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Article

Appraisal of Multidrug-Resistant Listeria monocytogenes and Salmonella spp. Recovered from Commercial Meat Samples in the Eastern Cape, South Africa: Implications for Public Health Safety

by
Luyanda Msolo
1,2,*,
Zanda Mbiko
1,2,
Sindisiwe Nokhatyana
1,2 and
Antony Ifeanyi Okoh
1,2
1
SAMRC Microbial Water Quality Monitoring Centre, University of Fort Hare, Alice 5700, South Africa
2
DSTI-NRF SARChI in Water Quality and Environmental Genomics, University of Fort Hare, Alice 5700, South Africa
*
Author to whom correspondence should be addressed.
Antibiotics 2026, 15(2), 175; https://doi.org/10.3390/antibiotics15020175
Submission received: 4 December 2025 / Revised: 22 January 2026 / Accepted: 28 January 2026 / Published: 5 February 2026
(This article belongs to the Special Issue Antibiotic Surveillance and Rational Use in Special Populations: Enhancing Stewardship for Vulnerable Groups)
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Abstract

Background: Multidrug-resistant bacteria have quadrupled globally, impacting effective treatment of infectious diseases. A growing concern is that many Gram-negative and Gram-positive bacteria harbor genes conferring resistance to various antibiotics including colistin. The alarming emergence of colistin resistance is exacerbated by the growing threat of MDR Salmonella species and Listeria monocytogenes (LMO), which pose an escalating risk to global public health. Materials and Methods: In the present study, red meat samples were collected from randomly selected key retail markets in the Eastern Cape province, South Africa, and were evaluated for the incidence of LMO and the Salmonella species using standard culture-based and molecular methods. The confirmed isolates were subjected to antibiotic susceptibility testing. Results: This study demonstrated the occurrence of multidrug-resistant LMO (62%) and Salmonella species (spp.) (58%) in the red meat specimen. There were high resistance rates in both LMO and Salmonella isolates, with LMO exhibiting resistance to penicillin (89%), colistin (81%), nitrofurantoin (78%), and erythromycin (29%), while Salmonella showed resistance to trimethoprim (96.87%), tetracycline, and colistin (90.62%). Antibiotic resistance genes were also detected including BlaTem, erm, Sul1, Sul2 and mcr 1–6. Notably, Salmonella did not harbor any mcr genes that were screened in this study, whereas Listeria isolates harbored the mcr 2 (10%), 3 (7%), 4 (10%), and 6 (3%), with mcr 5 being the most prevalent with 57%. Conclusions: These findings highlight a threat to food security and public health, emphasizing the need for sturdier food handling procedures to ensure safety, enhanced antimicrobial stewardship, and alternative therapeutic strategies to combat antibiotic-resistant pathogens.

1. Introduction

Presently, antimicrobial resistance (AMR) poses a vital therapeutic and public health threat, contributing to increased morbidity and mortality, as well as severe socio-economic and medical losses globally [1]. AMR infections are easily transferred from animals to humans through food consumption, with the primary cause of emerging AMR foodborne bacterial pathogens, including LMO and Salmonella, being the use of antibiotics in veterinary medicine.
Multidrug resistance (MDR), characterized by acquired nonsusceptibility to multiple antimicrobial agents, constitutes a pressing global health concern. It is defined as resistance to at least one agent in three or more antimicrobial categories [2]. The rising prevalence of MDR complicates the effective management of infectious diseases, particularly with limited antibiotic options, including last-resort treatments. The World Health Organization (WHO) rates antibiotic resistance among the top 10 threats to global health, highlighting its potential to significantly impact public well-being. Projections indicate that, if left unchecked, drug-resistant pathogens could drive a dramatic increase in global mortality rates, with deaths potentially rising from approximately 700,000 annually to as many as 10 million by 2050 [3]. This stark forecast underscores the urgent need for immediate, coordinated global action to address the growing threat of antibiotic resistance.
LMO and Salmonella are two major MDR pathogens that threaten human health and food safety [4]. These pathogens are frequently detected in poultry and animals, encouraging the development and spread of diseases, as well as resistance to treatment. Additionally, MDR pathogens can contaminate crops and plants through manure or sewage water used for fertilization and irrigation [5]. Salmonella species are Gram-negative bacteria that cause Salmonellosis by targeting intestinal cells in the gastrointestinal tract [6], leading to symptoms such as stomach cramps, diarrhea, vomiting, nausea, and headaches [7]. Foodborne cases of acute gastroenteritis are most often attributed to non-typhoidal Salmonella serotypes [8]. Globally, Salmonella infections result in over 93.8 million cases annually, with 85.6% of cases attributed to foodborne transmission, causing approximately 155,000 deaths each year, particularly among children under five and the general population over five [9]. Listeriosis, a potentially deadly infection especially in vulnerable individuals, is caused by the Gram-positive bacterium LMO [10]. There are two types of listeriosis: gastrointestinal listeriosis, which typically affects individuals with healthy immune systems, and invasive listeriosis, which primarily impacts those with weakened immune systems, leading to complications such as gastroenteritis, meningitis, stillbirths, and miscarriages [11]. Globally, listeriosis remains a significant public health issue, with approximately 100,000 cases reported annually [12]. Between 2017 and 2018, a Listeriosis epidemic occurred in South Africa, with over 674 cases and 183 deaths (27%) reported [13].
Regional factors, such as antibiotic practices, environmental conditions, and genetic influences, may be crucial in the development of resistance. Antibiotics are classed based on how they affect bacteria [14]. Antibiotics, depending on the type of antimicrobial agent, inhibit bacterial cell wall formation, nucleic acid synthesis [15], protein synthesis, and the folic acid pathway. Antimicrobial modification and inactivation, alterations to the antimicrobial target site, efflux pumps, and membrane impermeability are all mechanisms used to protect bacteria against antibiotics [16].
For instance, bacteria resistant to beta-lactam antibiotics employ strategies including synthesis and use of the beta-lactamase enzyme, which inactivates the beta-lactam ring structure [17] blocking the site-directed and controlled opening of the lactam and acylation of the bacterial enzyme [18], rendering the antibiotic ineffective. Listeria spp. efflux pumps have also been identified as a major resistance mechanism, expelling medicines from the bacterial cell [19]. Furthermore, Enterococcus and Staphylococcus spp. are important reservoirs of resistance genes, aiding the spread of antibiotic resistance in LMO. Additionally, Enterococcus spp. and Staphylococcus spp. serve as important reservoirs of resistance genes, contributing to the spread of AMR in LMO. These methods emphasize the complexity of AMR and its propensity to spread across various bacterial species [20].
Broadening the scope of research to include food-producing animal sources is essential, as they play an essential function in the creation, maintenance, and spread of antimicrobial-resistant strains within the food chain, potentially contributing to the spread of resistance from farm to fork. In South Africa, a study by Mthembu et al. [21] found Salmonella to be particularly prevalent in the country’s livestock, with the highest contamination rates in poultry and pigs. The study also identified multidrug-resistant Salmonella strains, often linked to specific resistance genes and plasmids. Contributing factors include the overuse of antibiotics, inadequate biosecurity measures, and poor animal husbandry practices. Similarly, a study by [22] on LMO isolates from the Western Cape region revealed concerning antibiotic resistance patterns, with many strains resistant to critical antibiotics like ampicillin, tetracycline, and erythromycin.
The presence of multidrug-resistant LMO in South Africa highlights the significance of robust antimicrobial stewardship, increased surveillance, and an exceptional understanding of regional antibiotic resistance trends in preventing the spread of resistant bacteria.
Despite the implementation of rigorous control measures and advancements in meat processing techniques, outbreaks of Salmonellosis and Listeriosis continue to persist worldwide, leading to numerous hospitalizations and fatalities. This ongoing issue reflects the growing threat caused by AMR pathogens and emphasizes the importance for continued research and innovation in strategies for controlling contamination in red meat. The aim of this study is to assess the frequency of multidrug-resistant Salmonella spp. and Listeria monocytogenes in commercial meat specimens purchased from vital retailers in the EC region of SA. By investigating the incidence of these resistant microorganisms in the local meat retailers, the study hopes to provide crucial insights into the present state of AMR in foodborne pathogens and contribute to worldwide efforts to tackle the growing issue of antimicrobial resistance.

2. Materials and Methods

2.1. Ethical Clearance

The University of Fort Hare Research Ethics Committee granted ethical authorization to conduct this investigation, with reference number 202112808-ZM-LM.

2.2. Description of the Study Area

Many people refer to the Eastern Cape (EC) province as a “world in one province.” Of the nine provinces in South Africa, it is one of the two largest provinces. The area, which is in the easternmost province of South Africa, is made up of two metropolitan municipalities and six district municipalities. Though there is potential for expansion in the chemical and petrochemicals, capital goods, manufacturing, automotive, and green sectors, the EC economy is primarily dependent on the automobile industry. While the EC Provincial Growth and Development Programme (PGDP) makes important investments in agriculture and agro-processing, the local government places a higher priority on food security, rural development, health, and education. Although Xhosa-speaking South Africans make up the majority of the EC, 11% and 6% of the population, respectively, speak Afrikaans and English. The Eastern Cape is South Africa’s third-most populous province, accounting for 6.6 million inhabitants (13% of the total). It is SA’s second-largest province in terms of land area, covering 169,580 square kilometers. The EC province is confronted with dilapidated sanitation infrastructure and hygienic water supply facilities, which makes it difficult to prevent and control the dissemination of microbial infections; thus, it is a bothersome public health concern. Figure 1 illustrates the geographical locations of the study sites.

2.3. Specimen Collection and Processing

Raw meat samples were collected from a total of six randomly selected key retail markets (Site A–F) within the Raymond Mhlaba Municipality, Eastern Cape, South Africa. The collected meat specimens were appropriately labeled and aseptically conveyed on ice to the SAMRC Microbial Water Quality Monitoring Centre laboratory at the University of Fort Hare, Alice, South Africa, for processing within four hours of collection. Table 1 illustrates the overall meat sample distribution across the six retail sites.

2.4. Bacterial Isolation

2.4.1. Isolation of Salmonella Species from Meat Specimens

Culture-based methods, as previously outlined by Soguilon-del Rosario et al. [23], were employed to detect and isolate presumptive Salmonella species from meat samples. Approximately 15 g of each sample were completely homogenized into 250 mL of Buffered Peptone Water and incubated at 37 °C for 18–24 h. Thereafter, 1 mL of the turbid culture was inoculated into 9 mL of Rappaport Vassiliadis (RVS) broth to further enhance the growth of presumptive Salmonella species, and the samples were then incubated at 42 °C for 18–24 h. Subsequently, 100 µL of the previously incubated broth cultures were spread plated on XLD agar plates and further incubated at 37 °C for a period of 18–24 h. Colonies displaying a distinctive red to pink color with a black center were selected as presumptive Salmonella isolates and further purified on XLD agar plates. Pure presumptive Salmonella isolates were stored in sterile 25% glycerol cryoprotectant stock and kept at a temperature of −80 °C for further evaluation.

2.4.2. Isolation of LMO from Meat Specimens

Twenty-five grams of each meat sample were thoroughly mixed in 250 mL of sterile buffered peptone water to promote the growth of Listeria species. The homogenized mixture was incubated at 37 °C for 24 h. After enrichment, a loopful of the culture was streaked onto Harlequin Listeria Chromogenic Agar (Ottaviani and Agosti) supplemented with Listeria Chromogenic Selective Supplement and incubated again at 37 °C for 24 h. Characteristic Listeria colonies appeared as small, round, convex, and green in color [24,25]. These suspected colonies were isolated, subcultured on fresh sterile Listeria Selective Agar for purification, and stored at −80 °C in 25% glycerol for further analysis.

2.5. Genomic DNA Extraction

Pure genomic DNA was extracted from presumptive Salmonella and LMO isolates using the boiling procedure outlined by Gugliandolo et al. [26]. Briefly, a loopful of recently grown presumptive Salmonella cultures was injected into sterile Tryptic Soy Broth and cultured at 37 °C for 18 to 24 h. After incubation, turbid cultures were transferred to sterile 2 mL Eppendorf tubes and centrifuged at 12,000 rpm for 10 min to pellet the cells. The cell pellet was redissolved in 200 μL after being washed twice with sterile distilled water. The cell solution was then heat-treated by exposure to a temperature of one hundred °C for 10 min using a Dri-Block. Following boiling, the cell lysate was cooled and then centrifuged at 13,000 rpm for 10 min. The supernatant was deposited into sterile microcentrifuge tubes using sterile technique and was used as the template in PCR amplification.

2.6. Molecular Confirmation of Suspected Salmonella and Listeria Isolates

All presumptive isolates were subjected to polymerase chain reaction (PCR) to confirm their identities. Specific primer pairs, prs (370 bp) and iap (131 bp) (Table 2 were used for molecular confirmation of Listeria genus and LMO, respectively [27]. Primer pairs invA (275 bp) [28] and ompC (204 bp) [29] were used for the confirmation of Salmonella isolates (Table 3).
PCR amplification was carried out in sterile 200 μL tubes using a 25 µL reaction mixture to attain the final volume; the reaction mixture contained 12.5 μL of PCR master mix (Thermo Scientific, Vilnius, Lithuania), 1 μL of each forward and reverse primers (White Sci, Cape Town, South Africa), 5 μL of DNA template, and 5.5 μL of PCR-grade water [31]. A thermal cycler was used to perform the amplification process under the conditions listed in Table 2. Each PCR cycle included negative control, while the positive control strains were L. monocytogenes ATCC 19118 and L. ivanovii ATCC 19119.

2.7. Antibiotics Susceptibility Profiling

The confirmed isolates were subjected to antibiotic susceptibility testing as outlined by the Clinical Laboratory Standards Institute (CLSI) [32]. Mueller Hinton agar plates were used to assess the antibiotic susceptibility profiles of Listeria against a panel of 10 antibiotics and Salmonella isolates against a panel of 9 antibiotics, across different antibiotic classes. Table 4 outlines the commercial antibiotics discs used for this study.

2.8. Antibiotic Resistance Gene Profiling

Isolates of Salmonella and Listeria displaying phenotypic resistance profiles were further examined using PCR for the prevalence of antibiotic resistance genes. Table 5 outlines the oligonucleotide primer sequences used for the detection of resistance genes. PCR amplifications were performed using a thermal cycler, and amplified DNA products were visualized on 2% agarose gels with 5 μL of ethidium bromide. A 100-base pair DNA ladder was used as a molecular size reference. Gel electrophoresis was conducted for 50 min.

3. Results

A sum of 65 raw meat samples obtained from six retail markets were screened for the presence of Salmonella and LMO isolates. A total of 44 (68%) isolates were phenotypically identified as presumptive Salmonella spp. while an additional 48 (74%) isolates were identified as presumptive Listeria spp. Table 6 demonstrates the frequency of detection of Salmonella and Listeria spp.

3.1. Molecular Confirmation

3.1.1. Molecular Confirmation of Salmonella spp. Using PCR Technique

Following the PCR amplification, 2% agarose gel electrophoresis was performed on the resultant amplicons (Figure 2). The gel analysis revealed the presence of two distinct bands corresponding to the expected sizes of the invA (275 bp) and opmC (204 bp) genes, confirming the identity of the isolates as belonging to the Salmonella genus.
From a total of 44 presumptive Salmonella isolates, only 32 (73%) were identified as Salmonella spp. and were recovered from raw beef, mutton and sausage samples (Table 6).

3.1.2. Molecular Confirmation of Listeria spp. Using PCR Technique

PCR confirmation of Listeria (Genus) and LMO was performed using prs (370 bp) and iap (131 bp) primers (Figure 3 and Figure 4). From a total of 48 presumptive Listeria isolates, 37 (77%) were positive for the Listeria genus, and 30 (81%) of these were identified as L. monocytogenes using Iap primer.

3.2. Antibiotics Susceptibility Profiling

3.2.1. Antibiotic Susceptibility Profiling of the Confirmed Salmonella Isolates

The antimicrobial patterns were analyzed according to CLSI guidelines, which are summarized in Figure 5 below. Inhibition zones were measured in millimeters with calipers and classified as susceptible, intermediate, or resistant for each antibiotic based on Clinical Laboratory Standards (2018) [32]. The highest resistance rate in Salmonella spp. was observed against trimethoprim, with a percentage of 97%, followed by tetracycline and colistin with 91%. Imipenem was the only antibiotic which Salmonella isolates exhibited 100% susceptibility, with Streptomycin closely at 97%.

3.2.2. Antibiotic Susceptibility Profiling of the Confirmed LMO

Antibiotic susceptibility profiles demonstrated significant variation across the LMO isolates (Figure 6). Amikacin and gentamicin exhibited 100% susceptibility, showing excellent effectiveness. Azithromycin had the highest susceptibility rate (94%), followed closely by meropenem (81%). Penicillin G, on the other hand, had the highest level of resistance, with 89% of isolates resistant. Furthermore, ampicillin and colistin both showed high resistance (81%), while erythromycin showed intermediate resistance (29%).

3.2.3. Multiple Antibiotics Resistance Phenotypes and Multiple Antibiotic Resistance Index

Multiple resistance characteristics were observed in 73% of Salmonella isolates (Table 7). Of these isolates, about 20% were resistant to as many as five different antibiotics, while 42% to four, and the few remaining isolates to three. These isolates had exhibited antibiotic resistance indices ranging from 0.3 to 0.5, with a minimum of 0.3 and a maximum of 0.5. Thus, surpassing the 0.2 MARI threshold, indicating that they originated from an environment where antibiotic usage was more prevalent. Similarly, MAR phenotypes in LMO revealed a high prevalence of antibiotic resistance, with over 60% of isolates exhibiting resistance to 3–5 antibiotics (Table 8). Notably, the MAR indices in this study varied; L. monocytogenes isolates exhibited MAR indices between 0.3 and 0.5, surpassing the acceptable MARI threshold.

3.3. Antimicrobial Resistance Determinants Among Listeria and Salmonella Isolates

Among the AMR gene determinants profiled; Bla-Tem was the only resistance gene amplified among the β-lactamase-resistant Listeria isolates (Figure 7). Amongst the confirmed L. monocytogenes, 43% harbored the Bla-TEM resistance gene, conferring resistance to β-lactam antibiotics. Conversely, 9% Salmonella isolates harbored Sul2 among the Sulfonamide-resistant isolates (Figure 8), whereas 11% carried the BlaTem β-lactamase resistant Salmonella isolates (Figure 9).
Disturbingly, 81% of Listeria isolates were included at least one colistin resistance gene, indicating a high rate of plasmid-mediated colistin resistance. Despite displaying colistin-resistant phenotypes, none of the Salmonella isolates harbored the colistin resistance genes. The resistance gene profile of colistin-resistant Listeria isolates indicates the presence of distinct mcr genes. Although the mcr-1 gene was not detected from all isolates, 10% of isolates harbored the mcr-2 and mcr-4 genes. A total of 3% of the isolates had the mcr-6 gene, while 7% had the mcr-3 gene. With mcr-5 was found in 57% of the isolates, it was the most prevalent. Table 9 summarizes the percentage distribution β-Lactam-resistant Salmonella and LMO isolates, across the study sites.
Following the amplification of the Sul2 gene, the amplicons were subjected to 2% gel electrophoresis and viewed under a UV transilluminator. Distinct bands corresponding to a size of 625 bp were observed, as illustrated in Figure 8.
Following the amplification of the BlaTem gene, the amplicons were subjected to 2% gel electrophoresis and viewed under a UV transilluminator. Distinct bands corresponding to a size of 445 bp were observed, as illustrated in Figure 8.

3.4. Colistin Resistance

Colistin is reportedly more effective against Gram-negative bacteria, and its primary mode of action is to disrupt the outer and the inner membrane of the Gram-negative bacteria. Colistin, however, regulates a number of other mechanisms, including the hydroxyl radical death pathway by generating reactive oxygen species (ROS), which include hydrogen peroxide (H2O2), superoxide (O2−), and hydroxyl radicals (OH). These substances can all cause oxidative stress in Gram-positive bacteria. These processes have the potential to cause oxidative damage to proteins, lipids, and DNA, which in turn can cause bacterial cell death. Additionally, Gram-positive bacteria have been shown to exhibit colistin’s antibacterial activity by inhibiting essential respiration enzymes, such as the NADH complexes [40,41,42,43].
Among the antibiotic resistance genes revealed in the present study, the mcr genes were found to be significant resistance determinants in colistin-resistant Listeria and Salmonella isolates. Notably, 81% of LMO isolates included at least one colistin resistance gene, indicating a high rate of plasmid-mediated colistin resistance. Despite displaying colistin-resistant phenotypes, none of the isolates of Salmonella had colistin resistance genes (mcr-1 to mcr-6). The resistance gene profile of colistin-resistant Listeria monocytogenes isolates indicates a variable presence of distinct mcr genes. Although the mcr-1 gene was absent from all isolates (0%), 10% of isolates had the mcr-2 and mcr-4 genes. A total of 3% of the isolates had the mcr-6 gene, while 7% had the mcr-3 gene. With mcr-5 was found in 57% of isolates, it was the most prevalent resistance gene, suggesting that colistin-resistant bacteria had a high frequency of this gene. These findings suggest that meat samples are potential reservoirs of plasmid-mediated colistin resistance (mcr) genes. Additionally, the findings of this study further advocate the prospect of horizontal gene transfer among bacteria in the environment. Figure 9, Figure 10, Figure 11 and Figure 12 illustrate the gel electrophoresis image for the detection of mcr resistance genes from the confirmed colistin-resistant Listeria monocytogenes.

4. Discussion

The complex and multifaceted nature of multidrug resistance makes it a formidable challenge to address, requiring a comprehensive approach that spans various sectors. The presence of LMO and Salmonella in meat, which has emerged as a major food safety issue, is a stark illustration of this challenge. As research has consistently shown, meat can serve as a reservoir for these pathogens, contributing to outbreaks of listeriosis and salmonellosis associated with contaminated products, and highlighting the need for enhanced surveillance, improved food safety practices, and targeted interventions to mitigate the risk of MDR pathogens in the food chain.
The study presents significant findings regarding the presence of Salmonella and LMO in meat products, underlining serious food safety concerns in the Eastern Cape region. With 74% of presumptive Salmonella isolates testing positive and confirming the presence of the OmpC and InvA genes, the study’s results align with prior research by Msolo et al. [39], further confirming Salmonella’s widespread presence in the region. The use of PCR to identify these genes provides a reliable method for tracing Salmonella strains, which is crucial for monitoring foodborne pathogens in the area.
The present study also emphasizes the variable presence of multidrug-resistant LMO in beef and other meats. This study adds to that body of scientific evidence, highlighting the 81% contamination rate of meat samples with LMO, which advocates the critical need for improved food safety measures. Although the findings differ significantly from those of a South African study by Matle et al. [44], which reported a much higher contamination rate of 31.4% in Gauteng and a lower rate of 5% in the Eastern Cape across various meat types, they confirm that LMO contamination remains a serious and tenacious concern.
The study also highlighted Salmonella isolates’ multidrug resistance, which complicates food safety and public health in the Eastern Cape. Salmonella isolates exhibited disturbingly high levels of resistance. Trimethoprim had a resistance rate of 96.87% among the isolates, followed by tetracycline and colistin, both with a resistance rate of 90.62%. These findings are consistent with previous studies, including that conducted by Amer et al. [45], which found that Salmonella enteritidis isolates exhibited 100% resistance to trimethoprim, whilst showing a significantly lower rate of 18.8% resistance to colistin. Similarly, Prasertsee et al. [46] found near-universal resistance to ampicillin and tetracycline in isolates from abattoirs, with farm isolates also showing high resistance rates against these antibiotics.
The enhanced resistance of Salmonella to antibiotics such as trimethoprim, tetracycline, and colistin can be attributed to several interconnected factors. One of the key factors is the excessive use and misuse of antibiotics in both human and veterinary medicine [47]. tetracycline and trimethoprim are two examples of antibiotics that are frequently utilized in agriculture to treat infections and to help cattle grow and prevent diseases. Salmonella strains can develop resistance through horizontal gene transfer, allowing bacteria to share genetic material with other species [48]. This can be contracted by humans through tainted meat or close contact with animals. This accelerates the spread of resistance, including tetracycline, trimethoprim, and colistin, across bacterial populations.
Finally, Salmonella can develop resistance through mutations, which are often triggered by the selective pressure of antibiotic exposure [49]. When exposed to antibiotics like trimethoprim, tetracycline, or colistin, resistant strains are more likely to survive and reproduce, leading to an increase in the resistant population. This process underscores the need for responsible antibiotic use, stronger surveillance, and regulations to control resistance, particularly in agricultural and clinical settings.
Since the first documentation of antibiotic-resistant Listeria species in 1988, concerns about antimicrobial resistance in LMO have steadily increased. Traditionally, β-lactam antibiotics such as ampicillin, penicillin, and cephalothin were considered effective therapeutic agents against LMO. However, Du et al. [50] reported strong resistance to ampicillin. Subsequently, Shourav et al. [51] observed similar resistance patterns, particularly against penicillin and erythromycin, highlighting the continued emergence and spread of resistant strains. More recently, a study by Kayode et al. [52] found that LMO isolates from ready-to-eat meat in South Africa showed high antimicrobial resistance against amoxicillin and erythromycin. Notably, 85.44% of isolates exhibited multidrug resistance.
Now, this particular study revealed that LMO isolates also exhibited elevated resistance levels, aligning with previously reported trends. High resistance rates were observed against penicillin (89%), colistin (81%), nitrofurantoin (78%), and erythromycin (29%). These findings further confirm the alarming expansion of multidrug-resistant LMO.
Penicillin, critical in both human and veterinary medicine for treating Gram-positive infections including those caused by Listeria, is losing effectiveness likely due to its overuse and the emergence of β-lactamase-producing strains. Similarly, resistance to nitrofurantoin, a drug commonly used to treat urinary tract infections by disrupting bacterial metabolism, suggests regional differences in resistance mechanisms and raises concerns over its efficacy in controlling Listeria in food products. Erythromycin, a macrolide used against Gram-positive bacteria and atypical pathogens [53], shows a 29% resistance rate in LMO, potentially due to its widespread use in clinical and veterinary settings, which promotes resistance through mechanisms such as ribosomal modification [54]. In contrast, gentamycin, an aminoglycoside which is more active against Gram-negative bacteria, has seen reduced usage in animal husbandry, which may help preserve its effectiveness by reducing selective pressure.
LMO uses a number of mechanisms to impede the effects of antibiotics, making it a formidable threat in both clinical and food industry settings. These resistance strategies include biofilm formation, the use of drug efflux pumps, enzymatic inactivation of antibiotics, restricted uptake of antimicrobial agents, and the alteration of antibiotic target sites to prevent effective binding [16,55]. Among these, biofilm formation stands out as a particularly effective adaptive mechanism. Biofilms not only protect the bacteria from environmental stresses such as pH changes and disinfectants but also improve access to nutrients and water while facilitating the horizontal transfer of resistance genes. This ability significantly enhances bacterial survival and contributes to increased resistance to antimicrobial agents, posing a major challenge to food security and public health.
Expanding on this, a study by Myintzaw et al. [56] emphasized the significant role of biofilm formation in the survival of LMO under adverse circumstances commonly encountered in food manufacturing and storage environments. The study found that when exposed to such stressors, LMO activates specific stress response genes that enable it to adapt and persist. A study by Luque-Sastre et al. [54] further highlights these resistance strategies. Resistance to quinolones and fluoroquinolones arises through plasmid-mediated resistance genes like qnr, and efflux pumps such as Lde, MdrL, and FepA [57,58,59]. Tetracycline resistance in Listeria is linked to five main genes: tet(A), tet(K), tet(L), tet(M), and tet(S), each with a distinct role [54,60]. Mobile genetic elements play a key role in the spread of resistance across Listeria populations, emphasizing the importance of monitoring antimicrobial use and resistance patterns in both clinical and food-production settings. The increased frequency of these strains in food and food processing settings is probably a result of these adaptive features, highlighting the threats to public health posed by their resistance and persistence.
The rise in multiple ARGs in Salmonella strains found in meat represents a significant global health threat, largely driven by the use of antibiotics in livestock and aquaculture [61]. Research indicates a strong connection between AMR pathogens in farm animals and those found in slaughtered products, suggesting that while similar genetic patterns may exist, they do not conclusively prove that pathogens on meat solely originate from animal carriers [62]. Rather, a considerable portion of the contamination is linked to farm sources, particularly during critical processing stages such as scalding, de-feathering, evisceration, meat inspection, and transport through conveyor belts and chilling or holding areas [63]. He et al. [64] further emphasize that environmental factors, such as contaminated water and feed, can introduce resistance genes into livestock.
Salmonella, in particular, can acquire resistance through mechanisms like plasmid-mediated resistance, mutations in antibiotic binding sites, and active efflux pumps allowing them to survive under antibiotic pressure [65]. Given that one of the main causes of the rise in antibiotic-resistant Salmonella in the food system is the abuse of antibiotics in both animal husbandry and meat processing, these findings highlight the need to tackle this issue.
Similarly, the analysis of MAR phenotypes in LMO from meat specimens in the EC region revealed a high prevalence of antibiotic resistance, with most isolates exhibiting resistance to 3–5 antibiotics. Notably, the MAR phenotypes were diverse, with all but four patterns being unique, further indicating the wide-ranging resistance profiles present among the isolates. The Listeria isolates in this study exhibited MAR indices between 0.3 and 0.5, surpassing the acceptable threshold value of 0.2, which highlights the significant prevalence of multidrug resistance in the region. This discovery not only illustrates the high level of resistance in Listeria monocytogenes, but it also highlights the incorrect use of antimicrobials in the area, adding to a growing public health concern. The widespread antibiotic resistance observed in both Salmonella and Listeria reinforces the critical need to address the overuse of antibiotics, particularly in livestock farming and meat processing, as these practices play a pivotal role in the emergence and spread of resistant pathogens. Additionally, the fact that both species exhibit plasmid-mediated resistance raises concerns about the possibility of horizontal gene transfer, which would make the dissemination of resistance among various bacterial populations much more severe. These results highlight the critical need for better antimicrobial stewardship and strengthened food safety protocols to reduce the negative implications of antibiotic resistance on public health.
This study examined confirmed LMO and Salmonella for relevant antibiotic resistance genes (ARGs), including BlaTem, erm, Sul1, Sul2, and mcr 1–6 (plasmid-mediated colistin resistance genes). The results revealed distinct ARG profiles for each pathogen. In Listeria, only BlaTem and mcr genes were detected, indicating a relatively low ARG prevalence. Notably, BlaTem was present in beef samples from all shops, revealing the possible spread of antibiotic-resistant Listeria along the food chain. In contrast, Salmonella isolates primarily harbored the Sul2 gene, with a prevalence similar to a study by Nazari et al. [66] (8.82% vs. 82.35% for Sul1). Among beta-lactam-resistant isolates (84.37%), only 11.11% carried the BlaTem gene, consistent with Naderi Mezajin et al. [67] (10%). This consistency highlights the low prevalence of BlaTem among beta-lactam-resistant isolates, indicating a specific resistance pattern.
The phenotypic resistance to colistin observed in Salmonella isolates during the antibiotic susceptibility testing suggests the presence of resistance mechanisms. Nonetheless, the dearth of mcr-1 to mcr-6 genes in these isolates implies that the plasmid-borne mcr genes investigated in this study may not constitute the mechanism of resistance. This finding suggests the possibility of alternative mechanisms of resistance, such as chromosomally encoded modifications. Mutations in genes like pmrA or pmrB, which are associated with lipopolysaccharide modifications, could be contributing to the observed resistance. Furthermore, the presence of mcr-7 and mcr-10 genes, which were not screened for, may be the source of resistance in these isolates. The potential involvement of these genes emphasizes the need for a more thorough investigation to completely understand the genetic basis of colistin resistance in Salmonella. One of the limitations in the present study is the lack of in-depth molecular analysis of colistin-resistant Salmonella isolates and the detection of other mcr variants (mcr-7 to mcr-10) which would give insight into the genetic profile of colistin resistance among Salmonella isolates.
The study reveals a significant prevalence of mobile colistin resistance genes, specifically mcr-5, in 57% of LMO isolates from meat samples. Conversely, other mcr genes exhibited significantly lower prevalence rates, with mcr-2 and mcr-4 each occurring in 10% of isolates, mcr-3 in 7%, and mcr-6 in 3%. Notably, mcr-1 was conspicuously absent. These results imply that mcr-5 is the primary driver of colistin resistance in Listeria within this study, whereas other mcr genes contribute marginally.
Mobile colistin resistance (mcr) genes are typically linked with Gram-negative bacteria, but there is evidence that they exist in Gram-positive organisms and may be transmitted to Gram-negative bacteria. While the mcr-1 gene is most well-known in Enterobacteriaceae (e.g., E. coli), research indicates that some mcr variations arose in Gram-positive or non-Enterobacteriaceae hosts. Moreover, the widespread spread of mcr genes in animals and humans poses a significant public health danger. Previous research indicated higher prevalence of mcr genes in animals and food samples compared to human samples, confirming the concept that mcr transmission occurs via the food chain [68]. The transmission of mcr between environmental strains is clonally unconstrained [69]. Furthermore, mobile colistin resistance-gene-comprising bacteria can spread through contact with mcr-containing reservoirs, consumption of infected animals or plant-based food and water. The ability of plasmids to horizontally transmit these auxiliary genes to new hosts has important consequences for ecosystems and human health, as evidenced by the fast spread of plasmid-mediated antibiotic resistance genes. The spread of MDR conjugative plasmids harboring antibiotic resistance genes has emerged as one of the most serious public health hazards to date [68,69,70,71,72].
It is pertinent to acknowledge that research on mcr genes in Listeria and Gram-positive bacteria is scarce, with existing studies primarily focusing on Gram-negative bacteria, such as Klebsiella pneumoniae and E. coli [69]. The present study may be one of the first regional studies of colistin-resistant determinants in Listeria species focusing on meat samples. This knowledge gap has significant implications for public health and food safety. As Salmonella and LMO continue to evolve and adapt, acquiring resistance to multiple antibiotics, our approach to food safety, antibiotic use, and public health must also evolve.

5. Conclusions

The isolation of MDR Salmonella and LMO from red meat highlights a critical threat to food safety and public health. The present study demonstrates the prevalence of multidrug-resistant Listeria monocytogenes and Salmonella species in commercial meat specimens traded in key retailers within the EC region, South Africa, which is a major cause for public health and food safety concern. The findings of the present study further highlight the critical urgency of implementing stricter food safety measures, promoting responsible antimicrobial use, and advancing alternative therapies to counter the spread of antibiotic-resistant microbes in the food chain. The disturbingly high prevalence rates of Salmonella and LMO, combined with significant antibiotic resistance, demand immediate action from regulatory agencies, food producers, and healthcare professionals. The findings of this study exhibit far-reaching implications, underscoring the need for region-specific antimicrobial resistance surveillance, addressing the misuse of antibiotics in meat processing and animal husbandry, and prioritizing consumer health. To reduce the public health impact of antibiotic resistance, collaborative efforts from stakeholders across agriculture, healthcare, and scientific research are essential. Strengthening the monitoring, handling and control measures in the meat supply chain, specifically processing, improving antimicrobial use in animal husbandry, and exploring alternative therapies for treating Salmonella and Listeria infections are imperative steps in alleviating the burden of MDR LMO and Salmonella pathogens within the meat industry. To safeguard public health and food safety requires a comprehensive, multi-pronged approach that prioritizes and emphasizes consumer health safety and the prudent use of antibiotics to avert the lingering threat of foodborne multidrug-resistant pathogens of public health importance.

Author Contributions

L.M. is the corresponding author and contributed to the manuscript through conceptualization of the study, validation of field procedures, monitoring and supervision of data collection, manuscript development, formal analysis, data curation, writing and editing. Z.M. contributed to conceptualization of the study, validation of field procedures, data compilation, monitoring and supervision of data collection, formal analysis, data curation, literature review, writing and editing. S.N. contributed to manuscript editing and revisions. A.I.O. contributed to data analysis, manuscript editing and revisions, supervision, funding acquisition, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

We are thankful to the South African Medical Research Council for funding support at the SAMRC Microbial Water Quality Monitoring Centre. Grant Agreement No. SAMRC-UFH-P790 and the National Research Foundation of South Africa (Grant number RCHDI241119283812) for financial support.

Institutional Review Board Statement

The University of Fort Hare Research Ethics Committee granted ethical authorization to conduct this investigation, with reference number 202112808-ZM-LM.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets used in the present study will be made available on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

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Antibiotics 15 00175 g001
Figure 1. A map of the EC province highlighting the geographical locations of the study sites.
Figure 1. A map of the EC province highlighting the geographical locations of the study sites.
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Figure 2. A gel electrophoresis image illustrating the confirmed Salmonella isolates that were recovered from commercial meat samples (Lane M: DNA marker, lane 1: negative control, and Lanes 2 to 9: representatives of the positive Salmonella isolates).
Figure 2. A gel electrophoresis image illustrating the confirmed Salmonella isolates that were recovered from commercial meat samples (Lane M: DNA marker, lane 1: negative control, and Lanes 2 to 9: representatives of the positive Salmonella isolates).
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Figure 3. Agarose gel electrophoresis image demonstrating the PCR amplification products of representative Listeria genus isolates recovered from meat samples. Lane M: 100 bp DNA ladder (Thermo Scientific); Lanes 1 and 2: positive controls L. monocytogenes ATCC 19118 and L. ivanovii ATCC 19119, respectively; Lane 3: negative control; and Lanes 4–13: representatives of the positive Listeria isolates. DNA fragments were separated on a 2% agarose gel at 100 V for 50 min.
Figure 3. Agarose gel electrophoresis image demonstrating the PCR amplification products of representative Listeria genus isolates recovered from meat samples. Lane M: 100 bp DNA ladder (Thermo Scientific); Lanes 1 and 2: positive controls L. monocytogenes ATCC 19118 and L. ivanovii ATCC 19119, respectively; Lane 3: negative control; and Lanes 4–13: representatives of the positive Listeria isolates. DNA fragments were separated on a 2% agarose gel at 100 V for 50 min.
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Figure 4. A representative gel image for PCR amplification of Listeria monocytogenes recovered from commercial meat specimens. Lane M: 100 bp ladder; Lane 1: Listeria monocytogenes ATCC 19118, the positive control strain; Lane 2: negative control; and Lanes 3–12: representatives of the confirmed Listeria monocytogenes.
Figure 4. A representative gel image for PCR amplification of Listeria monocytogenes recovered from commercial meat specimens. Lane M: 100 bp ladder; Lane 1: Listeria monocytogenes ATCC 19118, the positive control strain; Lane 2: negative control; and Lanes 3–12: representatives of the confirmed Listeria monocytogenes.
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Figure 5. Antimicrobial susceptibility patterns of the positive Salmonella isolates recovered from meat samples.
Figure 5. Antimicrobial susceptibility patterns of the positive Salmonella isolates recovered from meat samples.
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Figure 6. Antimicrobial susceptibility patterns of LMO recovered from commercial meat samples.
Figure 6. Antimicrobial susceptibility patterns of LMO recovered from commercial meat samples.
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Antibiotics 15 00175 g007
Figure 7. Agarose gel electrophoresis image of PCR products amplified from antibiotic-resistant Listeria isolates for the detection of BlaTem (445 bp) resistance gene from the β-Lactam resistant- Listeria monocytogenes recovered from commercial meat specimens. Lane M: 100 bp ladder; Lane 1: negative template control, Lanes 2–12: representatives of some of the confirmed Listeria isolates exhibiting the BlaTem resistance gene.
Figure 7. Agarose gel electrophoresis image of PCR products amplified from antibiotic-resistant Listeria isolates for the detection of BlaTem (445 bp) resistance gene from the β-Lactam resistant- Listeria monocytogenes recovered from commercial meat specimens. Lane M: 100 bp ladder; Lane 1: negative template control, Lanes 2–12: representatives of some of the confirmed Listeria isolates exhibiting the BlaTem resistance gene.
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Figure 8. Agarose gel electrophoresis image of PCR products amplified from antibiotic-resistant Salmonella isolates for the detection of Sul2 (625 bp) resistance gene from the sulfonamide-resistant Salmonella isolates recovered from commercial meat specimens; (Lane M: DNA marker; Lane 1: negative template control; Lanes 2–7-representatives of Salmonella isolates positive for the Sul2 resistance gene).
Figure 8. Agarose gel electrophoresis image of PCR products amplified from antibiotic-resistant Salmonella isolates for the detection of Sul2 (625 bp) resistance gene from the sulfonamide-resistant Salmonella isolates recovered from commercial meat specimens; (Lane M: DNA marker; Lane 1: negative template control; Lanes 2–7-representatives of Salmonella isolates positive for the Sul2 resistance gene).
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Figure 9. Agarose gel electrophoresis of PCR products amplified from antibiotic-resistant Salmonella screened for the BlaTem resistant gene. Lane M: 100 bp DNA marker; Lane 1: negative template control; Lanes 2–4: representatives of some of the confirmed Salmonella isolates that were positive for the BlaTem gene.
Figure 9. Agarose gel electrophoresis of PCR products amplified from antibiotic-resistant Salmonella screened for the BlaTem resistant gene. Lane M: 100 bp DNA marker; Lane 1: negative template control; Lanes 2–4: representatives of some of the confirmed Salmonella isolates that were positive for the BlaTem gene.
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Figure 10. Agarose gel electrophoresis image of PCR products amplified from antibiotic-resistant Listeria isolates screened for the detection of colistin resistance genes using the mcr 2, mcr 3 and mcr 4 gene primers. Lane M: 100 bp ladder; Lane 1: negative template control, Lanes 2–4: Listeria isolates exhibiting mcr 2 resistance gene, Lanes 5–6: Listeria isolates exhibiting mcr 3 resistance gene, Lanes 7–8: Listeria isolates exhibiting mcr 4 resistance gene.
Figure 10. Agarose gel electrophoresis image of PCR products amplified from antibiotic-resistant Listeria isolates screened for the detection of colistin resistance genes using the mcr 2, mcr 3 and mcr 4 gene primers. Lane M: 100 bp ladder; Lane 1: negative template control, Lanes 2–4: Listeria isolates exhibiting mcr 2 resistance gene, Lanes 5–6: Listeria isolates exhibiting mcr 3 resistance gene, Lanes 7–8: Listeria isolates exhibiting mcr 4 resistance gene.
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Figure 11. The agarose gel electrophoresis image of PCR products amplified from Listeria monocytogenes isolates obtained from meat samples, specifically targeting the mcr-5 colistin resistance gene. Lane M: 100 bp ladder, followed by PCR products of some of the confirmed colistin-resistant Listeria monocytogenes isolates (Lanes 1–10).
Figure 11. The agarose gel electrophoresis image of PCR products amplified from Listeria monocytogenes isolates obtained from meat samples, specifically targeting the mcr-5 colistin resistance gene. Lane M: 100 bp ladder, followed by PCR products of some of the confirmed colistin-resistant Listeria monocytogenes isolates (Lanes 1–10).
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Figure 12. The agarose gel electrophoresis image of the PCR product screening for the mcr-6 colistin resistance gene in an LMO isolate. Lane M: a 100 bp ladder, Lane 1: Negative control, Lane 2: Negative isolate and Lane 3: PCR product from the mcr 6 positive isolate.
Figure 12. The agarose gel electrophoresis image of the PCR product screening for the mcr-6 colistin resistance gene in an LMO isolate. Lane M: a 100 bp ladder, Lane 1: Negative control, Lane 2: Negative isolate and Lane 3: PCR product from the mcr 6 positive isolate.
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Table 1. Overall sample distribution across the six retail sites.
Table 1. Overall sample distribution across the six retail sites.
Sites (Retailers/Supermarkets)Classification of Retailers/SupermarketsMaximum Number of Raw Meat Samples Collected (n = 65)
BeefMuttonPorkSausages
Site ALarge5443
Site BMedium2343
Site CMedium4230
Site DMedium2222
Site EMedium3330
Site FMedium2333
Total number of raw meat samples collected across the six retail sites18171911
Grand Total65 meat samples
Large = This refers to much bigger or major supermarkets with more than 5 outlets. Medium = This refers to moderate supermarkets with 2–5 outlets.
Table 2. Oligonucleotide primers used for the confirmation of presumptive Listeria (Genus) and Listeria monocytogenes.
Table 2. Oligonucleotide primers used for the confirmation of presumptive Listeria (Genus) and Listeria monocytogenes.
PrimersPrimer Sequences (5′–3′)Amplicon Size (bp)Annealing Temperature (°C)Reference (s)
prsFGCTGAAGAGATTGCGAAAGAAG37052[30]
prsRCAAAGAAACCTTGGATTTGCGG
iapFACAAGCTGCACCTGTTGCAG13156[27]
iapRTGACAGCGTGTGTAGTAGCA
Table 3. Oligonucleotide primer sequences and PCR thermal cycling parameters for the molecular confirmation of Salmonella isolates.
Table 3. Oligonucleotide primer sequences and PCR thermal cycling parameters for the molecular confirmation of Salmonella isolates.
Primer(s)Primer Sequence(s)Amplicon Size (bp)PCR Thermal Cycling ParametersCycles
ompCF-ATCGCTGACTTATGCAAT
R-CGG GTTGCGTTATAGGTC		20495 °C, 95 °C, 57 °C, 72 °C, 72 °C
1′, 20″, 15″, 2′, 7′		35
invaAF-TATCGCCACGTTCGGGCAA
R-TCGCACCGTCAAAGGAACC		275
Table 4. List of antibiotic discs used in this study.
Table 4. List of antibiotic discs used in this study.
Antimicrobial ClassAntimicrobial AgentPotency
MacrolidesAzithromycin15 µg
Erythromycin15 µg
β-lactamsPenicillin G10 µg
Ampicillin10 µg
PolymyxinsColistin25 µg
Aminoglycosides Streptomycin10 µg
Amikacin30 µg
Gentamycin10 µg
Tetracyclines Tetracycline30 µg
NitrofuransNitrofurantoin200 µg
Cephalosporin antibiotics (3rd generation)Cefotaxime30 µg
AntimetabolitesTrimethoprim25 µg
FluoroquinolonesCiprofloxacin5 µg
3rd Generation Cephalosporins Ceftazidime30 µg
CarbapenemsMeropenem10 µg
Imipenem10 µg
Table 5. Oligonucleotide primer sequences employed in this study for the detection of resistance genes.
Table 5. Oligonucleotide primer sequences employed in this study for the detection of resistance genes.
Resistance GenesNucleotide Sequence (5′→3′)Amplicon Size (bp)Annealing Temperature (°C)Reference(s)
mcr-1F: CGGTCAGTCCGTTTGTTC
R: CTTGGTCGGTCTGTAGGG		30955[33]
mcr-2F: TGTTGCTTGTGCCGATTGGA
R: AGATGGTATTGTTGGTTGCTG		56765[34]
mcr-3F: TTGGCACTGTATTTTGCATTT
R: TTAACGAAATTGGCTGGAACA		54250[35]
mcr-4F: ATTGGGATAGTCGCCTTTTT
R: TTACAGCCAGAATCATTATCA		48858[36]
mcr-5F: TATCTCGACAAGGCCATGCTG
R: GAATCTGGCGTTCGTCGTAGT		61350[37]
mcr-6F: GTCCGGTCAATCCCTATCTGT
R: ATCACGGGATTGACATAGCTAC		55655[38]
BlaTemF: TTTCGTGTCGCCCTTATTC
R: CCGGCTCCAGATTTATCA		44560[39]
Sul2F: CGGCATCGTCAACATAA
R: GTGTGCGGATGAAGTCA		62550
Table 6. An overview of the frequency of detection of Salmonella and Listeria isolates recovered from commercial meat samples.
Table 6. An overview of the frequency of detection of Salmonella and Listeria isolates recovered from commercial meat samples.
Listeria spp.
Type of meatNumber of screened presumptive isolates (n = 48)Number of confirmed Listeria spp. (n = 37)Number of confirmed LMO (n = 30)
Beef181612
Mutton1286
Sausage1088
Pork854
Total483730
Salmonella   spp.
Type of meatNumber of screened presumptive isolates (n = 44)Number of confirmed Salmonella isolates
Beef1818
Mutton88
Sausage116
Pork7-
Total4432
Table 7. The MARPs and MARI of the confirmed Salmonella spp.
Table 7. The MARPs and MARI of the confirmed Salmonella spp.
No. of Salmonella spp. IsolatesMARP of Salmonella spp.MARI
1TS-CAZ-T0.3
29TS-CAZ-T0.3
36CAZ-T-CO0.3
18TS-T-CO0.3
20TS-CAZ-T0.3
3TS-CTX-CAZ-CO0.4
4TS-CAZ-T-CO0.4
35TS-CAZ-T-CO0.4
40TS-CAZ-T-CO0.4
5TS-CAZ-T-CO0.4
39TS-CTX-CAZ-CO0.4
7TS-CAZ-T-CO0.4
8TS-CTX-CAZ-CO0.4
10TS-CAZ-CTX-CO0.4
11TS-CAZ-T-CO0.4
13TS-CAZ-T-CO0.4
14TS-CTX-T-CO0.4
15TS-CAZ-T-CO0.4
16TS-CAZ-T-CO0.4
17TS-T-ATH-CO0.4
23TS-CAZ-T-CO0.4
32TS-CTX-CAZ-CO0.4
33TS-CTX-CAZ-CO0.4
34TS-CTX-CAZ-T-CO0.5
22TS-CAZ-T-ATH-CO0.5
31TS-CTX-CAZ-T-CO0.5
38TS-CTX-CAZ-T-CO0.5
2TS-CTX-CAZ-T-CO0.5
6TS-CAZ-CTX-T-CO0.5
9TS-CAZ-CTX-T-CO0.5
12TS-CTX-CAZ-T-CO0.5
Table 8. The MARPs and MARI of the confirmed Listeria isolates.
Table 8. The MARPs and MARI of the confirmed Listeria isolates.
MAR PhenotypesNumber of AntibioticsNo ObservedMARI
PG-NI-CO350.27
PG-MEM-CO310.27
PG-NI-CO350.27
PG-AP-NI310.27
PG-E-NI-CO310.27
CIP-NI-CO310.27
PG-AP-NI-CO440.36
PG-CIP-CO-OT410.36
PG-MEM-NI-CO430.36
PG-E-NI-CO430.36
PG-AP-NI-CO440.36
PG-E-NI-CO430.36
PG-MEM-NI-CO430.36
PG-E-NI-CO430.36
PG-AP-NI-CO440.36
PG-E-NI-CO430.36
PG-MEM-NI-CO430.36
PG-AP-NI-CO440.36
PG-AP-E-MEM-CO510.45
PG-E-CIP-NI-CO510.45
PG-E-MEM-NI-CO510.45
PG-ATH-CIP-CO-OT510.45
Key: Penicillin (PG), ampicillin (AP), erythromycin (E), azithromycin (ATH), ciprofloxacin (CIP), meropenem (MEM), nitrofurantoin (NI), colistin (CO), and oxytetracycline (OT).
Table 9. Percentage distribution of β-Lactam-resistant LMO and Salmonella isolates across study sites.
Table 9. Percentage distribution of β-Lactam-resistant LMO and Salmonella isolates across study sites.
Retailer(s)Type of MeatPercentage Distribution of β-Lactam-Resistant Salmonella IsolatesPercentage Distribution of β-Lactam-Resistant LMO Isolates
Site ABeefND7.6%
Site BMutton11.1%15%
BeefND7.6%
SausageND7.6%
Site DBeefND15%
SausageND7.6%
MuttonND15%
Site EPorkND7.6%
ND = Not Detected. None of the β-Lactam isolates were detected in sites C and F.
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MDPI and ACS Style

Msolo, L.; Mbiko, Z.; Nokhatyana, S.; Okoh, A.I. Appraisal of Multidrug-Resistant Listeria monocytogenes and Salmonella spp. Recovered from Commercial Meat Samples in the Eastern Cape, South Africa: Implications for Public Health Safety. Antibiotics 2026, 15, 175. https://doi.org/10.3390/antibiotics15020175

AMA Style

Msolo L, Mbiko Z, Nokhatyana S, Okoh AI. Appraisal of Multidrug-Resistant Listeria monocytogenes and Salmonella spp. Recovered from Commercial Meat Samples in the Eastern Cape, South Africa: Implications for Public Health Safety. Antibiotics. 2026; 15(2):175. https://doi.org/10.3390/antibiotics15020175

Chicago/Turabian Style

Msolo, Luyanda, Zanda Mbiko, Sindisiwe Nokhatyana, and Antony Ifeanyi Okoh. 2026. "Appraisal of Multidrug-Resistant Listeria monocytogenes and Salmonella spp. Recovered from Commercial Meat Samples in the Eastern Cape, South Africa: Implications for Public Health Safety" Antibiotics 15, no. 2: 175. https://doi.org/10.3390/antibiotics15020175

APA Style

Msolo, L., Mbiko, Z., Nokhatyana, S., & Okoh, A. I. (2026). Appraisal of Multidrug-Resistant Listeria monocytogenes and Salmonella spp. Recovered from Commercial Meat Samples in the Eastern Cape, South Africa: Implications for Public Health Safety. Antibiotics, 15(2), 175. https://doi.org/10.3390/antibiotics15020175

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