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Frontiers in Microbiology ·

Volume 17 - 2026 | https://doi.org/10.3389/fmicb.2026.1922185

Phenotypic and genotypic characterization of listeria monocytogenes strains isolated from meat industries

  • Despina Vougiouklaki1
  • Markos Dalezios1
  • Konstantina Kyriakou1
  • Marios Papaparaskevas1
  • Marina Siouti1
  • Simen Akkermans2
  • Jan F. M. Impe2
  • Efstathia Tsakali1,2
  • Dimitra Houhoula1*corresponding author
  1. 1Department of Food Science and Technology, Faculty of Food Sciences, University of West Attica, Athens, Greece
  2. 2Department of Chemical Engineering, BioTeC + Chemical and Biochemical Process Technology and Control, KU Leuven, Gent, Belgium
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Abstract

Listeria monocytogenes is a major foodborne pathogen of concern for the food industry due to its ability to persist in processing environments and contaminate ready-to-eat foods. This study aimed to characterize phenotypically and genotypically L. monocytogenes isolates recovered from meat-processing environments in Greece, with emphasis on antimicrobial susceptibility, resistance determinants, plasmid content, and sequence types. Eighteen environmental isolates were analyzed using broth microdilution MIC testing and Oxford Nanopore whole-genome sequencing followed by in silico screening for antimicrobial resistance genes and plasmids. All isolates were susceptible to ampicillin, erythromycin, and trimethoprim–sulfamethoxazole according to EUCAST criteria. For agents categorized by EUCAST as having insufficient evidence (“IE”) for clinical categorization in Listeria (moxifloxacin and linezolid), MICs were reported descriptively. Elevated MICs were observed for clindamycin (≥ 8 mg/L) in three isolates and for tetracycline (≥ 16 mg/L) in two isolates, while all isolates showed high fosfomycin MICs (≥ 128 mg/L) and intermediate fusidic acid MICs (4–8 mg/L). Genomic screening identified two acquired resistance genes, vga (G) and tet (M) , and detected plasmids in a subset of isolates, including plasmid types previously associated with stress tolerance and persistence in food environments. MLST revealed four sequence types (ST87, ST155, ST6, and ST504), including lineages linked to food-processing persistence and clinically relevant clonal complexes. Overall, the findings indicate limited clinically relevant resistance among the examined isolates, while highlighting the contribution of mobile genetic elements and diverse sequence types to environmental fitness and potential public-health risk in meat-processing settings.

Keywords

1 Introduction

In the European Union, human listeriosis is reported less frequently than many other foodborne infections; however, it is associated with high hospitalization and mortality rates, particularly among vulnerable population groups (ECDC, 2022). Consequently, Listeria monocytogenes remains a major concern for the food industry. The pathogen is widely distributed in food-production environments and can contaminate animal-derived products, including poultry, beef, and dairy products (Ramaswamy et al., 2007; Orsi and Wiedmann, 2016; Ferreira et al., 2014). Listeria monocytogenes is frequently recovered from both food-contact and non-food-contact sites in slaughterhouses and meat-processing facilities, including drains, floors, walls, processing equipment, and other difficult-to-clean niches (Sala et al., 2016). These sites may act as environmental reservoirs and contribute to repeated contamination of raw materials, processing lines, and finished products (Sala et al., 2016; Ferreira et al., 2014). The ability of certain strains to adhere to abiotic surfaces and tolerate refrigeration, nutrient limitation, and sanitation-related stresses may facilitate their long-term survival in food-processing environments (Ferreira et al., 2014; Fagerlund et al., 2022b). Therefore, environmental monitoring of both food-contact and non-food-contact surfaces is important for the early detection and control of persistent contamination.

L. monocytogenes can grow under a broad range of environmental conditions, including temperatures from −0.4°C to 45°C, pH values from 4.4 to 9.4, salinity up to 10% NaCl, and water activity as low as 0.90. These physiological characteristics enable survival during refrigeration, salting, and mild acidification and increase the risk of contamination of ready-to-eat foods and food-processing environments (Chan and Wiedmann, 2008; Orsi and Wiedmann, 2016). In addition, its capacity to form biofilms on food-contact surfaces enhances environmental persistence and resistance to sanitation procedures (Finn et al., 2023).

Despite its relatively low incidence in the European Union, listeriosis is associated with severe clinical outcomes, particularly among immunocompromised individuals, pregnant women, neonates, and older adults (ECDC, 2022). This disease burden necessitates continuous surveillance and effective control measures throughout the food-production chain.

Published phenotypic and genomic information on Listeria monocytogenes from Greek food-processing environments remains limited, particularly for the meat-processing sector. Previous studies conducted in Greece have mainly examined isolates from other food matrices, including seafood and seafood-market environments, and have reported variable antimicrobial-resistance profiles (Peratikos et al., 2024). In contrast, European surveillance studies have demonstrated that persistent L. monocytogenes populations in food-production facilities may carry specific stress-survival determinants, mobile genetic elements, and sequence types that facilitate long-term establishment (Fagerlund et al., 2022b; Unrath et al., 2021).

Antimicrobial resistance in Listeria has increasingly been reported worldwide in both clinical and food-associated isolates, although marked geographic variability exists, reflecting differences in antimicrobial use, environmental conditions, and processing practices (Capita and Alonso-Calleja, 2013; Panera-Martínez et al., 2022; Cufaoglu et al., 2021). Resistance development in Listeria is mainly associated with acquisition of mobile genetic elements such as plasmids, transposons, and integrative conjugative elements carrying resistance determinants and efflux pumps. Horizontal gene transfer between Enterococcus, Staphylococcus, Streptococcus, and Listeria species has been documented, facilitating dissemination of resistance genes in food-associated microbial communities (Urban-Chmiel et al., 2022). These elements may also be organized within integrons that enable capture, rearrangement, and expression of resistance genes from diverse sources (Hasan and Al-Harmoosh, 2020).

The present study aimed to characterize phenotypically and genotypically L. monocytogenes isolates recovered from meat-processing environments in Greece. Specifically, the study evaluated antimicrobial susceptibility profiles, acquired resistance genes, plasmid content, and sequence-type distribution using MIC testing, whole-genome sequencing, and multilocus sequence typing.

2 Materials and methods

2.1 Bacterial isolates and sampling

Listeria spp. isolates included in this study were retrieved from the culture collection of the Laboratory of Food and Beverage Quality Control and Hygiene, Agricultural University of Athens. Isolates originated from two meat-processing plants (Industry A and Industry B) and were collected during 2024–2025.

More than 100 environmental samples were obtained from multiple sites within the two facilities, including food-contact and non-food-contact surfaces (e.g., processing equipment, walls, floors, and drains). Eighteen Listeria monocytogenes isolates were selected for further analysis. Isolates were preserved in tryptone soy broth (TSB) supplemented with 20% (v/v) glycerol and stored at −20°C until use.

2.2 Phenotypic characterization

Isolates were recovered from frozen stocks by sub culturing on Agar Listeria according to Ottaviani and Agosti (ALOA) plates (Bioprepare, Keratea, Greece). ALOA is a selective and differential medium for isolation and presumptive identification of Listeria spp., enabling differentiation of L. monocytogenes based on phospholipase C activity (Jantzen et al., 2006). Plates were incubated at 37 ± 1°C for 24 h. Colonies with typical blue-green coloration and an opaque halo were selected for further testing.

Species identification was confirmed by MALDI-TOF MS using the Vitek MS Prime system (bioMérieux, Marcy l'Etoile, France), according to the manufacturer's instructions. Escherichia coli ATCC 8,739 was used as the quality-control strain for MALDI-TOF procedures.

2.3 Antibiotic susceptibility testing

Minimum inhibitory concentrations (MICs) were determined using in-house prepared 96-well broth microdilution plates. The following antimicrobials were tested: ampicillin, gentamicin, ciprofloxacin, moxifloxacin, erythromycin, clindamycin, linezolid, vancomycin, teicoplanin, tetracycline, tigecycline, fosfomycin, fusidic acid, rifampicin, and co-trimoxazole (trimethoprim–sulfamethoxazole).

Microdilution plates were prepared and tested according to EUCAST recommendations using Mueller–Hinton Fastidious Broth (Liofilchem, Italy). MIC determination was performed by visual inspection after incubation and was defined as the lowest antimicrobial concentration showing no visible bacterial growth. All isolates were tested in duplicate.

MIC interpretation followed EUCAST clinical breakpoints and guidance for Listeria monocytogenes (EUCAST v16.0; accessed from the EUCAST breakpoint tables). For agents categorized by EUCAST as “IE” (insufficient evidence), MICs were reported descriptively without classification as susceptible or resistant. Streptococcus pneumoniae ATCC 49,619 was used for quality control.

2.4 Genotypic characterization of listeria monocytogenes isolates

2.4.1 Serogrouping of isolates

The isolates were previously identified and classified as Listeria monocytogenes or non-identified Listeria spp. by the Laboratory of Food and Beverage Quality Control and Hygiene, Agricultural University of Athens. Serogrouping of the 18 confirmed L. monocytogenes isolates was performed according to the method described by Lachtara et al. (2021). The primer sequences used in the PCR were specific for L. monocytogenes serogroup determination: prs and lmo0737 for IIa; prs and ORF2819 for IIb; prs, lmo1118 and lmo0737 for IIc; and prs, ORF2110 and ORF2819 for IVb (Doumith et al., 2004).

2.4.2 DNA extraction and quantification

Actively growing cells were obtained by subculturing isolates on ALOA plates under aseptic conditions. Genomic DNA was extracted using the QIAamp® Fast DNA Stool Mini Kit (QIAGEN), following the manufacturer's instructions with minor modifications to optimize bacterial lysis. DNA concentration and quality were assessed fluorometrically using the Quantus™ Fluorometer (Promega) and QuantiFluor® ONE dsDNA dye. DNA extracts with concentrations >15 ng/μL were stored at −20°C until sequencing.

2.4.3 Whole-genome sequencing and genomic analysis

Whole-genome sequencing was performed using the Ligation Sequencing g DNA—Native Barcoding Kit 96 V14 (SQK-NBD114.96; Oxford Nanopore Technologies, Oxford, UK), according to the manufacturer's protocol. Sequencing runs were performed on new MinION flow cells (R10.4.1) using a MinION Mk1C device with MinKNOW software (v21.11.7). Basecalling was conducted using Guppy (v5.1.13) in high-accuracy mode, generating FASTQ files.

High-quality reads were uploaded to the cloud-based BUGSEQ platform for automated analysis, including taxonomic assignment at species/strain level and detection of antibiotic resistance genes (ARGs), plasmids, virulence-associated genes, and mutations linked to antimicrobial resistance. Outputs were subsequently curated and summarized using standard bioinformatics and statistical tools.

3 Results

3.1 Characterization of isolates and sampling sites

From more than 100 environmental samples collected from meat and meat-product processing facilities, 18 isolates were selected and previously confirmed as Listeria monocytogenes. These isolates were subsequently assigned to their corresponding serogroups. Serogroup distribution profiles are presented in Table 1.

Table 1. Final serogroups profiles (N = 18).

IsolateSerogroupN%
LM11/2b527.8
LM21/2a527.8
LM31/2a527.8
LM41/2a527.8
LM51/2c527.8
LM61/2b527.8
LM74b316.7
LM81/2b527.8
LM94b316.7
LM101/2a527.8
LM111/2c527.8
LM121/2c527.8
LM131/2c527.8
LM144b316.7
LM151/2c527.8
LM161/2b527.8
LM171/2b527.8
LM181/2a527.8

All isolates originated from food-contact and non-food-contact surfaces within meat-processing environments. Sampling sites included the meat scraping shelf (5.6%), transport carts (16.7%), wall skirting surfaces (5.6%), Teflon-coated meat-cutting surfaces (5.6%), drains (38.9%), tumbling barrel surfaces (27.8%), and meat-cutting benches (5.6%).

Serogroups 1/2a, 1/2c, and 1/2b were equally represented (n = 5; 27.8% each), whereas serogroup 4b was less frequently detected (n = 3; 16.7%).

3.2 Antibiotic susceptibility testing

MIC values for the 18 L. monocytogenes isolates are presented in Table 2. All isolates were susceptible to ampicillin, erythromycin, and co-trimoxazole according to EUCAST criteria. For moxifloxacin and linezolid, EUCAST currently classifies evidence as insufficient (“IE”) for clinical categorization in Listeria; therefore, MICs were reported descriptively. In general, moxifloxacin MICs were low (0.5–1 mg/L), whereas linezolid MICs clustered at 2–4 mg/L.

Table 2. MIC results of the 18 isolates.

NoSerogroupAmp*Mfx*Lzd*Ery*Sxt*GenCipCliVaTecTetTgcFosFaRa
LM11/2b≤ 114≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM21/2a≤ 114≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM31/2a≤ 114≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM41/2a≤ 114≤ 0.25≤ 0.06≤ 0.51≤ 0.25≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM51/2c≤ 114≤ 0.25≤ 0.06≤ 0.51≥8≤ 0.5≤ 0.5≥16≤ 0.12≥1288≤ 0.5
LM61/2b≤ 10.54≤ 0.25≤ 0.06≤ 0.5≤ 0.52≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM74b≤ 112≤ 0.25≤ 0.06≤ 0.51≤ 0.25≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM81/2b≤ 114≤ 0.25≤ 0.06≤ 0.51≤ 0.25≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM94b≤ 112≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM101/2a≤ 114≤ 0.25≤ 0.06≤ 0.51≥8≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM111/2c≤ 114≤ 0.25≤ 0.06≤ 0.51≤ 0.25≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM121/2c≤ 114≤ 0.25≤ 0.06≤ 0.51≥8≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM131/2c≤ 114≤ 0.25≤ 0.06≤ 0.51≤ 0.25≤ 0.5≤ 0.5≥16≤ 0.12≥1284≤ 0.5
LM144b≤ 114≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5
LM151/2c≤ 114≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM161/2b≤ 114≤ 0.25≤ 0.06≤ 0.511≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM171/2b≤ 114≤ 0.25≤ 0.06≤ 0.512≤ 0.5≤ 0.5≤ 1≤ 0.12≥1288≤ 0.5
LM181/2a≤ 10.54≤ 0.25≤ 0.06≤ 0.5≤ 0.5≤ 0.25≤ 0.5≤ 0.5≤ 1≤ 0.12≥1284≤ 0.5

Amp, ampicillin; Mfx, moxifloxacin; Lzd, linezolid; Ery, erythromycin; Sxt, co-trimoxazole; Gen, gentamicin; Cip, ciprofloxacin; Cli, clindamycin; Va, vancomycin; Tec, teicoplanin; Tet, tetracycline; Tgc, tigecycline; Fos, fosfomycin; Fa, fucidic acid; Ra, rifampicin. *EUCAST included agents. EUCAST V16.0 (2026) guidelines and susceptibility criteria: Amp S ≤ 1 R >1, Mfx IE, Lzd IE, Ery S ≤ 1 R >1 and Sxt S ≤ 0.06 R >0.06 (IE: insufficient evidence that the antibiotic can be used for Listeria infections). For the rest of the antibiotics there are no guidelines and susceptibility criteria.

For antimicrobials without EUCAST breakpoints for Listeria, most isolates exhibited low MICs for gentamicin, ciprofloxacin, vancomycin, teicoplanin, tigecycline, and rifampicin. Elevated clindamycin MICs (≥8 mg/L) were observed in isolates LM5 (serogroup 1/2c), LM10 (1/2a), and LM12 (1/2c). Elevated tetracycline MICs (≥16 mg/L) were observed in isolates LM5 (1/2c) and LM13 (1/2c). All isolates exhibited high fosfomycin MICs (≥128 mg/L) and intermediate fusidic acid MICs (4–8 mg/L).

Regarding other guidelines, CLSI provides Listeria breakpoints in the M45 document, where, regarding the antibiotics tested here, CLSI uses the Ampicillin 2 mg/L breakpoint and the Co-trimoxazole 0.5 mg/L breakpoint, and in that respect all our isolates were also classified as susceptible.

3.3 Antimicrobial resistance genes and genotypic prediction of antimicrobial resistance

Genomic screening using BUGSEQ did not detect resistance predictors for ampicillin, penicillin, meropenem, or trimethoprim–sulfamethoxazole in any of the 18 L. monocytogenes isolates. Two acquired antimicrobial resistance genes were detected across the dataset: vga(G) and tet(M).

3.4 Multilocus sequence typing (MLST)

Isolates classified as Listeria monocytogenes in the Top Taxa analysis and exhibiting >95% relative abundance were subjected to multilocus sequence typing (MLST) to determine their sequence types (STs). In heterogeneous samples where the full set of housekeeping loci could not be recovered, ST assignment was not performed. For such cases, the BIGSdb-Pasteur database was used to identify the closest matching sequence types based on the available allelic profiles. The detected sequence types (STs) included ST155, ST504, ST87, and ST6. Overall, among the typed isolates (n = 9), ST87 and ST155 were the most prevalent (each 33.3%), followed by ST6 (22.2%) and ST504 (11.1%) (Table 3).

Table 3. Distribution of isolates across the identified sequence types (STs) based on MLST analysis.

Sequence type (ST)Isolates (IDs)n% (of typed isolates, n = 9)
ST87LM8, LM14, LM18333.3
ST155LM2, LM3, LM10333.3
ST6LM7, LM9222.2
ST504LM4111.1
Total9100.0

3.5 Identification and characterization of plasmids

Genomic analysis identified plasmids in four isolates (LM10, LM12, LM14, and LM16). The LM10 isolate contained one plasmid assigned to the AG939 cluster. The LM12 isolate harbored two plasmids, assigned to the AC309 and AG939 clusters. The LM14 isolate harbored two plasmid subtypes: AG939-subAQ995 and AC310-subAL449. The LM16 isolate carried plasmid subtype AL445, belonging to the AC309 cluster. No antimicrobial resistance markers were detected.

4 Discussion

The present study investigated the phenotypic and genotypic characteristics of Listeria monocytogenes isolates originating from meat-processing environments in Greece, focusing on antimicrobial susceptibility, resistance determinants, plasmid content, and sequence types. Overall, the isolates exhibited low levels of clinically relevant antimicrobial resistance, consistent with previous reports indicating that food-associated L. monocytogenes generally remains susceptible to first-line anti-listerial agents (Wagner et al., 2020; Sousa et al., 2024).

All isolates were susceptible to ampicillin, erythromycin, and trimethoprim–sulfamethoxazole according to EUCAST criteria, confirming the continued effectiveness of recommended therapeutic options for listeriosis. No multidrug-resistant (MDR) phenotypes were detected. Similar susceptibility patterns have been reported in European food and environmental isolates, in contrast to studies from other regions where increased resistance and MDR have been described (Peratikos et al., 2024; Silva et al., 2024; Sołtysiuk et al., 2025). The comparatively low resistance observed here suggests limited antimicrobial selective pressure in the examined meat-processing environments or effective sanitation practices restricting dissemination of resistant clones.

Elevated MIC values for clindamycin and tetracycline were observed in four isolates (LM5, LM10, LM12, and LM13). Acquired resistance genes vga (G) and tet (M) were also detected in the dataset; however, direct isolate-level association between phenotypic resistance and specific resistance determinants could not be conclusively established. The vga (G) determinant encodes an ABC-F ribosomal protection protein mediating reduced susceptibility to lincosamides, streptogramin A, and pleuromutilins (Bechtel and Gibbons, 2021; Gana et al., 2024), whereas tet (M) is one of the most widely distributed tetracycline resistance genes associated with mobile genetic elements and horizontal transfer in food-associated bacteria (Haubert et al., 2016; Ji et al., 2023; Anupama et al., 2025). Their occurrence in a subset of isolates supports sporadic acquisition events within processing environments. Nevertheless, the limited distribution of these genes and absence of MDR profiles indicate that acquired resistance remains uncommon in the studied facilities.

All isolates displayed high MICs to fosfomycin and intermediate MICs to fusidic acid and linezolid. Interpretation of these findings should be cautious, as EUCAST breakpoints for Listeria are not established for these agents. High fosfomycin MICs are frequently reported in L. monocytogenes and are considered intrinsic or of limited clinical relevance, reflecting permeability and metabolic characteristics rather than acquired resistance (Rodríguez-Melcón et al., 2021). Similarly, intermediate linezolid and fusidic-acid MICs in the absence of known resistance determinants likely represent natural variability rather than clinically meaningful resistance. This highlights the importance of integrating phenotypic and genomic data and avoiding overinterpretation of MIC values for antibiotic–species combinations lacking validated breakpoints.

Genomic analysis identified plasmids belonging to the AC309, AC310, and AG939 clusters in four isolates. Related plasmids have previously been described in food-associated Listeria monocytogenes and have been linked mainly to stress adaptation and environmental persistence. AC309-related plasmids have been reported to carry genes associated with tolerance to disinfectants and heavy metals (Voronina et al., 2023), while pLM58-related plasmids carrying the heat-shock gene clpL have been shown to enhance survival under heat stress (Pöntinen et al., 2017). AC310-subAL449-like plasmids have also been associated with improved survival under high-salinity and acidic conditions (Hingston et al., 2019; Parra-Flores et al., 2022). In addition, AG939-related plasmids have been linked in previous studies to persistence-associated traits and have been reported to carry resistance determinants such as tet (M) and vga (G) (Hingston et al., 2019). However, these functional associations were not experimentally evaluated in the present study, and the detection of related plasmid clusters should not be interpreted as direct evidence of enhanced persistence or antimicrobial resistance in the examined isolates. MLST analysis identified ST87, ST155, ST6, and ST504, sequence types that have previously been reported in food-processing environments, food products, and clinical cases. ST155 has frequently been detected among food-associated and processing-environment isolates and has been linked in previous studies to prolonged environmental circulation, although strains within this sequence type may show heterogeneous virulence characteristics (Wagner et al., 2020). ST504 has been reported less frequently but has been recovered from meat-associated environments and invasive human infections, suggesting that its occurrence is not restricted to a single ecological niche (Sousa et al., 2024). ST6 belongs to a clinically important lineage repeatedly implicated in severe listeriosis cases and foodborne outbreaks, including outbreaks associated with ready-to-eat products (Slavinska et al., 2025). ST87 has also been reported in food and clinical settings and has been associated with serious human infections in previous epidemiological investigations (Cabal et al., 2019). However, MLST identifies broad genetic lineages and does not by itself establish persistence, virulence potential, or epidemiological relatedness at the isolate level (Cooper and Feil, 2004; Cortes et al., 2020). Therefore, cgMLST or SNP-based analysis, together with isolate-specific characterization of virulence and stress-survival determinants, would be required to define the precise public-health significance of the isolates examined here.

Compared with previous international studies reporting high resistance rates and MDR among food and environmental Listeria, the present isolates exhibited markedly lower resistance frequencies. For example, high clindamycin resistance has been reported in Greek seafood isolates (Peratikos et al., 2024), whereas MDR rates exceeding 80% have been described in other regions (Silva et al., 2024; Sołtysiuk et al., 2025). Differences in antimicrobial usage, sanitation practices, and methodological approaches—particularly non-standardized disk diffusion criteria—likely contribute to this variability. The use of EUCAST MIC-based interpretation in the present study provides more conservative and clinically relevant resistance assessment.

Importantly, the absence of genotypic predictors for clinically relevant antibiotics despite occasional elevated MICs indicates that phenotypic variation may arise from mechanisms not captured by current databases, such as regulatory changes or point mutations. This emphasizes the need for combined phenotypic and genomic surveillance to accurately evaluate antimicrobial resistance in Listeria populations.

A major limitation of the present study is the relatively small number of Listeria monocytogenes isolates analyzed and their origin from only two meat-processing facilities. Therefore, the observed antimicrobial susceptibility profiles, resistance determinants, plasmid distribution, and sequence types should not be considered representative of the broader epidemiology of L. monocytogenes in Greek meat-processing environments. Rather, the findings should be interpreted as preliminary, facility-specific surveillance data. Future studies should include larger isolate collections from multiple facilities and geographical regions and should incorporate longitudinal sampling to better assess the distribution, persistence, and epidemiological significance of specific clones.

The added value of the present study lies in the combined phenotypic and genomic characterization of Listeria monocytogenes isolates from an underrepresented food-production sector in Greece. Epidemiological data regarding Listeria monocytogenes and other Listeria species in fresh-meat processing environments in Greece are currently unavailable but unlike previous Greek reports focusing mainly on other food matrices, this dataset integrates MIC testing with resistance-gene screening, plasmid characterization, serogrouping, and MLST. The detection of both persistence-associated and clinically relevant sequence types, together with plasmid clusters linked in previous studies to environmental stress tolerance, provides a preliminary genomic baseline for Greek meat-processing facilities. Future studies should include the characterization of non-monocytogenes Listeria species, as well as the investigation of antimicrobial resistance, virulence, persistence, and biofilm-associated determinants, to obtain a more comprehensive understanding of the epidemiological situation in Greece. However, these observations should be interpreted as facility-specific findings rather than as representative of the national epidemiology of L. monocytogenes.

5 Conclusion

The 18 Listeria monocytogenes isolates recovered from two Greek meat-processing facilities showed limited clinically relevant antimicrobial resistance and remained susceptible to ampicillin, erythromycin, and trimethoprim–sulfamethoxazole according to EUCAST criteria. Elevated clindamycin and tetracycline MICs were detected in a small number of isolates, while the acquired resistance genes vga (G) and tet (M) were identified in the dataset. Plasmids associated mainly with stress tolerance and environmental persistence were detected in a subset of isolates. MLST identified ST87, ST155, ST6, and ST504, demonstrating the presence of both persistence-associated and clinically relevant lineages. These findings provide preliminary phenotypic and genomic data on L. monocytogenes from Greek meat-processing facilities and support the use of combined antimicrobial susceptibility testing and genomic surveillance for monitoring contamination and persistent strains. However, due to the limited number of isolates and facilities examined, the findings should be interpreted as facility-specific and not as representative of the national epidemiology of L. monocytogenes.

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Footnotes

Edited by: Adriana Morar, Banat University of Agricultural Sciences and Veterinary Medicine, Romania

Reviewed by: Maxsueli Machado, Federal University of Mato Grosso, Brazil

Kálmán Imre, University of Life Sciences “King Mihai I” from Timişoara, Romania

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This work was supported by the European Union within the framework of the Erasmus+ FOOD4S Programme (Erasmus Mundus Joint Master Degree in Food Systems Engineering, Technology and Business 619864-EPP-1-2020-1-BE-EPPKA1-JMD-MOB) and the Erasmus+ FIND4S Programme (Enhancing Higher Education Capacity for Sustainable Data Driven Food Systems in INDonesia Project 101179822 — FIND4S – ERASMUS-EDU-2024-CBHE). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.

Data availability

The original contributions presented in the study are available: https://doi.org/10.5281/zenodo.23035497.

Author contributions

DV: Conceptualization, Methodology, Writing – original draft, Formal analysis, Writing – review & editing, Investigation. MD: Writing – original draft, Investigation, Formal analysis. KK: Investigation, Formal analysis, Writing – original draft. MP: Formal analysis, Writing – original draft, Investigation. MS: Investigation, Writing – original draft, Formal analysis. SA: Formal analysis, Validation, Data curation, Writing – review & editing. JI: Resources, Funding acquisition, Supervision, Writing – review & editing. ET: Project administration, Writing – review & editing, Investigation, Writing – original draft. DH: Conceptualization, Validation, Methodology, Supervision, Writing – review & editing, Writing – original draft, Formal analysis.

References

  1. Anupama A., Pattapulavar V., Christopher J. G. (2025). The past, present, future of Listeria monocytogenes: understanding the molecular pathways, antibiotic resistance and public health implications. Med. Microecol. 25: 100127. doi: doi:10.1016/j.medmic.2025.100127
  2. Bechtel T. D., Gibbons J. G. (2021). Population genomic analysis of Listeria monocytogenes from food reveals substrate-specific genome variation. Front. Microbiol. 12: 620033. doi: doi:10.3389/fmicb.2021.620033
  3. Cabal A., Pietzka A., Huhulescu S., Allerberger F., Ruppitsch W., Schmid D. (2019). Isolate-based surveillance of Listeria monocytogenes by whole genome sequencing in Austria. Front. Microbiol. 10: 2282. doi: doi:10.3389/fmicb.2019.02282
  4. Capita R., Alonso-Calleja C. (2013). Antibiotic-resistant bacteria: a challenge for the food industry. Crit. Rev. Food Sci. Nutr. 53, 11 – 48. doi: doi:10.1080/10408398.2010.519837
  5. Chan Y. C., Wiedmann M. (2008). Physiology and genetics of Listeria monocytogenes survival and growth at low temperature. Crit. Rev. Food Sci. Nutr. 49, 237 – 253. doi: doi:10.1080/10408390701856272
  6. Cooper J. E., Feil E. J. (2004). Multilocus sequence typing – what is resolved? Trends Microbiol. 12, 373 – 377. doi: doi:10.1016/j.tim.2004.06.003
  7. Cortes B. W., Naditz A. L., Anast J. M., Schmitz-Esser S. (2020). Transcriptome sequencing of Listeria monocytogenes reveals major gene expression changes in response to lactic acid stress exposure but a less pronounced response to oxidative stress. Front. Microbiol. 10: 3110. doi: doi:10.3389/fmicb.2019.03110
  8. Cufaoglu G., Ambarcioglu P., Ayaz N. D. (2021). Meta-analysis of the prevalence of Listeria spp. and antibiotic resistant L. monocytogenes isolates from foods in Turkey. LWT 144: 111210. doi: doi:10.1016/j.lwt.2021.111210
  9. Doumith M., Buchrieser C., Glaser P., Jacquet C., Martin P. (2004). Differentiation of the major Listeria monocytogenes serovars by multiplex PCR. J. Clin. Microbiol. 42, 3819 – 3822. doi: doi:10.1128/JCM.42.8.3819-3822.2004
  10. ECDC (2022). Listeriosis: Annual Epidemiological Report for 2022. Stockholm: European Centre for Disease Prevention and Control.
  11. Fagerlund A., Wagner E., Møretrø T., Heir E., Moen B., Rychli K.. (2022b). Pervasive Listeria monocytogenes is common in the Norwegian food system and is associated with increased prevalence of stress survival and resistance determinants. Appl. Environ. Microbiol. 88: e0086122. doi: doi:10.1128/aem.00861-22
  12. Ferreira V., Wiedmann M., Teixeira P., Stasiewicz M. J. (2014). Listeria monocytogenes persistence in food-associated environments: epidemiology, strain characteristics, and implications for public health. J. Food Protec. 77, 150 – 170. doi: doi:10.4315/0362-028X.JFP-13-150
  13. Finn L., Onyeaka H., O'Neill S. (2023). Listeria monocytogenes biofilms in food-associated environments: a persistent enigma. Foods 12: 3339. doi: doi:10.3390/foods12183339
  14. Gana J., Gcebe N., Pierneef R. E., Chen Y., Moerane R., Adesiyun A. A. (2024). Whole genome sequence analysis of Listeria monocytogenes isolates obtained from the beef production chain in Gauteng Province, South Africa. Microorganisms 12: 1003. doi: doi:10.3390/microorganisms12051003
  15. Hasan R., Al-Harmoosh R. (2020). Mechanisms of antibiotic resistance in foodborne pathogens. Antibiotics 9: 326. doi: doi:10.3390/antibiotics9060326
  16. Haubert L., Mendonça M., Lopes G. V., Cardoso M. R. I., da Silva W. P. (2016). Listeria monocytogenes isolates from food and food environment harbouring tetM and ermB resistance genes. Lett. Appl. Microbiol. 62, 23 – 29. doi: doi:10.1111/lam.12516
  17. Hingston P., Brenner T., Hansen L. T., Wang S. (2019). Comparative analysis of Listeria monocytogenes plasmids and expression levels of plasmid-encoded genes during growth under salt and acid stress conditions. Toxins 11: 426. doi: doi:10.3390/toxins11070426
  18. Jantzen M. M., Navas J., de Paz M., Rodriguez B., da Silva W. P., Nunez M.. (2006). Evaluation of ALOA plating medium for its suitability to recover high pressure-injured Listeria monocytogenes from ground chicken meat. Lett. Appl. Microbiol. 43, 313 – 317. doi: doi:10.1111/j.1472-765X.2006.01950.x
  19. Ji S., Song Z., Luo L., Wang Y., Li L., Mao P.. (2023). Whole-genome sequencing reveals genomic characterization of Listeria monocytogenes from food in China. Front. Microbiol. 13: 1049843. doi: doi:10.3389/fmicb.2022.1049843
  20. Lachtara B., Osek J., Wieczorek K. (2021). Molecular typing of Listeria monocytogenes IVb serogroup isolated from food and food production environments in Poland. Pathogens 10, 482. doi: doi:10.3390/pathogens10040482
  21. Orsi R. H., Wiedmann M. (2016). Characteristics and distribution of Listeria spp., including Listeria species newly described since 2009. Appl. Microbiol. Biotechnol. 100, 5273 – 5287. doi: doi:10.1007/s00253-016-7552-2
  22. Panera-Martínez S., Rodríguez-Melcón C., Serrano-Galán V., Alonso-Calleja C., Capita R. (2022). Prevalence, quantification and antibiotic resistance of Listeria monocytogenes in poultry preparations. Food Control 135: 108608. doi: doi:10.1016/j.foodcont.2021.108608
  23. Parra-Flores J., Holý O., Bustamante F., Lepuschitz S., Pietzka A., Contreras-Fernández A.. (2022). Virulence and antibiotic resistance genes in Listeria monocytogenes strains isolated from ready-to-eat foods in Chile. Front. Microbiol. 12: 796040. doi: doi:10.3389/fmicb.2021.796040
  24. Peratikos P., Tsitsos A., Damianos A., Kyritsi M. A., Hadjichristodoulou C., Soultos N.. (2024). Listeria monocytogenes from marine fish and the seafood market environment in Northern Greece: prevalence, molecular characterization and antibiotic resistance. Appl. Sci. 14: 2725. doi: doi:10.3390/app14072725
  25. Pöntinen A., Aalto-Araneda M., Lindström M., Korkeala H. (2017). Heat resistance mediated by PLM58 plasmid-borne ClpL in Listeria monocytogenes. mSphere 2, e00364 – e00317. doi: doi:10.1128/mSphere.00364-17
  26. Ramaswamy V., Cresence V. M., Rejitha J. S., Lekshmi M. U., Dharsana K. S., Prasad S. P.. (2007). Listeria —review of epidemiology and pathogenesis. J. Microbiol. Immunol. Infect. 40, 4 – 13.
  27. Rodríguez-Melcón C., Alonso-Calleja C., García-Fernández C., Carballo J., Capita R. (2021). Minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) for twelve antimicrobials (biocides and antibiotics) in eight strains of Listeria monocytogenes. Biology 11: 46. doi: doi:10.3390/biology11010046
  28. Sala C., Morar A., Tîrziu E., Nichita I., Imre M., Imre K. (2016). Environmental occurrence and antibiotic susceptibility profile of Listeria monocytogenes at a slaughterhouse raw processing plant in Romania. J. Food Prot. 79, 1794 – 1797. doi: doi:10.4315/0362-028X.JFP-16-052
  29. Silva A., Silva V., Gomes J. P., Coelho A., Batista R., Saraiva C.. (2024). Listeria monocytogenes from food products and food associated environments: antimicrobial resistance, genetic clustering and biofilm insights. Antibiotics 13: 447. doi: doi:10.3390/antibiotics13050447
  30. Slavinska A., Jauneikaite E., Meškyte U., Kirkliauskiene A., Misevič A., Petrutiene A.. (2025). Genomic characterization of Listeria monocytogenes isolated from normally sterile human body fluids in Lithuania from 2016 to 2021. Microb Genom 11: 001410. doi: doi:10.1099/mgen.0.001410
  31. Sołtysiuk M., Przyborowska P., Wiszniewska-Łaszczych A., Tobolski D. (2025). Prevalence and antimicrobial resistance profile of Listeria spp. isolated from raw fish. BMC Vet. Res. 21: 4792. doi: doi:10.1186/s12917-025-04792-y
  32. Sousa M., Magalhães R., Ferreira V., Teixeira P. (2024). Current methodologies available to evaluate the virulence potential among Listeria monocytogenes clonal complexes. Front. Microbiol. 15: 1425437. doi: doi:10.3389/fmicb.2024.1425437
  33. Unrath N., McCabe E., Macori G., Fanning S. (2021). Application of whole genome sequencing to aid in deciphering the persistence potential of s in food production environments. Microorganisms 9: 1856. doi: doi:10.3390/microorganisms9091856
  34. Urban-Chmiel R., Marek A., Stepień-Pyśniak D., Wieczorek K., Dec M., Nowaczek A.. (2022). Antibiotic resistance in bacteria—a review. Antibiotics 11: 1079. doi: doi:10.3390/antibiotics11081079
  35. Voronina O. L., Ryzhova N. N., Aksenova E. I., Kunda M. S., Kutuzova A. V., Karpova T. I.. (2023). Genetic diversity of Listeria detected in the production environment of meat processing. Mol. Genet. Microbiol. Virol. 38, 21 – 28. doi: doi:10.3103/S0891416823010111
  36. Wagner E., Zaiser A., Leitner R., Quijada N. M., Pracser N., Pietzka A.. (2020). Virulence characterization and comparative genomics of Listeria monocytogenes sequence type 155 strains. BMC Genomics 21: 847. doi: doi:10.1186/s12864-020-07263-w

Citation

Vougiouklaki, D., et al. (2026). Phenotypic and genotypic characterization of listeria monocytogenes strains isolated from meat industries. Frontiers in Microbiology, Volume 17. https://doi.org/
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17 - 2026

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Copyright © 2026 Vougiouklaki, Dalezios, Kyriakou, Papaparaskevas, Siouti, Akkermans, Impe, Tsakali and Houhoula.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Dimitra Houhoula

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