Comparative proteomics, network analysis and post-translational modification identification reveal differential profiles of plasma Con A-bound glycoprotein biomarkers in gastric cancer (original) (raw)
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Talanta, 2010
Protein quantification based upon mass spectrometry is gaining ground in diverse applications of biological and clinical relevance. The present article focuses on one of the most complex biological fluids – serum – and provides a novel ICPL based quantification protocol. The results are compared to a label-free (data independent alternate scanning) absolute quantification method. The validation is performed using MRM based protein quantification technique. Regarding the ICPL approach, serum samples used in this study were depleted of high abundant proteins, labeled with ICPL and fractionated according to their respective pI (3–5, 5–7 and 7–12). The samples were further subjected to tryptic digestion followed by treatment with the Glu-C enzyme. The peptides were analyzed on a 2D-nano-LC system using four different concentrations of salt injections (45, 75, 150 and 500 mM ammonium acetate). The LC system was connected on-line with the electrospray ion-trap mass spectrometer. For the label-free quantification the serum samples were depleted and digested with trypsin. A proteome-wide comparison was performed using highly reproducible LC and data independent alternate scanning in conjunction with a high mass accuracy orthogonal time-of-flight mass spectrometer. Selected proteins, found by both methods, were validated using the MRM approach. For this purpose non-depleted tryptically digested serum samples were analyzed by LC coupled with a triple-quadrupole MS. The relative protein quantification using ICPL and mass spectrometry allowed for the detection of approximately 200 proteins, whereas about 2/3 of those contained the ICPL label and could therefore be quantified. Label-free approach used no fractionation, less sample and was able to identify and quantify over 110 proteins. The identified proteins covered generally 3–4 orders of magnitude of protein concentration in human serum. Changes in relative abundance of eight proteins were validated using MRM. This study, for the first time, shows the ability of the relative protein quantification based upon ICPL and 2D-LC–MS/MS to quantify serum biomarkers. It provides two additional label-free approaches that could validate and bring additional value to the label-based results, offering a starting point for comprehensive proteomics studies aiming at revealing biomarkers of clinical relevance.
Novel post-digest isotope coded protein labeling method for phospho- and glycoproteome analysis
Journal of proteomics, 2010
In the field of proteomics there is an apparent lack of reliable methodology for quantification of posttranslational modifications. Present study offers a novel post-digest ICPL quantification strategy directed towards characterization of phosphorylated and glycosylated proteins. The value of the method is demonstrated based on the comparison of two prostate related metastatic cell lines originating from two distinct metastasis sites (PC3 and LNCaP). The method consists of protein digestion, ICPL labeling, mixing of the samples, PTM enrichment and MS-analysis. Phosphorylated peptides were isolated using TiO2, whereas the enrichment of glycosylated peptides was performed using hydrazide based chemistry. Isolated PTM peptides were analyzed along with non enriched sample using 2D-(SCX-RP)-Nano-HPLC–MS/MS instrumentation. Taken together the novel ICPL labeling method offered a significant improvement of the number of identified (∼ 600 individual proteins) and quantified proteins (> 95%) in comparison to the classical ICPL method. The results were validated using alternative protein quantification strategies as well as label-free MS quantification method. On the biological level, the comparison of PC3 and LNCaP cells has shown specific modulation of proteins implicated in the fundamental process related to metastasis dissemination. Finally, a preliminary study involving clinically relevant autopsy cases reiterated the potential biological value of the discovered proteins.
Molecular & Cellular Proteomics, 2007
Identification and relative quantification of hundreds to thousands of proteins within complex biological samples have become realistic with the emergence of stable isotope labeling in combination with high throughput mass spectrometry. However, all current chemical approaches target a single amino acid functionality (most often lysine or cysteine) despite the fact that addressing two or more amino acid side chains would drastically increase quantifiable information as shown by in silico analysis in this study. Although the combination of existing approaches, e.g. ICAT with isotope-coded protein labeling, is analytically feasible, it implies high costs, and the combined application of two different chemistries (kits) may not be straightforward. Therefore, we describe here the development and validation of a new stable isotope-based quantitative proteomics approach, termed aniline benzoic acid labeling (ANIBAL), using a twin chemistry approach targeting two frequent amino acid functionalities, the carboxylic and amino groups. Two simple and inexpensive reagents, aniline and benzoic acid, in their 12 C and 13 C form with convenient mass peak spacing (6 Da) and without chromatographic discrimination or modification in fragmentation behavior, are used to modify carboxylic and amino groups at the protein level, resulting in an identical peptide bond-linked benzoyl modification for both reactions. The ANIBAL chemistry is simple and straightforward and is the first method that uses a 13 Creagent for a general stable isotope labeling approach of carboxylic groups. In silico as well as in vitro analyses clearly revealed the increase in available quantifiable information using such a twin approach. ANIBAL was validated by means of model peptides and proteins with regard to the quality of the chemistry as well as the ionization behavior of the derivatized peptides. A milk fraction was used for dynamic range assessment of protein quantification, and a bacterial lysate was used for the evaluation of relative protein quantification in a complex sample in two different biological states.
Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, 2014
The timely detection of gastric cancer will contribute significantly towards effective treatment and is aided by the availability and reliability of appropriate biomarkers. A combination of several biomarkers can improve the sensitivity and specificity of cancer detection and this work reports results from a panel of 4 proteins. By combining a validated preclinical mouse model with a proteomic approach we have recently discovered novel biomarkers for the detection of gastric cancer. Here, we investigate the specificity of four of those biomarkers (afamin, clusterin, VDBP and haptoglobin) for the detection of gastric cancer using two independent methods of validation: ELISA, and a non antibody based method: Multiple Reaction Monitoring with High Resolution Mass Spectrometry (MRM-HR). All four biomarkers reliably differentiated GC from benign patient serum, and also in a small cohort of 11 early stage cases. We also present a novel isoform specific biomarker alpha-1-antitrypsin (A1AT) that was identified using a mouse model for gastric cancer. This isoform is distinct in charge and mobility in a pH gradient and was validated using human samples by isoelectric focussing and Western-blot (IEF-WB). This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.
Rapid Communications in Mass Spectrometry, 2006
Two methods of differential isotopic coding of carboxylic groups have been developed to date. The first approach uses d0- or d3-methanol to convert carboxyl groups into the corresponding methyl esters. The second relies on the incorporation of two 18O atoms into the C-terminal carboxylic group during tryptic digestion of proteins in H218O. However, both methods have limitations such as chromatographic separation of 1H and 2H derivatives or overlap of isotopic distributions of light and heavy forms due to small mass shifts. Here we present a new tagging approach based on the specific incorporation of sulfanilic acid into carboxylic groups. The reagent was synthesized in a heavy form (13C phenyl ring), showing no chromatographic shift and an optimal isotopic separation with a 6 Da mass shift. Moreover, sulfanilic acid allows for simplified fragmentation in matrix-assisted laser desorption/ionization (MALDI) due the charge fixation of the sulfonate group at the C-terminus of the peptide. The derivatization is simple, specific and minimizes the number of sample treatment steps that can strongly alter the sample composition. The quantification is reproducible within an order of magnitude and can be analyzed either by electrospray ionization (ESI) or MALDI. Finally, the method is able to specifically identify the C-terminal peptide of a protein by using GluC as the proteolytic enzyme. Copyright © 2006 John Wiley & Sons, Ltd.
Analytical Chemistry, 2005
In this study, S. cerevisiae crude membrane fractions were prepared using the acid-labile detergent RapiGest from cells grown under rich and minimal media conditions using 14 N and 15 N ammonium sulfate as the sole nitrogen source. Four independent MudPIT analyses of 1:1 mixtures of sample were prepared and analyzed via quantitative multidimensional protein identification technology on a two-dimensional ion trap mass spectrometer. Using the method described in this study, low-abundance integral membrane proteins with up to 14 transmembrane domains were identified and their protein expression determined when sufficient spectrum counting and ion chromatogram information was generated. We demonstrate that spectrum counting and mass spectrometry derived ion chromatograms strongly correlate for determining quantitative changes in protein expression. Spectrum counting proved more reproducible and has a wider dynamic range contributing to the deviation of the two quantitative approaches from a perfect positive correlation.
Stable Isotope Labeling by Amino acid in Vivo (SILAV): a new method to explore protein metabolism
Rapid Communications in Mass Spectrometry, 2015
RATIONALE: Intravenous administration of stable isotope labeled amino acid ( 13 C 6 -leucine) to humans recently made it possible to study the metabolism of specific biomarkers in cerebrospinal fluid (CSF) using targeted mass spectrometry (MS). This labeling approach could be of great interest for monitoring many leucine-containing peptides in parallel, using high-resolution MS. This will make it possible to quantify the rates of synthesis and clearance of a large range of proteins in humans with a view to obtaining new insights into protein metabolism processes and the pathophysiology of diseases such as Alzheimer's disease. METHODS: Proteins from human lumbar and ventricular CSF samples collected at different times after intravenous 13 C 6 -leucine infusion were digested enzymatically with LysC/trypsin after being denatured, reduced and alkylated. Desalted tryptic peptides were fractionated using Strong Cation eXchange chromatography (SCX) and analyzed using nanoflow liquid chromatography (nano-LC) coupled to a QTOF Impact II (Bruker Daltonics) mass spectrometer. Datadependent acquisition (DDA) mode was used to identify and quantify light and heavy 13 C 6 -leucine peptides. The ratios of 13 C 6 -leucine incorporation were calculated using the Skyline software program in order to determine the rates of appearance and clearance of proteins in the CSF. RESULTS: After SCX fractionation and quadrupole time-of-flight (QTOF) analysis, 4528 peptides containing leucine were identified in five fractions prepared from 40 μL of CSF. Upon analyzing one of these fractions, 66 peptides (2.7%) corresponding to 61 individual proteins had significant and reproducible rate of 13 C 6 -leucine incorporation at various time points. The plots of the light-to-heavy peptide ratios showed the existence of proteins with different patterns of appearance and clearance in the CSF. CONCLUSIONS: The Stable Isotope Labeling Amino acid in Vivo (SILAV) method presented here, which yields unprecedented information about protein metabolism in humans, constitutes a promising new approach which certainly holds great potential in the field of clinical proteomics.
Bioanalysis, 2011
To ensure comparability of results in clinical proteomics, methods for accurate and traceable quantification of proteins are required. Typically this is done for recombinant proteins using isotopically labeled peptides as internal standards (IS). However, in order to perform quantification in complex matrices such as human serum, isotopically labeled protein standards have been suggested for use as IS to account for losses in sample preparation. The isotopic diluent must be chemically and physically identical to the analyte of interest, having the same amino acid sequence, post-translational modifications, secondary and tertiary structure. It must not be assumed but rather proven that the isotopic diluent is a true mimic, and here we consider both the advantages and potential pitfalls encountered when using isotopically labeled protein IS.
Quantitative proteomics for identification of cancer biomarkers
PROTEOMICS – CLINICAL APPLICATIONS, 2007
Quantitative proteomics can be used for the identification of cancer biomarkers that could be used for early detection, serve as therapeutic targets, or monitor response to treatment. Several quantitative proteomics tools are currently available to study differential expression of proteins in samples ranging from cancer cell lines to tissues to body fluids. 2-DE, which was classically used for proteomic profiling, has been coupled to fluorescence labeling for differential proteomics. Isotope labeling methods such as stable isotope labeling with amino acids in cell culture (SILAC), isotope-coded affinity tagging (ICAT), isobaric tags for relative and absolute quantitation (iTRAQ), and 18 O labeling have all been used in quantitative approaches for identification of cancer biomarkers. In addition, heavy isotope labeled peptides can be used to obtain absolute quantitative data. Most recently, label-free methods for quantitative proteomics, which have the potential of replacing isotope-labeling strategies, are becoming popular. Other emerging technologies such as protein microarrays have the potential for providing additional opportunities for biomarker identification. This review highlights commonly used methods for quantitative proteomic analysis and their advantages and limitations for cancer biomarker analysis.