Breast-Cancer-Derived Secretomes from MCF-7 Cells Modulate Bacterial Pathogenic Traits

Abstract

Breast cancer is the most frequently diagnosed malignancy among women worldwide, with the luminal A subtype being the most prevalent. Several studies have reported a complex interplay between breast cancer cells and the local microbiome; however, the mechanisms by which tumor cell-secreted factors influence bacterial biological properties remain insufficiently explored. In this study, we established an in vitro model that partially recapitulates the luminal A breast cancer microenvironment by exposing three breast-associated bacterial species, Pseudomonas aeruginosa, Enterococcus faecalis, and Escherichia coli, to conditioned media (CM) derived from MCF-7 (tumor) or MCF-10A (non-tumor control) cell lines. A combination of complementary approaches, including ultrastructural morphological assessment, biofilm formation assays, antimicrobial susceptibility testing, and virulence gene abundance profiling by genomic qPCR, was employed to reveal distinct tumor-microbiota interactions. Exposure to MCF-7 CM induced dose-dependent structural alterations in P. aeruginosa and E. faecalis, with pronounced membrane blebbing and structural disruption in E. faecalis. Biofilm formation was differentially modulated in a species- and concentration-dependent manner, with a persistent increase observed in E. coli. Antibiotic susceptibility profiles were selectively altered in E. faecalis, which displayed increased sensitivity to vancomycin, penicillin, and imipenem, along with decreased sensitivity to chloramphenicol. P. aeruginosa exhibited increased sensitivity to imipenem along with reduced sensitivity to meropenem and gentamicin, whereas no significant changes were observed in E. coli. qPCR analyses demonstrated that MCF-7 CM was associated with enrichment of multiple virulence-associated genes (e.g., lasB, exoS, pilB, plcH, fsrC, esp, fimH, and papG), reflecting enhanced pathogenic and adhesive potential. Collectively, these findings suggest that luminal A breast cancer-derived factors can reprogram microbial phenotypes in a species-specific manner, providing mechanistic insight into breast tumor-microbiome crosstalk and a platform to explore microbiome-targeted interventions.

1. Introduction

Breast cancer is one of the most common malignancies impacting women in Saudi Arabia and worldwide [1]. Despite advances in detection and treatment, mortality from breast cancer remains high due to drug resistance and metastatic disease, which severely restricts the efficacy of long-term therapy. Furthermore, adverse clinical outcomes are associated with intricate interactions between the tumor microenvironment and cancer cells, which promote tumor growth and limit therapy response [1,2]. The breast tissue microbiome is increasingly recognized as an active player in modulating carcinogenesis and therapeutic responsiveness in breast cancer. Despite growing evidence implicating microbial dysbiosis in various cancers, the specific interactions between tissue-resident bacteria and breast cancer cells remain poorly characterized. Recent studies have shown that the breast tissue harbors distinct microbial communities that differ according to molecular subtype, tumor grade, and disease aggressiveness, suggesting a close cross-talk between tumor biology and microbial composition [3,4]. Several studies have confirmed that healthy breast tissue hosts bacterial genera such as Pseudomonas, Lactobacillus, Prevotella, and Streptococcus, which contribute to maintaining breast health [5]. In contrast, reports show an enrichment of Methylobacterium and depletion of Sphingomonas yanoikuyae within the breast tumor microenvironment and adjacent tissue [6]. The tumor microenvironment provides favorable conditions for microbial colonization and persistence, contributing to the establishment of a distinct breast microbiome [7]. Some bacterial species may exert protective effects against breast cancer by modulating estrogen metabolism and improving immune surveillance [6]. In contrast, certain bacterial species may promote malignancy by inducing chronic inflammation, disrupting cellular homeostasis, and provoking dysregulated immune responses [8]. Consequently, characterizing these particular bacteria could uncover innovative therapeutic targets for the prevention and treatment of breast cancer.

In this study, we leveraged an in vitro model to slightly simulate the influence of luminal A tumor conditioned medium (secretomes) on bacterial physiology by exposing three breast-associated bacterial strains, E. coli, E. faecalis, and P. aeruginosa to conditioned media derived either from MCF-7 (CM-7) tumor cells or MCF-10A (CM-10A), serving as a non-tumorigenic control. By integrating analyses of bacterial morphology, biofilm formation, antibiotic susceptibility, and virulence gene abundance, this study reveals how tumor-derived factors modulate bacterial behavior, thereby offering mechanistic insights into the potential role of the breast microbiome in luminal A carcinogenesis.

2. Results

2.1. Conditioned-Media from MCF-7 Cancer Cells Induced Morphological Remodeling of P. aeruginosa and E. faecalis

To directly assess the impact of breast tumor and control cell secretomes on bacterial surface ultrastructure, P. aeruginosa and E. faecalis were first cultured from standardized, OD₆₀₀-adjusted overnight bacterial suspensions and exposed for 24 h to cell-free conditioned-media at defined concentrations (10% and 15% v/v), derived from either MCF-7 (CM-7; luminal A breast cancer) or MCF-10A (CM-10A; normal breast epithelial) cell lines. Conditioned media were obtained using serum-free culture procedures, followed by sterile collection and filtration. In parallel, cell-free media (CFM) controls were processed under identical conditions in the absence of cells. Bacterial cells were then processed for scanning electron microscopy (SEM) analysis. Figure 1 shows the SEM images of both bacterial species. P. aeruginosa and E. faecalis treated with 10% and 15% of CM-7 (Figure 1b,d,f,h) visibly produced structural disruptions when compared to CM-10A-treated bacteria (Figure 1a,c,e,g), which preserved native morphology with smooth, intact cell surfaces comparable to CFM control (Supplementary Figures S1 and S2). At 10% CM-7, both P. aeruginosa and E. faecalis exhibited increased surface roughness and emergence of membrane granules (Figure 1b,f). At 15% CM-7 (Figure 1d,h), SEM images displayed marked membrane ruptures, pronounced cell aggregation, and deformation. These effects were greatly intensified in E. faecalis, which developed extensive membrane blebbing and structural breakdown (Figure 1h), indicating a greater suitability to tumor-cell-derived secretomes. Altogether, SEM analysis demonstrates that MCF-7 secretomes elicit marked, concentration-dependent ultrastructural damage and remodeling in breast-associated bacteria.

2.2. Differential Modulation of Biofilm Formation by Breast Cancer Conditioned-Media

To evaluate whether breast cancer cell secretomes influence bacterial biofilm formation, P. aeruginosa, E. faecalis, and E. coli were incubated with variable concentrations (5%, 10%, and 15% v/v) of CM-7 or CM-10A (Control) for 24 h. Biofilm mass was quantified by spectrophotometer using a crystal violet retention assay, and values from CM-7 and CM-10A were normalized to their respective CFM controls. Figure 2A shows that P. aeruginosa biofilm formation was significantly reduced at 5% (p = 1.2 × 10⁻⁵) and significantly increased at 10% (p = 0.002) after exposure to CM-7, when compared to their relative control (5% and 10% CM-10A, respectively), whereas no significant difference was observed at 15% (p = 0.46). E. faecalis showed significant differences in biofilm formation at all tested CM-7 concentrations, with an increase at 5% (p = 2.0 × 10⁻⁶), a decrease at 10% (p = 1.1 × 10⁻⁶), and an increase at 15% (p = 5.0 × 10⁻⁶) (Figure 2B). In contrast, E. coli demonstrated a consistent and significant increase in biofilm formation following exposure to CM-7 at all tested concentrations, 5% (p = 4.7 × 10⁻⁷), 10% (p = 1.2 × 10⁻⁶), and 15% (p = 5.8 × 10⁻⁶) (Figure 2C). These findings reveal species-specific responses to breast cancer cell secretomes, with a pronounced enhancement of biofilm formation in E. coli and differential effects on P. aeruginosa and E. faecalis.

2.3. Altered Antibiotic Sensitivity Patterns Following Exposure to Breast Cancer Conditioned-Media

To determine whether breast cancer cell secretomes modulate the antimicrobial susceptibility of breast-associated bacteria, P. aeruginosa, E. faecalis, and E. coli were pre-exposed to 10% (v/v) of CM-7 or CM-10A, followed by an assessment using a standardized disc diffusion assay. Inhibition zone diameters for CM-7 and CM-10A were reported after normalization to their respective CFM controls (Supplementary Figure S3). Exposure of P. aeruginosa to CM-7 significantly affected antibiotic susceptibility compared with CM-10A. While susceptibility to imipenem increased significantly (p = 1 × 10⁻⁵), susceptibility to meropenem (p = 1 × 10⁻⁴) and gentamicin (p = 1 × 10⁻⁵) was significantly reduced in CM-7 compared with CM-10A (Figure 3A). In E. faecalis, CM-7 significantly increased susceptibility to vancomycin (p = 1.20 × 10⁻⁷), penicillin (p = 1.03 × 10⁻⁵), and imipenem (p = 0.0448), while decreasing susceptibility to chloramphenicol (p = 3.03 × 10⁻⁶) (Figure 3B). These findings indicate that CM-7 selectively modulates P. aeruginosa and E. faecalis antibiotic responses in a drug-dependent manner. For E. coli, inhibition zone diameters for imipenem, meropenem, gentamicin, or chloramphenicol showed no significant differences between CM-7 and CM-10A (Figure 3C). Taken together, MCF-7-derived secretomes selectively modulate antibiotic susceptibility in a species- and drug-specific manner. While CM-7 had no effect on E. coli, it significantly reprogrammed E. faecalis responses, enhancing sensitivity to vancomycin, penicillin, and imipenem, while reducing sensitivity to chloramphenicol. In P. aeruginosa, CM-7 also altered antibiotic responses, enhancing sensitivity to imipenem, while reducing sensitivity to meropenem and gentamicin. These findings suggest that luminal A breast cancer secretomes can differentially influence bacterial responses to clinically relevant antibiotics.

2.4. MCF-7 Breast Cancer Secretomes Modulate Virulence-Associated Gene Abundance in P. aeruginosa

We next investigated whether secretomes from breast cancer cells modulate the P. aeruginosa virulence gene repertoire, which governs adhesion, tissue damage, immune evasion, and inflammatory potential, providing a functional readout of tumor-driven modulation of bacterial pathogenic potential. Six key virulence-associated genes (pilB, lasB, exoS, algD, plcH, and exoU) were quantified over time by qPCR using genomic DNA following exposure to 10% (v/v) CM-7 or CM-10A. Results of CM-7 or CM-10A were normalized to the 16S rRNA gene and their respective CFM controls (Figure 4A–F). Gene abundance of pilB, which encodes a protein required for type IV pilus biogenesis and bacterial adhesion, was significantly higher in CM-7–treated cultures compared with CM-10A at all-time points (24 h: p = 2.81 × 10⁻⁴; 48 h: p = 6.68 × 10⁻⁴; 72 h: p = 8.81 × 10⁻³) (Figure 4A), indicating enhanced surface attachment and colonization potential. Similarly, lasB, which encodes the elastase responsible for extracellular matrix degradation, showed significantly increased gene abundance in CM-7–treated cultures compared to CM-10A at 24 h (p = 7.0 × 10⁻⁶), 48 h (p = 1.4 × 10⁻⁵), and 72 h (p = 3.41 × 10⁻⁴) (Figure 4B). The type III secretion system effector exoS, which interferes with host cell signaling and cytoskeletal integrity, was also significantly enriched in CM-7–treated cultures at all measured time points (24 h: p = 2.0 × 10⁻⁶; 48 h: p = 7.9 × 10⁻⁵; 72 h: p = 2.96 × 10⁻⁴) compared with CM-10A (Figure 4C). In contrast, algD, a key enzyme involved in alginate biosynthesis and biofilm-associated immune evasion, exhibited a time-dependent response to CM-7 exposure, showing a modest but statistically significant increase at 24 h (p = 1.07 × 10⁻²), followed by significant downregulation at 48 h (p = 1.40 × 10⁻⁴), and no significant difference at 72 h (p = 0.132) relative to CM-10A (Figure 4D). The plcH, which encodes hemolytic phospholipase C involved in host phospholipid hydrolysis, tissue damage, and nutrient acquisition, was significantly increased following CM-7 exposure compared with CM-10A at all-time points (24 h: p = 3.07 × 10⁻⁴; 48 h: p = 1.74 × 10⁻⁴; 72 h: p = 7.74 × 10⁻⁴) (Figure 4E). exoU, a potent cytotoxic effector, showed a significant decrease at 24 h (p = 2.81 × 10⁻⁴), followed by significant increases at 48 h (p = 6.68 × 10⁻⁴), and 72 h (p = 8.81 × 10⁻³) in CM-7–treated cultures compared with CM-10A (Figure 4F). Taken together, exposure to the MCF-7 secretome modulates the abundance of major P. aeruginosa virulence genes involved in adhesion (pilB), extracellular matrix degradation (lasB), host cell disruption (exoS, exoU), biofilm-associated metabolism (algD), and phospholipase-mediated cytotoxicity (plcH). These CM-7 induced alterations highlight a tumor-specific capacity to reprogram bacterial pathogenic potential.

2.5. MCF-7 Breast Cancer Secretomes Enhance Virulence-Associated Gene Abundance in E. faecalis

Virulence gene abundance was assessed in E. faecalis following exposure to 10% (v/v) CM-7 or CM-10A. Exposure to CM-7 resulted in a significant enrichment of fsrC, a regulator of the fsr quorum-sensing system controlling gelatinase production and biofilm-associated functions, at all-time points compared with CM-10A (24 h: p = 1.21 × 10⁻⁶; 48 h: p = 1.15 × 10⁻⁵; 72 h: p = 5.32 × 10⁻⁵) (Figure 5A). Similarly, esp encoding the enterococcal surface protein involved in adhesion, immune evasion, and biofilm formation, was significantly increased following CM-7 exposure at 24 h (p = 1.08 × 10⁻⁶), 48 h (p = 4.22 × 10⁻⁵), and 72 h (p = 1.92 × 10⁻⁵) relative to CM-10A (Figure 5B). Genes associated with adhesion and persistence also showed robust enrichment in response to CM-7. Abundance of ace, encoding a collagen-binding adhesin, was significantly increased by CM-7 at 24 h (p = 1.07 × 10⁻⁶), 48 h (p = 5.42 × 10⁻⁶), and 72 h (p = 1.36 × 10⁻⁵) compared with CM-10A (Figure 5C). Likewise, asa1, which mediates aggregation and cell-to-cell contact, exhibited a significant increase in abundance at 24 h (p = 2.31 × 10⁻⁶), 48 h (p = 1.04 × 10⁻⁵), and 72 h (p = 4.87 × 10⁻⁶) following CM-7 exposure (Figure 5D). Abundance of efa, encoding the endocarditis-associated antigen involved in host tissue colonization, was also significantly elevated at 24 h (p = 1.02 × 10⁻⁶), 48 h (p = 2.44 × 10⁻⁵), and 72 h (p = 1.36 × 10⁻⁵) in CM-7-treated cultures relative to CM-10A (Figure 5E). Collectively, these results demonstrate that exposure to the MCF-7 secretome coordinately and consistently enhances the abundance of multiple E. faecalis virulence determinants involved in quorum sensing, adhesion, aggregation, and host-tissue colonization, supporting a shift toward a phenotype associated with increased virulence potential.

2.6. MCF-7 Breast Cancer Secretomes Modulate Adhesion-Related Virulence Gene Abundance in E. coli

As described for P. aeruginosa and E. faecalis, the abundance of papG, draA, papC, and fimH was quantified in E. coli following exposure to 10% (v/v) CM-7 or CM-10A. The P-fimbrial genes (papG) encode components required for P-fimbriae assembly and epithelial adhesion. papG abundance was significantly increased in CM-7-treated cultures compared with CM-10A at 24 h (p = 4.29 × 10⁻¹⁰), 48 h (p = 3.30 × 10⁻⁸), and 72 h (p = 2.69 × 10⁻⁸) (Figure 6A). However, papC showed a significant decrease in relative gene abundance under CM-7 exposure at 24 h (p = 4.32 × 10⁻⁶), followed by significant upregulation at 48 h (p = 8.77 × 10⁻⁷) and 72 h (p = 1.78 × 10⁻⁷) (Figure 6B). The Dr-family adhesin gene draA, implicated in epithelial colonization, was also significantly enriched in CM-7-exposed cultures compared with CM-10A at 24 h (p = 1.28 × 10⁻⁵), 48 h (p = 1.31 × 10⁻⁶), and 72 h (p = 1.40 × 10⁻⁹) (Figure 6C). fimH, which encodes the mannose-binding tip adhesin of type 1 fimbriae that mediates attachment to host cells, exhibited significant downregulation following CM-7 exposure at 24 h (p = 4.28 × 10⁻⁴) and 48 h (p = 9.08 × 10⁻³), followed by significant upregulation at 72 h (p = 3.15 × 10⁻⁵) (Figure 6D). Altogether, these results demonstrate that exposure to the MCF-7 luminal A breast cancer secretome drives a coordinated and statistically robust increase in the abundance of E. coli adhesion-associated virulence genes involved in fimbriae assembly and epithelial colonization. This gene-level reprogramming is consistent with the enhanced biofilm formation observed under CM-7 exposure.

3. Discussion

The human microbiome is emerging as a dynamic modulator of host physiology, immunology, and disease progression, including cancer. While much attention has been paid to the gut microbiome, the discovery and potential implications of bacteria in tissue-specific sites such as the breast have only recently been appreciated. This study was designed to model, in a controlled in vitro system, how luminal A breast cancer-derived secretomes modulate the phenotype and virulence of breast-associated bacteria. P. aeruginosa, E. faecalis, and E. coli were exposed to tumor-conditioned media from MCF-7 (CM-7) or non-tumor MCF-10A (CM-10A) cells, and changes in morphology, biofilm formation, antibiotic susceptibility, and virulence-gene abundance were assessed. This work provides a mechanistic framework for understanding tumor-microbiome crosstalk within the breast microenvironment, using qPCR on genomic DNA to quantify virulence-gene copy number as a measure of gene abundance.

Our study shows that CM-7 causes clear, dose-dependent structural disturbances in P. aeruginosa and, most prominently, in E. faecalis, while CM-10A and its relative CFM controls preserved native bacterial morphology. These ultrastructural alterations—including membrane irregularities, blebbing, and aggregation—indicate that luminal A tumor-derived factors can directly perturb bacterial envelopes and surface architecture, with potential implications for bacterial persistence and immune recognition. Recently, AlDawsari et al. reported more pronounced membrane damage and structural disruption in P. aeruginosa that were exposed to secretomes from MDA-MB-231 triple-negative breast cancer cells [9]. This enhanced effect is consistent with the more aggressive biological behavior of triple-negative tumors (MDA-MB-231) compared with luminal A disease (MCF-7). These findings suggest that breast cancer molecular subtype may differentially shape the severity and nature of tumor–microbiota interactions at the level of bacterial envelope integrity. In parallel, these ultrastructural changes were accompanied by species-specific and concentration-dependent effects on biofilm formation, with non-linear responses observed in P. aeruginosa and E. faecalis, and a consistent enhancement of E. coli biofilm formation across all tested doses. Together, these findings indicate that luminal A tumor secretomes do not act uniformly but instead reprogram individual taxa toward distinct ecological roles. This observation aligns with emerging evidence that breast tumors harbor molecular-subtype-specific microbial signatures, with particular taxa enriched or depleted in malignant versus benign tissue and across prognostic groups [1,4,6,10]. Collectively, these findings suggest that luminal A breast cancer-derived secretomes actively reprogram breast-associated bacterial behavior, promoting species-specific changes in virulence, biofilm formation, and antibiotic responsiveness that may contribute to a pro-tumorigenic breast microenvironment (Figure 7).

Antibiotic susceptibility profiling further revealed that tumor secretomes selectively reshape drug responses in a species- and drug-dependent manner rather than inducing broad resistance. Notably, E. faecalis exposed to CM-7 exhibited increased susceptibility to vancomycin, penicillin, and imipenem, alongside reduced susceptibility to chloramphenicol. CM-7 exposure modulated antibiotic susceptibility in P. aeruginosa, enhancing sensitivity to imipenem but decreasing sensitivity to meropenem and gentamicin. In contrast, no statistically significant changes in antibiotic susceptibility were observed in E. coli following CM-7 exposure. These selective effects suggest that tumor-derived factors may fine-tune specific bacterial pathways involved in cell wall or stress responses rather than globally altering antimicrobial sensitivity. Such strain- and drug-specific modulation is consistent with broader evidence that host–microbiota interactions can influence infection risk and therapeutic outcomes in cancer patients [7,11,12].

At the gene-abundance level, this study demonstrated coordinated upregulation of multiple virulence-associated genes in all three bacterial species in response to the luminal A tumor secretome. In P. aeruginosa, CM-7 significantly increased the abundance of pilB, lasB, exoS, and plcH, while algD and exoU showed time-dependent response, with algD peaking at 24 h and exoU at 48–72 h. These CM-7-mediated changes in P. aeruginosa suggest enhanced adhesion, extracellular matrix degradation, secretion system-mediated cytotoxicity, and phospholipase-driven tissue damage. Enrichment of fsrC, esp, ace, asa1, and efa in E. faecalis following exposure to CM-7 indicates increased quorum sensing, aggregation, adhesion, and persistence. E. coli exhibited time-dependent induction of papG, draA, papC, and fimH, which encode P-fimbrial, Dr-family, and type 1 fimbrial adhesins, consistent with enhanced biofilm formation. Collectively, these results extend recent metabolomics studies that have demonstrated microbial reprogramming of breast cancer cells [13]. They show that the interaction is bidirectional, with luminal A breast cancer cells, via their secretome, reciprocally enhancing bacterial adhesion and virulence-associated genetic programs. Building on Fu et al.’s seminal work, which demonstrated that tumor-resident microbiota promotes metastatic survival and colonization [3], our findings provide mechanistic evidence that tumor secretomes can locally condition extracellular bacteria to exhibit more virulent and adaptive phenotypes. Finally, the secretome model introduced in this study provides a versatile platform for mechanistic and translational work on tumor–microbiome interactions in breast cancer. By offering a controlled in vitro system to assess how breast-cancer-derived conditioned media influence P. aeruginosa, E. faecalis, and E. coli, this model can be extended to examine subtype-specific microbial behaviors, host signaling effects, and microbiome-targeted interventions. Extending this approach to additional breast cancer subtypes, patient-derived organoids, or immune-inclusive co-culture systems may uncover subtype-specific microbial virulence signatures and guide microbiome-informed therapeutic strategies. Together, these findings support a model in which luminal A breast cancer cell-derived secretomes actively and selectively reprogram the phenotypes of resident bacteria. This reinforces the concept that tumors and their associated microbiota form an integrated, dynamic ecosystem, in which reciprocal interactions can influence microbial virulence, biofilm formation, and potentially disease progression, underscoring the clinical relevance of the tumor–microbiome interface.

4. Materials and Methods

4.1. Breast Cell Line Culture and Conditioned Media Preparation

MCF-7 (luminal A breast cancer cell line) and MCF-10A (normal breast epithelial cells) cells were purchased from ATCC (Manassas, VA, USA). Cells were regularly screened for mycoplasma contamination using MycoAlert Mycoplasma Detection Kits (Invitrogen, Paisley, UK). MCF-7 cells were maintained in DMEM/F12 from Gibco (Thermo Fisher Scientific, Waltham, MA, USA), supplemented with 10% FBS, 2 mM L-glutamine, and 1% antimycotic–antibiotic reagent. MCF-10A cells were grown in DMEM/F12 supplemented with 20 ng/mL EGF, 100 ng/mL cholera toxin, 10 μg/mL insulin, 500 ng/mL hydrocortisone, 5% horse serum, and 1% antimycotic-antibiotic. All cultures were incubated at 37 °C in a CO₂ incubator.

4.2. Bacterial Culture and Preservation

Pseudomonas aeruginosa (ATCC 27853), Enterococcus faecalis (ATCC 29212), and Escherichia coli (ATCC 25922) glycerol stocks stored at −80 °C were thawed and streaked onto lysogeny broth (LB) agar plates. A single colony of each was inoculated into 100 mL of LB and cultured overnight at 37 °C with orbital shaking (180 rpm). The overnight cultures were adjusted to an optical density (OD₆₀₀) of 0.1 to standardize cell concentration before experimental inoculation. For long-term storage, 600 μL of overnight suspension was mixed with 400 μL of 40% sterile glycerol and stored at −80 °C.

4.3. Bacterial Culture with Conditioned Media or Control Media

For experiments, standardized overnight cultures (OD₆₀₀ = 0.6–0.8) were diluted as necessary and inoculated into 100 mL of nutrient broth. Cultures were supplemented with varying concentrations (5%, 10%, or 15%) of cell-free conditioned media derived from MCF-7 (CM-7), MCF-10A (CM-10A), or their respective cell-free media controls (CFM-7 or CFM-10A), as described for each downstream assay. For collection of cell-free conditioned media, near-confluent cultures (~80%) were switched to medium containing 0.5% serum for 24 h. The supernatants (conditioned media) were then collected, centrifuged at 2000× g for 10 min to remove cellular debris. For control media preparation, the same media formulations used for MCF-7 (CFM-7) and MCF-10A (CFM-10A) were incubated under identical conditions but without cells and collected after 24 h, following the same procedure as the conditioned media. The resulting supernatants were either used instantly or stored at −80 °C for subsequent experiments [14].

4.4. Scanning Electron Microscopy (SEM) of Bacteria

Morphological changes in P. aeruginosa and E. faecalis were assessed using a Scanning Electron Microscope (SEM) at the Central Research Laboratory at King Saud University. Following exposure to CM-7 or CM-10A or their respective cell-free media controls (CFM-7 or CM-10A), bacterial pellets were fixed in 2.5% glutaraldehyde for 2 h at 4 °C, washed, dehydrated through a graded ethanol series, and dried. The samples were then sputter-coated with gold and visualized at 25,000× magnification [15].

4.5. Disc Diffusion for Antibiotic Sensitivity Test

Antimicrobial susceptibility of all strains was determined by standardized disc diffusion on Müller–Hinton Agar (Scharlab S.L., Barcelona, Spain) using log-phase cultures pre-exposed to 10% conditioned or the respective control media. Inocula were standardized to 0.5 McFarland, spread onto agar plates, and tested using antibiotic discs: penicillin (10 µg), meropenem (10 µg), imipenem (10 µg), gentamicin (10 µg), vancomycin (30 µg), and chloramphenicol (30 µg) (Atlas Medical, Berlin, Germany). After 24 h of incubation at 37 °C, inhibition zone diameters were measured and interpreted according to CLSI standards [16].

4.6. Quantitative Biofilm Formation Assays

Biofilm formation was quantified using the crystal violet assay in 96-well flat-bottom microplates as described [17]. Overnight bacterial cultures were diluted and dispensed into wells (200 μL/well) containing either 10% conditioned or the respective control media, with each condition tested in triplicate. After 24 h at 37 °C, wells were washed three times with Phosphate-Buffered Saline (PBS) to remove detached cells and reduce background staining. The wells were stained with 0.1% crystal violet (125 μL for 10 min), rinsed, and air-dried. Dye was solubilized with 30% v/v ethanol for 15 min, then absorbance was measured at 630 nm using a microplate reader.

4.7. Genomic DNA Extraction

Genomic DNA was extracted from bacterial pellets using the PureLink™ Genomic DNA Mini Kit (Thermo Fisher Scientific, Waltham, MA, USA), according to the manufacturer’s instructions [18]. DNA concentration and purity were measured using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). The extracted genomic DNA was stored at −20 °C for future use.

4.8. Quantitative PCR (qPCR) Analysis

Virulence gene abundance was quantified using SYBR™ Green-based real-time quantitative PCR (qPCR) from genomic DNA (Applied Biosystems, Thermo Fisher Scientific, Waltham, MA, USA) in 50 μL reactions containing 200 nM gene-specific primers (

Table 1. Primer sequences of the genes related to P. aeruginosa virulence factors.

Gene	Forward Primer (5′–3′)	Reverse Primer (5′–3′)	Size (bp)	Reference
pilB	ATG AAC GAC AGC ATC CAA CT	GGG TGT TGA CGC GAA AGT CGA T	82	[20]
lasB	GGA ATG AAC GAG GCG TTC TC	GGT CCA GTA GTA GCG GTT GG	300
exoS	CTT GAA GGG ACT CGA CAA GG	TTC AGG TCC GCG TAG TGA AT	504
algD	ATG CGA ATC AGC ATC TTT GGT	CTA CCA GCA GAT GCC CTC GGC	1310
plcH	GAA GCC ATG GGC TAC TTC AA	AGA GTG ACG AGG AGC GGTAG	307
exoU	GGG AAT ACT TTC CGG GAA GTT	CGA TCT CGC TGC TAA TGT GTT	428
16S rRNA	CCGAGTGCTTGCACTCAATTGG	CTCTTATGCCATGCGGCATAAAC	137	[19]

,

Table 2. Primer sequences of the genes related to E. faecalis virulence factors.

Gene	Forward Primer (5′–3′)	Reverse Primer (5′–3′)	Size (bp)	Reference
fsrC	GCTTATTTGGAAGAACAACGTATCAA	CGAAACATCGCTAGCTCTTCGT	100	[19]
esp	GGAACGCCTTGGTATGCTAAC	GCCACTTTATCAGCCTGA ACC	94
efa	TGGGACAGACCCTCACGAATA	CGCCTGTTTCTAAGTTCAAGCC	100
ace	GGAATGACCGAGAACGATGGC	GCTTGATGTTGGCCTGCTTCCG	616	[21]
asa1	GCACGCTATTACGAACTATGA	TAAGAAAGAACATCACCACGA	375	[22]
16S rRNA	CCGAGTGCTTGCACTCAATTGG	CTCTTATGCCATGCGGCATAAAC	137	[19]

and

Table 3. Primer sequences of the genes related to E. coli virulence factors.

Gene	Forward Primer (5′–3′)	Reverse Primer (5′–3′)	Size (bp)	Reference
fimH	TGCAGAACGGATAAGCCGTGG	GCAGTCACCTGCCCTCCGGTA	506	[23]
papC	GACGGCTGTACTGCAGGGTGTGGCG	ATATCCTTTCTGCAGGGATGCAATA	328
papG	TCGTGCTCAGGTCCGGAATTT	TGGCATCCCCCAACATTATCG	461
draA	GCCAACTGACGGACGCAGCAC	CCCCAGCTCCCGACATCGTTTTT	229
16S rRNA	CCGAGTGCTTGCACTCAATTGG	CTCTTATGCCATGCGGCATAAAC	137	[19]

), 25 μL SYBR Green PCR Master Mix (ABI), and 5 μL of template DNA. The PCR cyclic conditions were 95 °C for 10 min, followed by 50 cycles of 95 °C for 15 s and 60 °C for 1 min. Each sample was run in triplicate, with 16S rRNA serving as the internal control. Relative gene abundance was analyzed using the 2^−ΔΔCt method [19].

4.9. Statistical Analysis

Data were analyzed using GraphPad Prism v7.0 (GraphPad Software, San Diego, CA, USA). Results are presented as mean ± standard deviation (SD) from three independent experiments. Unpaired, two-tailed Student’s t-tests were used for pairwise comparisons between CM-7 and CM-10A conditions at corresponding concentrations. A p-value < 0.05 was considered statistically significant.