Proteomic characterization of mineralized tissues

Abstract

Purpose: Tissues that are rich in extracellular matrix (ECM) are complex in nature with a vast amount of post-translational modifications e.g., glycosylation, phosphorylation, sulfation and collagen cross-links. In order to understand the functional role of proteins particularly enriched in certain tissues it is important to characterize the ECM composition in detail. Proteomics technology can be used to characterize alterations in the tissue proteome in knockout animals as well as in pathology. In this study we characterized bone, articular cartilage, teeth and calvaria to enable further phenotype characterization of transgenic mice. Methods: Three months old (6 individuals) and six months old (3 individuals) of female C56BL/6 mice was sacrificed and cartilage from femoral head, femur bone, calvaria and incisor teeth were collected. Tissues from age matched individuals were pooled and powdered. Extraction of proteins from cartilage and calvaria was performed overnight in 4M GuHCl and extraction of proteins from bone and teeth tissues were in addition demineralized for 48 hour in 4M GuHCl/0.5M EDTA. High resolution nanoLC-MS (Q-ExactiveTM) with data-dependent acquisition was performed on tryptic digests of the final protein extracts for the identification of peptides (P=0.01) and proteins (at least one unique peptide). The Proteome Discoverer 2.1 software was used for the analysis and the quantification was made at the MS1 level using the top3 peptide peak intensity area. Results: We identified the following number of proteins (total n=1648) in the various tissues: cartilage (872), bone (378), teeth (223) and calvaria (1397), see also the Venn diagram in figure 1, where 123 proteins were present in all tissues. The cartilage and calvaria samples contained most proteins while the demineralized bone and teeth contained much less proteins. The proportions of ECM proteins were lower for cartilage (9.3%, n=232) and calvaria (5.86, n=236) than the content in bone (20.4%, n=203) and teeth (23.3%, n=143). The major reasons for this are differences in cellular content as well as that the non-mineralized extracts of bone and teeth were not investigated, most likely excluding many proteins. 80 out of 376 ECM proteins were detected in all tissues. The top20 most abundant proteins are listed in Table 1 where only COMP and MMP20 were exclusively identified (cartilage and teeth respectively). Note that collagens are poorly extracted with these protocols so they are vastly underestimated.Table 1Top 20 abundant proteins from each tissueboneteethcartilagecalvariaAlpha-2-HS-glycoproteinCollagen alpha-1(I)Collagen alpha-1(II)Collagen alpha-1(I)Collagen alpha-2(I)Collagen alpha-2(I)ChondroadherinCollagen alpha-2(I)Collagen alpha-1(I)Dentin sialophosphoproteinbiglycanHemoglobin alphaVitronectinAlpha-2-HS-glycoproteinFibromodulinHemoglobin beta-1ProthrombinbiglycanSparcSerum albuminCoagulation factor Xthrombospondin-1Hemoglobin alphaHistone H3.3Cthrombospondin-1Pigment epithelium-derived factorHyaluronan and proteoglycan link protein 1Actin, cytoplasmic 1biglycanSerum albuminCartilage oligomeric matrix protein (COMP)Alpha-2-HS-glycoproteinBone sialoprotein 2SparcCollagen alpha-1(I)Isoform 2 of Histone H2B type 1-PSparcCollagen alpha-2(XI)Collagen alpha-2(I)Histone H1.3Serum albuminMatrix metalloproteinase-20Aggrecan core proteinhistone H2A type 1Pigment epithelium-derived factorCollagen alpha-2(V)LactadherinVimentinApolipoprotein EProthrombinprolarginCollagen alpha-1(III)Coagulation factor IXLumicanHemoglobin subunit beta-1biglycanmatrix Gla proteinVitronectinHistone H3.3CHistone H1.4OsteopontinCalreticulinmatrix Gla proteinChitinase-like protein 3Secreted phosphoprotein 24Protein-lysine 6-oxidaseSerum albuminCreatine kinase M-typeCollagen alpha-1(XI)major urinary protein 18cartilage matrix proteinhistone H4Hyaluronan-binding protein 2tenascin-NdecorinApolipoprotein A-IApolipoprotein A-ICollagen alpha-1(XI)C-type lectin domain family 3 member ASerpin H1 Open table in a new tab Conclusions: We have shown that proteomics is a great tool to characterize complex samples such as mineralized tissues. Many proteins were found to be rather tissue specific even at the ECM level at least for the tissues studied here. On-going work characterizing transgenic mice versus wildtype would definitely be feasible and the quantitative comparisons for each separate tissue would be extremely interesting to explore.