274

has been revised to

24. Moyaert H, de Jong A, Simjee S, Rose M, Youala M, El Garch F, et al. Erratum: Survey of antimicrobial susceptibility of bacterial pathogens isolated from dogs and cats with respiratory tract infections in Europe: ComPath results. J. Appl. Microbiol. 2019 November; 127(5): 1594. https://doi.org/10.1111/jam.14420

3) Statement for:

• (Page 2, Line 33-35): ……… isolates in pets is an emerging issue of veterinary and public health significance [1] has been revised to ……… isolates such as MRSA and MDR E. coli and Klebsiella pneumoniae in pets is an emerging issue of veterinary and public health significance [1].

• (Page 6, Line 114-116): ……… as ‘multi-drug resistant’ if it were resistant to at least three or more classes of antibiotics [36] has been revised to ……… as ‘multi-drug resistant’ if it were resistant to at least one agent in three or more classes of antibiotics [36].

• (Page 25, Line 436-437): ……… wide range of pets and as part of the normal microbiota of pets [1,74] has been revised to ……… wide range of companion animals and as part of the their normal microbiota [1,74].

• (Page 26, Line 463-464): ……… between pets and humans and this creates opportunities for interspecies transmission of AMR-bacteria [1] has been revised to ……… between companion animals and humans and this creates opportunities for interspecies transmission of AMR-bacteria [1].

B. FIGURES

2. The presented figures as a whole show poor quality and thus re-plotting probably using more sophisticated software to enhance their quality is highly recommended Figures have been updated to the good quality using Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool.

C. STRENGTH OF THE STUDY

3. The strength of the study should be written [re-highlighted] in the discussion section. The strength of the study has been highlighted in the discussion section (Page 20-21, Line 343-350)

Attachment

Submitted filename: List Of Correction PLOS ONE_Second Revision.docx

Click here for additional data file.^{(31.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0277664.r005

Decision Letter 2

Emmanuel Serrano

2 Nov 2022

High Prevalence of Antimicrobial Resistance and Multidrug Resistance among Bacterial Isolates from Diseased Pets: Retrospective Laboratory Data (2015-2017)

PONE-D-22-09971R2

Dear Dr. Hassan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

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Kind regards,

Emmanuel Serrano, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0277664.r006

Acceptance letter

Emmanuel Serrano

10 Nov 2022

PONE-D-22-09971R2

High Prevalence of Antimicrobial Resistance and Multidrug Resistance among Bacterial Isolates from Diseased Pets: Retrospective Laboratory Data (2015-2017)

Dear Dr. Hassan:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Emmanuel Serrano

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Attachment

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Click here for additional data file.^{(58.8KB, pdf)}

Attachment

Submitted filename: List Of Correction PLOS ONE_Final.docx

Click here for additional data file.^{(24.8KB, docx)}

Attachment

Submitted filename: List Of Correction PLOS ONE_Second Revision.docx

Click here for additional data file.^{(31.9KB, docx)}

Data Availability Statement

All relevant data are within the paper.

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PERMALINK

High prevalence of antimicrobial resistance and multidrug resistance among bacterial isolates from diseased pets: Retrospective laboratory data (2015–2017)

Nurul Asyiqin Haulisah

Latiffah Hassan

Saleh Mohammed Jajere

Nur Indah Ahmad

Siti Khairani Bejo

Roles

Abstract

Introduction

Material and methods

Source of data

Data analysis

Results

Descriptive analysis of samples

Fig 1. The distribution of bacterial species (Gram-negative and gram-positive bacteria) from diseased pets isolated between January 2015 and December 2017.

Antimicrobial resistance of clinical isolates from cats

Table 1. Species of bacteria isolated from diagnostic samples from diseased cats received by the Bacteriology Laboratory between 2015 and 2017.

Antibiogram based on species of bacteria isolated from cats

Fig 2. Antibiotic susceptibility pattern from Staphylococcus pseudintermedius isolates from diseased cats (January 2015–December 2017).

Fig 5. Antibiotic susceptibility pattern from Klebsiella pneumoniae isolates from diseased cats (January 2015–December 2017).

Fig 6. Multidrug resistance of clinically important bacterial pathogens from diseased cats between 2015 and 2017.

Staphylococcus pseudintermedius

Escherichia coli

Fig 3. Antibiotic susceptibility pattern from Escherichia coli isolates from diseased cats (January 2015–December 2017).

Streptococcus canis

Fig 4. Antibiotic susceptibility pattern from Streptococcus canis isolates from diseased cats (January 2015–December 2017).

Klebsiella pneumoniae

Antimicrobial resistance patterns of clinical isolates from dogs

Table 2. Species of bacteria isolated from diagnostic samples from diseased dogs received by the Bacteriology Laboratory between 2015 and 2017.

Antibiogram based on the species of bacteria isolated from dogs

Fig 7. Antibiotic susceptibility pattern from Staphylococcus intermedius isolates from diseased dogs (January 2015-December 2017).

Fig 10. Antibiotic susceptibility pattern from Staphylococcus pseudintermedius isolates from diseased dogs (January 2015-December 2017).

Fig 11. Multidrug resistance of clinically important bacterial pathogens from diseased dogs between 2015 and 2017.

Staphylococcus intermedius

Escherichia coli

Fig 8. Antibiotic susceptibility pattern from Escherichia coli isolates from diseased dogs (January 2015-December 2017).

Proteus mirabilis

Fig 9. Antibiotic susceptibility pattern from Proteus mirabilis isolates from diseased dogs (January 2015-December 2017).

Staphylococcus pseudintermedius

Differences between the profile of resistances of isolates from cats and dogs

Table 3. Difference between E. coli isolates from diseased cats and dogs between 2015 and 2017.

Table 4. Differences between S. pseudintermedius isolates from diseased cats and dogs between 2015 and 2017.

Escherichia coli

Staphylococcus pseudintermedius

Discussion

Antimicrobial resistance of clinical isolates from cats

Antimicrobial resistance of clinical isolates from dogs

Comparison of antimicrobial resistance of clinical isolates from dogs and cats

Multi-drug resistance of clinical isolates from dogs and cats

Limitations of the study

Conclusion

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Emmanuel Serrano

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Author response to Decision Letter 0

Decision Letter 1

Emmanuel Serrano

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Author response to Decision Letter 1

Decision Letter 2

Emmanuel Serrano

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Acceptance letter

Emmanuel Serrano

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Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

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