DnaK of Parvimonas micra OMVs interacted with the host fibroblast Bag3-IKK-γ axis to accelerate TNF-α secretion in oral lichen planus

DnaK of Parvimonas micra OMVs interacted with the host fibroblast Bag3-IKK-γ axis to accelerate TNF-α secretion in oral lichen planus | 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 DnaK of Parvimonas micra OMVs interacted with the host fibroblast Bag3-IKK-γ axis to accelerate TNF-α secretion in oral lichen planus Xiaoli Ji, Mengfan Zhi, Xiufeng Gu, Ying Han, Xiang Lan, lixiang Song, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4578173/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jul, 2025 Read the published version in Microbiome → Version 1 posted 10 You are reading this latest preprint version Abstract Background Oral lichen planus (OLP) is one of the most frequent oral mucosal diseases associated with chronic inflammation despite extremely insufficient knowledge of its pathogenic mechanism. Results Here, the microbiome of buccal and lip mucosae, tongue dorsum and saliva among OLP patients and healthy individuals was analyzed. It was found that the oral microbiome, especially the buccal mucosa, varied significantly in OLP patients. Network, random forest and Netshift analyses simultaneously showed that Parvimonas micra ( P. micra ) was an important bacterium of OLP disease. Fluorescence in situ hybridization (FISH) and single-cell ribonucleic acid (RNA) sequencing profiling suggested that fibroblasts were the candidate target with the characteristic of up-regulating the nuclear factor kappa-B (NF-қB) signaling pathway related to tumor necrosis factor-alpha (TNF-α) and communicating with multiple immune cell types. Mechanism analysis showed that P. micra , P. micra- derived conditional medium (CM) and outer membrane vesicles (OMVs) could induce the activity of NF-қB signaling pathway and inhibit autophagy in buccal mucosal fibroblasts. As one of the main pathogenic effectors, the DnaK of P. micra- derived OMVs could inhibit autophagy and promote TNF-α secretion via the DnaK-Bcl-2 associated athanogene 3 (Bag3)-inhibitor of nuclear factor kappa-B kinase subunit gamma (IKK-γ) signaling axis. Conclusions Here we demonstrate that P. micra ’s OMV drives OLP via DnaK -Bag3-IKK-γ/NF-қB signaling axis in the fibroblasts as new insights into the pathogenic mechanism of OLP. Oral lichen planus DnaK Bag3 Outer membrane vesicles NF-κB Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Oral lichen planus (OLP) is one of the most common oral mucosal disease associated with chronic inflammation, affects up to 0.89% of the general population [ 1 , 2 ]. It most commonly leads to significant roughness, discomfort and pain, which rarely undergo spontaneous remission with a high tendency for malignant transformation [ 3 , 4 ]. The initiation and progression of OLP have no definitive and complex interaction between psychological factors, immunological factors, endocrine disorders, psychological factors and genetic factors [ 5 ]. Growing evidence indicates the possibly essential role of the oral microbiome in the etiology of OLP [ 6 ]. Next generation sequencing-based microbiome studies showe d that microbes from the saliva and lesions of OLP were varied from those of healthy individuals. For instance, the abundance of Porphyromonas, Solobacterium Capnocytophaga and Gemella exhibited a significant increase in OLP patients, whereas Haemophilus, Corynebacterium, Cellulosimicrobium and Campylobacter demonstrated a dramatic decrease. Porphyromonas was correlated to salivary interleukin (IL)-17 and IL-23 [ 7 – 10 ]. Regarding the contribution of the oral microbiome to OLP development, studies showed that oral pathogenic bacteria could invade OLP tissues [ 11 ], destroy the integrity of the oral mucosal epithelium barrier and facilitate the entry of more bacteria [ 7 ], followed by their aggregation in the lamina Apropria and the epithelial basal layer [ 6 ]. Fibroblasts, a main cellular component of the lamina propria [ 12 ], are important cellular targets of microbiome [ 13 ]. With the initiation and progression of OLP, fibroblasts could acquire an activated inflammatory phenotype via the release of cytokines and play a key role in the pathogenesis of inflammatory diseases like vitiligo whose pathogenesis is similar to that of OLP [ 12 – 15 ]. Research showed that OLP fibroblasts (OLPFs) could secrete IL-6, IL-8, tumor necrosis factor-alpha (TNF-α) and other inflammation-related cytokines in response to Porphyromonas gingivalis lipopolysaccharide [ 16 ]. The increased level of chemokine (C-C motif) ligand 5 (CCL5) from OLPFs promoted the proliferation and migration of cluster of differentiation 4 T helper (CD4 + T) cells and contributed to the disease process of OLP [ 17 ]. Also, fibroblasts secreted IL-6 enhancing the angiogenesis of OLP [ 18 ]. Currently, how fibroblasts interact with pathogenic oral microbes to promote the pathogenesis of OLP has been undervalued. In this study, the microbial profiles of buccal and lip mucosae, tongue dorsum and saliva in on-erosive/erosive-OLP (NE/E-OLP) patients and healthy controls were compared. A series of potential oral bacteria dramatically enriched in OLP patients’ buccal mucosae were identified. One significantly enriched bacterium, Parvimonas micra ( P. micra ), was validated in the buccal mucosae of OLP patients. A mechanism study of P. micra and OLPFs was carried out, which identified the main pathogenic effector in P. micra and revealed the cellular receptors, downstream regulators and pathways in fibroblasts. This study demonstrates that oral pathogenic microbes play a part in the pathogenesis of OLP. Materials and methods Sample collection The study earned the approval of the Ethics Committee of the School and Hospital of Stomatology, Shandong University (No. GR201702). The inclusion criteria of the patients were as follows: 1) Patients aged 18–60; 2) Patients without severe periodontal disease, untreated caries, endodontic and system diseases; 3) Patients without smoking habits; 4) Patients without taking antibiotics, antiviral drugs and glucocorticoid in six months; 5) Patients satisfying the histopathological and clinical diagnostic criteria of OLP [ 19 , 20 ]; 6) Patients with lesions only located on the buccal mucosa of both cheeks; 7) Patients signing informed consent to participate. Participants were not allowed to drink and eat within at least 2 hours before the collection between 8:00 and 11:00 a.m. Mouth swabs were collected from each buccal mucosa, lip mucosa, tongue dorsum and saliva using sterile swabs. Two hours after a meal, no saliva was stimulated by rinsing the mouth five times with sterile double-distilled water and allowing for the natural flow of saliva into an Eppendorf tube. All the samples were gathered with the sterile Eppendorf tube and stored at the temperature of -80°C. VAS score were obtained before treatment .The scale is divided from 0 to 10, with 0 being minimum level of pain and 10 being maximum level of pain [ 21 ]. CD3 + T cells, CD4 + T cells and CD8 + T cells were sorted with flow cytometry (FCM) from blood of OLP patients. Generation and analysis of microbiome data The hexadecyltrimethy lammonium bromide/sodium dodecyl sulfate (CTAB/SDS) method was employed to extract deoxyribonucleic acid (DNA) from samples. After the genomic DNA of all the samples was extracted, polymerase chain reaction (PCR) amplifications were performed. The V3-V4 hypervariable regions of the 16S ribosomal ribonucleic acid (rRNA) gene were amplified by the use of specific primers (341F: CCTAYGGGRBGCASCAG, 806R: GGACTACHVGGGTWTCTAAT). All PCRs were performed in 30-µL reactions with 15 µL of Phusion® High-Fidelity PCR Master Mix (Thermo, Waltham, Massachusetts (MA), the United States of America (USA)). A GeneJET Gel Extraction Kit (Thermo Scientific) was used for purifying PCR products that were analyzed by electrophoresis on 2% agarose gels. Samples with strong and clear bands were selected for further analysis, followed by the sequencing of the library on an Illumina HiSeq 2500 platform. Paired-end HiSeq 2500 sequencing reads were amalgamated with sequence tags following the overlap relationship between reads and passed the quality control (QC) test with UPARSE [ 22 ]. The filtering of poor-quality reads and chimaeras was realized by the USEARCH1 pipeline. After dereplication, clean reads were clustered into multiple operational taxonomy units (OTUs) with similarities above 97%. The representative reads of OTUs were aligned to the Ribosomal Database Project (RDP, release 18) to obtain a clear taxonomy of the microbiome. The metrics for the quantification of the core microbiome include abundance cutoff values (0.001) and minimum occupancy values (90%). The Adonis2 method from the “vegan” package was used to probe into the association between host OLP grouping and the microbiome of four oral niches. The α and beta (β) diversity distance matrices were computed using USEARCH11, with a minimum depth threshold of 36,000. Principal co-ordinates (PCoA) analysis was conducted, to assess differences in complexity based on Bray Curtis distance. Differences among healthy and OLP groups were tested using multivariate association with linear models (MaAsLin2) analysis. Effects of age and gender were adjusted. The remaining species or genera were chosen if the p-value was below 0.05. The intersection of differences between the healthy and the other two groups was selected for follow-up analysis. In addition, K-means clustering analysis was carried out for the grouping of differently distributed differential microbes at the buccal mucosa. Those differently distributed microbial species and genera at the buccal mucosa were clustered into three clusters by the similarity of their abundant-variation patterns and named clusters 1–3. After that, Spearman correlation analysis was utilized to determine the interrelationships between clusters in different groups (|Spearman correlation| ≥ 0.45, p-value < 0.05). Later, random forest analysis (version 4.7–1.1) was used to test the classification effect of these different microbes. Spearman correlation analysis was performed to determine the interrelationships between P. micra and other differential microbes. The NetShift method available at ( https://web.rniapps.net/netshift ) was used for identifying “driver” nodes in the network of microbial relationships between healthy and diseased groups. Cytoscape (version 3.7.1) and Gephi (version 0.9.2) were applied to draw the network diagram. Additionally, “ggplot2” (version 3.4.0) and “ComplexHeatmap” (version 2.16.0) were adopted to generate additional figures. Fluorescence in situ hybridization Fluorescence in situ hybridization (FISH) was done on the 5 µm formalin-fixed paraffin-embedded tissue sections of normal buccal mucosae and OLP tissues (buccal mucosae). The sections were incubated for 30 minutes in a pre-heated oven at 60°C and then 20 minutes in a xylene solution. Subsequently, they were immersed in gradient alcohol (100%, 95%, 90%, 80% and 70%; one minute each) and washed four times with phosphate buffered solution (PBS). The FISH procedure was performed as per the instructions of the manufacturer (GenePharma, Suzhou, China). The sequence of P. micra for Cyanine 3 (cy3) labeled FISH probes was CTG AGC GTC AGT AAA AGT CC [ 23 ]. The slides were rinsed with 4',6-diamidino-2-phenylindole (DAPI) and visualized under confocal laser scanning microscopes (CLSMs). The images were captured with Image-pro plus 6.0 (Media Cybernetics, Inc., in Rockville, Maryland (MD), the US). Single-cell RNA-sequencing analysis The 10× single-cell RNA-sequencing (scRNA-seq) data containing one normal mucosa sample and five OLP samples were acquired from the Gene Expression Omnibus (GEO) database (GSE211630). They were transformed into S eurat objects by use of the R software “Seurat” package (version 5.0.1). The double cells were removed with the “DoubletFinder” package (version 2.0.3). Counts were controlled via the exclusion of low-quality cells based on mitochondrial gene percentages and cycle gene scores. The “FindVariableFeatures” function was harnessed to screen the first 2,000 highly variable genes. Downscaling and cluster identification were completed using principal component analysis (PCA) based on 2,000 genes and Uniform Manifold Approximation and Projection (UMAP). All the samples were integrated with the “RunHarmony” function. The “FindAllMarkers” function was used for identifying significant marker genes within various clusters by setting log2FC to 1. Cluster annotation analysis was conducted based on the literature review of cluster markers. According to the gene family clustering results of fibroblasts, differential genes and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed between normal and OLP tissues with p.adjust 2 (FindMarkers and pathview version 1.38.0 clusterProfiler version 4.7.1.001). The cellular communication of cell subsets was conducted with CellChat (version 1.6.1). Bacterial strains and growth conditions P. micra strain ATCC 33270 was obtained from the American Type Culture Collection (Manassas, Virginia (VA), the USA) and cultured in heart (5 g/L) and brain extracts (12.5 g/L), proteose peptone (10.0 g/L), glucose (2.0 g/L), sodium chloride (NaCl, 2.0g/L) and disodium hydrogen phosphate (Na 2 HPO 4 , 2.5 g/L) at 37˚C under anaerobic conditions with 90% nitrogen (N 2 ), 5% hydrogen (H 2 ), and 5% carbon dioxide (CO 2 ). Isolation of normal and OLP fibroblasts Buccal mucosal tissues were acquired from 16 donors (Eight were pathologically confirmed as buccal mucosa OLP and eight were normal buccal mucosal tissues) at the School and Hospital of Stomatology, Shandong University. Tissues were treated by dispase (2 mg/ml, Sigma-Aldrich, Darmstadt, Germany) and rinsed in PBS. Then, they were cut into pieces with a size of 1 mm 3 and cultured in a T25 flask with α-minimum essential medium (α-MEM; Gibco, Washington, the USA) containing 10% fetal bovine serum (FBS; Gibco, Washington, the USA) and 1% penicillin-streptomycin at 37°C in a humidified atmosphere with 5% CO 2 . The purpose was to obtain fibroblasts (Passages 3–5 were utilized for sequent experiments). All the patients signed an informed consent form. The present study won the approval of the Ethics Committee of the School and Hospital of Stomatology, Shandong University (NO. GR201702). Isolation and identification of outer membrane vesicles Outer membrane vesicles (OMV) were isolated from the above cultures with an optical density at 600 nm (OD600) of 0.1 at 37°C for 48 hours. The cultures were pelleted with a centrifuge (7,800 g, 4°C, 20 minutes) and filtered with a 0.22 um filter membrane. The filtered supernatant was concentrated using 100 kd ultrafiltration tubes and collected by a Beckman Optima XPN-100 ultracentrifuge (292,700g, 4 ℃, 1 hour). After the removal of the supernatant, OMVs were re-suspended in 200 µl sterile PBS and normalized to an equivalent protein concentration with a bicinchoninic acid (BCA) assay kit (cwbiotech, Beijing, China). The scanning electron microscope images of OMVs were taken by scanning electron microscopy. The diameter of OMVs was quantified using a Nano Sight LM10 instrument (Malvern, Westborough, MA). The fluid of OMVs was analyzed by high-performance liquid chromatography-mass spectrography (HPLC-MS, UltiMate3000). Screening potential effector proteins of P. micra The FASTA protein sequences of P. micra ATCC33270 were downloaded from the National Center for Biotechnology Information (NCBI, https://www.ncbi.nlm.nih.gov/ ). Then, they were aligned using Virulence Factors of Pathogenic Bacteria (VFDB, http://www.mgc.ac.cn/VFs/ ) and Pathogen-Host Interactions (PHI, http://www.phibase.org/index.jsp ) database. The BUSCA tool ( http://busca.biocomp.unibo.it ) was used to predict subcellular localization. Cloning of recombinant DnaK in Escherichia coil The genomic DNA of P. micra was used to clone the DnaK gene into Escherichia coil ( E. coil ) expression vector pET-28a. The primers are 5‘-GTGCCGCGCGGCAGCCATATGATGTCAAAAATTATAGGTATTGATTTAGGTAC-3’ and 3‘-ACGGAGCTCGAATTCGGATCCCTATTTATTTTCATCTTCGTCAACTACTTC-5‘. Recombinant DnaK was generated and purified as a histidine (His)-tag protein in the pET-28a vector. pET-28a containing DnaK was expressed in E. coil cells with 0.4 mM Isopropyl-β- D-thiogalactoside at 37 ℃ for 4 hours until OD600 reached 1. The protein was purified in hydroxymethyl (Tris)–NaCl buffer, followed by its overnight dialysis against the dialysis buffer (10 mM Tris–hydrogen chloride (HCl) Pondus hydrogenii (pH) 8.0, 150 mM NaCl, 10% glycerol, 0.001% sarcosyl). The purified protein was concentrated using 30 kd ultrafiltration tubes and checked with SDS-polyacrylamide gel electrophoresis (PAGE). Localization of DnaK in OMVs DnaK or OMVs and 0.05 µg/µl proteinase K (cwbiotech, Beijing, China) (able to degrade DnaK) or 0.1% Triton X-100 (cwbiotech, Beijing, China) (able to punch on cell membranes) were incubated at 37 ℃ for 10 minutes and then added with 5 mM Phenylmethanesulfonyl fluoride (PMSF) (cwbiotech, Beijing, China) at room temperature for 10 minutes. Afterwards, the samples were heated at 70 ℃ for 5 minutes to suppress protein K. Untreated DnaK and OMVs were used as control groups. Enzyme-linked immunosorbent assay Normal fibroblasts (NFs), OLPFs, P. micra (6.875 × 10 7 ) treated NFs (The ratio of P. micra and NFs was 50:1) or P. micra conditional medium (CM, 20 µl, an optical density at the wavelength 600 nm of 1 OD = 1 was equivalent to 7.2 x 10 7 /mL ( P. micra ) ) treated NFs (The ratio of P. micra and NFs was 50:1), OMV (10 µg/uL) treated NFs, lentivirus-green fluorescent protein (GFP)-DnaK (lv-GFP-DnaK) or lentivirus-Flag-DnaK (lv-DnaK) and lentivirus-control in PCDNA3.1 (Wzbio, Jinan, China), Bcl-2 associated athanogene 3 (Bag3)-targeting small interfering RNA (siRNA) in lv-DnaK (si-Bag3) (S: CAGCAACCUUGAAGCAGAUTT; AS: AUCUGCUUCAAGGUUGCUGTT), inhibitor of nuclear factor kappa-B kinase subunit gamma (IKK-γ)-targeting siRNA (si-IKK-γ) in lv-DnaK (S: UGGAGAAGCUCGAUCUGAATT; AS: UUCAGAUCGAGCUUCUCCATT) and scrambled non-targeting control siRNA (si-control) treated with none or Bafilomycin A1 (BafA1, 5 nM) (The number of the above fibroblasts was 1.375 × 10 6 ) were plated at in complete medium (13.75 ml) in a 10-cm plate for 2 days for the generation of CM. The CM was gathered via a 0.2 µM filter and stored at the temperature of -80°C. The CM concentration of TNF-α was measured by enzyme-linked immunosorbent assay (ELISA, BioLegend, California, the USA) as per the instructions of the manufacturer. Western blot assay The proteins of NFs, OLPFs, P. micra treated NFs or P. micra CM treated NFs, OMV treated NFs, lv-DnaK, si-Bag3, si-IKK-γ and scrambled non-targeting control siRNA (si-control) treated with none or BafA1 (5 nM) were obtained with Radio Immunoprecipitation Assay (RIPA) buffer. Equal amounts of proteins were resolved by 10% SDS-PAGE [ 24 ] and immunoblotted with primary antibodies against many antigens overnight. These antigens included microtubule-associated protein 1 light chain 3 beta (LC3B), phosphorylated inhibitory subunit of NF kappa B alpha (p-Iκβα), total-Iκβα (CST, California, the USA), DnaK, p-p65, total-p65, IKK-γ (Abcam, Cambridge, England), Bag3, sequestosome 1 (SQSTM1, Proteintech, Wuhan, China) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH, Affinity, Ohio, the USA). These equal amounts of proteins were then incubated with the horseradish peroxidase (HRP)-conjugated secondary antibodies (Affinity, Ohio, the USA). Immunoreactive bands were analyzed by enhanced chemiluminescence reaction (ECL, Amersham Pharmacia Biotech, the USA) and normalized by GAPDH with Quantity One. mCherry-GFP-LC3B NFs, OLPFs, OMV treated NFs, lv-DnaK, si-Bag3 and si-IKK-γ were transfected with mCherry-GFP-LC3B adenovirus (Wzbio, Jinan, China). The cell nucleus was counterstained using DAPI. Images were captured for autophagosomes and autolysosomes (yellow and red puncta, respectively) on CLSMs. Image-pro plus 6.0 was used to analyze fluorescence signals. Immunofluorescence histochemistry NFs, NFs treated with OMVs, lv-DnaK or stably expressing enhanced GFP (EGFP)-LC3B were seeded in 12-well plates with sections for one night and fixed with 4% paraformaldehyde. The sections were processed with 3.0% hydrogen peroxide, followed by their incubation in 5.0% bovine serum albumin. Besides, they underwent overnight incubation at 4°C with antibodies against pkh67 (maokangbio, Shanghai, China), β-Tubulin (CST, California, the USA), Bag3 and IKK-γ, and then 1-hour incubation with Alexa Fluor 488/594-labelled goat anti-mouse/rabbit immunoglobulin G (IgG) (Abbkine, California, the USA) at 37°C in the dark. The images were captured with a laser scanning confocal microscope. Protein pull-down His-DnaK and NF suspended cell fluid was incubated in PBS at 4 ℃ for 1 hour. After complete binding, the bound proteins were immunoprecipitated by the instructions of PierceTM Pull-Down PolyHis Protein: Protein Interaction Kit (Thermo Fisher Scientific, New York, the USA) and analyzed by HPLC-MS (UltiMate3000). Co-immunoprecipitation The lysates of lv-Flag-DnaK, si-Bag3 and si-IKK-γ were processed by Nonidet P-40 (NP-40) buffer. They underwent overnight incubation at 4°C with DnaK or Bag3, IKK-γ, Flag (Proteintech, Wuhan, China) and normal IgG (Santa, California, USA) with rotation. Protein A/G PLUS agarose beads (Santa, California, the USA) underwent 1-hour incubation and rotation at 4°C. The complexes were washed and eluted from the beads through boiling in the SDS-PAGE sample. The immunoprecipitates were analyzed by Western blotting with DnaK or Bag3, IKK-γ and Flag. Statistical analysis Data were presented as the mean ± standard deviation (SD) and repeated three times. Student’s t-test or one- or two-way analysis of variance (ANOVA) was used to analyze inter-group comparisons. In addition, p ≤ 0.05 was considered to show the statistical significance that was analyzed using Statistical Package for the Social Sciences (SPSS) software version 17.0. Results Variation of the oral microbiome in OLP patients To reveal the variation of the oral microbiome in OLP patients, 704 samples of buccal mucosae, tongue dorsum, lip mucosae and saliva from 80 healthy individuals and 91 OLP patients (including 50 NE-OLP and 41 E-OLP patients) in Shandong Province, China (Tab.S1) were included. The clinical indicators and blood-derived CD3+, CD4 + and CD8 + T cells for each OLP patient were collected (Tab.S1). The 16S rRNA amplicon sequencing (CRA 003224) obtained 58.56 million clean reads (Fig. S1 A), which were annotated to 44 phyla, 976 genera and 1,138 species. The saturation of microbiome data at each oral site was illustrated in the rarefaction curves (Fig. S1 A). At the phylum level, Firmicutes, Proteobacteria and Bacteroidetes were the most enriched microorganisms across all the oral sites in the population of this study, but the ranking of their abundance varied across oral sites. In healthy individuals, for example, Firmicutes had the highest abundance in buccal and lip mucosae, while Bacteroidetes and Proteobacteria were mostly enriched in the tongue dorsum and saliva, respectively (Fig. 1 A). However, their abundance was significantly influenced by NE-OLP and E-OLP diseases (Fig. 1 A). At the genus level, Streptococcus, Haemophilus, Neisseria and Rothis were in high abundance at each oral site, but the ranking of their abundance was also affected by oral sites and OLP disease (Fig. 1 B). The Adonis analysis of Bray-Curtis and Jaccard distances simultaneously showed that the microbiome of buccal and lip mucosae, tongue dorsum and saliva was significantly correlated with OLP disease (Fig. 1 C,E). Among them, the buccal mucosa was the site mostly correlated with oral sites. Simpson and Shannon indices revealed that NE-OLP and E-OLP patients showed a significantly higher microbial diversity of the buccal mucosa compared with healthy individuals (Fig. 1 D). The microbiome at the lip mucosa and saliva showed the same trend, and the tongue dorsum increased in abundance despite being insignificant (Fig. S1 C,D). The core microbiome of the buccal mucosa at the genus level with occurrence rate ≥ 90% and relative abundance ≥ 0.001 was analyzed, and 18 core microorganisms were found in all populations. Meanwhile, it was found that seven microorganisms, including Parvimonas, Tannerella, Treponema , etc., were enriched in OLP patients with high frequency and abundance (Fig. S1 B). At the species level, 22 microbes exhibited high abundance in the whole population. Among them, eight microbes were core bacteria in OLP patients, including the periodontal pathogen Tannerella forsythia and P. micra (Fig. 1 F). β diversity analysis revealed that the microbial composition of the buccal mucosal of NE-OLP and E-OLP patients greatly differed from that of healthy individuals, especially the first principal component, 20.2% by Bray Curtis Distance and 14.1% by Jaccard distance (Fig. 1 F). The β diversity of the lip mucosa and saliva was insignificant among individuals. The first principal component of the dorsal tongue showed a significant difference between OLP patients and healthy controls (Fig. 1 F,H). Increase of P. micra in the buccal mucosae of OLP patients At the species level, MaAsLin analysis was performed among the buccal mucosae of NE-OLP and E-OLP patients and healthy individuals. It was discovered that 75 and 72 microbes showed significant differences between NE-OLP and E-OLP patients, and healthy individuals (Tab. S2). A heat map of 31 microbes overlapped in both groups of OLP patients is presented in Fig. 2 A. These microorganisms were divided into three clusters, and the microbes in clusters 2 and 3 were significantly enriched in NE-OLP and E-OLP patients. Among them, P. micra , Peptostreptococcus stomatis , Streptococcus oralis and Fusobacterium nucleatum were microbes most different from healthy individuals (Fig. 2 B). Spearman correlation network analysis showed that the microbes within clusters 2 and 3 were closely and positively correlated with each other, while cluster 1 was seldom associated with clusters 2 and 3 (Fig. 2 C). MaAsLin analysis at the genus level demonstrated that Parvimonas, Peptostreptococc u and Streptococcus were also the microorganisms most significantly divergent among healthy individuals and NE-OLP and E-OLP patients (Fig. S2 A). The random forest analysis of 31 differential bacteria at the buccal mucosa was performed to validate their classification effect in NE-OLP and E-OLP patients versus healthy controls. The results suggested that the area under the curve (AUC) of classifying NE-OLP patients and healthy individuals was 0.785 (Fig. 2 D) and that of E-OLP patients and healthy individuals was 0.849 (Fig. 2 D). This indicated that these bacteria in the buccal mucosa were closely correlated with OLP. Next, the MeanDecreaseAccuracy of these bacteria was calculated, and P. micra was found to be the microbe differentiating the largest contribution between NE-OLP and E-OLP patients from healthy controls (Fig. 2 E). Random forest analysis at the genus level also revealed that Parvimonas was the microorganism contributing most to distinguishing NE-OLP and E-OLP patients from healthy controls (Fig. S2 C). Spearman correlation analysis showed a positive correlation between P. micra and other high contributing microorganisms like Fusobacterium nucleatum and Tannerella forsythia (Fig. 2 F). NetShift analysis showed that P. micra was a network shift driver bacterium from healthy individuals to E-OLP patients and also from NE-OLP patients to E-OLP ones (Fig. S2 D). P. micra was regressed with clinical measures in NE-OLP and E-OLP patients. It was found that P. micra was significantly correlated with VAS in the NE-OLP group (p < 0.01), CD8 + T cells in the E-OLP group (p < 0.05) and CD4+/CD8 + T cells (p < 0.01) (Fig. 2 G). These results suggested that P. micra may be an important microorganism in OLP disease. Increase of inflammatory response and blockade of autophagy in OLPFs Whether P. micra was present in the buccal mucosae of OLP patients was validated by a FISH assay. It was proved that P. micra was significantly enriched in the junction of epithelial and connective tissue layers of OLP patients compared to healthy individuals (p < 0.05) (Fig. 3 A). As a proinflammatory bacterium in the oral cavity, P. micra can cause a series of inflammatory responses in invading tissues [ 25 ]. The activity of the inflammatory signaling pathway in the buccal mucosae of OLP patients was investigated. The scRNA-seq data of buccal mucosa tissues between normal and OLP patients (GSE211630) were analyzed, and 10 clusters of cells were annotated based on the enrichment of cluster-defining gene markers (Fig. 3 B). Cell component analysis showed that the proportion of fibroblasts dramatically decreased, while most immune cells increased, especially T cells (Fig. 3 C). Intercellular and molecular communication showed that communications between CD4 + T cells, CD8 + T cells and fibroblasts were increased, and fibroblasts could regulate a majority of other cell types in the epithelial and stromal tissues of OLP patients (Fig. 3 D). KEGG pathway enrichment analysis indicated that a variety of inflammatory-related pathways such as NF-қB, TNF, Janus tyrosine kinase-signal transducers and activators of transcription (JAK-STAT) and phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling pathways were enriched in OLPFs (Fig. 3 E). TNF-α was linked to the activation of T cells, Langerhans’ cells, mononuclear cells and epithelial keratinocytes in OLP [ 26 ]. The secreting cytokines in NF-қB pathway were analyzed. It was noted that TNF-α, CCL21 and CCL19 were significantly up-regulated in OLPF compared with NFs (Fig. 3 F). To validate the activation of TNF-α in fibroblasts in the buccal mucosa, fibroblasts were separated and cultured from healthy individuals (NFs) and OLP patients (OLPFs). Western blotting showed that p-p65 and p-Ikβα had significantly high expression in OLPFs compared with NFs (n = 3, (p < 0.05)) (Fig. 3 H). ELISA assay showed that OLPFs had a significantly higher level of TNF-α in comparison to NFs (p < 0.05) (Fig. 3 G). Autophagy is an important host cell defense strategy against microbial stimulation [ 27 ] [ 28 ]. The state of autophagy in NFs and OLPFs was examined. Western blotting showed that SQSTM1 and LC3B-Ⅱ exhibited a notable increase in OLPFs compared with NFs (p < 0.05) (Fig. 3 L). The autophagic flux of OLPFs using inhibitors BafA1 showed that LC3B-II increased in NFs and OLPFs when lysosomal-dependent LC3B-II degradation was blocked (Fig. 3 M). The quantification of mCherry (red) (autolysosomes) and yellow puncta (autophagosomes) in NFs and OLPFs with mCherry-GFP-LC3 demonstrated that OLP increased the number of autophagosomes in fibroblasts, and decreased the number of autolysosomes in comparison with NFs (Fig. 3 N). Next, whether the blockade of autophagy was involved in TNF-α secretion was investigated. ELISA assay was applied in NFs and OLPFs with or without BafA1. The results showed that the addition of BafA1 significantly increased the secretion of TNF-α in both NFs and OLPFs (p < 0.05, Fig. 3 O). Promotion of TNF-α release by P. micra and induction of autophagic blockade in fibroblasts Given the enrichment of P. micra in the stromal tissues of OLP, whether P. micra could induce inflammatory activation in NFs was tested. The abundance of TNF-α between NFs and NFs + P. micra was compared by ELISA assay. It was shown that P. micra increased the secretion of TNF-α to a large extent (p < 0.05) (Fig. 4 A). To verify whether P. micra had an inflammation-promoting effect, CM from P. micra was obtained and used to treat NFs. The results indicated that adding CM in NFs increased the secretion of TNF-α to a great degree (p < 0.05) (Fig. 4 A). OMVs are one of the key components secreted by microbes in the pathogenesis of oral disease [ 29 ]. Therefore, OMVs were isolated and characterized from the CM of P. micra (Supplementary Fig. 2), and the abundance of TNF-α between NFs and NFs + P. micra -derived OMVs was compared. The result indicated that the OMVs of P. micra also significantly increased the secretion of TNF-α (p < 0.05) (Fig. 4 A). Next, whether P. micra and CM and OMVs of P. micra could also activate NF-қB pathway was examined. The phosphorylation of p65 and Iқβα was significantly increased in P. micra/ CM/OMV groups in comparison with the NF group (Fig. 4 B). Next, the autophagic state of NFs with the stimulation of P. micra , CM or OMVs of P. micra was detected. Western blotting showed that both SQSTM1 and LC3B-Ⅱ were over-expressed in NFs + P. micra , NFs + CM of P. micra and NFs + OMVs of P. micra groups compared with NFs (p < 0.05) (Fig. 4 C). In addition, the expression of LC3B-II was not changed between NFs and NFs-OMVs treated with BafA1 (Fig. 4 D). In addition, mCherry-GFP-LC3 tests showed that the autophagy of P. micra -derived OMVs was blocked (Fig. 4 E). These results suggested OMVs are an important pathogenic component of P. micra to promote the inflammatory response and block the autophagic flux in fibroblasts. Involvement of DnaK in P. micra -derived OMVs in inflammatory activation and autophagy flux blockade To reveal how P. micra -derived OMVs promote inflammation and block autophagy flux, OMVs were first labeled with pkh67 and, NF cytoskeletal protein was labeled by β-tubulin. Immunofluorescence (IF) showed that OMVs could be detected in fibroblasts (Fig. 5 A). OMVs may exert toxic effects by releasing their components [ 29 ] (pathogenic proteins or small RNAs) within host cells [ 30 – 33 ]. Herein, the proteome of P. micra -derived OMVs was profiled by mass spectrometry, and 13 candidate effector proteins were identified (Tab. S3). Among them, DnaK was selected as the putative virulent effector for the following study. Whether DnaK could be detected in OLPFs was tested by Western blotting. The results revealed the high enrichment of DnaK in OLPFs in comparison to NFs(n = 3, p < 0.05, Fig. 5 B). Similarly, a higher abundance of DnaK could be detected in NFs + P. micra , NFs + CM of P. micra and NFs + P. micra -derived OMV groups in comparison with NFs (Fig. 5 C). To analyze the location of DnaK in OMVs, OMVs were treated with Proteinase K (degrade protein but not membranous structures) alone (OMV + K group) or both Proteinase K and Triton X-100 (OMV + K + T group) compared with Dnak (D group) or both DnaK and Proteinase K (D + K group). As shown in Fig. 5 D, the abundance of DnaK was reduced in the OMV + K group compared with the OMV group, and DnaK in the OMV + K + T group was less abundant than that in the OMV + K group. These results suggested that DnaK was located both in the outer membrane and cytoplasm of OMVs. To test its pathogenic effects, DnaK was transfected into NFs by lentivirus. IF assay showed that DnaK was situated in the cytoplasm and nucleus of NFs (Fig. 6 B). Whether DnaK could mimic the pathogenicity of OMVs on NFs was investigated. ELISA assay showed that the transfection of DnaK (lv-DnaK) could facilitate the significant increase of TNF-α compared with NFs (p < 0.05) (Fig. 5 E). Next, the activation of NF-қB pathway and autophagy under the stimulation of lv-DnaK was examined. The results indicated that the phosphorylation of Iқβα and p65 exhibited a marked increase (Fig. 5 F), and the expression of SQSTM1 and LC3B-Ⅱ was remarkably increased with the stimulation of DnaK (p < 0.05) (Fig. 5 G). BafA1 treatment and mCherry-GFP transfection tests exhibited that the over-expression of DnaK inhibited autophagy flux (Fig. 5 H,I). These results suggested that DnaK is an important pathogenic effector of P. micra -derived OMVs. Interaction of DnaK with Bag3 to activate NF-қB pathway and decrease autophagy flux To identify the interacted protein of DnaK in fibroblasts, GST/His pull-down assay and HPLC-MS analysis were applied to capture the candidate protein combined with His-tagged DnaK, which identified 87 candidate proteins (Tab. S4). Among these candidate proteins, Bag3 was reported as an autophagy-related protein [ 34 ]. The combination of DnaK and Bag3 was tested by co-immunoprecipitation (Co-IP) experiments. The result showed that DnaK could bind to Bag3 (Fig. 6 A). Co-IF assay showed the co-localization of DnaK with Bag3 in the nucleus and cytoplasm of lv-GFP-DnaK (Fig. 6 B). To investigate the impact of DnaK on Bag3, the abundance of DnaK and Bag3 in NFs and OLPFs was compared. The results showed that an increase of DnaK did not induce the over-expression of Bag3 in OLPFs (n = 3, Fig. 6 C). To examine the role of Bag3 in DnaK-induced inflammation, a transfection assay was performed to knock down Bag3 with small-interference RNA in lv-DnaK (si-Bag3). ELISA analysis showed that si-Bag3 could dramatically suppress the secretion of TNF-α compared with NFs (p < 0.05) (Fig. 6 D). Next, the activation of NF-қB pathway in si-Bag3 was examined, and p-Iқβα and p-p65 were found to be both significantly decreased in si-Bag3 (p < 0.05) (Fig. 6 E). Moreover, an investigation was conducted on the role of Bag3 in autophagy. In comparison to lv-DnaK, si-Bag3 promoted autophagic flux by BafA1 treatment and mCherry-GFP transfection (Fig. 6 F,H). These results suggested that Bag3 is an important protein mediating the inflammatory response and autophagy of DnaK. Interaction of DnaK and Bag3 with IKK-γ to activate inflammatory response and inhibit autophagy Bag3 is reported to modulate NF-κB pathway via IKK-γ [ 35 ]. IKK-γ was tested in OLPFs by Western blotting, and the results showed that IKK-γ was highly enriched in OLPFs in comparison with NFs (p<0.05, Fig. 7 A). Therefore, the interaction of IKK-γ-DnaK-Bag3 was verified by Co-IP in lv-DnaK, and it was shown that IKK-γ could be combined with DnaK-Bag3 (Fig. 7 B). This result in si-Bag3 was validated, and the knockdown of Bag3 was shown to significantly decrease the abundance of IKK-γ (p < 0.05) (Fig. 7 C). In addition, the combination of DnaK and IKK-γ reduced si-Bag3 compared with lv-DnaK (p < 0.05) (Fig. 7 D). These results suggested that DnaK was combined with Bag3 to interact and regulate the expression of IKK-γ. IKK-γ mediates the effect of autophagy [ 36 ] and NF-қB pathway [ 37 ]. IKK-γ and EGFP marked LC3B puncta were co-localized, which showed that the accumulation of LC3B puncta could be co-expressed with IKK-γ in lv-DnaK (Fig. 7 E). To determine which step of autophagy that IKK-γ participates in, IKK-γ was knocked down by siRNA in lv-DnaK (si-IKK-γ). The results showed that the abundance of SQSTM1 and LC3B-Ⅱ was significantly decreased in si-IKK-γ cells (Fig. 7 F). BafA1 treatment and mCherry-GFP transfection tests were used and showed that IKK-γ knockdown promoted the autophagic influx of lv-DnaK (Fig. 7 G,H). A study showed that IKK-γ can interact with SQSTM1 to regulate LC3 proteins [ 38 ]. The knockdown of IKK-γ could reduce the expression of SQSTM1 with and without BafA1 treatment (Fig. 7 G). Furthermore, the knockdown of IKK-γ reduced the abundance of p-Iқβα and p-p65 and decreased the level of TNF-α in lv-DnaK (Fig. 7 F,L). These results suggested the DnaK-Bag3-IKK-γ signaling axis could regulate autophagy and NF-қB pathway. Discussion The oral microbiome of OLP patients differed from that of healthy controls, which suggested that the oral microbiota may correlate with the onset and progression of OLP [ 5 – 7 , 9 , 14 ]. Nevertheless, how oral microbes contribute to OLP progression is still unknown. In the current study, the correlation between OLP and a rarely reported oral opportunistic pathogen, P. micra was demonstrated first. In addition, the first pathogenic study of P.micra in OLP was conducted, and a new mechanism by which P. micra promotes inflammatory response and blocks autophagy was discovered (Fig. 8 ). To systematically reveal the association of the oral microbiome with OLP disease, a comprehensive microbiome-wide association study was first conducted between NE/E-OLP patients and healthy controls at the oral niche of the buccal region, the lip mucosa, the tongue dorsum and saliva. Consistent with previous studies [ 7 , 9 , 39 ], OLP patients and healthy controls showed significant differences, especially at the oral site of the buccal mucosa. Of note, P. micra was the most differently distributed bacterium, which is known as an oral commensal bacterium closely related to chronic and periapical periodontitis [ 40 , 41 ]. FISH assay validated that P. micra was enriched in the junction of epithelial and connective tissue layers with high abundance in OLP patients. Fibroblasts, the main cellular component of connective tissues of the buccal mucosa, remain stationary in a stable environment [ 42 ]. In response to tissue damage and inflammatory reactions, fibroblasts can be activated to exert multiple immune effects. Single-cell analysis found that the TNF-α of the fibroblasts-related NF-қB pathway was activated and communicated with multiple cells in the tissues of OLP patients. Consistently, it was proved that fibroblasts from OLP and normal tissues could over-express TNF-α and activate NF-қB pathway in OLPFs. Thus, how the inflammatory response of fibroblasts is triggered is an important question in OLP disease. The FISH assay showed significant enrichment of P. micra in the junction of epithelial and connective tissue layers in OLP patients, which is a highly enriched region of fibroblasts. Hence, the pathogenic study was carried out among P. micra and fibroblasts. It was demonstrated that P. micra could promote TNF-α secretion and block autophagy. To explore the underlying mechanism, CM and OMVs were extracted from fibroblasts treated with P. micra , and similar results were obtained. As a result, OMVs as an important way for pathogens to exert pathogenicity have received attention [ 43 ]. Furthermore, it was noticed that DnaK of P. micra OMVs was one of the main effectors, which could activate NF-қB pathway and block autophagy. To explore the interacted protein of DnaK in fibroblasts, multiple host proteins were captured, and Bag3 was selected for the following study. As a sensor of heat shock protein 70 (HSP70), Bag3 can bind to numerous protein-protein domains that support different activities by affecting the upstream regulators of the signaling pathway and the process of autophagy flux [ 34 ]. Bag3 expression was silenced in lv-DnaK (si-Bag3). It was found that si-Bag3 could secrete less TNF-α, inhibit NF-қB pathway and activate autophagy. Next, Co-IP assays were conducted. It was proved that IKK-γ directly interacted with DnaK and Bag3; the expression of IKK-γ decreased with the decrease of Bag3 in si-Bag3; si-IKK-γ could secrete less TNF-a, inhibit NF-қB pathway and activate autophagy. Additionally, IKK-γ was mediated by LC3 proteins binding to LC3-interacting region (LIR) motifs present in p62 [ 38 ]. IKK-γ lowered the threshold of p62 in lv-DnaK and si-IKK-γ with and without BafA1 treatment. In conclusion, the results of this study suggested that P. micra plays a vital role in the oral dysbiosis of OLP disease. DnaK of P. micra OMVs interacted with the Bag3 of fibroblasts and modulated the expression of IKK-γ, which regulated the secretion of TNF-α by activating the NF-қB pathway and inhibiting autophagy. These results elucidate the potential pathogenesis of OLP and provide new insights into the treatment and prevention of OLP. Declarations Ethics approval and consent to participate The study obtained the approval of the Ethics Committee of the School and Hospital of Stomatology, Shandong University (No. GR201702). Consent for publication Not applicable. Competing interests The authors declare no competing interests. Availability of data and material All relevant data are included in the article or in the supplementary material.All datasets and raw data are available from the corresponding author onreasonable request. The raw data of 16S rRNA amplicon sequencing are available from GSA database (CRA 003224).The raw data of scRNA-seq are openly available in GEO database (GSE211630). Funding We sincerely thank the foundation support of National Natural Science Foundation of China (No. 82270980, 82071122), Shandong Natural Science Foundation (No. ZR2023MH045), the start-up fund for introduction of talents to Jinan Central Hospital (No. YJRC2021002), Science and Technology Development Program of Jinan Municipal Health Commission（No.2022-2-7）,the National Young Scientist Support Foundation (2019), Excellent Young Scientist Foundation of Shandong Province (No. ZR2021JQ29), Major Innovation Projects in Shandong Province (No. 2021SFGC0502), the Periodontitis innovation team of Jinan City (2021GXRC021), Taishan Young Scientist Project of Shandong Province (2019), Oral Microbiome Innovation Team of Shandong Province (No. 2020KJK001), Shandong Province Key Research and Development Program (No. 2021ZDSYS18). 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Supplementary Files Figs1.pdf Figs2.pdf supplementaryFiglengend.docx supplementarytab3.docx supplementarytab4.docx supplementarytable1.xlsx supplementarytable2.xlsx Cite Share Download PDF Status: Published Journal Publication published 14 Jul, 2025 Read the published version in Microbiome → Version 1 posted Editorial decision: Revision requested 06 Nov, 2024 Reviewers agreed at journal 16 Oct, 2024 Reviews received at journal 15 Oct, 2024 Reviewers agreed at journal 07 Oct, 2024 Reviews received at journal 04 Sep, 2024 Reviewers agreed at journal 08 Jul, 2024 Reviewers invited by journal 08 Jul, 2024 Editor assigned by journal 20 Jun, 2024 Submission checks completed at journal 17 Jun, 2024 First submitted to journal 13 Jun, 2024 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. 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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-4578173","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320198694,"identity":"591b1114-b4b9-4c4b-8ed7-f8c333c3cfa7","order_by":0,"name":"Xiaoli Ji","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBACxgbmNgYJBgY59gYQ18CCGC2MYC3GPAfAWiSIsqcNRCb2gLUwEKGFeUZi2wPLnMPpPew9pht+FEgw8Ld3J+C3o+dgu4HktsO5PTzH0m72AB0mcebsBvxa2hvbJEBa9kskH7vBA9RiIJFLQEszI1hLOo9EYtvNP0RpgdqSwAO05TZxtkD8km4I8sttGQMJHoJ+MZyRfOyx5DZreR72HrObb/7YyPG39xLQ0gAMaOTI4MGrHATkQY77QFDZKBgFo2AUjGgAAD6WRc5ypUDjAAAAAElFTkSuQmCC","orcid":"","institution":"Central Hospital Affiliated to Shandong First Medical University","correspondingAuthor":true,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Ji","suffix":""},{"id":320198696,"identity":"9ccf261c-59ff-4b2d-bae4-f83f7f4f65e5","order_by":1,"name":"Mengfan Zhi","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Mengfan","middleName":"","lastName":"Zhi","suffix":""},{"id":320198699,"identity":"4f0f0100-bd10-4a8e-8866-c0c41118d907","order_by":2,"name":"Xiufeng Gu","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Xiufeng","middleName":"","lastName":"Gu","suffix":""},{"id":320198703,"identity":"22945b3c-f328-4082-9d0b-6999511dfde8","order_by":3,"name":"Ying Han","email":"","orcid":"","institution":"Peking University School and Hospital of Stomatology","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Han","suffix":""},{"id":320198704,"identity":"96efa70a-81db-4b2c-85c0-71cf5fd5e178","order_by":4,"name":"Xiang Lan","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Lan","suffix":""},{"id":320198718,"identity":"c1e72a77-3dd2-40ce-be0e-276f4bbf5491","order_by":5,"name":"lixiang Song","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"lixiang","middleName":"","lastName":"Song","suffix":""},{"id":320198720,"identity":"54faaf4a-dd1d-42fd-9203-ffb76778602e","order_by":6,"name":"Peipei Sun","email":"","orcid":"","institution":"Central Hospital Affiliated to Shandong First Medical University","correspondingAuthor":false,"prefix":"","firstName":"Peipei","middleName":"","lastName":"Sun","suffix":""},{"id":320198721,"identity":"50a19fed-059d-428a-bf7a-f8ef8dadf1d9","order_by":7,"name":"Jingyuan Li","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Jingyuan","middleName":"","lastName":"Li","suffix":""},{"id":320198722,"identity":"c519d377-0a25-462d-b2f8-2cbe6186a530","order_by":8,"name":"XiangMin Qi","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"XiangMin","middleName":"","lastName":"Qi","suffix":""},{"id":320198723,"identity":"0b47e680-b6c5-4ea3-930d-27ffa7aa98a9","order_by":9,"name":"Qiang Feng","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Qiang","middleName":"","lastName":"Feng","suffix":""}],"badges":[],"createdAt":"2024-06-13 20:11:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4578173/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4578173/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40168-025-02151-5","type":"published","date":"2025-07-14T15:57:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60344259,"identity":"79b0e0c4-6ce4-4910-b0ee-4c3954c8fc68","added_by":"auto","created_at":"2024-07-15 19:21:39","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1283820,"visible":true,"origin":"","legend":"\u003cp\u003eCharacteristics of microbiome of buccal and lip mucosae, tongue dorsum and saliva of healthy controls and OLP patients. The ranking of abundance varied at both phylum (\u003cstrong\u003eA\u003c/strong\u003e) and genus levels (\u003cstrong\u003eB\u003c/strong\u003e). \u003cstrong\u003eC\u003c/strong\u003e Core microbiome of buccal and lip mucosae, tongue dorsum and saliva at the species level in control, NE-OLP and E-OLP groups. (\u003cstrong\u003eD\u003c/strong\u003e and \u003cstrong\u003eE\u003c/strong\u003e) Adonis analysis of Bray-Curtis and Jaccard distances showed the microbiome of four sites.\u003cstrong\u003e F\u003c/strong\u003e β diversity analysis of the microbial composition detected in the four sites by Shannon and Simpson. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/4c5c4fbe9436299546dd6616.png"},{"id":60344248,"identity":"4fa58dd0-2fd7-49be-a414-d66984e24aa8","added_by":"auto","created_at":"2024-07-15 19:21:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2416367,"visible":true,"origin":"","legend":"\u003cp\u003ePivotal pathogenic bacteria in the microbiome of OLP\u003cstrong\u003e. A\u003c/strong\u003e A heat map of microbes overlapped at the species level in control, NE-OLP and E-OLP groups. \u003cstrong\u003eB \u003c/strong\u003eRelative abundance of \u003cem\u003eP. micra\u003c/em\u003e, \u003cem\u003ePeptostreptococcus stomatis, Streptococcus oralis \u003c/em\u003eand \u003cem\u003eFusobacterium nucleatum \u003c/em\u003eshown in A. \u003cstrong\u003eC\u003c/strong\u003e Spearman correlation network analysis at the species level in control, NE-OLP and E-OLP groups. \u003cstrong\u003eD\u003c/strong\u003e Random forest predictions for the control and OLP microbiota of different parts were at the species level with MeanDecreaseAccuracy (\u003cstrong\u003eE\u003c/strong\u003e). \u003cstrong\u003eF\u003c/strong\u003e Spearman correlation analysis showed that \u003cem\u003eP. micra\u003c/em\u003e was positively correlated with other most of most contributing microorganisms.\u003cstrong\u003e G\u003c/strong\u003e \u003cem\u003eP. micra\u003c/em\u003ewith clinical measures in NE- and E-OLP patients. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/7b71389906812b2d9341023d.png"},{"id":60344254,"identity":"1a8a9210-ddab-4a3c-858a-548fb338e284","added_by":"auto","created_at":"2024-07-15 19:21:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1621172,"visible":true,"origin":"","legend":"\u003cp\u003eIncrease of inflammatory response and the blockade of autophagy in OLP fibroblasts.\u003cstrong\u003e A \u003c/strong\u003eFISH (\u003cem\u003eP. micra\u003c/em\u003e) of control (n = 16) and OLP (n = 15) groups. The white arrow represented \u003cem\u003eP. micra\u003c/em\u003e. \u003cstrong\u003eB\u003c/strong\u003e The annotated clusters in the scRNA-seq data of buccal mucosa tissues were between normal and OLP patients. \u003cstrong\u003eC\u003c/strong\u003e Cell component analysis of the scRNA-seq data. \u003cstrong\u003eD\u003c/strong\u003eIntercellular and molecular communication shown between CD4+ T cells, CD 8+ T cells and fibroblasts. \u003cstrong\u003eE\u003c/strong\u003e KEGG pathway enrichment analysis showed inflammatory-related pathways. \u003cstrong\u003eF\u003c/strong\u003e The abundance of secreted cytokines in the NF-қB pathway detected in the fibroblasts of control and OLP tissues. \u003cstrong\u003eG\u003c/strong\u003eELISA was carried out to detect the expression of TNF-α between NFs and OLPFs. \u003cstrong\u003eH-L\u003c/strong\u003e Western blot detection of the expression of autophagy markers LC3B-I and LC3B-II in NFs and OLPFs. \u003cstrong\u003eM\u003c/strong\u003e Western blotting analyzed LC3B-I and LC3B-II expression in NFs and OLPFs treated with BafA1. \u003cstrong\u003eN\u003c/strong\u003e Confocal images of NFs and OLPFs with Ad-mCherry-GFP-LC3B were used for distinguishing between autolysosomes (GFP−mCherry + vesicles) and autophagosomes (GFP+ mCherry+ vesicles) owing to the different instabilities of GFP and mCherry fluorescent proteins in autolysosomes. Scale bar: 10 µm. \u003cstrong\u003eO\u003c/strong\u003e ELISA detected the expression of TNF-α between NFs and OLPFs treated with BafA1. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/89eb00d2c91cb6c2182cebeb.png"},{"id":60344256,"identity":"4e1c5f08-9ddd-489c-abff-7ca30de57cd5","added_by":"auto","created_at":"2024-07-15 19:21:38","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":647430,"visible":true,"origin":"","legend":"\u003cp\u003eExacerbation of inflammatory factor secretion and the blockade of autophagic flux by \u003cem\u003eP. micra\u003c/em\u003e and OMVs.\u003cstrong\u003e A\u003c/strong\u003e Measurement of TNF-α by ELISA in the supernatant of NFs treated with \u003cem\u003eP. micra\u003c/em\u003e and CM and OMVs of \u003cem\u003eP. micra.\u003c/em\u003e The experiment was repeated independently three times. \u003cstrong\u003eB\u003c/strong\u003e Western blot detection of the expression of autophagy markers LC3B-I and LC3B-II in NFs treated with \u003cem\u003eP. micra\u003c/em\u003e and CM and OMVs of \u003cem\u003eP. micra\u003c/em\u003e. \u003cstrong\u003eC\u003c/strong\u003e Western blot detection of the expression of NF-қB pathway markers p-p65, total-p65, p-Iқβα and total-Iқβα, as well as autophagy markers SQSTM1, LC3B-I and LC3B-II in NFs treated with OMVs of \u003cem\u003eP. micra \u003c/em\u003eand BafA1 (\u003cstrong\u003eD\u003c/strong\u003e). \u003cstrong\u003eE\u003c/strong\u003e Confocal images of mCherry (red), GFP-LC3 (green) and DAPI (blue) fluorescence in NFs treated with OMVs of\u003cem\u003e P. micra\u003c/em\u003e. Scale bar: 25 µm. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/90308ebe503455d4324863cb.png"},{"id":60344247,"identity":"4ca51b9f-69d3-4727-9f34-b2cce257f485","added_by":"auto","created_at":"2024-07-15 19:21:37","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":898664,"visible":true,"origin":"","legend":"\u003cp\u003eInvolvement of DnaK in \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs in inflammatory activation and the blockade of autophagy flux. \u003cstrong\u003eA\u003c/strong\u003e Co-localization of OMV-labeled pkh67 and β-Tubulin in NFs treated with OMVs of \u003cem\u003eP. micra\u003c/em\u003e. \u003cstrong\u003eB\u003c/strong\u003e Western blotting was utilized for measuring the difference in DnaK expression between NFs (n = 3) and OLPFs (n = 3). \u003cstrong\u003eC\u003c/strong\u003eWestern blotting was used for measuring the difference in DnaK expression when NFs were treated with \u003cem\u003eP. micra\u003c/em\u003e and CM and MOVs of \u003cem\u003eP. micra\u003c/em\u003e. \u003cstrong\u003eD\u003c/strong\u003e Western blotting was employed for measuring the difference in DnaK expression when OMVs were treated with Proteinase K (K) and Triton X-100 (T). \u003cstrong\u003eE\u003c/strong\u003e ELISA was used for measuring TNF-α by the supernatant of NF lentiviral transfected with DnaK (lv-DnaK). \u003cstrong\u003eF\u003c/strong\u003eWestern blot detection of SQSTM1, LC3B-I and LC3B-II expression in NFs and lv-DnaK. Western blot detection of the expression of p-p65, total-p65, p-Iқβα and total-Iқβα (\u003cstrong\u003eF\u003c/strong\u003e), as well as LC3B-I and LC3B-II in lv-DnaK (\u003cstrong\u003eG\u003c/strong\u003e) and BafA1 (\u003cstrong\u003eH\u003c/strong\u003e). \u003cstrong\u003eI \u003c/strong\u003eConfocal images of mCherry, GFP-LC3 and DAPI fluorescence in NFs and lv-DnaK. Scale bar: 25 µm. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/1f3587b8e4a2f1141af1a15b.png"},{"id":60344244,"identity":"0dbb2d7c-ef91-4689-85cc-234c1b2bd4bb","added_by":"auto","created_at":"2024-07-15 19:21:34","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":796421,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction between the DnaK of \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs and Bag3 in fibroblasts.\u003cstrong\u003e A\u003c/strong\u003e Analysis of immunoprecipitated (IP) and whole-cell lysates (Input) by immunoblotting (IB) with Bag3 and Flag antibodies in lv-DnaK. The tests were conducted three times. \u003cstrong\u003eB\u003c/strong\u003e Co-localization of Bag3 and DnaK in lv-DnaK. \u003cstrong\u003eC\u003c/strong\u003e Western blotting was used for measuring the difference in Bag3 expression between NFs (n = 5) and OLPFs (n = 5). \u003cstrong\u003eD\u003c/strong\u003eMeasurement of TNF-α by ELISA in the supernatant oflv-DnaK and the knockdown Bag3 in lv-DnaK (si-Bag3). Western blotting was performed for detecting p65, IκBα (\u003cstrong\u003eE\u003c/strong\u003e) and SQSTM1, LC3B-I and LC3B-II (\u003cstrong\u003eF\u003c/strong\u003e) expression between lv-DnaK and si-Bag3. BafA1 treatment (\u003cstrong\u003eG\u003c/strong\u003e) and mCherry-GFP-LC3B (\u003cstrong\u003eH\u003c/strong\u003e) test detected autophagy flux. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/ece1a4428170cca12436fb5b.png"},{"id":60344258,"identity":"ebaea1ed-1b09-4aac-acbc-30fb41b5b124","added_by":"auto","created_at":"2024-07-15 19:21:39","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":816182,"visible":true,"origin":"","legend":"\u003cp\u003eInteraction of DnaK and Bag3 with IKK-γ to activate inflammatory response and inhibit autophagy. \u003cstrong\u003eA\u003c/strong\u003e Western blotting was used for detecting IKK-γ expression between NFs and OLPFs. \u003cstrong\u003eB\u003c/strong\u003e Analysis of IP and whole-cell lysates (Input) by IB with Bag3, Flag and IKK-γ antibodies in lv-DnaK and si-Bag3 (G). \u003cstrong\u003eC,D\u003c/strong\u003e Western blotting was utilized for detecting IKK-γ and DnaK expression in lv-DnaK and si-Bag3. \u003cstrong\u003eE\u003c/strong\u003e Co-localization of IKK-γ and EGFP-LC3B detected in lv-DnaK. Western blotting was used for detecting IKK-γ, SQSTM1, LC3B-I, LC3B-II p-p65, total-p65, p-Iқβα and total-Iқβα expression in lv-DnaK and si- IKK-γ (\u003cstrong\u003eF\u003c/strong\u003e) none or treated with BafA1(\u003cstrong\u003eG\u003c/strong\u003e). \u003cstrong\u003eH\u003c/strong\u003e Confocal images of mCherry, GFP-LC3 and DAPI fluorescence in lv-DnaK and si-Bag3. \u003cstrong\u003eL\u003c/strong\u003eMeasurement of TNF-α by ELISA in the supernatant of lv-DnaK and si-Bag3. The tests were conducted three times. * The difference showed statistical significance (p ˂ 0.05).\u003c/p\u003e","description":"","filename":"Fig7.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/0dd3296c64b647a678caa727.png"},{"id":60344257,"identity":"a04aa2ba-5f2d-4c47-946c-235fc99f5926","added_by":"auto","created_at":"2024-07-15 19:21:39","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2823418,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic depiction (by Figdraw). Interaction between the DnaK of \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs and the Bag3 of fibroblasts to promote the secretion of TNF-α by IKK-γ.\u003c/p\u003e","description":"","filename":"Fig8.png","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/afa43f7369cacdfcc24ac8bb.png"},{"id":87219369,"identity":"6707243c-758f-4205-8bd4-317c320a2741","added_by":"auto","created_at":"2025-07-21 16:04:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13467615,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/2e219ae7-fff4-4222-935e-038a17fe1c6e.pdf"},{"id":60344855,"identity":"0fe05f05-bd00-423c-90d7-f6a8b0c84289","added_by":"auto","created_at":"2024-07-15 19:29:38","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":828528,"visible":true,"origin":"","legend":"","description":"","filename":"Figs1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/124675fda675cc1f10f0d7f0.pdf"},{"id":60344252,"identity":"5b6be9fe-05e1-459b-b6f2-ecdea53de72f","added_by":"auto","created_at":"2024-07-15 19:21:38","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":18433436,"visible":true,"origin":"","legend":"","description":"","filename":"Figs2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/fa5d81a01daf59a4bca71f59.pdf"},{"id":60344246,"identity":"13e718ef-a56e-45bf-85e6-84a7a1f65130","added_by":"auto","created_at":"2024-07-15 19:21:36","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":19381,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryFiglengend.docx","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/45cad2fbb11b82f2f5bad849.docx"},{"id":60344243,"identity":"419b3408-f7d7-4779-a31f-06a7164be95a","added_by":"auto","created_at":"2024-07-15 19:21:34","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":19338,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytab3.docx","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/f6f4f7340552a36fb3121844.docx"},{"id":60344854,"identity":"57e8ae9c-a27b-407a-bc98-aa77a04829d0","added_by":"auto","created_at":"2024-07-15 19:29:37","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":24848,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytab4.docx","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/43f5a55f6c99c7e7dcaa10e4.docx"},{"id":60344251,"identity":"b9fbf07a-ef7a-43eb-8045-a4408f6b73e7","added_by":"auto","created_at":"2024-07-15 19:21:37","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":9696,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/61d7691c63f43462a4b8cb2d.xlsx"},{"id":60344249,"identity":"6145dd3e-c4ce-4c4c-b092-5b0ffa325a95","added_by":"auto","created_at":"2024-07-15 19:21:37","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":37597,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4578173/v1/e9fd46efc0a8116be83fa74b.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"DnaK of Parvimonas micra OMVs interacted with the host fibroblast Bag3-IKK-γ axis to accelerate TNF-α secretion in oral lichen planus","fulltext":[{"header":"Background","content":"\u003cp\u003eOral lichen planus (OLP) is one of the most common oral mucosal disease associated with chronic inflammation, affects up to 0.89% of the general population [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It most commonly leads to significant roughness, discomfort and pain, which rarely undergo spontaneous remission with a high tendency for malignant transformation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The initiation and progression of OLP have no definitive and complex interaction between psychological factors, immunological factors, endocrine disorders, psychological factors and genetic factors [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Growing evidence indicates the possibly essential role of the oral microbiome in the etiology of OLP [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNext generation sequencing-based microbiome studies showe\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ed\u003c/span\u003e that microbes from the saliva and lesions of OLP were varied from those of healthy individuals. For instance, the abundance of \u003cem\u003ePorphyromonas, Solobacterium Capnocytophaga\u003c/em\u003e and \u003cem\u003eGemella\u003c/em\u003e exhibited a significant increase in OLP patients, whereas \u003cem\u003eHaemophilus, Corynebacterium, Cellulosimicrobium\u003c/em\u003e and \u003cem\u003eCampylobacter\u003c/em\u003e demonstrated a dramatic decrease. \u003cem\u003ePorphyromonas\u003c/em\u003e was correlated to salivary interleukin (IL)-17 and IL-23 [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Regarding the contribution of the oral microbiome to OLP development, studies showed that oral pathogenic bacteria could invade OLP tissues [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], destroy the integrity of the oral mucosal epithelium barrier and facilitate the entry of more bacteria [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], followed by their aggregation in the lamina Apropria and the epithelial basal layer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFibroblasts, a main cellular component of the lamina propria [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], are important cellular targets of microbiome [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. With the initiation and progression of OLP, fibroblasts could acquire an activated inflammatory phenotype via the release of cytokines and play a key role in the pathogenesis of inflammatory diseases like vitiligo whose pathogenesis is similar to that of OLP [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Research showed that OLP fibroblasts (OLPFs) could secrete IL-6, IL-8, tumor necrosis factor-alpha (TNF-α) and other inflammation-related cytokines in response to \u003cem\u003ePorphyromonas gingivalis\u003c/em\u003e lipopolysaccharide [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The increased level of chemokine (C-C motif) ligand 5 (CCL5) from OLPFs promoted the proliferation and migration of cluster of differentiation 4 T helper (CD4\u0026thinsp;+\u0026thinsp;T) cells and contributed to the disease process of OLP [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Also, fibroblasts secreted IL-6 enhancing the angiogenesis of OLP [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Currently, how fibroblasts interact with pathogenic oral microbes to promote the pathogenesis of OLP has been undervalued.\u003c/p\u003e \u003cp\u003eIn this study, the microbial profiles of buccal and lip mucosae, tongue dorsum and saliva in on-erosive/erosive-OLP (NE/E-OLP) patients and healthy controls were compared. A series of potential oral bacteria dramatically enriched in OLP patients\u0026rsquo; buccal mucosae were identified. One significantly enriched bacterium, \u003cem\u003eParvimonas micra\u003c/em\u003e (\u003cem\u003eP. micra\u003c/em\u003e), was validated in the buccal mucosae of OLP patients. A mechanism study of \u003cem\u003eP. micra\u003c/em\u003e and OLPFs was carried out, which identified the main pathogenic effector in \u003cem\u003eP. micra\u003c/em\u003e and revealed the cellular receptors, downstream regulators and pathways in fibroblasts. This study demonstrates that oral pathogenic microbes play a part in the pathogenesis of OLP.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample collection\u003c/h2\u003e \u003cp\u003e The study earned the approval of the Ethics Committee of the School and Hospital of Stomatology, Shandong University (No. GR201702). The inclusion criteria of the patients were as follows: 1) Patients aged 18\u0026ndash;60; 2) Patients without severe periodontal disease, untreated caries, endodontic and system diseases; 3) Patients without smoking habits; 4) Patients without taking antibiotics, antiviral drugs and glucocorticoid in six months; 5) Patients satisfying the histopathological and clinical diagnostic criteria of OLP [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; 6) Patients with lesions only located on the buccal mucosa of both cheeks; 7) Patients signing informed consent to participate. Participants were not allowed to drink and eat within at least 2 hours before the collection between 8:00 and 11:00 a.m. Mouth swabs were collected from each buccal mucosa, lip mucosa, tongue dorsum and saliva using sterile swabs. Two hours after a meal, no saliva was stimulated by rinsing the mouth five times with sterile double-distilled water and allowing for the natural flow of saliva into an Eppendorf tube. All the samples were gathered with the sterile Eppendorf tube and stored at the temperature of -80\u0026deg;C. VAS score were obtained before treatment .The scale is divided from 0 to 10, with 0 being minimum level of pain and 10 being maximum level of pain [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. CD3\u0026thinsp;+\u0026thinsp;T cells, CD4\u0026thinsp;+\u0026thinsp;T cells and CD8\u0026thinsp;+\u0026thinsp;T cells were sorted with flow cytometry (FCM) from blood of OLP patients.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eGeneration and analysis of microbiome data\u003c/h2\u003e \u003cp\u003eThe hexadecyltrimethy lammonium bromide/sodium dodecyl sulfate (CTAB/SDS) method was employed to extract deoxyribonucleic acid (DNA) from samples. After the genomic DNA of all the samples was extracted, polymerase chain reaction (PCR) amplifications were performed. The V3-V4 hypervariable regions of the 16S ribosomal ribonucleic acid (rRNA) gene were amplified by the use of specific primers (341F: CCTAYGGGRBGCASCAG, 806R: GGACTACHVGGGTWTCTAAT). All PCRs were performed in 30-\u0026micro;L reactions with 15 \u0026micro;L of Phusion\u0026reg; High-Fidelity PCR Master Mix (Thermo, Waltham, Massachusetts (MA), the United States of America (USA)). A GeneJET Gel Extraction Kit (Thermo Scientific) was used for purifying PCR products that were analyzed by electrophoresis on 2% agarose gels. Samples with strong and clear bands were selected for further analysis, followed by the sequencing of the library on an Illumina HiSeq 2500 platform. Paired-end HiSeq 2500 sequencing reads were amalgamated with sequence tags following the overlap relationship between reads and passed the quality control (QC) test with UPARSE [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The filtering of poor-quality reads and chimaeras was realized by the USEARCH1 pipeline. After dereplication, clean reads were clustered into multiple operational taxonomy units (OTUs) with similarities above 97%. The representative reads of OTUs were aligned to the Ribosomal Database Project (RDP, release 18) to obtain a clear taxonomy of the microbiome.\u003c/p\u003e \u003cp\u003eThe metrics for the quantification of the core microbiome include abundance cutoff values (0.001) and minimum occupancy values (90%). The Adonis2 method from the \u0026ldquo;vegan\u0026rdquo; package was used to probe into the association between host OLP grouping and the microbiome of four oral niches. The α and beta (β) diversity distance matrices were computed using USEARCH11, with a minimum depth threshold of 36,000. Principal co-ordinates (PCoA) analysis was conducted, to assess differences in complexity based on Bray Curtis distance. Differences among healthy and OLP groups were tested using multivariate association with linear models (MaAsLin2) analysis. Effects of age and gender were adjusted. The remaining species or genera were chosen if the p-value was below 0.05. The intersection of differences between the healthy and the other two groups was selected for follow-up analysis. In addition, K-means clustering analysis was carried out for the grouping of differently distributed differential microbes at the buccal mucosa. Those differently distributed microbial species and genera at the buccal mucosa were clustered into three clusters by the similarity of their abundant-variation patterns and named clusters 1\u0026ndash;3. After that, Spearman correlation analysis was utilized to determine the interrelationships between clusters in different groups (|Spearman correlation| \u0026ge; 0.45, p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Later, random forest analysis (version 4.7\u0026ndash;1.1) was used to test the classification effect of these different microbes. Spearman correlation analysis was performed to determine the interrelationships between \u003cem\u003eP. micra\u003c/em\u003e and other differential microbes. The NetShift method available at (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://web.rniapps.net/netshift\u003c/span\u003e\u003cspan address=\"https://web.rniapps.net/netshift\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used for identifying \u0026ldquo;driver\u0026rdquo; nodes in the network of microbial relationships between healthy and diseased groups. Cytoscape (version 3.7.1) and Gephi (version 0.9.2) were applied to draw the network diagram. Additionally, \u0026ldquo;ggplot2\u0026rdquo; (version 3.4.0) and \u0026ldquo;ComplexHeatmap\u0026rdquo; (version 2.16.0) were adopted to generate additional figures.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eFluorescence in situ hybridization\u003c/h2\u003e \u003cp\u003eFluorescence in situ hybridization (FISH) was done on the 5 \u0026micro;m formalin-fixed paraffin-embedded tissue sections of normal buccal mucosae and OLP tissues (buccal mucosae). The sections were incubated for 30 minutes in a pre-heated oven at 60\u0026deg;C and then 20 minutes in a xylene solution. Subsequently, they were immersed in gradient alcohol (100%, 95%, 90%, 80% and 70%; one minute each) and washed four times with phosphate buffered solution (PBS). The FISH procedure was performed as per the instructions of the manufacturer (GenePharma, Suzhou, China). The sequence of \u003cem\u003eP. micra\u003c/em\u003e for Cyanine 3 (cy3) labeled FISH probes was CTG AGC GTC AGT AAA AGT CC [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The slides were rinsed with 4',6-diamidino-2-phenylindole (DAPI) and visualized under confocal laser scanning microscopes (CLSMs). The images were captured with Image-pro plus 6.0 (Media Cybernetics, Inc., in Rockville, Maryland (MD), the US).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSingle-cell RNA-sequencing analysis\u003c/h2\u003e \u003cp\u003eThe 10\u0026times; single-cell RNA-sequencing (scRNA-seq) data containing one normal mucosa sample and five OLP samples were acquired from the Gene Expression Omnibus (GEO) database (GSE211630). They were transformed into S eurat objects by use of the R software \u0026ldquo;Seurat\u0026rdquo; package (version 5.0.1). The double cells were removed with the \u0026ldquo;DoubletFinder\u0026rdquo; package (version 2.0.3). Counts were controlled via the exclusion of low-quality cells based on mitochondrial gene percentages and cycle gene scores. The \u0026ldquo;FindVariableFeatures\u0026rdquo; function was harnessed to screen the first 2,000 highly variable genes. Downscaling and cluster identification were completed using principal component analysis (PCA) based on 2,000 genes and Uniform Manifold Approximation and Projection (UMAP). All the samples were integrated with the \u0026ldquo;RunHarmony\u0026rdquo; function. The \u0026ldquo;FindAllMarkers\u0026rdquo; function was used for identifying significant marker genes within various clusters by setting log2FC to 1. Cluster annotation analysis was conducted based on the literature review of cluster markers. According to the gene family clustering results of fibroblasts, differential genes and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed between normal and OLP tissues with p.adjust\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and logFC\u0026thinsp;\u0026gt;\u0026thinsp;2 (FindMarkers and pathview version 1.38.0 clusterProfiler version 4.7.1.001). The cellular communication of cell subsets was conducted with CellChat (version 1.6.1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBacterial strains and growth conditions\u003c/h2\u003e \u003cp\u003e \u003cem\u003eP. micra\u003c/em\u003e strain ATCC 33270 was obtained from the American Type Culture Collection (Manassas, Virginia (VA), the USA) and cultured in heart (5 g/L) and brain extracts (12.5 g/L), proteose peptone (10.0 g/L), glucose (2.0 g/L), sodium chloride (NaCl, 2.0g/L) and disodium hydrogen phosphate (Na\u003csub\u003e2\u003c/sub\u003eHPO\u003csub\u003e4\u003c/sub\u003e, 2.5 g/L) at 37˚C under anaerobic conditions with 90% nitrogen (N\u003csub\u003e2\u003c/sub\u003e), 5% hydrogen (H\u003csub\u003e2\u003c/sub\u003e), and 5% carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eIsolation of normal and OLP fibroblasts\u003c/h2\u003e \u003cp\u003eBuccal mucosal tissues were acquired from 16 donors (Eight were pathologically confirmed as buccal mucosa OLP and eight were normal buccal mucosal tissues) at the School and Hospital of Stomatology, Shandong University. Tissues were treated by dispase (2 mg/ml, Sigma-Aldrich, Darmstadt, Germany) and rinsed in PBS. Then, they were cut into pieces with a size of 1 mm\u003csup\u003e3\u003c/sup\u003e and cultured in a T25 flask with α-minimum essential medium (α-MEM; Gibco, Washington, the USA) containing 10% fetal bovine serum (FBS; Gibco, Washington, the USA) and 1% penicillin-streptomycin at 37\u0026deg;C in a humidified atmosphere with 5% CO\u003csub\u003e2\u003c/sub\u003e. The purpose was to obtain fibroblasts (Passages 3\u0026ndash;5 were utilized for sequent experiments). All the patients signed an informed consent form. The present study won the approval of the Ethics Committee of the School and Hospital of Stomatology, Shandong University (NO. GR201702).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eIsolation and identification of outer membrane vesicles\u003c/h2\u003e \u003cp\u003eOuter membrane vesicles (OMV) were isolated from the above cultures with an optical density at 600 nm (OD600) of 0.1 at 37\u0026deg;C for 48 hours. The cultures were pelleted with a centrifuge (7,800 g, 4\u0026deg;C, 20 minutes) and filtered with a 0.22 um filter membrane. The filtered supernatant was concentrated using 100 kd ultrafiltration tubes and collected by a Beckman Optima XPN-100 ultracentrifuge (292,700g, 4 ℃, 1 hour). After the removal of the supernatant, OMVs were re-suspended in 200 \u0026micro;l sterile PBS and normalized to an equivalent protein concentration with a bicinchoninic acid (BCA) assay kit (cwbiotech, Beijing, China). The scanning electron microscope images of OMVs were taken by scanning electron microscopy. The diameter of OMVs was quantified using a Nano Sight LM10 instrument (Malvern, Westborough, MA). The fluid of OMVs was analyzed by high-performance liquid chromatography-mass spectrography (HPLC-MS, UltiMate3000).\u003c/p\u003e \u003cp\u003e \u003cb\u003eScreening potential effector proteins of\u003c/b\u003e \u003cb\u003eP. micra\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe FASTA protein sequences of \u003cem\u003eP. micra\u003c/em\u003e ATCC33270 were downloaded from the National Center for Biotechnology Information (NCBI, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Then, they were aligned using Virulence Factors of Pathogenic Bacteria (VFDB, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.mgc.ac.cn/VFs/\u003c/span\u003e\u003cspan address=\"http://www.mgc.ac.cn/VFs/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and Pathogen-Host Interactions (PHI, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.phibase.org/index.jsp\u003c/span\u003e\u003cspan address=\"http://www.phibase.org/index.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) database. The BUSCA tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://busca.biocomp.unibo.it\u003c/span\u003e\u003cspan address=\"http://busca.biocomp.unibo.it\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used to predict subcellular localization.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCloning of recombinant DnaK in\u003c/b\u003e \u003cb\u003eEscherichia coil\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe genomic DNA \u003cem\u003eof P. micra\u003c/em\u003e was used to clone the DnaK gene into \u003cem\u003eEscherichia coil\u003c/em\u003e (\u003cem\u003eE. coil\u003c/em\u003e) expression vector pET-28a. The primers are 5\u0026lsquo;-GTGCCGCGCGGCAGCCATATGATGTCAAAAATTATAGGTATTGATTTAGGTAC-3\u0026rsquo; and 3\u0026lsquo;-ACGGAGCTCGAATTCGGATCCCTATTTATTTTCATCTTCGTCAACTACTTC-5\u0026lsquo;. Recombinant DnaK was generated and purified as a histidine (His)-tag protein in the pET-28a vector. pET-28a containing DnaK was expressed in \u003cem\u003eE. coil\u003c/em\u003e cells with 0.4 mM Isopropyl-β- D-thiogalactoside at 37 ℃ for 4 hours until OD600 reached 1. The protein was purified in hydroxymethyl (Tris)\u0026ndash;NaCl buffer, followed by its overnight dialysis against the dialysis buffer (10 mM Tris\u0026ndash;hydrogen chloride (HCl) Pondus hydrogenii (pH) 8.0, 150 mM NaCl, 10% glycerol, 0.001% sarcosyl). The purified protein was concentrated using 30 kd ultrafiltration tubes and checked with SDS-polyacrylamide gel electrophoresis (PAGE).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eLocalization of DnaK in OMVs\u003c/h2\u003e \u003cp\u003eDnaK or OMVs and 0.05 \u0026micro;g/\u0026micro;l proteinase K (cwbiotech, Beijing, China) (able to degrade DnaK) or 0.1% Triton X-100 (cwbiotech, Beijing, China) (able to punch on cell membranes) were incubated at 37 ℃ for 10 minutes and then added with 5 mM Phenylmethanesulfonyl fluoride (PMSF) (cwbiotech, Beijing, China) at room temperature for 10 minutes. Afterwards, the samples were heated at 70 ℃ for 5 minutes to suppress protein K. Untreated DnaK and OMVs were used as control groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEnzyme-linked immunosorbent assay\u003c/h2\u003e \u003cp\u003eNormal fibroblasts (NFs), OLPFs, \u003cem\u003eP. micra\u003c/em\u003e (6.875 \u0026times; 10\u003csup\u003e7\u003c/sup\u003e) treated NFs (The ratio of \u003cem\u003eP. micra\u003c/em\u003e and NFs was 50:1) or \u003cem\u003eP. micra\u003c/em\u003e conditional medium (CM, 20 \u0026micro;l, an optical density at the wavelength 600 nm of 1 OD\u0026thinsp;=\u0026thinsp;1 was equivalent to 7.2 x 10\u003csup\u003e7\u003c/sup\u003e/mL (\u003cem\u003eP. micra\u003c/em\u003e) ) treated NFs (The ratio of \u003cem\u003eP. micra\u003c/em\u003e and NFs was 50:1), OMV (10 \u0026micro;g/uL) treated NFs, lentivirus-green fluorescent protein (GFP)-DnaK (lv-GFP-DnaK) or lentivirus-Flag-DnaK (lv-DnaK) and lentivirus-control in PCDNA3.1 (Wzbio, Jinan, China), Bcl-2 associated athanogene 3 (Bag3)-targeting small interfering RNA (siRNA) in lv-DnaK (si-Bag3) (S: CAGCAACCUUGAAGCAGAUTT; AS: AUCUGCUUCAAGGUUGCUGTT), inhibitor of nuclear factor kappa-B kinase subunit gamma (IKK-γ)-targeting siRNA (si-IKK-γ) in lv-DnaK (S: UGGAGAAGCUCGAUCUGAATT; AS: UUCAGAUCGAGCUUCUCCATT) and scrambled non-targeting control siRNA (si-control) treated with none or Bafilomycin A1 (BafA1, 5 nM) (The number of the above fibroblasts was 1.375 \u0026times; 10\u003csup\u003e6\u003c/sup\u003e) were plated at in complete medium (13.75 ml) in a 10-cm plate for 2 days for the generation of CM. The CM was gathered via a 0.2 \u0026micro;M filter and stored at the temperature of -80\u0026deg;C. The CM concentration of TNF-α was measured by enzyme-linked immunosorbent assay (ELISA, BioLegend, California, the USA) as per the instructions of the manufacturer.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot assay\u003c/h2\u003e \u003cp\u003eThe proteins of NFs, OLPFs, \u003cem\u003eP. micra\u003c/em\u003e treated NFs or \u003cem\u003eP. micra\u003c/em\u003e CM treated NFs, OMV treated NFs, lv-DnaK, si-Bag3, si-IKK-γ and scrambled non-targeting control siRNA (si-control) treated with none or BafA1 (5 nM) were obtained with Radio Immunoprecipitation Assay (RIPA) buffer. Equal amounts of proteins were resolved by 10% SDS-PAGE [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and immunoblotted with primary antibodies against many antigens overnight. These antigens included microtubule-associated protein 1 light chain 3 beta (LC3B), phosphorylated inhibitory subunit of NF kappa B alpha (p-Iκβα), total-Iκβα (CST, California, the USA), DnaK, p-p65, total-p65, IKK-γ (Abcam, Cambridge, England), Bag3, sequestosome 1 (SQSTM1, Proteintech, Wuhan, China) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH, Affinity, Ohio, the USA). These equal amounts of proteins were then incubated with the horseradish peroxidase (HRP)-conjugated secondary antibodies (Affinity, Ohio, the USA). Immunoreactive bands were analyzed by enhanced chemiluminescence reaction (ECL, Amersham Pharmacia Biotech, the USA) and normalized by GAPDH with Quantity One.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003emCherry-GFP-LC3B\u003c/h2\u003e \u003cp\u003eNFs, OLPFs, OMV treated NFs, lv-DnaK, si-Bag3 and si-IKK-γ were transfected with mCherry-GFP-LC3B adenovirus (Wzbio, Jinan, China). The cell nucleus was counterstained using DAPI. Images were captured for autophagosomes and autolysosomes (yellow and red puncta, respectively) on CLSMs. Image-pro plus 6.0 was used to analyze fluorescence signals.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eImmunofluorescence histochemistry\u003c/h2\u003e \u003cp\u003eNFs, NFs treated with OMVs, lv-DnaK or stably expressing enhanced GFP (EGFP)-LC3B were seeded in 12-well plates with sections for one night and fixed with 4% paraformaldehyde. The sections were processed with 3.0% hydrogen peroxide, followed by their incubation in 5.0% bovine serum albumin. Besides, they underwent overnight incubation at 4\u0026deg;C with antibodies against pkh67 (maokangbio, Shanghai, China), β-Tubulin (CST, California, the USA), Bag3 and IKK-γ, and then 1-hour incubation with Alexa Fluor 488/594-labelled goat anti-mouse/rabbit immunoglobulin G (IgG) (Abbkine, California, the USA) at 37\u0026deg;C in the dark. The images were captured with a laser scanning confocal microscope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eProtein pull-down\u003c/h2\u003e \u003cp\u003eHis-DnaK and NF suspended cell fluid was incubated in PBS at 4 ℃ for 1 hour. After complete binding, the bound proteins were immunoprecipitated by the instructions of PierceTM Pull-Down PolyHis Protein: Protein Interaction Kit (Thermo Fisher Scientific, New York, the USA) and analyzed by HPLC-MS (UltiMate3000).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eCo-immunoprecipitation\u003c/h2\u003e \u003cp\u003eThe lysates of lv-Flag-DnaK, si-Bag3 and si-IKK-γ were processed by Nonidet P-40 (NP-40) buffer. They underwent overnight incubation at 4\u0026deg;C with DnaK or Bag3, IKK-γ, Flag (Proteintech, Wuhan, China) and normal IgG (Santa, California, USA) with rotation. Protein A/G PLUS agarose beads (Santa, California, the USA) underwent 1-hour incubation and rotation at 4\u0026deg;C. The complexes were washed and eluted from the beads through boiling in the SDS-PAGE sample. The immunoprecipitates were analyzed by Western blotting with DnaK or Bag3, IKK-γ and Flag.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were presented as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) and repeated three times. Student\u0026rsquo;s t-test or one- or two-way analysis of variance (ANOVA) was used to analyze inter-group comparisons. In addition, p\u0026thinsp;\u0026le;\u0026thinsp;0.05 was considered to show the statistical significance that was analyzed using Statistical Package for the Social Sciences (SPSS) software version 17.0.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eVariation of the oral microbiome in OLP patients\u003c/h2\u003e \u003cp\u003e To reveal the variation of the oral microbiome in OLP patients, 704 samples of buccal mucosae, tongue dorsum, lip mucosae and saliva from 80 healthy individuals and 91 OLP patients (including 50 NE-OLP and 41 E-OLP patients) in Shandong Province, China (Tab.S1) were included. The clinical indicators and blood-derived CD3+, CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells for each OLP patient were collected (Tab.S1). The 16S rRNA amplicon sequencing (CRA 003224) obtained 58.56\u0026nbsp;million clean reads (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA), which were annotated to 44 phyla, 976 genera and 1,138 species. The saturation of microbiome data at each oral site was illustrated in the rarefaction curves (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA). At the phylum level, Firmicutes, Proteobacteria and Bacteroidetes were the most enriched microorganisms across all the oral sites in the population of this study, but the ranking of their abundance varied across oral sites. In healthy individuals, for example, Firmicutes had the highest abundance in buccal and lip mucosae, while Bacteroidetes and Proteobacteria were mostly enriched in the tongue dorsum and saliva, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). However, their abundance was significantly influenced by NE-OLP and E-OLP diseases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). At the genus level, \u003cem\u003eStreptococcus, Haemophilus, Neisseria\u003c/em\u003e and \u003cem\u003eRothis\u003c/em\u003e were in high abundance at each oral site, but the ranking of their abundance was also affected by oral sites and OLP disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eThe Adonis analysis of Bray-Curtis and Jaccard distances simultaneously showed that the microbiome of buccal and lip mucosae, tongue dorsum and saliva was significantly correlated with OLP disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC,E). Among them, the buccal mucosa was the site mostly correlated with oral sites. Simpson and Shannon indices revealed that NE-OLP and E-OLP patients showed a significantly higher microbial diversity of the buccal mucosa compared with healthy individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). The microbiome at the lip mucosa and saliva showed the same trend, and the tongue dorsum increased in abundance despite being insignificant (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC,D). The core microbiome of the buccal mucosa at the genus level with occurrence rate\u0026thinsp;\u0026ge;\u0026thinsp;90% and relative abundance\u0026thinsp;\u0026ge;\u0026thinsp;0.001 was analyzed, and 18 core microorganisms were found in all populations. Meanwhile, it was found that seven microorganisms, including \u003cem\u003eParvimonas, Tannerella, Treponema\u003c/em\u003e, etc., were enriched in OLP patients with high frequency and abundance (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). At the species level, 22 microbes exhibited high abundance in the whole population. Among them, eight microbes were core bacteria in OLP patients, including the periodontal pathogen \u003cem\u003eTannerella forsythia\u003c/em\u003e and \u003cem\u003eP. micra\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). β diversity analysis revealed that the microbial composition of the buccal mucosal of NE-OLP and E-OLP patients greatly differed from that of healthy individuals, especially the first principal component, 20.2% by Bray Curtis Distance and 14.1% by Jaccard distance (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF). The β diversity of the lip mucosa and saliva was insignificant among individuals. The first principal component of the dorsal tongue showed a significant difference between OLP patients and healthy controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eF,H).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eIncrease of\u003c/b\u003e \u003cb\u003eP. micra\u003c/b\u003e \u003cb\u003ein the buccal mucosae of OLP patients\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAt the species level, MaAsLin analysis was performed among the buccal mucosae of NE-OLP and E-OLP patients and healthy individuals. It was discovered that 75 and 72 microbes showed significant differences between NE-OLP and E-OLP patients, and healthy individuals (Tab. S2). A heat map of 31 microbes overlapped in both groups of OLP patients is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA. These microorganisms were divided into three clusters, and the microbes in clusters 2 and 3 were significantly enriched in NE-OLP and E-OLP patients. Among them, \u003cem\u003eP. micra\u003c/em\u003e, \u003cem\u003ePeptostreptococcus stomatis\u003c/em\u003e, \u003cem\u003eStreptococcus oralis\u003c/em\u003e and \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e were microbes most different from healthy individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Spearman correlation network analysis showed that the microbes within clusters 2 and 3 were closely and positively correlated with each other, while cluster 1 was seldom associated with clusters 2 and 3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). MaAsLin analysis at the genus level demonstrated that \u003cem\u003eParvimonas, Peptostreptococc\u003c/em\u003eu and \u003cem\u003eStreptococcus\u003c/em\u003e were also the microorganisms most significantly divergent among healthy individuals and NE-OLP and E-OLP patients (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eThe random forest analysis of 31 differential bacteria at the buccal mucosa was performed to validate their classification effect in NE-OLP and E-OLP patients versus healthy controls. The results suggested that the area under the curve (AUC) of classifying NE-OLP patients and healthy individuals was 0.785 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) and that of E-OLP patients and healthy individuals was 0.849 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). This indicated that these bacteria in the buccal mucosa were closely correlated with OLP. Next, the MeanDecreaseAccuracy of these bacteria was calculated, and \u003cem\u003eP. micra\u003c/em\u003e was found to be the microbe differentiating the largest contribution between NE-OLP and E-OLP patients from healthy controls (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Random forest analysis at the genus level also revealed that Parvimonas was the microorganism contributing most to distinguishing NE-OLP and E-OLP patients from healthy controls (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eC). Spearman correlation analysis showed a positive correlation between \u003cem\u003eP. micra\u003c/em\u003e and other high contributing microorganisms like \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e and \u003cem\u003eTannerella forsythia\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). NetShift analysis showed that \u003cem\u003eP. micra\u003c/em\u003e was a network shift driver bacterium from healthy individuals to E-OLP patients and also from NE-OLP patients to E-OLP ones (Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003eD). \u003cem\u003eP. micra\u003c/em\u003e was regressed with clinical measures in NE-OLP and E-OLP patients. It was found that \u003cem\u003eP. micra\u003c/em\u003e was significantly correlated with VAS in the NE-OLP group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), CD8\u0026thinsp;+\u0026thinsp;T cells in the E-OLP group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and CD4+/CD8\u0026thinsp;+\u0026thinsp;T cells (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG). These results suggested that \u003cem\u003eP. micra\u003c/em\u003e may be an important microorganism in OLP disease.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eIncrease of inflammatory response and blockade of autophagy in OLPFs\u003c/h2\u003e \u003cp\u003eWhether \u003cem\u003eP. micra\u003c/em\u003e was present in the buccal mucosae of OLP patients was validated by a FISH assay. It was proved that \u003cem\u003eP. micra\u003c/em\u003e was significantly enriched in the junction of epithelial and connective tissue layers of OLP patients compared to healthy individuals (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). As a proinflammatory bacterium in the oral cavity, \u003cem\u003eP. micra\u003c/em\u003e can cause a series of inflammatory responses in invading tissues [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The activity of the inflammatory signaling pathway in the buccal mucosae of OLP patients was investigated. The scRNA-seq data of buccal mucosa tissues between normal and OLP patients (GSE211630) were analyzed, and 10 clusters of cells were annotated based on the enrichment of cluster-defining gene markers (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Cell component analysis showed that the proportion of fibroblasts dramatically decreased, while most immune cells increased, especially T cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Intercellular and molecular communication showed that communications between CD4\u0026thinsp;+\u0026thinsp;T cells, CD8\u0026thinsp;+\u0026thinsp;T cells and fibroblasts were increased, and fibroblasts could regulate a majority of other cell types in the epithelial and stromal tissues of OLP patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). KEGG pathway enrichment analysis indicated that a variety of inflammatory-related pathways such as NF-қB, TNF, Janus tyrosine kinase-signal transducers and activators of transcription (JAK-STAT) and phosphatidylinositol 3-kinase-protein kinase B (PI3K-Akt) signaling pathways were enriched in OLPFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). TNF-α was linked to the activation of T cells, Langerhans\u0026rsquo; cells, mononuclear cells and epithelial keratinocytes in OLP [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The secreting cytokines in NF-қB pathway were analyzed. It was noted that TNF-α, CCL21 and CCL19 were significantly up-regulated in OLPF compared with NFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF). To validate the activation of TNF-α in fibroblasts in the buccal mucosa, fibroblasts were separated and cultured from healthy individuals (NFs) and OLP patients (OLPFs). Western blotting showed that p-p65 and p-Ikβα had significantly high expression in OLPFs compared with NFs (n\u0026thinsp;=\u0026thinsp;3, (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05)) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH). ELISA assay showed that OLPFs had a significantly higher level of TNF-α in comparison to NFs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG).\u003c/p\u003e \u003cp\u003eAutophagy is an important host cell defense strategy against microbial stimulation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The state of autophagy in NFs and OLPFs was examined. Western blotting showed that SQSTM1 and LC3B-Ⅱ exhibited a notable increase in OLPFs compared with NFs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eL). The autophagic flux of OLPFs using inhibitors BafA1 showed that LC3B-II increased in NFs and OLPFs when lysosomal-dependent LC3B-II degradation was blocked (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eM). The quantification of mCherry (red) (autolysosomes) and yellow puncta (autophagosomes) in NFs and OLPFs with mCherry-GFP-LC3 demonstrated that OLP increased the number of autophagosomes in fibroblasts, and decreased the number of autolysosomes in comparison with NFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eN). Next, whether the blockade of autophagy was involved in TNF-α secretion was investigated. ELISA assay was applied in NFs and OLPFs with or without BafA1. The results showed that the addition of BafA1 significantly increased the secretion of TNF-α in both NFs and OLPFs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eO).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003ePromotion of TNF-α release by\u003c/b\u003e \u003cb\u003eP. micra\u003c/b\u003e \u003cb\u003eand induction of autophagic blockade in fibroblasts\u003c/b\u003e\u003c/p\u003e \u003cp\u003eGiven the enrichment of \u003cem\u003eP. micra\u003c/em\u003e in the stromal tissues of OLP, whether \u003cem\u003eP. micra\u003c/em\u003e could induce inflammatory activation in NFs was tested. The abundance of TNF-α between NFs and NFs\u0026thinsp;+\u0026thinsp;\u003cem\u003eP. micra\u003c/em\u003e was compared by ELISA assay. It was shown that \u003cem\u003eP. micra\u003c/em\u003e increased the secretion of TNF-α to a large extent (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). To verify whether \u003cem\u003eP. micra\u003c/em\u003e had an inflammation-promoting effect, CM from \u003cem\u003eP. micra\u003c/em\u003e was obtained and used to treat NFs. The results indicated that adding CM in NFs increased the secretion of TNF-α to a great degree (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). OMVs are one of the key components secreted by microbes in the pathogenesis of oral disease [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Therefore, OMVs were isolated and characterized from the CM of \u003cem\u003eP. micra\u003c/em\u003e (Supplementary Fig.\u0026nbsp;2), and the abundance of TNF-α between NFs and NFs\u0026thinsp;+\u0026thinsp;\u003cem\u003eP. micra\u003c/em\u003e-derived OMVs was compared. The result indicated that the OMVs of \u003cem\u003eP. micra\u003c/em\u003e also significantly increased the secretion of TNF-α (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Next, whether \u003cem\u003eP. micra\u003c/em\u003e and CM and OMVs of \u003cem\u003eP. micra\u003c/em\u003e could also activate NF-қB pathway was examined. The phosphorylation of p65 and Iқβα was significantly increased in \u003cem\u003eP. micra/\u003c/em\u003eCM/OMV groups in comparison with the NF group (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eNext, the autophagic state of NFs with the stimulation of \u003cem\u003eP. micra\u003c/em\u003e, CM or OMVs of \u003cem\u003eP. micra\u003c/em\u003e was detected. Western blotting showed that both SQSTM1 and LC3B-Ⅱ were over-expressed in NFs\u0026thinsp;+\u0026thinsp;\u003cem\u003eP. micra\u003c/em\u003e, NFs\u0026thinsp;\u003cem\u003e+\u003c/em\u003e\u0026thinsp;CM of \u003cem\u003eP. micra\u003c/em\u003e and NFs\u0026thinsp;+\u0026thinsp;OMVs of \u003cem\u003eP. micra\u003c/em\u003e groups compared with NFs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). In addition, the expression of LC3B-II was not changed between NFs and NFs-OMVs treated with BafA1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). In addition, mCherry-GFP-LC3 tests showed that the autophagy of \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs was blocked (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). These results suggested OMVs are an important pathogenic component of \u003cem\u003eP. micra\u003c/em\u003e to promote the inflammatory response and block the autophagic flux in fibroblasts.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eInvolvement of DnaK in\u003c/b\u003e \u003cb\u003eP. micra\u003c/b\u003e\u003cb\u003e-derived OMVs in inflammatory activation and autophagy flux blockade\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo reveal how \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs promote inflammation and block autophagy flux, OMVs were first labeled with pkh67 and, NF cytoskeletal protein was labeled by β-tubulin. Immunofluorescence (IF) showed that OMVs could be detected in fibroblasts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). OMVs may exert toxic effects by releasing their components [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] (pathogenic proteins or small RNAs) within host cells [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Herein, the proteome of \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs was profiled by mass spectrometry, and 13 candidate effector proteins were identified (Tab. S3). Among them, DnaK was selected as the putative virulent effector for the following study. Whether DnaK could be detected in OLPFs was tested by Western blotting. The results revealed the high enrichment of DnaK in OLPFs in comparison to NFs(n\u0026thinsp;=\u0026thinsp;3, p \u0026lt; 0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Similarly, a higher abundance of DnaK could be detected in NFs\u0026thinsp;+\u0026thinsp;\u003cem\u003eP. micra\u003c/em\u003e, NFs\u0026thinsp;\u003cem\u003e+\u003c/em\u003e\u0026thinsp;CM of \u003cem\u003eP. micra\u003c/em\u003e and NFs\u0026thinsp;+\u0026thinsp;\u003cem\u003eP. micra\u003c/em\u003e-derived OMV groups in comparison with NFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC).\u003c/p\u003e \u003cp\u003eTo analyze the location of DnaK in OMVs, OMVs were treated with Proteinase K (degrade protein but not membranous structures) alone (OMV\u0026thinsp;+\u0026thinsp;K group) or both Proteinase K and Triton X-100 (OMV\u0026thinsp;+\u0026thinsp;K\u0026thinsp;+\u0026thinsp;T group) compared with Dnak (D group) or both DnaK and Proteinase K (D\u0026thinsp;+\u0026thinsp;K group). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, the abundance of DnaK was reduced in the OMV\u0026thinsp;+\u0026thinsp;K group compared with the OMV group, and DnaK in the OMV\u0026thinsp;+\u0026thinsp;K\u0026thinsp;+\u0026thinsp;T group was less abundant than that in the OMV\u0026thinsp;+\u0026thinsp;K group. These results suggested that DnaK was located both in the outer membrane and cytoplasm of OMVs.\u003c/p\u003e \u003cp\u003eTo test its pathogenic effects, DnaK was transfected into NFs by lentivirus. IF assay showed that DnaK was situated in the cytoplasm and nucleus of NFs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Whether DnaK could mimic the pathogenicity of OMVs on NFs was investigated. ELISA assay showed that the transfection of DnaK (lv-DnaK) could facilitate the significant increase of TNF-α compared with NFs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE). Next, the activation of NF-қB pathway and autophagy under the stimulation of lv-DnaK was examined. The results indicated that the phosphorylation of Iқβα and p65 exhibited a marked increase (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF), and the expression of SQSTM1 and LC3B-Ⅱ was remarkably increased with the stimulation of DnaK (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eG). BafA1 treatment and mCherry-GFP transfection tests exhibited that the over-expression of DnaK inhibited autophagy flux (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eH,I). These results suggested that DnaK is an important pathogenic effector of \u003cem\u003eP. micra\u003c/em\u003e-derived OMVs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eInteraction of DnaK with Bag3 to activate NF-қB pathway and decrease autophagy flux\u003c/h2\u003e \u003cp\u003eTo identify the interacted protein of DnaK in fibroblasts, GST/His pull-down assay and HPLC-MS analysis were applied to capture the candidate protein combined with His-tagged DnaK, which identified 87 candidate proteins (Tab. S4). Among these candidate proteins, Bag3 was reported as an autophagy-related protein [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The combination of DnaK and Bag3 was tested by co-immunoprecipitation (Co-IP) experiments. The result showed that DnaK could bind to Bag3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Co-IF assay showed the co-localization of DnaK with Bag3 in the nucleus and cytoplasm of lv-GFP-DnaK (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eTo investigate the impact of DnaK on Bag3, the abundance of DnaK and Bag3 in NFs and OLPFs was compared. The results showed that an increase of DnaK did not induce the over-expression of Bag3 in OLPFs (n\u0026thinsp;=\u0026thinsp;3, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). To examine the role of Bag3 in DnaK-induced inflammation, a transfection assay was performed to knock down Bag3 with small-interference RNA in lv-DnaK (si-Bag3). ELISA analysis showed that si-Bag3 could dramatically suppress the secretion of TNF-α compared with NFs (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). Next, the activation of NF-қB pathway in si-Bag3 was examined, and p-Iқβα and p-p65 were found to be both significantly decreased in si-Bag3 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE). Moreover, an investigation was conducted on the role of Bag3 in autophagy. In comparison to lv-DnaK, si-Bag3 promoted autophagic flux by BafA1 treatment and mCherry-GFP transfection (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eF,H). These results suggested that Bag3 is an important protein mediating the inflammatory response and autophagy of DnaK.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eInteraction of DnaK and Bag3 with IKK-γ to activate inflammatory response and inhibit autophagy\u003c/h2\u003e \u003cp\u003eBag3 is reported to modulate NF-κB pathway via IKK-γ [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. IKK-γ was tested in OLPFs by Western blotting, and the results showed that IKK-γ was highly enriched in OLPFs in comparison with NFs (p\u0026lt;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). Therefore, the interaction of IKK-γ-DnaK-Bag3 was verified by Co-IP in lv-DnaK, and it was shown that IKK-γ could be combined with DnaK-Bag3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eB). This result in si-Bag3 was validated, and the knockdown of Bag3 was shown to significantly decrease the abundance of IKK-γ (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eC). In addition, the combination of DnaK and IKK-γ reduced si-Bag3 compared with lv-DnaK (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eD). These results suggested that DnaK was combined with Bag3 to interact and regulate the expression of IKK-γ.\u003c/p\u003e \u003cp\u003eIKK-γ mediates the effect of autophagy [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and NF-қB pathway [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. IKK-γ and EGFP marked LC3B puncta were co-localized, which showed that the accumulation of LC3B puncta could be co-expressed with IKK-γ in lv-DnaK (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). To determine which step of autophagy that IKK-γ participates in, IKK-γ was knocked down by siRNA in lv-DnaK (si-IKK-γ). The results showed that the abundance of SQSTM1 and LC3B-Ⅱ was significantly decreased in si-IKK-γ cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF). BafA1 treatment and mCherry-GFP transfection tests were used and showed that IKK-γ knockdown promoted the autophagic influx of lv-DnaK (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG,H). A study showed that IKK-γ can interact with SQSTM1 to regulate LC3 proteins [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The knockdown of IKK-γ could reduce the expression of SQSTM1 with and without BafA1 treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eG). Furthermore, the knockdown of IKK-γ reduced the abundance of p-Iқβα and p-p65 and decreased the level of TNF-α in lv-DnaK (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003eF,L). These results suggested the DnaK-Bag3-IKK-γ signaling axis could regulate autophagy and NF-қB pathway.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe oral microbiome of OLP patients differed from that of healthy controls, which suggested that the oral microbiota may correlate with the onset and progression of OLP [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Nevertheless, how oral microbes contribute to OLP progression is still unknown. In the current study, the correlation between OLP and a rarely reported oral opportunistic pathogen, \u003cem\u003eP. micra\u003c/em\u003e was demonstrated first. In addition, the first pathogenic study of \u003cem\u003eP.micra\u003c/em\u003e in OLP was conducted, and a new mechanism by which \u003cem\u003eP. micra\u003c/em\u003e promotes inflammatory response and blocks autophagy was discovered (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e To systematically reveal the association of the oral microbiome with OLP disease, a comprehensive microbiome-wide association study was first conducted between NE/E-OLP patients and healthy controls at the oral niche of the buccal region, the lip mucosa, the tongue dorsum and saliva. Consistent with previous studies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], OLP patients and healthy controls showed significant differences, especially at the oral site of the buccal mucosa. Of note, \u003cem\u003eP. micra\u003c/em\u003e was the most differently distributed bacterium, which is known as an oral commensal bacterium closely related to chronic and periapical periodontitis [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. FISH assay validated that \u003cem\u003eP. micra\u003c/em\u003e was enriched in the junction of epithelial and connective tissue layers with high abundance in OLP patients.\u003c/p\u003e \u003cp\u003eFibroblasts, the main cellular component of connective tissues of the buccal mucosa, remain stationary in a stable environment [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. In response to tissue damage and inflammatory reactions, fibroblasts can be activated to exert multiple immune effects. Single-cell analysis found that the TNF-α of the fibroblasts-related NF-қB pathway was activated and communicated with multiple cells in the tissues of OLP patients. Consistently, it was proved that fibroblasts from OLP and normal tissues could over-express TNF-α and activate NF-қB pathway in OLPFs. Thus, how the inflammatory response of fibroblasts is triggered is an important question in OLP disease.\u003c/p\u003e \u003cp\u003eThe FISH assay showed significant enrichment of \u003cem\u003eP. micra\u003c/em\u003e in the junction of epithelial and connective tissue layers in OLP patients, which is a highly enriched region of fibroblasts. Hence, the pathogenic study was carried out among \u003cem\u003eP. micra\u003c/em\u003e and fibroblasts. It was demonstrated that \u003cem\u003eP. micra\u003c/em\u003e could promote TNF-α secretion and block autophagy. To explore the underlying mechanism, CM and OMVs were extracted from fibroblasts treated with \u003cem\u003eP. micra\u003c/em\u003e, and similar results were obtained. As a result, OMVs as an important way for pathogens to exert pathogenicity have received attention [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, it was noticed that DnaK of \u003cem\u003eP. micra\u003c/em\u003e OMVs was one of the main effectors, which could activate NF-қB pathway and block autophagy. To explore the interacted protein of DnaK in fibroblasts, multiple host proteins were captured, and Bag3 was selected for the following study. As a sensor of heat shock protein 70 (HSP70), Bag3 can bind to numerous protein-protein domains that support different activities by affecting the upstream regulators of the signaling pathway and the process of autophagy flux [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Bag3 expression was silenced in lv-DnaK (si-Bag3). It was found that si-Bag3 could secrete less TNF-α, inhibit NF-қB pathway and activate autophagy. Next, Co-IP assays were conducted. It was proved that IKK-γ directly interacted with DnaK and Bag3; the expression of IKK-γ decreased with the decrease of Bag3 in si-Bag3; si-IKK-γ could secrete less TNF-a, inhibit NF-қB pathway and activate autophagy. Additionally, IKK-γ was mediated by LC3 proteins binding to LC3-interacting region (LIR) motifs present in p62 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. IKK-γ lowered the threshold of p62 in lv-DnaK and si-IKK-γ with and without BafA1 treatment.\u003c/p\u003e \u003cp\u003eIn conclusion, the results of this study suggested that \u003cem\u003eP. micra\u003c/em\u003e plays a vital role in the oral dysbiosis of OLP disease. DnaK of \u003cem\u003eP. micra\u003c/em\u003e OMVs interacted with the Bag3 of fibroblasts and modulated the expression of IKK-γ, which regulated the secretion of TNF-α by activating the NF-қB pathway and inhibiting autophagy. These results elucidate the potential pathogenesis of OLP and provide new insights into the treatment and prevention of OLP.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study obtained the approval of the Ethics Committee of the School and Hospital of Stomatology, Shandong University (No. GR201702).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data are included in the article or in the supplementary material.All datasets and raw data are available from the corresponding author onreasonable request. The raw data of 16S rRNA amplicon sequencing are available from GSA database (CRA 003224).The raw data of scRNA-seq are openly available in GEO database (GSE211630).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe sincerely thank the foundation support of National Natural Science Foundation of China (No. 82270980, 82071122), Shandong Natural Science Foundation (No. ZR2023MH045), the start-up fund for introduction of talents to Jinan Central Hospital (No. YJRC2021002), Science and Technology Development Program of Jinan Municipal Health Commission（No.2022-2-7）,the National Young Scientist Support Foundation (2019), Excellent Young Scientist Foundation of Shandong Province (No. ZR2021JQ29), Major Innovation Projects in Shandong Province (No. 2021SFGC0502), the Periodontitis innovation team of Jinan City (2021GXRC021), Taishan Young Scientist Project of Shandong Province (2019), Oral Microbiome Innovation Team of Shandong Province (No. 2020KJK001), Shandong Province Key Research and Development Program (No. 2021ZDSYS18).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQiang Feng, Xiaoli Ji conceived and designed the project. Xiaoli Ji performed most of the experiments and analyzed the data. \u0026nbsp;Mengfan Zhi and Xiang Lan analyzed the 16S rRNA amplicon \u0026nbsp;and scRNA sequencing. Xiufeng Gu, and Lixiang Song provided technical assistance.\u0026nbsp;\u0026nbsp;Xiangming Qi, Yin Han, Peipei Sun, \u0026nbsp;Jingyuan Li and Lixiang Song collected the samples. Xiaoli Ji, Qiang Feng wrote and revised the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Prof. Yixiang Wang (Peking University School and Hospital of Stomatology) for excellent technical assistance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi C, Tang X, Zheng X, Ge S, Wen H, Lin X, et al. Global Prevalence and Incidence Estimates of Oral Lichen Planus: A Systematic Review and Meta-analysis. 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EMBO J. 2021;40:e108174.\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mbio","sideBox":"Learn more about [Microbiome](http://microbiomejournal.biomedcentral.com/)","snPcode":"40168","submissionUrl":"https://submission.nature.com/new-submission/40168/3","title":"Microbiome","twitterHandle":"@MicrobiomeJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Oral lichen planus, DnaK, Bag3, Outer membrane vesicles, NF-κB","lastPublishedDoi":"10.21203/rs.3.rs-4578173/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4578173/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\u003eOral lichen planus (OLP) is one of the most frequent oral mucosal diseases associated with chronic inflammation despite extremely insufficient knowledge of its pathogenic mechanism.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHere, the microbiome of buccal and lip mucosae, tongue dorsum and saliva among OLP patients and healthy individuals was analyzed. It was found that the oral microbiome, especially the buccal mucosa, varied significantly in OLP patients. Network, random forest and Netshift analyses simultaneously showed that \u003cem\u003eParvimonas micra\u003c/em\u003e (\u003cem\u003eP. micra\u003c/em\u003e) was an important bacterium of OLP disease. Fluorescence in situ hybridization (FISH) and single-cell ribonucleic acid (RNA) sequencing profiling suggested that fibroblasts were the candidate target with the characteristic of up-regulating the nuclear factor kappa-B (NF-қB) signaling pathway related to tumor necrosis factor-alpha (TNF-α) and communicating with multiple immune cell types. Mechanism analysis showed that \u003cem\u003eP. micra\u003c/em\u003e, \u003cem\u003eP. micra-\u003c/em\u003ederived conditional medium (CM) and outer membrane vesicles (OMVs) could induce the activity of NF-қB signaling pathway and inhibit autophagy in buccal mucosal fibroblasts. As one of the main pathogenic effectors, the DnaK of \u003cem\u003eP. micra-\u003c/em\u003ederived OMVs could inhibit autophagy and promote TNF-α secretion via the DnaK-Bcl-2 associated athanogene 3 (Bag3)-inhibitor of nuclear factor kappa-B kinase subunit gamma (IKK-γ) signaling axis.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHere we demonstrate that \u003cem\u003eP. micra\u003c/em\u003e\u0026rsquo;s OMV drives OLP via DnaK -Bag3-IKK-γ/NF-қB signaling axis in the fibroblasts as new insights into the pathogenic mechanism of OLP.\u003c/p\u003e","manuscriptTitle":"DnaK of Parvimonas micra OMVs interacted with the host fibroblast Bag3-IKK-γ axis to accelerate TNF-α secretion in oral lichen planus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-15 19:21:17","doi":"10.21203/rs.3.rs-4578173/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-06T13:44:02+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"325161775504345295253049053303367514990","date":"2024-10-16T12:44:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-15T19:55:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331898193409421087263625372200624489621","date":"2024-10-07T16:31:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-04T13:08:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"305879870541258391162626458640366241383","date":"2024-07-08T10:17:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-08T09:33:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-20T10:41:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-17T10:01:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Microbiome","date":"2024-06-13T20:09:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mbio","sideBox":"Learn more about [Microbiome](http://microbiomejournal.biomedcentral.com/)","snPcode":"40168","submissionUrl":"https://submission.nature.com/new-submission/40168/3","title":"Microbiome","twitterHandle":"@MicrobiomeJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"291f72ae-3e27-4b1d-b65a-0ea37f9d6ee8","owner":[],"postedDate":"July 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T16:02:32+00:00","versionOfRecord":{"articleIdentity":"rs-4578173","link":"https://doi.org/10.1186/s40168-025-02151-5","journal":{"identity":"microbiome","isVorOnly":false,"title":"Microbiome"},"publishedOn":"2025-07-14 15:57:00","publishedOnDateReadable":"July 14th, 2025"},"versionCreatedAt":"2024-07-15 19:21:17","video":{"identity":"6135ab81001335614a7251d37247b810"},"vorDoi":"10.1186/s40168-025-02151-5","vorDoiUrl":"https://doi.org/10.1186/s40168-025-02151-5","workflowStages":[]},"version":"v1","identity":"rs-4578173","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4578173","identity":"rs-4578173","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}