ABSTRACT: Abstract: Proteomics has been successfully used for cell culture on dishes, but more complex cellular systems have proven to be challenging and so far poorly approached with proteomics. Because of the complexity of the angiogenic program, we still do not have a complete understanding of the molecular mechanisms involved in this process, and there have been no in depth quantitative proteomic studies. Plating endothelial cells on matrigel recapitulates aspects of vessel growth, and here we investigate this mechanism by using a spike-in SILAC quantitative proteomic approach. By comparing proteomic changes in primary human endothelial cells morphogenesis on matrigel to general adhesion mechanisms in cells spreading on culture dish, we pinpoint pathways and proteins modulated by endothelial cells. The cell-extracellular matrix adhesion proteome depends on the adhesion substrate, and a detailed proteomic profile of the extracellular matrix secreted by endothelial cells identified CLEC14A as a matrix component, which binds to MMRN2. We verify deregulated levels of these proteins during tumor angiogenesis in models of multi-stage carcinogenesis. This is the most in depth quantitative proteomic study of endothelial cell morphogenesis, which shows the potential of applying high accuracy quantitative proteomics to in vitro models of vessel growth to shed new light on mechanisms that accompany pathological angiogenesis. MS data acquisition and analysis: Digested peptides were analyzed by EASY-nLC system (Thermo Fisher Scientific) coupled on line to a LTQ-Orbitrap XL (for the EC morphogenesis and the spreading, and immunoprecipitation studies) or Velos (for the ECM study) (Thermo Fisher Scientific) via a nanoelectrospray ion source (Thermo Fisher Scientific). Chromatographic peptide separation was done in a 15 cm fused silica emitter (Thermo Fisher Scientific) packed in house with reversed-phase Reprosil (Dr. Maisch GmbH) and eluted with a flow of 250 nl/min from 5% to 70% ACN in 0.5% acetic acid, in a 140 min gradient. The full scan MS spectra were acquired with a resolution of 30,000 at m/z 400 in the Orbitrap. The top 5-10 most intense ions were sequentially isolated for fragmentation using CID (for the EC morphogenesis and spreading, and immunoprecipitation studies) or high-energy collision dissociation (for the ECM study), and recorded in the LTQ or Orbitrap, respectively. In the determination of CLEC14A phosphorylation sites, the neutral loss algorithm in the Xcalibur software was enabled for each MS/MS spectrum. Data were acquired with Xcalibur software (Thermo Fisher Scientific). The MS files were processed with the MaxQuant software version 1.2.6.20 and searched with Andromeda search engine against the human UniProt database (release-2012 01, 81,213 entries). To search parent mass and fragment ions, an initial mass deviation of 6 ppm and 0.5 Da (CID) or 20 ppm (HCD), respectively, were required. The minimum peptide length was set to 7 amino acids and strict specificity for trypsin cleavage was required, allowing up to two missed cleavage sites. Carbamidomethylation (Cys) was set as fixed modification, whereas oxidation (Met) and N-acetylation were considered as variable modifications. No labeling or double SILAC labeling was defined accordingly. The false discovery rates (FDRs) at the protein and peptide level were set to 1%. Scores were calculated in MaxQuant as described previously. The reverse and common contaminants hits (in the ECM proteome analysis, KRT1 and KRT9 were additionally included), were removed from MaxQuant output. Only proteins identified with at least one peptide uniquely assigned to the respective sequence were considered for the analysis. For SILAC protein quantification, the re-quantification feature was enabled, and the relative quantification of the peptides against their SILAC-labeled counterparts was performed by MaxQuant. Only unique peptides were used for quantification and we required proteins being quantified with at least two ratio counts. For the immunoprecipitation and ECM analyses, proteins were quantified according to the MaxQuant label-free algorithm; unique and razor (=most likely belonging to the protein group) peptides were used for protein quantification.
Sara Zanivan 
