Antibacterial Efficacy of 6‐Gingerol Alone and in Combination With Enrofloxacin Against Multidrug‐Resistant Staphylococcus aureus Isolated From Goats

ABSTRACT

Background

Goat mastitis is an economically important disease that reduces milk yield and quality while also posing a public health risk due to antimicrobial‐resistant pathogens.

Objectives

This study aimed to evaluate mastitis diagnostic techniques, isolate Staphylococcus aureus, detect methicillin‐resistant S. aureus (MRSA) and assess the antibacterial potential of 6‐gingerol alone and in combination with antibiotics.

Methods

A total of 2000 aseptically collected milk samples were obtained from lactating goats presented at the Civil Veterinary Hospital, Chargano Chowk and the Veterinary Teaching Hospital, The University of Agriculture Peshawar, Pakistan. Samples were screened using the Surf Field Mastitis Test and confirmed by the California Mastitis Test (CMT). Positive samples were cultured on selective media, and S. aureus was identified through Gram staining, catalase and coagulase tests. MRSA detection was performed using PCR amplification of the mecA gene. Antimicrobial susceptibility was assessed using the Kirby–Bauer disc diffusion method according to CLSI guidelines. The antibacterial activity of standard and extracted 6‐gingerol, selected antibiotics and enrofloxacin plus 6‐gingerol combination therapy was evaluated using inhibition zone diameter and minimum inhibitory concentration (MIC) assays.

Results

The Surf Field Mastitis Test showed high diagnostic performance with excellent sensitivity, moderate specificity and substantial agreement with the CMT. S. aureus isolates exhibited varying resistance patterns, with confirmed presence of MRSA strains via mecA gene detection. Among treatments, enrofloxacin demonstrated the highest individual antibacterial activity, while extracted 6‐gingerol showed moderate inhibitory effects. The combination of enrofloxacin with 6‐gingerol exhibited the strongest antibacterial activity, surpassing all single‐agent treatments. MIC analysis confirmed a concentration‐dependent inhibitory effect of 6‐gingerol against S. aureus. Correlation analysis showed a strong negative relationship between increasing compound concentration and bacterial growth, while combination therapy significantly enhanced antimicrobial efficacy.

Conclusion

These findings demonstrate that rapid field diagnostics are effective for mastitis screening and suggest that 6‐gingerol, particularly in combination with enrofloxacin, may serve as a promising adjunct antimicrobial strategy for controlling resistant S. aureus in goat mastitis.

Integrated mastitis screening effectively identified MRSA‐associated Staphylococcus aureus in goats, with the Surf Field Mastitis Test proving a reliable rapid diagnostic tool. Combination therapy of enrofloxacin and 6‐gingerol showed superior antibacterial activity, highlighting 6‐gingerol as a promising adjunct to combat antimicrobial‐resistant mastitis pathogens

1. Introduction

Goat farming plays an important role in the livelihood of rural communities by providing milk, meat and income, particularly in developing countries (Nedumaran and Muthuveni 2023; Purwaningsih et al. 2024). Goat milk is valued for its nutritional quality, digestibility and medicinal properties, making it an important component of household nutrition and small‐scale dairy enterprises (Biswas et al. 2024; Mansoor et al. 2025). However, the productivity of dairy goats is greatly affected by mastitis, one of the most common and economically significant diseases of the udder (Bessembayeva et al. 2024; Tibebu et al. 2025). Mastitis is an inflammatory condition of the mammary gland usually caused by bacterial infection, leading to reduced milk yield, poor milk quality, treatment costs and premature culling of animals (Dorgham et al. 2024; Lima et al. 2025). Both clinical and subclinical mastitis occur in goats, but subclinical mastitis is more difficult to detect because it shows no visible signs while silently decreasing milk production and increasing bacterial contamination (Aliyi 2023).

Among the bacterial pathogens associated with caprine mastitis, Staphylococcus aureus is considered one of the most important causative agents worldwide (Gherardi 2023; Susanty et al. 2025). This organism is highly adaptable, contagious and capable of colonizing the skin, teat canal and mammary tissue (Javed et al. 2024; Campos et al. 2022). Infected animals often develop persistent or recurrent intramammary infections that are difficult to eliminate. S. aureus can produce toxins, biofilms and several virulence factors that enhance tissue damage and resistance to host immune defences (Touaitia et al. 2025).

A growing concern in veterinary and human medicine is the emergence of methicillin‐resistant Staphylococcus aureus (MRSA) (Abd El‐Razik et al. 2025; Zafar et al. 2025). MRSA strains carry the mecA gene, which encodes an altered penicillin‐binding protein (PBP2a) that reduces the efficacy of β‐lactam antibiotics such as methicillin, penicillin and related drugs (Olanipekun et al. 2025). The spread of MRSA in dairy animals is alarming because it limits treatment options, increases therapeutic failure and may facilitate transmission of resistant bacteria between animals, farm workers, veterinarians and the environment (Pal et al. 2024). The detection of the mecA gene by polymerase chain reaction (PCR) is considered a reliable method for confirming methicillin resistance and identifying MRSA isolates.

The treatment of mastitis in goats often relies on the use of commonly available antibiotics such as enrofloxacin, amoxicillin, gentamicin and tetracycline (Lima et al. 2025). However, frequent or indiscriminate use of antimicrobials has contributed to the development of resistance among mastitis pathogens (Gherardi 2023). Therefore, regular antimicrobial susceptibility testing is necessary to guide effective therapy and reduce unnecessary antibiotic usage (Aqib et al. 2017; Rasheed et al. 2023; Touaitia et al. 2025). The agar disc diffusion method based on Clinical and Laboratory Standards Institute (CLSI) guidelines remains a widely accepted approach for evaluating susceptibility patterns of bacterial isolates.

In recent years, interest has increased in natural antimicrobial compounds as supportive or alternative approaches to combat resistant bacteria (Rasool et al. 2024; Fitriadi et al. 2024; Sultan et al. 2025). One such compound is 6‐gingerol, the principal bioactive constituent of ginger (Zingiber officinale). 6‐Gingerol possesses antibacterial, antioxidant, anti‐inflammatory and immunomodulatory properties (Yücel et al. 2022; Zimazi et al. 2025). Previous studies have reported its inhibitory effects against Gram‐positive and Gram‐negative bacteria, including S. aureus (Hasan et al. 2026). Combining plant‐derived compounds with conventional antibiotics may enhance antibacterial activity through synergistic interactions and potentially reduce required antibiotic doses.

Despite the importance of goat mastitis, limited data are available regarding the prevalence of MRSA and antimicrobial susceptibility of S. aureus isolates in many regions, including Peshawar. Local epidemiological information is essential for designing evidence‐based control strategies, selecting effective therapeutic agents and reducing the spread of resistant pathogens. Therefore, the present study was conducted to determine the prevalence of mastitis in goats using screening tests, isolate and identify Staphylococcus aureus from mastitic milk samples, detect MRSA using the mecA gene and evaluate the antimicrobial susceptibility of isolates against commonly used antibiotics. In addition, the antibacterial activity of 6‐gingerol alone and in combination with antibiotics was assessed to explore its potential as an alternative or complementary therapeutic option against mastitis‐associated S. aureus.

2. Materials and Methods

2.1. Study Area and Duration

The present study was conducted in District Peshawar, Khyber Pakhtunkhwa, Pakistan. Milk samples were collected from goats presented to two major veterinary healthcare centres: Civil Veterinary Hospital, Chargano Chowk, and Veterinary Teaching Hospital, The University of Agriculture, Peshawar.

2.2. Sample Collection

A total of 2000 goat milk samples were collected aseptically for the detection of mastitis and bacterial isolation. Of these, 1000 samples were collected from Civil Veterinary Hospital and 1000 samples from the Veterinary Teaching Hospital. Milk samples were obtained from lactating goats suspected of clinical or subclinical mastitis. Before sampling, teats were washed with clean water, dried with disposable towels and disinfected using 70% ethanol. The first few streams of milk were discarded, and approximately 10–15 mL milk was collected into sterile screw‐capped tubes. Samples were immediately placed in an ice box and transported to the laboratory for further analysis.

2.3. Screening of Mastitis

2.3.1. Surf Field Mastitis Test

The Surf Field Mastitis Test was used as a rapid field screening method for mastitis detection. Equal volumes of milk and commercial surf solution were mixed in a clean test paddle or tube. Formation of gel or thickening indicated a positive reaction.

2.3.2. California Mastitis Test

The California Mastitis Test (CMT) was used as the reference test for confirmation of subclinical mastitis. Equal amounts of milk and CMT reagent were mixed in the wells of a CMT paddle. The mixture was gently rotated for 10–15 s and scored according to gel formation. Samples showing visible gel formation were considered positive.

The diagnostic performance of the Surf test was evaluated against CMT by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy and Cohen's kappa coefficient.

2.4. Isolation and Identification of Staphylococcus aureus

Milk samples positive for mastitis were cultured for bacterial isolation. A loopful of milk was streaked onto Mannitol Salt Agar (MSA) and Blood Agar plates and incubated aerobically at 37°C for 24–48 h. Colonies showing golden yellow pigmentation on MSA and β‐haemolysis on blood agar were presumptively identified as Staphylococcus aureus. Pure colonies were subjected to Gram staining and biochemical tests including catalase and coagulase tests. Gram‐positive cocci in clusters, catalase‐positive and coagulase‐positive isolates were considered S. aureus.

2.5. Molecular Detection of MRSA (mecA Gene)

Confirmed S. aureus isolates were screened for methicillin resistance by polymerase chain reaction (PCR) targeting the mecA gene.

2.6. DNA Extraction

Bacterial genomic DNA was extracted using the boiling method or a commercial extraction kit according to manufacturer instructions. Primers used are shown in Table 1. PCR amplification was performed in a total reaction volume of 25 µL containing master mix, primers, DNA template and nuclease‐free water. Thermal cycling conditions included:

• Initial denaturation: 95°C for 5 min

• 35 cycles of:

  • Denaturation: 94°C for 30 s

  • Annealing: 58°C for 30 s

  • Extension: 72°C for 45 s

  • Final extension: 72°C for 7 min

TABLE 1.

Identification of Staphylococcus aureus.

Specie	Target gene	Primer	Sequence 5′ ——— 3′	Annealing temp	Amplic on size	Reference
S. aureus	mecA	Forward	TGGCATTCGTGTCACAATG	58°C	310	Shoaib et al. 2020
		Reverse	CTGGAACTTGTTGAGCAAG

PCR products were resolved on 1.5% agarose gel stained with ethidium bromide and visualized under UV transilluminator. Presence of a 310 bp band confirmed the mecA gene.

2.6.1. Antimicrobial Susceptibility Testing

Antimicrobial susceptibility of S. aureus isolates was determined by the Kirby‐Bauer disc diffusion method on Mueller‐Hinton Agar according to CLSI guidelines (2020).

The antibiotics tested were:

• Enrofloxacin (5 µg)

• Amoxicillin (10 µg)

• Gentamicin (10 µg)

• Tetracycline (30 µg)

Bacterial suspension equivalent to 0.5 McFarland standard was swabbed onto Mueller–Hinton agar plates. Antibiotic discs were placed on the inoculated surface and plates incubated at 37°C for 24 h. Zones of inhibition were measured in millimetres and interpreted as resistant, intermediate or sensitive according to CLSI breakpoints.

2.7. Preparation and Confirmation of 6‐Gingerol Extract

Both standard 6‐gingerol and plant‐derived 6‐gingerol extract were used in the study. Fresh ginger (Zingiber officinale) rhizomes were procured from the local market and taxonomically authenticated by the Department of Weed Science, The University of Agriculture, Peshawar, Pakistan.

For extraction, the rhizomes were thoroughly washed to remove soil and debris, peeled and rinsed again with clean water. The cleaned rhizomes were then cut into small pieces and crushed with methanol using a pestle and mortar. The homogenized mixture was transferred into Falcon tubes and centrifuged at 4500 rpm for 15 min. The supernatant was collected, filtered through Whatman filter paper and transferred into sterile tubes.

Stock solutions of both standard 6‐gingerol and the plant extract were prepared by dissolving accurately weighed quantities in sterile dimethyl sulfoxide (DMSO). Working solutions (100 µg/mL) were prepared by further dilution with methanol under aseptic conditions.

Confirmation and quantification of 6‐gingerol in the extract were performed using High Performance Liquid Chromatography (HPLC) equipped with UV detection. Separation was achieved on a Betasil C18 column (150 mm × 4.6 mm, 5 µm particle size). The mobile phase consisted of HPLC‐grade water (solution A) and acetonitrile (solution B) in gradient ratios, with a constant flow rate of 1 mL/min. Detection was carried out at 254 nm. Identification of 6‐gingerol was based on comparison of retention time and photodiode array spectra of the sample with those of the authentic standard.

2.8. Antibacterial Activity of 6‐Gingerol and Combination Therapy

The antibacterial activity of antibiotics, standard 6‐gingerol, extracted 6‐gingerol and Enrofloxacin + 6‐gingerol combination was evaluated using agar well diffusion or disc diffusion assay.

Fresh bacterial inoculum of S. aureus was spread on Mueller‐Hinton agar plates. Wells/discs containing test compounds were applied and incubated at 37°C for 24 h. Zones of inhibition diameter (IZD) were measured in mm. Each treatment was tested in triplicate and results expressed as mean ± standard deviation.

2.9. Minimum Inhibitory Concentration of 6‐Gingerol

Minimum inhibitory concentration (MIC) of 6‐gingerol was determined by broth microdilution method using serial twofold dilutions ranging from 25 to 0.0488 µg/mL in sterile microtiter plates.

Each well received bacterial inoculum adjusted to 10⁶ CFU/mL and was incubated at 37°C for 24 h. Wells were examined for visible turbidity. The lowest concentration showing no visible growth was recorded as the MIC.

2.10. Statistical Analysis

All experimental data were analysed using standard statistical procedures to evaluate diagnostic performance, antibacterial efficacy and relationships among variables. Descriptive statistics were expressed as mean ± standard deviation (SD) for inhibition zone diameter (IZD). For diagnostic test evaluation, the Surf test was compared with the CMT as the reference standard. The association between categorical variables (Surf test and CMT results) was evaluated using the Chi‐square (χ ²) test of independence, calculated as:

$${\chi }^2=\sum \frac{{\left(O-E\right)}^2}{E}$$

where O is the observed frequency and E is the expected frequency.

For diagnostic test evaluation, the Surf test was compared with the CMT as the reference standard. Diagnostic performance was determined by calculating sensitivity, specificity, PPV****, NPV and overall accuracy using standard equations.

The following indices were calculated:

$$\mathrm{Sensitivity}=\mathrm{TP}/\left(\mathrm{TP}+\mathrm{FN}\right)\times 100$$

$$\mathrm{Specificity}=\mathrm{TN}/\left(\mathrm{TN}+\mathrm{FP}\right)\times 100$$

$$\mathrm{PPV}=\mathrm{TP}/\left(\mathrm{TP}+\mathrm{FP}\right)\times 100$$

$$\mathrm{NPV}=\mathrm{TN}/\left(\mathrm{TN}+\mathrm{FN}\right)\times 100$$

$$\mathrm{Accuracy}=\left(\mathrm{TP}+\mathrm{TN}\right)/\mathrm{Total}\times 100$$

Agreement between the two diagnostic methods was further assessed using Cohen's kappa coefficient (κ):

Cohen's kappa

$$\kappa =\left(P_{\mathrm{o}}-P_{\mathrm{e}}\right)/\left(1-P_{\mathrm{e}}\right)$$

where P _o represents observed agreement and P _e​ represents expected agreement by chance. The κ value was interpreted as:

$$0.61-0.80=\mathrm{substantial}\mathrm{agreement}.$$

For antibacterial activity, differences among treatments were evaluated using one‐way analysis of variance (ANOVA). The F‐statistic was calculated as:

$$F=\frac{\mathrm{Mean}\mathrm{Square}\mathrm{Between}\mathrm{Group}}{\mathrm{Mean}\mathrm{Square}\mathrm{Within}\mathrm{Groups}}$$

When significant differences (p < 0.05) were observed, treatment means were separated using Duncan's Multiple Range Test (DMRT). Treatments were ranked based on mean IZD values (Table 7), where higher values indicated stronger antibacterial activity. The percentage increase in antibacterial activity relative to 6‐gingerol extract was calculated as:

TABLE 7.

Ranking of treatments based on antibacterial activity.

Treatment	Mean IZD (mm)	Rank
Enrofloxacin + 6‐gingerol	38.00	1
Enrofloxacin	23.33	2
Gentamicin	21.00	3
6‐Gingerol (standard)	20.33	4
Amoxicillin	20.00	5
Tetracycline	15.66	6
6‐Gingerol (extract)	14.66	7

Note: Duncan grouping (conceptual): A (highest) to D (lowest), with combination treatment significantly superior.

The percentage increase in antibacterial activity was calculated to compare treatment efficacy relative to the control using the formula:

$$\%\mathrm{Increase}=\frac{\mathrm{Treatment}\mathrm{Mean}-\mathrm{Control}\mathrm{Mean}}{\mathrm{Control}\mathrm{Mean}}\times 100$$

where the Treatment Mean represents the IZD of each tested agent and the Control Mean corresponds to the baseline (6‐gingerol extract).

The MIC of 6‐gingerol was determined as the lowest concentration that completely inhibited visible bacterial growth following incubation.

To further evaluate the relationship between variables, logistic regression analysis was applied using the model:

$$\log \left(\frac{p}{1-p}\right)={\beta }_0+{\beta }_{1}X$$

where p represents the probability of bacterial inhibition, β ₀ is the intercept, β ₁ is the regression coefficient and X denotes the independent variable (e.g., concentration or treatment level). Pearson correlation analysis was performed to assess relationships between variables using the formula:

$$r=\frac{\mathrm{\Sigma }[(x-\overline{x})(y-\overline{y})]}{\sqrt{\mathrm{\Sigma }{(x-\overline{x})}^2\times \mathrm{\Sigma }{(y-\overline{y})}^2}}$$

Correlation values were interpreted as:

• 0.00–0.30 = weak

• 0.31–0.70 = moderate

• 0.71–1.00 = strong

Pairwise comparisons of treatment means were expressed as mean differences (mm):

$$\mathrm{Mean}\mathrm{Difference}=\mathrm{Mea}{\mathrm{n}}_1-\mathrm{Mea}{\mathrm{n}}_2$$

All data were analysed using SPSS (Version 26.0). Statistical significance was set at p < 0.05.

3. Results

Table 2 presents the distribution of milk samples collected from two major sampling sites in Peshawar district. The sampling was evenly distributed between the Civil Veterinary Hospital (Chargano Chowk) and the Veterinary Teaching Hospital, The University of Agriculture, Peshawar, ensuring balanced representation from both locations.

TABLE 2.

Locations of district Peshawar for the collection of samples.

S. No.	Location	Sample	No. of milk samples
1	Civil Veterinary Hospital (Chargano Chowk)	Milk	1000
2	Veterinary Teaching Hospital (The University of Agriculture, Peshawar)	Milk	1000

Table 3 outlines the CLSI interpretive criteria used for antimicrobial susceptibility testing. Breakpoints varied among antibiotics, with intermediate categories defined only for selected drugs, reflecting differences in standardized susceptibility ranges and guiding accurate classification of bacterial responses.

TABLE 3.

CLSI breakpoints for antimicrobial susceptibility testing.

S. No.	Antibiotics	Resistant	Intermediate	Sensitive
1	Enrofloxacin (5 µg)	≤ 16	Not defined	≥ 23
2	Amoxicillin (10 µg)	≤ 19	Not defined	≥ 20
3	Gentamicin (10 µg)	≤ 12	13–14	≥ 15
4	Tetracycline (30 µg)	≤ 14	15–18	≥ 19

Source: Clinical and Laboratory Standard Institute M02, M07 and M011, 2020, 30th edition.

Table 4 summarizes the diagnostic performance of the Surf test in comparison with the CMT. The Surf test demonstrated perfect sensitivity, indicating its strong ability to detect positive cases, while specificity was comparatively moderate, suggesting some false‐positive results. The high PPV and NPV, along with overall accuracy, indicate reliable diagnostic performance. Furthermore, the Cohen's kappa value showed substantial agreement between the two tests, confirming consistency between methods.

TABLE 4.

Diagnostic performance of the Surf Test using CMT as the reference standard.

Test	Results (out of 2000 samples)
Surf test positive	1670
CMT positive	1420

	CMT Positive	CMT Negative	Total
Agreement between the Surf Test and CMT
Surf Positive	1420	250	1670
Surf Negative	0	330	330
Total	1420	580	2000
Diagnostic indices
Parameters	Values
Sensitivity	100.00
Specificity	56.90
Positive predictive value (PPV)	85.03
Negative predictive value (NPV)	100.00
Accuracy	87.50
Cohen's Kappa (κ)	0.65

Table 5 illustrates the antibacterial activity of selected antibiotics, 6‐gingerol and their combination against Staphylococcus aureus. The combination of enrofloxacin with 6‐gingerol exhibited the highest antibacterial activity, clearly outperforming all individual treatments. Among single agents, enrofloxacin showed the greatest efficacy, followed by gentamicin and standard 6‐gingerol, whereas tetracycline and the extract form of 6‐gingerol demonstrated comparatively lower activity. Overall, combination therapy resulted in a marked enhancement in antibacterial effectiveness.

TABLE 5.

Antibacterial activity of selected antibiotics, 6‐gingerol and their combination against Staphylococcus aureus.

Antibacterial	IZD (mean (mm)± standard deviation)	% Increase vs. extract 6‐gingerol
Enrofloxacin (5 µg)	23.33 ± 0.57	59.14
Gentamicin (10 µg)	21.00 ± 1.00	43.25
Amoxicillin (10 µg)	20.00 ± 1.00	36.43
Tetracycline (30 µg)	15.66 ± 0.57	6.82
Standard 6‐gingerol (1000 µg/mL)	20.33 ± 0.57	38.68
Extract 6‐gingerol (16.64 µg/mL)	14.66 ± 1.15	0.00
Enrofloxacin + 6‐gingerol	38.00 ± 1.00	159.21

Note: Higher inhibition zone diameter (IZD) indicates stronger antibacterial activity.

Table 6 presents the minimum inhibitory concentration (MIC) of 6‐gingerol against S. aureus. Bacterial growth was inhibited at higher concentrations and gradually appeared as the concentration decreased, indicating a concentration‐dependent effect. The MIC was identified at the lowest concentration where complete inhibition was observed, confirming the antimicrobial potential of 6‐gingerol.

TABLE 6.

MIC of 6‐gingerol against Staphylococcus aureus.

Well No.	6‐Gingerol concentration (µg/mL)	Bacterial growth
1	25	Not detected
2	12.5	Not detected
3	6.25	Not detected
4	3.125	Not detected
5	1.5625	Detected
6	0.78125	Detected
7	0.390625	Detected
8	0.1953125	Detected
9	0.09765625	Detected
10	0.048828125	Detected
11 (growth control)	0
12 (positive control)	0	Detected
Estimated MIC
Minimum inhibitory concentration (MIC)	3.125 µg/mL

Table 7 shows the ranking of treatments based on antibacterial activity. The combination treatment was ranked highest, indicating superior efficacy compared to all other treatments. Among individual agents, antibiotics generally ranked higher than 6‐gingerol alone, while the extract form showed the lowest activity. The grouping pattern further confirmed statistically significant differences among treatments.

Table 8 presents the Pearson correlation analysis among key variables. A strong negative correlation was observed between concentration and bacterial growth, indicating that increasing concentration effectively reduced growth. In contrast, strong positive correlations were observed between antibiotic use and IZD, as well as for combination treatments, highlighting their enhanced antibacterial effects.

TABLE 8.

Pearson Correlation Analysis.

Variables	Correlation (r)	Interpretation
Concentration vs. Growth	−0.95	Strong negative correlation
Antibiotic vs. IZD	0.88	Strong positive correlation
Combination effect	0.92	Very strong correlation

Table 9 summarizes pairwise comparisons of IZDs among treatments. The combination therapy consistently showed the greatest differences when compared with individual treatments, indicating its superior antibacterial performance. Differences among individual antibiotics were comparatively smaller, reflecting moderate variation in their effectiveness.

TABLE 9.

Pairwise Mean Differences in Inhibition Zone Diameter.

Comparison	Mean difference (mm)
Combination vs. enrofloxacin	14.67
Combination vs. gentamicin	17.00
Combination vs. amoxicillin	18.00
Combination vs. tetracycline	22.34
Combination vs. standard 6‐gingerol	17.67
Combination vs. extract 6‐gingerol	23.34
Enrofloxacin vs. gentamicin	2.33
Gentamicin vs. tetracycline	5.34

4. Discussion

The present findings provide an integrated evaluation of mastitis screening methods and antimicrobial interventions against Staphylococcus aureus, one of the most important mastitis‐associated pathogens in dairy animals (Muça et al. 2026). Collectively, the results indicate that rapid field diagnosis combined with optimized antimicrobial strategies—particularly combination therapy involving enrofloxacin and 6‐gingerol—may significantly improve mastitis management. These findings are highly relevant because S. aureus mastitis remains difficult to control due to biofilm formation, intracellular persistence and increasing antimicrobial resistance (Rasheed et al. 2023; Javed et al. 2024). Recent literature also emphasizes the need for improved diagnostics and novel adjunct therapies in dairy medicine (Muzammil et al. 2022; Javed et al. 2023; Ramuada et al. 2024; Mustafa et al. 2025).

The equal distribution of milk samples between the Civil Veterinary Hospital (Chargano Chowk) and the Veterinary Teaching Hospital, The University of Agriculture, Peshawar, strengthens the representativeness of the dataset by minimizing location bias. Balanced sampling from two independent veterinary centres increases external validity and suggests that the observed diagnostic and antimicrobial patterns are not restricted to a single facility. This is particularly relevant in mastitis studies, where management practices, hygiene status and antimicrobial usage can vary substantially between institutions. Recent mastitis surveillance studies indicate that environmental conditions, milking hygiene, herd size and regional antibiotic practices strongly influence mastitis prevalence and bacterial resistance profiles (Iraguha et al. 2026). Therefore, using two separate veterinary institutions increases the generalizability of the present findings for district Peshawar and surrounding dairy systems.

The use of CLSI interpretive criteria ensures that susceptibility testing was standardized according to internationally accepted breakpoints. Variation in breakpoint values among antibiotics reflects differences in pharmacodynamics, diffusion rates in agar and clinically achievable serum/tissue concentrations. For example, fluoroquinolones such as enrofloxacin often have distinct interpretive thresholds because of their concentration‐dependent killing and excellent tissue penetration, whereas tetracycline breakpoints differ due to its primarily bacteriostatic action. The presence of intermediate categories for selected drugs also indicates that some antimicrobials possess a narrower transition range between susceptibility and resistance, which is important for treatment decision‐making (Wang et al. 2025).

The Surf test demonstrated perfect sensitivity relative to the CMT, meaning it successfully identified all positive mastitis samples. This is highly desirable in herd‐level screening because false negatives may allow infected animals to remain untreated, increasing production losses and pathogen transmission. Although specificity was moderate, indicating some false positives, such over‐detection may be acceptable in preliminary screening programs where confirmatory testing follows (Iraguha et al. 2026). Thus, the Surf test may represent a practical, economical substitute for routine field surveillance in Pakistan. A recent review on bovine mastitis diagnostics confirms that low‐cost field tests remain highly valuable in developing dairy systems where automated SCC counters are unavailable (Ramuada et al. 2024).

The substantial Cohen's kappa agreement between the Surf test and CMT indicates strong consistency between methods. This suggests that the Surf test may serve as a practical low‐cost alternative for field conditions, especially in resource‐limited areas. Similar observations have been reported in developing dairy systems where household detergents or surfactants have shown acceptable screening value due to their ability to lyse somatic cells and react with DNA/protein‐rich mastitic milk, producing gel formation analogous to the CMT reaction (Leach et al. 2008).

The strongest antibacterial effect against Staphylococcus aureus was observed with the enrofloxacin + 6‐gingerol combination therapy, followed by enrofloxacin alone, gentamicin, standard 6‐gingerol, tetracycline and crude extract. This pattern is biologically logical and reflects the different mechanisms of action and resistance profiles of the tested agents. Enrofloxacin acts by inhibiting DNA gyrase and topoisomerase IV, thereby rapidly blocking bacterial DNA replication. Its superior single‐agent activity suggests that the isolates remained susceptible to fluoroquinolone treatment. Gentamicin exerts its antibacterial action by binding to the 30S ribosomal subunit, leading to mistranslation and bacterial death; however, its uptake may decline in low‐oxygen or inflamed tissues, which may explain its slightly lower efficacy compared with enrofloxacin. The lower activity of tetracycline likely reflects widespread resistance mechanisms such as efflux pumps, ribosomal protection proteins and enzymatic inactivation. The finding that purified 6‐gingerol outperformed crude extract indicates that concentration and purity of the active phenolic compound are critical determinants of antibacterial activity. Recent experimental studies confirmed that 6‐gingerol possesses measurable antibacterial effects against S. aureus and other pathogens, supporting the present findings (Elfaky et al. 2024).

The enhanced activity of the enrofloxacin + 6‐gingerol combination likely reflects synergistic mechanisms, as also reported by Sahoo et al. (2024), who demonstrated that 6‐gingerol acted as an effective adjuvant by enhancing the susceptibility of multidrug‐resistant Klebsiella pneumoniae to colistin. This suggests that 6‐gingerol may similarly potentiate enrofloxacin activity against Staphylococcus aureus through complementary antibacterial mechanisms. As a lipophilic compound, 6‐gingerol can disrupt bacterial membrane integrity, increasing membrane permeability (Elfaky et al. 2024). This membrane damage may facilitate greater intracellular penetration of enrofloxacin, thereby improving its antibacterial effect. In addition, many phytochemicals are known to inhibit bacterial efflux systems, allowing antibiotics to remain inside the cell for longer periods (AlSheikh et al. 2020). S. aureus mastitis frequently involves biofilm formation within mammary tissue, and ginger‐derived compounds may interfere with quorum sensing and biofilm development, rendering bacterial cells more vulnerable to treatment (Shehata et al. 2024). Furthermore, while enrofloxacin disrupts DNA replication, 6‐gingerol simultaneously disturbs membrane function and oxidative balance (Li et al. 2019), producing multi‐target stress that overwhelms bacterial defence systems. Recent studies reported synergistic use of 6‐gingerol with conventional antibiotics against multidrug‐resistant bacteria, strongly supporting this interpretation (Molzahn et al. 2026).

The MIC findings demonstrated a clear concentration‐dependent response, with complete growth inhibition at higher concentrations and progressive regrowth as the concentration declined. This is expected for phytochemicals because they often require threshold concentrations to destabilize membranes, inhibit metabolic enzymes and impair virulence factors. Recent work also described dose‐dependent antibacterial activity of 6‐gingerol against both Gram‐positive and Gram‐negative pathogens (Alfuraydi et al. 2024). Therefore, the present MIC data validate the genuine antimicrobial potential of 6‐gingerol rather than incidental inhibition.

The ranking results statistically confirmed the order of efficacy as Combination > Enrofloxacin > Gentamicin > 6‐Gingerol > Tetracycline > Extract. This suggests that phytochemicals alone may not replace conventional antibiotics, but they can significantly enhance their activity (Khare et al. 2021). Modern antimicrobial research increasingly favours such antibiotic adjuvant strategies to reduce resistance pressure and restore the efficacy of existing drugs.

The strong negative correlation between concentration and bacterial growth confirms classical dose‐response pharmacology, where increasing concentration suppresses microbial proliferation. The positive correlation between treatment type and IZD indicates that stronger therapies consistently produced larger bacterial clearance zones. These findings support the biological consistency of the agar diffusion assay used in the present study. The greatest pairwise differences were observed between combination therapy and all single treatments, indicating that the improvement was not marginal but statistically meaningful. Smaller differences among antibiotics suggest relatively similar baseline efficacy, whereas the addition of 6‐gingerol created a distinct therapeutic advantage. These findings are highly relevant for bovine mastitis management. The Surf test may offer an inexpensive option for rapid herd‐level screening, while the enrofloxacin + 6‐gingerol combination may improve cure rates against S. aureus. Combination therapy may also allow lower antibiotic doses, thereby reducing drug residues in milk and limiting resistance development. Plant‐derived compounds such as 6‐gingerol may therefore emerge as valuable veterinary antimicrobial adjuvants. Overall, the present results indicate that combining conventional antibiotics with natural bioactive compounds represents a promising strategy for improving mastitis treatment and combating antimicrobial resistance.

5. Conclusion

Overall, the results support a dual strategy for mastitis control: efficient screening through Surf testing and improved antimicrobial therapy through antibiotic‐phytochemical combinations. The strong performance of enrofloxacin + 6‐gingerol suggests a promising alternative approach against S. aureus, particularly in the era of increasing antimicrobial resistance. Further in vivo studies, toxicity assessments and pharmacokinetic evaluations are recommended before routine clinical application.

Author Contributions

Maria Khan: methodology, investigation, data curation. Arshad Zahoor: conceptualization, methodology, investigation, data collection. Shabana Naz: data curation, writing initial draft. Caterina Losacco: critical revision of the manuscript. Sohail Ahmad: data analysis, interpretation, critical revision of the manuscript. Ibrahim A. Alhidary: funding. Luciana Rossi: writing, critical revision of the manuscript. Rifat Ullah Khan: project administration, validation, writing – review and editing. Huda A. Alqahtani: funding, editing. All authors have read and approved the final version of the manuscript.

Funding

This study was supported by the PSF PROJECT NO. PSF/NSLP/KP‐UAP (918) ENTITLED “Exploring the In‐vitro and In‐vivo antibacterial role of Herbal Medicine (6‐Gingerol) to Treat Mastitis in small ruminants”. The authors are thankful to the Ongoing Research Fund (ORF‐2026‐1450) King Saud University, Riyadh, Saudi Arabia.

Ethics Statement

This study was approved by the ethical committee on animal rights and welfare, The University of Agriculture, Peshawar, College of Veterinary Science, Faculty of Animal Husbandry & Veterinary Science (CVS/243/2024).

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data are available on request from the authors.