S. mutans UA159, C. albicans SC5314, and L. plantarum ATCC 14917 were purchased from ATCC and recovered from frozen stock and subsequently inoculated onto the following media: blood agar (TSA with sheep blood, Thermo Scientific™, Waltham, MA, USA, catalog number R01202), YPD agar (BD Difco™, San Jose, CA, USA, catalog number 242720), and MRS agar (BD Difco™, catalog number 288210). After incubation for 48 hours, S. mutans, C. albicans, and L. plantarum were transferred to respective growth media: TSBYE broth (3% Tryptic Soy, 0.5% Yeast Extract Broth, BD Bacto™ 286220 and Gibco™ 212750) with 1% glucose, YPD broth (BD Difco™, 242820), and MRS broth (BD Difco™, 288130). The cultures were incubated overnight. The following morning, 0.5 ml of each overnight culture was added to fresh broth and incubated for 3–4 hours until the optical density (OD) reached the target values: 1.0 for S. mutans, 0.8 for C. albicans and 2.2 for L. plantarum). The morning cultures were then serially diluted to prepare starting concentrations for the mucosal models described below.

The starting concentrations of S. mutans (10⁵ CFU/mL) and C. albicans (10³ CFU/mL) were selected to simulate a clinical setting with a high risk of caries. The concentrations of L. plantarum (10⁷ CFU/mL) was chosen based on previous studies that demonstrated its inhibitory effects on the growth of both S. mutans and C. albicans. Dual- and multi-species conditions of S. mutans, C. albicans, and L. plantarum were cultivated in 10 mL of TSBYE broth supplemented with either 1% GOS (BOS Science, New York, NY, USA) or 1% glucose for 20 h (5% CO₂, 37°C). After incubation, the supernatant was collected by centrifugation and stored at -80 °C for untargeted metabolomics analysis.

The TR-146 epithelial cell line was obtained from Millipore Sigma. TR-146 cells (100,000 cells per insert, passages 4 and 10) were seeded onto transwell culture plate inserts (VWR, PET membrane, 3 μm pore size) with medium in both chambers. Cultures were incubated at 37 °C with 5% CO₂. The mucosal model was ready for microorganism inoculation after reaching confluence in 14 days, with a transepithelial electrical resistance of 50 Ohms×cm². Dual- and multi-species conditions of S. mutans (10⁵ CFU/mL), C. albicans (10³ CFU/mL), and L. plantarum (10⁷ CFU/mL) were cultivated in DMEM/F12 medium with 1% glucose, 1% sucrose or 1% GOS for 12–24 hours (5% CO₂, 37 °C).

TR-146 cells grown on Transwell inserts were inoculated with dual- and multi-species suspensions of S. mutans, C. albicans, and L. plantarum for 1 hour. The cells were washed three times with PBS to remove non-adherent microbes. Adherent microbes were detached by scraping with a sterile spatula, suspended in 1 mL of sterile 0.9% sodium chloride solution, and transferred to an Eppendorf tube. The suspensions were serially diluted and plated onto blood agar and YPD agar plates to determine viable counts of S. mutans and C. albicans, respectively.

Transwell inserts containing TR-146 cells were inoculated in parallel experiments with 10³ CFU of C. albicans and 10⁵ CFU of S. mutans, then incubated at 37 °C for 24 hours. After incubation, the culture medium from the lower chamber was collected, serially diluted, and plated onto selective agar as described above to determine viable cell counts.

The barrier function of the TR-146 mucosal model was assessed 24 hours post-infection. TEER measurements were conducted using an Endohm chamber linked to an EVOM epithelial voltometer (World Precision Instruments, Sarasota County, FL, USA). Inserts were placed in the Endohm chamber, and an electrode cap was positioned on top to obtain the TEER reading. Relative TEER in Ω × cm² was calculated by subtracting the background resistance (from an insert with only media) from the average TEER reading per well and multiplying the result by the insert’s surface area (1.12 cm²).

At 18 hours, 1 mL of culture suspensions was collected from the insert of the mucosal model for RNA extraction. Complementary DNA (cDNA) was synthesized from 0.2 µg of purified RNA using the Bio-Rad iScript cDNA synthesis kit (Bio-Rad Laboratories, Inc., Hercules, CA, USA). Amplification of cDNA and negative controls was performed with SYBR Green Master Mix and a QuantStudio Real-Time PCR System (Thermo Fisher Scientific, Wilmington, DE, USA). Each 20 µL reaction contained cDNA, 10 µM of each primer, and a 2× SYBR Green mix (which includes SYBR Green and Taq DNA Polymerase). The internal reference genes used were gyrA for S. mutans and ACT1 for C. albicans. Gene expression was quantified using the comparative 2−ΔΔCT method. The sequences of the primers are detailed in Supplementary Table S1 .

The culture media were removed from the transwells and immediately replaced with EM fixative solution containing 2.5% glutaraldehyde and 4% paraformaldehyde in buffer. Samples were fixed at room temperature for 1 hour, rinsed, and post-fixed in 1% osmium tetroxide. Samples were dehydrated through a graded ethanol series, embedded in epoxy resin, and polymerized. Semi-thin (1 µm) toluidine blue–stained sections were used to identify regions of interest, after which ultrathin sections (~70 nm) were cut with an ultramicrotome, and stained with uranyl acetate and lead citrate. Sections were imaged using a transmission electron microscope.

After 24 hours, the culture suspension was collected from the upper chamber of the mucosal model. The suspension was then centrifuged at 5,000 × g for 10 minutes to obtain the supernatant samples. These samples were analyzed using a multiplex assay to measure various cytokines and inflammatory mediators. The assay was performed according to the manufacturer’s instructions for the MILLIPLEX^® Cytokine/Chemokine Magnetic Bead Panel. The analytes measured included Fractalkine, GM-CSF, IFN-γ, IL-1a, IL-1B, IL-1RA, IL-6, IL-8, IL-18, MIP-1a, RANTES, TNFα, ENA-78 and MIP-3a. Results were obtained using a Luminex^® 200™ instrument (Luminex, Austin, TX, USA) and reported based on standard curve values.

Transwell inserts containing dual- and multi-species mucosal models were cultured in a medium supplemented with 1 μM Alexa Fluor 647-labeled dextran conjugate (Invitrogen Corp, Carlsbad, CA) for 12 hours to visualize exopolysaccharides. After this incubation, the inserts were fixed in 4% paraformaldehyde, and Calcofluor White was used to stain the chitin in the cell walls of C. albicans. The membrane was then removed and mounted onto slides using FluorSave reagent. Imaging was conducted using a Leica SP5-AOBS confocal laser scanning microscope (CLSM) attached to a Leica DM I6000 inverted epifluorescence microscope. The acquired images were processed with Imaris v9.5 software (Bitplane AG, Zurich, Switzerland).

Thermo Vanquish HPLC/Orbitrap ID-X MS was used for metabolimics analysis. The samples were thawed on ice and 2 x 100 µL was aliquoted (1 for reversed-phase C18 and 1 for HILIC chromatography) into Eppendorf tubes and extracted with 400 µL of ice-cold methanol. The samples were then vortexed and centrifuged at 18,000 x g at 4 °C for 5 min, A 400 µL aliquot of each supernatant was dried in a 96-well plate under nitrogen at 45 °C and reconstituted in HPLC mobile phases. An aliquot of homogenate was taken to prpare quality control (QC) samples, which were processed in the same manner. The samples were analyzed in 4 separate LC/MS experiments on the Thermo Scientific UHPLC/Orbitrap ID-X mass spectrometer, scanned from m/z 70 to 1000 at a resolution of 120,000. Samples were first run using reversed-phase C18 chromatography (retention of medium to nonpolar metabolites) with electrospray ionization in the positive and negative ionization modes separately on an Orbitrap ID-X mass spectrometer. A separate sample was then analyzed using HILIC chromatography (retention of polar metabolites) also in both ionization modes. Data from the raw outputs were processed using Thermo Scientific’s Compound Discoverer.Metabolomic data processing, analysis, and interpretation using MetaboAnalyst 6.0.

All analyses were performed using SPSS (V24.0). To compare the abundance of S. mutans, C. albicans, and L. plantarum in mucosal models, the CFU/mL values were first converted into natural log values before analysis. Normality tests (Shapiro–Wilk Test) were conducted for converted CFU/mL value, 2^−ΔΔCT and the concentrations of immune markers (concentrations of immune markers converted to natural log value). For normally distributed data, differences were assessed using t-tests for two independent groups and one-way analysis of variance (ANOVA) for multiple group comparisons followed by post hoc Tukey’s test. When data were not normally distributed, the Mann–Whitney U test was used to compare the results of the two groups. For LC-MS/MS, Thermo Scientific’s Compound Discoverer was used to extract metabolites, normalize area counts to the pooled QC samples run throughout the LC/MS analysis, identify metabolites via a curated database search, and generate principal component analysis (PCA) plots, fold changes between comparison groups with adjusted p-values. Statistical significance was set at p < 0.05. Sample sizes for each experiment are detailed in the figure legends.

The schematic design of the mucosal model and microbial inoculation ( Figure 1A ). Compared to the single-species model, co-inoculation with S. mutans and C. albicans significantly increased the adhesion of each species to oral epithelial cells (TR146) after 1-hour incubation in all sugar condition ( Figure 1B ). Notably, the addition of L. plantarum to the S. mutans and C. albicans mucosal model significantly inhibited the adhesion of both species in all sugar-conditions ( Figure 1C ).

In the schematic model of microbial transmigration through the mucosal barrier, mucosal integrity is reflected by the trans-epithelial electrical resistance (TEER) value, while microbial transmigration is indicated by the viable cell counts in the lower chamber ( Figure 2A ). Compared to the dual-species condition, the addition of L. plantarum increased the TEER value across all sugar conditions, demonstrating its protective effect on mucosal integrity ( Figure 2B ). By numerating the colonies of S. mutans that transmigrated into the lower chamber after 24-hour incubation, we found that L. plantarum significantly inhibited the transmigration of S. mutans, regardless of sugar conditions ( Figure 2C ). By measuring the viable cell counts in both the upper and lower chambers, we observed that L. plantarum significantly reduced the viability of S. mutans in both chamber ( Figure 2D ).

The expression of S. mutans virulence genes eno and gtfC were significantly downregulated with added L. plantarum in 1% sucrose, 1% glucose, or 1% GOS condtions. While, AptD in the 1% GOS, gtfB in control and 1% GOS conditions, gtfD in control and 1% GOS condition, lacC across all conditions, and lacG in control and 1% glucose conditions were upregulated with the addition of L. plantarum. This upregulation might be due to feedback regulation by the surviving S. mutans ( Supplementary Figure S1 ).

The migration of C. albicans was not significantly inhibited by L. plantarum under control and 1% glucose conditions, and it increased under 1% sucrose and 1% GOS conditions ( Figure 3A ). The expression of C. albicans virulence genes (HWP1, ECE1, CHT2, ERG4, and SOD3) was downregulated at 18 hours with the addition of L. plantarum ( Figures 3B–F ). Additionally, C. albicans hyphae formation was significantly reduced under the 1% GOS condition ( Figure 3G ).

Furthermore, we evaluated the regulatory effects of the prebiotic GOS on the transmigration of S. mutans and C. albicans. For S. mutans, there was no significant difference between 1% GOS and 1% glucose in the dual-species condition, and 1% GOS promoted more S. mutans transmigration than 1% sucrose ( Supplementary Figure S2A , left). In the multi-species condition with L. plantarum, the transmigration of S. mutans in the GOS group was significantly lower than in the glucose group and showed a decreasing trend compared to the sucrose group ( Supplementary Figure S2A , right). For C. albicans, a downward trend was observed in the 1% GOS group compared with the sucrose group, regardless of whether the condition was dual-species or multi-species ( Supplementary Figure S2B ).

Transmission electron microscopy (TEM) was used to photograph mucosal models under different conditions. In the dual-species model in 1% sucrose condition, S. mutans and C. albicans damaged the mucosal structure, expanded cell spaces, and invaded cell interiors, leading to cell necrosis ( Figure 4A-1 ). In the GOS-containing dual-species condition, barrier damage was slightly reduced, and C. albicans invasion was inhibited ( Figure 4A-2 ). In the multi-species model with L. plantarum, although C. albicans still invaded cell interiors in the sucrose-containing condition, the mucosa was significantly thickened, with better integrity than in the dual-species ( Figure 4A-3 ). Moreover, in the 1% GOS multi-species condition, the invasion of S. mutans and C. albicans was notably reduced, and the mucosal barrier was more complete ( Figure 4A-4 ), suggesting that L. plantarum combined with the prebiotic GOS could better maintain mucosal barrier function. Morphological changes of C. albicans observed under electron microscopy were consistent with optical microscopy results. Sucrose contributes to the maintenance of virulent hyphal forms ( Figures 4B-1, 3 ), while GOS promotes the transformation of C. albicans into yeast forms with lower virulence ( Figures 4B-2, 4 ). This further suggests that GOS has an inhibitory effect on the virulence of C. albicans.

When comparing intercellular connections across different models, we found that in the control group, epithelial cells displayed tight junction (red arrows) and desmosomes (yellow arrows), maintaining cell connection and communication ( Figure 4C-1 ). In the dual-species inoculation model, the barrier structure in the sucrose culture was severely damaged, with larger cell gaps, facilitating the invasion and transmigration of pathogenic bacteria ( Figure 4C-2 ). In 1% GOS conditions, tight junctions remained, but desmosomes were absent, and cell gaps were still large ( Figure 4C-3 ). While, the addition of L. plantarum maintained the intercellular junction structure. Both tight junctions and desmosomes were present under sucrose conditions ( Figure 4C-4 ), and more were observed under GOS conditions ( Figure 4C-5 ), indicating enhanced intercellular connections and improved barrier function. This finding was further supported by cellular immunofluorescence, which showed that occludin and E-cadherin were upregulated in the multi-species models. These proteins are essential for regulating intercellular connections and barrier function in epithelial tissues, helping to maintain tissue integrity and homeostasis ( Supplementary Figure S3 ).

We also observed more glycogen accumulation and lipid droplet formation in epithelial cells in the dual-species inoculation model ( Figures 4D-1, 2 ). In the multi-species inoculation model, the reduction of lipid droplets and glycogen suggests a weakened inflammatory response, indicating that L. plantarum may have anti-inflammatory effects ( Figures 4D-3, 4 ). To verify these effects, we examined the levels of immune markers in culture medium using Luminex^® Multiplex Assays. The results showed that in 1% sucrose condition, L. plantarum significantly downregulated pro-inflammatory factors GM-CSF, IFNγ, IL-6, IL-8, IL-18, MIP-1a, TNFα, and ENA-78 ( Figure 4E , left). In 1% GOS condition, L. plantarum inhibited the release of Fractalkine, GM-CSF, IL-8 and MIP-3a ( Figure 4E , right). Additionally, L. plantarum downregulated the levels of ten pro-inflammatory markers, including Fractalkine, GM-CSF, IFNγ, IL1-RA, IL-8, IL-18, MIP-1a, RANTES, ENA-78 and MIP-3a under glucose conditions ( Supplementary Figure S4A ). In the sugar-free negative control group, the levels of three pro-inflammatory factors—Fractalkine, GM-CSF and MIP-3a—were also found to be downregulated ( Supplementary Figure S4B ).

Confocal microscopy results demonstrated that the combination of L. plantarum and GOS significantly inhibited both EPS accumulation and hyphae formation ( Figure 5A ). In the dual-species model, 1% GOS reduced C. albicans hyphae compared to the 1% sucrose condition ( Figure 5B-3 ). In the multi-species model, C. albicans predominantly remained in yeast form under 1% GOS conditions ( Figure 5B-4 ). Moreover, compared to the dual-species model under 1% sucrose conditions ( Figure 5B-5 ), both L. plantarum addition and the 1% GOS condition significantly reduced EPS production ( Figures 5B-6, 7 ). Notably, L. plantarum under 1% GOS conditions exhibited the most substantial inhibitory effect on both EPS accumulation and C. albicans hyphae formation ( Figure 5B-12 ).

The addition of L. plantarum significantly inhibited acid production by S. mutans-C. albicans under 1% GOS conditions. The mean pH of the supernatant in both the dual- and multi-species models was significantly lower under glucose (4.73 vs 4.80, p = 0.0002) and sucrose conditions (4.61 vs 4.33, p < 0.0001) compared to the control group (5.76 vs 5.67). However, under GOS conditions, the pH in both models remained around 5.5 ( Figure 5C ). Notably, in the GOS multi-species group, the pH was higher than in the dual-species group (5.71 vs 5.28, p = 0.0036), approaching the levels observed in the control group ( Figure 5D ).

The supernatant of a planktonic model was collected for LC-MS/MS untargeted metabolomics analysis to evaluate the effects of L. plantarum on the metabolism of S. mutans and C. albicans ( Figure 6A ). The clustering of samples in PCA plots indicated distinct global metabolomic profiles between groups ( Figure 6B ). We found that 371 metabolites were significantly altered with the addition of L. plantarum, with 256 down-regulated metabolites and 115 up-regulated metabolites, with the top ten most significantly up-regulated and down-regulated metabolites listed ( Figure 6C ). A clustering heatmap revealed clear differences in altered metabolite profiles between dual-species and multi-species planktonic models ( Figure 6D ).

Pathway analysis of the significantly down-regulated metabolites (p-value < 0.05, log2 (Fold Change) < -1) was conducted based on S. mutans and C. albicans pathway libraries. L. plantarum significantly down-regulates the metabolic pathways of S. mutans and C. albicans that are crucial for energy and biomolecule production. For S. mutans, 19 metabolic pathways were identified, with purine metabolism being the most down-regulated ( Figure 6E ). These pathways were primarily enriched in carbohydrate metabolism, amino acid metabolism, and the metabolism of cofactors and vitamins ( Figure 6F ). For C. albicans, 22 metabolic pathways were identified, with purine metabolism and the citrate cycle being the most significantly down-regulated ( Figure 6G ). Similar enrichments were observed in C. albicans ( Figure 6H ).

We also examined the metabolic regulatory effects of GOS on L. plantarum, S. mutans and C. albicans in multispecies planktonic model. Volcano plots indicated that under GOS conditions, 275 metabolites were down-regulated, and 211 were up-regulated compared to glucose conditions ( Figure 7A ). Heatmap results showed significant differences in metabolite profiles between GOS and glucose conditions in a multi-species planktonic model ( Figure 7B ). Pathway analysis of the up-regulated metabolites was performed using the L. plantarum pathway library. Twenty metabolic pathways were identified, with significant up-regulation in purine metabolism, alanine, aspartate and glutamate metabolism, pantothenate and CoA biosynthesis, and arginine biosynthesis ( Figure 7C ). These pathways were mainly enriched in carbohydrate metabolism, amino acid metabolism, and the metabolism of cofactors and vitamins ( Figure 7D ).

Pathway analysis of the down-regulated metabolites was performed using S. mutans and C. albicans pathway libraries. For S. mutans, 19 metabolic pathways were identified, with pyrimidine metabolism, cysteine and methionine metabolism, and sulfur metabolism being the most significantly down-regulated ( Figure 7E ). These pathways were mainly enriched in amino acid metabolism, carbohydrate metabolism, and the metabolism of cofactors and vitamins ( Figure 7F ). For C. albicans, 30 metabolic pathways were identified, with significant down-regulation observed in pyrimidine metabolism and taurine and hypotaurine metabolism ( Figure 7G ). Here, the pathways related to amino acid metabolism, carbohydrate metabolism, metabolism of other amino acids, metabolism of cofactors and vitamins, energy metabolism, and cofactors and vitamins metabolism were frequently enriched ( Figure 7H ).

The volcano plot showed that 371 metabolites changed significantly with the addition of L. plantarum under GOS condition, with 344 metabolites down-regulated and 167 up-regulated ( Figure 8A ). The heatmap revealed notable differences in altered metabolite profiles between dual-species (1% glucose) and multi-species (1% GOS) conditions in planktonic models ( Figure 8B ).

For down-regulated metabolites, pathway analysis was conducted using the S. mutans and C. albicans pathway libraries. For S. mutans, 25 metabolic pathways were identified, with purine metabolism being the most down-regulated ( Figure 8C ). Similar to L. plantarum under glucose conditions, these pathways were mainly enriched in carbohydrate metabolism, amino acid metabolism, and the metabolism of cofactors and vitamins. However, a notable difference was the presence of pathways related to xenobiotic biodegradation and metabolism. Microorganisms, including bacteria and fungi, play a crucial role in the biodegradation of xenobiotics, utilizing specific enzymes to metabolize these compounds ( Figure 8D ).

For C. albicans, 36 metabolic pathways were identified, with significant down-regulation in alanine, aspartate and glutamate metabolism, cysteine and methionine metabolism, glycine, serine and threonine metabolism, the citrate cycle, and taurine and hypotaurine metabolism ( Figure 8E ). Here, pathways related to amino acid metabolism, carbohydrate metabolism, metabolism of other amino acids, metabolism of cofactors and vitamins, and energy metabolism were frequently enriched ( Figure 8F ).

This study demonstrated inhibitory effects of L. plantarum and the prebiotic GOS on S. mutans and C. albicans in mucosal models. Our findings indicate that under GOS conditions, L. plantarum induces anti-inflammatory effects in mucosal infection models and reshapes the metabolic landscape of planktonic models, leading to reduced viability and virulence of both S. mutans and C. albicans, thereby maintaining mucosal integrity.

The interaction between S. mutans and C. albicans in saliva and biofilm environments plays a critical role in ECC and other oral mucosal infections. S. mutans synthesizes EPS, promoting the formation of dense biofilms. Within these biofilms, S. mutans ferments sugars, producing lactic acid as a byproduct. EPS further enhances the retention of sugar substrates and acid, leading to a localized pH reduction. The risk of caries increases when saliva pH drops to 5.5 or lower. C. albicans is a polymorphic species capable of transforming between single-celled yeast and multicellular hyphae to adapt to environmental changes (Liang et al., 2024; Moffa et al., 2015). Additionally, the expression of its virulence genes varies under specific environmental stress, influencing its pathogenicity (Verma-Gaur and Traven, 2016; Muñoz et al., 2018). In this study, we found that L. plantarum significantly reduced the adherence of S. mutans and C. albicans to the mucosal barrier, thereby inhibiting EPS accumulation. Moreover, L. plantarum directly inhibits the viability and transmigration of S. mutans. It also reduces the virulence and pathogenicity C. albicans by suppressing hyphae formation and downregulating virulence gene expression. Furthermore, the GOS condition enhanced this inhibitory effect more effectively than glucose and sucrose conditions.

The oral mucosa is crucial for barrier protection by maintaining thickness, integrity, cellular connectivity, and providing immune defense against pathogen invasion (Muñoz et al., 2018; Ptasiewicz et al., 2022; Gaffen and Moutsopoulos, 2020). In this study, we identified that GOS enhanced the protective effects of L. plantarum on mucosal integrity. In the group inoculated with L. plantarum under GOS conditions, mucosal thickness and intercellular connections increased, ensuring normal barrier function. These findings illustrate the potential of L. plantarum, especially in conjunction with GOS, to modulate microbial virulence and maintain mucosal barrier integrity, indicating promising therapeutic avenues for oral health interventions.

Untargeted metabolomics is a valuable tool for discovering products of cellular biochemical reactions in various diseases (Ramos et al., 2022; Chen et al., 2022; Crestani et al., 2020; Yang et al., 2022; Niziol et al., 2023). Our study showed that L. plantarum can inhibit pathogenic bacteria by regulating the metabolic microenvironment. We utilized LC-MS/MS to identify thousands of metabolites. Among the ten most significantly up-regulated metabolites by L. plantarum, methyl (9E)-9-octadecenoate, eugenyl glucoside, neotame and kresoxim-methyl altered the diversity of the gut microbiome and likely exhibited antimicrobial activities (Chi et al., 2018; Zhao et al., 2010; Rozman et al., 2017; Filippou et al., 2016). Conversely, the most down-regulated metabolites, including xanthine, CXA-10, citric acid, arabinosylhypoxanthine, inosine, and riboprine, serve as nutrient sources that promote microbial proliferation (Martin-Gallausiaux et al., 2021; Trefely et al., 2020). For GOS, the up-regulated metabolites, such as cxa-10, proxyphylline, and N-(4-Amino-1-carboxybutyl)glutamic acid have bactericidal properties (Moya et al., 2010; Ajayeoba et al., 2019; Fazly Bazzaz et al., 2016). Meanwhile, down-regulated metabolites, including ureidosuccinic acid, aceglutamide, and 4-(L-Alanin-3-yl)-2-hydroxy-cis, cis-muconate 6-semialdehyde, can enhance bacterial and fungal growth through protein synthesis and other metabolic pathways (Zeng et al., 2024; Zhou et al., 2023; Martino et al., 2018; Cai et al., 2007). Among the top ten metabolites up-regulated by L. plantarum and GOS, N(3)-(4-Methoxyfumaroyl)-2,3-diaminopropionic acid, picolinic acid and pyrogallol are recognized for their antimicrobial properties (Otite et al., 2024; Tian et al., 2023). In contrast, the top down-regulated metabolites included xanthosine and inosine, both nucleosides that serve as nutrient sources capable of stimulating microbial growth (McKeague et al., 2016; Li et al., 2021). Furthermore, our analysis of these regulated pathways elucidates the metabolic interactions among L. plantarum, S. mutans, and C. albicans, indicating that L. plantarum significantly alters the metabolic landscape of these pathogens, especially under GOS conditions. The down-regulation of critical nutrient metabolic pathways in S. mutans and C. albicans suggests a competitive suppression mechanism initiated by L. plantarum, potentially impairing their energy production and virulence. Conversely, the up-regulation of these nutrient or energy metabolic pathways in L. plantarum emphasizes its adaptability and resilience, enhancing its survival and functionality within the oral cavity.

Immunometabolism is a multidisciplinary area of immunology research that intricately links metabolism and immunology. It has emerged as a central mechanism in adaptive and innate immune regulation (Makowski et al., 2020). Glycogen and lipid droplets serve as energy reserves in metabolism and also have immunomodulatory functions, increasing during infection and inflammation to regulate the inflammatory response (Marschallinger et al., 2020; Sadiku et al., 2021). Transmission electron microscopy revealed that L. plantarum reduces the accumulation of lipid droplets and glycogen, which are indicators of an enhanced cell autoinflammatory response. This suggests that L. plantarum may reduce the autoimmunity of mucosal cells. Pro-inflammatory markers play key roles in immune responses. Luminex results confirmed a significant reduction in immune marker release in the L. plantarum added group. Generally, these markers orchestrate inflammatory and immune responses, with TNFα stimulating cytokines like IL-6 and chemokines such as IL-8 and MIP-1a (Lee and Moon, 2023; Abbott et al., 2021; Beringer and Miossec, 2019). IL-6 enhances acute-phase protein production, while IL-18, in synergy with IL-12, promotes IFNγ production to strengthen Th1 responses (Chen et al., 2021; Ngwa et al., 2022; Yasuda et al., 2019; Wawrocki et al., 2016). GM-CSF facilitates immune cell maturation, and fractalkine recruits immune cells, amplifying cytokine effects (Subbotin, 2014; Yang et al., 2024; Kumar et al., 2022). The observed reduction in these pro-inflammatory markers suggests that L. plantarum may help regulate inflammation and maintain normal cell function.