ABSTRACT
Background and Aim: Antimicrobial resistance (AMR) in
Materials and Methods: A total of 121 bacterial isolates were collected from bovine milk (n = 30), cats (n = 61), dogs (n = 18), rabbits (n = 7), and goats (n = 5) between June 2024 and August 2025 in Yogyakarta and Central Java, Indonesia. Phenotypic identification involved biochemical tests (catalase, coagulase, mannitol fermentation), antimicrobial susceptibility testing via disk diffusion against seven antibiotics (tetracycline, gentamicin, erythromycin, penicillin G, cefoxitin, ciprofloxacin, clindamycin), and genotypic confirmation using polymerase chain reaction (PCR) for
Results: Of the isolates, 55 (45.5%) were confirmed as
Conclusion: This study reveals shared resistance gene profiles in MDR
Keywords: antimicrobial resistance, companion animals, Indonesia, livestock animals, multidrug resistance, One Health,
INTRODUCTION
Antimicrobial resistance (AMR) has become a serious global health threat, affecting human and veterinary medicine. Pathogenic bacteria continue to evolve resistance mechanisms to multiple antibiotics, reducing treatment effectiveness and increasing morbidity and mortality from bacterial infections. The scarcity of new antimicrobial discoveries intensifies the issue of replacing ineffective drugs. In 2019, the World Health Organization (WHO) estimated that 1.2 million deaths were directly attributable to antibiotic-resistant bacterial infections in 2019, and that up to 4.95 million deaths were associated with antimicrobial resistance in 2022. Without effective interventions, AMR is projected to cause 10 million deaths annually by 2050 [1, 2].
The emergence of multidrug-resistant (MDR) bacteria, defined as strains resistant to three or more antimicrobial classes, poses a significant challenge for infection control. MDR bacteria have been detected not only in companion animals but also in livestock and animal-derived food products, such as milk, meat, and processed animal-derived foods [3, 4]. Their presence in animals poses a zoonotic risk, as transmission can occur through direct contact or the food chain. Among these bacteria,
The MDR of
Specific resistance genes mediate antibiotic resistance in
Despite increasing reports of MDR
Addressing this gap is essential to support national and global AMR surveillance initiatives in line with the WHO Global Action Plan on AMR [10]. Therefore, this study aimed to characterize the genotypes of key antimicrobial resistance genes in multidrug-resistant
MATERIALS AND METHODS
Ethical approval
Informed consent and permission for sample collection were obtained from animal owners and veterinary facilities before sampling. The Research Ethics Committee of the Faculty of Veterinary Medicine, Universitas Gadjah Mada, Yogyakarta, Indonesia, approved the collection and use of animal isolates (Approval No. 143/EC-FKH/Int./2024).
Study design, period, and location
This study used a cross-sectional, laboratory-based observational design to investigate the genotypic characteristics of AMR in
Sample collection and bacterial isolation
A total of 121 bacterial isolates, comprising 30 from bovine milk, 61 from cats, 18 from dogs, 7 from rabbits, and 5 from goat milk, were used in this study. Bovine and goat milk samples were obtained from dairy farms in Boyolali, Central Java, Indonesia, whereas companion animal samples were collected from veterinary clinics and hospitals in Yogyakarta and Semarang.
Animals exhibiting clinical signs suggestive of bacterial infection, such as pyogenic skin lesions, rhinitis, pyrexia, lethargy, or mastitis (dairy animals) were included in the study. Swab samples were collected from the oropharynx, nasal cavity, ears, and skin lesions of companion animals. Milk samples were aseptically collected from dairy animals with clinical or subclinical mastitis. Animals that had received systemic antibiotics within 2 weeks before sampling or samples showing mixed bacterial growth were excluded from the analysis.
Continuous sample collection was conducted throughout the study period to minimize seasonal or temporal bias. All samples were aseptically transported and processed immediately upon arrival at the laboratory. Specimens were cultured on 5% defibrinated sheep blood agar and incubated aerobically at 37°C for 24 h. Colonies with typical
Antimicrobial susceptibility testing
All
The culture was standardized to a 0.5 McFarland standard, and 70 µL was spread on Mueller-Hinton agar (MHA; Merck, Germany) using a glass spreader. Antibiotic disks were placed on MHA at a specified distance from one another and incubated at 37°C for 24 h. The antibiotic disks (Oxoid, UK) used in this study were tetracycline (30 µg), gentamicin (10 µg), erythromycin (15 µg), penicillin G (10 µg), cefoxitin (30 µg), ciprofloxacin (5 µg), and clindamycin (10 µg). Inhibition zone diameters were measured and interpreted as susceptible, intermediate, or resistant according to CLSI M100 (2024) criteria. Multidrug resistance (MDR) was defined as resistance to ≥1 agent in ≥3 antimicrobial classes, as defined by Magiorakos
DNA extraction, molecular identification, and resistance gene detection
Genomic DNA was extracted from
Detection of antibiotic resistance genes, including
Table 1. Oligonucleotide primers and polymerase chain reaction (PCR) programs for amplification of species-specific and antibiotic resistance genes in
| Target gene | Primer sequence (5’–3’) | Annealing (°C) | Target size (bp) | PCR program | Reference |
|---|---|---|---|---|---|
|
| AGCGAGTTACAAAGGAGGAC; AGCTCAGCCTTAACGAGTAC | 64 | 1250 | 35 cycles: 95°C 15 s/64°C 30 s/72°C 10 s | [9] |
|
| GCGATTGATGGTGATACGGTT; ACGCAAGCCTTGACGAACTAAAGC | 55 | 279 | 37 cycles: 98°C 10 s/55°C 30 s/72°C 5 s | [9] |
|
| GTCTTGAAAGTAGCTCATCTAAACTTG; ATCCAAATGTTCCATCGTTGTATTC | 55 | 228 | 40 cycles: 95°C 10 s/55°C 20 s/72°C 25 s | [13] |
|
| ACTTCAACACCTGCTGCTTTC; TGACCACTTTTATCAGCAACC | 55 | 173 | 30 cycles: 94°C 30 s/55°C 30 s/72°C 1 min | [14] |
|
| TAATCCAAGAGCAATAAGGGC; GCCACACTATCATAACCACTA | 55 | 227 | 30 cycles: 94°C 30 s/55°C 30 s/72°C 30 s | [15] |
|
| ACGATATTCACGGTTTACCCACTTA; AACCAGAAAAACCCTAAAGACACG | 55 | 610 | 30 cycles: 94°C 30 s/55°C 30 s/72°C 30 s | [16] |
|
| TATGATATCCATAATAATTATCCAATC; AAGTTATATCATGAATAGATTGTCCTGTT | 50 | 595 | 35 cycles: 95°C 15 s/50°C 15 s/72°C 10 s | [17] |
|
| GTGCGACAATAGGTAATAGT; GTAGTGACAATAAACCTCCTA | 55 | 360 | 35 cycles: 95°C 30 s/55°C 30 s/72°C 10 s | [18] |
|
| AGTGGAGCGATTACAGAA; CATATGTCCTGGCGTGTCTA | 55 | 158 | 35 cycles: 95°C 30 s/55°C 30 s/72°C 10 s | [19] |
|
| GGTGGCTGGGGGGTAGATGTATTAACTGG; GCTTCTTTTGAAATACATGGTATTTTTCGATC | 57 | 323 | 35 cycles: 95°C 15 s/57°C 15 s/72°C 10 s | [20] |
|
| GACATTTCACCAAGCCATCAA; TGCCATAAATCCACCAATCC | 55 | 102 | 30 cycles: 98°C 10 s/55°C 30 s/72°C 30 s | [21] |
|
| AAAATCGATGGTAAAGGTTGGC; AGTTCTGCAGTACCGGATTTGC | 56 | 533 | 35 cycles: 95°C 30 s/55°C 30 s/72°C 10 s | [9] |
The PCR products were separated by electrophoresis on a 1.5% (w/v) agarose gel (GeneDireX, USA) in 1× TBE buffer and stained with Safe-Red™ Gel Stain (ABM, Canada). Bands were visualized using a UV transilluminator and compared with a 100-bp DNA ladder (Smobio, Taiwan).
Quality control strains
We ensured quality control by including a well-characterized
Statistical analysis
Descriptive statistics were used to summarize the distribution of
RESULTS
Identification of S. aureus isolates
A total of 55 isolates were confirmed as
Phenotypic characteristics
Typical
Figure 1. Comparison of colony morphology between small-colony variant and wild-type
Table 2. Phenotypic characteristics of
| Source of the isolates | Number of samples | No. of identified | Gram stain | Catalase-positive (%) | Positive mannitol fermentation (%) | Coagulase-positive (%) | Type of hemolysis observed | SCV identified (%) |
|---|---|---|---|---|---|---|---|---|
| Bovine milk | 30 | 24 | + | 83.3 (20/24) | 100 (24/24) | 33.3 (8/24) | α, β, γ | 8.3 (2/24) |
| Cats | 61 | 18 | + | 94.4 (17/18) | 94.4 (17/18) | 38.9 (7/18) | α, β, γ | 0 (0/18) |
| Dogs | 18 | 5 | + | 80.0 (4/5) | 100 (5/5) | 60.0 (3/5) | β, γ | 40 (2/5) |
| Rabbits | 7 | 6 | + | 83.3 (5/6) | 100 (6/6) | 83.3 (5/6) | β, γ | 0 (0/6) |
| Goat milk | 5 | 2 | + | 100 (2/2) | 100 (2/2) | 50.0 (1/2) | α, β | 50 (1/2) |
| Total | 121 | 55 |
* Hemolysis types: α = Alpha-hemolysis, β = Beta-hemolysis, γ = Gamma-hemolysis (non-hemolytic), SCV = Small-colony variant
Molecular confirmation
Molecular confirmation of all isolates was performed by PCR amplification of the
Figure 2. Polymerase chain reaction amplification of
Antimicrobial resistance profiles
All
Table 3 and Figure 3 summarize the overall resistance rates among
Table 3. Antibiotic resistance profiles of
| Antibiotic | Bovine milk (n = 24) | Cats (n = 18) | Dogs (n = 5) | Rabbits (n = 6) | Goat milk (n = 2) |
|---|---|---|---|---|---|
| Resistant (%) | |||||
| TE (30 µg) | 20.8 (5/24) | 27.8 (5/18) | 20 (1/5) | 16.7 (1/6) | 0 (0/2) |
| CN (10 µg) | 12.5 (3/24) | 16.7 (3/18) | 0 (0/5) | 16.7 (1/6) | 0 (0/2) |
| E (15 µg) | 0 (0/24) | 50 (9/18) | 0 (0/5) | 33.3 (2/6) | 0 (0/2) |
| P (10 µg) | 62.5 (15/24) | 72.2 (13/18) | 20 (1/5) | 33.3 (2/6) | 0 (0/2) |
| FOX (30 µg) | 12.5 (3/24) | 27.8 (5/18) | 0 (0/5) | 0 (0/6) | 0 (0/2) |
| CIP (5 µg) | 4.2 (1/24) | 16.7 (3/18) | 0 (0/5) | 0 (0/6) | 0 (0/2) |
| DA (10 µg) | 4.2 (1/24) | 38.9 (7/18) | 0 (0/5) | 0 (0/6) | 50 (1/2) |
| Susceptible (%) | |||||
| TE (30 µg) | 79.2 (19/24) | 55.6 (10/18) | 80 (4/5) | 83.3 (5/6) | 100 (2/2) |
| CN (10 µg) | 79.2 (19/24) | 72.2 (13/18) | 100 (5/5) | 83.3 (5/6) | 100 (2/2) |
| E (15 µg) | 83.3 (20/24) | 50 (9/18) | 80 (4/5) | 66.7 (4/6) | 100 (2/2) |
| P (10 µg) | 37.5 (9/24) | 27.8 (5/18) | 80 (4/5) | 66.7 (4/6) | 100 (2/2) |
| FOX (30 µg) | 87.5 (21/24) | 72.2 (13/18) | 100 (5/5) | 100 (6/6) | 100 (2/2) |
| CIP (5 µg) | 91.7 (22/24) | 66.7 (12/18) | 100 (5/5) | 83.3 (5/6) | 50 (1/2) |
| DA (10 µg) | 87.5 (21/24) | 55.6 (10/18) | 100 (5/5) | 100 (6/6) | 50 (1/2) |
TE = Tetracycline, CN = Gentamicin, E = Erythromycin, P = Penicillin G, FOX = Cefoxitin, CIP = Ciprofloxacin, DA = Clindamycin.
Figure 3. Antimicrobial susceptibility profiles of
Detection of antibiotic resistance genes
All 55
Figure 4. Polymerase chain reaction amplification of antibiotic resistance–encoding genes in
Figure 5. Distribution of antimicrobial resistance genes among
Phenotypic and genotypic patterns of multidrug resistance
The MDR pattern of
Figure 6. Phenotypic multidrug resistance patterns among
Figure 7. Genotypic multidrug resistance (MDR) profiles of
DISCUSSION
Identification and phenotypic variations of S. aureus
Based on the biochemical characteristics and PCR amplification of the
A small proportion of isolates from bovine milk, cats, dogs, and rabbits were catalase-negative, a rare phenotype in
Hemolytic activity and host adaptation
Hemolytic activity varies by host origin, reflecting host-adaptive virulence traits. Beta-hemolysis predominated among isolates from cats, consistent with studies implicating β-hemolysin in skin and soft-tissue infections in companion animals [29, 30]. In contrast, gamma-hemolysis was more common among bovine milk isolates, consistent with reports of mastitis-associated
Small-colony variants and their implications
In this study, five isolates exhibited atypical growth, forming pinpoint-sized colonies smaller than those of wild-type
Antimicrobial susceptibility patterns
In this study, the antimicrobial susceptibility profiles showed that resistance patterns were broadly comparable across animal sources for most antibiotics tested, with no statistically significant differences. This suggests a relatively uniform distribution of resistance phenotypes across animal sources, which may reflect similar antimicrobial exposure or shared environmental and management conditions. Erythromycin was the only antimicrobial for which a significant difference was observed among animal sources. Resistance to macrolides may be influenced by host-associated factors or differences in usage patterns. The majority of macrolide use was in food-producing animals; in the U. S. in 2017, macrolides were the most commonly used in cattle [38].
In this study,
Multidrug resistance patterns
Bacteria were classified as MDR if they showed resistance or intermediate resistance to at least one antibiotic from three or more antimicrobial classes [12, 13]. MDR
MDR
Phenotypic-genotypic discrepancies
PCR amplification detected several antibiotic resistance genes, including
Conversely, several isolates harbored resistance genes but remained phenotypically susceptible.
Factors contributing to MDR emergence
The overall MDR genotypic pattern (Figure 7) corresponded well with the phenotypic resistance profiles. MDR
CONCLUSION
This study provides the first comparative insight into the resistance gene profiles of MDR
The practical implications of these findings underscore the zoonotic potential of MDR
A major strength of this research lies in its multi-host approach, combining phenotypic and targeted PCR analyses across diverse animal sources, thereby providing a comprehensive baseline for AMR patterns in understudied regions, such as Yogyakarta and Central Java.
Limitations include reliance on targeted PCR, which may miss the full resistome or genetic contexts; uneven sample sizes across species, potentially affecting generalizability; and the absence of human isolates to directly evaluate zoonotic transmission.
Future scope should encompass whole-genome sequencing for detailed resistome mapping, investigation of biofilm and virulence factors, and longitudinal studies on transmission dynamics between animals, humans, and the environment to inform targeted interventions.
In conclusion, these results underscore animals as critical AMR reservoirs and call for collaborative One Health strategies to curb the dissemination of MDR
DATA AVAILABILITY
All the generated data are included in the manuscript.
AUTHORS’ CONTRIBUTIONS
ARPY: Performed the experiment, data analysis, and wrote the manuscript. SIO: Conceptualization, funding acquisition, supervision, and wrote the manuscript. GGA: Contributed to sample collection and the experiment. FA: Data analysis and review of the manuscript. All authors have read and approved the final manuscript.
COMPETING INTERESTS
The authors declare that they have no competing interests.
PUBLISHER’S NOTE
Veterinary World remains neutral with regard to jurisdictional claims in the published institutional affiliations.
ACKNOWLEDGMENTS
We thank the Indonesian Ministry of Higher Education, Science, and Technology for providing the PMDSU scholarship (Contract No. 048/E5/PG.02.00.PL/2024). We would like to thank the dairy farms in Central Java, Prof. Soeparwi Veterinary Hospital, and veterinary clinics in Yogyakarta and Central Java for providing samples for this study.
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