Phosphoproteome reveals an atlas of protein signaling networks during osteoblast adhesion

Abstract

Cell adhesion on surfaces is a fundamental process in the emerging biomaterials field and developmental events as well. However, the mechanisms regulating this biological process in osteoblasts are not fully understood. Reversible phosphorylation catalyzed by kinases is probably the most important regulatory mechanism in eukaryotes. Therefore, the goal of this study is to assess osteoblast adhesion through a molecular prism under a peptide array technology, revealing essential signaling proteins governing adhesion-related events. First, we showed that there are main morphological changes on osteoblast shape during adhesion up to 3 h. Second, besides classical proteins activated upon integrin activation, our results showed a novel network involving signaling proteins such as Rap1A, PKA, PKC, and GSK3beta during osteoblast adhesion on polystyrene. Third, these proteins were grouped in different signaling cascades including focal adhesion establishment, cytoskeleton rearrangement, and cell-cycle arrest. We have thus provided evidence that a global phosphorylation screening is able to yield a systems-oriented look at osteoblast adhesion, providing new insights for understanding of bone formation and improvement of cell-substratum interactions. Altogether, these statements are necessary means for further intervention and development of new approaches for the progress of tissue engineering.

Profiling the changes in signaling pathways in ascorbic acid/β‐glycerophosphate‐induced osteoblastic differentiation

“…The level of incorporated radioactivity, which reflects the extent of phosphorylation, was quantified with specific array software (EisenLab ScanAlyze, version 2.50) as described elsewhere [Diks et al, 2004;Lö wenberg et al, 2005;Tuynman et al, 2008]. Datasets from chips were then analyzed statistically using PepMatrix, as described by Milani et al [2010]. Basically, spot replications were scrutinized for consistency using two indexes: one being the standard deviation:average (SD/A) ratio and the other being the ratio between the average and the median (A/M) of all three replications for each chip.…”

Deciphering Enzyme Function Using Peptide Arrays

“…Using peptide microarrays, Taher et al were able to detect differences in tyrosine phosphorylation in B-cells from patients with Systemic Lupus Erythematosus compared with matched controls [212] and Vivanco et al identified a critical role for PTEN in EGFR signal termination using peptide microarrays displaying more than 140 human tyrosine phosphorylation site peptides [213]. Milani reported use of peptide microarrays displaying more than 1,000 human phosphorylation sites for profiling the phosphoproteome of MC3T3 pre-osteoblast mouse cell line seeded on polystyrene surfaces [193]. Thus, it might be anticipated that extension of this methodology to more features on the microarrays and to other enzymatic activities, like lysine side chain acetylation [214] and methylation [99], will generate novel biomarkers for cancer and autoimmune diseases in the near future.…”

“…It could be demonstrated that phosphorylation profiles show a large overlap despite the divergence of the protein kinases on the primary structure level. These findings are underlined by the facts that peptide microarrays with human sequences were successfully used to characterise the substrate specificity of mitogen-activated protein kinases from tomato [87], big mitogen-activated protein kinase 1 from mice [89], protein kinase 7 from P.falciparum [189], proline-directed kinase PknB from S.aureus [190], kinase activities in sugar-stimulated and sorbitol treated A.thaliana cells [88,191], tyrosine kinase activities in jasmonate and/or salicylate treated A.thaliana cells [192], kinase activities in mouse osteoblast cell lines [193] and tyrosine kinase activities in zebrafish embryos [38,39].…”

Systems medicine approaches for peptide array-based protein kinase profiling: progress and prospects

“…[47]). For the analysis of clinical data usually less advanced software platforms like the statistical spot reliability approach called PepMatrix [48] are used. It is thus possible that specific kinome patterns recognizable by PIIKA are not recognized by other platforms and comparative studies on the same data set are needed to provide clarity with respect to this issue.…”