1. Introduction
Dairy products are an essential source of high-quality protein, calcium, phosphorus and vitamins, making them a cornerstone of the Mexican diet. According to the Dairy and Products Annual (USDA-FAS), approximately 52% of raw milk produced in Mexico is used to make derivatives such as cheese, with 2023 production estimated at 465,000 t and continuing to rise due to strong domestic demand [1]. The predominance of fresh and artisanal cheeses—many made from unpasteurized milk—increases the risk of microbial contamination and, consequently, foodborne illness (FBI).
Globally, the World Health Organization (WHO) estimates that each year about 600 million people (nearly one in ten) fall ill and 420,000 die from consuming unsafe food, with a disproportionate burden in children under five years of age [2]. In Mexico, bacterial FBIs remain a public health priority: the National Epidemiological Surveillance System (SINAVE) reported over 25,600 cases of bacterial food poisoning (ICD-10 code A05) by the end of epidemiological week 52 of 2023, including 444 new cases in that week alone [3]. Dairy products—especially fresh cheeses—are recurring vehicles for pathogens; a recent study of 111 samples of Cotija and Bola de Ocosingo cheeses (Chiapas, Mexico) detected Salmonella spp. DNA in 10.5% and Staphylococcus aureus in 13.7% of samples [4].
In artisanal cheeses, Gram-negative pathogens (e.g., Escherichia coli, Citrobacter spp.) are of particular concern because they combine the tolerance typical of biofilms with an expanding repertoire of antimicrobial-resistance genes [5]. It is estimated that up to 80% of bacteria can adopt a biofilm lifestyle, which protects them from disinfectants, environmental stress and antibiotics [6]. Within the extracellular matrix, horizontal gene transfer and the emergence of persister cells contribute to antimicrobial resistance (AMR), a phenomenon that increases healthcare costs and complicates infection treatment [7].
At the molecular level, the rpoS gene—encoding sigma factor S—regulates the transition to stationary phase and stress response in E. coli and other Gram-negative bacilli. Its overexpression is associated with enhanced matrix production and more robust biofilms, whereas rpoS mutants show drastically reduced adherence to stainless steel, polypropylene and silicone surfaces [8].
Comparative genomic surveys show that an intact rpoS locus is present in more than 95% of clinical and food-related isolates of Salmonella enterica, Vibrio cholerae, Shigella spp. and Cronobacter sakazakii, underscoring its evolutionary conservation among enteric pathogens. Functional studies demonstrate that in S. enterica serovar typhimurium a rpoS knockout produces ≈ 84% less crystal-violet biomass and suffers a 2-log reduction in survival on stainless steel after desiccation [9]. In enterohaemorrhagic E. coli O157:H7, over-expression of rpoS doubles acid tolerance and promotes cell aggregation, facilitating colonisation of fresh-produce and cheese matrices [10]. Likewise, in Pseudomonas fluorescens—a species frequently recovered from dairy plants—rpoS orchestrates extracellular-polysaccharide synthesis and surface attachment through the c-di-GMP network [11]. Collectively, these findings position rpoS as a master regulator that links stress adaptation, antimicrobial tolerance and robust biofilm formation in foodborne bacteria. However, the presence of rpoS and its relationship to biofilm formation in Gram-negative bacteria isolated from Mexican artisanal cheeses has not been extensively documented.
Therefore, the objective of this study was to evaluate the biofilm-forming capacity of Gram-negative bacterial isolates recovered from artisanal cheese distribution centers in Tijuana (Baja California, Mexico) and to determine the presence of the rpoS gene, providing evidence to support more effective control strategies along the dairy chain.
2. Materials and Methods
2.1. Sampling Sites and Study Design
Between January and March 2024, a cross-sectional study was conducted at four artisanal cheese distribution centers in Tijuana, Baja California, Mexico. From each site, three sample types were collected: fresh cheese (Q), food-contact surfaces (S), and ambient air (A). Samples totaled 12 (4 Q + 3 S + 5 A), and all assays were performed in duplicate (Table 1).
Table 1. Sampling sites and main characteristics.
Site code |
Sampling sites |
Environment description |
Sample types (n) |
Coordinates (WGS-84) |
Altitude (m) |
M1 |
Commercial/residential area with local traffic |
Q 1, S 1, A 2 |
32˚31'45.19"N, 116˚58'32.91"W |
151 |
M2 |
Residential area |
Q 1, A 1 |
32˚29'07.22"N, 116˚51'22.50"W |
200 |
M3 |
Commercial/residential area |
Q 1, S 1, A 1 |
32˚26'16.62"N, 117˚02'24.34"W |
267 |
M4 |
Commercial/residential area |
Q 1, S 1, A 1 |
32˚29'18.93"N, 116˚57'04.39"W |
70 |
2.2. Sample Collection and Transport
Fresh cheese samples (100 g) were placed in sterile bags and kept at 4˚C - 8˚C for up to 4 h. Food-contact surfaces (20 - 100 cm2) were swabbed using pre-moistened swabs in tryptic soy broth, following ISO 18593: 2004 [12]. Ambient air samples were obtained by settle plate method on Plate Count Agar for 10 min at positions determined by p = 0.15 √S (where S is room area in m2) according to UNE 171330-1: 2008 [13].
2.3. Initial Microbiological Processing
After incubation for 24 h at 37˚C on tryptic soy agar (TSA) and MacConkey agar (BD Difco, USA), each sample was processed in accordance with the relevant Mexican Official Standards (Table 2). From every plate, no more than five colonies that differed in morphology or pigmentation were sub-cultured onto brain–heart infusion (BHI) agar; duplicate morphotypes were discarded to avoid over-representation. Pure cultures were characterised by Gram stain, oxidase and catalase tests, followed by species-level identification with the VITEK-2 system (bioMérieux).
The analyser was checked every 48 h with E. coli ATCC 25922 and S. aureus ATCC 29213, and results had to fall within CLSI M100-S34 acceptance limits [14].
Table 2. Mexican official standards applied.
Standard |
Purpose |
Application in this study |
NOM-110-SSA1-1994 [15] |
Sample preparation and serial dilution |
Homogenization and serial dilution of cheese and swabs |
NOM-092-SSA1-1994 [16] |
Enumeration of mesophilic aerobic bacteria |
Incubation at 35˚C ± 2˚C for 48 ± 2 h |
NOM-210-SSA1-2014 [17] |
Microbiological sampling of dairy products |
Acceptance criteria (absence of pathogens) |
2.4. Isolation and Identification of Gram-Negative Bacteria
Presumptive Gram-negative isolates were identified using the VITEK 2 GN system (bioMérieux, Mexico) with a 0.5 McFarland inoculum. Results were available after approximately 18 h. Pure cultures were cryopreserved in TSB with 20% glycerol at −80˚C.
2.5. Antimicrobial Susceptibility Testing
Antibiotic susceptibility was determined by VITEK 2 AST-GN cards and interpreted according to CLSI M100 (2024) breakpoints. Table 3 lists the antibiotics tested.
Table 3. Antibiotics included in the VITEK 2 AST-GN card.
Class |
Antibiotics |
Penicillins |
Piperacillin, Ticarcillin, Ampicillin, Piperacillin/Tazobactam, Amoxicillin/Clavulanic acid |
Cephalosporinas |
Cephalothin, Cefuroxime, Cefotaxime, Ceftriaxone, Ceftazidime, Cefepime |
Carbapenems |
Imipenem, Meropenem, Ertapenem |
Monobactams |
Aztreonam |
Aminoglycosides |
Gentamicin, Amikacin, Tobramycin |
Fluoroquinolones |
Ciprofloxacin, Levofloxacin, Norfloxacin |
Polymyxins |
Colistin |
Other |
Trimethoprim/Sulfamethoxazole, Tetracycline, Tigecycline |
2.6. Bacterial Growth Curves
To characterize the growth kinetics of five selected Gram-negative genera (Escherichia coli, Serratia marcescens, Pantoea agglomerans, Raoultella planticola and Citrobacter freundii), each strain was grown for 18 h in BHI at 37˚C and adjusted to 0.5 McFarland (≈1 × 108 CFU/mL) with a DensiCHEK Plus (bioMérieux). Only Gram-negative isolates were included because the study did not plan to analyze the rpoS gene in Gram-positive cocci. Erlenmeyer flasks (250 mL) containing 100 mL BHI were inoculated to ~1 × 106 CFU/mL (1% v/v) and incubated at 37˚C, 120 rpm. At regular intervals (Table 4), 2 mL samples were withdrawn and the OD600 was measured in duplicate on a Genesys 20 spectrophotometer (Thermo Scientific) using sterile BHI as blank. The exponential phase was identified from OD600-versus-time plots, and the specific growth rate (µ) was calculated with Equation (1).
µ = [ln(OD2) − ln(OD1)]/(t2 – t1) (1)
and generation time (g) as Equation (2)
g = ln2/µ. (2)
Data were compared by one-way ANOVA (p < 0.05). E. coli ATCC 25922 served as quality control, and any curve with R2 < 0.95 was repeated.
Table 4. Schedule of OD600 measurements for each genus.
Genus (strain) |
No. of readings |
Approx. interval |
Total duration (h) |
E. coli |
10 |
60 min |
11 |
S. marcescens |
7 |
90 min |
11 |
P. agglomerans |
8 |
90 min |
12 |
R. planticola |
9 |
90 min |
12.5 |
C. freundii |
7 |
90 min |
11 |
These kinetic parameters (µ, g) were used to identify the onset of stationary phase for subsequent assays, ensuring all cultures were sampled at comparable physiological states.
2.7. Biofilm Formation Assay
Biofilms were quantified using the microtiter plate method of O’Toole [18] and classified per Stepanović et al. [19]. Stationary-phase cultures were adjusted to ≈106 CFU/mL (1:100 dilution of 0.5 McFarland cultures). Seventeen Gram-negative isolates were tested in condition C1 and additionally under C2-C4 (Table 5). Briefly, 200 µL of each suspension was inoculated into 96-well polystyrene plates, washed three times with PBS, fixed at 60˚C for 15 min, and stained with 0.1% crystal violet for 15 min. After rinsing and air-drying, dye was solubilized in 200 µL 30% (v/v) glacial acetic acid, and OD630 [20] was measured with a Multiskan FC (Thermo Fisher, USA) at the crystal violet absorption maximum in acidic medium. Biofilm production was categorized using ODc = mean blank + 3 SD: non-producers (OD ≤ ODc), weak (ODc < OD ≤ 2 × ODc), moderate (2 × ODc < OD ≤ 4 × ODc) or strong (OD > 4 × ODc). Statistical analysis was performed by one-way ANOVA with Tukey’s post-hoc test (p < 0.05).
Table 5. Conditions for biofilm assays.
Condition |
Medium (200 µL/well) |
Temperature |
Incubation time |
C1 |
BHI + 2% glucose |
37˚C |
24 h |
C2 |
Peptone water 0.1% |
37˚C |
24 h |
C3 |
BHI + 2% glucose |
22˚C ± 2˚C |
24 h |
C4 |
BHI + 2% glucose |
4˚C ± 2˚C |
24 h |
2.8. Genomic DNA Extraction and Polymerase Chain Reaction (PCR)
Specific primer sets were carefully designed for each targeted genus, as detailed in Table 6, resulting in PCR products of varying lengths: 226 bp for Escherichia coli, 201 bp for Serratia marcescens, 242 bp for Pantoea agglomerans 236 bp for Raoultella planticola, and 157 bp for Citrobacter freundii. As illustrated in Figure 4, agarose gel electrophoresis (1.2% TBE) confirmed that all Gram-negative isolates generated bands corresponding to their respective genera. Notably, the positive controls—E. coli K-12 MG1655 and C. freundii ATCC 8090—produced PCR product sizes aligned with those observed in the field isolates. In contrast, the negative control (PCR-grade water) yielded no amplification. A purification protocol was optimized to isolate high-quality DNA before molecular testing, adapted from Weerakkody et al. [21]. This procedure was conducted in a biosafety cabinet under aseptic conditions, using sterilized materials and strict sanitation practices to prevent cross-contamination. Approximately 20 μL of bacterial biomass from fresh cultures (TSA plate scraping) was transferred to a 1.5 mL microtube for cell lysis. 300 μL of lysis buffer (containing NaOH and SDS) was added and mixed for 15 seconds on a vortex mixer. The samples were incubated for 5 minutes at 80˚C in a water bath to denature proteins and disrupt the cell wall. Following incubation, the tubes were briefly cooled, and 1.5 μL of RNase A (10 mg/mL) was added, followed by a 10-minute incubation at 37˚C to degrade residual RNA. Subsequently, 100 μL of precipitation buffer (4M potassium acetate, pH 4.0) was added and mixed gently. The tubes were centrifuged for 3 minutes at 13,000 rpm, discarding the pellet containing precipitated detritus and proteins. The clarified supernatant was transferred to a clean tube, and 300 μL of isopropanol was introduced to precipitate the DNA, which was mixed by inversion. The samples were stored at −20˚C for 24 hours to ensure complete precipitation. Afterward, the samples were centrifuged for 1 minute at 13,000 rpm, with the isopropanol discarded. The resultant pellet was washed with 100 μL of 70% ethanol and centrifuged again. The pellet was air-dried at room temperature until all residual ethanol evaporated. Ultimately, the DNA was resuspended in 100 μL of nuclease-free water and stored at −20˚C until further use [22].
The oligonucleotides were designed from the sequences reported in the National Library of Medicine (https://www.ncbi.nlm.nih.gov/) Gene ID: 947210, (for Escherichia coli), Gene ID: 57426935 (Raoultella planticola), Gene ID: 66824848 (Pantoea agglomerans), Gene ID: 86999769 (Citrobacter freundii), Gene ID: 93695333 (Serratia marcescens) and using the software Primer3web version 4.1.0. [23].
For the detection of the rpoS gene, conventional PCR was performed on the extracted genomic DNA. Each 25 μL reaction mix comprised 12.5 μL of 2 × Taq PCR Master Mix (Bioneer, USA), five μL of a primer mixture (both forward and reverse primers at 10 μM; refer to Table 2), two μL of template DNA, and 5.5 μL of nuclease-free water. Amplification was carried out in a ATC 201 Thermal Cycler (Nyx Technik, Inc. San Diego, CA, USA). following this protocol: initial denaturation at 95˚C for 10 minutes, followed by 30 cycles of denaturation at 95˚C for 30 seconds, annealing at 66.8˚C for 30 seconds, and elongation at 72˚C for 30 seconds, concluding with a final extension at 72˚C for 10 minutes. The PCR products were resolved on a 1.2% agarose gel (in TBE buffer) at 120 V for 25 minutes and visualized under UV light post-staining with ethidium bromide, using a 100 bp ladder (Invitrogen) for size estimation of the amplicons. Positive controls included genomic DNA from Escherichia coli K-12 MG1655 and Citrobacter freundii ATCC 8090, while PCR-grade water was a negative control. The detection of rpoS was confirmed by the presence of a band of the expected size, correlating this finding with the intensity of the biofilm.
3. Results
3.1. Identification of Isolates and Sample Origins
A total of 30 viable isolates were obtained from fresh cheese, food-contact surfaces and ambient air: 17 Gram-negative (56.7%) and 13 Gram-positive (43.3%). Sampling was carried out in duplicate per matrix and each sample was labelled with a unique alphanumeric code (date-site-matrix-replicate). Fresh-cheese wedges (~100 g) were placed directly into sterile Whirl-Pak® bags by the sampling team wearing new nitrile gloves, which were changed between vendors; the outer 1 cm of rind was aseptically trimmed inside the bag with a sterile disposable scalpel to minimise carry-over from retail knives. Bags were stored at 4˚C - 8˚C in insulated coolers equipped with a calibrated thermometer and were processed within 4 h. Surfaces (20 - 100 cm2) were swabbed with single-use, pre-moistened swabs and transported on ice; ambient air was collected by 10-min settle plates sealed with ParafilmTM. A complete set of field blanks (bag, swab, plate) accompanied every round, and none showed growth after incubation. All subsequent handling was performed in a class II biosafety cabinet under aseptic conditions.
Figure 1 summarizes their distribution by sample type. The Gram-negative isolates included Escherichia coli (10), Raoultella planticola (3), Pantoea agglomerans (2), Serratia marcescens (1) and Citrobacter freundii (1). The Gram-positive isolates comprised Staphylococcus aureus (6), Kocuria kristinae (3), Propionibacterium acnes (1), Staphylococcus epidermidis (1), Staphylococcus auricularis (1) and Eggerthia catenaformis (1). Fresh cheese yielded the greatest diversity (21/30 isolates), followed by surfaces (8/30); only one Gram-positive cocci (S. epidermidis) was recovered from air (Figure 1).
Figure 1. Distribution of gram-negative and gram-positive isolates by sampling matrix (cheese, surface, air).
3.2. Antimicrobial Susceptibility Profile
Using the VITEK 2 AST-GN system, only 3 of 17 Gram-negative isolates (17.6%) exhibited resistance (Table 6): two P. agglomerans (cheese and surface) were resistant to cefoxitin (MIC = 16 µg/mL), and one E. coli (cheese) was resistant to ampicillin/sulbactam (MIC ≥ 32 µg/mL). All other Gram-negatives—including R. planticola, S. marcescens and C. freundii—were susceptible to the full panel. Among the 13 Gram-positive isolates, only a single Staphylococcus epidermidis from air exhibited tetracycline resistance (MIC ≥ 16 µg/mL). All S. aureus, K. kristinae, P. acnes, S. auricularis and E. catenaformis strains were susceptible to every antibiotic tested.
Table 6. Antimicrobial resistance among gram-negative isolates.
Species |
Source |
Antibiotic |
MIC (µg/mL) |
Interpretation |
P. agglomerans |
Cheese |
Cefoxitin |
16 |
R |
P. agglomerans |
Surface |
Cefoxitin |
16 |
R |
E. coli |
Cheese |
Ampicillin/Sulbactam |
≥32 |
R |
3.3. Growth Curves of Five Gram-Negative Genera
Figure 2 displays the growth curves at 37˚C for representative strains of E. coli, S. marcescens, P. agglomerans, R. planticola and C. freundii. All followed a typical sigmoid pattern, with a short lag phase (<45 min) and transition to stationary phase between 6 and 10 h, depending on the genus. Also during the development of the growth curve, the growth rate and generation time were determined (Table 7).
Figure 2. Growth curves (OD600 vs. readings) for representative strains of the five Gram-negative genera.
Table 7. Kinetic parameters derived from the exponential phase.
Genus |
Specific growth rate (µ, h−1) |
Generation time (g, min) |
E. coli |
0.280 ± 0.012 |
149 ± 6 |
S. marcescens |
0.255 ± 0.010 |
163 ± 5 |
P. agglomerans |
0.230 ± 0.009 |
181 ± 6 |
R. planticola |
0.207 ± 0.011 |
201 ± 7 |
C. freundii |
0.185 ± 0.008 |
225 ± 8 |
A one-way ANOVA revealed significant differences in µ among genera (F = 11.6; p < 0.01). Tukey’s post-hoc test showed that E. coli grew significantly faster than P. agglomerans, R. planticola and C. freundii (p < 0.05), while differences between S. marcescens and P. agglomerans were not significant (p = 0.08). These parameters defined the precise sampling point at OD600 ≈ 1.2 ± 0.1 for stationary phase prior to biofilm assays, ensuring comparable physiological states.
3.4. Biofilm Formation
All 17 Gram-negative isolates were tested under four conditions: C1 (BHI + 2% glucose, 37˚C), C2 (peptone water, 37˚C), C3 (BHI + 2% glucose, 22˚C) and C4 (BHI + 2% glucose, 4˚C). Biofilm biomass was measured as OD630 after crystal violet solubilization in 30% glacial acetic acid.
3.4.1. Biofilm Biomass by Condition
Figure 3 shows the mean ± SD of OD630 for each genus and condition. Overall, C1 produced the highest biomass (mean 0.62 ± 0.14), followed by C3 (0.45 ± 0.12). C2 and C4 reduced biomass to 0.31 ± 0.10 and 0.27 ± 0.09, respectively. A two-way ANOVA (genus × condition) confirmed significant effects of both factors (p < 0.05) and their interaction (p = 0.03), indicating genus-dependent responses to temperature and nutrient availability.
Figure 3. Mean biofilm biomass (OD630 ± SD) formed by five Gram-negative bacterial genera under four experimental conditions: C1 (BHI + 2% glucose, 37˚C), C2 (peptone water, 37˚C), C3 (BHI + 2% glucose, 22˚C), and C4 (BHI + 2% glucose, 4˚C). Error bars represent standard deviation (SD).
3.4.2. Biofilm Intensity Classification
Using ODc = mean blank + 3 SD (0.12), isolates were classified as non-producers (OD ≤ ODc), weak (ODc < OD ≤ 2 × ODc), moderate (2 × ODc < OD ≤ 4 × ODc) or strong (OD > 4 × ODc) (Table 8).
Table 8. Biofilm intensity classification by genus.
Genus |
Non-producer |
Weak |
Moderate |
Strong |
Total |
E. coli (n = 10) |
2 |
6 |
2 |
0 |
10 |
R. planticola (n = 3) |
2 |
1 |
0 |
0 |
3 |
P. agglomerans (n = 2) |
0 |
2 |
0 |
0 |
2 |
S. marcescens (n = 1) |
0 |
1 |
0 |
0 |
1 |
C. freundii (n = 1) |
0 |
0 |
0 |
1 |
1 |
Total (%) |
4 (23.5) |
10 (58.8) |
2 (11.8) |
1 (5.9) |
17 |
A chi-square test of homogeneity (χ2 = 14.2; df = 6; p = 0.028) showed that intensity distributions differed by genus: C. freundii was the only “strong” biofilm former in all conditions, while R. planticola was mainly “non-producer” (67%). Most E. coli and S. marcescens were classified as “weak”, although two E. coli strains reached “moderate” in C1.
3.4.3. Relationship to Stationary Phase and rpoS
All isolates tested positive for the rpoS gene confirming the presence of the stationary-phase sigma factor. However, rpoS presence alone did not predict biofilm robustness: R. planticola carried rpoS but produced little biomass, whereas C. freundii combined slow growth with dense biofilms under all conditions, suggesting that additional extracellular matrix components and regulatory mechanisms govern biofilm strength.
3.5. Detection of the rpoS Gene
Specific primer sets were meticulously designed for each targeted genus, as outlined in Table 9, resulting in PCR products of distinct lengths: 226 bp for Escherichia coli, 201 bp for Serratia marcescens, 242 bp for Pantoea agglomerans, 236 bp for Raoultella planticola, and 157 bp for Citrobacter freundii.
Table 9. Primers used for amplification of the rpoS gene.
Genus |
Forward primer (5'→3') |
Reverse primer (5'→3') |
Expected amplicon size (bp) |
Escherichia coli |
GCT GAA CGT TTA CCT GCG AA |
GGT ATC TTC CGG ACC GTT CG |
226 |
Raoultella planticola |
CCC GTA CCA TCC GTT TAC CT |
ATC GGC CAG AAT ATC CAG CA |
236 |
Pantoea agglomerans |
ATC AAA CCC GTA CCA TCC GT |
ATC GGC CAG AAT ATC CAG CA |
242 |
Citrobacter freundii |
TAA ACT GGA CCA CGA ACC GA |
GGC CAG AAT ATC CAG CAA CG |
157 |
Serratia marcescens |
TCG AAC GAG AAT GGA GCT GAG |
GCC GCG CAA AAT AGA CTT CT |
201 |
As demonstrated in Figure 4, the agarose gel electrophoresis (1.2% TBE) revealed that all Gram-negative isolates produced bands corresponding to their respective genera. Notably, the positive controls—E. coli K-12 MG1655 and C. freundii ATCC 8090—exhibited PCR product sizes consistent with those of the field isolates. At the same time, the negative control (PCR-grade water) showed no amplification, effectively ruling out any potential reagent contamination. Gram-positive strains were excluded from this analysis, as the rpoS gene is specific to Gram-negative bacilli [19]. The rpoS gene is a critical regulator of biofilm formation, enhancing bacterial resilience in challenging environments. Factors influencing rpoS activity include oxidative stress, osmotic pressure, and nutrient availability. A thorough understanding of the regulatory networks governed by rpoS is pivotal for devising targeted biofilm management strategies, ultimately aimed at augmenting food quality and safety. 100% of Gram-negative isolates carry rpoS, although biofilm intensity varied among genera.
![]()
Figure 4. PCR of bacterial strains isolated from cheese samples, characterized by biochemical tests. A. Lane 1: Molecular weight marker, Lane 2: E. coli, Lane 3: E. coli, Lane 4: E. coli, Lane 5: E. coli, Lane 6: S. marcescens, Lane 7: Positive control (E. coli ATCC), Lane 8: Negative control. B. Lane 1: Molecular weight marker, Lane 2: R. planticola, Lane 3: R. planticola, Lane 4: E. coli, Lane 5: R. planticola, Lane 6: E. coli, Lane 7: Positive control (E. coli ATCC), Lane 8: Negative control. C. Lane 1: Molecular weight marker, Lane 2: E. coli, Lane 3: E. coli, Lane 4: E. coli, Lane 5: E. coli, Lane 6: Positive control (E. coli ATCC), Lane 7: Negative control. D. Lane 1: Molecular weight marker, Lane 2: P. agglomerans, Lane 3: P. agglomerans, Lane 4: C. freundii, Lane 5: Positive control (C. freundii), Lane 6: Negative control.
4. Discussion
The recovery of 17 Gram-negative and 13 Gram-positive isolates from fresh cheese and food-contact surfaces underscores the high microbial diversity reported in Mexican artisanal cheeses. That 57% of isolates were Gram-negative bacilli aligns with studies of unpasteurized dairy products in Latin America, where Escherichia coli and other Enterobacterales predominate contaminant microbiota [23].
4.1. Antimicrobial Resistance
The detection of only three resistant phenotypes among Gram negatives (17.6%) and one among Gram positives confirms the low prevalence of antimicrobial resistance (AMR) in fresh cheeses observed by Cabrera-Díaz et al. [23] in central Mexico. Nevertheless, cefoxitin resistance in Pantoea agglomerans and ampicillin/sulbactam resistance in one E. coli suggest local selective pressure, possibly due to β-lactam use in dairy herds as documented by the FAO [24]. Although no ESBL or multidrug-resistant profiles were found, the WHO warns that even low percentages can rapidly amplify within biofilm niches [2].
4.2. Growth Kinetics
Growth curves showed that E. coli (µ ≈ 0.28 h−1) multiplied significantly faster than P. agglomerans, R. planticola and C. freundii. However, biofilm biomass did not correlate linearly with growth rate: C. freundii, despite being the slowest grower (µ ≈ 0.19 h−1), produced the only “strong” biofilms under all conditions. This supports the concept that prolonged stationary phase enhances matrix gene expression and three-dimensional architecture, as described for Enterobacter spp. by Pires et al. [6].
4.3. Biofilm Formation
Biofilm biomass was the highest in BHI at 37˚C (C1), yet incubation at 22˚C (C3) retained 73% of the biomass, indicating that typical retail-display temperatures still allow substantial biofilm formation. Cold storage at 4˚C reduced biomass by ≈ 55%, confirming that refrigeration slows but does not eliminate adherence [8]. The significant genus × condition interaction (p = 0.03) highlights genus-specific responses: for example, P. agglomerans doubled its OD630 in peptone water compared to BHI, possibly driven by a “biofilm-by-starvation” mechanism reported for environmental Enterobacterales [6].
4.4. Universality and Relative Impact of rpoS
The 100% positivity for rpoS confirms a universal stress-response potential among the isolates. However, rpoS presence alone did not predict biofilm strength: R. planticola carried the gene but was largely a non-producer, while C. freundii combined slow growth with dense biofilm formation under all conditions, suggesting that upstream regulatory mutations or interaction with bolA modulate matrix synthesis [7]. It is plausible that R. planticola has less efficient rpoS regulation or produces an EPS with weaker affinity for polystyrene.
Interaction between Biofilm, rpoS and Antimicrobial Resistance
No significant correlation was found between biofilm biomass (OD630) and the number of antibiotics to which an isolate was resistant (ρ = 0.21, n = 30, p = 0.32). Similar results were reported by Robbe-Saule et al. for Salmonella [9] and by Priego-Salado et al. for dairy Citrobacter isolates [24]. Although oxidative stress can activate the AcrAB efflux pump via rpoS and slightly increase multidrug tolerance in E. coli [25], recent genomic studies indicate that rpoS chiefly aids environmental adaptation and contributes little to clinically relevant AMR [26]. Our data support this view: in artisanal cheeses, rpoS enhances persistence through biofilm formation, whereas antimicrobial resistance depends mainly on other factors
4.5. Implications for the Artisanal Dairy Chain
Although AMR prevalence was low and most strains formed weak biofilms, the isolation of C. freundii—a strong biofilm former carrying rpoS—poses a potential hazard. Pipeline model studies demonstrate that dense Citrobacter biofilms protect coliform pathogens and hinder alkaline detergent penetration [27] [28]. Furthermore, tolerance at 22˚C implies that open-market display surfaces facilitate persistence and dissemination.
4.6. Public-Health Implications and Control Strategies
Fresh, raw-milk cheeses sold at room temperature can carry rpoS-positive Gram-negative bacteria that form biofilms on knives and display cases. These biofilms may survive routine rinsing for at least two days, seeding the cheese with stress-tolerant cells and occasional β-lactam resistance. Similar strains were traced from artisanal cheeses to patients during recent outbreaks in Europe and Latin America [29]. Even low-level resistance can complicate treatment in vulnerable consumers, yet Mexico’s NOM-243 focuses only on coliform counts and overlooks biofilms. Based on our findings, we recommend: 1) disinfectants validated against biofilms, 2) regular disassembly and scrubbing of utensils, and 3) targeted monitoring of rpoS and key AMR genes along the producer-to-retailer chain. These measures would reduce microbial load and the selection pressure for resistance, aligning local practice with the One Health guidance of the FAO and WHO [30].
4.7. Limitations and Future Directions
1) This study was limited to a single municipality and a winter–spring sampling period, so seasonal variation may alter microbial diversity. 2) Biofilm assays were performed on polystyrene, whereas stainless steel predominates in dairy equipment [31] [32]. 3) Biomass was estimated solely by the crystal-violet OD630 assay, which stains both living cells and extracellular matrix; differences in matrix composition, washing intensity and plate surface chemistry can over- or under-estimate viable biofilm [33] [34]. Complementary methods such as viable-cell counts or confocal microscopy should be included in future work. 4) Upcoming studies should therefore assess rpoS and EPS-gene expression via RT-qPCR. 5) evaluate dual-species biofilms involving Gram-positive cocci. 6) validate cleaning strategies such as enzyme-based disinfectants.
5. Conclusion
Artisanal cheeses marketed in Tijuana (a U.S-Mexico border city), harbour a diverse microbiota in which more than half of the isolates are Gram-negative bacilli that carry the rpoS gene and can form biofilms. Although the antimicrobial resistance detected was low and sporadic, the presence of “strong” biofilms in Citrobacter freundii and the persistence of several genera at 22˚C and 4˚C indicate a potential food-safety risk. Detection of rpoS alone does not explain biofilm intensity; regulatory and environmental factors also contribute. These findings support tightening cleaning protocols aimed at mixed-species biofilms and maintaining continuous monitoring of resistance along the artisanal dairy chain.