Secretomes of Gingival Fibroblasts From Periodontally Diseased Tissues: A Proteomic Analysis
Introduction Human gingival fibroblasts (GF) are a crucial component of the gingival stroma and have a significant role in the maintenance of periodontal tissue architecture and homeostasis (Wielento et al. ). Fibroblasts primarily synthesize the extracellular matrix (ECM), which consists of a variety of macromolecules whose assembly, architecture, and biomechanical properties vary within and between tissues (Plikus et al. ; McCulloch and Bordin ). Moreover, fibroblasts communicate with each other and with other cells by secreting growth factors and cytokines or by developing cell–cell contacts, creating cellular communication networks (Plikus et al. ). While the primary function of GF is the maintenance of the homeostasis of the gingival tissues by regulating the production of ECM, these cells also play important roles in various physiological (wound healing) and pathological situations (inflammation) due to their high regeneration potential (Wielento et al. ; Häkkinen et al. ). In periodontitis, periodontal tissue destruction occurs due to the combination of a dysbiotic subgingival biofilm and a non‐resolving host‐response, which results in changes in the ECM and surrounding microenvironment. This dysbiosis, in turn, activates fibroblasts through migration, proliferation, and contraction to restore homeostasis in the damaged tissue (Wielento et al. ). This ability to respond to chemical and physical signals from the ECM, allows the GF to adopt a secretory and migratory phenotype resulting in “scarless” tissue healing, with a regenerative potential similar to adult mesenchymal stem cells (MSC), as demonstrated both in vitro and in vivo (Häkkinen et al. ; Kim et al. ). Thus, gingiva represents a minimally invasive source of cells for therapeutic applications. Of particular interest in the context of current regenerative therapies is the paracrine activity of cells via their secretomes (Wang, Chen, et al. ). According to the Medical Subject Headings (MeSH) secretomes are defined as “the set of all the soluble factors and extracellular vesicles secreted into the extracellular space by cells.” Secretion of such components, including soluble proteins (growth factors, cytokines, chemokines), lipids, nucleic acids and extracellular vesicles (EV), serves fundamental functions in both the autocrine and paracrine cell signaling pathways for regulating the local microenvironment. Therefore, the use of cell secretomes, in the form of cell conditioned media (CM), may offer a promising alternative to currently complex and cost‐intensive cell therapies for advanced tissue regeneration. Practical benefits include relative ease of preparation, “off‐the‐shelf” application, and better cost‐efficacy (Marolt Presen et al. ). In the context of periodontal/bone regeneration, previous data suggest that CM may be at least equally, if not more, effective than cell transplantation (Hiraki et al. ; Osugi et al. ; Sanchooli et al. ; Shanbhag et al. ). Currently, various tissue/cell sources are being investigated to produce secretomes for therapeutic applications. Clinical grade secretome production requires ex vivo cell culture and expansion, ideally under Good Manufacturing Practice (GMP) conditions. Gingival tissues can be easily obtained during periodontal surgical procedures and are often discarded as clinical waste during resective surgery, which further enhances the prospects of gingiva as a source of therapeutic cells (McCulloch and Bordin ). Previous studies have compared various properties of GF (Baek et al. ; Li et al. ; Kang et al. ; Yang et al. ; Bartold and Page ; Kanda‐Nakamura et al. ; Bao et al. ; Bartold and Page ), or gingival progenitor cells (Makkad ; Bekić et al. ; Ge et al. ), isolated from healthy versus periodontitis‐affected tissues. Moreover, proteomic analyses of in situ or in vitro cultured GF from healthy (Bao et al. ; McKnight et al. ; Onyedibe et al. ) and diseased sites (Bao et al. ) have been reported. Recent data also indicates that the CM of GF has anti‐inflammatory and pro‐wound healing effects based on in vitro and in vivo assays (Ahangar et al. ). However, proteomic analyses of the secretomes of GF from periodontitis‐affected tissues (GF‐perio) are lacking. Given the important roles of GF in homeostasis, ECM synthesis/remodeling, immune modulation, and wound healing during both periodontal health and disease, it is reasonable to expect that the proteomic mediators of these functions would be reflected (at least to some extent) in their secretomes. Therefore, the objective of the present study was to investigate the composition of the secretomes of GF‐perio using proteomics.   Materials and Methods 2.1 Cell Culture The use of human cells and tissues was approved by the Regional Committees for Medical Research Ethics in Norway (2011/1516/REK, 2016/1267/REK‐nord). GF‐perio were isolated from biopsies obtained following informed donor consent, as previously described (Shanbhag et al. ). Briefly, gingival connective tissues were harvested from systemically healthy nonsmoking Stage III or IV periodontitis patients ( n = 6; 46–72 years) undergoing access flap surgery at the Department of Clinical Dentistry, University of Bergen, Bergen, Norway. All patients fulfilled the criteria for surgical intervention, that is, not fulfilling the therapeutic endpoints after subgingival instrumentation and adequate plaque control (periodontal therapy steps 1 and 2), as reflected by probing pocket depth (PPD) > 5 mm and bleeding on probing (BoP), that is, persistent inflammation , despite previous nonsurgical therapy and adequate plaque control (Sanz et al. ). One connective tissue biopsy per patient was harvested from the interdental aspect of a full‐thickness mucoperiosteal flap around maxillary or mandibular first or second molars. The tissue biopsy was placed in a tube containing phosphate‐buffered saline (PBS; Invitrogen, Waltham, MA, USA) and immediately transferred to the laboratory for processing. After thorough washing (3×) with PBS, primary explant cultures of GF‐perio were established in Dulbecco's Modified Eagle's medium (DMEM, Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (GE Healthcare, South Logan, UT, USA) and 1% antibiotics (penicillin/streptomycin; GE Healthcare). Cells were sub‐cultured and expanded in humidified 5% CO 2 at 37°C. Passage‐2 or ‐3 cells from each of the donors were used to prepare CM (Shanbhag et al. ) (Figure ). As a reference group for the proteomic analysis, CM was prepared from GF (passage‐2 or ‐3) of periodontally healthy subjects (n = 6; GF‐healthy) obtained from a biobank at the Department of Clinical Dentistry, University of Bergen. These cells were obtained during routine dental procedures from clinically healthy and non‐inflamed gingival tissue sites and cryopreserved for general research use (not specifically for the present study). 2.2 Preparation of CM CM from GF‐perio and GF‐healthy were prepared using a standardized protocol (Shanbhag et al. ). Briefly, passage‐2 or ‐3 cells from each donor were separately cultured in growth media until 80% confluency at which point the media was removed and, following 3× washes with PBS (Invitrogen, Waltham, MA, USA), replaced with serum‐ and antibiotic‐free DMEM. After 48 h, the supernatant media (CM) were collected, centrifuged (4000 g , 10 min), aliquoted, and stored at −80°C until further use. Before experiments, the CM were concentrated (~30 fold) using Amicon Ultra‐15 3 kDa centrifugal filter devices (Merck Millipore, Billerica, MA, USA) following the manufacturer's protocol. Briefly, after PBS equilibration, 15 mL of each CM was centrifuged in the Ultra‐15 tubes at 4000 g for 30 min at 4°C, followed by buffer exchange with PBS and re‐centrifugation at 4000 g for 30 min at 4°C. The corresponding concentrated CM from the individual donors were used for proteomic analysis. 2.3 Liquid Chromatography With Tandem Mass Spectrometry (LC‐MS/MS) CM from GF‐perio and GF‐healthy were analyzed using LC‐MS/MS via label‐free quantitation, as previously described (Aasebø et al. ). Briefly, total protein concentration of each sample was measured using bioinchonic acid assay (Pierce BCA Kit, Thermo Fisher, Waltham, MA, USA) and 10 μg protein was processed to obtain tryptic peptides. About 0.5 μg protein, as tryptic peptides dissolved in 2% acetonitrile and 0.5% formic acid, was injected into an Ultimate 3000 RSLC system connected online to an Exploris 480 mass spectrometer equipped with EASY‐spray nano‐electrospray ion source (all from Thermo Scientific, Sunnyvale, CA, USA). Additional details of LC‐MS/MS are reported in the . The LC‐MS/MS data have been deposited to the Proteome‐Xchange Consortium via the PRIDE partner repository ( https://www.ebi.ac.uk/pride/ ; accessed on 07.08.2024) with the data set identifier PXD054664. 2.4 Bioinformatic Analysis The LC‐MS/MS raw files were searched using Proteome Discoverer software (version 2.5.0.400; Thermo Scientific) against the human database. Data were analyzed using Perseus software (version 2.0.9.0) (Tyanova et al. ). To ensure accurate quantification of proteins, a filtration strategy based on detection of proteins in at least five (of six) donors in each CM group (GF‐perio and GF‐healthy) was applied. First, common (proteins identified in both groups) and exclusive proteins (proteins identified in only the perio or healthy group) were identified. Next, quantitative analysis of the common proteins was performed to identify the differentially expressed proteins (DEPs) using a two‐sided Student's t ‐test [−log10( p ‐value) and p < 0.05] in combination with a permutation‐based correction for multiple hypothesis testing (false discovery rate; FDR = 0.05). Functional profiling of common proteins between the groups and exclusive proteins in each group was performed using the g: Profiler software (version e111_eg58_p18_30541362) (Kolberg et al. ) based on the gene ontology (GO) categories of molecular function (MF), biological process (BP), and cellular component (CC) databases. Additional details of the bioinformatic analysis are reported in the . Functional enrichment analysis (FEA) was performed to classify individual proteins into similar functional categories (MP, BP, CC) using the open‐access functional enrichment analysis tool – FunRich, as previously described (Pathan et al. ). 2.5 Multiplex Immunoassay For validation of LC‐MS/MS data, the Quantibody Human Bone Metabolism Array Q1 (RayBiotech Inc., Norcross, GA, USA) with 31 bone‐related cytokines Supporting information: Table ) was used, as previously described (Shanbhag et al. ). This array is based on the sandwich enzyme‐linked immunosorbent assay (ELISA) technology, which allows simultaneous quantitative measurement of multiple proteins in a sample. Briefly, following the manufacturer's protocol, array hybridization was performed using test samples and standard cytokines on a custom microarray slide (RayBiotech Inc.), where each antibody is spotted in quadruplicate. Array scanning was performed using a laser scanner (GenePix 4000B) and proprietary software (both from Axon Instruments Burladingen, Germany) at different photomultiplier tube gains; the most suitable scan was selected for normalization. Cytokine concentrations were calculated based on linear standard curves and normalized to the corresponding total protein levels (pg/μg total protein); data are presented as fold changes in GF‐perio CM relative to the reference group. 2.6 Statistical Analysis Identification of DEPs was performed using a two‐sided Student's t ‐test with Fisher's correction in Perseus software. FEA was performed using the FunRich open access tool, which applies the hypergeometric test with Bonferroni correction for p ‐values. All other statistical analyses were performed using the Prism 9 software (GraphPad Software, San Diego, CA, USA). Linear data are presented as means (±SD), unless specified. Normality testing was performed using Shapiro–Wilk test and independent sample t‐ tests with a 0.05 significance level were applied.   Cell Culture The use of human cells and tissues was approved by the Regional Committees for Medical Research Ethics in Norway (2011/1516/REK, 2016/1267/REK‐nord). GF‐perio were isolated from biopsies obtained following informed donor consent, as previously described (Shanbhag et al. ). Briefly, gingival connective tissues were harvested from systemically healthy nonsmoking Stage III or IV periodontitis patients ( n = 6; 46–72 years) undergoing access flap surgery at the Department of Clinical Dentistry, University of Bergen, Bergen, Norway. All patients fulfilled the criteria for surgical intervention, that is, not fulfilling the therapeutic endpoints after subgingival instrumentation and adequate plaque control (periodontal therapy steps 1 and 2), as reflected by probing pocket depth (PPD) > 5 mm and bleeding on probing (BoP), that is, persistent inflammation , despite previous nonsurgical therapy and adequate plaque control (Sanz et al. ). One connective tissue biopsy per patient was harvested from the interdental aspect of a full‐thickness mucoperiosteal flap around maxillary or mandibular first or second molars. The tissue biopsy was placed in a tube containing phosphate‐buffered saline (PBS; Invitrogen, Waltham, MA, USA) and immediately transferred to the laboratory for processing. After thorough washing (3×) with PBS, primary explant cultures of GF‐perio were established in Dulbecco's Modified Eagle's medium (DMEM, Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (GE Healthcare, South Logan, UT, USA) and 1% antibiotics (penicillin/streptomycin; GE Healthcare). Cells were sub‐cultured and expanded in humidified 5% CO 2 at 37°C. Passage‐2 or ‐3 cells from each of the donors were used to prepare CM (Shanbhag et al. ) (Figure ). As a reference group for the proteomic analysis, CM was prepared from GF (passage‐2 or ‐3) of periodontally healthy subjects (n = 6; GF‐healthy) obtained from a biobank at the Department of Clinical Dentistry, University of Bergen. These cells were obtained during routine dental procedures from clinically healthy and non‐inflamed gingival tissue sites and cryopreserved for general research use (not specifically for the present study).   Preparation of CM CM from GF‐perio and GF‐healthy were prepared using a standardized protocol (Shanbhag et al. ). Briefly, passage‐2 or ‐3 cells from each donor were separately cultured in growth media until 80% confluency at which point the media was removed and, following 3× washes with PBS (Invitrogen, Waltham, MA, USA), replaced with serum‐ and antibiotic‐free DMEM. After 48 h, the supernatant media (CM) were collected, centrifuged (4000 g , 10 min), aliquoted, and stored at −80°C until further use. Before experiments, the CM were concentrated (~30 fold) using Amicon Ultra‐15 3 kDa centrifugal filter devices (Merck Millipore, Billerica, MA, USA) following the manufacturer's protocol. Briefly, after PBS equilibration, 15 mL of each CM was centrifuged in the Ultra‐15 tubes at 4000 g for 30 min at 4°C, followed by buffer exchange with PBS and re‐centrifugation at 4000 g for 30 min at 4°C. The corresponding concentrated CM from the individual donors were used for proteomic analysis.   Liquid Chromatography With Tandem Mass Spectrometry (LC‐MS/MS) CM from GF‐perio and GF‐healthy were analyzed using LC‐MS/MS via label‐free quantitation, as previously described (Aasebø et al. ). Briefly, total protein concentration of each sample was measured using bioinchonic acid assay (Pierce BCA Kit, Thermo Fisher, Waltham, MA, USA) and 10 μg protein was processed to obtain tryptic peptides. About 0.5 μg protein, as tryptic peptides dissolved in 2% acetonitrile and 0.5% formic acid, was injected into an Ultimate 3000 RSLC system connected online to an Exploris 480 mass spectrometer equipped with EASY‐spray nano‐electrospray ion source (all from Thermo Scientific, Sunnyvale, CA, USA). Additional details of LC‐MS/MS are reported in the . The LC‐MS/MS data have been deposited to the Proteome‐Xchange Consortium via the PRIDE partner repository ( https://www.ebi.ac.uk/pride/ ; accessed on 07.08.2024) with the data set identifier PXD054664.   Bioinformatic Analysis The LC‐MS/MS raw files were searched using Proteome Discoverer software (version 2.5.0.400; Thermo Scientific) against the human database. Data were analyzed using Perseus software (version 2.0.9.0) (Tyanova et al. ). To ensure accurate quantification of proteins, a filtration strategy based on detection of proteins in at least five (of six) donors in each CM group (GF‐perio and GF‐healthy) was applied. First, common (proteins identified in both groups) and exclusive proteins (proteins identified in only the perio or healthy group) were identified. Next, quantitative analysis of the common proteins was performed to identify the differentially expressed proteins (DEPs) using a two‐sided Student's t ‐test [−log10( p ‐value) and p < 0.05] in combination with a permutation‐based correction for multiple hypothesis testing (false discovery rate; FDR = 0.05). Functional profiling of common proteins between the groups and exclusive proteins in each group was performed using the g: Profiler software (version e111_eg58_p18_30541362) (Kolberg et al. ) based on the gene ontology (GO) categories of molecular function (MF), biological process (BP), and cellular component (CC) databases. Additional details of the bioinformatic analysis are reported in the . Functional enrichment analysis (FEA) was performed to classify individual proteins into similar functional categories (MP, BP, CC) using the open‐access functional enrichment analysis tool – FunRich, as previously described (Pathan et al. ).   Multiplex Immunoassay For validation of LC‐MS/MS data, the Quantibody Human Bone Metabolism Array Q1 (RayBiotech Inc., Norcross, GA, USA) with 31 bone‐related cytokines Supporting information: Table ) was used, as previously described (Shanbhag et al. ). This array is based on the sandwich enzyme‐linked immunosorbent assay (ELISA) technology, which allows simultaneous quantitative measurement of multiple proteins in a sample. Briefly, following the manufacturer's protocol, array hybridization was performed using test samples and standard cytokines on a custom microarray slide (RayBiotech Inc.), where each antibody is spotted in quadruplicate. Array scanning was performed using a laser scanner (GenePix 4000B) and proprietary software (both from Axon Instruments Burladingen, Germany) at different photomultiplier tube gains; the most suitable scan was selected for normalization. Cytokine concentrations were calculated based on linear standard curves and normalized to the corresponding total protein levels (pg/μg total protein); data are presented as fold changes in GF‐perio CM relative to the reference group.   Statistical Analysis Identification of DEPs was performed using a two‐sided Student's t ‐test with Fisher's correction in Perseus software. FEA was performed using the FunRich open access tool, which applies the hypergeometric test with Bonferroni correction for p ‐values. All other statistical analyses were performed using the Prism 9 software (GraphPad Software, San Diego, CA, USA). Linear data are presented as means (±SD), unless specified. Normality testing was performed using Shapiro–Wilk test and independent sample t‐ tests with a 0.05 significance level were applied.   Results 3.1 Proteomic Profile of GF‐Perio Secretomes LC‐MS/MS revealed a total of 1833 proteins in GF‐perio CM, slightly more than in the healthy reference group ( n = 1817). Protein intensity correlation analysis showed a strong correlation between GF‐perio donors with an average Pearson R value of 0.93 (range 0.90–0.95). Compared to the healthy reference group, GF‐perio CM revealed: a. More exclusive proteins ( n = 127 vs. 111), that is, proteins detected only in GF‐perio CM, and b. More DEPs ( n = 73 vs. 0), that is, proteins with significantly greater abundance (Figure , Table ). 3.2 Functional Analysis of Proteins in GF‐Perio Secretomes GO profiling of the total proteins in GF‐perio CM revealed enrichment of specific categories according to CC, MF, and BP. Among the top 10 enriched categories certain CC (“extracellular matrix”), MF (“protein binding”), and BP terms (“adaptive immune response”) were directly related to wound healing (Table ). Next, FEA was performed to determine specifically enriched categories of proteins among the DEPs (relative to the reference group) and exclusive proteins (independent of the reference group) in GF‐perio CM. Among the top 10 enriched categories in DEPs, the CC categories of “exosomes” and “cytoplasm” were statistically significant ( p < 0.05 according to multiple testing) (Table ). Similarly, among the exclusive proteins, the CC categories of “exosomes,” “lysosomes” and “cytoplasm,” and the MF category of “chaperone activity,” were significantly enriched ( p < 0.05 according to multiple testing) in GF‐perio CM (Table ). 3.3 Proteins in GF‐Perio Secretomes Related to Wound Healing and Bone Regeneration Several key mediators of wound healing were detected in GF‐perio CM, such as growth factors [transforming growth factor beta (TGFβ), bone morphogenic protein (BMP), vascular endothelial growth factor (VEGF), insulin‐like growth factor (IGF), and platelet‐derived growth factor (PDGF) family proteins], cell adhesion molecules [cadherins (CDH2, CDH6, CDH11, CDH13), tetranectin (CLEC3B), fibronectin (FN1), integrins, etc.], and ECM proteins [collagens (COL), collagenases/metalloproteinases (MMP), tissue inhibitors of metalloproteinases (TIMP), etc.] (Tables and ). Moreover, among the top 10 DEPs in GF‐perio were important cell adhesion molecules, such as cadherin‐5/VE‐cadherin (CDH5), tetranectin (CLEC3B), and ECM proteins, such as SPARC‐like protein‐1 (SPARCL1) (Table ). While a majority of the relevant wound healing‐related proteins were identified in both GF‐perio and GF‐healthy CM, some differences were observed between the groups among the exclusive proteins (Table ). For example, certain growth factors [e.g., platelet‐derived growth factor C (PDGFC), neuroligin‐2 (NLGN2)] were only detected in GF‐perio CM, while others [platelet‐derived growth factor receptor‐like protein (PDGFRL), fibroblast growth factor‐7 (FGF7), hepatoma‐derived growth factor‐related protein‐3 (HDGFL3), vascular endothelial growth factor receptor‐2 (KDR)] were only detected in the healthy reference group. To validate the LC‐MS data, a multiplex immunoassay of bone‐related cytokines was used. Six of the included cytokines revealed consistent values for all tested samples; these included proteins related to the inflammation [interleukins (IL6, IL8)], cell proliferation [fibroblast growth factor‐2 (FGF2), monocyte chemoattractant protein‐1 (MCP1)/CC motif chemokine ligand‐2 (CCL2), and ECM components [matrix metallopeptidase‐2 (MMP2), osteoactivin/transmembrane glycoprotein NMB (GPNMB)]. Compared to the healthy reference group, GF‐perio CM revealed trends for increased detection of all but one cytokine (GPNMB), although none of these reached statistical significance ( p > 0.05 for all) (Figure ).   Proteomic Profile of GF‐Perio Secretomes LC‐MS/MS revealed a total of 1833 proteins in GF‐perio CM, slightly more than in the healthy reference group ( n = 1817). Protein intensity correlation analysis showed a strong correlation between GF‐perio donors with an average Pearson R value of 0.93 (range 0.90–0.95). Compared to the healthy reference group, GF‐perio CM revealed: a. More exclusive proteins ( n = 127 vs. 111), that is, proteins detected only in GF‐perio CM, and b. More DEPs ( n = 73 vs. 0), that is, proteins with significantly greater abundance (Figure , Table ).   Functional Analysis of Proteins in GF‐Perio Secretomes GO profiling of the total proteins in GF‐perio CM revealed enrichment of specific categories according to CC, MF, and BP. Among the top 10 enriched categories certain CC (“extracellular matrix”), MF (“protein binding”), and BP terms (“adaptive immune response”) were directly related to wound healing (Table ). Next, FEA was performed to determine specifically enriched categories of proteins among the DEPs (relative to the reference group) and exclusive proteins (independent of the reference group) in GF‐perio CM. Among the top 10 enriched categories in DEPs, the CC categories of “exosomes” and “cytoplasm” were statistically significant ( p < 0.05 according to multiple testing) (Table ). Similarly, among the exclusive proteins, the CC categories of “exosomes,” “lysosomes” and “cytoplasm,” and the MF category of “chaperone activity,” were significantly enriched ( p < 0.05 according to multiple testing) in GF‐perio CM (Table ).   Proteins in GF‐Perio Secretomes Related to Wound Healing and Bone Regeneration Several key mediators of wound healing were detected in GF‐perio CM, such as growth factors [transforming growth factor beta (TGFβ), bone morphogenic protein (BMP), vascular endothelial growth factor (VEGF), insulin‐like growth factor (IGF), and platelet‐derived growth factor (PDGF) family proteins], cell adhesion molecules [cadherins (CDH2, CDH6, CDH11, CDH13), tetranectin (CLEC3B), fibronectin (FN1), integrins, etc.], and ECM proteins [collagens (COL), collagenases/metalloproteinases (MMP), tissue inhibitors of metalloproteinases (TIMP), etc.] (Tables and ). Moreover, among the top 10 DEPs in GF‐perio were important cell adhesion molecules, such as cadherin‐5/VE‐cadherin (CDH5), tetranectin (CLEC3B), and ECM proteins, such as SPARC‐like protein‐1 (SPARCL1) (Table ). While a majority of the relevant wound healing‐related proteins were identified in both GF‐perio and GF‐healthy CM, some differences were observed between the groups among the exclusive proteins (Table ). For example, certain growth factors [e.g., platelet‐derived growth factor C (PDGFC), neuroligin‐2 (NLGN2)] were only detected in GF‐perio CM, while others [platelet‐derived growth factor receptor‐like protein (PDGFRL), fibroblast growth factor‐7 (FGF7), hepatoma‐derived growth factor‐related protein‐3 (HDGFL3), vascular endothelial growth factor receptor‐2 (KDR)] were only detected in the healthy reference group. To validate the LC‐MS data, a multiplex immunoassay of bone‐related cytokines was used. Six of the included cytokines revealed consistent values for all tested samples; these included proteins related to the inflammation [interleukins (IL6, IL8)], cell proliferation [fibroblast growth factor‐2 (FGF2), monocyte chemoattractant protein‐1 (MCP1)/CC motif chemokine ligand‐2 (CCL2), and ECM components [matrix metallopeptidase‐2 (MMP2), osteoactivin/transmembrane glycoprotein NMB (GPNMB)]. Compared to the healthy reference group, GF‐perio CM revealed trends for increased detection of all but one cytokine (GPNMB), although none of these reached statistical significance ( p > 0.05 for all) (Figure ).   Discussion The objective of the present study was to characterize the secretomes of GF‐perio using LC‐MS/MS. Several growth factors, cytokines, chemokines, and extracellular matrix proteins important for wound healing and regeneration were identified in GF‐perio CM. The presence of selected bone‐related proteins was confirmed via an immunoassay. Relative to a reference group of healthy GF, significant enrichment of specific protein categories, particularly exosomes, was observed in GF‐perio CM. Thus, the present findings offer relevant insights on the secretomes of GF‐perio with implications for use in regenerative therapies. Previous studies have characterized the proteomic profiles of GF (cell‐lysates) (McKnight et al. ) and their CM (secretomes) (Onyedibe et al. ) from healthy donors. Recently, Bao et al (Bao et al. ). compared the protein profiles of in situ gingival biopsies harvested from healthy and periodontally‐diseased sites. Consistent with our findings, the authors reported similar global profiles between healthy and diseased sites and a similar number of DEPs ( n = 69), mostly detected in the diseased sites (Bao et al. ). Functional profiling also revealed enrichment of similar GO categories and components as in the present study. These consistent findings are especially interesting given the differences in study designs. While in the former study (Bao et al. ) proteins were analyzed directly from in situ harvested gingival tissues, the secreted proteins in the present study were obtained from in vitro cultured GF. While it may be argued that the in vitro culture process introduced some modifications in the properties and secretory profiles of the cells, based on the above findings, it may be speculated that the inherent (in vivo) secretory profiles of GF are largely unaltered following in vitro culture. Nevertheless, the present study findings are relevant for regenerative therapy protocols where secretomes/CM are produced via ex vivo culture expansion of cells harvested from tissue biopsies. In the context of wound healing, GF‐perio CM revealed the presence of several proteins related to the different phases (Table ). Wound healing is a complex and dynamic process comprising four interconnected phases, that is, hemostasis, inflammation, proliferation/angiogenesis, and ECM synthesis/remodeling (Velnar et al. ). Of particular interest was the detection of several growth factors of the TGFβ‐, BMP‐, VEGF‐, IGF‐, PDGF‐, and CCN‐family, important for cell proliferation and differentiation (Barrientos et al. ; Linkhart et al. ). Moreover, relative to the reference group (GF‐healthy CM), a number of cell adhesion molecules (CDH5, CLEC3B) and ECM proteins (SPARCL1) were significantly overexpressed in GF‐perio CM. Functional analysis of DEPs also revealed a significant enrichment of proteins related to exosomes in GF‐perio CM. This is of particular interest, given the emerging role of EVs in wound healing (Lu et al. ) and in periodontal and bone regenerative therapies (Wang, Chen, et al. ; Wang, Cao, et al. ). In addition to soluble proteins, GF is known to release EVs, including exosomes, to mediate their paracrine functions (Yin et al. ; Zhuang and Zhou ; Sun et al. ). A post‐hoc analysis confirmed that at least 85 of the “top 100 EV proteins” according to Vesiclepedia (Chitti et al. ) were present in GF‐perio CM (Table ). In light of these data, further characterization of the EV‐component of GF‐perio CM and its effects on target cells is warranted. It is relevant to discuss the present findings in the context of the defining clinical factor characterizing GF‐perio, that is, inflammation. These cells were obtained from the periodontally affected teeth of patients undergoing surgery. According to current guidelines (Sanz et al. ), these teeth were assigned to a surgical intervention since they presented with persisting signs of inflammation (PPD > 5 mm and/or BoP), despite previous nonsurgical instrumentation and adequate plaque control. Since GF were isolated from connective tissue biopsies collected during access flap surgery around periodontally affected teeth, it is reasonable to assume that these cells were obtained from a microenvironment characterized by, among other things, inflammation and hypoxia (Celik and Kantarci ). In context, inflammation (via cytokine stimulation) and hypoxia are among the most commonly reported “preconditioning” strategies to enhance the therapeutic efficacy of cells and their secretomes (Chen et al. ; Hertel et al. ; Pulido‐Escribano et al. ). The mechanisms implicated in these effects have included, in the case of hypoxia, enhanced stemness and differentiation potential, and, in the case of cytokine stimulation, a shift towards a more “anti‐inflammatory phenotype” and enhance immune modulation (Chen et al. ). Indeed, these changes are also reflected in the secretomes and EVs of the preconditioned cells (Long and Wang ). Whether the molecular findings of the present study, for example, enrichment of exosomes in GF‐perio CM, could be partly attributed to some form of inflammatory “preconditioning,” is presently speculative and requires further investigation. It is also relevant to discuss the present findings in the context of the evidence of fibroblast heterogeneity in the periodontium. The relevance of different fibroblast subpopulations (based on lineage, development, differentiation potential, response to stimuli, etc.) has been extensively discussed in the context of both periodontal health and disease (McCulloch and Bordin ; Phipps et al. ; Lekic et al. ). Such heterogeneity has been reported not only between fibroblasts from different tissue components (e.g., PDL vs. gingiva) but also within the same tissue. In the gingiva, different fibroblast subtypes have been identified, with additional differences being detected in healthy and diseased tissues (Hakkinen and Larjava ; Hassell and Stanek ). While a majority of the fibroblast subtypes have been characterized based on in vitro differences in morphology, proliferation rate and differentiation potential, some evidence also suggests that these subtypes may differ in their secretory properties (Lekic et al. ). Thus, certain fibroblast subtypes may dominate during specific phases of a healthy or disease state, thereby influencing the secretory profile. However, reliable identification of these subtypes in vivo has been limited by the lack of highly specific surface markers which could allow their differential detection. Using emerging techniques (e.g., single‐cell analysis), future studies may reveal distinct fibroblast subpopulations in the gingiva (in health and disease) with corresponding differences in secretory profiles. With regard to the methodology, a systematic and comprehensive bioinformatic approach was used to analyze the LC‐MS/MS data in the present study. Moreover, proteomic findings were validated using a more conventional ELISA‐based immunoassay. Nevertheless, some study limitations must be acknowledged. Firstly, the number of GF donors ( n = 6) was limited. Although recent comparative studies of proteomic data have reported similar donor numbers (Lertruangpanya et al. ; Chen et al. ; Shin et al. ), inclusion of additional donors may have provided a clearer picture of donor‐related variations in GF‐perio secretomes. Moreover, the “healthy” reference GFs were obtained from a biobank of previously isolated cells from clinically healthy gingival tissues and not from age‐ and gender‐matched controls to the GF‐perio donors. While “donor‐matched” (same patients) cell harvesting may have reduced some potential bias, the reliability of obtaining truly “healthy” tissue controls in periodontitis patients, especially severe‐to‐advanced cases (Stage III–IV) requiring surgery, may be questioned (Bao et al. ). Additionally, no “functional” assay, for example, in vitro wound healing, gene expression, was performed to investigate the effects of GF‐perio CM on relevant target cells, for example, osteoblasts or PDL fibroblasts. A bioassay (e.g., RNA‐sequencing) to detect differential effects of GF‐perio and GF‐healthy secretomes on such target cells would be interesting for future research. Finally, GF in the present study were cultured in vitro in plastic adherent and serum‐supplemented conditions, which may not reflect the true in vivo scenario but represents a more clinically relevant approach since secretomes for clinical applications are produced from ex vivo culture‐expanded cells under GMP conditions (Sagaradze et al. ).   Conclusions Within its limitations, the present study demonstrates that, in addition to several proteins important for wound healing and bone regeneration, the secretome of GF from periodontally diseased tissues is significantly enriched for proteins related to exosomes. Since gingival biopsies can be easily obtained during periodontal surgery, the secretomes of GF‐perio represent a promising biological therapy for regenerative applications. Further investigation of their potency, along with efficacy testing in relevant in vitro and in vivo models, is warranted.   Siddharth Shanbhag, Dagmar Fosså Bunæs and Kamal Mustafa conceived and designed the study. Anne Kari Smedås, Lovise Gangeskar Paris, and Siddharth Shanbhag performed the experiments. Anne Kari Smedås, Lovise Gangeskar Paris, Dagmar Fosså Bunæs, Niyaz Al‐Sharabi, and Siddharth Shanbhag contributed to data analysis. All authors contributed to the interpretation of data and writing. All authors read and approved the final manuscript.   The use of human cells and tissues was approved by the Regional Committees for Medical Research Ethics (REK) in Norway (2011/1516/REK and 2016/1267/REK‐nord).   The authors have nothing to report.   The authors declare no conflicts of interest.   Supporting information. Supporting information.   