Dataset Information

PDLSCs Regulate Angiogenesis of Periodontal Ligaments via VEGF Transferred by Exosomes in Periodontitis.

ABSTRACT: Abnormal angiogenesis is one of the significant features in periodontitis leading to progressive inflammation, but angiogenic changes of periodontal ligaments under inflammatory condition were rarely reported. Periodontal ligament stem cells (PDLSCs) were a kind of dental stem cells associated with vascularization. Here we investigated the alteration of angiogenesis of periodontal ligament in periodontitis, and revealed an exosome-mediated pathway to support the effect of PDLSCs on angiogenic improvement. Vascular specific marker CD31 and VEGFA were found to be highly expressed in periodontal ligaments of periodontitis. The VEGFA expression was up-regulated in inflamed PDLSCs compared to control, meanwhile the tube formation of HUVECs was improved when co-cultured with inflamed PDLSCs. Exosomes secretion of PDSLCs was augmented by inflammation, and promoted angiogenesis of HUVECs, whereas blocking secretion of exosomes led to degenerated angiogenesis of HUVECs. Exosome-trasferred VEGFA was proven to be the crucial communicator between PDLSCs and HUVECs. Inflammation inhibited miR-17-5p expression of PDLSCs and relieved its target VEGFA. However, overexpression of miR-17-5p blocked the pro-angiogenic ability of inflamed PDLSCs. In conclusion, the findings indicated that vascularization of periodontal ligaments was enhanced, and inflammatory micro-environment of periodontitis facilitated pro-angiogenesis of PDLSCs through regulating exosome-mediated transfer of VEGFA, which was targeted by miR-17-5p.

SUBMITTER: Zhang Z

PROVIDER: S-EPMC7085218 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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PDLSCs Regulate Angiogenesis of Periodontal Ligaments via VEGF Transferred by Exosomes in Periodontitis.

Zhang Zhang Z Shuai Yi Y Zhou Feng F Yin Jikai J Hu Jiachen J Guo Songlin S Wang Yan Y Liu Wenjia W

International journal of medical sciences 20200210 5

Abnormal angiogenesis is one of the significant features in periodontitis leading to progressive inflammation, but angiogenic changes of periodontal ligaments under inflammatory condition were rarely reported. Periodontal ligament stem cells (PDLSCs) were a kind of dental stem cells associated with vascularization. Here we investigated the alteration of angiogenesis of periodontal ligament in periodontitis, and revealed an exosome-mediated pathway to support the effect of PDLSCs on angiogenic im ...[more]

PMID: 32210705

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Project description:Background: Although human gingival fibroblasts (hGF) and human periodontal ligament fibroblasts (hPDLF) exhibit numerous phenotypic similarities, it has been suggested that the secretory and behavioral differences, which exist between these cell types, are a result of the membrane protein composition of these cells. Methods: Four matched pairs of hGF and hPDLF were cultured. Prior to confluence, membrane bound and associated proteins from cells of the 4th passage were extracted. The processed protein samples were identified by digestion with trypsin and sequenced using capillary-liquid chromatography tandem mass spectrometry on an Thermo Scientific LTQ-Orbitrap XL mass spectrometer. Scaffold by Proteome Software was used to quantitate and validate protein identifications derived from MS/MS sequencing results. Results: Four hundred fifty proteins were common to both hGF and hPDLF. Of the proteins identified, 214 were known membrane bound or associated proteins and 165 proteins were known nuclear associated proteins. Twenty-seven proteins, identified from the 450 proteins, common to both hGF and hPDLF, were detected in statistically significant greater quantities in either hGF or hPDLF. More specifically, 13 proteins were detected in significantly greater quantities in hGF, while 14 proteins were detected in significantly greater quantities in hPDLF. Conclusions: Distinct differences in the cellular protein catalog may reflect the dynamic role and high energy requirements of hGF in extracellular matrix remodeling and response to inflammatory challenge as well as the role of hPDGF in monitoring mechanical stress and maintaining tissue homeostasis during regeneration and remineralization. Method Details: Sequence information from the MS/MS data was processed by converting the .raw files into a merged file (.mgf) using an in-house program, RAW2MZXML_n_MGF_batch (merge.pl, a Perl script). Isotope distributions for the precursor ions of the MS/MS spectra were deconvoluted to obtain the charge states and monoisotopic m/z values of the precursor ions during the data conversion. The resulting mgf files were searched using Mascot Daemon by Matrix Science version 2.3.2 (Boston, MA) and the database searched against the full SwissProt database version 2012_06 (536,489 sequences; 190,389,898 residues) or NCBI database version 20120515 (18,099,548 sequences; 6,208,559,787 residues The mass accuracy of the precursor ions were set to 20ppm, accidental pick of 13C peaks was also included into the search. The fragment mass tolerance was set to 0.5 Da. Considered variable modifications were oxidation (Met), deamidation (N and Q) and carbamidomethylation (Cys). Four missed cleavages for the enzyme were permitted. A decoy database was also searched to determine the false discovery rate (FDR) and peptides were filtered according to the FDR. The significance threshold was set at p less than 0.05 and bold red peptides is required for valid peptide identification. Proteins with a Mascot score of 50 or higher with a minimum of two unique peptides from one protein having a -b or -y ion sequence tag of five residues or better were accepted. Any modifications or low score peptide/protein identifications were manually checked for validation. Spectral Counting: Label Free Quantitation was performed using the spectral counting approach. Scaffold (version Scaffold_3.4.9, Proteome Software Inc., Portland, OR) was used to validate MS/MS based peptide and protein identifications. Peptide identifications were accepted if they could be established at greater than 95.0% probability as specified by the Peptide Prophet algorithm (Keller, A et al Anal. Chem. 2002;74(20):5383-92). Protein identifications were accepted if they could be established at greater than 95.0% probability and contained at least 1 identified peptides. Protein probabilities were assigned by the Protein Prophet algorithm (Nesvizhskii, AI Anal Chem. 2003 Sep 1;75(17):4646-58). Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony.

Dataset Information

PDLSCs Regulate Angiogenesis of Periodontal Ligaments via VEGF Transferred by Exosomes in Periodontitis.

Publications

PDLSCs Regulate Angiogenesis of Periodontal Ligaments via VEGF Transferred by Exosomes in Periodontitis.

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