Open Veterinary Journal, (2026), Vol. 16(4): 2521-2528

Research Article

10.5455/OVJ.2026.v16.i4.52

Gene-based detection of antibiotic resistance and virulence determinants in dairy-associated bacteria and their molecular differentiation using random amplified polymorphic DNA-PCR typing

Hind Tahseen Ibrahim¹, Noor Adil Abood², Orooba Meteab Faja^3* and Ziad M. Alkhozai⁴

¹Department of Medical Physics, College of Science, Alfarahidi University, Baghdad, Iraq

²College of Pharmacy, AL-Nahrain University, Baghdad, Iraq

³Department of Public Health, College of Veterinary Medicine, University of Al-Qadisiyah, Al-Diwaniyah City, Iraq

⁴College of Science, University of AL-Qadisiyah, Al Diwaniyah, Iraq

*Corresponding Author: Orooba Meteab Faja. Department of Public Health, College of Veterinary Medicine, University of Al-Qadisiyah, Al-Diwaniyah City, Iraq. Email: orooba.faja [at] qu.edu.iq

Submitted: 28/11/2025 Revised: 06/04/2025 Accepted: 19/03/2026 Published: XX/XX/XXXX

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ABSTRACT

Background: Dairy products are regularly implicated as reservoirs for various bacterial contaminants capable of harboring antibiotic resistance and virulence genes. The spread of these genes is of major concern to public health in the presence of virulent and multidrug-resistant strains that persist in various processing locations.

Aim: This study aimed to identify antibiotic resistance and virulence genes in bacterial isolates obtained from cheese, yogurt, and cream and assess their molecular diversity using Random Amplified Polymorphic DNA polymerase chain reaction (RAPD-PCR).

Methods: Samples of 290 dairy products were collected over a continuous 67-day period from various local markets and retail outlets. These included 98 cheese samples, 95 yogurt samples, and 97 cream samples. For each sample, 10 g or 10 ml of each sample was added to 90 ml of sterile buffered peptone water and homogenized. These were then serially diluted (10^-¹–10^-5). Aliquots of each dilution were placed into selective and differential culture media to recover both gram-negative and gram-positive bacteria. They were incubated under aerobic conditions at 37°C for 24–48 hours. Presumptive colonies were selected from the macroscopic examination and further biochemical tests. After purification, sub-culturing portions of the isolates were stored in nutrient broth containing 20% glycerol and frozen
at −20°C.

Results: Among 290 total samples, 136 bacterial isolates were recovered and identified: 19 of Escherichia coli, 19 of Staphylococcus aureus, 16 of Listeria monocytogenes, 18 of Pseudomonas aeruginosa, and 15 of Salmonella enterica, among others. Hemolysin genes were detected among 47.79% of the isolates, with the highest rates for the cheese samples at 54.34%. Genes for adhesion were detected in 51.47% of samples, with isolates for the cream samples being the highest at 58.69%. Multiple bacterial isolates were found to demonstrate the presence of the virulence factors in combination. RAPD-PCR with 80% similarity succeeded in splitting the Gram-negative isolates into 8 and the Gram-positive ones into 4 distinct groups, demonstrating significant molecular variability and likely indicating several contamination points in the dairy industry.

Conclusion: This study clearly demonstrated the significant presence of virulence factors and antibiotic-associated genes for the dairy industry bacteria, including the genetically heterogeneous nature of the bacteria as analyzed by RAPD-PCR, calling for greater sanitary handling of dairy and ongoing molecular monitoring to reduce the presence of virulence-carrying bacteria in dairy for human consumption.

Keywords: Adhesion genes, Antibiotic-resistance genes, Dairy bacteria, RAPD-PCR.

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Introduction

The contamination of dairy products by pathogenic and opportunistic bacteria remains a potential public challenge worldwide, especially with the increasing identification of gene-encoded virulence and antibiotic resistance in dairy products. Recent studies have indicated that dairy environments have added to the reservoirs of antimicrobial resistance (AMR) plasmids and other mobile genetic elements (Madec and Haenni, 2018). Modern dairy processing systems, even with advanced improvements in food hygiene, are still susceptible to contamination due to biofilm-forming and stress-adapted bacteria that can survive pasteurization and other biosecurity measures in food processing (Martin et al., 2021). The increased use of antimicrobial drugs in food animals has also fueled the spread of foodborne pathogenic bacteria and complicated the public health challenge of AMR (Manyi-Loh et al., 2018). The combination of these issues has created the imperative of the surveillance of dairy products to identify potential virulence factors, such as linoleate, that augment pathogenicity and facilitate the potential for host invasion (Arciola et al., 2012; González-Fandos et al., 2021).

Hemolytic genes such as hlyA in Listeria monocytogenes are vital for the intracellular survival cycle of the microbe to escape phagosome capture and colonize tissues (Radoshevich and Cossart, 2018). On the other hand, gene sets encoding adhesins greatly promote bacterial attachment and biofilm formation, both of which are essential for the long-term contamination of dairy equipment and processing surfaces (Arciola et al., 2012; Mahmood and Atyah, 2021). Certain species, such as Proteus mirabilis, exhibit coordinated expression of biofilm and virulence genes in addition to resistance determinants, suggesting sophisticated adaptive mechanisms under pressure (Mishu et al., 2022). Studies involving clinical and foodborne isolates have shown that antibiotic resistance genes are often linked to plasmids and integrons that provide portability among bacteria, including genes that confer resistance to chloramphenicol, aminoglycosides, and beta-lactams (Schwarz et al., 2019).

The Random Amplified Polymorphic DNA polymerase chain reaction (RAPD-PC) technique and other similar tools have emerged as highly efficient methods for differentiating bacterial isolates according to their genetic variations to identify and detect clonal relationships within dairy chains. RAPD-PCR clustering achieved optimum performance and comparative differentiation of foodborne bacteria in species and sources of contamination, attributed to several classical typing methods (Mo et al., 2015). Furthermore, the prevalent antimicrobial resistance trends to erythromycin, gentamicin, and tetracycline strengthened the concern of dairy products as vehicles of transmission for resistant bacteria, bolstering the increasing concern of antimicrobial resistance in dairy (Manyi-Loh et al., 2018; WHO , 2019). The findings of the recently available literature indicate the importance of in-depth studies of the contamination to understand the virulence and the resistance genes, to profile their genotypes, and to derive a tailored solution to the public health threats provoked by the consumption of contaminated dairy products.

The main goal of this research was to identify antibiotic resistance and virulence genes in bacterial isolates obtained from cheese, yogurt, and cream, and to assess their molecular diversity using RAPD-PCR.

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Materials and Methods

Sample collection and bacterial isolation

To document different phases in the dairy supply chain, a total of raw milk, yogurt, cream, soft cheese, and other fermented dairy products were aseptically gathered from various analytics markets and retail stores. After being transported on ice, each sample was processed in the lab in a time frame of 1–2 hours from the time of collection. Each dairy sample, weighing or measuring 10 g or milliliters, respectively, was homogenized in sterile buffered peptone water (Cat No. CM0509; Oxoid, UK) and vortexed for 2 minutes. Culture on selective and differential media for serial dilutions (10^-¹–10^-5) was performed on MacConkey Agar (HiMedia, India; Cat No. M081), Blood Agar Base (HiMedia, India; Cat No. M073), and XLD agar (Oxoid; CM0469), as well as other media: Mannitol Salt Agar for staphylococci (HiMedia; M118) and Bile Esculin Agar for enterococci (Oxoid; CM0888). Following 24–48 hours of incubation at 37°C, the colonies were selected based on their morphology and pigment formation, hemolytic activity, lactose fermentation, and biochemical composition profile, which were examined using oxidase (Liofilchem, Italy; Cat No. 81020) and catalase tests. The various isolated colonies were purified by repeated streaking, and for future molecular analysis, they were stored in 20% glycerol at −20°C.

Extraction of genomic DNA

Using the GeneJET Genomic DNA Purification Kit from Terrir O Feishher (K0721), the genomic DNA of the overnight cultures that had grown in the nutrient broth (HiMedia, M002) was extracted, in accordance with the manufacturer’s instructions. In summary, the bacterial pellets were lysed with lysis buffer and RNase A, and the solutions were then incubated at 65°C for 10 minutes before being placed in purification columns to remove proteins and polysaccharides. Once any extraneous cell constituents were removed, DNA was subsequently dehydrated in (nuclease-free) water and then stored at −20°C (this being the temperature of other scientific equipment). The concentration and purity of the DNA were checked before and after storage using a NanoDrop 2,000 spectrophotometer (Thermo Fisher, USA). A260/280 ratios between 1.7 and 1.9 were then confirmed. DNA was checked by running 5 µl of the eluted DNA on a 1% agarose gel prepared with UltraPure agarose (Invitrogen, USA, 16,500–500) and was subsequently stained with ethidium bromide (Sigma-Aldrich, USA, E1510).

Detection of pathogenic genes by PCR

To ascertain the potential pathogenicity of the isolates, amplification of species-specific virulence factors was performed (Table 1). The genes of interest were invA for Salmonella enterica, hlyA for Listeria monocytogenes, ureC for P. mirabilis, stx1 and stx2 for Escherichia coli, exoS for Pseudomonas aeruginosa, entB for Klebsiella spp, and cylA for Enterococcus spp. The primers and the corresponding targets are shown in Table 2. The PCR amplification procedures were as previously outlined, and the annealing temperatures were customized for each gene according to previously calculated melting temperatures. The amplification products were subjected to electrophoresis in 1.5%–2% agarose gels, depending on the expected amplicon size, and were captured on a UV transilluminator system (UVP, USA).

Table 1. Pritmer sequences of the virulence genes.

Table 2. RAPD-PCR primers for molecular typing (MTM).

RAPD-PCR genomic fingerprinting

Molecular typing of isolates analyzed potential routes of contamination and the clonality of isolates by employing RAPD-PCR. Two primers used (Table 5). for this analysis, OPA-02 (5’-TGCCGAGCTG-3’) and OPA-10 (5’-GTGATCGCAG-3’) (Operon Technologies, USA). Each RAPD-PCR reaction (25 µl) consisted of 12.5 µl of the DreamTaq Hot Start PCR Master Mix (Cat No. K9021; Thermo Fisher, USA), 3 µl of one primer (20 pmol), 3 µl of DNA template, and 6.5 µl of nuclease-free water. The cycling conditions were as follows: 95°C for 3 minutes; then 40 cycles, with the 1st step of 94°C for 1 minute, 2nd step of 36°C for 1 minute, and 3rd step of 72°C for 2 minutes; finishing with an extension step of 72°C for 10 minutes. The bands were then analyzed using 1.8% agarose gel and with the aid of GelCompar II software (Applied Math, Belgium), set with UPGMA clustering at 80% similarity. The RAPD profiles served to place the isolates into clades in relation to the diversity at the species and strain levels, as explained in the document.

Table 5. RAPD-PCR clustering profiles of Gram-negative and Gram-positive bacterial isolates based on OPA-02 and OPA-10 primers.

Statistical methods

All molecular data, including the frequencies of virulence and resistance genes, were analyzed using the Statistical Package for the Social Sciences v. 26 (IBM, USA). The chi-square and Fisher’s exact tests were performed to compare the gene frequencies among the species. The significance of the tests was determined using p < 0.05. The RAPD similarity matrices were generated using the Pearson correlation coefficient, and the strength of the clustering was evaluated using 1,000× bootstrapping.

Ethical approval

Not needed for this study.

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Results

Bacterial isolation and distribution

Of the 290 dairy samples, 136 bacterial isolates from the dairy samples had pathogenic and opportunistic genera known to have dairy contaminations. The bacterial isolates from the dairy samples were as follows: 19 E. coli, 19 Staphylococcus aureus, 16 Listeria monocytogenes, 18 P. aeruginosa, 15 S. enterica, 14 P. mirabilis, 13 Klebsiella pneumoniae, 11 Enterococcus faecalis, 6 Citrobacter freundii, and 5 Shigella sonnei. Their individual totals are shown in Table 3. Of all the samples, the greatest recovery rate was from the cheese sample (54.34%), cream sample (30.43%), and yogurt sample (15.22%). A considerable range of dairy contamination was found. Verification of the species occurred through identification to confirmation using colony morphology, numerous biochemical tests, and growth on selective media before molecular screenings. Some isolates showed blood beta-hemolysis and a mucoid character in MacConkey agar in addition to other variants, which could mean that the strains were strongly virulent. The first of these notable observations was the relatively simple characterization of the isolates.

Table 3. Distribution of bacterial isolates isolated from dairy products.

Detection of virulence genes

We examined PCR amplifications aimed at virulence-associated genes. We found that all of the isolates showed signs of overlapping virulence-associated gene amplification in at least some other amplification failures. Overall positive rates (confirmed by controls) were >50% for multiple species (particularly L. monocytogenes, Stanford P004637, and L. monocytogenes, Stanford P004637) (Table 4). The hlyA gene in L. monocytogenes was hlyA gene was seen in 62.5% as observed in the electrophoresis image, it was amplified at the expected gene length (Fig. 1A). The invA gene was found in 86.6% of S. enterica isolates, suggesting a possible pathogenic lineage (Fig. 1B). All Proteus mirabilis growing in urea were ureC positive (100% likely due to the ammonia and urea-activity consitosaurs). Pseudomonas aeruginosa showed that approximately 70% of isolates had the exoS gene, which likely contributed to pathogenicity (Fig. 1C); Klebsiella pneumoniae was positive for the sidero-iron genes. A large proportion of E. coli isolates were found to possess the stx1 (42.1%) and stx2 genes (36.8%); some isolates were found to have both genes. CylA, the cytolysin gene, was found to be positive for 72.7% of E. faecalis isolates. In all cases, amplification was specific.

Table 4. Prevalence of virulence-associated genes as determined by PCR.

Fig. 1. RAPD-PCR fingerprinting of bacterial isolates using OPA-02 and OPA-10 primers. Panel A: RAPD banding patterns generated by OPA-02; Panel B: RAPD banding patterns generated by OPA-10; Panel C: Salmonella enterica; Panel D: Enterobacter cloacae; Panel E: Pseudomonas aeruginosa; Panel F: Klebsiella pneumoniae; Panel G: Klebsiella aerogenes; Panel H: Escherichia coli. Panel I: UPGMA dendrogram showing clustering at 80% similarity.

RAPD-PCR molecular typing findings

The application of RAPD-PCR with OPA-02 and OPA-10 primers resulted in patterns of high polymorphism and easy discrimination of different isolates from different species and within the same species. With the OPA-02 primer, bands spanning 250–1,750 bp were produced, while with OPA-10, bands spanning from 300 to 2,000 bp were produced . Using the UPGMA clustering method, 8 main clusters were identified for gram-negative isolates and 4 for the Gram-positive isolates. This indicates extensive genetic diversity and polymorphism within the population. The E. coli isolates were assigned to 3 different RAPD clusters, indicating the existence of more than one source of contamination existed and there was no clonal spread. The S. aureus isolates were divided into 2 clusters that were quite close to each other genetically, probably due to the close dissemination of the dairy farm environment. The L. monocytogenes isolates demonstrated the highest diversity within species clustering than any other and having 3 separate clusters in which no clearly dominant clone was found, while there was a close clustering of P. aeruginosa, indicating that it shared the same environmental factors. The RAPD patterns were somewhat in agreement with the patterns of the virulence genes in the isolates: isolates were in closer clusters and contained more virulence genes, whereas the virulence-gene-negative isolates were more spread apart and in more separate clusters. The RAPD results showed that molecular fingerprinting was valuable in revealing the intricate relationships between contamination events and strain relationships at the dairy chain.

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Discussion

The results on the prevalence of virulence-associated genes obtained in the current work are also supported by the latest molecular surveys on dairy-borne pathogens. For instance, in the work of Fougy et al. (2020), hlyA, which shows the potential of these strains of Listeria monocytogenes obtained from raw milk and dairy apparatus, was also detected in 62.5% of these strains and was similarly associated with the intensity of hlyA pathogenicity. This also applies to Elmonir et al. (2021), who detected 86.6% invA in S. enterica and similarly documented the prevalence of invA above 80% in dairy products. Unlike the above references, the prevalence of stx1 and stx2 among the E. coli isolates in this study was lower than that reported by Rani et al. (2021) on contaminated dairy desserts, indicating some differences in the geographic area and products regarding the dissemination of the shiga-toxin genes. The detection of ureC in the isolates of P. mirabilis was also documented by Abd El-Tawab et al. (2020), indicating the presence of this virulence factor in these strains and others associated with foodborne disease.

In contrast to the more limited diversity reported among dairy-associated and soil-associated E. coli and Klebsiella spp. (Abebe et al. 2020), the current study showed a pattern of extensive RAPD heterogeneity, especially among the gram-negative isolates. High RAPD diversity suggests that the dairy-processing chain suffers from diffuse bacterial contamination. This observation is similar to that of Borges et al. (2021), who reported that S. aureus isolates from bulk tank milk and cheese contained at least 2 RAPD types. This observation parallels the clustering results of isolated Gram-positive bacterial species from the current study, where 4 clusters were formed at 80% similarity. In contrast to the relatively clustering results of P. aeruginosa, Nisar et al. (2021) showed that Pseudomonas spp. from the environment showed high RAPD variation. This suggests that the Pseudomonas spp isolated in this dataset were sampled from a similar and more homogeneous environment that is often used in the dairy industry, such as refrigerating units or water reservoirs that are often used to supply dairy vendors.

The presence of multiple virulence markers in a single isolate has become a concern, as noted by Sharma et al. (2022). These authors demonstrated that dairy-associated bacteria with 2 or more virulence genes exhibited greater pathogenicity and increased biofilm production. This trend mirrored the current study, where E. coli, P. aeruginosa, and E. faecalis were frequently found to carry 2 virulence determinants. The clustering relationships observed in RAPD analysis further corroborated the findings of Ghatak et al. (2021), who noted that isolates with multiple virulence attributes tended to cluster in more closely related groups, indicating that these markers remain genomically stable. The lower detection of virulence genes in K. pneumoniae in this study, compared to Khoshbakht et al. (2020), suggests some potential inter-regional variation in the virulence plasmid carriage.

Identifying the same pathogenesis traits in some species and the greater survival of these species in dairy-related food processing indicates the presence of host-adapted pathogenic mechanisms and strategies. The long maturation periods of the cheese, the considerable manual processing, and the exposure to the post-pasteurization environment are the most plausible explanations for the high prevalence of such traits and the survival of the bacteria in the cheese. The similarity of the isolates in the different RAPD-PCR samples stems from the overlaps of the contamination sources in tasting, processing, storage, or retail, as all the samples appear to have the same contamination and are still supported by the evidence of no contamination on several isolates.

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Conclusion

Research results show that bacteria from cheese and other dairy products have a higher number of virulence-associated genes in dairy bacteria, and considerable genetic variation suggests more than one point of contamination in the dairy food supply system. The detection of virulence factors that hinder the expression of hlyA, invA, ureC, and exoS genes indicated the need for surveillance of the pathogenic potential of the isolate. Further, virulence factor genes in food and dairy products and continuous survey for dairy product isolates showed the pathogenic potential of the exoS gene with its exoS virulence factor, ureC dairy products, and the virulence exoS of microbiological products, indicating a need for surveying the pathogenic potential of dairy products and virulence factors and the exoS of microorganisms and genetic variation. Within this variability. Thus, potential bacterial populations from dairy products in food pathogenic exoS of microbiological products with the capability to persist in pathogens in exoS microbiological food products and the exoS in food pathogens.

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Acknowledgment

The authors would like to express their gratitude to the College of Veterinary Medicine for providing laboratory facilities and technical support throughout the study.

Conflict of interest

The authors declare that there are no conflicts of interest existed in this work.

Funding

This research was self-funded by the authors with no external financial support.

Authors’ contributions

All authors have contributed to this study.

Data availability

Data are available upon request from the corresponding author.

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