Dataset Information

Label-Free Quantitative Proteomic Analysis Reveals Inflammatory Pattern Associated with Obesity and Periodontitis in Pregnant Women.

ABSTRACT: Obesity and pregnancy may have synergistic effects on periodontal condition, and proteomics could be an ideal approach to highlight the pathophysiological mechanisms associated with these outcomes. This study analyzed the salivary proteomics related to obesity and periodontitis in women during pregnancy (T1) and after delivery (T2). Initially, 126 women were recruited and forty were allocated into groups: with obesity and periodontitis (OP); with obesity, but without periodontitis (OWP); with normal BMI, but with periodontitis (NP); with normal BMI and without periodontitis (NWP). Whole-mouth saliva was collected in T1 and T2, and proteins were extracted and individually processed by label-free proteomics (nLC-ESI-MS/MS). The up-regulations of Heat shock 70 kDa protein 1A, 1B, and 1-like were related to both obesity and periodontitis, separately. Albumin and Thioredoxin were up-regulated in periodontitis cases, while Cystatins (mainly S, SA, SN) and Lactotransferrin were down-regulated. The high abundances of Submaxillary gland androgen-regulated protein 3B, Protein S100-A8, Matrix metalloproteinase-9, Heat shock 70 kDa protein 2 and 6, Putative Heat shock 70 kDa protein 7, Heat shock 71 kDa protein, Haptoglobin and Plastin-1 were significant in the combination of obesity and periodontitis. Obesity and periodontitis remarkably altered the proteome of the saliva during pregnancy with substantial alterations after delivery.

SUBMITTER: Foratori-Junior GA

PROVIDER: S-EPMC9692340 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Label-Free Quantitative Proteomic Analysis Reveals Inflammatory Pattern Associated with Obesity and Periodontitis in Pregnant Women.

Foratori-Junior Gerson Aparecido GA Ventura Talita Mendes Oliveira TMO Grizzo Larissa Tercilia LT Carpenter Guy Howard GH Buzalaf Marília Afonso Rabelo MAR Sales-Peres Silvia Helena de Carvalho SHC

Metabolites 20221110 11

Obesity and pregnancy may have synergistic effects on periodontal condition, and proteomics could be an ideal approach to highlight the pathophysiological mechanisms associated with these outcomes. This study analyzed the salivary proteomics related to obesity and periodontitis in women during pregnancy (T1) and after delivery (T2). Initially, 126 women were recruited and forty were allocated into groups: with obesity and periodontitis (OP); with obesity, but without periodontitis (OWP); with no ...[more]

PMID: 36355174

Similar Datasets

Project description:IntroductionTreatment and management of obesity is clinically challenging. The inclusion of GLP-1 receptor agonists (GLP1RA) in the medical management of obesity has proven to be efficacious. However, mechanisms underlying the molecular changes arising from GLP1RA treatment in patients with obesity remain to be elucidated.MethodsA single-center, prospective study was undertaken to evaluate the changes in the plasma proteins after liraglutide 3 mg therapy in twenty patients (M/F: 7/13) with obesity (mean BMI 40.65 ± 3.7 kg/m2). Anthropometric and laboratory parameters were measured, and blood samples were collected at two time points: baseline, before initiating treatment (pretreatment group, PT), and after three months of receiving the full dose liraglutide 3 mg (posttreatment group, PoT). An untargeted label-free LC MSMS mass spectrometric approach combined with bioinformatics and network pathway analysis was used to determine changes in the proteomic profiles.ResultsThe mean age of the study participants was 36.0 ± 11.1 years. A statistically significant change was observed in weight, BMI and HbA1c levels between the PT and PoT groups (paired t-test, P < 0.001). A significant dysregulation was noted in the abundances of 151 proteins (31 up and 120 downregulated) between the two groups. The potential biomarkers were evaluated using receiver operating characteristic (ROC) curves. The top ten proteins (area under the curve (AUC) of 0.999 (95% CI)) were identified as potential biomarkers between PT and PoT groups and included Cystatin-B, major vault protein, and plastin-3, which were upregulated, whereas multimerin-2, large ribosomal P2, and proline-rich acidic protein 1 were downregulated in the PoT group compared with the PT group. The top network pathway identified using ingenuity pathway analysis (IPA), centered around dysregulation of MAPK, AKT, and PKc signaling pathways and related to cell-to-cell signaling and interaction, cellular assembly and organization, cellular compromise and a score of 46 with 25 focus proteins.DiscussionThrough label-free quantitative proteomic analysis, our study revealed significant dysregulation of plasma proteins after liraglutide 3 mg treatment in patients with obesity. The alterations in the proteomic profile between the PT and PoT groups demonstrated a decrease in levels of proteins involved in inflammation and oxidative stress pathways. On the other hand proteins involved in the glycolytic and lipolytic metabolic pathways as well as those participating in cytoskeletal and endothelial reorganization were observed to be increased. Understanding actions of liraglutide at a molecular and proteomic levels provides a holistic look into how liraglutide impacts metabolism, induces weight loss and improves overall metabolic health.

Project description:The use of quantitative proteomics methods to study protein complexes has the potential to provide in-depth information on the abundance of different protein components as well as their modification state in various cellular conditions. To interrogate protein complex quantitation using shotgun proteomic methods, we have focused on the analysis of protein complexes using label-free multidimensional protein identification technology and studied the reproducibility of biological replicates. For these studies, we focused on three highly related and essential multi-protein enzymes, RNA polymerase I, II, and III from Saccharomyces cerevisiae. We found that label-free quantitation using spectral counting is highly reproducible at the protein and peptide level when analyzing RNA polymerase I, II, and III. In addition, we show that peptide sampling does not follow a random sampling model, and we show the need for advanced computational models to predict peptide detection probabilities. In order to address these issues, we used the APEX protocol to model the expected peptide detectability based on whole cell lysate acquired using the same multidimensional protein identification technology analysis used for the protein complexes. Neither method was able to predict the peptide sampling levels that we observed using replicate multidimensional protein identification technology analyses. In addition to the analysis of the RNA polymerase complexes, our analysis provides quantitative information about several RNAP associated proteins including the RNAPII elongation factor complexes DSIF and TFIIF. Our data shows that DSIF and TFIIF are the most highly enriched RNAP accessory factors in Rpb3-TAP purifications and demonstrate our ability to measure low level associated protein abundance across biological replicates. In addition, our quantitative data supports a model in which DSIF and TFIIF interact with RNAPII in a dynamic fashion in agreement with previously published reports.

Dataset Information

Label-Free Quantitative Proteomic Analysis Reveals Inflammatory Pattern Associated with Obesity and Periodontitis in Pregnant Women.

Publications

Label-Free Quantitative Proteomic Analysis Reveals Inflammatory Pattern Associated with Obesity and Periodontitis in Pregnant Women.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets