Pressure Cycling Technology Assisted Mass Spectrometric Quantification of Gingival Tissue Reveals Proteome Dynamics during the Initiation and Progression of Inflammatory Periodontal Disease

Bao, Kai; Li, Xiaofei; Kajikawa, Tetsuhiro; Abe, Toshiharu; Selevsek, Nathalie; Grossmann, Jonas; Hajishengallis, George; Bostancı, Nagihan

doi:10.1002/pmic.201900253

Cited by 11 publications

(15 citation statements)

References 71 publications

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“…Furthermore, the prediction of the protein functions shows that most of the regulated proteins were localised in the extracellular space. Similarly, increased numbers of secreted proteins were previously identified in human experimental gingivitis (Bostanci et al, 2013) and murine ligature-induced periodontitis (Bao et al, 2019). Hence, it is not surprising to find that many of the regulated proteins had transport-related functions.…”

Section: Discussionmentioning

confidence: 72%

“…Gingival tissues were washed three times, each for 5 min in PBS to remove any residues prior to lysis. The tissues were then lysed and digested using a Barocycler NEP2320 (Pressure BioSciences) at 33°C as described previously (Bao et al, 2019 ). In brief, 2.5 to 3 mg of samples ( n = 10) were placed in MicroTubes (Pressure BioSciences) and lysed with a 60–cycle barocyling process.…”

Section: Methodsmentioning

confidence: 99%

“…A sensitive pressure cycling technology (PCT)-assistant workflow with proven efficiency in gingival tissue disruption (Bao et al, 2019 ) was used in this study. The present study aimed to concomitantly characterise the gingival tissue proteome and microbiome of systematically healthy individuals with periodontitis, by comparing healthy and diseased sites.…”

Section: Introductionmentioning

confidence: 99%

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Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease

Bao

Poveda

et al. 2020

Front. Cell. Infect. Microbiol.

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Efforts to map gingival tissue proteomes and microbiomes have been hampered by lack of sufficient tissue extraction methods. The pressure cycling technology (PCT) is an emerging platform for reproducible tissue homogenisation and improved sequence retrieval coverage. Therefore, we employed PCT to characterise the proteome and microbiome profiles in healthy and diseased gingival tissue. Healthy and diseased contralateral gingival tissue samples (total n = 10) were collected from five systemically healthy individuals (51.6 ± 4.3 years) with generalised chronic periodontitis. The tissues were then lysed and digested using a Barocycler, proteins were prepared and submitted for mass spectrometric analysis and microbiome DNA for 16S rRNA profiling analysis. Overall, 1,366 human proteins were quantified (false discovery rate 0.22%), of which 69 proteins were differentially expressed (≥2 peptides and p < 0.05, 62 up, 7 down) in periodontally diseased sites, compared to healthy sites. These were primarily extracellular or vesicle-associated proteins, with functions in molecular transport. On the microbiome level, 362 species-level operational taxonomic units were identified. Of those, 14 predominant species accounted for >80% of the total relative abundance, whereas 11 proved to be significantly different between healthy and diseased sites. Among them, Treponema sp. HMT253 and Fusobacterium naviforme and were associated with disease sites and strongly interacted ( r > 0.7) with 30 and 6 up-regulated proteins, respectively. Healthy-site associated strains Streptococcus vestibularis, Veillonella dispar, Selenomonas sp. HMT478 and Leptotrichia sp. HMT417 showed strong negative interactions ( r < −0.7) with 31, 21, 9, and 18 up-regulated proteins, respectively. In contrast the down-regulated proteins did not show strong interactions with the regulated bacteria. The present study identified the proteomic and intra-tissue microbiome profile of human gingiva by employing a PCT-assisted workflow. This is the first report demonstrating the feasibility to analyse full proteome profiles of gingival tissues in both healthy and disease sites, while deciphering the tissue site-specific microbiome signatures.

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Section: Discussionmentioning

confidence: 72%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease

Bao

Poveda

et al. 2020

Front. Cell. Infect. Microbiol.

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“…The gingival tissue protein abundance was shown to be mainly dependent on the progression of periodontitis by unsupervised clustering analysis. Additionally, over-representation of innate immune regulation, signal transduction, and homeostasis processes was revealed by gene ontology (GO) enrichment analysis [39]. Moreover, although ferritin, an iron-binding protein, was detected in the gingival epithelium and gingival connective tissue by immunochemical staining, the intensity of positive staining became significantly stronger along with the extent of inflammatory infiltration [40].…”

Section: Evaluation In Gingivamentioning

confidence: 99%

Application of Ligature-Induced Periodontitis in Mice to Explore the Molecular Mechanism of Periodontal Disease

Lin

Niimi

Ohsugi

et al. 2021

IJMS

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Periodontitis is an inflammatory disease characterized by the destruction of the periodontium. In the last decade, a new murine model of periodontitis has been widely used to simulate alveolar bone resorption and periodontal soft tissue destruction by ligation. Typically, 3-0 to 9-0 silks are selected for ligation around the molars in mice, and significant bone loss and inflammatory infiltration are observed within a week. The ligature-maintained period can vary according to specific aims. We reviewed the findings on the interaction of systemic diseases with periodontitis, periodontal tissue destruction, the immunological and bacteriological responses, and new treatments. In these studies, the activation of osteoclasts, upregulation of pro-inflammatory factors, and excessive immune response have been considered as major factors in periodontal disruption. Multiple genes identified in periodontal tissues partly reflect the complexity of the pathogenesis of periodontitis. The effects of novel treatment methods on periodontitis have also been evaluated in a ligature-induced periodontitis model in mice. This model cannot completely represent all aspects of periodontitis in humans but is considered an effective method for the exploration of its mechanisms. Through this review, we aimed to provide evidence and enlightenment for future studies planning to use this model.

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“…16 Hence, the characterization of the protein profile of PDL in conditions of periodontitis, associated or not to obesity, becomes an important point for identifying possible biological markers of the association between comorbidities. Proteomic analysis has been used in oral tissues, such as enamel, 17 pulp, 18,19 gingival crevicular fluid, 20 periodontal ligament cells, 21 gingival tissue, 22,23 dental cementum, 24 and alveolar bone, 25 promoting insights into their possible pathologies.…”

Section: Introductionmentioning

confidence: 99%

Obesity influences the proteome of periodontal ligament tissues following periodontitis induction in rats

Lopes

Marcantonio

Molon

et al. 2022

J of Periodontal Research

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Background and Objectives Many studies have been conducted to better understand the molecular mechanism involved with periodontitis progression. There has been growing interest in the potential impact of obesity on periodontitis onset and progression, but the mechanisms involved remain to be elucidated. The present study was designed to determine the impact of obesity on experimentally induced periodontitis in rats and identify novel pathways involved. Methods Sixteen Holtzman rats were distributed into two groups (n = 8): ligature‐induced periodontitis (P) and obesity plus ligature‐induced periodontitis (OP). Obesity was induced by a high‐fat diet for 70 days, whereas periodontitis was induced for 20 days, with a cotton thread placed around the upper first molars bilaterally. Alveolar bone loss was measured by microtomographic analysis and histologically by histometry on the hemimaxillae. The protein composition of the periodontal ligament was evaluated by proteomic analysis. Results Data analysis (body weight, adipose tissue weight, and blood test) confirmed obesity induction, whereas bone loss was confirmed by micro‐CT and histologic analyses. Proteome analysis from the periodontal ligament tissues (PDL) identified 819 proteins, 53 exclusive to the P group, 28 exclusive to the OP group, and 738 commonly expressed. Validation was performed by immunohistochemistry for selected proteins (spondin1, vinculin, and TRAP). Conclusion Histologically, it was found that obesity did not significantly affect bone loss resulting from periodontitis. However, the present study's findings indicated that obesity affects the proteome of PDL submitted to experimental periodontitis, allowing for identifying potential targets for personalized approaches.

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Pressure Cycling Technology Assisted Mass Spectrometric Quantification of Gingival Tissue Reveals Proteome Dynamics during the Initiation and Progression of Inflammatory Periodontal Disease

Cited by 11 publications

References 71 publications

Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease

Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease

Application of Ligature-Induced Periodontitis in Mice to Explore the Molecular Mechanism of Periodontal Disease

Obesity influences the proteome of periodontal ligament tissues following periodontitis induction in rats

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