Unraveling Biomarkers of Abdominal Aortic Aneurisms by iTRAQ Analysis of Depleted Plasma

  • Enrique Calvo
  • Roxana Martínez-Pinna
  • Priscila Ramos-Mozo
  • C. Pastor-Vargas
  • Emilio Camafeita
  • Jesús Egido
  • José Luis Martin-Ventura
  • Juan Antonio Lopez
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1000)

Abstract

Abdominal aortic aneurysm (AAA) is a significant health problem in Western countries. The diameter of AAA is a surrogate marker of its growth rate that reflects the magnitude of the degenerative process in the vascular wall, although most AAAs show discontinuous growth patterns and alternate periods of stability and nongrowth with periods of acute expansion and occasionally ruptures. Thus, the identification of biomarkers of AAA in plasma could aid in the diagnosis, prognosis, and therapy of AAA progression. However, owing to the complex composition of plasma, depletion methods must be applied before the analytical approaches for detecting low-abundant plasma protein components. In the present work, we describe a proteomic study on MARS 14-depleted plasma based on mass spectrometry (MS) which combines peptide labelling (isobaric tagging for relative and absolute quantification, iTRAQ) and liquid chromatography–tandem mass spectrometry (LC–MS/MS). This quantitative approach revealed altered levels of several proteins related to the complement system in AAA patients.

Key words

Abdominal aortic aneurysm iTRAQ Mass spectrometry Proteomics Depleted plasma Biomarkers 

1 Introduction

High-throughput “omics” in systems biology approaches will ­ameliorate both prediction and treatment of patients on the way to the era of individualized medicine (1–3). Human plasma is the most clinically valuable specimen because it is routinely sampled with minimal invasiveness and constitutes a rich source of proteins since it is in contact with all tissues in the body. Plasma proteomics has gained much attention in the last years, despite the high complexity of the human plasma-derived proteome. Plasma samples display an extremely wide concentration range of protein components in which a set of high-abundance proteins often hinder the detection of ­low-abundance proteins with much higher biological relevance. Therefore, the initial step in most analytical approaches applied to serum or plasma is to deplete as many high-abundance proteins as possible (4). These methods facilitate plasma analysis mainly by reducing the dynamic range of protein concentration or by enriching for potentially interesting subgroups of proteins (5). Prefractionation methods can be carried out either at the protein or the peptide level, or at both. At the protein level, immunoaffinity capture using antibodies against the most abundant proteins, such as albumin or globulins, is the most popular depletion method (6). One of these systems is the Multiple Affinity Removal System (MARS) from Agilent Technologies, which offers reproducibility and sensitivity levels adequate for quantitative candidate biomarker discovery. In the present study, we described the analysis of depleted plasma from AAA patients in a nontargeted, quantitative analytical approach based on iTRAQ labelling, coupled to nLC–MS/MS (7). The depletion of the 14 most abundant proteins present in human plasma using MARS14, combined with the aforementioned MS-based strategy, enabled the reliable identification of a large number of proteins in patient and control plasma samples, while only a few peptides from proteins previously depleted by affinity chromatography were found. Quantitative data evidenced the overexpression of several proteins related to the complement system in plasma samples from patients in early disease stage, which suggests a potential role of complement proteins in the evolution of AAA.

2 Materials

All reagents are purchased from Sigma-Aldrich, unless noted otherwise, and are prepared with ultrapure water (Millipore). For HPLC and MS, all the solvents used are MS grade.

2.1 Plasma Depletion and Quantitation

  1. 1.

    Spin-X Centrifuge 0.45 μm filters.

     
  2. 2.

    MARS 14 High-Abundant Protein Depletion Column (or similar depletion kit): HPLC MARS Buffer A (Buffer A is a salt-containing neutral buffer, pH 7.4, used for loading, washing, and re-equilibrating the column). HPLC MARS Buffer B (Buffer B is a low-pH urea buffer used for eluting the bound high-abundant proteins from the column), all from Agilent Technologies.

     
  3. 3.

    RC-DC Protein Assay Kit (Bio-Rad).

     

2.2 Trypsin Digestion and iTRAQ Labelling

  1. 1.

    iTRAQ Reagent Kit, 4-plex (Applied Biosystems), which ­contains dissolution buffer, 500 mM triethylammonium ­bicarbonate (TEAB, pH 8.5), Denaturant solution, which contains 2 % (w/v) SDS, Reducing agent, 50 mM ­Tris-(2-carboxyethyl)phosphine (TCEP), Cysteine-blocking reagent, 200 mM methyl methanethiosulfonate (MMTS) in isopropanol. Single iTRAQ reagents (114–117).

     
  2. 2.

    Trypsin (Sequence Grade Modified Trypsin, Promega).

     

2.3 LC–MS/MS Analysis

  1. 1.

    Pre-column for peptide online desalting: C-18 reversed-phase (RP) micro-column (300 mm ID  ×  5 mm PepMap™) (LC Packings).

     
  2. 2.

    Analytical RP column: self-packed 15-cm-long C18, 100 μm ID column (Mediterranean sea, Teknokroma).

     
  3. 3.

    Picotip emitter, 15 mm tip (New Objective).

     
  4. 4.

    HPLC Buffer A: 0.5 % (v/v) acetic acid in water.

     
  5. 5.

    HPLC Buffer B: 0.5 % (v/v) acetic acid in 90 % (v/v) acetonitrile.

     
  6. 6.

    Software for analysis and quantitation: Proteome Discoverer (Thermo Fisher Scientific), Mascot (Matrix Science), and Scaffold (Proteome Software).

     

2.4 Specialized Equipment

  1. 1.

    Agilent HPLC or similar.

     
  2. 2.

    Lyophilizer.

     
  3. 3.

    Ultimate 3000 nano-HPLC System (or equivalent) (Dionex Corporation).

     
  4. 4.

    LTQ-Orbitrap XL hybrid Linear Ion Trap Mass Spectrometer (or equivalent) (Thermo Fisher Scientific).

     

3 Methods

A schedule of the general procedures and multitagging experimental design is shown on Fig. 1.
Fig. 1

Schematic of multitagging experimental strategy used in the analysis. (a) Plasma samples from six patients (small, three patients with small aaa; large, three patients with large AAA) and three control subjects (CT) were depleted using a MARS 14 column. Flow-through fractions containing low-abundant proteins were trypsin digested; the resulting peptides were labelled using 114–117 iTRAQ tags and, finally, analyzed by nLC–MS/MS in a LTQ Orbitrap XL mass spectrometer. (b) A fragmentation spectrum of a representative peptide from complement protein 4B with sequence assignment is shown; a detailed inspection of the iTRAQ reporter ion profiles in the low m/z region for protein quantification is also shown

3.1 Plasma

  1. 1.

    Collect, into EDTA tubes, three blood samples of each two groups of AAA patients: small (aaa, diameter  =  3–5 cm) and large (AAA, diameter  >  5 cm), and three healthy age- and sex-matched controls (seeNote1).

     
  2. 2.

    Store blood samples vertically at 4 °C for 30 min, and centrifuge blood at 3,000  ×  g for 20 min at 4 °C.

     
  3. 3.

    Store plasma samples aliquots at −80 °C for further analysis (seeNote2).

     

3.2 High-Abundant Protein Depletion from Plasma

  1. 1.

    Deplete plasma samples at room temperature with an Agilent 1100 HPLC system using a 10  ×  100 mm MARS14 column according to the manufacturer’s instructions (seeNote3).

     
  2. 2.

    Attach the MARS column and equilibrate for 4 min, with 4 mL of HPLC MARS Buffer A at a flow rate of 1 mL/min (seeNote4).

     
  3. 3.

    Dilute 200 μL of human plasma with 600 μL of HPLC MARS Buffer A (seeNote5).

     
  4. 4.

    Centrifuge diluted plasma through a Spin-X Centrifuge 0.45 μm filter, 1 min at 16,000  ×  g to remove particulates.

     
  5. 5.

    Inject the diluted sample using a flow rate of 0.5–1 mL/min (seeNote6).

     
  6. 6.

    Collect the flow-through fraction in the 10.5–14.5 min retention time range. This corresponds to the low-abundant protein fraction.

     
  7. 7.

    Dialyse the flow-through fractions (four fractions per sample) with ammonium bicarbonate to exchange buffer and then lyophilize them. Store at −80 °C for later analysis (seeNote7).

     
  8. 8.

    Elute bound proteins by adding HPLC MARS Buffer B at a flow rate of 3 mL/min during 7.5 min.

     
  9. 9.

    Regenerate column using HPLC MARS Buffer A at a flow rate of 3 mL/min for 10 min and store column with Buffer A at 2–8 °C.

     
  10. 10.

    Resuspend lyophilized fractions in TEAB Buffer.

     
  11. 11.

    Determine protein concentration by RC-DC protein assay, using bovine albumin diluted in TEAB Buffer to prepare the standard curve (seeNote8).

     

3.3 Trypsin Digestion

  1. 1.

    Pipette 50 μg of proteins from the four samples into four separate tubes (seeNote9). Make up to 19 μL with TEAB.

     
  2. 2.

    Add 1 μL of the Denaturant solution (final 0.1 % SDS) to each tube. Mix by vortexing and spin down briefly to collect the sample to the bottom of the tube (seeNote10).

     
  3. 3.

    Add 2 μL of Reducing reagent and vortex. Incubate at 60 °C for 1 h.

     
  4. 4.

    Add 1 μL of the Cysteine-blocking reagent. Incubate at room temperature for 30 min in the dark.

     
  5. 5.

    Reconstitute one vial of trypsin (20 μg) with 45 μL of MS-grade water. Mix briefly avoiding formation of foam.

     
  6. 6.

    Add 10 μL of the trypsin solution (1:10 enzyme-to-protein ratio) and vortex. Incubate overnight at 37 °C (seeNote11).

     
  7. 7.

    Transfer the resulting digestion solutions to small RT-PCR tubes and keep at 4 °C for iTRAQ labelling, or store at −80 °C.

     

3.4 iTRAQ Labelling

  1. 1.

    Take the iTRAQ reagents to room temperature. Add 70 μL of ethanol into each reagent vial, cap the vial, and vortex vigorously, and then centrifuge briefly to settle the iTRAQ reagents at the vial bottom.

     
  2. 2.

    Transfer the contents of each vial to the appropriate sample tube and mix well. For example, peptides derived from two control samples are labelled with iTRAQ Reagents 114 and 115, whereas peptides obtained from AAA and aaa patient samples are labelled with iTRAQ Reagents 116 and 117, respectively (seeNote12).

     
  3. 3.

    Transfer the entire content of one iTRAQ reagent vial to each of the four sample tubes and mix (seeNote13).

     
  4. 4.

    Incubate the reaction vials at room temperature for 2 h.

     
  5. 5.

    Analyze a small fraction of each reaction to check labelling efficiency (seeNote14).

     
  6. 6.

    If the labelling is complete, stop reaction with 3 μL glacial acetic acid and combine labelled samples. Concentrate samples in the Speedvac to remove solvent (seeNote15).

     

3.5 Reversed-Phase Liquid Chromatography

Use a reversed-phase cartridge for desalting the peptides and removing excess iTRAQ reagent. Then analyze the peptides by nano-electrospray ionization after separation by nano-HPLC.
  1. 1.

    Redissolve peptides in HPLC Buffer A and remove particulate material by centrifugation (10 min at 15,000  ×  g).

     
  2. 2.

    Load peptides onto a homemade reversed-phase C18 cartridge for peptide desalting (seeNote16).

     
  3. 3.

    Elute peptides in 50 % HPLC Buffer, dry down samples in a vacuum centrifuge, and resuspend peptides in 20 μL of HPLC Buffer A just before MS analysis.

     
  4. 4.

    Equilibrate the analytical HPLC column with 3 % HPLC Buffer B for at least 15 min prior to sample injection.

     
  5. 5.

    Resolve the bound peptides on a C-18 reversed-phase (RP) nano-column to an emitter nanospray needle for real-time ionization and peptide fragmentation, at a flow rate of 300 nL/min using the gradient 0–50 % B in 90 min and 50–90 % B in 1 min (seeNote17).

     

3.6 Mass Spectrometry

Tandem mass spectrometry analysis is performed using an LTQ Orbitrap XL hybrid mass spectrometer. The MS is operated in positive ion mode with a capillary temperature of 200 °C with no sheath gas.
  1. 1.

    Acquire full scan MS in profile mode from 390 to 1,200 m/z at 30,000 resolution using an internal lock mass. Maximal accumulation time for MS1 is set to 390 ms to a target fill of 1  ×  106.

     
  2. 2.

    A minimum signal of 1,000 counts is required to trigger data-dependent acquisition of MS/MS spectra. These are acquired in a data-dependent mode consisting of selection of the three most abundant ions on each cycle. For iTRAQ analysis, alternate between collision-induced disassociation (CID) and higher energy dissociation (HCD) modes for each selected precursor ion, so only three precursor ions are analyzed per cycle. For both fragmentation modes, accumulate to 5  ×  104 ions (seeNote18).

     
  3. 3.

    Dynamic exclusion parameters allow two repeat hits before the precursor m/z is added to an exclusion list for 180 s.

     

3.7 Database Searching and iTRAQ Labelling Analysis

  1. 1.

    Extract mass spectra by using Proteome Discoverer v1.2 software. For peptide identification, search the MS/MS spectra against a human protein database subset of the IPI database (human_ref.fasta; 2003, April; 39414 entries; seeNote19) using Sequest (Thermo Fisher version 1.0.43.2) and Mascot (local version 2.1.) engines. Use the following search parameters: trypsin digestion with up to two missed cleavages; mass tolerance of 15 ppm and 0.8 Da for precursor and fragment search, respectively; MMTS-labelled cysteines and iTRAQ-labelled N-termini as fixed modifications; and phosphorylation of serine, threonine, and tyrosine and iTRAQ labelling of threonine and lysine residues as variable modifications. Corrections were applied for impurity of iTRAQ reagents according to the manufacturer’s instructions (seeNote20).

     
  2. 2.

    Use Scaffold v.3.00.02 for validation and quantitation (seeNote21). Consider peptides identified with a probability greater than 80 % and accept proteins identified at greater than 80 % probability with at least one peptide identified, as specified by the Peptide and Protein Prophet (8) algorithms, respectively.

     
  3. 3.

    For protein quantification, decrease the minimum peptide and protein identification probabilities to 0.0 and 20 %, respectively, to include the low quality HCD spectra containing iTRAQ reporter quantitative data.

     
  4. 4.

    Quantify proteins containing at least two matched peptides to reduce the probability of a false-positive identification.

     
  5. 5.

    Highlight differentially expressed proteins using two criteria: (i) p values  ≤  0.05 and (ii) fold change value higher than 2 (seeNote22).

     

4 Notes

  1. 1.

    Written consent from all the individuals must be obtained, following the guidelines of the Ethics Committee of your institution. All subjects are in a fasting state; blood samples are taken in the morning (between 8 and 11 h) in an EDTA vacutainer.

     
  2. 2.

    Protein concentration can be measured at this step to determine the volume of plasma proteins to be loaded into the depletion column.

     
  3. 3.

    Depletion of high-abundant proteins can be performed using a variety of commercially available depletion technologies. The method described here is based on the MARS 14 column (4.6  ×  100 mm), designed to remove 14 abundant proteins based on affinity interactions (albumin, IgG, antitrypsin, IgA, transferrin, haptoglobin, fibrinogen, alpha2-macroglobulin, alpha1-acid glycoprotein, IgM, apolipoprotein AІ, apolipoprotein AII, complement C3, and transthyretin). While the high-abundant proteins are specifically retained into the column, the low-abundant proteins are collected to the flow-through fractions for further analysis.

     
  4. 4.

    The LC system must be purged before attaching the column for 10 min using HPLC MARS Buffer A at a flow rate of 1 mL/min, and set up HPLC MARS Buffer A and B as the only mobile phases.

     
  5. 5.

    It is recommended to dilute samples four times with HPLC MARS Buffer A before loading to facilitate protein binding.

     
  6. 6.

    Let samples interact with the stationary phase for complete binding of high-abundant proteins using a low flow rate.

     
  7. 7.

    It is important to carry out a thorough desalting, as iTRAQ labelling could be hampered by the presence of unwanted components like primary amines from Tris–HCl buffer.

     
  8. 8.

    If the lysis buffer contains detergents or reducing agents, RC-DC protein assay must be used for accurate protein concentration estimation.

     
  9. 9.

    It is essential to use comparable protein amounts in the four samples to facilitate later data analysis and to ensure adequate iTRAQ labelling; excessive protein amounts will result in incomplete labelling and/or bias in the quantification.

     
  10. 10.

    Mix well throughout the whole protocol: add carefully the components, vortex, and briefly centrifuge to spin down the sample to the bottom of the tubes.

     
  11. 11.

    To avoid partial digestion, overnight incubation is recommended. If possible, check protein digestion efficiency by analyzing a minute amount of the digested sample: desalt it using a ZipTip (Millipore), mix the eluted peptides with MALDI matrix solution, and spot them onto a MALDI plate (Bruker Daltonik). Check the MS spectra for comparable peptide ion signals between samples.

     
  12. 12.

    Based on iTRAQ instructions from ABI, the concentration of ethanol and iTRAQ reagents in the iTRAQ labelling reactions should be larger than 60 % (v/v) to maximize labelling efficiency.

     
  13. 13.

    Based on iTRAQ instructions from ABI, each iTRAQ vial can be used to label up to 100 μg of protein.

     
  14. 14.

    Because partial labelling is feasible, it is advisable to test the labelling efficiency in a small peptide sample before mixing using MALDI MS as in Note11.

     
  15. 15.

    To completely remove TEAB, reconstitute iTRAQ-labelled samples in 100 μL of MS-grade water and dry the sample in a vacuum concentrator. Repeat this step twice to ensure complete evaporation of TEAB.

     
  16. 16.

    Despite that a RP-C18 cartridge was employed for peptide desalting, the use of strong cation exchange (SCX) cartridges or columns for peptide desalting is widespread. Furthermore, depending of sample complexity and the amount of labelled protein, additional fractionation steps may be necessary to effectively reduce peptide complexity (e.g., by SCX chromatography).

     
  17. 17.

    The gradient used depends on the complexity of the peptide mixture and the available HLPC.

     
  18. 18.

    Different MS instruments have different optimal MS and MS/MS methods for the analysis of iTRAQ-labelled peptides (see refs. 9, 10, 11).

     
  19. 19.

    It is recommended to use the latest version of the protein database (i.e., Swissprot, IPI, or NCBI protein database) to ensure comprehensive peptide identification. In this study the IPI database was chosen owing to its high number of protein sequence entries, but this database has been recently discontinued.

     
  20. 20.

    If too many variable modifications are considered, confidence interval values for spectra matching can decrease due to the increased random matches. It is preferable to include only those modifications relevant to the experiment.

     
  21. 21.

    There are many other programs for the analysis of iTRAQ data (e.g., ref. 12).

     
  22. 22.

    Student’s t test is utilized to account for the relative protein expression changes between groups for each protein. It is advisable to employ several biological and control sample replicates for increasing the statistical confidence of analysis. It is very important to verify the iTRAQ results using biological complementary techniques, as Western blotting, ELISA, or immunohistochemistry.

     

Notes

Acknowledgments

The work has been supported by the Spanish MICIN (SAF2010/21852), Redes RECAVA (RD06/0014/0035), EUS2008-03565, and Fundacion Pro-CNIC. The Centro Nacional de Investigaciones Cardiovasculares is supported by the Spanish Ministry of Science and Innovation (MICIN) and the Pro-CNIC Foundation.

References

  1. 1.
    Sakalihasan N, Limet R, Defawe OD (2005) Abdominal aortic aneurysm. Lancet 365:1577–1589PubMedCrossRefGoogle Scholar
  2. 2.
    Vega de Céniga M, Gómez R, Estallo L, de la Fuente N, Viviens B, Barba A (2008) Analysis of expansion patterns in 4-4.9 cm abdominal aortic aneurysms. Ann Vasc Surg 22:37–44PubMedCrossRefGoogle Scholar
  3. 3.
    Martinez-Pinna R, Barbas C, Blanco-Colio LM, Tunon J, Ramos-Mozo P, Lopez JA, Meilhac O, Michel JB, Egido J, Martin-Ventura JL (2010) Proteomic and metabolomic profiles in atherothrombotic vascular disease. Curr Atheroscler Rep 12:202–208PubMedCrossRefGoogle Scholar
  4. 4.
    Pernemalm M, Lewensohn R, Lehtiö J (2009) Affinity prefractionation for MS-based plasma proteomics. Proteomics 9:1420–1427PubMedCrossRefGoogle Scholar
  5. 5.
    Polaskova V, Kapur A, Khan A, Molloy MP, Baker MS (2010) High-abundance protein depletion: comparison of methods for human plasma biomarker discovery. Electrophoresis 31:471–482PubMedCrossRefGoogle Scholar
  6. 6.
    Gong Y, Li X, Yang B, Ying W, Li D, Zhang Y, Dai S, Cai Y, Wang J, He F, Qian X (2006) Different immunoaffinity fractionation strategies to characterize the human plasma proteome. J Proteome Res 5:1379–1387PubMedCrossRefGoogle Scholar
  7. 7.
    Treumann A, Thiede B (2010) Isobaric protein and peptide quantification: perspectives and issues. Expert Rev Proteomics 7:647–653PubMedCrossRefGoogle Scholar
  8. 8.
    Nesvizhskii AI, Keller A, Kolker E, Aebersold R (2003) A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem 75:4646–4658PubMedCrossRefGoogle Scholar
  9. 9.
    Mischerikow N, van Nierop P, Li KW, Bernstein HG, Smith AB, Heck AJ, Altelaar AF (2010) Gaining efficiency by parallel quantification and identification of iTRAQ-labelled peptides using HCD and decision tree guided CID/ETD on an LTQ Orbitrap. Analyst 135:2643–2652PubMedCrossRefGoogle Scholar
  10. 10.
    Bantscheff M, Boesche M, Eberhard D, Matthieson T, Sweetman G, Kuster B (2008) Robust and sensitive iTRAQ quantification on an LTQ Orbitrap mass spectrometer. Mol Cell Proteomics 7:1702–1713PubMedCrossRefGoogle Scholar
  11. 11.
    Dayon L, Pasquarello C, Hoogland C, Sanchez JC, Scherl A (2010) Combining low- and high-energy tandem mass spectra for optimized peptide quantification with isobaric tags. J Proteomics 73:769–777PubMedCrossRefGoogle Scholar
  12. 12.
    Li Z, Adams RM, Chourey K, Hurst GB, Hettich RL, Pan C (2012) Systematic comparison of label-free, metabolic labeling, and isobaric chemical labeling for quantitative proteomics on LTQ Orbitrap Velos. J Proteome Res 11(3):1582–1590PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Enrique Calvo
    • 1
  • Roxana Martínez-Pinna
    • 2
  • Priscila Ramos-Mozo
    • 3
  • C. Pastor-Vargas
    • 4
  • Emilio Camafeita
    • 1
  • Jesús Egido
    • 2
  • José Luis Martin-Ventura
    • 2
  • Juan Antonio Lopez
    • 1
  1. 1.Unidad de ProteómicaCentro Nacional de Investigaciones Cardiovasculares, CNICMadridSpain
  2. 2.Vascular Research Lab IIS-Fundación Jiménez Díaz, Instituto de Investigacion Sanitaria Fundacion Jimenez Diaz (IIS-FJD)Universidad Autónoma de MadridMadridSpain
  3. 3.Vascular Research Laboratory, IISFundación Jiménez Díaz ands Autónoma UniversityMadridSpain
  4. 4.Department of ImmunologyInstituto de Investigacion Sanitaria Fundacion Jimenez Diaz (IIS-FJD)MadridSpain

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