Document Detail

Extracellular matrix composition and remodeling in human abdominal aortic aneurysms: a proteomics approach.
Jump to Full Text
MedLine Citation:
PMID:  21593211     Owner:  NLM     Status:  MEDLINE    
Abdominal aortic aneurysms (AAA) are characterized by pathological remodeling of the aortic extracellular matrix (ECM). However, besides the well-characterized elastolysis and collagenolysis little is known about changes in other ECM proteins. Previous proteomics studies on AAA focused on cellular changes without emphasis on the ECM. In the present study, ECM proteins and their degradation products were selectively extracted from aneurysmal and control aortas using a solubility-based subfractionation methodology and analyzed by gel-liquid chromatography-tandem MS and label-free quantitation. The proteomics analysis revealed novel changes in the ECM of AAA, including increased expression as well as degradation of collagen XII, thrombospondin 2, aortic carboxypeptidase-like protein, periostin, fibronectin and tenascin. Proteomics also confirmed the accumulation of macrophage metalloelastase (MMP-12). Incubation of control aortic tissue with recombinant MMP-12 resulted in the extensive fragmentation of these glycoproteins, most of which are novel substrates of MMP-12. In conclusion, our proteomics methodology allowed the first detailed analysis of the ECM in AAA and identified markers of pathological ECM remodeling related to MMP-12 activity.
Athanasios Didangelos; Xiaoke Yin; Kaushik Mandal; Angelika Saje; Alberto Smith; Qingbo Xu; Marjan Jahangiri; Manuel Mayr
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2011-05-18
Journal Detail:
Title:  Molecular & cellular proteomics : MCP     Volume:  10     ISSN:  1535-9484     ISO Abbreviation:  Mol. Cell Proteomics     Publication Date:  2011 Aug 
Date Detail:
Created Date:  2011-08-04     Completed Date:  2012-05-29     Revised Date:  2014-02-20    
Medline Journal Info:
Nlm Unique ID:  101125647     Medline TA:  Mol Cell Proteomics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  M111.008128     Citation Subset:  IM    
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Aorta, Abdominal / pathology,  physiopathology*
Aortic Aneurysm, Abdominal / metabolism*
Carboxypeptidases / metabolism
Case-Control Studies
Chemical Fractionation
Cluster Analysis
Extracellular Matrix Proteins / chemistry,  isolation & purification,  metabolism*
Glycoproteins / chemistry,  isolation & purification,  metabolism
Guanidine / chemistry
Inflammation Mediators / chemistry,  isolation & purification,  metabolism
Matrix Metalloproteinase 12 / metabolism
Middle Aged
Proteome / chemistry,  isolation & purification,  metabolism*
Repressor Proteins / metabolism
Young Adult
Grant Support
FS/08/002/24537//British Heart Foundation; //British Heart Foundation
Reg. No./Substance:
0/AEBP1 protein, human; 0/Extracellular Matrix Proteins; 0/Glycoproteins; 0/Inflammation Mediators; 0/Proteome; 0/Repressor Proteins; EC 3.4.-/Carboxypeptidases; EC protein, human; EC Metalloproteinase 12; JU58VJ6Y3B/Guanidine

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

Full Text
Journal Information
Journal ID (nlm-ta): Mol Cell Proteomics
Journal ID (hwp): mcprot
Journal ID (pmc): mcprot
Journal ID (publisher-id): MCP
ISSN: 1535-9476
ISSN: 1535-9484
Publisher: The American Society for Biochemistry and Molecular Biology
Article Information
Download PDF
© 2011 by The American Society for Biochemistry and Molecular Biology, Inc.
Received Day: 22 Month: 1 Year: 2011
Revision Received Day: 27 Month: 4 Year: 2011
Print publication date: Month: 8 Year: 2011
Electronic publication date: Day: 18 Month: 5 Year: 2011
pmc-release publication date: Day: 18 Month: 5 Year: 2011
Volume: 10 Issue: 8
E-location ID: M111.008128
ID: 3149094
PubMed Id: 21593211
Publisher Id: M111.008128
DOI: 10.1074/mcp.M111.008128

Extracellular Matrix Composition and Remodeling in Human Abdominal Aortic Aneurysms: A Proteomics Approach*, Alternate Title:Proteomics of Abdominal Aortic Aneurysms
Athanasios Didangelos
Xiaoke Yin
Kaushik Mandal§
Angelika Saje
Alberto Smith
Qingbo Xu
Marjan Jahangiri
Manuel Mayr
From the ‡King's British Heart Foundation Centre, King's College London, London, UK;
§Department of Cardiac Surgery, Johns Hopkins University School of Medicine, Baltimore, USA;
¶Department of Cardiac Surgery, St. George's Healthcare NHS Trust, London, UK
Correspondence: ‖ To whom correspondence should be addressed: Cardiovascular Division, British Heart Foundation Center, King's College London, 125 Coldharbour Lane, London SE5 9NU, UK. Tel.: +44 (0) 20-7848-5132; E-mail:

Abdominal aortic aneurysms (AAA)1 affect 2–10% of the elderly population (1, 2) and are histopathologically characterized by the extensive degeneration of the aortic extracellular matrix (ECM) (3). The breakdown of structural proteins, in particular medial elastin and collagen I and III, is responsible for the inability of the aortic wall to withstand the hemodynamic forces (4). Transmural inflammatory infiltrates (5) combined with a reduction in the number of medial smooth muscle cells trigger the destruction of the aortic connective tissue via unregulated proteinase activity (6, 7). However, apart from the well-established elastolysis and collagenolysis, little is known about other changes in ECM composition and turnover in AAA. Recent proteomics studies on aneurysms have used whole tissue lysates (8, 9) and reported significant changes in cellular proteins but provided limited insights into matrix remodeling. Regarding the ECM these approaches had several limitations: first, whole tissue lysates are rich in cellular proteins, which mask the identification of scarce extracellular components, including proteinases and proteinase inhibitors. Second, ECM proteins are difficult to solubilize and analyze by proteomics because of their unique biochemical properties (aggregation, cross-linking, and glycosylation). Third, during pathological processes, such as aneurysm formation, the ECM undergoes extensive turnover with continuous degradation as well as deposition of newly synthesized matrix proteins. In analysis of whole tissue lysates, newly synthesized ECM proteins cannot be readily discerned from existing matrix proteins and only abundant degradation products are detected (9). To overcome these shortcomings we have recently developed a solubility-based, protein subfractionation procedure, which facilitates the selective extraction of newly synthesized ECM proteins and degradation products, reduces the contamination with cellular proteins, and ensures the solubilization of the interstitial ECM and its associated proteins, thereby improving their analysis by proteomics (10). In this study, we applied this subfractionation method to AAA. Our aim was to characterize the changes in ECM and associated proteins involved in the pathological remodeling process. We achieved the most detailed proteomics characterization of the aneurysmal ECM to date and revealed major differences between healthy and AAA tissues including the increased deposition and fragmentation of collagen XII, thrombospondin 2, aortic carboxypeptidase-like protein (ACLP), periostin, and fibronectin. In addition, we were able to show that these glycoproteins are novel proteolytic targets of MMP-12. Thus, our proteomics approach can serve as a platform for the identification of candidate markers of pathological remodeling in clinical samples (11).

Source of Tissue

This study was approved by the Research Ethics Committees of King's College London and St. George's Hospital London. All patients gave written informed consent. Advanced, asymptomatic, infrarenal AAA specimens were collected from four male patients >65 yr of age during open aneurysm repair surgery based on aneurysm size exceeding 5.5 cm in diameter (representative hematoxylin and eosin stained sections are shown in supplemental Fig. S1). Four control samples from patients without connective tissue disorder (one female and three males aged 20 to 55) were obtained upon aortotomy performed during routine aortic valve replacement from positions of the ascending aorta that were free of macroscopically evident vascular pathology (supplemental Fig. S1). There were no known potential confounders during sampling of clinical specimens and tissues were immediately snap-frozen and kept in liquid nitrogen for later use.

Tissue Preparation

Before extraction the tissue specimens were partially thawed and weighed. Approximately 150 mg of tissue per aortic sample were placed in ice-cold phosphate buffered saline to remove plasma contaminants. The buffer was supplemented with 1% v/v proteinase inhibitor mixture (Sigma-Aldrich), which contains AEBSF, aprotinin, bestatin, E-64, leupeptin, and pepstatin, with a broad specificity for serine, cysteine, and acid proteinases, and aminopeptidases and 1% v/v phosphatase inhibitor mixture (Sigma-Aldrich), which contains, sodium orthovanadate, cantharidin, imidazole, and calyculin A, to inhibit a broad range of phosphatases. In addition, 25 mM EDTA were added to ensure inhibition of metalloproteinases. While the tissue samples were immersed in the cold saline, they were diced with a scalpel into 8–10 smaller pieces to facilitate the removal of plasma contaminants and the effective extraction of extracellular proteins as described below.

Three-step Extraction Methodology

For the proteomics methodology we used three healthy aortic specimens (CON) and four AAA specimens. The diced samples were first incubated in a 0.5 M NaCl, 10 mM Tris, pH 7.5 buffer supplemented with proteinase and phosphatase inhibitor cocktails as above and 25 mM EDTA. The volume of the buffer was adjusted to 10:1 of the tissue weight (i.e. 100 mg in 1 ml). The samples were mildly vortexed for 4 h at room temperature. The NaCl extracts were then desalted with centrifugation using desalting columns (Zeba Spin, Pierce Biotechnology, Cramlington, Northumberland, UK). After desalting the extracts were mixed with 100% acetone (5:1 volume ratio) at −20 °C for 16 h. Proteins were precipitated with centrifugation (16,000 × g for 45 min) and the pellets were vacuum-dried and redissolved in deglycosylation buffer (see below). Subsequently, the aortic samples were incubated with 0.08% SDS (10:1 buffer volume to tissue weight), including proteinase and phosphatase inhibitor cocktails and 25 mM EDTA. The samples were mildly vortexed, to minimize mechanical disruption of the ECM, for 4 h at room temperature. The SDS solution was then removed and stored frozen for later use. Finally, the samples were incubated in a 4 M guanidine-HCl, 50 mM sodium acetate pH 5.8 buffer (5:1 buffer volume to tissue weight), plus proteinase and phosphatase inhibitor cocktails and 25 mM EDTA. pH was adjusted to 5.8 to improve the extractability of vascular proteoglycans (12). The samples were incubated for 48 h at room temperature and vortexed vigorously to enhance the mechanical disruption of matrix proteins. After the denaturing extraction guanidine was removed by mixing the samples with 100% ethanol (5:1 volume ratio) at −20 °C for 16 h. Proteins were then precipitated with centrifugation (16,000 × g for 45 min) and the pellets were washed with 90% ethanol, dried, and redissolved in deglycosylation buffer.


Deglycosylation (removal of glycosaminoglycan side chains) of the different extracts was achieved in a 150 mM NaCl, 50 mM sodium acetate pH 6.8 buffer supplemented with proteinase inhibitors and 10 mM EDTA for 16 h at 37 °C. The deglycosylation enzymes (0.05 U) were: 1) chondroitinase ABC from Proteus vulgaris (catalyzes the removal of polysaccharides containing 1⃗4-β-D-hexosaminyl and 1⃗3-β-D-glucuronosyl or 1⃗3-α-L-iduronosyl linkages to disaccharides containing 4-deoxy-β-D-gluc-4-enuronosyl groups. It acts on chondroitin 4-sulfate, chondroitin 6-sulfate, and dermatan sulfate glycosaminoglycan side chains). One unit will liberate 1.0 μM of 2-acetamido-2-deoxy-3-O-(β-D-gluc-4-ene-pyranosyluronic acid)-4-O-sulfo-D-galactose from chondroitin sulfate A or 1.0 μM of 2-acetamido-2-deoxy-3-O-(β-D-gluc-4-ene-pyranosyluronic acid)-6-O-sulfo-D-galactose from chondroitin sulfate C per minute at pH 8.0 at 37 °C. 2) keratanase from Bacteroides fragillis (cleaves internal 1⃗4-β-galactose linkages in unbranched, repeating poly-N-acetyl-lactosamine and keratan sulfate). One unit will release 1.0 μM of reducing sugar per minute at 37 °C and pH 5.8 from bovine corneal keratan sulfate. 3) heparatinase II Flavobacterium heparinum (cleaves heparan sulfate). One unit forms 0.1 μM of unsaturated uronic acid per hour at pH 7.0 at 37 °C. All enzymes were purchased from Sigma-Aldrich. After, deglycosylation the solutions were clarified with centrifugation (16.000 × g for 10 min) to ensure that the samples were free of turbidity and protein concentration was estimated by UV absorbance at 280 nm. Because of the expected contamination with nucleic acids that remain in the tissue after decellularization, in the 4 M guanidine extracts we used the Groves equation [(A280 × 1.55) – (A260 × 0.76)] to account for nucleic acid interference (13).

One-dimensional Electrophoresis

The 0.5 M NaCl and 4 M guanidine extracts were denatured and reduced in sample buffer containing 100 mM Tris, pH 6.8, 40% glycerol, 0.2% SDS, 2% β-mercaptoethanol and 0.02% bromphenol blue and boiled at 96 °C for 10 min. Thirty-five micrograms of protein per sample were loaded and separated on Bis-Tris discontinuous 4–12% polyacrylamide gradient gels (NuPage, Invitrogen). Protein standards were run along side the samples (prestained All Blue, Precision Plus, Bio-Rad Laboratories, Cramlington, Northumberland, UK).

Nanoflow LC-MS/MS

After electrophoresis, gels were stained using the PlusOne Silver staining Kit (GE Healthcare). Silver staining was used for band staining to avoid cross-contamination with fainter gel bands (14) All gel bands were excised in identical parallel positions across lanes and no empty gel pieces were left behind. Subsequently, all gel bands were subjected to in-gel tryptic digestion using an Investigator ProGest (Genomic Solutions) robotic digestion system. Tryptic peptides were separated on a nanoflow LC system (Dionex UltiMate 3000, UK) and eluted with a 10 min gradient (10–25% B in 35 min, 25–40% B in 5 min, 90% B in 10 min, and 2% B in 30 min where A is 2% acetonitrile, 0.1% formic acid in high performance liquid chromatography (HPLC) H2O and B is 90% acetonitrile, 0.1% formic acid in HPLC H2O). The column (Dionex PepMap C18, 25 cm length, 75 μm internal diameter, 3 μm particle size) was coupled to a nanospray source (Picoview) using RePlay (Advion). After the direct liquid chromatography (LC)-MS run, the flow was switched and the portion stored in the capillary of the RePlay device re-analyzed (“replay run”) (15). Spectra were collected from a high-mass accuracy analyzer (LTQ Orbitrap XL, ThermoFisher Scientific) using full ion scan mode over the mass-to-charge (m/z) range 450–1600. Tandem MS (MS/MS) was performed on the top six ions in each MS scan using the data-dependent acquisition mode with dynamic exclusion enabled. MS/MS peaklists were generated by extract_msn.exe and matched to human database (UniProtKB/Swiss-Prot Release 14.6, 20333 protein entries) using SEQUEST v.28 (rev. 13), (Bioworks Browser 3.3.1 SP1, ThermoFisher Scientific) and X! Tandem, (Version 2007.01.01.2). Carboxyamidomethylation of cysteine was chosen as fixed modification and oxidation of methionine as variable modification. The mass tolerance was set at 1.5 AMU for the precursor ions and at 1.0 AMU for fragment ions. Two missed cleavages were allowed. Scaffold (version 2.0.6, Proteome Software Inc., Portland, OR) was used to calculate the normalized spectral counts, and to validate peptide and protein identifications (16, 17). According to the default values in the Scaffold software, peptide identifications were accepted if they could be established at greater than 95.0% probability as specified by the Peptide Prophet algorithm (16). Only tryptic peptides were included in the analysis. Protein identifications were accepted if they could be established at greater than 99.0% probability (17) with at least two independent peptides and a mass accuracy of ≤10ppm of the precursor ion. ECM proteins identified for the first time by proteomics in the vasculature as well as ECM proteins with low spectral counts were further examined to ensure the quality of the identified spectra.

Western Blotting

Aliquots of the NaCl, guanidine, and SDS extracts were mixed with denaturing sample buffer and boiled. Thirty micrograms of protein per sample were loaded and separated on 4–12% gradient gels as above. Proteins were then transferred on nitrocellulose membranes. Membranes were blocked in 5% fat-free milk powder in PBS and probed for 16 h at 4 °C with primary antibodies to: CD68 (sc-70761, Santa Cruz Biotechnology, Santa Cruz, CA) and smooth muscle actin (A5228, Sigma-Aldrich) (0.08% SDS extracts). Collagen XII (sc-166020), thrombospondin 2 (sc-12313), fibronectin (sc-56391), ACLP (sc-32919), periostin (sc-67233), and MMP-12 (sc-133151) all from Santa Cruz Biotechnology, and tenascin (ab6393) and TIMP-1 (ab38978) both from Abcam (Cambridge, UK) (0.5 M NaCl extracts). The 4 M guanidine extracts were immunoblotted for eSOD (SOD-105) from Stressgen (Victoria, BC, Canada). All antibodies were used at 1:500 dilution in 5% bovine serum albumin. The membranes were treated with the appropriate secondary, horseradish peroxidase (HRP) conjugated antibodies (Dako) at a 1:2000 dilution. Finally, the blots were imaged using enhanced chemilluminenscence (ECL, GE Healthcare) and films were developed on an Xograph processor. The densitometry for the lanes from developed films for collagen XII, tenascin, thrombospondin 2, fibronectin, ACLP, periostin, eSOD, MMP-12, and TIMP-1 was measured using the ImageJ software (v1.42q, NIH, USA).

In Vitro MMP Digestion Assay

Normal aortic specimens taken upon aortotomy (as described above) from patients without connective tissue disorder, were dissected into equal blocks (≈30 mg), and were washed five times in ice-cold, 1× PBS. The tissue blocks were then mixed with 10 volumes MMP reaction buffer (10 mM CaCl2, 120 mM NaCl, 50 mM Trizma base, and 0.05%w/v Brij-35, pH 7.5), which was either used plain or supplemented with human recombinant MMP-9 or human recombinant MMP-12, both derived from murine myeloma cell lines (R&D Systems, Minneapolis, MN). MMP-9 was activated by incubation with 0.5 mM APMA (Aminophenylmercuric acetate) (Sigma-Aldrich) in MMP reaction buffer at 37 °C for 24 h, while MMP-12 was auto-activated in MMP reaction buffer at 37 °C for 30 h, both according to manufacturer's instructions. APMA was removed by desalting through a Zeba Spin (Thermo Scientific) desalting column (MMP-12 was also spun through a desalting column for comparison). The mixtures were supplemented with the proteinase inhibitor mixture to inhibit non-MMP proteinase activity. After the incubation of the aortic tissue with the activated MMPs, the tissue supernatants were deglycosylated, and then immunoblotted using antibodies to collagen XII, thrombospondin 2, tenascin, fibronectin ACLP, and periostin. Activated MMP-12 was also used on human recombinant periostin and thrombospondin 2 both derived from murine myeloma cell lines (R&D Systems) and on purified human fibronectin (Sigma-Aldrich). Ten micrograms of each protein were incubated in MMP reaction buffer, supplemented with proteinase inhibitor mixture, at 37 °C for 16 h with or without MMP-12.


Small representative pieces from AAA and control aortic samples were placed in OCT compound (BD Healthcare) and used to generate consecutive 7 μm thick sections on a Leica cryostat. The sections were air-dried (30 min) and fixed in 100% acetone for 20 min. Subsequently, sections were either stained with hematoxylin and eosin (H&E) or incubated with primary antibodies. Before immunohistochemistry, the internal peroxidase activity was quenched using a 3% hydrogen peroxide solution in methanol for 15 min. Sections were probed with antibodies to CD68 (sc-70761), ACLP (sc-32919), MMP-12 (sc-133151) from Santa Cruz Biotechnology. Primary antibodies were used at 2 μg/ml. Staining was produced using appropriate HRP-conjugated secondary antibodies, developed with diaminobenzidine purchased from Dako. Negative controls were generated with mouse and rabbit isotype IgG antibodies (Sigma-Aldrich, 2 μg/ml). Nuclei were counterstained blue using Mayer's hematoxylin solution (Sigma-Aldrich) for 5 min. Images were taken by a Zeiss Axioplan 2ie microscope interfaced to AxioVision software (version 3.0.6).

Statistical Analysis

For each clinical sample (CON, n = 3 and AAA, n = 4) and biochemical fraction (0.5 M NaCl and 4 M guanidine), we obtained a technical LC-MS/MS replicate using the RePlay device (Advion). The value reported as spectral count for each protein was calculated as the average ±S.E. of all samples and technical replicates (i.e. CON, n = 6 and AAA, n = 8). All assigned spectra for each protein were used for spectral counting. Before statistical analysis protein spectral counts were normalized using the Scaffold software (version 2.0.6, Proteome Software Inc., Portland, OR) by calculating and averaging the number of identified spectra in each sample, then multiplying the number of spectra assigned to each protein by the ratio of the average spectral count and the number of total spectra in that sample. Protein ambiguity issues were handled using tools available in the Scaffold software and peptides assigned to more than one protein are highlighted in supplemental Table S1. The difference in normalized spectral counts for each identified extracellular protein between control and AAA was computed using two-tailed, unpaired t test (GraphPad Prism 5). A p value of ≤0.05 was considered significant. Only proteins identified with at least two unique peptides were included in the analysis and no outliers were removed. Proteins with a significant difference in normalized spectral counts (p ≤ 0.05) between control and AAA samples were progressively joined into clusters. Pairwise similarity in spectral counts between different proteins (rows) and different samples (columns) was computed using Pearson Correlation Coefficient. The dendrograms and quantitative heat maps were produced using the GenePattern software (version 3.2.3) (18). The relative difference in normalized spectral counts is represented by a color gradient. No outliers were removed. The correlation between the spectral counts and the densitometry values of immunoblots was calculated using Spearman's rank correlation coefficient (GraphPad Prism 5). A p value of ≤0.05 was considered significant.

Characterization of AAA and ECM Extraction

Before proteomics, all tissue specimens were examined histologically. Extensive medial degeneration with few intact elastic laminae, inflammatory infiltrates (indicated by CD68 staining) and loss of smooth muscle cells (SMCs) were evident in AAA. Representative images are shown in Fig. 1A–C. The macrophage marker CD68 was not detected in normal aortic specimens (Fig. 1D). CD68 positivity in AAA inversely correlated to smooth muscle actin (SMA) staining (Fig. 1D). The ECM and its associated proteins were extracted from four AAA and three control (CON) aortas following our established, procedure (10). The proteomics workflow is summarized in Fig. 2. Briefly, in the first step the ionic strength of the 0.5 M NaCl buffer is sufficient to solubilize extracellular proteins that are weakly bound to the ECM (19), including newly synthesized ECM proteins (20), which are not heavily cross-linked, degradation products and other proteins present in the extracellular space. In the second step the samples are decellularized using 0.08% SDS to reduce the highly abundant cellular proteins. Finally, in the third step the extraction of the mature, heavily cross-linked ECM (proteoglycans, glycoproteins, and collagens) is achieved using 4 M guanidine, a strongly denaturing agent.

Proteomics Analysis of the 0.5 M NaCl and 4 M Guanidine Extracts

After deglycosylation, proteins in the 0.5 M NaCl and 4 M guanidine extracts were separated by one-dimensional SDS-PAGE (supplemental Fig. S2), subjected to in-gel tryptic digestion, and analyzed by LC-MS/MS using a high mass accuracy ion trap (LTQ-Orbitrap XL, Thermo Fisher Scientific) interfaced to the RePlay device (Advion) to obtain a technical replicate for each biological sample. The entire MS/MS dataset has been deposited in PRIDE, a public repository for mass spectrometry data (, accession numbers: 16940–17107). Only proteins passing stringent identification criteria are listed in supplemental Tables S2 and S3 (0.5 M NaCl and 4 M guanidine extracts, respectively). According to the Gene Ontology Annotation database, 80 nonredundant proteins in the 0.5 M NaCl (Table I) and 117 nonredundant proteins in the 4 M guanidine (Table II) fractions were either ECM proteins (proteoglycans, glycoproteins, and collagens) or proteins associated with the ECM such as secreted proteinases, extracellular enzymes, growth factors, cytokines, and lipoproteins. Among the identified extracellular proteins eight were only found in the 0.5 M NaCl extracts whereas 45 proteins were unique to the 4 M guanidine extracts (Fig. 3A). As expected, most unique proteins in the 0.5 M NaCl extracts were secreted factors such as cathepsin S, eosinophil cationic protein, hepatoma-derived growth factor, leukocyte elastase inhibitor, and proactivator polypeptide, whereas the proteins exclusive to the 4 M guanidine extracts were predominantly matrix proteins such as asporin, cartilage acidic protein 1, link protein, prolargin, laminins, matrix Gla protein, sclerostin, and collagen V. Interestingly, spectral counts for ECM proteins were significantly increased in the salt-soluble protein fraction of AAA (p < 0.0001, Fig. 3B). In contrast, in the 4 M guanidine extracts the spectral counts for ECM proteins (Fig. 3C) as well as the number of total spectra in either the 0.5 M NaCl or 4 M guanidine extracts (data not shown) were not significantly different between control and AAA.

ECM and Associated Proteins in AAA

Differences in relative protein abundance between control (CON) and AAA were estimated using normalized spectral counts (Table I and Table II). No outliers were removed. Details can be found in Experimental Procedures. Hierarchical clustering of the differentially expressed extracellular proteins in both the NaCl and guanidine extracts clearly separated the control and AAA samples and highlighted major differences in their ECM composition (Fig. 4). Increased levels of collagens I and VI and the fibril-associated collagen XII, fibronectin, vitronectin, tenascin (alternative name: tenascin-C), thrombospondins 1 and 2, and ACLP were observed in the 0.5 M NaCl extracts of AAA (Fig. 4A, Table I). These proteins, excluding ACLP, were also more abundant in the 4 M guanidine extracts of AAA (Fig. 4B, Table II) indicating that they are components of the mature, salt-insoluble aneurysmal ECM. We also noted a decrease in the spectral counts of the large proteoglycans aggrecan, versican, and perlecan in AAA (Fig. 4B, Table II), perhaps because of proteolysis at an earlier stage of the disease. The reduction in perlecan could explain the loss of extracellular superoxide dismutase (eSOD) (Fig. 4A and 4B, Table I and II) because this antioxidant enzyme is attached to perlecan and other heparan sulfate proteoglycans in extracellular space (21). There was also a reduction in another fibril-associated collagen, type XIV, and the poorly characterized extracellular proteins, retinal pigment epithelium spondin (RPE-spondin), dyxin and target of Nesh-SH3 (Fig. 4B, Table II). Moreover, proteomics identified scarce extracellular proteins including the calgranulins S100A8 and A9 (Figs. 4A and 4B, Table I and II), calcium-binding neutrophil proteins that are involved in macrophage adhesion and transmigration (22), the tissue inhibitor of metalloproteinases 1 (TIMP-1) and macrophage metalloelastase, MMP-12 (Figs. 4A and 4BTable I and Table II). Representative MS/MS spectra from extracellular proteins identified for the first time by proteomics in the vasculature are shown in supplemental Fig. S3.

Inflammatory Markers in AAA

Besides a clear distinction between control and AAA samples, the hierarchical clustering revealed notable differences among the four AAA specimens (Figs. 4A and 4B). Proteins involved in inflammation, such as apolipoprotein D, ceruloplasmin, myeloperoxidase, S100A8, and A9 were more abundant in samples 1 and 3, whereas the ECM proteins perlecan, aggrecan, versican, collagen XIV, and the matrix associated enzyme eSOD were higher in samples 2 and 4 (Figs. 4A and 4B). These differences reflect the cellular composition observed in the SDS extracts (Fig. 1D). AAA specimens 1 and 3 had a higher macrophage content explaining the abundance of inflammatory factors whereas the loss of smooth muscle cells is consistent with the reduction in ECM components.

Validation of Proteomics and ECM Remodelling

Six glycoproteins covering the detectable range of protein abundance in our samples were selected for further validation. According to spectral counting, collagen XII, tenascin, thrombospondin 2, fibronectin, ACLP, and periostin (Fig. 5, left panels) were increased in the 0.5 M NaCl extracts of the four AAA specimens. Immunoblotting confirmed higher levels in AAA (Fig. 5, middle panels). The loss of eSOD as well as the accumulation of MMP-12 and TIMP-1 were also validated by immunoblotting. Overall, there was a good correlation (Spearman correlation, r ≥ 0.8, p ≤ 0.05) between the protein abundance estimated by spectral counting and Western blotting (Fig. 5, right panels). For periostin and MMP-12 the correlation was not significant because spectral counting is less accurate when protein levels are low (23). Nonetheless, our methodology allowed the detection of matrix macromolecules as well as scarce secreted proteins in complex clinical samples.

ECM Remodelling and the Role of MMP-12

The Western blots presented in Fig. 5 highlight the fragmentation of collagen XII, tenascin, thrombospondin 2, fibronectin, ACLP, and periostin in the AAA samples. Indeed, detailed examination of the gel-LC-MS/MS data revealed that a high number of MS/MS spectra were identified in gel segments below the expected molecular weight of these proteins (Fig. 6A) confirming the presence of proteolytic products in the aneurysmal tissue. Although various MMPs, including MMP-12, have been linked to matrix proteolysis during aneurysm formation (24, B2526), MMP-12 was the only metalloproteinase that was significantly increased in our proteomics analysis (Fig. 4). To investigate the possible relationship between the observed fragmentation of these glycoproteins and the presence of MMP-12, we incubated macroscopically normal, human aortic specimens with recombinant MMP-12 in vitro (Fig. 6B). MMP-9, another metalloproteinase implicated in AAA pathology (27), served as an additional control. MMP-12 induced extensive fragmentation of fibronectin and cleaved collagen XII, tenascin, and periostin. Thrombospondin 2 was degraded producing two small cleavage products (≈20 kDa). In comparison to MMP-9, MMP-12 had more pronounced effects on the degradation of fibronectin, tenascin, collagen XII, and thrombospondin 2, whereas MMP-9 induced the release of full-length periostin from the aortic matrix, presumably by limited proteolysis. Intriguingly, treatment with both proteinases resulted in an almost complete loss of ACLP immunostaining. With the exception of fibronectin (28), all other glycoproteins are novel substrates for MMP-12. The proteinase had a dose (0–50 pM, supplemental Fig. S4) and time-dependent (2–16h, supplemental Fig. S5) effect on these glycoproteins in the aortic explants. Importantly, its proteolytic effect on the tissue was almost completely abolished by 10 mM EDTA (supplemental Fig. S6). In addition, MMP-12 was able to cleave human recombinant periostin and thrombospondin 2 in vitro (Fig. 6C). Human fibronectin, a known MMP-12 substrate, was used as a positive control.

ACLP and MMP-12

The proteolytic effect of MMP-12 on ACLP was very pronounced and considering the lack of knowledge on this collagen-associated glycoprotein (29) in aneurysms, we sought to examine its localization by immunohistochemistry. In AAA, extracellular ACLP staining was present both in the hypocellular regions of the media (Fig. 7A), where tissue architecture is more preserved with intact elastic laminae and absence of inflammatory infiltrates, and in the amorphous, inflammatory areas, where connective tissue loss is evident (Fig. 7B). In consecutive serial sections, MMP-12 staining was predominantly found in the inflammatory areas (Figs. 7C and 7D) and there was an inverse correlation in the staining intensity of the two proteins, supporting the proteolytic effect of MMP-12 on ACLP in the tissue. Negative controls are shown in Figs. 7E and 7F.


The destruction of the aortic connective tissue in aneurysms is driven by a severe inflammatory reaction and involves the excessive degradation of the aortic ECM. However, the abundance of cellular proteins in the aorta and the biochemical properties of matrix components have so far limited the characterization of the ECM in vascular pathologies (30). In this study we employed a solubility-based, protein subfractionation methodology that enabled the detailed characterization of the ECM and its associated proteins in AAA. Importantly, this approach offered novel insights into the pathological remodeling process and allowed us to relate changes in the turnover of certain ECM proteins to the increased levels of MMP-12 in AAA.

Changes in the Extracellular Proteome of AAA

Proteomics revealed marked differences in the ECM composition between control and AAA specimens (Figs. 4 and 5). As a consequence of the pathological remodeling, the salt-soluble protein fraction of aneurysms was enriched in ECM fragmentation products. Many of the identified protein changes have not been previously reported in AAA, including collagen XII, thrombospondin 2, periostin, and ACLP. Collagen XII is a fibril-associated collagen and accumulates in tissues exposed to high tensile forces (31) whereas periostin and thrombospondin 2 are glycoproteins involved in cellular adhesion and spreading (32, 33). ACLP is an extracellular glycoprotein, which is known to accumulate in the ECM associated with collagen fibers (29), but its function is not well understood. Recently, Schissel et al., showed that ACLP is a positive regulator of fibrosis in the injured lung (34). Fibronectin is the primary component of granulation tissue after wound healing (35) and this may explain its accumulation in the injured aortic wall. Increased tenascin mRNA expression has been previously reported in AAA and was associated with the accumulation of macrophages (36). Our proteomics data also revealed the fragmentation of these ECM proteins (Fig. 5). Degradation products reflect the pathological remodeling process in AAA.

In the 4 M guanidine extracts of AAA there was a reduction in the three major proteoglycans versican, perlecan, and aggrecan, as well as link protein, the glycoprotein which links aggregating proteoglycans to hyaluronic acid. Although a previous study demonstrated that versican was reduced in aneurysms (37), not much is known about the contribution of perlecan and aggrecan to this pathology (38, 39). The loss of these major proteoglycans is likely to have major impact on SMC attachment, proliferation, and migration but it will also affect the binding and storage of various regulatory molecules in the extracellular space including extracellular enzymes and growth factors (40). For example, extracellular superoxide dismutase (eSOD) was reduced in AAA (Fig. 5). This potent antioxidant enzyme is located in the vascular extracellular space bound to subendothelial heparan sulfate proteoglycans such as perlecan (21). A loss of these proteoglycans could result in reduced retention of eSOD and other extracellular proteins, thereby affecting the overall integrity of the vascular wall.

MMP-12 in AAA

Studies investigating the proteolytic activity in human tissues rely on mRNA expression, immunostaining or zymography and tend to focus on individual proteinases and their inhibitors. MMPs -1, -2, -3, -7, -9, and -12 have previously been detected in macrophage-rich areas of AAA and their proteolytic activity has been linked to aneurysm formation (24, B2526). Interestingly, little is known about their relative abundance in AAA. A limitation of antibody-based detection is that the staining intensity is not only dependent on the protein amount but also on the binding affinity and specificity of the antibody. Hence, staining with different antibodies cannot be directly compared. Instead, a proteomics approach provides an unbiased assessment of proteinases and potential degradation products in diseased tissue. Whereas previous proteomics studies primarily focused on cellular proteins and failed to identify MMPs in AAA (8, 9), our subfractionation method enabled the detection of MMP-12. This does not exclude the presence of other MMPs, but suggests that MMP-12 is probably more abundant and underscores its role in the pathology of AAA (41, 42). MMP-2, cathepsins D, G, S, and Z, and the mast cell proteinases chymase and tryptase β-1 were also identified (Table I and Table II), but only cathepsin G was significantly increased in AAA (Fig. 4B). Interestingly, cathepsin G was recently shown to degrade intraluminal thrombi in aneurysms (43).

Novel Targets of MMP-12 in the Aortic Tissue

Apart from its well-established elastolytic and collagenolytic properties (24), little is known about the ability of MMP-12 to degrade other substrates in the aorta. Thus far, the presence of proteolytic products from known MMP targets has been mainly studied by immunostaining using neoepitope antibodies against the cleaved substrates (44). Our subfractionation methodology allowed a more comprehensive analysis of the ECM remodelling in AAA. For instance, in the salt-soluble protein fraction, we observed not only an increase but also a partial degradation of collagen XII, fibronectin, tenascin, thrombospondin 2, ACLP, and periostin. When healthy aortic tissue was incubated with recombinant MMP-12, the proteinase was able to cleave these substrates. Its effect, at least in vitro, was more potent than MMP-9, suggesting that MMP-12 might be responsible for the degradation of these proteins in AAA. Of course, the fragmentation pattern after MMP-12 treatment was not identical to the laddering observed in the 0.5 M NaCl extracts. This is expected because the proteolytic activity in tissues is a highly dynamic process regulated by the interplay of MMPs with TIMPs and other inhibitors. In agreement with previous studies (45), we found that TIMP-1 and -3 were significantly increased in AAAs (Figs. 4A and 4B) indicating a compensatory anticatabolic response. One of the fragmented proteins in AAA was ACLP (Fig. 5). MMP-12 was able to degrade it in vitro (Fig. 6B). Further analysis by immunohistochemistry confirmed an inverse correlation of the staining intensities for ACLP and MMP-12 in the inflammatory regions of AAA (Figs. 7B and 7D), providing additional evidence that the proteinase could target ACLP in vivo.

Strengths and Limitations

The gel-based separation employed in this study, preserves the molecular mass of proteins and allows the assessment of proteolytic degradation in diseased tissues. This key information on protein fragmentation is lost in conventional shotgun proteomics. The label-free quantitation based on spectral counting allows the relative estimation of protein abundance (46) and shows a good correlation with approaches based on isotopic labels (47) and precursor peak area intensity measurements (23). However, its accuracy is limited to large differences and proteins with reasonable abundance. Hence, caution should be taken in the interpretation of modest changes and the quantitation of scarce proteins (48). In this study we analyzed simplified subproteomes and nine extracellular proteins were validated by Western blotting to ensure the accuracy of our proteomics findings. The observed changes between healthy and aneurysmal tissues were pronounced allowing reliable conclusions to be made despite the low number of clinical specimens available. Because AAAs are currently treated by endovascular stenting rather than open repair interventions, surgical specimens are increasingly rare. Additionally, healthy control tissue could only be obtained from the thoracic part of the aorta.


This study is the first to employ a solubility-based extraction procedure to study the ECM composition in human AAA by proteomics. Our methodology led to the identification of novel candidate markers of pathological tissue remodeling and identified new proteolytic targets of MMP-12, one of the key proteinases in AAA.


FN1* This work was funded by the British Heart Foundation and the Oak Foundation. M.M. is a Senior Fellow of the British Heart Foundation.

FN2 This article contains supplemental Figs. S1 to S6 and Tables S1 to S3.

G11 The abbreviations used are:

AAA Abdominal aortic aneurysm
ACLP Aortic carboxypeptidase-like protein
ECM Extracellular matrix
eSOD extracellular superoxide dismutase
LTQ Linear trap quadrupole
MMP Matrix metalloproteinase
TIMP Tissue inhibitor of metalloproteinases
LC liquid chromatography
MS/MS tandem MS.

1.. Alcorn H. G.,Wolfson S. K. Jr.,Sutton-Tyrrell K.,Kuller L. H.,O'Leary D.. (Year: 1996) Risk factors for abdominal aortic aneurysms in older adults enrolled in The Cardiovascular Health Study. Arterioscler. Thromb. Vasc. Biol. 16, 963–9708696960
2.. Baumgartner I.,Hirsch A. T.,Abola M. T.,Cacoub P. P.,Poldermans D.,Steg P. G.,Creager M. A.,Bhatt D. L.. (Year: 2008) Cardiovascular risk profile and outcome of patients with abdominal aortic aneurysm in out-patients with atherothrombosis: data from the Reduction of Atherothrombosis for Continued Health (REACH) Registry. J Vasc Surg48, 808–81418639426
3.. Golledge J.,Tsao P. S.,Dalman R. L.,Norman P. E.. (Year: 2008) Circulating markers of abdominal aortic aneurysm presence and progression. Circulation118, 2382–239219047592
4.. Hellenthal F. A.,Buurman W. A.,Wodzig W. K.,Schurink G. W.. (Year: 2009) Biomarkers of AAA progression. Part 1: extracellular matrix degeneration. Nat Rev Cardiol6, 464–47419468292
5.. Shiraya S.,Miyake T.,Aoki M.,Yoshikazu F.,Ohgi S.,Nishimura M.,Ogihara T.,Morishita R.. (Year: 2009) Inhibition of development of experimental aortic abdominal aneurysm in rat model by atorvastatin through inhibition of macrophage migration. Atherosclerosis202, 34–4018482727
6.. Shah P. K.. (Year: 1997) Inflammation, metalloproteinases, and increased proteolysis: an emerging pathophysiological paradigm in aortic aneurysm. Circulation96, 2115–21179337176
7.. Shimizu K.,Shichiri M.,Libby P.,Lee R. T.,Mitchell R. N.. (Year: 2004) Th2-predominant inflammation and blockade of IFN-gamma signaling induce aneurysms in allografted aortas. J. Clin. Invest. 114, 300–30815254597
8.. Liao M.,Liu Z.,Bao J.,Zhao Z.,Hu J.,Feng X.,Feng R.,Lu Q.,Mei Z.,Liu Y.,Wu Q.,Jing Z.. (Year: 2008) A proteomic study of the aortic media in human thoracic aortic dissection: implication for oxidative stress. J. Thorac. Cardiovasc. Surg. 136, 65–72, 72, e61–6318603055
9.. Pilop C.,Aregger F.,Gorman R. C.,Brunisholz R.,Gerrits B.,Schaffner T.,Gorman J. H. 3rd,Matyas G.,Carrel T.,Frey B. M.. (Year: 2009) Proteomic analysis in aortic media of patients with Marfan syndrome reveals increased activity of calpain 2 in aortic aneurysms. Circulation120, 983–99119720936
10.. Didangelos A.,Yin X.,Mandal K.,Baumert M.,Jahangiri M.,Mayr M.. (Year: 2010) Proteomics characterization of extracellular space components in the human aorta. Mol. Cell Proteomics9, 2048–206220551380
11.. Mayr M.,Zhang J.,Greene A. S.,Gutterman D.,Perloff J.,Ping P.. (Year: 2006) Proteomics-based development of biomarkers in cardiovascular disease: mechanistic, clinical, and therapeutic insights. Mol. Cell Proteomics5, 1853–186416733263
12.. Eisenstein R.,Larsson S. E.,Kuettner K. E.,Sorgente N.,Hascal V. C.. (Year: 1975) The ground substance of the arterial wall. Part 1. Extractability of glycosaminoglycans and the isolation of a proteoglycan from bovine aorta. Atherosclerosis22, 1–17125595
13.. Groves W. E.,Davis F. C. Jr.,Sells B. H.. (Year: 1968) Spectrophotometric determination of microgram quantities of protein without nucleic acid interference. Anal. Biochem. 22, 195–2104171014
14.. Yin X.,Cuello F.,Mayr U.,Hao Z.,Hornshaw M.,Ehler E.,Avkiran M.,Mayr M.. (Year: 2010) Proteomics analysis of the cardiac myofilament subproteome reveals dynamic alterations in phosphatase subunit distribution. Mol. Cell Proteomics9, 497–50920037178
15.. Waanders L. F.,Almeida R.,Prosser S.,Cox J.,Eikel D.,Allen M. H.,Schultz G. A.,Mann M.. (Year: 2008) A novel chromatographic method allows on-line reanalysis of the proteome. Mol. Cell Proteomics7, 1452–145918448420
16.. Keller A.,Nesvizhskii A. I.,Kolker E.,Aebersold R.. (Year: 2002) Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 74, 5383–539212403597
17.. Nesvizhskii A. I.,Keller A.,Kolker E.,Aebersold R.. (Year: 2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal. Chem. 75, 4646–465814632076
18.. Reich M.,Liefeld T.,Gould J.,Lerner J.,Tamayo P.,Mesirov J. P.. (Year: 2006) GenePattern 2.0. Nat. Genet. 38, 500–50116642009
19.. Mason R. M.,Mayes R. W.. (Year: 1973) Extraction of cartilage protein-polysaccharides with inorganic salt solutions. Biochem. J. 131, 535–5404269048
20.. Wilson R.,Diseberg A. F.,Gordon L.,Zivkovic S.,Tatarczuch L.,Mackie E. J.,Gorman J. J.,Bateman J. F.. (Year: 2010) Comprehensive profiling of cartilage extracellular matrix formation and maturation using sequential extraction and label-free quantitative proteomics. Mol. Cell Proteomics9, 1296–131320190199
21.. Karlsson K.,Sandström J.,Edlund A.,Marklund S. L.. (Year: 1994) Turnover of extracellular-superoxide dismutase in tissues. Lab. Invest. 70, 705–7108196366
22.. Croce K.,Gao H.,Wang Y.,Mooroka T.,Sakuma M.,Shi C.,Sukhova G. K.,Packard R. R.,Hogg N.,Libby P.,Simon D. I.. (Year: 2009) Myeloid-related protein-8/14 is critical for the biological response to vascular injury. Circulation120, 427–43619620505
23.. Old W. M.,Meyer-Arendt K.,Aveline-Wolf L.,Pierce K. G.,Mendoza A.,Sevinsky J. R.,Resing K. A.,Ahn N. G.. (Year: 2005) Comparison of label-free methods for quantifying human proteins by shotgun proteomics. Mol. Cell Proteomics4, 1487–150215979981
24.. Curci J. A.,Liao S.,Huffman M. D.,Shapiro S. D.,Thompson R. W.. (Year: 1998) Expression and localization of macrophage elastase (matrix metalloproteinase-12) in abdominal aortic aneurysms. J. Clin. Invest. 102, 1900–19109835614
25.. Knox J. B.,Sukhova G. K.,Whittemore A. D.,Libby P.. (Year: 1997) Evidence for altered balance between matrix metalloproteinases and their inhibitors in human aortic diseases. Circulation95, 205–2128994438
26.. Pyo R.,Lee J. K.,Shipley J. M.,Curci J. A.,Mao D.,Ziporin S. J.,Ennis T. L.,Shapiro S. D.,Senior R. M.,Thompson R. W.. (Year: 2000) Targeted gene disruption of matrix metalloproteinase-9 (gelatinase B) suppresses development of experimental abdominal aortic aneurysms. J. Clin. Invest. 105, 1641–164910841523
27.. Newman K. M.,Ogata Y.,Malon A. M.,Irizarry E.,Gandhi R. H.,Nagase H.,Tilson M. D.. (Year: 1994) Identification of matrix metalloproteinases 3 (stromelysin-1) and 9 (gelatinase B) in abdominal aortic aneurysm. Arterioscler. Thromb. 14, 1315–13208049193
28.. Fu J. Y.,Lyga A.,Shi H.,Blue M. L.,Dixon B.,Chen D.. (Year: 2001) Cloning, expression, purification, and characterization of rat MMP-12. Protein Expr. Purif. 21, 268–27411237688
29.. Layne M. D.,Endege W. O.,Jain M. K.,Yet S. F.,Hsieh C. M.,Chin M. T.,Perrella M. A.,Blanar M. A.,Haber E.,Lee M. E.. (Year: 1998) Aortic carboxypeptidase-like protein, a novel protein with discoidin and carboxypeptidase-like domains, is up-regulated during vascular smooth muscle cell differentiation. J. Biol. Chem. 273, 15654–156609624159
30.. Mayr M.,Chung Y. L.,Mayr U.,Yin X.,Ly L.,Troy H.,Fredericks S.,Hu Y.,Griffiths J. R.,Xu Q.. (Year: 2005) Proteomic and metabolomic analyses of atherosclerotic vessels from apolipoprotein E-deficient mice reveal alterations in inflammation, oxidative stress, and energy metabolism. Arterioscler. Thromb. Vasc. Biol. 25, 2135–214216123314
31.. Trächslin J.,Koch M.,Chiquet M.. (Year: 1999) Rapid and reversible regulation of collagen XII expression by changes in tensile stress. Exp. Cell Res. 247, 320–32810066359
32.. Gillan L.,Matei D.,Fishman D. A.,Gerbin C. S.,Karlan B. Y.,Chang D. D.. (Year: 2002) Periostin secreted by epithelial ovarian carcinoma is a ligand for alpha(V)beta(3) and alpha(V)beta(5) integrins and promotes cell motility. Cancer Res. 62, 5358–536412235007
33.. Lopes N.,Gregg D.,Vasudevan S.,Hassanain H.,Goldschmidt-Clermont P.,Kovacic H.. (Year: 2003) Thrombospondin 2 regulates cell proliferation induced by Rac1 redox-dependent signaling. Mol. Cell. Biol. 23, 5401–540812861025
34.. Schissel S. L.,Dunsmore S. E.,Liu X.,Shine R. W.,Perrella M. A.,Layne M. D.. (Year: 2009) Aortic carboxypeptidase-like protein is expressed in fibrotic human lung and its absence protects against bleomycin-induced lung fibrosis. Am. J. Pathol. 174, 818–82819179605
35.. Valenick L. V.,Hsia H. C.,Schwarzbauer J. E.. (Year: 2005) Fibronectin fragmentation promotes alpha4beta1 integrin-mediated contraction of a fibrin-fibronectin provisional matrix. Exp. Cell Res. 309, 48–5515992798
36.. Satta J.,Soini Y.,Pöllänen R.,Pääkko P.,Juvonen T.. (Year: 1997) Tenascin expression is associated with a chronic inflammatory process in abdominal aortic aneurysms. J. Vasc. Surg. 26, 670–6759357470
37.. Theocharis A. D.,Tsolakis I.,Hjerpe A.,Karamanos N. K.. (Year: 2001) Human abdominal aortic aneurysm is characterized by decreased versican concentration and specific downregulation of versican isoform V(0). Atherosclerosis154, 367–37611166769
38.. Melrose J.,Whitelock J.,Xu Q.,Ghosh P.. (Year: 1998) Pathogenesis of abdominal aortic aneurysms: possible role of differential production of proteoglycans by smooth muscle cells. J. Vasc. Surg. 28, 676–6869786264
39.. Baas A. F.,Medic J.,van't Slot R.,de Vries J. P.,van Sambeek M. R.,Verhoeven E. L.,Boll B. P.,Grobbee D. E.,Wijmenga C.,Blankensteijn J. D.,Ruigrok Y. M.. (Year: 2010) The intracranial aneurysm susceptibility genes HSPG2 and CSPG2 are not associated with abdominal aortic aneurysm. Angiology61, 238–24220053631
40.. Vincent T.,Hermansson M.,Bolton M.,Wait R.,Saklatvala J.. (Year: 2002) Basic FGF mediates an immediate response of articular cartilage to mechanical injury. Proc. Natl. Acad. Sci. U.S.A. 99, 8259–826412034879
41.. Longo G. M.,Buda S. J.,Fiotta N.,Xiong W.,Griener T.,Shapiro S.,Baxter B. T.. (Year: 2005) MMP-12 has a role in abdominal aortic aneurysms in mice. Surgery137, 457–46215800495
42.. Wang Y.,Ait-Oufella H.,Herbin O.,Bonnin P.,Ramkhelawon B.,Taleb S.,Huang J.,Offenstadt G.,Combadière C.,Rénia L.,Johnson J. L.,Tharaux P. L.,Tedgui A.,Mallat Z.. (Year: 2010) TGF-beta activity protects against inflammatory aortic aneurysm progression and complications in angiotensin II-infused mice. J. Clin. Invest. 120, 422–43220101093
43.. Dejouvencel T.,Féron D.,Rossignol P.,Sapoval M.,Kauffmann C.,Piot J. M.,Michel J. B.,Fruitier-Arnaudin I.,Meilhac O.. (Year: 2010) Hemorphin 7 reflects hemoglobin proteolysis in abdominal aortic aneurysm. Arterioscler. Thromb. Vasc. Biol. 30, 269–27519910633
44.. Sukhova G. K.,Schönbeck U.,Rabkin E.,Schoen F. J.,Poole A. R.,Billinghurst R. C.,Libby P.. (Year: 1999) Evidence for increased collagenolysis by interstitial collagenases-1 and -3 in vulnerable human atheromatous plaques. Circulation99, 2503–250910330380
45.. Mao D.,VanVickle S. J.,Curci J. A.,Thompson R. W.. (Year: 1999) Expression of matrix metalloproteinases and TIMPs in human abdominal aortic aneurysms. Ann. Vasc. Surg. 13, 236–23710072471
46.. Liu H.,Sadygov R. G.,Yates J. R. 3rd. (Year: 2004) A model for random sampling and estimation of relative protein abundance in shotgun proteomics. Anal. Chem. 76, 4193–420115253663
47.. Zybailov B.,Coleman M. K.,Florens L.,Washburn M. P.. (Year: 2005) Correlation of relative abundance ratios derived from peptide ion chromatograms and spectrum counting for quantitative proteomic analysis using stable isotope labeling. Anal. Chem. 77, 6218–622416194081
48.. Simper D.,Mayr U.,Urbich C.,Zampetaki A.,Prokopi M.,Didangelos A.,Saje A.,Mueller M.,Benbow U.,Newby A. C.,Apweiler R.,Rahman S.,Dimmeler S.,Xu Q.,Mayr M.. (Year: 2010) Comparative proteomics profiling reveals role of smooth muscle progenitors in extracellular matrix production. Arterioscler. Thromb. Vasc. Biol. 30, 1325–133220431068


[Figure ID: F1]
Fig. 1. 

Characterization of clinical specimens. Representative sections of AAA (A) and control aortas (B) were stained with hematoxylin & eosin as well as antibodies against the monocyte/macrophage marker CD68 (C). Immunoreactivity appears in brown and nuclei are counterstained with Mayer's hematoxylin. Scale bar, 5x: 100 μm and 20x: 25 μm. D, In the cellular extracts (0.08% SDS) of AAA, smooth muscle actin (SMA) was inversely correlated to CD68.

[Figure ID: F2]
Fig. 2. 

Proteomics workflow. The methodology is based on a three-step subfractionation of the vascular proteome (A), which enriches ECM, its associated proteins and degradation products. First, specimens are extracted in 0.5 M NaCl. This buffer solubilizes proteins or protein fragments that are weakly bound to the ECM, including newly synthesized ECM proteins and degradation products. In addition, secreted proteinases such as MMPs are also extracted. Second, specimens are decellularized with 0.08% SDS to deplete cellular proteins. Finally, the salt-insoluble ECM proteins are extracted using 4 M guanidine to solubilize the tightly interacting, cross-linked matrix. In the second stage (B), the identified MMPs are further investigated by incubating healthy tissue with recombinant enzymes to identify novel proteolytic targets and characterize their proteolytic activity in disease.

[Figure ID: F3]
Fig. 3. 

Differential solubility of extracellular proteins.A, The Venn diagram displays the number of ECM and associated proteins extracted with either 0.5 M NaCl or 4 M guanidine. The SwissProt entry codes of uniquely identified proteins are given for each extract. All identifications are listed in Tables I and II. B, In the 0.5 M NaCl extracts the spectral counts for ECM proteins were significantly increased in the AAA samples in comparison to control aortas (CON). The total number of identified spectra was similar. C, In the 4 M guanidine extracts neither the spectral counts for ECM proteins nor the total number of spectra were significantly different between controls and AAA. Values are mean ± S.E. *** p0.001. Statistical analysis was performed using 2-tailed, unpaired t test.

[Figure ID: F4]
Fig. 4. 

Hierarchical clustering of extracellular proteins. The dendrograms display hierarchical clustering analysis (Pearson correlation coefficient) of the differentially expressed extracellular proteins in the 0.5 M NaCl extracts (A) and in the 4 M guanidine extracts (B). “R” denotes the technical replicate obtained for each clinical sample using the RePlay device. Differences in spectral counts are color-coded as indicated.

[Figure ID: F5]
Fig. 5. 

Validation of ECM remodeling markers. The spectral counts (left panels) for collagen XII, tenascin, thrombospondin 2, fibronectin and ACLP (alternative name: adipocyte enchancer-binding protein 1; AEBP-1) were significantly higher in the 0.5 M NaCl extracts of AAA compared with controls. Values are mean ± S.E. *** p0.001, ** p0.01, ** p0.05, ns not significant. Statistical analysis was performed using two-tailed, unpaired t test. Immunoblotting (middle panels) confirmed increased levels as well as fragmentation of these ECM proteins in AAA. The loss of eSOD and the accumulation of MMP-12 and TIMP-1 in AAA were also validated by immunoblotting. Arrows indicate the expected molecular mass of full-length proteins. With the exception of periostin and MMP-12, there was a high correlation (Spearman correlation r0.8, p0.05) in protein abundance determined by spectral counting and Western blotting (right panels).

[Figure ID: F6]
Fig. 6. 

Novel MMP-12 targets.A, The color-coded heat map demonstrates the number of identified spectra for the 6 glycoproteins in the 0. 5 M NaCl extracts in control and AAA samples and their molecular weight distribution after SDS-PAGE. B, A normal aortic specimen was dissected into three equal blocks and treated with either 50 pM MMP-9, 50 pM MMP-12, or left untreated (CON) in MMP reaction buffer for 24 h at 37 °C. The resulting supernatants were analyzed by immunoblotting for collagen XII, tenascin, thrombospondin 2 (TSP2), fibronectin, ACLP, and periostin. Arrows indicate proteolytic fragments generated by MMP-12 treatment. C, 10 μg human purified fibronectin and 10 μg human recombinant periostin and TSP2 were incubated for 16h at 37 °C either in plain MMP reaction buffer or supplemented with 50 pM MMP-12 (+MMP-12). The protein mixtures were separated by one-dimensional SDS-PAGE and stained in a 0.05% w/v Coomasie G-250, 5% v/v glacial acetic acid solution to monitor substrate degradation.

[Figure ID: F7]
Fig. 7. 

Immunohistochemical staining for ACLP and MMP-12. Consecutive serial sections of AAA tissue were stained with antibodies to ACLP (A and B) or MMP-12 (C and D). ACLP was found in both the hypocellular areas with the remaining elastic laminae (A) and in the amorphous, inflammatory regions of the media with evidence of connective tissue destruction (B). MMP-12 was predominantly found in the inflammatory regions (D). Positive immunostaining is indicated by brown color obtained with diaminobenzidine (DAB) development of horseradish peroxidase-conjugated secondary antibodies. Negative controls were incubated with isotype control antibodies (E and F). Nuclei were counterstained with Mayer's hematoxylin. 20X magnification. Scale bar: 25 μm.

[TableWrap ID: TI] Table I  Extracellular matrix and associated proteins identified by proteomics in the 0.5 M NaCl extracts. aThree biological samples performed with two technical replicates each (n = 6). bFour biological samples performed with two technical replicates each (n = 8). cIndicates proteins identified for the first time by proteomics in the vasculature. ND: none detected
Protein name Swiss Prot Accession MW (kDa) Mean spectra±S.E. CONa Mean spectra±S.E. AAAb p value (t-test)
Proteoglycans and glycoproteins
    Thrombospondin-1 TSP1_HUMAN 129 8 ± 0 238 ± 13 0.0004
    Fibronectin FINC_HUMAN 263 26 ± 2 144 ± 4 ≥0.0001
    Lumican LUM_HUMAN 38 55 ± 1 67 ± 1 0.1000
    Aortic carboxypeptidase-like protein AEBP1_HUMAN 131 38 ± 1 53 ± 1 0.0500
    EGF-containing fibulin-like ECM protein 1 FBLN3_HUMAN 55 34 ± 1 50 ± 3 0.1200
    Tenascin-X TENX_HUMAN 464 47 ± 3 32 ± 1 0.1200
    Versican CSPG2_HUMAN 373 20 ± 1 20 ± 1 0.7600
    Tenascin TENA_HUMAN 241 1 ± 0 24 ± 1 0.0004
    Mimecan MIME_HUMAN 34 19 ± 0 10 ± 0 0.0001
    Perlecan PGBM_HUMAN 469 14 ± 3 8 ± 2 0.0840
    Thrombospondin-2 TSP2_HUMAN 130 ND 19 ± 1 0.0003
    Fibulin-1 FBLN1_HUMAN 77 9 ± 0 11 ± 0 0.4800
    Fibrillin-1 FBN1_HUMAN 312 5 ± 0 11 ± 2 0.4600
    Vitronectin VTNC_HUMAN 54 ND 15 ± 1 0.0034
    Fibromodulin FMOD_HUMAN 43 9 ± 1 7 ± 0 0.2300
    Decorin PGS2_HUMAN 40 2 ± 0 5 ± 0 0.0066
    Galectin-1 LEG1_HUMAN 15 5 ± 0 6 ± 0 0.3800
    TGFβ-induced protein ig-h3 BGH3_HUMAN 75 ND 5 ± 0 0.0019
    Podocan PODN_HUMAN 69 3 ± 0 2 ± 0 0.1700
    Cartilage oligomeric matrix protein COMP_HUMAN 83 1 ± 0 3 ± 0 0.2500
    Biglycan PGS1_HUMAN 42 1 ± 0 2 ± 0 0.1600
    Fibulin-5 FBLN5_HUMAN 50 3 ± 0 1 ± 0 0.0620
    Aggrecan PGCA_HUMAN 250 2 ± 0 1 ± 0 0.0580
    Lactadherin MFGM_HUMAN 43 1 ± 0 2 ± 0 0.8300
    Galectin-3 LEG3_HUMAN 26 ND 2 ± 0 0.2500
    Microfibril-associated glycoprotein 4 MFAP4_HUMAN 29 2 ± 0 1 ± 0 0.4600
    Periostin POSTN_HUMAN 93 ND 2 ± 0 0.2300
    Adlicanc MXRA5_HUMAN 312 ND 1 ± 0 0.0600
    Laminin subunit alpha-5 LAMA5_HUMAN 400 1 ± 0 1 ± 0 0.7100
    Spondin-1 SPON1_HUMAN 91 2 ± 0 ND 0.0390
    Nidogen-1 NID1_HUMAN 136 1 ± 0 1 ± 0 0.4100
    Dermatopontin DERM_HUMAN 24 1 ± 0 1 ± 0 0.6300
ECM-associated proteins
    Extracellular superoxide dismutase SODE_HUMAN 26 60 ± 3 19 ± 2 0.0011
    Serum amyloid P-component SAMP_HUMAN 25 14 ± 0 38 ± 2 0.0190
    Pigment epithelium-derived factor PEDF_HUMAN 46 17 ± 0 29 ± 0 0.0003
    Apolipoprotein A-I APOA1_HUMAN 31 7 ± 1 30 ± 1 0.0006
    Myeloperoxidase PERM_HUMAN 84 2 ± 0 25 ± 2 0.0045
    Latent-transforming growth factor beta-binding protein 2 LTBP2_HUMAN 195 9 ± 1 12 ± 1 0.1500
    Apolipoprotein E APOE_HUMAN 36 3 ± 0 17 ± 1 0.0230
    Tetranectin TETN_HUMAN 23 10 ± 0 12 ± 0 0.3500
    Procollagen C-endopeptidase enhancer 1 PCOC1_HUMAN 48 8 ± 0 12 ± 1 0.1500
    Cathepsin D CATD_HUMAN 45 5 ± 0 9 ± 1 0.4200
    Ceruloplasmin CERU_HUMAN 122 2 ± 0 12 ± 1 0.0018
    Tryptase beta-1 TRYB1_HUMAN 31 7 ± 1 7 ± 1 0.8600
    Clusterin CLUS_HUMAN 52 2 ± 0 12 ± 1 0.0003
    Insulin-like growth factor-binding protein 7 IBP7_HUMAN 29 11 ± 0 4 ± 0 0.0004
    Apolipoprotein D APOD_HUMAN 21 2 ± 0 9 ± 1 0.0270
    Protein S100-A8c S10A8_HUMAN 11 1 ± 0 9 ± 1 0.0110
    Secreted frizzled-related protein 3 SFRP3_HUMAN 36 6 ± 0 3 ± 0 0.1800
    Calreticulin CALR_HUMAN 48 5 ± 0 5 ± 0 0.9300
    Protein S100-A9c S10A9_HUMAN 13 ND 6 ± 1 0.0300
    Apolipoprotein A-IV APOA4_HUMAN 45 4 ± 0 4 ± 0 0.8900
    Metalloproteinase inhibitor 1 TIMP1_HUMAN 23 1 ± 0 4 ± 0 0.0019
    Latent-TGFβ-binding protein, isoform 1S LTB1S_HUMAN 153 2 ± 0 3 ± 0 0.4800
    Cathepsin G CATG_HUMAN 29 1 ± 0 2 ± 0 0.6500
    Apolipoprotein B-100 APOB_HUMAN 516 1 ± 0 3 ± 0 0.0220
    Leukocyte elastase inhibitor ILEU_HUMAN 43 2 ± 0 2 ± 0 0.7900
    Target of Nesh-SH3 TARSH_HUMAN 119 2 ± 0 3 ± 0 0.4100
    Carboxypeptidase-like protein X2 CPXM2_HUMAN 86 2 ± 0 1 ± 0 0.9700
    Hepatoma-derived growth factor HDGF_HUMAN 27 2 ± 0 1 ± 0 0.0590
    Macrophage metalloelastasec MMP12_HUMAN 54 ND 3 ± 0 0.0500
    Cathepsin Z CATZ_HUMAN 34 3 ± 0 1 ± 0 0.0250
    Proactivator polypeptide SAP_HUMAN 58 3 ± 0 ND 0.0067
    Latent-TGFβ-binding protein 4 LTBP4_HUMAN 173 2 ± 0 ND 0.0600
    Secreted frizzled-related protein 1 SFRP1_HUMAN 35 2 ± 0 ND 0.0830
    Cathepsin S CATS_HUMAN 37 ND 1 ± 0 0.2300
    72 type IV collagenase MMP2_HUMAN 74 1 ± 0 ND 0.1300
    Glia-derived nexin GDN_HUMAN 44 ND 1 ± 0 0.2900
    Chymase CMA1_HUMAN 27 ND 1 ± 0 0.3000
    Eosinophil cationic proteinc ECP_HUMAN 18 ND 1 ± 0 0.5300
    Collagen alpha-1(XIV) COEA1_HUMAN 194 71 ± 1 50 ± 2 0.0009
    Collagen alpha-1(XII) COCA1_HUMAN 333 13 ± 1 81 ± 5 0.0014
    Collagen alpha-3(VI) CO6A3_HUMAN 344 13 ± 1 36 ± 3 0.0430
    Collagen alpha-1(VI) CO6A1_HUMAN 109 4 ± 0 8 ± 1 0.2000
    Collagen alpha-1(XVIII) COIA1_HUMAN 178 5 ± 0 7 ± 0 0.1700
    Collagen alpha-2(VI) CO6A2_HUMAN 109 2 ± 0 3 ± 0 0.6100
    Collagen alpha-1(I) CO1A1_HUMAN 139 1 ± 0 3 ± 0 0.1900
    Collagen alpha-1(XV) COFA1_HUMAN 142 2 ± 0 3 ± 0 0.5600
    Collagen alpha-2(I) CO1A2_HUMAN 129 1 ± 0 3 ± 0 0.0130
    Collagen alpha-1(III) CO3A1_HUMAN 139 ND 1 ± 0 0.3900

[TableWrap ID: TII] Table II  Extracellular matrix and associated proteins identified by proteomics in the 4 M guanidine extracts. aThree biological samples performed with two technical replicates each (n = 6). bFour biological samples performed with two technical replicates each (n = 8). cIndicates proteins identified for the first time by proteomics in the vasculature. ND: none detected
Protein name Swiss Prot Accession MW (kDa) Mean spectra±S.E. CONa Mean spectra±S.E. AAAb p value (t-test)
Proteoglycans and glycoproteins
    Fibronectin FINC_HUMAN 263 210 ± 15 336 ± 16 ≥0.0001
    Perlecan PGBM_HUMAN 469 323 ± 13 176 ± 43 0.0280
    Versican CSPG2_HUMAN 373 190 ± 5 84 ± 18 0.0010
    Aggrecan PGCA_HUMAN 250 154 ± 23 28 ± 11 0.0003
    Prolargin PRELP_HUMAN 44 76 ± 8 86 ± 8 0.3100
    Tenascin TENA_HUMAN 241 11 ± 1 144 ± 21 ≥0.0001
    Biglycan PGS1_HUMAN 42 74 ± 4 78 ± 10 0.4400
    Vitronectin VTNC_HUMAN 54 26 ± 2 117 ± 12 ≥0.0001
    Decorin PGS2_HUMAN 40 35 ± 7 70 ± 14 0.0430
    Clusterin CLUS_HUMAN 52 34 ± 2 69 ± 7 ≥0.0001
    Periostin POSTN_HUMAN 93 56 ± 6 47 ± 6 0.6400
    Lactadherin MFGM_HUMAN 43 60 ± 12 39 ± 11 0.2400
    Lumican LUM_HUMAN 38 41 ± 2 51 ± 6 0.1400
    Thrombospondin-1 TSP1_HUMAN 129 2 ± 1 90 ± 12 ≥0.0001
    Tenascin-X TENX_HUMAN 464 31 ± 1 39 ± 10 0.3600
    Nidogen-1 NID1_HUMAN 136 29 ± 4 24 ± 7 0.6700
    Aortic carboxypeptidase-like protein AEBP1_HUMAN 131 21 ± 2 28 ± 6 0.2900
    Laminin subunit gamma 1 LAMC1_HUMAN 178 26 ± 6 16 ± 6 0.3300
    Mimecan MIME_HUMAN 34 15 ± 2 23 ± 8 0.3200
    Laminin subunit beta 2 LAMB2_HUMAN 196 23 ± 4 12 ± 4 0.0960
    Dermatopontin DERM_HUMAN 24 17 ± 5 16 ± 3 0.8100
    Annexin A2 ANXA2_HUMAN 39 13 ± 2 19 ± 5 0.2600
    Hyaluronan and proteoglycan link protein 1 HPLN1_HUMAN 40 25 ± 9 6 ± 2 0.0510
    Fibrillin-1 FBN1_HUMAN 312 4 ± 1 26 ± 4 ≥0.0001
    Laminin subunit alpha 5 LAMA5_HUMAN 400 19 ± 4 6 ± 2 0.0060
    Fibulin-5 FBLN5_HUMAN 50 14 ± 3 3 ± 1 0.0110
    Metalloproteinase inhibitor 3 TIMP3_HUMAN 24 3 ± 1 14 ± 3 0.0067
    Galectin-1 LEG1_HUMAN 15 9 ± 3 8 ± 2 0.9900
    Asporin ASPN_HUMAN 43 2 ± 1 12 ± 5 0.0800
    EMILIN-1 EMIL1_HUMAN 107 8 ± 3 3 ± 1 0.1700
    Microfibril-associated glycoprotein 4 MFAP4_HUMAN 29 9 ± 2 2 ± 1 0.0120
    Nidogen-2 NID2_HUMAN 151 2 ± 0 7 ± 3 0.0630
    Fibromodulin FMOD_HUMAN 43 5 ± 2 3 ± 0 0.3700
    Fibulin-1 FBLN1_HUMAN 77 6 ± 2 1 ± 0 0.0110
    Agrin AGRIN_HUMAN 215 4 ± 2 3 ± 1 0.5700
    Thrombospondin-2 TSP2_HUMAN 130 ND 7 ± 1 ≥0.0001
    Microfibrillar-associated protein 5 MFAP5_HUMAN 20 3 ± 1 3 ± 1 0.5400
    Glia-derived nexin GDN_HUMAN 44 ND 4 ± 1 0.0014
    Laminin subunit beta 1 LAMB1_HUMAN 198 ND 4 ± 1 0.0110
    RPE-spondin RPESP_HUMAN 30 4 ± 2 1 ± 1 0.0330
    Podocan PODN_HUMAN 69 ND 3 ± 1 0.0700
    Matrix Gla proteinc MGP_HUMAN 12 1 ± 0 1 ± 1 0.7500
    Sclerostin SOST_HUMAN 24 1 ± 0 ND 0.1800
    SPARC-like protein 1c SPRL1_HUMAN 75 1 ± 1 ND 0.1100
    Cartilage oligomeric matrix protein COMP_HUMAN 83 1 ± 1 ND 0.0930
    Matrilin-2 MATN2_HUMAN 107 1 ± 0 1 ± 1 0.7900
    Galectin-3 LEG3_HUMAN 26 1 ± 1 ND 0.2700
    Spondin-1 SPON1_HUMAN 91 1 ± 1 ND 0.1300
    Cartilage acidic protein 1c CRAC1_HUMAN 71 ND 1 ± 1 0.2100
    SPARC-related modular calcium-binding protein 2 SMOC2_HUMAN 50 1 ± 0 ND 0.3200
    Fibronectin type III domain-containing protein 1 FNDC1_HUMAN 205 1 ± 0 ND 0.2300
    Laminin subunit alpha 4 LAMA4_HUMAN 203 1 ± 0 ND 0.3000
    Hemicentin-1 HMCN1_HUMAN 613 ND 1 ± 0 0.4100
ECM-associated proteins
    Serum amyloid P component SAMP_HUMAN 25 39 ± 6 91 ± 20 0.0220
    Apolipoprotein B-100 APOB_HUMAN 516 ND 96 ± 34 0.0470
    Apolipoprotein A-I APOA1_HUMAN 31 ND 50 ± 16 0.0230
    Serine protease HTRA1 HTRA1_HUMAN 51 16 ± 4 19 ± 7 0.7600
    TGF-beta induced protein ig-h3 BGH3_HUMAN 75 8 ± 3 27 ± 4 ≥0.0001
    Insulin-like growth factor-binding protein 7 IBP7_HUMAN 29 20 ± 2 9 ± 3 0.0430
    EGF-containing fibulin-like extracellular matrix protein 1 FBLN3_HUMAN 55 13 ± 2 12 ± 5 0.9900
    Cathepsin D CATD_HUMAN 22 8 ± 2 14 ± 4 0.1090
    Extracellular superoxide dismutase SODE_HUMAN 26 18 ± 3 5 ± 2 0.0020
    Target of Nesh-SH3 TARSH_HUMAN 119 20 ± 4 3 ± 1 0.0002
    Metalloproteinase inhibitor 3 TIMP3_HUMAN 24 3 ± 1 14 ± 3 0.0067
    Apolipoprotein E APOE_HUMAN 36 ND 15 ± 4 0.0180
    Macrophage metalloelastasec MMP12_HUMAN 54 ND 15 ± 3 0.0033
    Apolipoprotein D APOD_HUMAN 21 ND 13 ± 2 0.0035
    Latent-transforming growth factor beta-binding protein 2 LTBP2_HUMAN 195 9 ± 2 4 ± 1 0.0570
    Latent-TGF-beta binding protein, isoform 1S LTB1S_HUMAN 153 8 ± 2 4 ± 2 0.3000
    Ceruloplasmin CERU_HUMAN 122 ND 12 ± 5 0.0650
    Transforming growth factor beta-1-induced transcript 1 protein TGFI1_HUMAN 50 10 ± 2 1 ± 1 0.0003
    Cathepsin G CATG_HUMAN 29 3 ± 2 7 ± 2 0.0450
    Chymase CMA1_HUMAN 27 7 ± 1 3 ± 2 0.2700
    Myeloperoxidase PERM_HUMAN 84 ND 10 ± 3 0.0210
    Neutrophil defensin 1 DEF1_HUMAN 10 1 ± 1 9 ± 1 0.0003
    LIM and cysteine-rich domains protein 1 LMCD1_HUMAN 41 9 ± 2 ND 0.0067
    Lysyl oxidase homolog 1 LOXL1_HUMAN 63 5 ± 2 3 ± 1 0.2900
    Galectin-3-binding protein LG3BP_HUMAN 65 6 ± 3 2 ± 0 0.1000
    Tryptase beta-1 TRYB1_HUMAN 31 4 ± 1 3 ± 2 0.9900
    Metalloproteinase inhibitor-3 TIMP1_HUMAN 23 ND 6 ± 2 0.0270
    Pigment epithelium-derived factor PEDF_HUMAN 46 2 ± 1 3 ± 1 0.6100
    Carboxypeptidase-like protein X2 CPXM2_HUMAN 86 4 ± 2 ND 0.1600
    Apolipoprotein A-IV APOA4_HUMAN 45 ND 4 ± 3 0.1900
    Phospholipase A2, membrane associated PA2GA_HUMAN 16 2 ± 1 2 ± 1 0.9300
    Apolipoprotein L1 APOL1_HUMAN 44 ND 4 ± 2 0.1900
    Protein S100-A9c S10A9_HUMAN 13 ND 4 ± 1 0.0290
    Latent-transforming growth factor beta-binding protein 4 LTBP4_HUMAN 173 3 ± 1 ND 0.0550
    Procollagen C-endopeptidase enhancer 1 PCOC1_HUMAN 48 2 ± 1 ND 0.1700
    Kallistatin KAIN_HUMAN 49 ND 2 ± 2 0.3300
    Properdin PROP_HUMAN 51 1 ± 1 1 ± 0 0.7500
    Calreticulin CALR_HUMAN 48 1 ± 1 1 ± 0 0.2900
    Antileukoproteinase SLPI_HUMAN 14 1 ± 0 ND 0.0980
    Cathepsin Z CATZ_HUMAN 34 1 ± 1 ND 0.4800
    Secreted frizzled-related protein 1 SFRP1_HUMAN 35 2 ± 1 ND 0.1200
    SPARC-like protein 1 SPRL1_HUMAN 75 1 ± 1 ND 0.1100
    Protein S100-A8c S10A8_HUMAN 11 1 ± 0 1 ± 0 0.4200
    Secreted frizzled-related protein 3 SFRP3_HUMAN 36 1 ± 1 ND 0.1400
    C-type lectin domain family 11 member Ac CLC11_HUMAN 36 1 ± 0 1 ± 0 0.9500
    Lipocalin 1c LCN1_HUMAN 19 ND 1 ± 0 0.1800
    Secreted phosphoprotein 24 SPP24_HUMAN 24 ND 1 ± 1 0.1600
    EGF-like repeat and discoidin I-like domain-
        containing protein 3 EDIL3_HUMAN 54 ND 1 ± 1 0.2400
    Insulin-like growth-factor binding protein complex acid labilec ALS_HUMAN 66 ND 1 ± 0 0.2900
    Collagen alpha 3(VI) CO6A3_HUMAN 344 194 ± 35 343 ± 37 0.0025
    Collagen alpha 1(VI) CO6A1_HUMAN 109 74 ± 10 95 ± 16 0.1100
    Collagen alpha 1(XIV) COEA1_HUMAN 194 112 ± 17 40 ± 9 0.0005
    Collagen alpha 1(XVIII) COIA1_HUMAN 178 69 ± 6 13 ± 4 ≥0.0001
    Collagen alpha 1(I) CO1A1_HUMAN 139 36 ± 5 41 ± 2 0.0580
    Collagen alpha 1(XII) COCA1_HUMAN 333 17 ± 3 60 ± 10 0.0006
    Collagen alpha 2(VI) CO6A2_HUMAN 109 35 ± 6 40 ± 7 0.2400
    Collagen alpha 2(I) CO1A2_HUMAN 129 34 ± 2 36 ± 2 0.0580
    Collagen alpha 2(IV) CO4A2_HUMAN 168 37 ± 6 31 ± 12 0.7700
    Collagen alpha 1(XV) COFA1_HUMAN 142 24 ± 6 17 ± 5 0.4300
    Collagen alpha 1(V) CO5A1_HUMAN 184 8 ± 1 11 ± 2 0.0300
    Collagen alpha 1(VIII) CO8A1_HUMAN 73 7 ± 2 9 ± 3 0.6200
    Collagen alpha 2(VIII) CO8A2_HUMAN 67 2 ± 1 3 ± 1 0.3100
    Collagen alpha 1(IV) CO4A1_HUMAN 161 1 ± 1 2 ± 1 0.4700
    Collagen alpha 1(XXI) COLA1_HUMAN 99 1 ± 0 2 ± 1 0.2100
    Collagen alpha 2(V) CO5A2_HUMAN 145 ND 1 ± 0 0.0820

Article Categories:
  • Research

Previous Document:  CDK-dependent phosphorylation of Mob2 is essential for hyphal development in Candida albicans.
Next Document:  Proteomic analysis of schistosoma japonicum schistosomulum proteins that are differentially expresse...