Lactobacillus brevis Cell-Free Supernatant Recalibrates TLR-Mediated Inflammatory Signaling While Preserving Immune Competence in HT-29 Intestinal Epithelial Cells

Lactobacillus brevis Cell-Free Supernatant Recalibrates TLR-Mediated Inflammatory Signaling While Preserving Immune Competence in HT-29 Intestinal Epithelial Cells | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Lactobacillus brevis Cell-Free Supernatant Recalibrates TLR-Mediated Inflammatory Signaling While Preserving Immune Competence in HT-29 Intestinal Epithelial Cells Alireza Moghanlou, Shima Rasouli, Sheyda Asadi, Sarvenaz Falsafi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9542241/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background Dysregulated Toll-like receptor (TLR) signaling in intestinal epithelial cells contributes to persistent mucosal inflammation in inflammatory bowel disease (IBD). Although Lactobacillus brevis has demonstrated anti-inflammatory potential, the pathway-level mechanisms by which its secreted metabolites influence epithelial innate immune signaling remain insufficiently characterized. This study investigated L. brevis cell-free supernatant (CFS) TLR-mediated inflammatory signaling modulation while preserving epithelial immune competence. Methods HT-29 human intestinal epithelial cells were treated with 50% L. brevis CFS following viability assessment using MTT assay. Transcriptional profiling of 84 key genes involved in the TLR signaling pathway was performed using the RT² Profiler™ PCR Array. Differential gene expression was analyzed using the ΔΔCt method, and pathway-level mapping was conducted to evaluate coordinated modulation across MyD88- and TRIF-dependent branches. Results Treatment with L. brevis CFS significantly enhanced HT-29 cell viability and induced a structured transcriptional reprogramming of the TLR signaling network. Core components of the MyD88-dependent pro-inflammatory axis—including TLR2 , TLR4 , MYD88 , IRAK1/4 , MAP3K7 , NFKB1 , and downstream cytokines ( IL1A, IL1B, IL6, IL12A, CCL2 )—were significantly downregulated. Concurrent attenuation of TRIF-dependent signaling was observed through modulation of TLR3 , TICAM1 , TBK1 , IRF3 , and CXCL10 . Importantly, selective preservation of immune-associated mediators and absence of exaggerated IL-10 induction indicated maintained basal immune competence rather than global immunosuppression. Conclusions L. brevis CFS induces multi-tier recalibration of TLR-mediated inflammatory signaling in intestinal epithelial cells. By attenuating upstream adaptor and kinase modules while preserving essential immune responsiveness, L. brevis -derived metabolites promote controlled inflammatory tuning rather than indiscriminate immune suppression. These findings support a mechanistic basis for postbiotic-mediated modulation of epithelial innate immunity relevant to IBD-associated inflammation. Lactobacillus brevis postbiotics Toll-like receptor (TLR) signaling MyD88 TRIF NF-κB HT-29 intestinal epithelial cells inflammatory bowel disease (IBD) Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Background Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, is a group of chronic, relapsing inflammatory disorders of the gastrointestinal tract that impose a substantial global health burden [ 1 ]. The pathogenesis of IBD is multifactorial, involving complex interactions between genetic predisposition, environmental triggers, gut microbiota dysbiosis, and dysregulated immune responses, ultimately resulting in persistent intestinal inflammation [ 2 , 3 ]. Recent epidemiological data highlight that, although incidence rates in many Western countries have plateaued, the prevalence of IBD continues to rise worldwide, with a marked increase in newly industrialized regions, particularly in Asia, the Middle East, and South America [ 3 ]. This epidemiological transition, coupled with the chronic, incurable nature of IBD and the limitations of current therapies, underscores its growing impact on public health and the urgent need for innovative therapeutic approaches [ 2 ]. Toll-like receptors (TLRs) are key pattern recognition receptors (PRRs) that sense microbial- and damage-associated molecular patterns, thereby linking the gut microbiota to host innate immunity. Through adaptor proteins such as MyD88 and TRIF, TLR signaling activates downstream cascades including NF-κB and MAPK, which regulate the expression of pro-inflammatory cytokines and type I interferons [ 4 , 5 ]. Under physiological conditions, TLR activity helps maintain mucosal homeostasis by balancing immune tolerance and protective responses [ 6 ]. However, dysregulated TLR signaling has been implicated in epithelial barrier dysfunction, exaggerated cytokine release, and chronic intestinal inflammation characteristic of IBD [ 7 ]. Clinical studies further confirm this association, reporting increased expression of TLR2, TLR4, and TLR9 in the colonic mucosa of ulcerative colitis patients, correlating with disease severity and microbial dysbiosis [ 8 ]. Probiotics, defined as live microorganisms that confer health benefits when administered in adequate amounts, have been increasingly recognized as promising adjunctive strategies for IBD management. By modulating gut microbiota composition, enhancing epithelial barrier integrity, and regulating host immune responses, probiotics exert significant anti-inflammatory effects [ 9 , 10 ]. Among them, Lactobacillus species are the most widely studied, with evidence showing that various strains can attenuate colitis severity, restore immune balance, and reduce mucosal inflammation in both preclinical models and clinical trials [ 11 ]. Specifically, Lactobacillus brevis ( L. brevis ) has demonstrated potent immunomodulatory properties, including the suppression of pro-inflammatory cytokines (e.g., TNF-α, IL-6, IL-1β) and the induction of anti-inflammatory mediators such as IL-10, while simultaneously strengthening epithelial tight junction proteins (e.g., ZO-1, occludin, and E-cadherin) [ 12 ]. These findings highlight the therapeutic potential of L. brevis as a strain-specific probiotic capable of modulating key pathways implicated in IBD pathogenesis, particularly through the regulation of TLR-mediated signaling and cytokine networks. Despite growing evidence supporting the beneficial effects of probiotics in IBD, the precise molecular mechanisms through which L. brevis exerts its immunomodulatory functions remain poorly understood. In particular, limited data are available on how L. brevis -derived metabolites influence Toll-like receptor–mediated signaling in intestinal epithelial cells, a pathway central to the initiation and perpetuation of mucosal inflammation. To address this gap, the present study employed an in vitro HT-29 cell model to investigate the transcriptional alterations induced by L. brevis cell-free supernatant (CFS). By profiling the expression of 84 key genes within the TLR signaling pathway, we aimed to elucidate the potential regulatory effects of L. brevis on innate immune responses relevant to IBD pathogenesis. 2. Methods 2.1. L. brevis culture and Preparation of CFS The probiotic strain L. brevis (ATCC-14869) was obtained from the National Genetic and Biological Resources Center (Tehran, Iran). The bacterium was cultivated on de Man, Rogosa, and Sharpe (MRS) broth (Merck, Germany) (37 °C , anaerobic conditions, 24h). After confirmation of bacterial identity using Gram staining, a 0.5 McFarland standard (OD ≈ 0.6) of L. brevis was centrifuged (4,000 × g for 15 min at 4 °C ) using a refrigerated centrifuge (Eppendorf 5810R, Germany). The resulting supernatant was collected and passed through a 0.22 µm sterile membrane filter (Sartorius, Germany) to ensure removal of bacterial cells. The sterile filtrate, designated as CFS, was aliquoted and stored at − 20 °C until further use in cell treatment experiments. Serial dilutions of the CFS (100%, 50%, 25%, and 12.5%) were prepared in culture medium for subsequent assays. 2.2. HT-29 cell culture The human colorectal adenocarcinoma epithelial cell line HT-29 (ATCC HTB-38) was obtained from the Pasteur Institute (Tehran, Iran). Cells were maintained in Dulbecco’s Modified Eagle Medium (DMEM, Gibco™, USA) supplemented with 10% fetal bovine serum (FBS, Gibco™, USA) and 1% penicillin–streptomycin (Gibco™, USA) and incubated (37 °C , humidified atmosphere with 5% CO₂). Cells were subcultured upon reaching ~ 80% confluency using 0.25% trypsin–EDTA solution (Gibco™, USA). 2.3. Cell Viability (MTT) and Treatment Design HT-29 cells (2×10⁴/well) were cultured in 96-well plates for 24 h. After medium replacement with serial dilutions of the CFS (100%, 50%, 25%, 12.5%), cells were incubated for an additional 24 and 48 h. Cell viability was then assessed using MTT [ 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide ] (Sigma, Germany) solution (5 mg/mL, 3 h incubation), followed by DMSO solubilization. Absorbance was measured at 570 nm, and viability was calculated relative to untreated controls. For treatment experiments, HT-29 cells were seeded into six-well plates at a density of 1×10⁶ cells/well and allowed to adhere for 24 h. Subsequently, the cells were exposed to the 50% CFS of L. brevis (48 h), which have been identified in preliminary MTT assays as the concentration and time providing the highest cell viability (> 90%). Untreated cells cultured under identical conditions served as the control group. 2.4. RNA Extraction, cDNA Synthesis, and Gene Expression Analysis of TLR Signaling Pathway by Real-Time PCR Total RNA was extracted from cultured cells using the RNeasy Mini Kit (Qiagen, Hilden, Germany, Cat. No. 74106) according to the manufacturer's protocol. Briefly, approximately 1 × 10⁶ cells were harvested, pelleted, and lysed in 350 µL of RLT lysis buffer. The lysate was homogenized by pipetting and mixed thoroughly with 350 µL of 70% ethanol. The mixture was then applied to a RNeasy Mini spin column and centrifuged (8000× g, 15 s). The column was washed sequentially with 350 µL of RW1 buffer and twice with 500 µL of RPE buffer (for each centrifuged at 8000× g,15 s and a final centrifugation at 8000 × g, 2 min). Finally, RNA was eluted in 30 µL of RNase-free water (8000× g,1 min). RNA concentration and purity were determined using a NanoDrop spectrophotometer, and integrity was confirmed by 1% agarose gel electrophoresis. RNA samples were stored at − 80°C until further use. cDNA was synthesized using the QuantiNova Reverse Transcription Kit (Qiagen, Cat. No. 205411, Germany) following the manufacturer's protocol. Briefly, up to 5 µg of total RNA was combined with 2 µL of gDNA Removal Mix in a 15 µL reaction volume and incubated )45 °C for 2 min(. Subsequently, 5 µL of the Reverse-transcription Master Mix (containing 4 µL of Reverse Transcription Mix and 1 µL of Reverse Transcription Enzyme) was added. The complete reaction was incubated in a thermal cycler for annealing (25 °C for 3 min), Reverse-transcription (45 °C for 10 min), and final Inactivation of reaction (85 °C for 5 min) steps. Concentration of synthesized cDNA was measured using a NanoDrop spectrophotometer and were normalized to a uniform concentration with RNase-free water. The synthesized cDNA was stored at -20 °C . Gene expression profiling of the Toll-like receptor (TLR) signaling pathway was performed using the RT² Profiler™ PCR Array Human Toll-Like Receptor Signaling Pathway (Qiagen, Germany, Cat. No. PAHS-018Z). A PCR master mix was prepared by combining 1350 µl of 2× RT² SYBR Green Mastermix, 102 µl of synthesized cDNA, and 1248 µl of RNase-free water (total volume: 2700 µl). Then, 25 µl of the master mix was loaded into each well of the pre-designed 96-well array plate (Fig. 2.1 ). The plate contains primers for 84 TLR pathway-related genes, 5 housekeeping genes, 1 genomic DNA control, 3 reverse transcription controls (RTC), and 3 positive PCR controls (PPC). Quantitative real-time PCR was run on a Roche LightCycler 480 with the following cycling protocol: initial activation (95 °C for 10 min), followed by 40 cycles of denaturation (95 °C for 15 s) and annealing/extension (60 °C for 1 min) (with fluorescence acquisition). Data quality was validated by requiring the genomic DNA control to have a Cq > 38 and the positive PCR controls to have a Cq < 20. Relative gene expression was analyzed using the GeneGlobe Data Analysis Center ( https://geneglobe.qiagen.com/us/analyze ), which calculates the fold change/regulation of the investigated genes using the delta Ct (∆Ct) method. Briefly, ∆Ct was calculated between each gene and an average of the housekeeping genes. Then, ∆∆Ct was extrapolated as the difference between ∆Ct of genes in the tested group and ∆Ct of the same genes in the control group. Finally, fold change was calculated using 2 (−∆∆Ct) formula. Data analyses were also performed using PathVisio software, KEGG String, and WikiPathways online websites ( https://www.wikipathways.org/index.php/WikiPathways ). 2.5. Statistical Analysis All experiments were performed in triplicate, and data are presented as mean ± standard deviation (SD). Statistical analyses were carried out using GraphPad Prism version 8.0 (GraphPad Software, USA). Differences between treated and control groups were evaluated using one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test. A p .value less than 0.05 was considered statistically significant. 3. Results 3.1. 50% L. brevis CFS Enhances HT-29 Cell Proliferation in MTT Assay The MTT assay demonstrated both concentration- and time-dependent effects of L. brevis CFS on HT-29 cell viability (each treatment group normalized to the unstimulated HT-29 control) (Fig. 3.1 ). Treatment with 50% L. brevis CFS significantly enhanced HT-29 cell proliferation, with no significant difference between 24 h and 48 h exposure. Since 24 h exposure was sufficient to induce significant proliferation, we chose 50% CFS at 48 hours with the aim of subsequent gene expression and molecular pathway analysis, as the extended exposure was expected to provide a more robust model for examining signaling pathways relevant to IBD pathogenesis. 3.2. L. brevis Induced Significant Alterations in Gene Expression of HT-29 Cells The qPCR array analysis of 84 key genes involved in the Toll-like receptor (TLR) signaling pathway revealed significant transcriptional changes following treatment of HT-29 cells with 50% L. brevis CFS (Fig. 3.2 ). While a concise group of seven genes was significantly upregulated—including BTK ( p = 0.016), FOS ( p < 0.001), HSPA1A ( p < 0.001), JUN ( p < 0.001), TICAM2 ( p < 0.001), TLR1 ( p = 0.016), and TLR10 ( p = 0.030) (Fig. 3.2 .A)—the overall response was predominantly characterized by a broad and coordinated downregulation across three major innate immune signaling modules. First, the TRIF-dependent antiviral and interferon response axis was markedly inhibited, evidenced by downregulation of TLR3 ( p < 0.001), its adaptor TICAM1 ( p < 0.001), the kinase TBK1 ( p < 0.001), the transcription factor IRF3 ( p < 0.001), and the chemokine CXCL10 ( p < 0.001) (Fig. 3.2 .B1). Second, the core components of the canonical TLR/MyD88-dependent pro-inflammatory pathway were suppressed, encompassing receptors ( TLR2 p < 0.001, TLR4 p < 0.001), adaptors and kinases ( MYD88 p < 0.001, TIRAP p < 0.001, IRAK1 p < 0.001, IRAK4 p < 0.001, MAP3K7 p < 0.001), transcription factors ( NFKB1 p < 0.001, REL p < 0.001), and effector cytokines ( IL1A p < 0.001, IL1B p < 0.001, IL6 p < 0.001, IL12A p < 0.001, CCL2 p < 0.001, PTGS2 p < 0.001) (Fig. 3.2 .B2). Third, a network of integrated modulatory pathways was attenuated, including mediators of apoptosis ( CASP8 p < 0.001, FADD p < 0.001), key elements of the MAPK/JNK stress-signaling cascade ( MAP3K1 p < 0.001, MAP2K3 p < 0.001, MAP2K4 p < 0.001, MAPK8 p < 0.001), the immunomodulatory nuclear receptor PPARA ( p < 0.001), and pleiotropic cellular regulators ( HRAS p < 0.001, HMGB1 p < 0.001) (Fig. 3.2 .B3). Collectively, these data demonstrate that L. brevis CFS induces a potent immunomodulatory transcriptomic signature in intestinal epithelial cells, primarily through the simultaneous dampening of multiple TLR-driven inflammatory and antiviral programs, suggesting a mechanistic basis for promoting an anti-inflammatory milieu. 3.3. Pathway-Level Impacts of L. brevis CFS on TLR Signaling To obtain a systems-level understanding of the transcriptional alterations induced by L. brevis 50% CFS, differentially expressed genes were integrated into a curated TLR signaling pathway adapted for HT-29 intestinal epithelial cells (Fig. 3.3 .). Pathway mapping revealed coordinated modulation of both the MyD88-dependent and MyD88-independent (TRIF-dependent) signaling branches. As illustrated in Fig. 3.3 ., multiple components of the MyD88-dependent cascade—including adaptor molecules and downstream kinase modules—displayed altered expression profiles. These changes collectively suggest attenuation of NF-κB and MAPK activation, which is consistent with the observed modulation of downstream inflammatory mediators and chemokines. The pathway visualization demonstrates that transcriptional regulation was not confined to a single node but extended across adaptor proteins, signal transducers, and effector genes. To further delineate the effects within the canonical inflammatory axis, the MyD88-dependent arm was separately highlighted (Fig. 3.4 .). This focused representation emphasizes the modulation of IRAK-associated signaling, TRAF6-mediated ubiquitination events, MAPK cascades, and NF-κB family transcription factors, ultimately impacting the expression of pro-inflammatory genes. The collective pathway-level analysis indicates that L. brevis CFS exerts broad regulatory effects on TLR-mediated signaling networks in HT-29 cells rather than selectively targeting an isolated downstream effector. The Toll-like receptor (TLR) signaling pathway was adapted for intestinal epithelial cells (HT-29). Gene expression changes are color-coded as follows: gray indicates no statistically significant change; dark blue indicates significantly downregulated genes ( p 2); light blue indicates significantly downregulated genes ( p < 0.05 and fold regulation < 2); dark red indicates significantly upregulated genes ( p 2); light red indicates significantly upregulated genes ( p < 0.05 and fold regulation < 2). Signaling cascades include MyD88-dependent and MyD88-independent pathways leading to NF-κB, MAPK, and IRF activation and subsequent inflammatory gene transcription. 4. Discussion The intestinal epithelium maintains mucosal homeostasis through tightly regulated TLR signaling [ 13 ]. In inflammatory bowel disease (IBD), dysregulation of this system leads to chronic inflammation [ 5 ]. Although probiotics have been reported to modulate epithelial immune responses, the pathway-level mechanisms by which bacterial metabolites influence TLR signaling remain incompletely defined. In the present study, exposure of HT-29 cells to L. brevis cell-free supernatant (CFS) induced a coordinated transcriptional reprogramming across the TLR signaling network, indicating broad dampening of TLR activation rather than isolated regulation of individual cytokines. At the receptor level, L. brevis CFS induced structured remodeling rather than uniform suppression. TLR2 was markedly downregulated, whereas TLR1 and TLR10 were upregulated. TLR2 is known to drive MyD88-NF-κB inflammatory activation in intestinal inflammation [ 14 ], and its overexpression has been associated with inflammatory amplification in colitis models [ 15 ]. Thus, its reduction aligns with attenuation of classical pro-inflammatory signaling. In contrast, TLR10 has been recognized as a modulatory receptor capable of suppressing NF-κB activation [ 16 , 17 ], and probiotic-induced TLR2/TLR10-dependent signaling has been linked to epithelial immune tolerance [ 18 ]. The asymmetric regulation of the TLR2–TLR6 pair (TLR2 down; TLR6 unchanged) further supports disruption of canonical lipoteichoic acid-driven inflammatory signaling [ 14 ]. The most coordinated suppression occurred within the TLR4 sensing module. TLR4 downregulation paralleled reduced CD14 and HMGB1 expression, alongside modulation of the CD180–LY86 regulatory complex. Because CD14 facilitates LPS delivery to the TLR4–MD-2 complex and HMGB1 amplifies TLR2/4-mediated NF-κB activation, their concurrent reduction suggests attenuation of a high-gain inflammatory amplification loop rather than isolated transcriptional fluctuation. Probiotic-mediated suppression of TLR4/MyD88/NF-κB signaling has similarly been reported in DSS colitis models [ 19 ], and decreased TLR4 expression with enhanced tolerogenic cytokine production has been observed in immune cells from IBD patients treated with probiotics [ 20 ]. Our data extend these observations by demonstrating coordinated modulation across multiple components of the LPS recognition complex at the epithelial level. In contrast to surface bacterial sensors, endosomal TLRs exhibited selective modulation. TLR3 and TLR9 were reduced, whereas TLR7 and TLR8 remained unchanged. Given that TLR3 and TLR9 overactivation contributes to mucosal inflammatory amplification in IBD and colitis-associated pathology [ 21 , 22 ], their attenuation may reflect restoration of epithelial activation thresholds rather than compromised antiviral defense. Preservation of TLR7/8 is notable, as TLR7–MyD88 signaling is critical for antiviral competence [ 23 ]. Consistent with this receptor pattern, adaptor redistribution (MYD88 and TIRAP decreased; TICAM1 decreased while TICAM2 increased) suggests rebalancing between inflammatory MyD88-dependent signaling and TRIF-associated interferon routing rather than global innate suppression. Within the MYD88-dependent arm, transcriptional modulation extended into the core Myddosome architecture. IRAK1/2, MAP3K7 (TAK1), TAB1, TRAF6, and TIRAP were coordinately regulated, indicating attenuation at the level of signalosome assembly and TRAF6–TAK1 complex formation rather than isolated receptor dampening. Because this complex controls activation of both the IKK–NF-κB axis and MAPK cascades, modulation at this tier constrains inflammatory signal propagation upstream of cytokine transcription [ 24 ]. Consistently, components governing IKK activation and NF-κB nuclear translocation—including CHUK, IKBKB, UBE2N, NFKB1/2, REL, and RELA—were transcriptionally modulated. Similar adaptor- and kinase-level suppression has been reported in HT-29 cells treated with Lactobacillus / Bifidobacterium mixtures, where TIRAP, IRAK4, and NEMO were downregulated alongside reduced NF-κB activity [ 25 ]. Likewise, L. acidophilus and B. animalis suppressed phosphorylated p65 and p38 MAPK in stimulated HT-29 models [ 26 ]. Notably, L. brevis itself reduced RELA expression and shifted the RELA–IKB balance in HT-29 cells [ 27 ], supporting restrained NF-κB transcriptional activity. Parallel modulation of MAP3K7–TAB1 and downstream MAP2K3/MAP2K4/MAPK8 modules further indicates dampening of JNK and p38 signaling, pathways that cooperate with NF-κB to drive AP-1-dependent transcription. In vivo, L. brevis G-101 inhibited IRAK1 phosphorylation and suppressed NF-κB/MAPK activation in TNBS colitis while reducing TNF-α, IL-1β, and IL-6 production [ 24 ], aligning with our kinase-tier findings. Importantly, MYD88 modulation should be interpreted as recalibration rather than abrogation. Complete MyD88 loss disrupts microbial homeostasis and can worsen colitis through compensatory inflammatory pathways [ 28 , 29 ]. Thus, the coordinated attenuation observed here most likely reflects controlled signal gating, preserving basal innate responsiveness while limiting excessive amplification relevant to epithelial homeostasis in IBD. In parallel with MyD88-dependent attenuation, components of the TICAM1 (TRIF)-dependent pathway were also selectively regulated, indicating broader recalibration of innate signaling topology. Core TRIF-axis elements—including TICAM1, TICAM2, TBK1, TRAF6, MAP3K7, and PELI1—were transcriptionally modulated. Because TRIF signaling downstream of TLR3/4 governs TBK1–IRF-mediated interferon responses while intersecting with NF-κB via TRAF6–TAK1 [ 25 ], regulation at this tier reflects control of signal branching rather than restriction of a single inflammatory output. Consistently, downstream IRF1/IRF3 and interferon-related genes ( IFNA1 , IFNB1 , IFNG , CXCL10 ) were selectively modulated. In pathogenic contexts, TRIF-linked signaling can drive high-amplitude interferon activation. For example, Caco-2 cells exposed to E. coli OMVs exhibited marked upregulation of IFNA1 / IFNB1 alongside TLR3/7/8 activation [ 30 ], illustrating the amplification capacity of this branch. Compared with such hyperactivation, the pattern observed here suggests controlled attenuation rather than antiviral shutdown. Similarly, native Lactobacillus spp. have been reported to modulate MYD88-independent transcripts without abolishing immunoregulatory effects, supporting a model of pathway recalibration rather than collapse [ 31 ]. Given that several differentially expressed cytokines in our dataset—including CCL2 , CSF2 , IFNG , IL12A , IL2 , and IL6 —signal through canonical JAK/STAT pathways, the observed transcriptional shifts extend beyond primary TLR activation into secondary cytokine-driven amplification loops. IL-6 primarily activates JAK1/JAK2–STAT3, whereas IFNγ and IL-12 preferentially engage STAT1 and STAT4, respectively [ 25 ]. Since STAT phosphorylation sustains inflammatory gene transcription, modulation at this level directly influences the persistence of mucosal inflammation. In HT-29 IBD models, probiotic cocktails have been shown to downregulate JAK genes alongside NF-κB components, with concomitant reductions in IL-6 and IL-1β production [ 25 , 32 ], supporting functional linkage between pathway modulation and cytokine suppression. Similarly, Lactobacillus spp. have been reported to coordinately downregulate JAK genes together with TIRAP and IRAK4 in HT-29 cells, disrupting the TLR–cytokine–STAT feed-forward loop [ 33 ]. Because JAK/STAT signaling intersects with NF-κB transcriptional programs in epithelial cells [ 34 ], simultaneous modulation of both axes suggests coordinated restriction of inflammatory reinforcement circuits. Consistent with this, prior work on L. brevis demonstrated regulation of RELA and IKB expression in HT-29 cells [ 27 ], indicating that probiotic-derived factors can influence transcriptional regulators upstream of cytokine amplification. Modulation of downstream effector molecules—including CASP8 , FADD , EIF2AK2 (PKR), PRKRA , PPARA , ECSIT , UBE2N , and TRAF6 —further underscores that L. brevis CFS influences multiple tiers of intracellular signaling architecture beyond proximal adaptor complexes. At the level of ubiquitin-dependent NF-κB regulation, coordinated modulation of TRAF6 and UBE2N is particularly notable. TRAF6 functions as a central E3 ubiquitin ligase within TLR pathways, mediating K63-linked ubiquitination events required for IKK activation and NF-κB nuclear translocation. Recent evidence demonstrates that alterations in TRAF6 protein stability critically influence IBD severity; ASB3-mediated K48-linked polyubiquitination of TRAF6 promotes dysregulated NF-κB activation and intestinal microbiota imbalance [ 35 ]. Therefore, transcriptional regulation of TRAF6 and its associated ubiquitination machinery in our dataset suggests upstream tuning of NF-κB activation thresholds. Consistent with this, modulation of ECSIT further implicates control at the level of ubiquitin-dependent NF-κB activation. ECSIT serves as a TRAF6-interacting scaffold within TLR4 signaling and requires ubiquitination at lysine 372 for effective interaction with p65/p50 NF-κB and nuclear colocalization [ 36 ]. Because ubiquitinated ECSIT facilitates NF-κB DNA-binding activity and pro-inflammatory cytokine production, its regulation implies potential attenuation of nuclear NF-κB transcriptional competence rather than simple cytoplasmic signal restriction. The observed shifts in CASP8 and FADD indicate additional cross-talk between inflammatory and apoptotic signaling nodes. In the context of IBD, epithelial apoptosis and barrier dysfunction contribute directly to mucosal inflammation. Therefore, coordinated regulation of CASP8 / FADD suggests impact on the epithelial survival–inflammation balance. Modulation of EIF2AK2 (PKR) and its activator PRKRA extends this regulatory influence into antiviral and stress-response pathways. Finally, transcriptional regulation of PPARA introduces a nuclear receptor-mediated anti-inflammatory layer. PPARα exerts inhibitory effects on NF-κB-dependent gene expression and represses inflammatory mediators such as IL-6 and COX-2 [ 37 ]. Collectively, the coordinated modulation of ubiquitination regulators, scaffold proteins, apoptotic mediators, antiviral kinases, and nuclear receptors indicates structured regulation across cytoplasmic, nuclear, and post-translational signaling layers. The coordinated modulation of SIGIRR , SARM1 , and TOLLIP indicates reinforcement of intrinsic inhibitory checkpoints within the TLR network rather than indiscriminate pathway suppression. These regulators operate at distinct tiers—TOLLIP at the IRAK level, SIGIRR at receptor complex assembly, and SARM1 at adaptor-routing control—collectively constraining excessive MYD88-driven amplification. TOLLIP inhibits IRAK activation within the TLR4 cascade. In Caco-2 cells, Lactobacillus plantarum MYL26 induced LPS tolerance via TOLLIP upregulation, impairing TLR4–NF-κB signaling [ 38 ], and Bifidobacterium adolescentis increased intestinal TOLLIP while reducing TLR4 expression in NEC models [ 39 ]. This aligns with our observation that TOLLIP modulation accompanies upstream TLR attenuation, suggesting active negative-feedback reinforcement. SIGIRR (TIR8) functions as a decoy receptor limiting IL-1R/TLR signaling. SIGIRR deficiency enhances NF-κB activation and susceptibility to colitis [ 40 ]. Probiotic strains—including L. brevis —have been shown to upregulate SIGIRR in HT-29 cells while suppressing pathogen-induced cytokines [ 41 ], and Bifidobacterium breve similarly enhanced SIGIRR alongside A20 and Tollip to restrain NF-κB/MAPK activation [ 42 ]. SARM1 further modulates MYD88–TRAF signaling dynamics, with recent data indicating that SARM1 regulates MYD88-mediated inflammatory routing [ 43 ] and influences intestinal inflammatory responses in IBD models [ 44 ]. Together, the regulation of TOLLIP, SIGIRR, and SARM1 supports a model in which L. brevis CFS strengthens endogenous braking mechanisms—limiting NF-κB/MAPK amplification while preserving basal antimicrobial competence. Functional stratification of the differentially expressed genes into pathogen-associated response modules revealed structured and non-uniform tuning across microbial sensing axes. Genes linked to bacterial sensing ( TLR2 , TLR4 , CD14 , LY96 , RIPK2 ), viral recognition ( TLR3 , TLR7 , TLR8 , TBK1 , IRF3 , EIF2AK2 ), and fungal/parasitic pathways ( CLEC4E , TIRAP ) were differentially regulated rather than globally suppressed. Importantly, antiviral competence appears preserved. In contrast to pharmacologic suppression of the TLR–TBK1–IRF3/7 axis, which reduces IFN-α/β transcription [ 45 ], our dataset did not demonstrate collapse of interferon-associated mediators. Preservation of TNF expression in our system similarly argues against impaired antibacterial defense. Equally important, no disproportionate IL-10 induction was observed. While Levilactobacillus brevis IBARAKI-TS3 promotes IL-10 production via TLR2 engagement [ 46 ], and L. reuteri postbiotics shift IL-17/IL-10 balance toward regulation in inflamed HT-29 cells [ 47 ], our epithelial dataset did not exhibit excessive regulatory skewing suggestive of compromised vigilance. Barrier preservation provides an additional safeguard; Lactobacillus plantarum prevents tight junction disruption and endotoxemia through EGFR-dependent mechanisms [ 48 ]. Collectively, the differential modulation of pathogen-sensing modules in our system reflects structured immune recalibration rather than generalized immunosuppression. Several limitations warrant consideration. First, the analysis was confined to a targeted RT² Profiler PCR Array centered on TLR-related genes; although this enables pathway-focused resolution, broader transcriptomic alterations beyond the predefined panel may have been overlooked. Second, our interpretations rely on mRNA-level modulation without parallel protein or functional validation, and transcript changes do not necessarily translate into proportional alterations in protein abundance or signaling activity, particularly for adaptor proteins and transcription factors subject to post-translational regulation. Third, the use of an in vitro HT-29 epithelial model, while providing controlled mechanistic insight, does not fully recapitulate the cellular complexity of the intestinal microenvironment, including immune cell interactions, microbiota dynamics, and barrier architecture. Future studies incorporating protein-level validation and more physiologically relevant in vivo or co-culture systems will be required to confirm the pathway-level inferences proposed here. In conclusion, L. brevis CFS treatment of HT-29 epithelial cells induced coordinated, multi-layer reprogramming of the TLR signaling network rather than isolated cytokine suppression. Remodeling occurred across receptor complexes, adaptor routing, kinase tiers, JAK/STAT amplification loops, and intrinsic inhibitory checkpoints, collectively indicating structured attenuation of inflammatory signal propagation at multiple upstream nodes. Importantly, this pattern does not represent global immunosuppression. Interferon-associated pathways remained transcriptionally competent, TNF signaling was not pathologically suppressed, and IL-10 did not display disproportionate induction. Instead, pathogen-specific sensing modules were differentially tuned, suggesting preserved antiviral and antibacterial capacity alongside constrained inflammatory amplification. Together, these findings support a mechanistic model in which probiotic-derived metabolites recalibrate epithelial immune thresholds through signal gating and reinforcement of endogenous regulatory circuits. Such multi-tier modulation may represent a rational strategy for restoring mucosal immune balance in IBD-associated inflammation without compromising core host defense functions. Statement of Ethics This study did not involve human participants, animal experiments, or clinical samples. All procedures were conducted using established human cell lines (HT-29) obtained from the Pasteur Institute of Iran, and therefore ethical approval was not required according to institutional and national guidelines. Abbreviations BTK Bruton agammaglobulinemia tyrosine kinase CASP8 Caspase 8, apoptosis-related cysteine peptidase CCL2 Chemokine (C-C motif) ligand 2 CD14 CD14 molecule CD180 CD180 molecule CD80 CD80 molecule CD86 CD86 molecule CHUK Conserved helix-loop-helix ubiquitous kinase CLEC4E C-type lectin domain family 4, member E CSF2 Colony stimulating factor 2 (granulocyte-macrophage) CSF3 Colony stimulating factor 3 (granulocyte) CXCL10 Chemokine (C-X-C motif) ligand 10 ECSIT ECSIT homolog (Drosophila) EIF2AK2 Eukaryotic translation initiation factor 2-alpha kinase 2 ELK1 ELK1, member of ETS oncogene family FADD Fas (TNFRSF6)-associated via death domain FOS FBJ murine osteosarcoma viral oncogene homolog HMGB1 High mobility group box 1 HRAS V-Ha-ras Harvey rat sarcoma viral oncogene homolog HSPA1A Heat shock 70kDa protein 1A HSPD1 Heat shock 60kDa protein 1 (chaperonin) IFNA1 Interferon, alpha 1 IFNB1 Interferon, beta 1, fibroblast IFNG Interferon, gamma IKBKB Inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta IL10 Interleukin 10 IL12A Interleukin 12A (natural killer cell stimulatory factor 1, cytotoxic lymphocyte maturation factor 1, p35) IL1A Interleukin 1, alpha IL1B Interleukin 1, beta IL2 Interleukin 2 IL6 Interleukin 6 (interferon, beta 2) CXCL8 Interleukin 8 IRAK1 Interleukin-1 receptor-associated kinase 1 IRAK2 Interleukin-1 receptor-associated kinase 2 IRAK4 Interleukin-1 receptor-associated kinase 4 IRF1 Interferon regulatory factor 1 IRF3 Interferon regulatory factor 3 JUN Jun proto-oncogene LTA Lymphotoxin alpha (TNF superfamily, member 1) LY86 Lymphocyte antigen 86 LY96 Lymphocyte antigen 96 MAP2K3 Mitogen-activated protein kinase kinase 3 MAP2K4 Mitogen-activated protein kinase kinase 4 MAP3K1 Mitogen-activated protein kinase kinase kinase 1 MAP3K7 Mitogen-activated protein kinase kinase kinase 7 MAP4K4 Mitogen-activated protein kinase kinase kinase kinase 4 MAPK8 Mitogen-activated protein kinase 8 MAPK8IP3 Mitogen-activated protein kinase 8 interacting protein 3 MYD88 Myeloid differentiation primary response gene (88) NFKB1 Nuclear factor of kappa light polypeptide gene enhancer in B-cells 1 NFKB2 Nuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (p49/p100) NFKBIA Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha NFKBIL1 Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-like 1 NFRKB Nuclear factor related to kappaB binding protein NR2C2 Nuclear receptor subfamily 2, group C, member 2 PELI1 Pellino homolog 1 (Drosophila) PPARA Peroxisome proliferator-activated receptor alpha PRKRA Protein kinase, interferon-inducible double stranded RNA dependent activator PTGS2 Prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase) REL V-rel reticuloendotheliosis viral oncogene homolog (avian) RELA V-rel reticuloendotheliosis viral oncogene homolog A (avian) RIPK2 Receptor-interacting serine-threonine kinase 2 SARM1 Sterile alpha and TIR motif containing 1 SIGIRR Single immunoglobulin and toll-interleukin 1 receptor (TIR) domain TAB1 TGF-beta activated kinase 1/MAP3K7 binding protein 1 TBK1 TANK-binding kinase 1 TICAM1 Toll-like receptor adaptor molecule 1 TICAM2 Toll-like receptor adaptor molecule 2 TIRAP Toll-interleukin 1 receptor (TIR) domain containing adaptor protein TLR1 Toll-like receptor 1 TLR10 Toll-like receptor 10 TLR2 Toll-like receptor 2 TLR3 Toll-like receptor 3 TLR4 Toll-like receptor 4 TLR5 Toll-like receptor 5 TLR6 Toll-like receptor 6 TLR7 Toll-like receptor 7 TLR8 Toll-like receptor 8 TLR9 Toll-like receptor 9 TNF Tumor necrosis factor TNFRSF1A Tumor necrosis factor receptor superfamily, member 1A TOLLIP Toll interacting protein TRAF6 TNF receptor-associated factor 6 UBE2N Ubiquitin-conjugating enzyme E2N ACTB Actin, beta B2M Beta-2-microglobulin GAPDH Glyceraldehyde-3-phosphate dehydrogenase HPRT1 Hypoxanthine phosphoribosyltransferase 1 RPLP0 Ribosomal protein, large, P0 RTC Reverse Transcription Control PPC Positive PCR Control Declarations Conflict of Interest Authors declare no conflict of interest. CRediT authorship contribution statement Alireza Moghanlou ( [email protected] ): Data curation. Shima Rasouli ( [email protected] ): Writing – original draft. Sheyda Asadi ( [email protected] ) : Investigation. Sarvenaz Falsafi ( [email protected] ): Investigation. Behrouzi Ava ( [email protected] ): Writing – original draft. Funding The authors declare that no funds, grants, or other support was received during the preparation of this manuscript. Author Contribution Data curation: A.M. & A.B. & S.R.Investigation: S.A. & S.F.Writing – original draft: A.B. & S.R. Data Availability The data that support the findings of this study are available from the corresponding author upon reasonable request. References Bruner LP, White AM, Proksell S (2023) Inflammatory Bowel Disease. Prim Care 50(3):411–427 Adolph TE, Meyer M, Schwarzler J, Mayr L, Grabherr F, Tilg H (2022) The metabolic nature of inflammatory bowel diseases. 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PLoS ONE 15(3):e0229647 Murata K, Tomosada Y, Villena J, Chiba E, Shimazu T, Aso H et al (2014) Bifidobacterium breve MCC-117 Induces Tolerance in Porcine Intestinal Epithelial Cells: Study of the Mechanisms Involved in the Immunoregulatory Effect. Biosci Microbiota Food Health 33(1):1–10 Fan H, Song C, Zhang J (2024) Sarm1 Controls the MYD88-Mediated Inflammatory Responses in Inflammatory Bowel Disease via the Regulation of TRAF3 Recruitment. Immunol Invest 53(5):800–812 Sun Y, Wang Q, Wang Y, Ren W, Cao Y, Li J et al (2021) Sarm1-mediated neurodegeneration within the enteric nervous system protects against local inflammation of the colon. Protein Cell 12(8):621–638 Ogasawara N, Sasaki M, Itoh Y, Tokudome K, Kondo Y, Ito Y et al (2011) Rebamipide suppresses TLR-TBK1 signaling pathway resulting in regulating IRF3/7 and IFN-α/β reduction. 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Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 13 May, 2026 Reviews received at journal 13 May, 2026 Reviews received at journal 13 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 28 Apr, 2026 Editor assigned by journal 28 Apr, 2026 Submission checks completed at journal 28 Apr, 2026 First submitted to journal 27 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9542241","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635817371,"identity":"d5626737-2222-463f-9c22-553ed2197fb9","order_by":0,"name":"Alireza Moghanlou","email":"","orcid":"","institution":"TeMS.C., Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Alireza","middleName":"","lastName":"Moghanlou","suffix":""},{"id":635817372,"identity":"5beeb343-3043-4fe1-bfe9-490263cbddef","order_by":1,"name":"Shima Rasouli","email":"","orcid":"","institution":"TeMS.C., Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Shima","middleName":"","lastName":"Rasouli","suffix":""},{"id":635817373,"identity":"71596fc1-17d2-4292-8678-c24d6d6ded0e","order_by":2,"name":"Sheyda Asadi","email":"","orcid":"","institution":"Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Sheyda","middleName":"","lastName":"Asadi","suffix":""},{"id":635817374,"identity":"0268d5d0-e43d-4b6a-b21d-cfb5e1d3499b","order_by":3,"name":"Sarvenaz Falsafi","email":"","orcid":"","institution":"TeMS.C., Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Sarvenaz","middleName":"","lastName":"Falsafi","suffix":""},{"id":635817375,"identity":"8c7a555a-840d-49cd-a02c-531fdcbd007d","order_by":4,"name":"Ava Behrouzi","email":"data:image/png;base64,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","orcid":"","institution":"TeMS.C., Islamic Azad University","correspondingAuthor":true,"prefix":"","firstName":"Ava","middleName":"","lastName":"Behrouzi","suffix":""}],"badges":[],"createdAt":"2026-04-27 13:09:45","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9542241/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9542241/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108701369,"identity":"a01d752b-4f54-4b96-8ba0-9ec4ba4853fa","added_by":"auto","created_at":"2026-05-07 12:42:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":123662,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig 2.1. Schematic of the 96-well RT² Profiler™ PCR Array Human Toll-Like Receptor Signaling Pathway (Qiagen, Germany) used for gene expression analysis. \u003c/strong\u003eThe plate includes 84 TLR pathway-related genes, 5 housekeeping genes, and controls: genomic DNA control (GDC), reverse transcription controls (RTC), and positive PCR controls (PPC). Housekeeping genes (HK1 to HK5) were used for normalization of gene expression data. Each sample was loaded into the corresponding wells (A1–H12), as shown in the figure. The plate was used in conjunction with the.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9542241/v1/2ae64863cbad60e0ca98156b.png"},{"id":108701299,"identity":"6daa1268-4374-4baa-9752-b5e64d7301ed","added_by":"auto","created_at":"2026-05-07 12:42:12","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201924,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig 3.1. Effects of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. brevis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eFCS on HT-29 cell proliferation (MTT assay). \u003c/strong\u003eData are expressed as percentage of the unstimulated control (set at 100%, indicated by dashed line). (A) Time-dependent effects of CFS on proliferation at 24 h and 48 h compared with untreated control. (B) Concentration-dependent response at 24 h following treatment with 12.5%, 25%, 50% and 100% CFS. (C) Proliferation profile at 48 h across the same concentration range. (D1–D4) Direct comparison of 24 h and 48 h exposure within each concentration: (D1) 12.5%, (D2) 25%, (D3) 50%, and (D4) 100%.\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using one-way ANOVA followed by Tukey’s post-hoc test, with significance accepted at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9542241/v1/08a13e75d746dd5f74f65889.png"},{"id":108701259,"identity":"332c4c91-80f8-4524-bb32-20c9a1e3b6cf","added_by":"auto","created_at":"2026-05-07 12:42:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":157765,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig 3.2. Transcriptional response of HT-29 cells to 50% \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. brevis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e CFS treatment.\u003c/strong\u003e Genes were categorized into an upregulated panel (A) and three downregulated panels (B1-B3) based on their primary role in TLR signaling pathways: the TLR/MyD88-dependent pro-inflammatory pathway (B1), the TRIF-dependent antiviral pathway (B2), and an integrated modulation network (B3). Expression data are presented as log2 fold change normalized to the geometric mean of five housekeeping genes (\u003cem\u003eACTB\u003c/em\u003e, \u003cem\u003eB2M\u003c/em\u003e, \u003cem\u003eGAPDH\u003c/em\u003e, \u003cem\u003eHPRT1\u003c/em\u003e, and \u003cem\u003eRPLP0\u003c/em\u003e). The color scale indicates the magnitude and direction of gene expression change relative to the untreated control.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9542241/v1/612062b56fd6502e55a9025f.png"},{"id":108701320,"identity":"590183c2-aa62-40aa-9599-33b40cc5db71","added_by":"auto","created_at":"2026-05-07 12:42:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":99028,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig 3.3. Adapted TLR signaling pathway in HT-29 cells with differential gene expression profiling.\u003c/strong\u003e\u003cbr\u003e\nThe Toll-like receptor (TLR) signaling pathway was adapted for intestinal epithelial cells (HT-29). Gene expression changes are color-coded as follows: gray indicates no statistically significant change; dark blue indicates significantly downregulated genes (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and fold regulation \u0026gt; 2); light blue indicates significantly downregulated genes (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and fold regulation \u0026lt; 2); dark red indicates significantly upregulated genes (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and fold regulation \u0026gt; 2); light red indicates significantly upregulated genes (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 and fold regulation \u0026lt; 2). Signaling cascades include MyD88-dependent and MyD88-independent pathways leading to NF-κB, MAPK, and IRF activation and subsequent inflammatory gene transcription.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9542241/v1/c2c2d2348fab97dd29a1adc4.png"},{"id":108701365,"identity":"05e4432e-6e1b-4a82-bcd1-d3ab1e82c04e","added_by":"auto","created_at":"2026-05-07 12:42:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":43352,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig 3.4. MYD88-dependent TLR signaling pathway in HT-29 cells following treatment with \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eL. brevis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e cell-free supernatant (CFS). \u003c/strong\u003eDifferentially expressed genes identified by RT² Profiler PCR Array were mapped onto the MYD88-dependent TLR signaling cascade. Genes are color-coded according to expression changes: dark red, significantly upregulated (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, fold regulation ≥ 2); light red, significantly upregulated (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, fold regulation \u0026lt; 2); dark blue, significantly downregulated (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, fold regulation ≥ 2); light blue, significantly downregulated (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, fold regulation \u0026lt; 2); gray, no statistically significant change (\u003cem\u003ep\u003c/em\u003e ≥ 0.05). The pathway illustrates modulation of adaptor molecules, kinases, transcription factors, and downstream inflammatory mediators.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9542241/v1/ee19fae0b94d925ef6eecf96.png"},{"id":108701379,"identity":"3ceb57ce-b09a-4c84-b616-8e065cae01fa","added_by":"auto","created_at":"2026-05-07 12:42:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1037826,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9542241/v1/1439362e-f2b1-4c64-a5c7-7105296ebe7f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Lactobacillus brevis Cell-Free Supernatant Recalibrates TLR-Mediated Inflammatory Signaling While Preserving Immune Competence in HT-29 Intestinal Epithelial Cells","fulltext":[{"header":"1. Background","content":"\u003cp\u003eInflammatory bowel disease (IBD), encompassing Crohn\u0026rsquo;s disease and ulcerative colitis, is a group of chronic, relapsing inflammatory disorders of the gastrointestinal tract that impose a substantial global health burden [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The pathogenesis of IBD is multifactorial, involving complex interactions between genetic predisposition, environmental triggers, gut microbiota dysbiosis, and dysregulated immune responses, ultimately resulting in persistent intestinal inflammation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Recent epidemiological data highlight that, although incidence rates in many Western countries have plateaued, the prevalence of IBD continues to rise worldwide, with a marked increase in newly industrialized regions, particularly in Asia, the Middle East, and South America [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This epidemiological transition, coupled with the chronic, incurable nature of IBD and the limitations of current therapies, underscores its growing impact on public health and the urgent need for innovative therapeutic approaches [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eToll-like receptors (TLRs) are key pattern recognition receptors (PRRs) that sense microbial- and damage-associated molecular patterns, thereby linking the gut microbiota to host innate immunity. Through adaptor proteins such as MyD88 and TRIF, TLR signaling activates downstream cascades including NF-κB and MAPK, which regulate the expression of pro-inflammatory cytokines and type I interferons [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Under physiological conditions, TLR activity helps maintain mucosal homeostasis by balancing immune tolerance and protective responses [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, dysregulated TLR signaling has been implicated in epithelial barrier dysfunction, exaggerated cytokine release, and chronic intestinal inflammation characteristic of IBD [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Clinical studies further confirm this association, reporting increased expression of TLR2, TLR4, and TLR9 in the colonic mucosa of ulcerative colitis patients, correlating with disease severity and microbial dysbiosis [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eProbiotics, defined as live microorganisms that confer health benefits when administered in adequate amounts, have been increasingly recognized as promising adjunctive strategies for IBD management. By modulating gut microbiota composition, enhancing epithelial barrier integrity, and regulating host immune responses, probiotics exert significant anti-inflammatory effects [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Among them, Lactobacillus species are the most widely studied, with evidence showing that various strains can attenuate colitis severity, restore immune balance, and reduce mucosal inflammation in both preclinical models and clinical trials [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Specifically, \u003cem\u003eLactobacillus brevis\u003c/em\u003e (\u003cem\u003eL. brevis\u003c/em\u003e) has demonstrated potent immunomodulatory properties, including the suppression of pro-inflammatory cytokines (e.g., TNF-α, IL-6, IL-1β) and the induction of anti-inflammatory mediators such as IL-10, while simultaneously strengthening epithelial tight junction proteins (e.g., ZO-1, occludin, and E-cadherin) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These findings highlight the therapeutic potential of \u003cem\u003eL. brevis\u003c/em\u003e as a strain-specific probiotic capable of modulating key pathways implicated in IBD pathogenesis, particularly through the regulation of TLR-mediated signaling and cytokine networks.\u003c/p\u003e \u003cp\u003eDespite growing evidence supporting the beneficial effects of probiotics in IBD, the precise molecular mechanisms through which \u003cem\u003eL. brevis\u003c/em\u003e exerts its immunomodulatory functions remain poorly understood. In particular, limited data are available on how \u003cem\u003eL. brevis\u003c/em\u003e-derived metabolites influence Toll-like receptor\u0026ndash;mediated signaling in intestinal epithelial cells, a pathway central to the initiation and perpetuation of mucosal inflammation. To address this gap, the present study employed an in vitro HT-29 cell model to investigate the transcriptional alterations induced by \u003cem\u003eL. brevis\u003c/em\u003e cell-free supernatant (CFS). By profiling the expression of 84 key genes within the TLR signaling pathway, we aimed to elucidate the potential regulatory effects of \u003cem\u003eL. brevis\u003c/em\u003e on innate immune responses relevant to IBD pathogenesis.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. L. brevis culture and Preparation of CFS\u003c/h2\u003e \u003cp\u003eThe probiotic strain \u003cem\u003eL. brevis\u003c/em\u003e (ATCC-14869) was obtained from the National Genetic and Biological Resources Center (Tehran, Iran). The bacterium was cultivated on de Man, Rogosa, and Sharpe (MRS) broth (Merck, Germany) (37\u003csup\u003e\u0026deg;C\u003c/sup\u003e, anaerobic conditions, 24h). After confirmation of bacterial identity using Gram staining, a 0.5 McFarland standard (OD\u0026thinsp;\u0026asymp;\u0026thinsp;0.6) of \u003cem\u003eL. brevis\u003c/em\u003e was centrifuged (4,000 \u0026times; g for 15 min at 4\u003csup\u003e\u0026deg;C\u003c/sup\u003e) using a refrigerated centrifuge (Eppendorf 5810R, Germany). The resulting supernatant was collected and passed through a 0.22 \u0026micro;m sterile membrane filter (Sartorius, Germany) to ensure removal of bacterial cells. The sterile filtrate, designated as CFS, was aliquoted and stored at \u0026minus;\u0026thinsp;20\u003csup\u003e\u0026deg;C\u003c/sup\u003e until further use in cell treatment experiments. Serial dilutions of the CFS (100%, 50%, 25%, and 12.5%) were prepared in culture medium for subsequent assays.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. HT-29 cell culture\u003c/h2\u003e \u003cp\u003eThe human colorectal adenocarcinoma epithelial cell line HT-29 (ATCC HTB-38) was obtained from the Pasteur Institute (Tehran, Iran). Cells were maintained in Dulbecco\u0026rsquo;s Modified Eagle Medium (DMEM, Gibco\u0026trade;, USA) supplemented with 10% fetal bovine serum (FBS, Gibco\u0026trade;, USA) and 1% penicillin\u0026ndash;streptomycin (Gibco\u0026trade;, USA) and incubated (37\u003csup\u003e\u0026deg;C\u003c/sup\u003e, humidified atmosphere with 5% CO₂). Cells were subcultured upon reaching\u0026thinsp;~\u0026thinsp;80% confluency using 0.25% trypsin\u0026ndash;EDTA solution (Gibco\u0026trade;, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Cell Viability (MTT) and Treatment Design\u003c/h2\u003e \u003cp\u003eHT-29 cells (2\u0026times;10⁴/well) were cultured in 96-well plates for 24 h. After medium replacement with serial dilutions of the CFS (100%, 50%, 25%, 12.5%), cells were incubated for an additional 24 and 48 h. Cell viability was then assessed using MTT [\u003cem\u003e3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide\u003c/em\u003e] (Sigma, Germany) solution (5 mg/mL, 3 h incubation), followed by DMSO solubilization. Absorbance was measured at 570 nm, and viability was calculated relative to untreated controls.\u003c/p\u003e \u003cp\u003eFor treatment experiments, HT-29 cells were seeded into six-well plates at a density of 1\u0026times;10⁶ cells/well and allowed to adhere for 24 h. Subsequently, the cells were exposed to the 50% CFS of \u003cem\u003eL. brevis\u003c/em\u003e (48 h), which have been identified in preliminary MTT assays as the concentration and time providing the highest cell viability (\u0026gt;\u0026thinsp;90%). Untreated cells cultured under identical conditions served as the control group.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. RNA Extraction, cDNA Synthesis, and Gene Expression Analysis of TLR Signaling Pathway by Real-Time PCR\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from cultured cells using the RNeasy Mini Kit (Qiagen, Hilden, Germany, Cat. No. 74106) according to the manufacturer's protocol. Briefly, approximately 1 \u0026times; 10⁶ cells were harvested, pelleted, and lysed in 350 \u0026micro;L of RLT lysis buffer. The lysate was homogenized by pipetting and mixed thoroughly with 350 \u0026micro;L of 70% ethanol. The mixture was then applied to a RNeasy Mini spin column and centrifuged (8000\u0026times; g, 15 s). The column was washed sequentially with 350 \u0026micro;L of RW1 buffer and twice with 500 \u0026micro;L of RPE buffer (for each centrifuged at 8000\u0026times; g,15 s and a final centrifugation at 8000 \u0026times; g, 2 min). Finally, RNA was eluted in 30 \u0026micro;L of RNase-free water (8000\u0026times; g,1 min). RNA concentration and purity were determined using a NanoDrop spectrophotometer, and integrity was confirmed by 1% agarose gel electrophoresis. RNA samples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C until further use.\u003c/p\u003e \u003cp\u003ecDNA was synthesized using the QuantiNova Reverse Transcription Kit (Qiagen, Cat. No. 205411, Germany) following the manufacturer's protocol. Briefly, up to 5 \u0026micro;g of total RNA was combined with 2 \u0026micro;L of gDNA Removal Mix in a 15 \u0026micro;L reaction volume and incubated )45\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 2 min(. Subsequently, 5 \u0026micro;L of the Reverse-transcription Master Mix (containing 4 \u0026micro;L of Reverse Transcription Mix and 1 \u0026micro;L of Reverse Transcription Enzyme) was added. The complete reaction was incubated in a thermal cycler for annealing (25\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 3 min), Reverse-transcription (45\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 10 min), and final Inactivation of reaction (85\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 5 min) steps. Concentration of synthesized cDNA was measured using a NanoDrop spectrophotometer and were normalized to a uniform concentration with RNase-free water. The synthesized cDNA was stored at -20\u003csup\u003e\u0026deg;C\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGene expression profiling of the Toll-like receptor (TLR) signaling pathway was performed using the RT\u0026sup2; Profiler\u0026trade; PCR Array Human Toll-Like Receptor Signaling Pathway (Qiagen, Germany, Cat. No. PAHS-018Z). A PCR master mix was prepared by combining 1350 \u0026micro;l of 2\u0026times; RT\u0026sup2; SYBR Green Mastermix, 102 \u0026micro;l of synthesized cDNA, and 1248 \u0026micro;l of RNase-free water (total volume: 2700 \u0026micro;l). Then, 25 \u0026micro;l of the master mix was loaded into each well of the pre-designed 96-well array plate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2.1\u003c/span\u003e). The plate contains primers for 84 TLR pathway-related genes, 5 housekeeping genes, 1 genomic DNA control, 3 reverse transcription controls (RTC), and 3 positive PCR controls (PPC). Quantitative real-time PCR was run on a Roche LightCycler 480 with the following cycling protocol: initial activation (95\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 10 min), followed by 40 cycles of denaturation (95\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 15 s) and annealing/extension (60\u003csup\u003e\u0026deg;C\u003c/sup\u003e for 1 min) (with fluorescence acquisition).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eData quality was validated by requiring the genomic DNA control to have a Cq\u0026thinsp;\u0026gt;\u0026thinsp;38 and the positive PCR controls to have a Cq\u0026thinsp;\u0026lt;\u0026thinsp;20. Relative gene expression was analyzed using the GeneGlobe Data Analysis Center (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://geneglobe.qiagen.com/us/analyze\u003c/span\u003e\u003cspan address=\"https://geneglobe.qiagen.com/us/analyze\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), which calculates the fold change/regulation of the investigated genes using the delta Ct (∆Ct) method. Briefly, ∆Ct was calculated between each gene and an average of the housekeeping genes. Then, ∆∆Ct was extrapolated as the difference between ∆Ct of genes in the tested group and ∆Ct of the same genes in the control group. Finally, fold change was calculated using 2\u003csup\u003e(\u0026minus;∆∆Ct)\u003c/sup\u003e formula.\u003c/p\u003e \u003cp\u003eData analyses were also performed using PathVisio software, KEGG String, and WikiPathways online websites (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wikipathways.org/index.php/WikiPathways\u003c/span\u003e\u003cspan address=\"https://www.wikipathways.org/index.php/WikiPathways\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll experiments were performed in triplicate, and data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Statistical analyses were carried out using GraphPad Prism version 8.0 (GraphPad Software, USA). Differences between treated and control groups were evaluated using one-way analysis of variance (ANOVA) followed by Tukey\u0026rsquo;s post hoc test. A \u003cem\u003ep\u003c/em\u003e.value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. 50% L. brevis CFS Enhances HT-29 Cell Proliferation in MTT Assay\u003c/h2\u003e \u003cp\u003eThe MTT assay demonstrated both concentration- and time-dependent effects of \u003cem\u003eL. brevis\u003c/em\u003e CFS on HT-29 cell viability (each treatment group normalized to the unstimulated HT-29 control) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e). Treatment with 50% \u003cem\u003eL. brevis\u003c/em\u003e CFS significantly enhanced HT-29 cell proliferation, with no significant difference between 24 h and 48 h exposure. Since 24 h exposure was sufficient to induce significant proliferation, we chose 50% CFS at 48 hours with the aim of subsequent gene expression and molecular pathway analysis, as the extended exposure was expected to provide a more robust model for examining signaling pathways relevant to IBD pathogenesis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. L. brevis Induced Significant Alterations in Gene Expression of HT-29 Cells\u003c/h2\u003e \u003cp\u003eThe qPCR array analysis of 84 key genes involved in the Toll-like receptor (TLR) signaling pathway revealed significant transcriptional changes following treatment of HT-29 cells with 50% \u003cem\u003eL. brevis\u003c/em\u003e CFS (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e). While a concise group of seven genes was significantly upregulated\u0026mdash;including \u003cem\u003eBTK\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), \u003cem\u003eFOS\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eHSPA1A\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eJUN\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eTICAM2\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003eTLR1\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016), and \u003cem\u003eTLR10\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.030) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e.A)\u0026mdash;the overall response was predominantly characterized by a broad and coordinated downregulation across three major innate immune signaling modules. First, the TRIF-dependent antiviral and interferon response axis was markedly inhibited, evidenced by downregulation of \u003cem\u003eTLR3\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), its adaptor \u003cem\u003eTICAM1\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the kinase \u003cem\u003eTBK1\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the transcription factor \u003cem\u003eIRF3\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the chemokine \u003cem\u003eCXCL10\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e.B1). Second, the core components of the canonical TLR/MyD88-dependent pro-inflammatory pathway were suppressed, encompassing receptors (\u003cem\u003eTLR2 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eTLR4 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), adaptors and kinases (\u003cem\u003eMYD88 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eTIRAP p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eIRAK1 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eIRAK4 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eMAP3K7 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), transcription factors (\u003cem\u003eNFKB1 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eREL p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and effector cytokines (\u003cem\u003eIL1A p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eIL1B p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eIL6 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eIL12A p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eCCL2 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003ePTGS2 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e.B2). Third, a network of integrated modulatory pathways was attenuated, including mediators of apoptosis (\u003cem\u003eCASP8 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eFADD p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), key elements of the MAPK/JNK stress-signaling cascade (\u003cem\u003eMAP3K1 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eMAP2K3 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eMAP2K4 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eMAPK8 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the immunomodulatory nuclear receptor \u003cem\u003ePPARA\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and pleiotropic cellular regulators (\u003cem\u003eHRAS p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eHMGB1 p\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e.B3). Collectively, these data demonstrate that \u003cem\u003eL. brevis\u003c/em\u003e CFS induces a potent immunomodulatory transcriptomic signature in intestinal epithelial cells, primarily through the simultaneous dampening of multiple TLR-driven inflammatory and antiviral programs, suggesting a mechanistic basis for promoting an anti-inflammatory milieu.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Pathway-Level Impacts of L. brevis CFS on TLR Signaling\u003c/h2\u003e \u003cp\u003eTo obtain a systems-level understanding of the transcriptional alterations induced by \u003cem\u003eL. brevis\u003c/em\u003e 50% CFS, differentially expressed genes were integrated into a curated TLR signaling pathway adapted for HT-29 intestinal epithelial cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e.). Pathway mapping revealed coordinated modulation of both the MyD88-dependent and MyD88-independent (TRIF-dependent) signaling branches.\u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3.3\u003c/span\u003e., multiple components of the MyD88-dependent cascade\u0026mdash;including adaptor molecules and downstream kinase modules\u0026mdash;displayed altered expression profiles. These changes collectively suggest attenuation of NF-κB and MAPK activation, which is consistent with the observed modulation of downstream inflammatory mediators and chemokines. The pathway visualization demonstrates that transcriptional regulation was not confined to a single node but extended across adaptor proteins, signal transducers, and effector genes.\u003c/p\u003e \u003cp\u003eTo further delineate the effects within the canonical inflammatory axis, the MyD88-dependent arm was separately highlighted (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3.4\u003c/span\u003e.). This focused representation emphasizes the modulation of IRAK-associated signaling, TRAF6-mediated ubiquitination events, MAPK cascades, and NF-κB family transcription factors, ultimately impacting the expression of pro-inflammatory genes. The collective pathway-level analysis indicates that \u003cem\u003eL. brevis\u003c/em\u003e CFS exerts broad regulatory effects on TLR-mediated signaling networks in HT-29 cells rather than selectively targeting an isolated downstream effector.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Toll-like receptor (TLR) signaling pathway was adapted for intestinal epithelial cells (HT-29). Gene expression changes are color-coded as follows: gray indicates no statistically significant change; dark blue indicates significantly downregulated genes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and fold regulation\u0026thinsp;\u0026gt;\u0026thinsp;2); light blue indicates significantly downregulated genes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and fold regulation\u0026thinsp;\u0026lt;\u0026thinsp;2); dark red indicates significantly upregulated genes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and fold regulation\u0026thinsp;\u0026gt;\u0026thinsp;2); light red indicates significantly upregulated genes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and fold regulation\u0026thinsp;\u0026lt;\u0026thinsp;2). Signaling cascades include MyD88-dependent and MyD88-independent pathways leading to NF-κB, MAPK, and IRF activation and subsequent inflammatory gene transcription.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe intestinal epithelium maintains mucosal homeostasis through tightly regulated TLR signaling [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In inflammatory bowel disease (IBD), dysregulation of this system leads to chronic inflammation [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although probiotics have been reported to modulate epithelial immune responses, the pathway-level mechanisms by which bacterial metabolites influence TLR signaling remain incompletely defined. In the present study, exposure of HT-29 cells to \u003cem\u003eL. brevis\u003c/em\u003e cell-free supernatant (CFS) induced a coordinated transcriptional reprogramming across the TLR signaling network, indicating broad dampening of TLR activation rather than isolated regulation of individual cytokines.\u003c/p\u003e \u003cp\u003eAt the receptor level, \u003cem\u003eL. brevis\u003c/em\u003e CFS induced structured remodeling rather than uniform suppression. TLR2 was markedly downregulated, whereas TLR1 and TLR10 were upregulated. TLR2 is known to drive MyD88-NF-κB inflammatory activation in intestinal inflammation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and its overexpression has been associated with inflammatory amplification in colitis models [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Thus, its reduction aligns with attenuation of classical pro-inflammatory signaling. In contrast, TLR10 has been recognized as a modulatory receptor capable of suppressing NF-κB activation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and probiotic-induced TLR2/TLR10-dependent signaling has been linked to epithelial immune tolerance [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The asymmetric regulation of the TLR2\u0026ndash;TLR6 pair (TLR2 down; TLR6 unchanged) further supports disruption of canonical lipoteichoic acid-driven inflammatory signaling [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The most coordinated suppression occurred within the TLR4 sensing module. TLR4 downregulation paralleled reduced CD14 and HMGB1 expression, alongside modulation of the CD180\u0026ndash;LY86 regulatory complex. Because CD14 facilitates LPS delivery to the TLR4\u0026ndash;MD-2 complex and HMGB1 amplifies TLR2/4-mediated NF-κB activation, their concurrent reduction suggests attenuation of a high-gain inflammatory amplification loop rather than isolated transcriptional fluctuation. Probiotic-mediated suppression of TLR4/MyD88/NF-κB signaling has similarly been reported in DSS colitis models [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and decreased TLR4 expression with enhanced tolerogenic cytokine production has been observed in immune cells from IBD patients treated with probiotics [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our data extend these observations by demonstrating coordinated modulation across multiple components of the LPS recognition complex at the epithelial level. In contrast to surface bacterial sensors, endosomal TLRs exhibited selective modulation. TLR3 and TLR9 were reduced, whereas TLR7 and TLR8 remained unchanged. Given that TLR3 and TLR9 overactivation contributes to mucosal inflammatory amplification in IBD and colitis-associated pathology [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], their attenuation may reflect restoration of epithelial activation thresholds rather than compromised antiviral defense. Preservation of TLR7/8 is notable, as TLR7\u0026ndash;MyD88 signaling is critical for antiviral competence [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Consistent with this receptor pattern, adaptor redistribution (MYD88 and TIRAP decreased; TICAM1 decreased while TICAM2 increased) suggests rebalancing between inflammatory MyD88-dependent signaling and TRIF-associated interferon routing rather than global innate suppression.\u003c/p\u003e \u003cp\u003eWithin the MYD88-dependent arm, transcriptional modulation extended into the core Myddosome architecture. IRAK1/2, MAP3K7 (TAK1), TAB1, TRAF6, and TIRAP were coordinately regulated, indicating attenuation at the level of signalosome assembly and TRAF6\u0026ndash;TAK1 complex formation rather than isolated receptor dampening. Because this complex controls activation of both the IKK\u0026ndash;NF-κB axis and MAPK cascades, modulation at this tier constrains inflammatory signal propagation upstream of cytokine transcription [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Consistently, components governing IKK activation and NF-κB nuclear translocation\u0026mdash;including CHUK, IKBKB, UBE2N, NFKB1/2, REL, and RELA\u0026mdash;were transcriptionally modulated. Similar adaptor- and kinase-level suppression has been reported in HT-29 cells treated with \u003cem\u003eLactobacillus\u003c/em\u003e/\u003cem\u003eBifidobacterium\u003c/em\u003e mixtures, where TIRAP, IRAK4, and NEMO were downregulated alongside reduced NF-κB activity [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Likewise, \u003cem\u003eL. acidophilus\u003c/em\u003e and \u003cem\u003eB. animalis\u003c/em\u003e suppressed phosphorylated p65 and p38 MAPK in stimulated HT-29 models [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Notably, \u003cem\u003eL. brevis\u003c/em\u003e itself reduced RELA expression and shifted the RELA\u0026ndash;IKB balance in HT-29 cells [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], supporting restrained NF-κB transcriptional activity. Parallel modulation of MAP3K7\u0026ndash;TAB1 and downstream MAP2K3/MAP2K4/MAPK8 modules further indicates dampening of JNK and p38 signaling, pathways that cooperate with NF-κB to drive AP-1-dependent transcription. In vivo, \u003cem\u003eL. brevis\u003c/em\u003e G-101 inhibited IRAK1 phosphorylation and suppressed NF-κB/MAPK activation in TNBS colitis while reducing TNF-α, IL-1β, and IL-6 production [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], aligning with our kinase-tier findings. Importantly, MYD88 modulation should be interpreted as recalibration rather than abrogation. Complete MyD88 loss disrupts microbial homeostasis and can worsen colitis through compensatory inflammatory pathways [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Thus, the coordinated attenuation observed here most likely reflects controlled signal gating, preserving basal innate responsiveness while limiting excessive amplification relevant to epithelial homeostasis in IBD.\u003c/p\u003e \u003cp\u003eIn parallel with MyD88-dependent attenuation, components of the TICAM1 (TRIF)-dependent pathway were also selectively regulated, indicating broader recalibration of innate signaling topology. Core TRIF-axis elements\u0026mdash;including TICAM1, TICAM2, TBK1, TRAF6, MAP3K7, and PELI1\u0026mdash;were transcriptionally modulated. Because TRIF signaling downstream of TLR3/4 governs TBK1\u0026ndash;IRF-mediated interferon responses while intersecting with NF-κB via TRAF6\u0026ndash;TAK1 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], regulation at this tier reflects control of signal branching rather than restriction of a single inflammatory output. Consistently, downstream IRF1/IRF3 and interferon-related genes (\u003cem\u003eIFNA1\u003c/em\u003e, \u003cem\u003eIFNB1\u003c/em\u003e, \u003cem\u003eIFNG\u003c/em\u003e, \u003cem\u003eCXCL10\u003c/em\u003e) were selectively modulated. In pathogenic contexts, TRIF-linked signaling can drive high-amplitude interferon activation. For example, Caco-2 cells exposed to \u003cem\u003eE. coli\u003c/em\u003e OMVs exhibited marked upregulation of \u003cem\u003eIFNA1\u003c/em\u003e/\u003cem\u003eIFNB1\u003c/em\u003e alongside TLR3/7/8 activation [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], illustrating the amplification capacity of this branch. Compared with such hyperactivation, the pattern observed here suggests controlled attenuation rather than antiviral shutdown. Similarly, native \u003cem\u003eLactobacillus\u003c/em\u003e spp. have been reported to modulate MYD88-independent transcripts without abolishing immunoregulatory effects, supporting a model of pathway recalibration rather than collapse [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven that several differentially expressed cytokines in our dataset\u0026mdash;including \u003cem\u003eCCL2\u003c/em\u003e, \u003cem\u003eCSF2\u003c/em\u003e, \u003cem\u003eIFNG\u003c/em\u003e, \u003cem\u003eIL12A\u003c/em\u003e, \u003cem\u003eIL2\u003c/em\u003e, and \u003cem\u003eIL6\u003c/em\u003e\u0026mdash;signal through canonical JAK/STAT pathways, the observed transcriptional shifts extend beyond primary TLR activation into secondary cytokine-driven amplification loops. IL-6 primarily activates JAK1/JAK2\u0026ndash;STAT3, whereas IFNγ and IL-12 preferentially engage STAT1 and STAT4, respectively [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Since STAT phosphorylation sustains inflammatory gene transcription, modulation at this level directly influences the persistence of mucosal inflammation. In HT-29 IBD models, probiotic cocktails have been shown to downregulate JAK genes alongside NF-κB components, with concomitant reductions in IL-6 and IL-1β production [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], supporting functional linkage between pathway modulation and cytokine suppression. Similarly, \u003cem\u003eLactobacillus\u003c/em\u003e spp. have been reported to coordinately downregulate JAK genes together with TIRAP and IRAK4 in HT-29 cells, disrupting the TLR\u0026ndash;cytokine\u0026ndash;STAT feed-forward loop [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Because JAK/STAT signaling intersects with NF-κB transcriptional programs in epithelial cells [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], simultaneous modulation of both axes suggests coordinated restriction of inflammatory reinforcement circuits. Consistent with this, prior work on \u003cem\u003eL. brevis\u003c/em\u003e demonstrated regulation of RELA and IKB expression in HT-29 cells [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], indicating that probiotic-derived factors can influence transcriptional regulators upstream of cytokine amplification.\u003c/p\u003e \u003cp\u003eModulation of downstream effector molecules\u0026mdash;including \u003cem\u003eCASP8\u003c/em\u003e, \u003cem\u003eFADD\u003c/em\u003e, \u003cem\u003eEIF2AK2\u003c/em\u003e (PKR), \u003cem\u003ePRKRA\u003c/em\u003e, \u003cem\u003ePPARA\u003c/em\u003e, \u003cem\u003eECSIT\u003c/em\u003e, \u003cem\u003eUBE2N\u003c/em\u003e, and \u003cem\u003eTRAF6\u003c/em\u003e\u0026mdash;further underscores that \u003cem\u003eL. brevis\u003c/em\u003e CFS influences multiple tiers of intracellular signaling architecture beyond proximal adaptor complexes. At the level of ubiquitin-dependent NF-κB regulation, coordinated modulation of TRAF6 and UBE2N is particularly notable. TRAF6 functions as a central E3 ubiquitin ligase within TLR pathways, mediating K63-linked ubiquitination events required for IKK activation and NF-κB nuclear translocation. Recent evidence demonstrates that alterations in TRAF6 protein stability critically influence IBD severity; ASB3-mediated K48-linked polyubiquitination of TRAF6 promotes dysregulated NF-κB activation and intestinal microbiota imbalance [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Therefore, transcriptional regulation of TRAF6 and its associated ubiquitination machinery in our dataset suggests upstream tuning of NF-κB activation thresholds. Consistent with this, modulation of ECSIT further implicates control at the level of ubiquitin-dependent NF-κB activation. ECSIT serves as a TRAF6-interacting scaffold within TLR4 signaling and requires ubiquitination at lysine 372 for effective interaction with p65/p50 NF-κB and nuclear colocalization [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Because ubiquitinated ECSIT facilitates NF-κB DNA-binding activity and pro-inflammatory cytokine production, its regulation implies potential attenuation of nuclear NF-κB transcriptional competence rather than simple cytoplasmic signal restriction. The observed shifts in CASP8 and FADD indicate additional cross-talk between inflammatory and apoptotic signaling nodes. In the context of IBD, epithelial apoptosis and barrier dysfunction contribute directly to mucosal inflammation. Therefore, coordinated regulation of \u003cem\u003eCASP8\u003c/em\u003e/\u003cem\u003eFADD\u003c/em\u003e suggests impact on the epithelial survival\u0026ndash;inflammation balance. Modulation of \u003cem\u003eEIF2AK2\u003c/em\u003e (PKR) and its activator \u003cem\u003ePRKRA\u003c/em\u003e extends this regulatory influence into antiviral and stress-response pathways. Finally, transcriptional regulation of \u003cem\u003ePPARA\u003c/em\u003e introduces a nuclear receptor-mediated anti-inflammatory layer. PPARα exerts inhibitory effects on NF-κB-dependent gene expression and represses inflammatory mediators such as IL-6 and COX-2 [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Collectively, the coordinated modulation of ubiquitination regulators, scaffold proteins, apoptotic mediators, antiviral kinases, and nuclear receptors indicates structured regulation across cytoplasmic, nuclear, and post-translational signaling layers.\u003c/p\u003e \u003cp\u003eThe coordinated modulation of \u003cem\u003eSIGIRR\u003c/em\u003e, \u003cem\u003eSARM1\u003c/em\u003e, and \u003cem\u003eTOLLIP\u003c/em\u003e indicates reinforcement of intrinsic inhibitory checkpoints within the TLR network rather than indiscriminate pathway suppression. These regulators operate at distinct tiers\u0026mdash;TOLLIP at the IRAK level, SIGIRR at receptor complex assembly, and SARM1 at adaptor-routing control\u0026mdash;collectively constraining excessive MYD88-driven amplification. TOLLIP inhibits IRAK activation within the TLR4 cascade. In Caco-2 cells, \u003cem\u003eLactobacillus plantarum\u003c/em\u003e MYL26 induced LPS tolerance via TOLLIP upregulation, impairing TLR4\u0026ndash;NF-κB signaling [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e increased intestinal TOLLIP while reducing TLR4 expression in NEC models [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. This aligns with our observation that TOLLIP modulation accompanies upstream TLR attenuation, suggesting active negative-feedback reinforcement. SIGIRR (TIR8) functions as a decoy receptor limiting IL-1R/TLR signaling. SIGIRR deficiency enhances NF-κB activation and susceptibility to colitis [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Probiotic strains\u0026mdash;including \u003cem\u003eL. brevis\u003c/em\u003e\u0026mdash;have been shown to upregulate SIGIRR in HT-29 cells while suppressing pathogen-induced cytokines [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and \u003cem\u003eBifidobacterium breve\u003c/em\u003e similarly enhanced SIGIRR alongside A20 and Tollip to restrain NF-κB/MAPK activation [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. SARM1 further modulates MYD88\u0026ndash;TRAF signaling dynamics, with recent data indicating that SARM1 regulates MYD88-mediated inflammatory routing [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] and influences intestinal inflammatory responses in IBD models [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Together, the regulation of TOLLIP, SIGIRR, and SARM1 supports a model in which \u003cem\u003eL. brevis\u003c/em\u003e CFS strengthens endogenous braking mechanisms\u0026mdash;limiting NF-κB/MAPK amplification while preserving basal antimicrobial competence.\u003c/p\u003e \u003cp\u003eFunctional stratification of the differentially expressed genes into pathogen-associated response modules revealed structured and non-uniform tuning across microbial sensing axes. Genes linked to bacterial sensing (\u003cem\u003eTLR2\u003c/em\u003e, \u003cem\u003eTLR4\u003c/em\u003e, \u003cem\u003eCD14\u003c/em\u003e, \u003cem\u003eLY96\u003c/em\u003e, \u003cem\u003eRIPK2\u003c/em\u003e), viral recognition (\u003cem\u003eTLR3\u003c/em\u003e, \u003cem\u003eTLR7\u003c/em\u003e, \u003cem\u003eTLR8\u003c/em\u003e, \u003cem\u003eTBK1\u003c/em\u003e, \u003cem\u003eIRF3\u003c/em\u003e, \u003cem\u003eEIF2AK2\u003c/em\u003e), and fungal/parasitic pathways (\u003cem\u003eCLEC4E\u003c/em\u003e, \u003cem\u003eTIRAP\u003c/em\u003e) were differentially regulated rather than globally suppressed. Importantly, antiviral competence appears preserved. In contrast to pharmacologic suppression of the TLR\u0026ndash;TBK1\u0026ndash;IRF3/7 axis, which reduces IFN-α/β transcription [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], our dataset did not demonstrate collapse of interferon-associated mediators. Preservation of TNF expression in our system similarly argues against impaired antibacterial defense. Equally important, no disproportionate IL-10 induction was observed. While \u003cem\u003eLevilactobacillus brevis\u003c/em\u003e IBARAKI-TS3 promotes IL-10 production via TLR2 engagement [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], and \u003cem\u003eL. reuteri\u003c/em\u003e postbiotics shift IL-17/IL-10 balance toward regulation in inflamed HT-29 cells [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], our epithelial dataset did not exhibit excessive regulatory skewing suggestive of compromised vigilance. Barrier preservation provides an additional safeguard; \u003cem\u003eLactobacillus plantarum\u003c/em\u003e prevents tight junction disruption and endotoxemia through EGFR-dependent mechanisms [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Collectively, the differential modulation of pathogen-sensing modules in our system reflects structured immune recalibration rather than generalized immunosuppression.\u003c/p\u003e \u003cp\u003eSeveral limitations warrant consideration. First, the analysis was confined to a targeted RT\u0026sup2; Profiler PCR Array centered on TLR-related genes; although this enables pathway-focused resolution, broader transcriptomic alterations beyond the predefined panel may have been overlooked. Second, our interpretations rely on mRNA-level modulation without parallel protein or functional validation, and transcript changes do not necessarily translate into proportional alterations in protein abundance or signaling activity, particularly for adaptor proteins and transcription factors subject to post-translational regulation. Third, the use of an in vitro HT-29 epithelial model, while providing controlled mechanistic insight, does not fully recapitulate the cellular complexity of the intestinal microenvironment, including immune cell interactions, microbiota dynamics, and barrier architecture. Future studies incorporating protein-level validation and more physiologically relevant in vivo or co-culture systems will be required to confirm the pathway-level inferences proposed here.\u003c/p\u003e \u003cp\u003eIn conclusion, \u003cem\u003eL. brevis\u003c/em\u003e CFS treatment of HT-29 epithelial cells induced coordinated, multi-layer reprogramming of the TLR signaling network rather than isolated cytokine suppression. Remodeling occurred across receptor complexes, adaptor routing, kinase tiers, JAK/STAT amplification loops, and intrinsic inhibitory checkpoints, collectively indicating structured attenuation of inflammatory signal propagation at multiple upstream nodes. Importantly, this pattern does not represent global immunosuppression. Interferon-associated pathways remained transcriptionally competent, TNF signaling was not pathologically suppressed, and IL-10 did not display disproportionate induction. Instead, pathogen-specific sensing modules were differentially tuned, suggesting preserved antiviral and antibacterial capacity alongside constrained inflammatory amplification. Together, these findings support a mechanistic model in which probiotic-derived metabolites recalibrate epithelial immune thresholds through signal gating and reinforcement of endogenous regulatory circuits. Such multi-tier modulation may represent a rational strategy for restoring mucosal immune balance in IBD-associated inflammation without compromising core host defense functions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatement of Ethics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study did not involve human participants, animal experiments, or clinical samples. All procedures were conducted using established human cell lines (HT-29) obtained from the Pasteur Institute of Iran, and therefore ethical approval was not required according to institutional and national guidelines.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBTK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBruton agammaglobulinemia tyrosine kinase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCASP8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCaspase 8, apoptosis-related cysteine peptidase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCCL2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChemokine (C-C motif) ligand 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCD14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCD14 molecule\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCD180\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCD180 molecule\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCD80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCD80 molecule\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCD86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCD86 molecule\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCHUK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eConserved helix-loop-helix ubiquitous kinase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCLEC4E\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eC-type lectin domain family 4, member E\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCSF2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eColony stimulating factor 2 (granulocyte-macrophage)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCSF3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eColony stimulating factor 3 (granulocyte)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCXCL10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eChemokine (C-X-C motif) ligand 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eECSIT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eECSIT homolog (Drosophila)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEIF2AK2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEukaryotic translation initiation factor 2-alpha kinase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eELK1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eELK1, member of ETS oncogene family\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFADD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eFas (TNFRSF6)-associated via death domain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFOS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eFBJ murine osteosarcoma viral oncogene homolog\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHMGB1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh mobility group box 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHRAS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eV-Ha-ras Harvey rat sarcoma viral oncogene homolog\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHSPA1A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHeat shock 70kDa protein 1A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHSPD1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHeat shock 60kDa protein 1 (chaperonin)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIFNA1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterferon, alpha 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIFNB1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterferon, beta 1, fibroblast\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIFNG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterferon, gamma\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIKBKB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInhibitor of kappa light polypeptide gene enhancer in B-cells, kinase beta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIL10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIL12A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 12A (natural killer cell stimulatory factor 1, cytotoxic lymphocyte maturation factor 1, p35)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIL1A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 1, alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIL1B\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 1, beta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIL2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIL6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 6 (interferon, beta 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCXCL8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin 8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIRAK1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin-1 receptor-associated kinase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIRAK2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin-1 receptor-associated kinase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIRAK4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterleukin-1 receptor-associated kinase 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIRF1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterferon regulatory factor 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eIRF3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInterferon regulatory factor 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eJUN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eJun proto-oncogene\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLTA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLymphotoxin alpha (TNF superfamily, member 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLY86\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLymphocyte antigen 86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eLY96\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLymphocyte antigen 96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAP2K3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase kinase 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAP2K4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase kinase 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAP3K1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase kinase kinase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAP3K7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase kinase kinase 7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAP4K4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase kinase kinase kinase 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAPK8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase 8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMAPK8IP3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMitogen-activated protein kinase 8 interacting protein 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMYD88\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMyeloid differentiation primary response gene (88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNFKB1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNuclear factor of kappa light polypeptide gene enhancer in B-cells 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNFKB2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (p49/p100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNFKBIA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNFKBIL1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-like 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNFRKB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNuclear factor related to kappaB binding protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNR2C2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNuclear receptor subfamily 2, group C, member 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePELI1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePellino homolog 1 (Drosophila)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePPARA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePeroxisome proliferator-activated receptor alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePRKRA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eProtein kinase, interferon-inducible double stranded RNA dependent activator\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePTGS2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eProstaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and cyclooxygenase)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eREL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eV-rel reticuloendotheliosis viral oncogene homolog (avian)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRELA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eV-rel reticuloendotheliosis viral oncogene homolog A (avian)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRIPK2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eReceptor-interacting serine-threonine kinase 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSARM1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSterile alpha and TIR motif containing 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSIGIRR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eSingle immunoglobulin and toll-interleukin 1 receptor (TIR) domain\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTAB1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTGF-beta activated kinase 1/MAP3K7 binding protein 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTBK1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTANK-binding kinase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTICAM1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor adaptor molecule 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTICAM2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor adaptor molecule 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTIRAP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-interleukin 1 receptor (TIR) domain containing adaptor protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTLR9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll-like receptor 9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTNF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTumor necrosis factor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTNFRSF1A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTumor necrosis factor receptor superfamily, member 1A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTOLLIP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eToll interacting protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTRAF6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTNF receptor-associated factor 6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eUBE2N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eUbiquitin-conjugating enzyme E2N\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eACTB\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eActin, beta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eB2M\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eBeta-2-microglobulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGAPDH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGlyceraldehyde-3-phosphate dehydrogenase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eHPRT1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHypoxanthine phosphoribosyltransferase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRPLP0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRibosomal protein, large, P0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRTC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eReverse Transcription Control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePositive PCR Control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of Interest\u003c/h2\u003e \u003cp\u003eAuthors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCRediT authorship contribution statement\u003c/h2\u003e \u003cp\u003eAlireza Moghanlou ([email protected]): Data curation. Shima Rasouli ([email protected]): Writing \u0026ndash; original draft. Sheyda Asadi ([email protected]) : Investigation. Sarvenaz Falsafi ([email protected]): Investigation. Behrouzi Ava ([email protected]): Writing \u0026ndash; original draft.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors declare that no funds, grants, or other support was received during the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eData curation: A.M. \u0026amp; A.B. \u0026amp; S.R.Investigation: S.A. \u0026amp; S.F.Writing \u0026ndash; original draft: A.B. \u0026amp; S.R.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBruner LP, White AM, Proksell S (2023) Inflammatory Bowel Disease. Prim Care 50(3):411\u0026ndash;427\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdolph TE, Meyer M, Schwarzler J, Mayr L, Grabherr F, Tilg H (2022) The metabolic nature of inflammatory bowel diseases. Nat Rev Gastroenterol Hepatol 19(12):753\u0026ndash;767\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang R, Li Z, Liu S, Zhang D (2023) Global, regional and national burden of inflammatory bowel disease in 204 countries and territories from 1990 to 2019: a systematic analysis based on the Global Burden of Disease Study 2019. BMJ Open 13(3):e065186\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen L, Zhang L, Hua H, Liu L, Mao Y, Wang R (2024) Interactions between toll-like receptors signaling pathway and gut microbiota in host homeostasis. Immun Inflamm Dis 12(7):e1356\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiambra V, Pagliari D, Rio P, Totti B, Di Nunzio C, Bosi A et al (2023) Gut Microbiota, Inflammatory Bowel Disease, and Cancer: The Role of Guardians of Innate Immunity. Cells. ;12(22)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbraham C, Abreu MT, Turner JR (2022) Pattern Recognition Receptor Signaling and Cytokine Networks in Microbial Defenses and Regulation of Intestinal Barriers: Implications for Inflammatory Bowel Disease. Gastroenterology 162(6):1602\u0026ndash;1616 e6\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTan Y, Zou KF, Qian W, Chen S, Hou XH (2014) Expression and implication of toll-like receptors TLR2, TLR4 and TLR9 in colonic mucosa of patients with ulcerative colitis. 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Faseb j 32(11):fj201800351R\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"probiotics-and-antimicrobial-proteins","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"paap","sideBox":"Learn more about [Probiotics and Antimicrobial Proteins](http://link.springer.com/journal/12601)","snPcode":"12602","submissionUrl":"https://submission.nature.com/new-submission/12602/3","title":"Probiotics and Antimicrobial Proteins","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Lactobacillus brevis, postbiotics, Toll-like receptor (TLR) signaling, MyD88, TRIF, NF-κB, HT-29 intestinal epithelial cells, inflammatory bowel disease (IBD)","lastPublishedDoi":"10.21203/rs.3.rs-9542241/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9542241/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDysregulated Toll-like receptor (TLR) signaling in intestinal epithelial cells contributes to persistent mucosal inflammation in inflammatory bowel disease (IBD). Although \u003cem\u003eLactobacillus brevis\u003c/em\u003e has demonstrated anti-inflammatory potential, the pathway-level mechanisms by which its secreted metabolites influence epithelial innate immune signaling remain insufficiently characterized. This study investigated \u003cem\u003eL. brevis\u003c/em\u003e cell-free supernatant (CFS) TLR-mediated inflammatory signaling modulation while preserving epithelial immune competence.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHT-29 human intestinal epithelial cells were treated with 50% \u003cem\u003eL. brevis\u003c/em\u003e CFS following viability assessment using MTT assay. Transcriptional profiling of 84 key genes involved in the TLR signaling pathway was performed using the RT\u0026sup2; Profiler\u0026trade; PCR Array. Differential gene expression was analyzed using the ΔΔCt method, and pathway-level mapping was conducted to evaluate coordinated modulation across MyD88- and TRIF-dependent branches.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTreatment with \u003cem\u003eL. brevis\u003c/em\u003e CFS significantly enhanced HT-29 cell viability and induced a structured transcriptional reprogramming of the TLR signaling network. Core components of the MyD88-dependent pro-inflammatory axis\u0026mdash;including \u003cem\u003eTLR2\u003c/em\u003e, \u003cem\u003eTLR4\u003c/em\u003e, \u003cem\u003eMYD88\u003c/em\u003e, \u003cem\u003eIRAK1/4\u003c/em\u003e, \u003cem\u003eMAP3K7\u003c/em\u003e, \u003cem\u003eNFKB1\u003c/em\u003e, and downstream cytokines (\u003cem\u003eIL1A, IL1B, IL6, IL12A, CCL2\u003c/em\u003e)\u0026mdash;were significantly downregulated. Concurrent attenuation of TRIF-dependent signaling was observed through modulation of \u003cem\u003eTLR3\u003c/em\u003e, \u003cem\u003eTICAM1\u003c/em\u003e, \u003cem\u003eTBK1\u003c/em\u003e, \u003cem\u003eIRF3\u003c/em\u003e, and \u003cem\u003eCXCL10\u003c/em\u003e. Importantly, selective preservation of immune-associated mediators and absence of exaggerated \u003cem\u003eIL-10\u003c/em\u003e induction indicated maintained basal immune competence rather than global immunosuppression.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eL. brevis\u003c/em\u003e CFS induces multi-tier recalibration of TLR-mediated inflammatory signaling in intestinal epithelial cells. By attenuating upstream adaptor and kinase modules while preserving essential immune responsiveness, \u003cem\u003eL. brevis\u003c/em\u003e-derived metabolites promote controlled inflammatory tuning rather than indiscriminate immune suppression. These findings support a mechanistic basis for postbiotic-mediated modulation of epithelial innate immunity relevant to IBD-associated inflammation.\u003c/p\u003e","manuscriptTitle":"Lactobacillus brevis Cell-Free Supernatant Recalibrates TLR-Mediated Inflammatory Signaling While Preserving Immune Competence in HT-29 Intestinal Epithelial Cells","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-07 12:41:36","doi":"10.21203/rs.3.rs-9542241/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T20:18:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T20:00:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T12:36:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95453465710803383460300409071488540994","date":"2026-05-07T14:10:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"174746599583691785147391265011250931245","date":"2026-05-06T01:24:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"257844918062518527564554170861153451065","date":"2026-05-05T15:31:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218847317770687033863966175687351092836","date":"2026-05-05T11:11:05+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-28T13:59:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-28T05:11:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-28T05:10:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Probiotics and Antimicrobial Proteins","date":"2026-04-27T12:59:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"probiotics-and-antimicrobial-proteins","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"paap","sideBox":"Learn more about [Probiotics and Antimicrobial Proteins](http://link.springer.com/journal/12601)","snPcode":"12602","submissionUrl":"https://submission.nature.com/new-submission/12602/3","title":"Probiotics and Antimicrobial Proteins","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9fcad3f8-6f28-4ab2-a95d-3cfa901196c6","owner":[],"postedDate":"May 7th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T20:18:22+00:00","index":194,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T20:00:30+00:00","index":193,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T12:36:03+00:00","index":192,"fulltext":""},{"type":"reviewerAgreed","content":"95453465710803383460300409071488540994","date":"2026-05-07T14:10:18+00:00","index":184,"fulltext":""},{"type":"reviewerAgreed","content":"174746599583691785147391265011250931245","date":"2026-05-06T01:24:36+00:00","index":177,"fulltext":""},{"type":"reviewerAgreed","content":"257844918062518527564554170861153451065","date":"2026-05-05T15:31:53+00:00","index":172,"fulltext":""},{"type":"reviewerAgreed","content":"218847317770687033863966175687351092836","date":"2026-05-05T11:11:05+00:00","index":157,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-07T12:41:36+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-07 12:41:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9542241","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9542241","identity":"rs-9542241","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}