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Article

Antimicrobial Resistance Gene Patterns in Traditional Montenegrin Njeguški Cheese Revealed by qPCR

1
Dipartimento di Scienze Agrarie, Alimentari ed Ambientali, Università Politecnica delle Marche, Via Brecce Bianche, 60131 Ancona, Italy
2
Centre of Excellence for Digitalisation of Microbial Food Safety Risk Assessment and Quality Parameters for Accurate Food Authenticity Certification, University of Donja Gorica, 81000 Podgorica, Montenegro
3
Dipartimento di Scienze Biomediche e Sanità Pubblica (DSBSP), Università Politecnica delle Marche, Via Tronto 10/A, 60126 Ancona, Italy
*
Author to whom correspondence should be addressed.
Genes 2025, 16(9), 1089; https://doi.org/10.3390/genes16091089
Submission received: 7 August 2025 / Revised: 6 September 2025 / Accepted: 10 September 2025 / Published: 16 September 2025
(This article belongs to the Section Molecular Genetics and Genomics)

Abstract

Background/Objectives: This study was aimed to investigate the safety profile of traditional Montenegrin Njeguški cheese by quantifying genes associated with resistance to clinically important antibiotics. Methods: Samples of Njeguški cheese were sourced from three artisan producers in Montenegro, identified as A, B, and C, with three individual batches selected per producer. Quantitative PCR (qPCR) was performed on bacterial DNA extracted directly from samples to detect genes encoding resistance to macrolide–lincosamide–streptogramin B (MLSB) [erm(A), erm(B), erm(C)], vancomycin (vanA, vanB), tetracyclines [tet(M), tet(O), tet(S), tet(K), tet(W)], β-lactams (mecA, blaZ), aminoglycosides [aac (6′)-Ie aph (2″)-Ia], and carbapenems (blaKPC, blaOXA-48, blaNDM-1, blaGES, and blaVIM). Results: Among the MLSB resistance genes, erm(B) was detected in all samples, erm(C) was present only in those from producer B, while erm(A) was found exclusively in batch 3 from producer C. Tetracycline resistance genes were widely distributed, except for tet(O), which was absent in batch 3 from producers A and B. Regarding β-lactam resistance, both blaZ and mecA were consistently detected across all samples, with statistically significant differences observed between producers. None of the samples tested positive for vancomycin resistance genes or the aminoglycoside resistance gene, regardless of producer. Among the carbapenemase genes analyzed, blaNDM-1 was the only one detected, found in most samples from producers B and C. Conclusions: This research provides the first risk assessment of artisanal and commercial Njeguški cheese regarding antimicrobial resistance genes. The findings offer valuable insights to enhance the microbiological safety of traditional Montenegrin cheeses, supporting consumer confidence in local and international markets.

1. Introduction

Over the past few decades, bacteria have increasingly developed resistance to antimicrobials, largely as a result of the selective pressure caused by their wide use and misuse in human medicine, agriculture, aquaculture, and animal farming [1,2,3,4,5,6]. Antimicrobial resistance (AMR) poses a significant threat to public health, with an increasing incidence of treatment failure in infections caused by multidrug-resistant bacterial strains [6,7]. As highlighted by Caniça et al. [5,8], AMR is a complex and dynamic network with resistant bacteria and resistance genes capable of spreading globally across diverse environments, including human, animal, and ecological settings. This is primarily because AMR genes are frequently carried on mobile genetic elements like plasmids and transposons, which facilitate their transfer between bacteria and contribute to the genomic adaptability of bacterial populations. In addition, the transfer of antimicrobial-resistant microorganisms and/or resistance genes to humans through the food chain is an issue of growing concern. Indeed, the food chain is widely acknowledged as one of the primary pathways through which AMR spreads to the human population [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16]. Specifically, the consumption of food can introduce bacteria and their AMR genes into the human gastrointestinal tract. Viable bacteria that survive the gastric barrier, as well as free bacterial DNA capable of transforming the human gut microbiota, may contribute to the development of the AMR gene reservoir, thereby facilitating the spread of AMR [1,4]. The emergence of carbapenem-resistant bacteria has further worsened the situation, as carbapenems are regarded as the last line of defense for treating severe infections caused by multidrug-resistant Gram-negative bacteria [5,17].
At the same time, the development and application of rapid, sensitive, and reliable molecular methods for detecting AMR genes in complex food matrices remains a significant challenge [3,9,10]. Among molecular techniques, qPCR provides an effective tool for monitoring the spread of AMR in food products. It also supports the implementation of good manufacturing practices in food production and helps trace spreading to other environments.
Among foods, animal-derived and fermented products are the primary potential vehicles for the diffusion of AMR along the food chain to consumers [1,6,15]. This is due to their typically high bacterial loads, the use of starter cultures, and to their possible cross-contamination with intestines of farm animals [1,15]. Specifically, fermented dairy products have been found strongly linked to the dissemination of AMR genes [18,19,20].
Njeguški cheese is a traditional Montenegrin hard, full-fat cheese originally made from raw sheep’s milk. It is well-known and highly appreciated, despite being relatively understudied [21,22,23]. In our previous study by Cardinali et al. [21], artisanal Njeguški cheese was thoroughly characterized with respect to its microbiota, physicochemical and morpho-textural properties, biogenic amine content, and volatilome. To complete the characterization of Njeguški cheese, the present study aims to assess its safety profile by quantifying genes encoding resistance to six classes of antibiotics commonly used in both animal husbandry and clinical practice, namely tetracyclines, macrolide–lincosamide–streptogramin B (MLSB), vancomycin, glycopeptides, β-lactams, and carbapenems (the latter used exclusively in clinical settings). This investigation employs a molecular approach based on qPCR analysis of bacterial DNA directly extracted from cheese samples. Specifically, the target genes namely tet(M), tet(O), tet(K), tet(W), tet(S), erm(A), erm(B), erm(C), vanA, vanB, aac (6′)-Ie aph (2″)-Ia, mecA, and blaZ were selected as commonly found in foodborne commensal such as lactic acid bacteria (LAB) as well as in human pathogens [12]. The five carbapenemase encoding genes, blaNDM−1, blaVIM, blaGES, blaOXA−48, and blaKPC, often referred to as the “big five” due to their widespread prevalence, are primarily found within the genomes of Enterobacteriaceae, Pseudomonas spp., and Acinetobacter spp., which are commonly present in fermented foods of animal origin [24]. The previous study on Njeguški cheese [21] reported high loads of presumptive lactobacilli and lactococcci, both exceeding 8 log cfu g−1, along with relatively high counts of Enterobacteriaceae and Pseudomonas spp., exceeding 5 log cfu g−1. These findings justify the present study, which aims to further highlight safety and health issues related to the production of this cheese.

2. Materials and Methods

2.1. Samples Collection and Microbial DNA Extraction

Samples collection and microbial DNA extraction were carried out as previously described by Cardinali et al. [21]. In detail, 18 Njeguški cheese samples were collected in duplicate from three different production batches (b1, b2, and b3) produced by three independent Montenegrin artisanal cheesemakers (A, B, and C) between May and July 2023. This sampling scheme was designed to capture both inter-producer variability, associated with differences in artisanal practices and milk sources, and intra-producer variability across production batches. Considering the limited production scale of Njeguški cheese and the practical constraints of collection, it provided a feasible yet representative framework for characterizing the AMR gene patterns of this traditional product. Each cheese weighed approximately 1 kg, with an average diameter of 14 cm and a height of 3.5 cm. In line with traditional practices, all cheeses were prepared primarily from sheeps’ milk (70%) with a minor inclusion of cow’s milk (30%), using animal rennet and marine salt, and were ripened for approximately 30 days prior to sampling.
After collection, cheeses were sealed in sterile vacuum-packaged polyethylene bags, transported to Italy by express courier under refrigerated conditions in insulated iceboxes, and stored at 4 °C upon arrival until processing. Samples were stored for no longer than 24 h prior to DNA extraction.
For microbial DNA extraction, 10 g of each cheese were aseptically weighed and homogenized in 90 mL of sterile peptone water (1 g L−1; Oxoid, Milan, Italy) using a Stomacher 400 Circulator (VWR International PBI, Milan, Italy) at 260 rpm for 5 min. From each homogenate, 1 mL aliquots corresponding to the 10−1 dilution were centrifuged at 14,000 rpm for 10 min at room temperature. The supernatants were discarded, and the resulting pellets were subjected to DNA extraction. Total microbial DNA was extracted using the E.Z.N.A. Soil DNA Kit (Omega Bio-Tek, Norcross, GA, USA) according to the manufacturer’s protocol, which incorporates both mechanical disruption and chemical lysis steps to optimize bacterial DNA recovery.
DNA concentrations were determined with the Qubit dsDNA HS Assay Kit (Life Technologies, Milan, Italy), while purity was assessed by spectrophotometric absorbance ratios (A260/A280) using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA).
To confirm successful extraction of bacterial DNA, 2 µL of each extract were used as template for PCR amplification of the V3–V4 region of the 16S rRNA gene with the primer set and cycling conditions described by Klindworth et al. [25]. Positive and negative controls were included in each PCR run to ensure reliability of amplification, and the products were visualized by electrophoresis on a 1.5% (w/v) agarose gel.

2.2. qPCR Protocols

To quantify genes conferring resistance to clinically relevant antibiotics, qPCR was conducted targeting MLSB resistance genes [erm(A), erm(B), erm(C)], vancomycin resistance genes (vanA, vanB), tetracyclines resistance genes [tet(M), tet(O), tet(S), tet(K), tet(W)], β-lactams resistance genes (mecA, blaZ), aminoglycosides resistance gene [aac (6′)-Ie aph (2″)-Ia], and carbapenems resistance genes (blaKPC, blaOXA-48, blaNDM-1, blaGES, and blaVIM) as previously described by Garofalo et al. [11] and Milanović et al. [26]. Calibration curves were established using serial tenfold dilutions of genomic DNA from 18 reference bacterial strains, each carrying one of the AMR genes under investigation. Assays were run on a CFX Connect Real-Time PCR Instrument (Bio-Rad, Hercules, CA, USA), which computed amplification efficiencies (E) and correlation coefficients (R2) based on the slopes of the calibration curves. These curves ranged from below 1 to 7 log gene copies per reaction, and the lowest dilution point with consistent amplification across triplicates was taken as the detection threshold for each gene. Absolute quantification was performed by analyzing sample-derived DNA in parallel with the standard dilutions, with gene copy numbers per reaction calculated from the standard curve slopes. Each qPCR mixture contained: (i) 4 μL of extracted DNA, (ii) 5 μL of Type-it 2X HRM PCR Master Mix (Qiagen, Hilden, Germany); (iii) forward and reverse primers for each AMR gene at the following concentrations: 1000 nM for vancomycin resistance genes, 900 nM for erm(B), tet(K), tet(M), tet(O), tet(S), and mecA, 500 nM for erm(A), blaZ, and aac (6′)-Ie aph (2″)-Ia, 400 nM for erm(C) and tet(W), and 200 nM for carbapenem resistance genes; and (iv) nuclease-free water, to reach a final reaction volume of 10 μL. Amplification of MLSB, tetracycline, β-lactam, aminoglycoside, and vancomycin resistance genes followed a protocol of 5 min at 95 °C, then 40 cycles of 15 s at 95 °C and 30 s at 60 °C. For carbapenem resistance genes, the cycling conditions were 5 min at 95 °C, followed by 35 cycles of 20 s at 95 °C, 45 s at 55 °C, and 30 s at 72 °C. Specificity of amplicons was verified by generating melt curves, incrementally increasing the temperature from 65 °C to 95 °C at 0.2 °C/s. Each run included both no-template controls to exclude contamination and positive controls (genomic DNA from reference strains) to confirm assay performance. Gene copy numbers were determined by comparing sample amplification to the calibration standards, with results expressed as log gene copies per gram of sample. Data were derived from three biological replicates, each run in triplicate, and reported as mean ± standard deviation.

2.3. Statistical Analysis

To assess differences among samples, a one-way analysis of variance (ANOVA) was performed, followed by Tukey–Kramer’s Honest Significant Difference (HSD) test to identify specific group differences at a significance threshold of p < 0.05. Statistical computations were conducted using JMP software (version 11.0.0, SAS Institute Inc., Cary, NC, USA). To investigate overall trends and associations between AMR gene profiles and samples, Principal Component Analysis (PCA) was conducted using the factoextra and ggplot2 packages in R (version 4.4.3). AMR genes consistently below the detection limit in all samples were excluded from the analysis.

3. Results

The concentrations of AMR genes in Njeguški cheese samples, expressed as log gene copies per gram of sample, are detailed in Table 1.
Regarding MLSB resistance genes, a wide variability was observed across samples from different producers or batches. The erm(A) gene was detected exclusively in b3 samples from producer C (4.50 ± 0.14 log gene copies/g). Samples from producer A showed statistically higher levels of erm(B) gene (7.08 ± 0.45 log gene copies/g) compared to producers B and C (6.35 ± 0.23 and 6.20 ± 0.54 log gene copies/g, respectively). Notably, erm(C) gene was detected only in samples from producer B, with values ranging between 4.62 ± 0.17 and 5.32 ± 0.10 log gene copies/g.
Tetracycline resistance genes were broadly distributed across samples, except for b3 from producers A and B, in which tet(O) was not detected. The tet(K), tet(M), and tet(S) genes were the lowest in samples from producer A, whereas the samples from producer C were characterized by the highest levels of tet(W) gene (7.05 ± 0.54 log gene copies/g). The concentration of tet(O) gene ranged from 2.49 ± 1.93 to 4.11 ± 0.50 log gene copies/g, with no statistically significant differences among producers.
Regarding the tested β-lactam resistance genes, both blaZ and mecA genes were consistently detected in all samples. Although intra-producer variation was not statistically significant, inter-producer differences were observed: blaZ levels were the highest in samples from producer B, while mecA concentrations were highest in samples from producer C.
None of the samples tested positive for vancomycin resistance genes (vanA or vanB) or aminoglycoside resistance gene aac (6′)-Ie aph (2″)-Ia, regardless of the producer.
Among carbapenem resistant genes, blaNDM-1 was the only gene detected. This gene was present in most samples from producers B and C, showing mean concentrations of 6.07 ± 0.58 and 4.19 ± 3.27 log gene copies/g, respectively.
PCA was performed to explore the variation in AMR genes profiles among the Njeguški samples. The first two principal components (PC1 and PC2) accounted for 40.2% and 28.7% of the total variance, respectively. The PCA biplot (Figure 1) revealed a clear separation of producers along both axes.
Samples from producer A were distinctly separated from those of producers B and C, primarily along the positive axis of PC1, reflecting elevated levels of erm(B) gene. Conversely, samples from producer C clustered toward the lower PC2 region, correlating with higher levels of tet(O), tet(W), mecA, and erm(A) genes. Samples from producer B displayed a distinct clustering pattern along the negative axis of PC1, primarily influenced by elevated levels of erm(C) and blaZ genes. Of note, the close spatial grouping of samples from the same producer and batch suggests a high degree of batch-level consistency in AMR genes composition within each producer.

4. Discussion

Very recently, Tiedje et al. [16] highlighted the risks associated with the spread of antimicrobial-resistant bacteria and AMR genes in agri-food production systems, emphasizing the urgent need for rapid and effective measures within the One Health framework. This holistic approach underscores the perspective that the environment, animals, plants, food, feed, and humans are interconnected components of a whole system, interacting with and influencing each other through the exchange of AMR genes and antimicrobial-resistant bacteria. Cheese is one of the most widely consumed foods in the human diet and is often associated with health benefits. It is produced through milk fermentation driven by the metabolic activities of LAB, including genera such as Lactobacillus, Streptococcus, Enterococcus, and Leuconostoc. These bacteria can also act as reservoirs of AMR genes, which may be transferred to other bacteria, including pathogenic species [6,20]. Furthermore, factors such as the extensive use and misuse of antibiotics in livestock, inadequate hygiene during food production, improper use of disinfectants, lack of pasteurization, uncontrolled fermentation, food processing conditions involving acidic and osmotic stresses on LAB, as well as prolonged cold storage (around 30 days at 4 °C), all contribute to increasing the frequency of AMR gene transfer [16,20]. Chaves et al. [20] recently reviewed the emergence of AMR among LAB and human pathogens in raw milk cheeses. Specifically, raw sheep’s milk and cheeses, whose global consumption is increasing due to their high nutritional value, can act as a vehicle for the transmission of pathogens and potential pathogens, including AMR strains such as Staphylococcus aureus, Streptococcus spp., Enterococcus spp., Enterobacteriaceae, coliforms, Escherichia coli, Pseudomonas aeruginosa, Yersinia enterocolitica, and Bacillus spp. [6,27,28,29,30,31,32,33,34,35,36,37,38,39,40]. In the context of public health, the microbiological quality and safety of dairy products are crucial for consumers and depend on various factors, including the health of the animals, seasonal variations, sampling techniques, and adherence to strict hygiene practices both on farms and during processing. For instance, the presence of S. aureus is often linked to subclinical mastitis in animals, whereas the detection of Enterococcus species, Enterobacteriaceae, coliforms, and E. coli typically indicates inadequate hygiene measures [27,28]. Meanwhile, Zinno et al. [18] mapped the distribution of antimicrobial-resistant bacteria and AMR genes in animal-based foods, including fermented products, identifying dairy products as the most contaminated food categories, accounting for 56% and 76% of the total foods analyzed, respectively. In this context, effectively monitoring and quantifying genes that confer resistance to antibiotics commonly used in livestock and clinical settings within Njeguški cheese—a traditional Montenegrin cheese originally made from raw sheep’s milk that is gaining popularity in both local and global markets—plays an important role in understanding its safety profile.
Specifically, the genes erm(A), erm(B), and erm(C) cause cross resistance to macrolide, lincosamides and streptogramin B (namely MLSB resistance) by encoding erythromycin ribosomal RNA methylases. These enzymes methylate the bacterial ribosome, preventing the binding of MLS antibiotics to their target site [41]. This is the most widespread mechanism of resistance to MLSB in Gram-positive bacteria such as streptococci, S. aureus and coagulase-negative staphylococci (CNS). It is primarily associated with the presence of transposons and plasmids that carry the erm(A), erm(B), and erm(C) genes [41]. Njeguški cheese microbiota was found to be dominated by Streptococcus spp. and Streptococcus thermophilus, with high presumptive lactococci counts of about 9 log cfu g−1 [21], suggesting a feasible association of these microorganisms with erm genes detection. This hypothesis aligns with the findings reviewed by Verraes et al. [15], who reported that Lactococcus and Streptococcus thermophilus isolates from dairy products frequently exhibit resistance to erythromycin and tetracycline. In the present study, erm(B) gene was detected in all Njeguški cheese samples, followed by erm(C) gene detected in all samples from producer B. The pattern of erm genes observed in Njeguški cheese samples is consistent with previous studies reporting erm(B) gene as the most prevalent, followed by erm(C) gene, in dairy products from various countries such as Poland, China, India, Ethiopia, Brazil, Turkey, Spain and Italy [18,20,42,43,44,45].
Tetracycline resistance can occur through various mechanisms, including efflux pumps, protection of ribosomal binding sites, or enzymatic modification of the antibiotic. The tet(M), tet(O), tet(W), and tet(S) genes encode ribosomal protection proteins, whereas tet(K) gene encodes a tetracycline-specific efflux pump [46,47,48,49]. As expected, tet genes were widely distributed among the cheese samples analyzed, likely due to the extensive global use of tetracyclines over the past decades across various ecosystems, including livestock farming, where they have been used to promote animal growth [45,50,51]. As reviewed by Verraes et al. [15], a high frequency of tetracycline and erythromycin resistance has been observed among Lactobacillus strains isolated from artisanal cheeses. Njeguški cheese is characterized by the dominance of Lactobacillus spp. and viable lactobacilli counts reaching up to 8 log cfu g−1 [21], suggesting a likely involvement of the cheese’s LAB microbiota in the dissemination of these resistance traits. Overall, tet(M), tet(O), tet(W), tet(K), and tet(S) have been previously identified as the most prevalent tet genes in foodborne LAB using PCR-based assays, supporting the findings of the present study. In particular, tet(M) is the most commonly detected gene among tet genes in Lactobacillus species isolated from dairy products [20,42,45,51].
β-lactam antibiotics, including penicillin and methicillin, are inactivated through the action of the blaZ and mecA genes. The blaZ gene encodes a β-lactamase enzyme that hydrolyzes the β-lactam ring of penicillin, while mecA gene encodes penicillin-binding protein 2a (PBP2a), which confers resistance to methicillin [52]. These resistances are mainly related to S. aureus strains, the so-called methicillin-resistant S. aureus (MRSA) strains that encode both β-lactamase and PBP2a. MRSA strains are frequently resistant to several categories of antibiotics such as macrolides, tetracyclines, and aminoglycosides [52]. CNS isolated from cheeses in Turkey have been found to carry the mecA gene [43]. Similarly, S. aureus strains isolated from Brazilian raw milk artisanal cheeses were also reported to harbor this gene [53,54,55,56]. By contrast, S. aureus strains isolated from 92 samples of raw sheep’s milk cheese from Slovak Republic shown a penicillin-resistant phenotype carrying blaZ gene [40]. Similarly, blaZ gene was the prevalent β-lactams resistance gene in 35 Brazilian cheeses made from pasteurized bovine milk [51]. Intriguingly, although metataxonomic analysis [21] did not detect staphylococci, the blaZ and mecA genes were found in all Njeguški cheese samples, suggesting that other bacterial groups may be involved in the dissemination of these resistance genes. This hypothesis is supported by the study of Santamarina-García et al. [6], which reports an increasing number of LAB isolates resistant to β-lactams. The ubiquitous presence of blaZ and mecA genes in the samples analyzed can be attributed to the extensive global use of β-lactams in livestock farming and to the dissemination of AMR genes, which is reflected in the high prevalence of these genes among bacterial isolates from animal-derived products [6,51,56].
The vanA and vanB genes confer resistance to vancomycin, a glycopeptide antibiotic that inhibits bacterial cell wall synthesis by binding to its precursors. These genes are commonly found in enterococci, staphylococci, and lactobacilli, which act as reservoirs [57]. Enterococci play a crucial role in cheese maturation by contributing to its distinctive aroma, flavor, and texture, and are therefore often used as starter cultures [20,44]. However, Enterococcus strains are also known for their capacity to acquire highly transmissible genetic elements such as plasmids, transposons, and insertion sequences. This ability enhances their potential to carry multiple antibiotic resistances, particularly to erythromycin and tetracyclines, and to transfer AMR genes among different bacterial species [20,29,38,44,58]. Specifically, among vancomycin-resistant enterococci (VRE), Enterococcus faecium carries the vanA gene, which is considered the primary gene responsible for vancomycin resistance. This gene is located on the transposon Tn1546, which is frequently found on plasmids [20,44]. Despite the high viable counts of lactobacilli and lactococci, the predominance of Lactobacillus spp., and the presence of Enterococcus spp. (albeit at low relative abundances) as revealed by metataxonomic analysis [21], neither vanA nor vanB genes were detected in the samples analyzed. These findings are consistent with the studies by Chajęcka-Wierzchowska et al. [42] on dairy products from Poland and by Yao et al. [59] on industrial and artisanal cheeses from various regions in China, where no van genes were detected using multiplex PCR and qPCR, respectively. Similarly, none of the Njeguški cheese samples tested positive for the aminoglycoside resistance gene aac(6′)-Ie-aph(2″)-Ia, which is typically located on the Tn5281 transposon in enterococci and confers resistance to gentamicin by producing aminoglycoside-modifying enzymes [60]. Our findings are consistent with the study by Özdemir and Tuncer [61], who reported the absence of the aac(6′)-Ie-aph(2″)-Ia gene among 59 high-level aminoglycoside-resistant enterococci isolates from raw milk and dairy products.
Carbapenems are broad-spectrum β-lactam antibiotics commonly used in clinical medicine, but their use is banned in livestock farming worldwide [17,24]. Bacteria develop resistance to carbapenems primarily by acquiring genes that encode carbapenemases that are β-lactamase enzymes capable of hydrolyzing carbapenems and other β-lactam antibiotics by breaking the β-lactam ring [11,17,24,62]. Carbapenem resistance is a relatively recent phenomenon but is rapidly increasing because carbapenemases encoding genes are carried on mobile genetic elements that can be easily transferred horizontally between different bacteria, both commensal and pathogenic. This facilitates the spread of resistance across various reservoirs, ultimately diminishing the effectiveness of carbapenems in treating bacterial infections [11,17,24,62]. Among these genes, blaNDM-1 was the only one detected in Njeguški cheese samples, specifically in those from producers B and C. The blaNDM-1 gene codify for 17 variants of class B or metallo-β-lactamases (MBLs) called New Delhi metallo-β-lactamase (NDM) that use a zinc ion (Zn++) for the hydrolysis of β-lactam ring [17,62]. Typically, this gene has been found in clinically relevant microorganisms as Enterobacteriaceae [62]. Therefore, this finding may be associated with the medium to high viable counts of Enterobacteriaceae and E. coli observed in the Njeguški cheese samples, although no significant differences were found among samples from the three producers [21]. The origin of carbapenemase encoding genes in dairy products remains controversial. Al et al. [63] screened 427 raw milk samples for the presence of blaKPC, blaNDM and blaOXA-48 gene using qPCR and found no evidence of these genes, thereby excluding raw milk as a source for the dissemination of carbapenemase encoding genes. By contrast, as reviewed by Ramírez-Castillo et al. [17], the blaNDM gene and its variants have been detected in E. coli and Klebsiella pneumoniae strains isolated from cattle and milk samples from India, Algeria, Spain, and China. Furthermore, it is well established that livestock animals serve as major reservoirs of multidrug-resistant bacteria, including carbapenem-resistant strains, which can disseminate carbapenem resistance genes to humans either through the food chain or via environments contaminated with animal feces. Specifically, the blaNDM gene and its variants have been reported in poultry, swine, dairy and beef cattle livestock, farm environments, raw milk, animals’ feces, seafood, wildlife and companion animals [17]. The detection of blaNDM-1 in Njeguški cheese samples may therefore suggest that potential sources of contamination could originate from the raw milk, farm environment and/or production environment. These findings highlight the importance of surveillance of AMR genes in raw materials, animals from livestock, farm environment, and animal-based products. From a public health perspective, although the incidence of carbapenem resistance genes in the cheeses under study is low, this remains a significant finding due to their clinical relevance, as carbapenems represent the final therapeutic option for managing multidrug-resistant bacterial infections, particularly those causing life-threatening illnesses [11,17,24,62]. Specifically, the presence of blaNDM-1 in Njeguški cheese samples has important implications for consumer health, as NDM-1 enzymes can hydrolyze all β-lactam antibiotics and possess a high potential for rapid dissemination [17,62], thereby facilitating transmission to human microbiota and pathogens, which poses a significant public health risk. Interestingly, according to a recent review by Alvisi et al. [62], international travel and trade have contributed to the global dissemination of NDM-producing bacteria, with evidence of their spread in the Western Balkans.
Overall, this study is consistent with the research by Delannoy et al. [36] on the resistome of 360 raw sheep’s cheeses and 360 raw cow’s cheeses from France, which demonstrated that genes conferring resistance to first-generation β-lactams and tetracyclines are widespread, while those conferring resistance to critically important antibiotics, such as carbapenems, are rare or absent.
Finally, this study revealed a considerable variability in the presence and abundance of AMR genes among samples collected from different artisan producers. The differences in resistance gene profiles suggest that production practices and specific environmental conditions unique to each producer may significantly shape the composition and abundance of AMR genes in the final product. Furthermore, the high consistency in AMR gene profiles within batches from each producer suggests the adoption of stable production practices, highlighting control points for the development of targeted strategies to mitigate AMR. Indeed, the findings of the present study can support the production of safer traditional Njeguški cheese, primarily by increasing consumer and producer awareness of the AMR phenomenon along the food chain, and secondarily by guiding the implementation of suitable strategies to monitor and mitigate AMR in these unique artisanal productions. In detail, the primary area of concern lies at the livestock level, where the use of antibiotics must be significantly reduced or entirely avoided to lessen the selective pressure contributing to AMR. At the same time, cheese producers play a crucial role by ensuring careful monitoring of raw materials, ensuring the supply of safe water and maintaining strict hygienic and processing standards throughout cheese production. This includes implementing proper sanitation procedures and waste disposal practices to minimize the environmental release of AMR. To achieve this, workers should receive professional training to adopt effective AMR containment measures across the whole cheese production chain [5,16]. Another effective strategy for mitigating AMR may involve the appropriate screening, selection, and use of autochthonous starter cultures [64], thereby enhancing the quality and safety of cheeses without compromising their traditional character. Intriguingly, very recently the research of Santamarina-García et al. [6] highlighted that cheese production chain, monitored from ovine faeces, ewe milk, whey, fresh cheese, until 60-day-ripened cheese, may have a role in minimizing AMR in the final product since the relative abundance of resistance genes was reduced along the production chain depending on LAB dynamics. In parallel, implementing efficient surveillance systems and conducting research in food production through the use of rapid diagnostic tools that combine culture-based techniques with molecular methods can help identify food-related niches of AMR genes and AMR bacteria. Overall, data collected from food production monitoring systems can guide decision-makers in shaping legislation and policies, as well as in establishing standardized codes of good practice and guidelines designed to support AMR mitigation strategies across all stages of the farm-to-table supply chain [5,16].

5. Conclusions

This study represents the first systematic risk assessment of Montenegrin Njeguški cheese regarding AMR gene profiles. The high incidence of genes associated with resistance to tetracyclines and β-lactams, combined with the lower and sporadic detection of genes conferring resistance to MLSB and carbapenems, aligns with previously reported data and reflects the long-standing and widespread use of tetracyclines and β-lactams across various ecosystems. While some concerning genes were identified, the overall findings of the present study provide useful guidance for improving microbiological safety and production practices in traditional cheese-making. A limitation of the study could be that it quantifies genes but does not link them to specific bacterial hosts thus limiting interpretation of the potential risk for horizontal gene transfer or pathogenicity. However, the study of AMR genes distribution in cheese samples has been complemented by previous results from viable cell counts and metagenomic sequencing, enabling a feasible correlation between the microbiota of Njeguški cheese and the detection of AMR genes. Future research perspectives could include seasonal samplings of the products and longitudinal monitoring to capture variability of AMR genes over time, as well as the selection and application of autochthonous starter cultures not harboring AMR genes. Ultimately, this study underscores the importance of continuous monitoring of fermented foods to evaluate the potential impact of the diet on food safety and public health.

Author Contributions

Conceptualization, C.G.; Formal analysis, V.M., G.R., F.C. and G.P.; Funding acquisition, A.M. and C.G.; Investigation, V.M., G.R., A.C., F.C., G.P. and A.B.; Methodology, V.M.; Project administration, A.M. and C.G.; Resources, C.G.; Supervision, C.G.; Writing—original draft, V.M., A.M., L.A., A.O. and C.G.; Writing—review and editing, L.A., A.O. and C.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported in part by the Italian Ministry of Foreign Affairs and International Cooperation (grant number ME23GR01) and by the Montenegrin’s Ministry of Education, Science and Innovation (grant number 01-082*22-1624/5-2 dated 29 December 2022) within the bilateral project entitled “Valorization and innovation of Montenegro traditional fermented foods” (FOODVALUE).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AMRAntimicrobial Resistance
CNSCoagulase-Negative Staphylococci
LABLactic Acid Bacteria
MLSBMacrolide–Lincosamide–Streptogramin B
MRSAMethicillin-Resistant Staphylococcus aureus
PBP2aPenicillin-Binding Protein 2a
PCAPrincipal Component Analysis
PCRPolymerase Chain Reaction
qPCRQuantitative Polymerase Chain Reaction
VREVancomycin-Resistant Enterococci

References

  1. Aquilanti, L.; Garofalo, C.; Osimani, A.; Silvestri, G.; Vignaroli, C.; Clementi, F. Isolation and Molecular Characterization of Antibiotic-Resistant Lactic Acid Bacteria from Poultry and Swine Meat Products. J. Food Prot. 2007, 70, 557–565. [Google Scholar] [CrossRef]
  2. Garofalo, C.; Vignaroli, C.; Zandri, G.; Aquilanti, L.; Bordoni, D.; Osimani, A.; Clementi, F.; Biavasco, F. Direct Detection of Antibiotic Resistance Genes in Specimens of Chicken and Pork Meat. Int. J. Food Microbiol. 2007, 113, 75–83. [Google Scholar] [CrossRef]
  3. Likotrafiti, E.; Oniciuc, E.; Prieto, M.; Santos, J.; López, S.; Alvarez-Ordóñez, A. Risk Assessment of Antimicrobial Resistance along the Food Chain through Culture-independent Methodologies. EFSA J. 2018, 16, e160811. [Google Scholar] [CrossRef] [PubMed]
  4. Milanović, V.; Osimani, A.; Cardinali, F.; Litta-Mulondo, A.; Vignaroli, C.; Citterio, B.; Mangiaterra, G.; Aquilanti, L.; Garofalo, C.; Biavasco, F.; et al. Erythromycin-Resistant Lactic Acid Bacteria in the Healthy Gut of Vegans, Ovo-Lacto Vegetarians and Omnivores. PLoS ONE 2019, 14, e0220549. [Google Scholar] [CrossRef] [PubMed]
  5. Caniça, M.; Manageiro, V.; Abriouel, H.; Moran-Gilad, J.; Franz, C.M.A.P. Antibiotic Resistance in Foodborne Bacteria. Trends Food Sci. Technol. 2019, 84, 41–44. [Google Scholar] [CrossRef]
  6. Santamarina-García, G.; Amores, G.; Llamazares, D.; Hernández, I.; Javier, R.; Barron, L.; Virto, M. Phenotypic and Genotypic Characterization of Antimicrobial Resistances Reveals the Effect of the Production Chain in Reducing Resistant Lactic Acid Bacteria in an Artisanal Raw Ewe Milk PDO Cheese. Food Res. Int. 2024, 187, 114308. [Google Scholar] [CrossRef]
  7. Founou, L.L.; Founou, R.C.; Essack, S.Y. Antibiotic Resistance in the Food Chain: A Developing Country-Perspective. Front. Microbiol. 2016, 7, 1881. [Google Scholar] [CrossRef]
  8. Caniça, M.; Manageiro, V.; Jones-Dias, D.; Clemente, L.; Gomes-Neves, E.; Poeta, P.; Dias, E.; Ferreira, E. Current Perspectives on the Dynamics of Antibiotic Resistance in Different Reservoirs. Res. Microbiol. 2015, 166, 594–600. [Google Scholar] [CrossRef]
  9. Bergšpica, I.; Kaprou, G.; Alexa, E.A.; Prieto-Maradona, M.; Alvarez-Ordóñez, A. Identification of Risk Factors and Hotspots of Antibiotic Resistance along the Food Chain Using Next-generation Sequencing. EFSA J. 2020, 18, e181107. [Google Scholar] [CrossRef]
  10. Carelli, M.; Griggio, F.; Mingoia, M.; Garofalo, C.; Milanović, V.; Pozzato, N.; Leoni, F.; Veschetti, L.; Malerba, G.; Sandri, A.; et al. Detecting Carbapenemases in Animal and Food Samples by Droplet Digital PCR. Antibiotics 2022, 11, 1696. [Google Scholar] [CrossRef]
  11. Garofalo, C.; Cesaro, C.; Milanović, V.; Belleggia, L.; Matricardi, T.; Osimani, A.; Aquilanti, L.; Cardinali, F.; Rampanti, G.; Simoni, S.; et al. Search for Carbapenem-Resistant Bacteria and Carbapenem Resistance Genes along Swine Food Chains in Central Italy. PLoS ONE 2024, 19, e0296098. [Google Scholar] [CrossRef] [PubMed]
  12. Milanović, V.; Aquilanti, L.; Tavoletti, S.; Garofalo, C.; Osimani, A.; De Filippis, F.; Ercolini, D.; Ferrocino, I.; Di Cagno, R.; Turroni, S.; et al. Distribution of Antibiotic Resistance Genes in the Saliva of Healthy Omnivores, Ovo-Lacto-Vegetarians, and Vegans. Genes 2020, 11, 1088. [Google Scholar] [CrossRef]
  13. Milanović, V.; Osimani, A.; Aquilanti, L.; Tavoletti, S.; Garofalo, C.; Polverigiani, S.; Litta-Mulondo, A.; Cocolin, L.; Ferrocino, I.; Di Cagno, R.; et al. Occurrence of Antibiotic Resistance Genes in the Fecal DNA of Healthy Omnivores, Ovo-Lacto Vegetarians and Vegans. Mol. Nutr. Food Res. 2017, 61, 1601098. [Google Scholar] [CrossRef]
  14. Samtiya, M.; Matthews, K.R.; Dhewa, T.; Puniya, A.K. Antimicrobial Resistance in the Food Chain: Trends, Mechanisms, Pathways, and Possible Regulation Strategies. Foods 2022, 11, 2966. [Google Scholar] [CrossRef]
  15. Verraes, C.; Van Boxstael, S.; Van Meervenne, E.; Van Coillie, E.; Butaye, P.; Catry, B.; De Schaetzen, M.-A.; Van Huffel, X.; Imberechts, H.; Dierick, K.; et al. Antimicrobial Resistance in the Food Chain: A Review. Int. J. Environ. Res. Public Health 2013, 10, 2643–2669. [Google Scholar] [CrossRef]
  16. Tiedje, J.M.; Fu, Y.; Mei, Z.; Schäffer, A.; Dou, Q.; Amelung, W.; Elsner, M.; Adu-Gyamfi, J.; Heng, L.; Virta, M.; et al. Antibiotic Resistance Genes in Food Production Systems Support One Health Opinions. Curr. Opin. Environ. Sci. Health 2023, 34, 100492. [Google Scholar] [CrossRef]
  17. Ramírez-Castillo, F.Y.; Guerrero-Barrera, A.L.; Avelar-González, F.J. An Overview of Carbapenem-Resistant Organisms from Food-Producing Animals, Seafood, Aquaculture, Companion Animals, and Wildlife. Front. Vet. Sci. 2023, 10, 1158588. [Google Scholar] [CrossRef] [PubMed]
  18. Zinno, P.; Perozzi, G.; Devirgiliis, C. Foodborne Microbial Communities as Potential Reservoirs of Antimicrobial Resistance Genes for Pathogens: A Critical Review of the Recent Literature. Microorganisms 2023, 11, 1696. [Google Scholar] [CrossRef]
  19. Wolfe, B.E. Are Fermented Foods an Overlooked Reservoir of Antimicrobial Resistance? Curr. Opin. Food Sci. 2023, 51, 101018. [Google Scholar] [CrossRef]
  20. Chaves, C.R.S.; Salamandane, A.; Vieira, E.J.F.; Salamandane, C. Antibiotic Resistance in Fermented Foods Chain: Evaluating the Risks of Emergence of Enterococci as an Emerging Pathogen in Raw Milk Cheese. Int. J. Microbiol. 2024, 2024, 2409270. [Google Scholar] [CrossRef]
  21. Cardinali, F.; Rampanti, G.; Paderni, G.; Milanović, V.; Ferrocino, I.; Reale, A.; Boscaino, F.; Raicevic, N.; Ilincic, M.; Osimani, A.; et al. A Comprehensive Study on the Autochthonous Microbiota, Volatilome, Physico-Chemical, and Morpho-Textural Features of Montenegrin Njeguški Cheese. Food Res. Int. 2024, 197, 115169. [Google Scholar] [CrossRef] [PubMed]
  22. Jokanovic, O.; Markovic, B.; Mirecki, S.; Veljic, M.; Miloradovic, Z.; Radulovic, A.; Miocinovic, J. Composition and α-Tocopherol Content of Njeguski-Type Cheese Made from Cow, Ewe and Goat Milk. Int. Dairy J. 2022, 134, 105469. [Google Scholar] [CrossRef]
  23. Mirecki, S.; Popović, N.; Antunac, N.; Mikulec, N.; Plavljanić, D. Production Technology and Some Quality Parameters of Njeguši Cheese. Mljekarstvo 2015, 65, 280–286. [Google Scholar] [CrossRef]
  24. Milanović, V.; Osimani, A.; Roncolini, A.; Garofalo, C.; Aquilanti, L.; Pasquini, M.; Tavoletti, S.; Vignaroli, C.; Canonico, L.; Ciani, M.; et al. Investigation of the Dominant Microbiota in Ready-to-Eat Grasshoppers and Mealworms and Quantification of Carbapenem Resistance Genes by qPCR. Front. Microbiol. 2018, 9, 3036. [Google Scholar] [CrossRef]
  25. Klindworth, A.; Pruesse, E.; Schweer, T.; Peplies, J.; Quast, C.; Horn, M.; Glöckner, F.O. Evaluation of General 16S Ribosomal RNA Gene PCR Primers for Classical and Next-Generation Sequencing-Based Diversity Studies. Nucleic Acids Res. 2013, 41, e1. [Google Scholar] [CrossRef]
  26. Milanović, V.; Cardinali, F.; Aquilanti, L.; Maoloni, A.; Garofalo, C.; Zarantoniello, M.; Olivotto, I.; Riolo, P.; Ruschioni, S.; Isidoro, N.; et al. Quantitative Assessment of Transferable Antibiotic Resistance Genes in Zebrafish (Danio rerio) Fed Hermetia Illucens-Based Feed. Anim. Feed Sci. Technol. 2021, 277, 114978. [Google Scholar] [CrossRef]
  27. Iancu, I.; Igna, V.; Popa, S.A.; Imre, K.; Pascu, C.; Costinar, L.; Degi, J.; Gligor, A.; Iorgoni, V.; Badea, C.; et al. Etiology and Antimicrobial Resistance of Subclinical Mastitis Pathogens Staphylococcus aureus, Streptococcus spp. and Enterococcus spp. in Sheep Milk. Vet. Res. Commun. 2025, 49, 30. [Google Scholar] [CrossRef]
  28. Kováčová, M.; Výrostková, J.; Dudriková, E.; Zigo, F.; Semjon, B.; Regecová, I. Assessment of Quality and Safety of Farm Level Produced Cheeses from Sheep and Goat Milk. Appl. Sci. 2021, 11, 3196. [Google Scholar] [CrossRef]
  29. Gołaś-Prądzyńska, M.; Łuszczyńska, M.; Rola, J.G. Dairy Products: A Potential Source of Multidrug-Resistant Enterococcus faecalis and Enterococcus faecium Strains. Foods 2022, 11, 4116. [Google Scholar] [CrossRef]
  30. Palmeri, M.; Mancuso, I.; Gaglio, R.; Arcuri, L.; Barreca, S.; Barbaccia, P.; Scatassa, M.L. Identification and Evaluation of Antimicrobial Resistance of Enterococci Isolated from Raw Ewes’ and Cows’ Milk Collected in Western Sicily: A Preliminary Investigation. Ital. J. Food Saf. 2021, 9, 220–225. [Google Scholar] [CrossRef]
  31. Roșu, R.-D.; Morar, A.; Ban-Cucerzan, A.; Imre, M.; Popa, S.A.; Pătrînjan, R.-T.; Pocinoc, A.; Imre, K. Raw Sheep Milk as a Reservoir of Multidrug-Resistant Staphylococcus aureus: Evidence from Traditional Farming Systems in Romania. Antibiotics 2025, 14, 787. [Google Scholar] [CrossRef]
  32. Regecová, I.; Výrostková, J.; Zigo, F.; Gregová, G.; Kováčová, M. Detection of Antimicrobial Resistance of Bacteria Staphylococcus chromogenes Isolated from Sheep’s Milk and Cheese. Antibiotics 2021, 10, 570. [Google Scholar] [CrossRef]
  33. Souza, D.B.; Pereira, R.I.; Endres, C.M.; Frazzon, J.; Prichula, J.; Frazzon, A.P.G. Resistant Enterococci Isolated from Raw Sheep’s Milk and Cheeses from South Region of Brazil. Ciência Rural 2023, 53, e20220288. [Google Scholar] [CrossRef]
  34. Bruzaroski, S.R.; Correia, S.; Araújo, K.E.; Santos, L.R.d.S.; Alegro, L.A.; dos Santos, N.T.B.; Poli-Frederico, R.C.; Carvalho, R.C.T.; Santana, E.H.W. High Spoilage Potential and Multidrug Resistance of P. aeruginosa Strains Isolated from Sheep Milk. Int. Dairy J. 2025, 167, 106280. [Google Scholar] [CrossRef]
  35. Piras, F.; Spanu, C.; Sanna, R.; Siddi, G.; Mocci, A.M.; Demontis, M.; Meloni, M.P.; Spanu, V.; De Santis, E.P.L.; Scarano, C. Detection, Virulence Genes and Antimicrobial Resistance of Yersinia enterocolitica in Sheep and Goat Raw Milk. Int. Dairy J. 2021, 117, 105011. [Google Scholar] [CrossRef]
  36. Delannoy, S.; Hoffer, C.; Tran, M.-L.; Madec, J.-Y.; Brisabois, A.; Fach, P.; Haenni, M. High Throughput qPCR Analyses Suggest That Enterobacterales of French Sheep and Cow Cheese Rarely Carry Genes Conferring Resistances to Critically Important Antibiotics for Human Medicine. Int. J. Food Microbiol. 2023, 403, 110303. [Google Scholar] [CrossRef]
  37. Spanu, V.; Spanu, C.; Virdis, S.; Cossu, F.; Scarano, C.; De Santis, E.P.L. Virulence Factors and Genetic Variability of Staphylococcus aureus Strains Isolated from Raw Sheep’s Milk Cheese. Int. J. Food Microbiol. 2012, 153, 53–57. [Google Scholar] [CrossRef] [PubMed]
  38. Výrostková, J.; Regecová, I.; Dudriková, E.; Marcinčák, S.; Vargová, M.; Kováčová, M.; Maľová, J. Antimicrobial Resistance of Enterococcus sp. Isolated from Sheep and Goat Cheeses. Foods 2021, 10, 1844. [Google Scholar] [CrossRef]
  39. Slyvka, I.; Tsisaryk, O.; Musii, L.; Kushnir, I.; Koziorowski, M.; Koziorowska, A. Identification and Investigation of Properties of Strains Enterococcus spp. Isolated from Artisanal Carpathian Cheese. Biocatal. Agric. Biotechnol. 2022, 39, 102259. [Google Scholar] [CrossRef]
  40. Karahutová, L.; Bujňáková, D. Occurrence and Molecular Surveillance of Pathogenesis Risk-Associated Factors in Staphylococcus aureus Recovered from Raw Sheep’s Milk Cheese. Small Rumin. Res. 2023, 222, 106967. [Google Scholar] [CrossRef]
  41. Petinaki, E.; Papagiannitsis, C. Resistance of Staphylococci to Macrolides-Lincosamides-Streptogramins B (MLSB): Epidemiology and Mechanisms of Resistance. In Staphylococcus aureus; IntechOpen: Rijeka, Croatia, 2018. [Google Scholar] [CrossRef]
  42. Chajęcka-Wierzchowska, W.; Zadernowska, A.; García-Solache, M. Ready-to-Eat Dairy Products as a Source of Multidrug-Resistant Enterococcus Strains: Phenotypic and Genotypic Characteristics. J. Dairy Sci. 2020, 103, 4068–4077. [Google Scholar] [CrossRef]
  43. Kürekci, C. Short Communication: Prevalence, Antimicrobial Resistance, and Resistant Traits of Coagulase-Negative Staphylococci Isolated from Cheese Samples in Turkey. J. Dairy Sci. 2016, 99, 2675–2679. [Google Scholar] [CrossRef]
  44. Salamandane, A.; Cahango, G.; Muetanene, B.A.; Malfeito-Ferreira, M.; Brito, L. Multidrug Resistance in Enterococci Isolated from Cheese and Capable of Producing Benzalkonium Chloride-Resistant Biofilms. Biology 2023, 12, 1353. [Google Scholar] [CrossRef]
  45. Flórez, A.B.; Alegría, Á.; Rossi, F.; Delgado, S.; Felis, G.E.; Torriani, S.; Mayo, B. Molecular Identification and Quantification of Tetracycline and Erythromycin Resistance Genes in Spanish and Italian Retail Cheeses. Biomed. Res. Int. 2014, 2014, 746859. [Google Scholar] [CrossRef]
  46. Aires, J.; Doucet-Populaire, F.; Butel, M.J. Tetracycline Resistance Mediated by Tet(W), Tet(M), and Tet(O) Genes of Bifidobacterium Isolates from Humans. Appl. Environ. Microbiol. 2007, 73, 2751–2754. [Google Scholar] [CrossRef]
  47. Kim, S.-R.; Nonaka, L.; Suzuki, S. Occurrence of Tetracycline Resistance Genes Tet(M) and Tet(S) in Bacteria from Marine Aquaculture Sites. FEMS Microbiol. Lett. 2004, 237, 147–156. [Google Scholar] [CrossRef]
  48. Li, W.; Atkinson, G.C.; Thakor, N.S.; Allas, Ü.; Lu, C.; Chan, K.-Y.; Tenson, T.; Schulten, K.; Wilson, K.S.; Hauryliuk, V.; et al. Mechanism of Tetracycline Resistance by Ribosomal Protection Protein Tet(O). Nat. Commun. 2013, 4, 1477. [Google Scholar] [CrossRef] [PubMed]
  49. Grossman, T.H. Tetracycline Antibiotics and Resistance. Cold Spring Harb. Perspect. Med. 2016, 6, a025387. [Google Scholar] [CrossRef]
  50. Speer, B.S.; Shoemaker, N.B.; Salyers, A. Bacterial Resistance to Tetracycline: Mechanisms, Transfer, and Clinical Significance. Clin. Microbiol. Rev. 1992, 5, 387–399. [Google Scholar] [CrossRef] [PubMed]
  51. De Paula, A.C.; Medeiros, J.; De Azevedo, A.; De Assis Chagas, J.; Da Silva, V.; Diniz, C. Antibiotic Resistance Genetic Markers and Integrons in White Soft Cheese: Aspects of Clinical Resistome and Potentiality of Horizontal Gene Transfer. Genes 2018, 9, 106. [Google Scholar] [CrossRef] [PubMed]
  52. Lade, H.; Kim, J.-S. Molecular Determinants of β-Lactam Resistance in Methicillin-Resistant Staphylococcus aureus (MRSA): An Updated Review. Antibiotics 2023, 12, 1362. [Google Scholar] [CrossRef]
  53. da Silva Abreu, A.C.; Matos, L.G.; da Silva Cândido, T.J.; Barboza, G.R.; de Souza, V.V.M.A.; Munive Nuñez, K.V.; Cirone Silva, N.C. Antimicrobial Resistance of Staphylococcus spp. Isolated from Organic and Conventional Minas Frescal Cheese Producers in São Paulo, Brazil. J. Dairy Sci. 2021, 104, 4012–4022. [Google Scholar] [CrossRef]
  54. Carneiro Aguiar, R.A.; Ferreira, F.A.; Dias, R.S.; Nero, L.A.; Miotto, M.; Verruck, S.; De Marco, I.; De Dea Lindner, J. Graduate Student Literature Review: Enterotoxigenic Potential and Antimicrobial Resistance of Staphylococci from Brazilian Artisanal Raw Milk Cheeses. J. Dairy Sci. 2022, 105, 5685–5699. [Google Scholar] [CrossRef]
  55. Aragão, B.B.; Trajano, S.C.; Silva, J.G.; Silva, B.P.; Oliveira, R.P.; Junior, J.W.P.; Peixoto, R.M.; Mota, R.A. Short Communication: High Frequency of β-Lactam-Resistant Staphylococcus aureus in Artisanal Coalho Cheese Made from Goat Milk Produced in Northeastern Brazil. J. Dairy Sci. 2019, 102, 6923–6927. [Google Scholar] [CrossRef] [PubMed]
  56. Pineda, A.P.A.; Chacón, R.D.; Costa, T.G.d.; Campos, G.Z.; Munive Nuñez, K.V.; Ramos, R.C.Z.; Camargo, C.H.; Lacorte, G.A.; Silva, N.C.C.; Pinto, U.M. Molecular Characterization and Virulence Potential of Staphylococcus aureus from Raw Milk Artisanal Cheeses. Int. Dairy J. 2025, 160, 106097. [Google Scholar] [CrossRef]
  57. Selim, S. Mechanisms of Gram-positive Vancomycin Resistance (Review). Biomed. Rep. 2021, 16, 7. [Google Scholar] [CrossRef]
  58. Gaglio, R.; Couto, N.; Marques, C.; de Fatima Silva Lopes, M.; Moschetti, G.; Pomba, C.; Settanni, L. Evaluation of Antimicrobial Resistance and Virulence of Enterococci from Equipment Surfaces, Raw Materials, and Traditional Cheeses. Int. J. Food Microbiol. 2016, 236, 107–114. [Google Scholar] [CrossRef]
  59. Yao, J.; Gao, J.; Guo, J.; Wang, H.; Zhang, E.; Lin, Y.; Chen, Z.; Li, S.; Tao, S. Characterization of Bacteria and Antibiotic Resistance in Commercially Produced Cheeses Sold in China. J. Food Prot. 2022, 85, 484–493. [Google Scholar] [CrossRef]
  60. Mirnejad, R.; Sajjadi, N.; Masoumi Zavaryani, S.; Piranfar, V.; Hajihosseini, M.; Roshanfekr, M. Identification of Aminoglycoside Resistance Genes by Triplex PCR in Enterococcus spp. Isolated from ICUs. Infez. Med. 2016, 24, 222–229. [Google Scholar] [PubMed]
  61. Özdemir, R.; Tuncer, Y. Detection of Antibiotic Resistance Profiles and Aminoglycoside-Modifying Enzyme (AME) Genes in High-Level Aminoglycoside-Resistant (HLAR) Enterococci Isolated from Raw Milk and Traditional Cheeses in Turkey. Mol. Biol. Rep. 2020, 47, 1703–1712. [Google Scholar] [CrossRef] [PubMed]
  62. Alvisi, G.; Curtoni, A.; Fonnesu, R.; Piazza, A.; Signoretto, C.; Piccinini, G.; Sassera, D.; Gaibani, P. Epidemiology and Genetic Traits of Carbapenemase-Producing Enterobacterales: A Global Threat to Human Health. Antibiotics 2025, 14, 141. [Google Scholar] [CrossRef] [PubMed]
  63. Al, S.; Hizlisoy, H.; Onmaz, N.E.; Karadal, F.; Barel, M.; Yildirim, Y.; Gönülalan, Z. Çiğ Sütlerde Karbapenem Dirençli Enterobacteriaceae ve BlaKPC, BlaNDM ve BlaOXA-48 Gen Varlığının Moleküler Olarak İncelenmesi. Kafkas Univ. Vet. Fak. Derg. 2020, 26, 391–396. [Google Scholar] [CrossRef]
  64. Wörmann, M.E.; Pech, J.; Reich, F.; Tenhagen, B.-A.; Wichmann-Schauer, H.; Lienen, T. Growth of Methicillin-Resistant Staphylococcus aureus during Raw Milk Soft Cheese-Production and the Inhibitory Effect of Starter Cultures. Food Microbiol. 2024, 119, 104451. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Principal component analysis (PCA) biplot of antimicrobial resistance (AMR) gene profiles in Njeguški cheese samples. Ellipses represent 95% confidence intervals for each producer group.
Figure 1. Principal component analysis (PCA) biplot of antimicrobial resistance (AMR) gene profiles in Njeguški cheese samples. Ellipses represent 95% confidence intervals for each producer group.
Genes 16 01089 g001
Table 1. Log copy number of antimicrobial resistance (AMR) genes detected in Njeguški cheese samples.
Table 1. Log copy number of antimicrobial resistance (AMR) genes detected in Njeguški cheese samples.
ProducerBatchAntimicrobial Resistant Genes (Log Gene Copies/g ± Standard Deviation)
MLSB 1Tetracyclinesβ-LactamsVancomycinAminoglycosidesCarbapenems
erm(A)erm(B)erm(C)tet(K)tet(M)tet(O)tet(S)tet(W)blaZmecAvanAvanBaac(6′)-Ie-aph(2″)-IablaOXA-48blaVIMblaNDM-1blaGESblaKPC
Ab1n.d. a7.54 ± 0.27 an.d. a4.88 ± 0.19 c8.26 ± 0.12 a3.79 ± 0.02 a9.26 ± 0.06 a4.83 ± 0.00 a5.24 ± 0.04 a3.23 ± 0.30 an.d. an.d. an.d. an.d. an.d. an.d. an.d. an.d. a
b2n.d. a7.02 ± 0.30 an.d. a5.49 ± 0.06 b7.72 ± 0.32 a3.83 ± 0.04 a8.60 ± 0.28 a4.86 ± 0.21 a5.07 ± 0.20 a3.49 ± 0.07 an.d. an.d. an.d. an.d. an.d. an.d. an.d. an.d. a
b3n.d. a6.67 ± 0.31 an.d. a6.09 ± 0.01 a7.61 ± 0.26 an.d. b9.14 ± 0.14 a4.58 ± 0.08 a4.96 ± 0.06 a3.48 ± 0.37 an.d. an.d. an.d. an.d. an.d. an.d. an.d. an.d. a
Overall n.d. A7.08 ± 0.45 An.d. B5.49 ± 0.55 C7.86 ± 0.36 B2.54 ± 1.97 A9.00 ± 0.35 B4.76 ± 0.17 B5.09 ± 0.16 B3.40 ± 0.25 Bn.d. An.d. An.d. An.d. An.d. An.d. Bn.d. An.d. A
Bb1n.d. a6.60 ± 0.16 a4.84 ± 0.24 a7.15 ± 0.04 a8.91 ± 0.30 a3.74 ± 0.16 a10.28 ± 0.31 a4.72 ± 0.11 a5.42 ± 0.19 a3.52 ± 0.24 an.d. an.d. an.d. an.d. an.d. a6.23 ± 0.25 an.d. an.d. a
b2n.d. a6.11 ± 0.11 b4.62 ± 0.17 a7.23 ± 0.20 a8.98 ± 0.15 a3.74 ± 0.01 a9.91 ± 0.14 a4.64 ± 0.10 a5.35 ± 0.15 a3.40 ± 0.55 an.d. an.d. an.d. an.d. an.d. a5.51 ± 0.77 an.d. an.d. a
b3n.d. a6.35 ± 0.03 a,b5.32 ± 0.10 a7.21 ± 0.02 a8.37 ± 0.01 an.d. b10.65 ± 0.05 a4.64 ± 0.00 a5.82 ± 0.05 a2.97 ± 0.31 an.d. an.d. an.d. an.d. an.d. a6.46 ± 0.03 an.d. an.d. a
Overall n.d. A6.35 ± 0.23 B4.93 ± 0.35 A7.20 ± 0.10 A8.75 ± 0.34 A2.49 ± 1.93 A10.28 ± 0.36 A4.67 ± 0.08 B5.53 ± 0.25 A3.30 ± 0.40 Bn.d. An.d. An.d. An.d. An.d. A6.07 ± 0.58 An.d. An.d. A
Cb1n.d. b6.87 ± 0.05 an.d. a7.03 ± 0.24 a8.75 ± 0.35 a4.65 ± 0.21 a9.73 ± 0.05 a6.70 ± 0.07 b5.24 ± 0.09 a5.65 ± 0.67 an.d. an.d. an.d. an.d. an.d. a6.49 ± 0.39 an.d. an.d. a
b2n.d. b5.88 ± 0.28 bn.d. a6.17 ± 0.27 a8.16 ± 0.15 a4.03 ± 0.39 a9.74 ± 0.22 a6.70 ± 0.00 b5.04 ± 0.21 a4.76 ± 0.58 an.d. an.d. an.d. an.d. an.d. a6.07 ± 0.61 an.d. an.d. a
b34.50 ± 0.14 a5.85 ± 0.06 bn.d. a6.24 ± 0.22 a8.63 ± 0.09 a3.64 ± 0.06 a10.09 ± 0.14 a7.75 ± 0.10 a5.10 ± 0.04 a4.65 ± 0.20 an.d. an.d. an.d. an.d. an.d. an.d. bn.d. an.d. a
Overall 1.50 ± 2.32 A6.20 ± 0.54 Bn.d. B6.48 ± 0.46 B8.51 ± 0.33 A4.11 ± 0.50 A9.85 ± 0.22 A7.05 ± 0.54 A5.13 ± 0.14 B5.02 ± 0.63 An.d. An.d. An.d. An.d. An.d. A4.19 ± 3.27 An.d. An.d. A
1 MLSB, macrolide–lincosamide–streptogramin B; n.d., not detected (detection limit for all tested AMR genes: < 1 log gene copy per reaction). Within each column, means followed by different lowercase letters indicate significant differences (p < 0.05) among different batches, and capital letters indicate significant differences (p < 0.05) among different producers.
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MDPI and ACS Style

Milanović, V.; Rampanti, G.; Cantarini, A.; Cardinali, F.; Paderni, G.; Martinovic, A.; Brenciani, A.; Aquilanti, L.; Osimani, A.; Garofalo, C. Antimicrobial Resistance Gene Patterns in Traditional Montenegrin Njeguški Cheese Revealed by qPCR. Genes 2025, 16, 1089. https://doi.org/10.3390/genes16091089

AMA Style

Milanović V, Rampanti G, Cantarini A, Cardinali F, Paderni G, Martinovic A, Brenciani A, Aquilanti L, Osimani A, Garofalo C. Antimicrobial Resistance Gene Patterns in Traditional Montenegrin Njeguški Cheese Revealed by qPCR. Genes. 2025; 16(9):1089. https://doi.org/10.3390/genes16091089

Chicago/Turabian Style

Milanović, Vesna, Giorgia Rampanti, Andrea Cantarini, Federica Cardinali, Giuseppe Paderni, Aleksandra Martinovic, Andrea Brenciani, Lucia Aquilanti, Andrea Osimani, and Cristiana Garofalo. 2025. "Antimicrobial Resistance Gene Patterns in Traditional Montenegrin Njeguški Cheese Revealed by qPCR" Genes 16, no. 9: 1089. https://doi.org/10.3390/genes16091089

APA Style

Milanović, V., Rampanti, G., Cantarini, A., Cardinali, F., Paderni, G., Martinovic, A., Brenciani, A., Aquilanti, L., Osimani, A., & Garofalo, C. (2025). Antimicrobial Resistance Gene Patterns in Traditional Montenegrin Njeguški Cheese Revealed by qPCR. Genes, 16(9), 1089. https://doi.org/10.3390/genes16091089

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