Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus

Design considerations for proteomic reference materials

In order to improve the repeatability, comparability, and accuracy of MS-based proteomic measurements, there has been considerable international effort to develop appropriate reference materials. Although the majority of reference materials are developed to support measurement quality of routine assays, the development of reference materials for a diverse and changing research field such as proteomics represents unique challenges. In order to define common measurement components and common features of typical proteomic samples, the metrology underpinning proteomics must be considered due to the diversity and changing nature of the field. Reference materials can then be designed around common aspects in order to produce reference materials with the broadest applicability. Reference materials are needed to support both qualitative and quantitative proteomic measurements, involving different design considerations. Consensus and validated statistical approaches to describe the confidence in qualitative measurement, such as protein identification, needs to be established. Common sources of measurement bias also need to be considered in proteomic reference material design.

High-throughput peptide quantification using mTRAQ reagent triplex

BACKGROUND

Protein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents.

METHODS AND RESULTS

Here we propose a novel data analysis algorithm for peptide quantification in triplex mTRAQ experiments. It improved the accuracy of quantification in two features. First, it identified and separated triplex isotopic clusters of a peptide in each full MS scan. We designed a schematic model of triplex overlapping isotopic clusters, and separated triplex isotopic clusters by solving cubic equations, which are deduced from the schematic model. Second, it automatically determined the elution areas of peptides. Some peptides have similar atomic masses and elution times, so their elution areas can have overlaps. Our algorithm successfully identified the overlaps and found accurate elution areas. We validated our algorithm using standard protein mixture experiments.

CONCLUSIONS

We showed that our algorithm was able to accurately quantify peptides in triplex mTRAQ experiments. Its software implementation is compatible with Trans-Proteomic Pipeline (TPP), and thus enables high-throughput analysis of proteomics data.

Quantitative secretome analysis reveals that COL6A1 is a metastasis-associated protein using stacking gel-aided purification combined with iTRAQ labeling

In cancer metastasis, secreted proteins play an important role in promoting cancer cell migration and invasion and thus also in the increase of cancer metastasis in the extracellular microenvironment. In this study, we developed a strategy that combined a simple gel-aided protein purification with iTRAQ labeling to quantify and discover the metastasis-associated proteins in the lung cancer cell secretome. Secreted proteins associated with lung cancer metastasis were produced using CL1-0 and CL1-5 cells with different metastatic abilities. Quantitative secretomics analysis identified a total of 353 proteins, 7 of which were considered to be metastasis-associated proteins. These included TIMP1, COL6A1, uPA, and AAT, all of which were higher in CL1-5, and AL1A1, PRDX1, and NID1, which were higher in CL1-0. Six of these metastasis-associated proteins were validated with Western blot analysis. In addition, pathway analysis was performed in building the interaction network between the identified metastasis-associated proteins. Further functional analysis of COL6A1 on the metastatic abilities of CL1 cells was also carried out. An RNA interference-based knock-down of COL6A1 suppressed the metastatic ability of CL1-5 cells; in contrast, a plasmid-transfected overexpression of COL6A1 increased the metastatic ability of CL1-0 cells. This study describes a simple and high throughput sample purification method that can be used for the quantitative secretomics analysis of metastasis-associated proteins.

Clinical proteomics: current status, challenges, and future perspectives

This account will give an overview and evaluation of the current advances in mass spectrometry (MS)-based proteomics platforms and technology. A general review of some background information concerning the application of these methods in the characterization of molecular sizes and related protein expression profiles associated with different types of cells under varied experimental conditions will be presented. It is intended to provide a concise and succinct overview to those clinical researchers first exposed to this foremost powerful methodology in modern life sciences of postgenomic era. Proteomic characterization using highly sophisticated and expensive instrumentation of MS has been used to characterize biological samples of complex protein mixtures with vastly different protein structure and composition. These systems are then used to highlight the versatility and potential of the MS-based proteomic strategies for facilitating protein expression analysis of various disease-related organisms or tissues of interest. Major MS-based strategies reviewed herein include (1) matrix-assisted laser desorption ionization-MS and electron-spray ionization proteomics; (2) one-dimensional or two-dimensional gel-based proteomics; (3) gel-free shotgun proteomics in conjunction with liquid chromatography/tandem MS; (4) Multiple reaction monitoring coupled tandem MS quantitative proteomics and; (5) Phosphoproteomics based on immobilized metal affinity chromatography and liquid chromatography-MS/MS.

Ultrasonic-based protein quantitation by (18) O-labeling: optimization and comparison between different procedures

Herein we report results regarding the optimization and comparison between different ultrasonic-based procedures for protein quantitation by the direct (18) O-labeling approach. The labeling procedure was evaluated using different proteins, different ultrasonic devices and different reaction times: from 30 s to 10 min with the ultrasonic probe and from 30 s to 30 min with the sonoreactor. Variables such as the enzyme-to-protein ratio and protein concentration were also assessed. The results show that it is possible to accelerate the labeling reaction from 12 h to only 15 min with the sonoreactor without compromising the labeling efficiency. A larger variation in the double labeling yield was obtained among the different peptides, but the values for the smaller peptides are similar to the ones achieved with the classic methodology. These findings were further confirmed by labeling a complex protein mixture from human plasma. It was also found that the labeling reaction is affected by the sample concentration, even when performed with the classic overnight procedure.

An approach to quantifying N-linked glycoproteins by enzyme-catalyzed 18O3-labeling of solid-phase enriched glycopeptides

Global analysis of glycoproteins shows great promise for the discovery of therapeutic targets and clinical biomarkers. Selective capture of glycopeptides by hydrazide resin followed by mass spectrometric identification of the peptides released by PNGaseF treatment has been most widely used. However, the majority of the reports using this approach focus on global profiling, rather than relative quantitation of glycoprotein alternations in pathological states. We describe an integrated strategy allowing for relative quantitation of glycoproteins in complex biological mixtures using this approach. The strategy includes periodate oxidation of tryptic digests, solid-phase enrichment of glycopeptides via hydrazide-coupled magnetic beads, in conjunction with (18)O stable isotope labeling catalyzed by both trypsin and PNGaseF, and subsequent identification and quantitation by LC-MS/MS analysis. Three (18)O atoms ((18)O(3)) are incorporated into N-linked glycopeptides for samples treated in (18)O-water, two at the carboxyl terminus by trypsin during hydrazide coupling and the third at the N-glycosylation site through PNGaseF-mediated deglycosylation. Thus, mass shifts of 6 and 8 Da are indicative of singly and doubly glycosylated peptides, respectively. Experimental conditions were optimized to promote the trypsin-mediated (18)O(2) incorporation and prevent backbone exchange. The accuracy, reproducibility, and linearity of relative quantitation were evaluated by using 15 glycoproteins spiked into mouse serum at different concentration ratios. Using this approach, we were able to identify and quantitate 224 N-glycopeptides representing 130 unique glycoproteins from 20 μL of the undepleted mouse serum samples. The strategy can be easily adapted to the analysis of glycoproteins in tissues, cell lines, and other sample origins.

Trypsin-catalyzed oxygen-18 labeling for quantitative proteomics

Stable isotope labeling based on relative peptide/protein abundance measurements is commonly applied for quantitative proteomics. Recently, trypsin-catalyzed oxygen-18 labeling has grown in popularity due to its simplicity, cost-effectiveness, and its ability to universally label peptides with high sample recovery. In (18)O labeling, both C-terminal carboxyl group atoms of tryptic peptides can be enzymatically exchanged with (18)O, thus providing the labeled peptide with a 4 Da mass shift from the (16)O-labeled sample. Peptide (18)O labeling is ideally suited for generating a labeled "universal" reference sample used for obtaining accurate and reproducible quantitative measurements across large number of samples in quantitative discovery proteomics.

Quantitative measurement of phosphopeptides and proteins via stable isotope labeling in Arabidopsis and functional phosphoproteomic strategies

Protein phosphorylation is one type of posttranslational modification, which regulates a large number of cellular processes in plant cells. As an emerging powerful biotechnology that integrates all aspects of advantages from mass spectrometry, bioinformatics, and genomics, phosphoproteomics offers us an unprecedented high-throughput methodology with high sensitivity and dashing speed in identifying a large complement of phosphoproteins from plant cells within a relatively short period of time. Needless to say, phosphoproteomics has become an integral portion of life sciences, which penetrates various research disciplines of biology, agriculture, and forestry and irreversibly changes the way by which plant scientists study biological problems.Because phosphorylation/dephosphorylation of protein is dynamic in cells and the amount of phosphoproteins is low, the preservation of a phosphor group onto phosphosite throughout protein purification as well as enrichment of these phosphoproteins during purification has become a serious technical issue. To overcome difficulties commonly associated with phosphoprotein isolation, phosphopeptides' enrichment, and mass spectrometry analysis, we have developed a urea-based phosphoprotein purification protocol for plants, which instantly denatures plant proteins once the total cell content comes into contact with the UEB solution. To measure the alteration of phosphorylation on a phosphosite using mass spectrometer, an in vivo (15)N metabolic labeling method (SILIA, i.e., stable isotope labeling in Arabidopsis) has been developed and applied for Arabidopsis differential phosphoproteomics. Thus far, hundreds of signaling-specific phosphoproteins have been identified using both label-free and (15)N-labeled differential phosphoproteomic approach. The phosphoproteomics has allowed us to identify a number of signaling components mediating plant cell signaling in Arabidopsis. It is envisaged that a huge number of phosphosites will continue to be uncovered from phosphoproteomics in the near future, which will become instrumental for the development of plant phosphor-relay networks and molecular systems biology.

Instruments and methods in proteomics

In the past decade, major developments in instrumentation and methodology have been achieved in proteomics. For proteome investigations of complex biological samples derived from cell cultures, tissues, or whole organisms, several techniques are state of the art. Especially, many improvements have been undertaken to quantify differences in protein expression between samples from, e.g., treated vs. untreated cells and healthy vs. control patients. In this review, we give a brief insight into the main techniques, including gel-based protein separation techniques, and the growing field of mass spectrometry.

DeepQuanTR: MALDI-MS-based label-free quantification of proteins in complex biological samples

The quantification of changes in protein abundance in complex biological specimens is essential for proteomic studies in basic and applied research. Here we report on the development and validation of the DeepQuanTR software for identification and quantification of differentially expressed proteins using LC-MALDI-MS. Following enzymatic digestion, HPLC peptide separation and normalization of MALDI-MS signal intensities to the ones of internal standards, the software extracts peptide features, adjusts differences in HPLC retention times and performs a relative quantification of features. The annotation of multiple peptides to the corresponding parent protein allows the definition of a Protein Quant Value, which is related to protein abundance and which allows inter-sample comparisons. The performance of DeepQuanTR was evaluated by analyzing 24 samples deriving from human serum spiked with different amounts of four proteins and eight complex samples of vascular proteins, derived from surgically resected human kidneys with cancer following ex vivo perfusion with a reactive ester biotin derivative. The identification and experimental validation of proteins, which were differentially regulated in cancerous lesions as compared with normal kidney, was used to demonstrate the power of DeepQuanTR. This software, which can easily be used with established proteomic methodologies, facilitates the relative quantification of proteins derived from a wide variety of different samples.

Using power spectrum analysis to evaluate (18)O-water labeling data acquired from low resolution mass spectrometers

We describe a method for ratio estimations in (18)O-water labeling experiments acquired from low resolution isotopically resolved data. The method is implemented in a software package specifically designed for use in experiments making use of zoom-scan mode data acquisition. Zoom-scan mode data allow commonly used ion trap mass spectrometers to attain isotopic resolution, which makes them amenable to use in labeling schemes such as (18)O-water labeling, but algorithms and software developed for high resolution instruments may not be appropriate for the lower resolution data acquired in zoom-scan mode. The use of power spectrum analysis is proposed as a general approach that may be uniquely suited to these data types. The software implementation uses a power spectrum to remove high-frequency noise and band-filter contributions from coeluting species of differing charge states. From the elemental composition of a peptide sequence, we generate theoretical isotope envelopes of heavy-light peptide pairs in five different ratios; these theoretical envelopes are correlated with the filtered experimental zoom scans. To automate peptide quantification in high-throughput experiments, we have implemented our approach in a computer program, MassXplorer. We demonstrate the application of MassXplorer to two model mixtures of known proteins and to a complex mixture of mouse kidney cortical extract. Comparison with another algorithm for ratio estimations demonstrates the increased precision and automation of MassXplorer.

Stable isotope labelled mass spectrometry for quantification of the relative abundances for expressed proteins induced by PeaT1

The protein elicitor from the mycelium of Alternaria tenuissima has been isolated. The elicitor triggered resistance to the tobacco mosaic virus in tobacco by inducing relative oxygen species, but without causing hypersensitive necrosis. The elicitor is reported to impart resistance against Verticillium dahliae and to increase yield in cotton, but its mechanism is not yet clear. In this study, the stable isotope labelled mass spectrometry method was used to quantify the relative abundances of protein expression induced by PeaT1 in Arabidopsis. A significant difference in the relative abundances for the expression of different proteins related to metabolism, modification, regulatory, defense, stress and antioxidation was found in Arabidopsis.

Accelerated 18O-labeling in urinary proteomics

Proteolytic (18)O-labeling of peptides has been studied and optimized in order to improve the labeling efficiency and to accelerate the process without increasing the degree of incomplete labeling. Using peptides generated from tryptic digested bovine serum albumin (BSA) and cytochrome c as model proteins, it was shown that complete labeling was achieved after 2 h at pH 6. To increase the sample throughput in a bottom-up proteomic setup, tryptic digestion of proteins in-solution was replaced with tryptic digestion using immobilized trypsin. As a result, an integrated approach was made possible, where both digestion (pH 8) and (18)O/(16)O-labeling of the resulting peptides (pH 6) were done using immobilized trypsin beads. This simplified the sample handling and reduced the overall reaction time significantly: the setup enabled tryptic digestion and (18)O/(16)O-labeling without sample transfer steps within 3.5 h with average (18)O/(16)O-ratios of 0.96±0.13 in aqueous buffer. The initial results were confirmed with a more complex matrix, by spiking urine with the model proteins, yielding results comparable with the ratios obtained in buffer. Satisfying ratios were also achieved regarding urinary proteins identified in a full scale bottom-up experiment. Average (18)O/(16)O-peptide ratios of 0.83±0.13 and 0.91±0.27 indicated good performance in a highly relevant matrix for biomarker discovery.

Subcellular phosphoproteomics

Protein phosphorylation represents one of the most extensively studied post-translational modifications, primarily due to the emergence of sensitive methods enabling the detection of this modification both in vitro and in vivo. The availability of enrichment methods combined with sensitive mass spectrometry instrumentation has played a crucial role in uncovering the dynamic changes and the large expanding repertoire of this reversible modification. The structural changes imparted by the phosphorylation of specific residues afford exquisite mechanisms for the regulation of protein functions by modulating new binding sites on scaffold proteins or by abrogating protein-protein interactions. However, the dynamic interplay of protein phosphorylation is not occurring randomly within the cell but is rather finely orchestrated by specific kinases and phosphatases that are unevenly distributed across subcellular compartments. This spatial separation not only regulates protein phosphorylation but can also control the activity of other enzymes and the transfer of other post-translational modifications. While numerous large-scale phosphoproteomics studies highlighted the extent and diversity of phosphoproteins present in total cell lysates, the further understanding of their regulation and biological activities require a spatio-temporal resolution only achievable through subcellular fractionation. This review presents a first account of the emerging field of subcellular phosphoproteomics where cell fractionation approaches are combined with sensitive mass spectrometry methods to facilitate the identification of low abundance proteins and to unravel the intricate regulation of protein phosphorylation.

Targeted proteomics by selected reaction monitoring mass spectrometry: applications to systems biology and biomarker discovery

Mass Spectrometry-based proteomics is now considered a relatively established strategy for protein analysis, ranging from global expression profiling to the identification of protein complexes and specific post-translational modifications. Recently, Selected Reaction Monitoring Mass Spectrometry (SRM-MS) has become increasingly popular in proteome research for the targeted quantification of proteins and post-translational modifications. Using triple quadrupole instrumentation (QqQ), specific analyte molecules are targeted in a data-directed mode. Used routinely for the quantitative analysis of small molecular compounds for at least three decades, the technology is now experiencing broadened application in the proteomics community. In the current review, we will provide a detailed summary of current developments in targeted proteomics, including some of the recent applications to biological research and biomarker discovery.

Solid phase isobaric mass tag reagent for simultaneous protein identification and assay

The solid phase isobaric mass tagging (SPIMT) approach is presented for simultaneous protein quantitation and identification. The novelty of the SPIMT strategy relies on a CID-based differentiation of regioisomeric species for quantitation of tagged proteolytic peptides. SPIMTs are unlabeled mass-tagging reagents, which consist of a reporter group, a mass balance group, and a spacer with a amine-specific reactive group, able to be linked to any N-terminal peptide. Therefore SPIMT-linked peptides from a two-plex set appear as a single unresolved precursor ion in MS, whereas the reporter groups lead to quantitation signals of m/z 168.2 and 182.2 Da upon tandem mass spectrometry (MS/MS) analysis with matrix-assisted laser desorption time-of-flight/time-of-flight (MALDI TOF/TOF). This strategy allows ease protein identification by direct submission of MS and MS/MS data to the MASCOT database. SPIMT approach showed an excellent quantitation linearity, detecting any relative concentration differences of peptides in two solutions over a 5-fold concentration range without losing sequencing information. Therefore, SPIMTs are an attractive, simple, and low cost alternative for two-plex quantitation of proteins and offer possibilities of tuning the two-plex signal mass window by replacing the spacer.

Mass spectrometry-based proteomics in biomedical research: emerging technologies and future strategies

In recent years, the technology and methods widely available for mass spectrometry (MS)-based proteomics have increased in power and potential, allowing the study of protein-level processes occurring in biological systems. Although these methods remain an active area of research, established techniques are already helping answer biological questions. Here, this recent evolution of MS-based proteomics and its applications are reviewed, including standard methods for protein and peptide separation, biochemical fractionation, quantitation, targeted MS approaches such as selected reaction monitoring, data analysis and bioinformatics. Recent research in many of these areas reveals that proteomics has moved beyond simply cataloguing proteins in biological systems and is finally living up to its initial potential – as an essential tool to aid related disciplines, notably health research. From here, there is great potential for MS-based proteomics to move beyond basic research, into clinical research and diagnostics.

Strategies for quantitation of phosphoproteomic data

Recent developments in phosphoproteomic sample-preparation techniques and sensitive mass spectrometry instrumentation have led to large-scale identifications of phosphoproteins and phosphorylation sites from highly complex samples. This has facilitated the implementation of different quantitation strategies in order to study the biological role of protein phosphorylation during disease progression, differentiation or during external stimulation of a cellular system. In this article, a brief summary of the most popular strategies for phosphoproteomic studies is given; however, the main focus will be on different quantitation strategies. Methods for metabolic labeling, chemical modification and label-free quantitation and their applicability or inapplicability in phosphoproteomic studies are discussed.

A robust method for quantitative high-throughput analysis of proteomes by 18O labeling

MS-based quantitative proteomics plays an increasingly important role in biological and medical research and the development of these techniques remains one of the most important challenges in mass spectrometry. Numerous stable isotope labeling approaches have been proposed. However, and particularly in the case of (18)O-labeling, a standard protocol of general applicability is still lacking, and statistical issues associated to these methods remain to be investigated. In this work we present an improved high-throughput quantitative proteomics method based on whole proteome concentration by SDS-PAGE, optimized in-gel digestion, peptide (18)O-labeling, and separation by off-gel isoelectric focusing followed by liquid chromatography-LIT-MS. We demonstrate that the off-gel technique is fully compatible with (18)O peptide labeling in any pH range. A recently developed statistical model indicated that partial digestions and methionine oxidation do not alter protein quantification and that variances at the scan, peptide, and protein levels are stable and reproducible in a variety of proteomes of different origin. We have also analyzed the dynamic range of quantification and demonstrated the practical utility of the method by detecting expression changes in a model of activation of Jurkat T-cells. Our protocol provides a general approach to perform quantitative proteomics by (18)O-labeling in high-throughput studies, with the added value that it has a validated statistical model for the null hypothesis. To the best of our knowledge, this is the first report where a general protocol for stable isotope labeling is tested in practice using a collection of samples and analyzed at this degree of statistical detail.

Mass spectrometry based glycoproteomics--from a proteomics perspective

Glycosylation is one of the most important and common forms of protein post-translational modification that is involved in many physiological functions and biological pathways. Altered glycosylation has been associated with a variety of diseases, including cancer, inflammatory and degenerative diseases. Glycoproteins are becoming important targets for the development of biomarkers for disease diagnosis, prognosis, and therapeutic response to drugs. The emerging technology of glycoproteomics, which focuses on glycoproteome analysis, is increasingly becoming an important tool for biomarker discovery. An in-depth, comprehensive identification of aberrant glycoproteins, and further, quantitative detection of specific glycosylation abnormalities in a complex environment require a concerted approach drawing from a variety of techniques. This report provides an overview of the recent advances in mass spectrometry based glycoproteomic methods and technology, in the context of biomarker discovery and clinical application.

Quantitative analysis of cell surface membrane proteins using membrane-impermeable chemical probe coupled with 18O labeling

We report a mass spectrometry-based strategy for quantitative analysis of cell surface membrane proteome changes. The strategy includes enrichment of surface membrane proteins using a membrane-impermeable chemical probe followed by stable isotope (18)O labeling and LC-MS analysis. We applied this strategy for enriching membrane proteins expressed by Shewanella oneidensis MR-1, a Gram-negative bacterium with known metal-reduction capability via extracellular electron transfer between outer membrane proteins and extracellular electron receptors. LC/MS/MS analysis resulted in the identification of about 400 proteins with 79% of them being predicted to be membrane localized. Quantitative aspects of the membrane enrichment were shown by peptide level (16)O and (18)O labeling of proteins from wild-type and mutant cells (generated from deletion of a type II secretion protein, GspD) prior to LC-MS analysis. Using a chemical probe labeled pure protein as an internal standard for normalization, the quantitative data revealed reduced abundances in Delta gspD mutant cells of many outer membrane proteins including the outer membrane c-type cytochromes OmcA and MtrC, in agreement with a previous report that these proteins are substrates of the type II secretion system.

SnO2@Poly(HEMA-co-St-co-VPBA) core-shell nanoparticles designed for selectively enriching glycopeptides followed by MALDI-MS analysis

The core-shell boronic-acid functionalized nanoparticles SnO(2)@Poly(HEMA-co-St-co-VPBA) are designed for selectively enriching glycopeptides, followed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) analysis. Such 60 nm sized core-shell nanoparticles are prepared by means of copolymerization between 2-hydroxyethyl methacrylate (HEMA) grafted on SnO(2) nanoparticles, styrene, and 4-vinylphenylboronic acid (VPBA). All of the synthesis procedures are completed within 3 h. Cyclic boronate esters form between boronic-acid groups on the polymer chains and cis-diol groups on glycopeptides, and thus almost all intact glycopeptides from low-abundant horseradish peroxidase (HRP) and bovine asialofetuin (ASF) are enriched with high selectivity and efficiency. After enrichment, both intact N- and O-glycopeptides are characterized by multistage MS. Furthermore, we successfully apply this method to the human serum sample for characterizing the target glycoproteins haptoglobin and alpha-1-acid-glycoprotein. The present selective enriching method followed by multistage-MS analysis is proven to be a good choice for routine glycopeptide characterization.

Measuring the turnover rates of Arabidopsis proteins using deuterium oxide: an auxin signaling case study

Rapid environmental responses in plants rely on endogenous signaling mechanisms, which in many cases are mediated by changes in protein turnover rates. It is therefore necessary to develop methods for measuring protein dynamics that monitor large sets of plant proteins to begin to apply a systems biology approach to the study of plant behavior. The use of stable isotope labeling strategies that are adaptable to proteomic methods is particularly attractive for this purpose. Here, we explore one example of such methods that is particularly suitable for plants at the seedling stage, where measurement of amino acid and protein turnover rates is accomplished using a heavy water labeling strategy. The method is backed by microarray evaluation to define its feasibility for specific experimental approaches, and the CULLIN-ASSOCIATED AND NEDDYLATION DISSOCIATED 1 (CAND1) and TRANSPORT INHIBITOR RESPONSE 1 (TIR1) proteins are used to illustrate the potential utility in understanding hormonal signaling regulation. These studies provide insight not only into the potential utility of the method, but also address possible areas of concern regarding the use of heavy water labeling during plant growth. These considerations suggest a prescription for specific experimental designs that minimize interference resulting from the induction of treatment-specific gene expression in the results obtained.

Elucidating the higher-order structure of biopolymers by structural probing and mass spectrometry: MS3D

Chemical probing represents a very versatile alternative for studying the structure and dynamics of substrates that are intractable by established high-resolution techniques. The implementation of MS-based strategies for the characterization of probing products has not only extended the range of applicability to virtually all types of biopolymers but has also paved the way for the introduction of new reagents that would not have been viable with traditional analytical platforms. As the availability of probing data is steadily increasing on the wings of the development of dedicated interpretation aids, powerful computational approaches have been explored to enable the effective utilization of such information to generate valid molecular models. This combination of factors has contributed to making the possibility of obtaining actual 3D structures by MS-based technologies (MS3D) a reality. Although approaches for achieving structure determination of unknown targets or assessing the dynamics of known structures may share similar reagents and development trajectories, they clearly involve distinctive experimental strategies, analytical concerns and interpretation paradigms. This Perspective offers a commentary on methods aimed at obtaining distance constraints for the modeling of full-fledged structures while highlighting common elements, salient distinctions and complementary capabilities exhibited by methods used in dynamics studies. We discuss critical factors to be addressed for completing effective structural determinations and expose possible pitfalls of chemical methods. We survey programs developed for facilitating the interpretation of experimental data and discuss possible computational strategies for translating sparse spatial constraints into all-atom models. Examples are provided to illustrate how the concerted application of very diverse probing techniques can lead to the solution of actual biological systems.

Targeted 18O-labeling for improved proteomic analysis of carbonylated peptides by mass spectrometry

Proteomic characterization of carbonylated amino acid sites currently relies on confidently matching tandem mass spectra (MS(2)) to peptides within a sequence database. Although effective to some degree, reliable proteomic characterization of carbonylated peptides using this approach remains a challenge needing new, complementary solutions. To this end, we developed a method based on partial (18)O-labeling of reactive carbonyl modifications, which produces a unique isotope signature in mass spectra of carbonylated peptides and enables their detection without reliance on matching MS(2) spectra to a peptide sequence. Key to our method were optimized measures for eliminating trypsin-catalyzed incorporation of (18)O at peptide C-termini, and for stabilizing the incorporated (18)O within the carbonyl modification to prevent its loss during liquid chromatography separation. Applying our method to a rat skeletal muscle homogenate treated with the carbonyl modification 4-hyroxynonenal (4-HNE), we demonstrated its compatibility with solid-phase hydrazide enrichment of carbonylated peptides from complex mixtures. Additionally, we demonstrated the value of (18)O isotope signatures for confirming HNE-modified peptide sequences matched via sequence database searching, and identifying modified peptides missed by MS(2) and/or sequence database searching. Combining our (18)O-labeling method with a customized automated software script, we systematically evaluated for the first time the efficiency of MS(2) and sequence database searching for identifying HNE-modified peptides. We estimated that less than half of the modified peptides selected for MS(2) were successfully identified. Collectively, our method and software should provide valuable new tools for investigators studying protein carbonylation via mass spectrometry-based proteomics.

Altered retinoic acid metabolism in diabetic mouse kidney identified by O isotopic labeling and 2D mass spectrometry

BACKGROUND

Numerous metabolic pathways have been implicated in diabetes-induced renal injury, yet few studies have utilized unbiased systems biology approaches for mapping the interconnectivity of diabetes-dysregulated proteins that are involved. We utilized a global, quantitative, differential proteomic approach to identify a novel retinoic acid hub in renal cortical protein networks dysregulated by type 2 diabetes.

METHODOLOGY/PRINCIPAL FINDINGS

Total proteins were extracted from renal cortex of control and db/db mice at 20 weeks of age (after 12 weeks of hyperglycemia in the diabetic mice). Following trypsinization, (18)O- and (16)O-labeled control and diabetic peptides, respectively, were pooled and separated by two dimensional liquid chromatography (strong cation exchange creating 60 fractions further separated by nano-HPLC), followed by peptide identification and quantification using mass spectrometry. Proteomic analysis identified 53 proteins with fold change >or=1.5 and p<or=0.05 after Benjamini-Hochberg adjustment (out of 1,806 proteins identified), including alcohol dehydrogenase (ADH) and retinaldehyde dehydrogenase (RALDH1/ALDH1A1). Ingenuity Pathway Analysis identified altered retinoic acid as a key signaling hub that was altered in the diabetic renal cortical proteome. Western blotting and real-time PCR confirmed diabetes-induced upregulation of RALDH1, which was localized by immunofluorescence predominantly to the proximal tubule in the diabetic renal cortex, while PCR confirmed the downregulation of ADH identified with mass spectrometry. Despite increased renal cortical tissue levels of retinol and RALDH1 in db/db versus control mice, all-trans-retinoic acid was significantly decreased in association with a significant decrease in PPARbeta/delta mRNA.

CONCLUSIONS/SIGNIFICANCE

Our results indicate that retinoic acid metabolism is significantly dysregulated in diabetic kidneys, and suggest that a shift in all-trans-retinoic acid metabolism is a novel feature in type 2 diabetic renal disease. Our observations provide novel insights into potential links between altered lipid metabolism and other gene networks controlled by retinoic acid in the diabetic kidney, and demonstrate the utility of using systems biology to gain new insights into diabetic nephropathy.

On-plate enrichment of glycopeptides by using boronic acid functionalized gold-coated Si wafer

Boronic acid functionalized gold-coated Si wafer has been used as MALDI plate to isolate and enrich glycopeptides for MS analysis. This on-plate enrichment strategy offers good benefits due to the combination of specific selectivity through enrichment and direct manipulation on the wafer. First, solution transfer and eluting steps required in conventional enrichment strategies are not needed any more, thereby reducing sample loss during these steps. Second, the LODs of glycopeptides have been increased by two orders of magnitude. Third, non-specific bindings have not been detected even when non-glycopeptides are 100 times more than glycopeptides. Furthermore, the recovery of glycopeptide is up to 65.8% and glycopeptides even can be sensitively detected in the presence of 200 mM ammonium bicarbonate or physiological buffer PBS.

Optimization and quality assessment of the post-digestion 18O labeling based on urea for protein denaturation by HPLC/ESI-TOF mass spectrometry

The post-digestion (18)O labeling method decouples protein digestion and peptide labeling. This method allows labeling conditions to be optimized separately and increases labeling efficiency. A common method for protein denaturation in proteomics is the use of urea. Though some previous studies have used urea-based protein denaturation before post-digestion (18)O labeling, the optimal (18)O labeling conditions in this case have not been yet reported. Present study investigated the effects of urea concentration and pH on the labeling efficiency and obtained an optimized protocol. It was demonstrated that urea inhibited (18)O incorporation depending on concentration. However, a urea concentration between 1 and 2M had minimal effects on labeling. It was also demonstrated that the use of FA to quench the digestion reaction severely affected the labeling efficiency. This study revealed the reason why previous studies gave different optimal pH for labeling. They neglect the effects of different digestion conditions on the labeling conditions. Excellent labeling quality was obtained at the optimized conditions using urea 1-2 M and pH 4.5, 98.4+/-1.9% for a standard protein mixture and 97.2+/-6.2% for a complex biological sample. For a 1:1 mixture analysis of the (16)O- and (18)O-labeled peptides from the same protein sample, the average abundance ratios reached 1.05+/-0.31, demonstrating a good quantitation quality at the optimized conditions. This work will benefit other researchers who pair urea-based protein denaturation with a post-digestion (18)O labeling method.

Proteomics of plant pathogenic fungi

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

Proteomic analysis of shear stress-mediated protection from TNF-alpha in endothelial cells

Previous studies have shown that physiological levels of shear stress can protect endothelial cells (ECs) from apoptotic stimuli. Here, we differentiate between acute and chronic protection and demonstrate the use of proteomic technologies to uncover mechanisms associated with chronic protection of ECs. We hypothesized that changes in abundance of proteins associated with the TNF-alpha signaling cascade orchestrate shear stress-mediated protection from TNF-alpha when cells are preconditioned with shear prior to the exposure of apoptotic stimuli. Detection of cleaved caspase 3 through Western blot analysis confirmed chronic shear stress-mediated protection from TNF-alpha. In the presence of the nitric oxide synthase inhibitor, LNMA (N(omega)-monomethyl-l-arginine), chronic protection remained. Treatment with a de novo protein synthesis inhibitor, cycloheximide, eliminated this protective effect. Isotopic-labeling experiments, coupled with LC-MS/MS (liquid chromatography-tandem mass spectrometry) of isolated components of the TNF-alpha pathway revealed that CARD9, a known activator of the NF-kappaB pathway, was increased (60%) in sheared cells versus nonsheared cells. This result was confirmed through Western blot analysis. Our data suggest that de novo formation of proteins is required for protection from TNF-alpha in ECs chronically exposed to shear stress, and that CARD9 is a candidate protein in this response.

Quantitative analysis of glycation sites on human serum albumin using (16)O/(18)O-labeling and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry

BACKGROUND

One of the long term complications of diabetes is the non-enzymatic addition of glucose to proteins in blood, such as human serum albumin (HSA), which leads to the formation of an Amadori product and advanced glycation end products (AGEs). This study uses (16)O/(18)O-labeling and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to provide quantitative data on the extent of modification that occurs in the presence of glucose at various regions in the structure of minimally glycated HSA.

METHODS

Normal HSA, with no significant levels of glycation, was digested by various proteolytic enzymes in the presence of water, while a similar sample containing in vitro glycated HSA was digested in (18)O-enriched water. These samples were then mixed and the (16)O/(18)O ratios were measured for peptides in each digest. The values obtained for the (16)O/(18)O ratios of the detected peptides for the mixed sample were used to determine the degree of modification that occurred in various regions of glycated HSA.

RESULTS

Peptides containing arginines 114, 81, or 218 and lysines 413, 432, 159, 212, or 323 were found to have (16)O/(18)O ratios greater than a cut off value of 2.0 (i.e., a cut off value based on results noted when using only normal HSA as a reference). A qualitative comparison of the (16)O- and (18)O-labeled digests indicated that lysines 525 and 439 also had significant degrees of modification. The modifications that occurred at these sites were variations of fructosyl-lysine and AGEs which included 1-alkyl-2-formyl-3,4-glycoyl-pyrole and pyrraline.

CONCLUSIONS

Peptides containing arginine 218 and lysines 212, 413, 432, and 439 contained high levels of modification and are also present near the major drug binding sites on HSA. This result is clinically relevant because it suggests the glycation of HSA may alter its ability to bind various drugs and small solutes in blood.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

Plasma membrane proteomics and its application in clinical cancer biomarker discovery

Plasma membrane proteins that are exposed on the cell surface have important biological functions, such as signaling into and out of the cells, ion transport, and cell-cell and cell-matrix interactions. The expression level of many of the plasma membrane proteins involved in these key functions is altered on cancer cells, and these proteins may also be subject to post-translational modification, such as altered phosphorylation and glycosylation. Additional protein alterations on cancer cells confer metastatic capacities, and some of these cell surface proteins have already been successfully targeted by protein drugs, such as human antibodies, that have enhanced survival of several groups of cancer patients. The combination of novel analytical approaches and subcellular fractionation procedures has made it possible to study the plasma membrane proteome in more detail, which will elucidate cancer biology, particularly metastasis, and guide future development of novel drug targets. The technical advances in plasma membrane proteomics and the consequent biological revelations will be discussed herein. Many of the advances have been made using cancer cell lines, but because the main goal of this research is to improve individualized treatment and increase cancer patient survival, further development is crucial to direct analysis of clinically relevant patient samples. These efforts include optimized specimen handling and preparation as well as improved proteomics platforms. Identification of potentially useful proteomics-based biomarkers must be validated in larger, well defined retrospective and prospective clinical studies, and these combined efforts should result in identification of biomarkers that will greatly improve early detection, prognosis, and prediction of treatment response.

Tandem 18O stable isotope labeling for quantification of N-glycoproteome

A new strategy using tandem (18)O stable isotope labeling (TOSIL) to quantify the N-glycosylation site occupancy is reported. Three heavy oxygen atoms are introduced into N-glycosylated peptides: two (18)O atoms are incorporated into the carboxyl terminal of all peptides during a tryptic digestion, and the third (18)O atom is incorporated into the N-glycosylation site of asparagines-linked sugar chains specifically via a N-glycosidase F (PNGase F)-mediated hydrolysis. Comparing samples treated in H(2)(18)O and samples treated in H(2)(16)O, a unique mass shift of 6 Da can be shown for N-glycosylated peptide with single glycosylation site, which could be easily distinguished from those nonglycosite peptide pairs with a mass difference of 4 Da only. The relative quantities of N-glycosylated and its parent protein-levels were obtained simultaneous by measuring the intensity ratios of (18)O/(16)O for glycosylated (6 Da) and for nonglycosylated (4 Da) peptides, respectively. Thus, a comparison of these two ratios can be utilized to evaluate the changes of occupancy of N-glycosylation at specific sites between healthy and diseased individuals. The TOSIL approach yielded good linearity in quantitative response within 10-fold dynamic range with the correlation coefficient r(2) > 0.99. The standard deviation (SD) ranged from 0.06 to 0.21, for four glycopeptides from two model glycoproteins. Furthermore, serums from a patient with ovarian cancer and healthy individual were used as test examples to validate the novel TOSIL method. A total of 86 N-glycosylation sites were quantified and N-glycosylation levels of 56 glycopeptides showed significant changes. Most changes in N-glycosylation at specific sites have the same trends as those of protein expression levels; however, the occupancies of three N-glycosylation sites were significantly changed with no change in proteins levels.

Quantitative serum proteomics using dual stable isotope coding and nano LC-MS/MSMS

Stable isotope coding technique in combination with mass spectrometry has emerged as a powerful tool to accurately identify and differentially quantify proteins within complex protein mixtures. We present a novel methodology to increase the yield of quantified proteins while maintaining a high stable-isotopic labeling efficacy. With this approach, intact proteins in complex biological sample such as sera are labeled with the designated dual stable isotope coding (DSIC) systems. In brief, intact proteins are coded sequentially with acrylamide to label Cysteine residues (Cys) and with succinic anhydride to label Lysine residues (Lys). Protein samples coded with this dual stable isotope are subjected to an online 2D-HPLC fractionation. The resolved protein fractions are individually digested with trypsin and analyzed with nano LC-MS/MSMS. Our results show that the DSIC labeling efficiency is 100% for Cysteine (Cys) labeled with acrylamide and 98% for Lysine (Lys) labeled with succinic anhydride. A comparative analysis of DSIC labeling and single labeling of Cysteine residues was made. Analysis of an entire anion-exchange chromatography subfraction of sera yielded 165 identified proteins (criteria: error rate <5% and unique peptides >or=2), 104 of which were quantified using the single labeling method (i.e., Cysteine acrylamide labeling only). In contrast, using same criteria for identification, a total 185 proteins were identified and 174 proteins were quantified using the DSIC labeling technique.

Yeast expression proteomics by high-resolution mass spectrometry

Comprehensive analysis of yeast as a model system requires to reliably determine its composition. Systematic approaches to globally determine the abundance of RNAs have existed for more than a decade and measurements of mRNAs are widely used as proxies for detecting changes in protein abundance. In contrast, methodologies to globally quantitate proteins are only recently becoming available. Such experiments are essential as proteins mediate the majority of biological processes and their abundance does not always correlate well with changes in gene expression. Particularly translational and post-translational controls contribute majorly to regulation of protein abundance, for example in heat shock stress response. The development of new sample preparation methods, high-resolution mass spectrometry and novel bioinfomatic tools close this gap and allow the global quantitation of the yeast proteome under different conditions. Here, we provide background information on proteomics by mass-spectrometry and describe the practice of a comprehensive yeast proteome analysis.

A universal strategy for development of a method for absolute quantification of therapeutic monoclonal antibodies in biological matrices using differential dimethyl labeling coupled with ultra performance liquid chromatography-tandem mass spectrometry

Although the strategic use of enzymatic digestion combined with isotope dilution mass spectrometry has been increasingly developed and used for the absolute quantification of therapeutic and endogenous proteins in the biopharmaceutical industry over the past several years, the lack of an appropriate internal standard has become the rate-limiting step in the development of a standardized analytical approach to provide bioanalytical support for both preclinical and clinical studies. In this study, we present a universal strategy for fast development and validation (within 1-2 weeks) of a method for absolute quantification of a therapeutic monoclonal antibody in biological matrices using differential dimethyl labeling coupled with UPLC-MS/MS. Differential dimethyl labeling of tryptic peptides generated from the purified therapeutic monoclonal antibody and those derived from proteins in cynomolgus monkey serum with either d(2)- or d(0)-formaldehyde provided a fast, cost-effective, and standardized approach to generate internal standards for any surrogate peptides that are used to quantify the therapeutic monoclonal antibody in biological matrices. This labeling reaction employs inexpensive and commercially available reagents, d(0)- or d(2)-formaldehyde, to globally label the N-terminus and epsilon-amino group of Lys in a peptide via reductive amination. Moreover, the process is simple, relatively fast (<2 h reaction time), specific, and quantitative under mild reaction conditions. The chromatographic run time is 6 min per sample. The linearity of the assay for the selected monoclonal antibody was established from 1.00 to 1000 mug/mL with accuracy and precision within 15% at all concentrations. The intraday and interday assay accuracy (%RE) and coefficient of variations (CV%) are all within 15% for all QCs (2.00, 4.00, 20.0, 100, 750 mug/mL) prepared in three different serum pools from male and female cynomolgus monkeys.

Temporal proteome and lipidome profiles reveal hepatitis C virus-associated reprogramming of hepatocellular metabolism and bioenergetics

Proteomic and lipidomic profiling was performed over a time course of acute hepatitis C virus (HCV) infection in cultured Huh-7.5 cells to gain new insights into the intracellular processes influenced by this virus. Our proteomic data suggest that HCV induces early perturbations in glycolysis, the pentose phosphate pathway, and the citric acid cycle, which favor host biosynthetic activities supporting viral replication and propagation. This is followed by a compensatory shift in metabolism aimed at maintaining energy homeostasis and cell viability during elevated viral replication and increasing cellular stress. Complementary lipidomic analyses identified numerous temporal perturbations in select lipid species (e.g. phospholipids and sphingomyelins) predicted to play important roles in viral replication and downstream assembly and secretion events. The elevation of lipotoxic ceramide species suggests a potential link between HCV-associated biochemical alterations and the direct cytopathic effect observed in this in vitro system. Using innovative computational modeling approaches, we further identified mitochondrial fatty acid oxidation enzymes, which are comparably regulated during in vitro infection and in patients with histological evidence of fibrosis, as possible targets through which HCV regulates temporal alterations in cellular metabolic homeostasis.

Current technological challenges in biomarker discovery and validation

In this review we will give an overview of the issues related to biomarker discovery studies with a focus on liquid chromatography-mass spectrometry (LC-MS) methods. Biomarker discovery is based on a close collaboration between clinicians, analytical scientists and chemometritians/statisticians. It is critical to define the final purpose of a biomarker or biomarker pattern at the onset of the study and to select case and control samples accordingly. This is followed by designing the experiment, starting with the sampling strategy, sample collection, storage and separation protocols, choice and validation of the quantitative profiling platform followed by data processing, statistical analysis and validation workflows. Biomarker candidates that result after statistical validation should be submitted for further validation and, ideally, be connected to the disease mechanism after their identification. Since most discovery studies work with a relatively small number of samples, it is necessary to assess the specificity and sensitivity of a given biomarker-based assay in a larger set of independent samples, preferably analyzed at another clinical center. Targeted analytical methods of higher throughput than the original discovery method are needed at this point and LC-tandem mass spectrometry is gaining acceptance in this field. Throughout this review, we will focus on possible sources of variance and how they can be assessed and reduced in order to avoid false positives and to reduce the number of false negatives in biomarker discovery research.

Methods and algorithms for relative quantitative proteomics by mass spectrometry

Protein quantitation by mass spectrometry (MS) is attractive since it is possible to obtain both the identification and quantitative values of novel proteins and their posttranslational modifications in one experiment. In contrast, protein arrays only provide quantitative values of targeted proteins and their modifications. There are an overwhelming number of quantitative mass spectrometry (MS) methods for protein and peptide quantitation. The aim here is to provide an overview of the most common MS-based quantitative methods used in the proteomics field and discuss the computational algorithms needed for the robust quantitation of proteins, peptides, and their posttranslational modifications.

Overview of quantitative LC-MS techniques for proteomics and activitomics

LC-MS is a useful technique for protein and peptide quantification. In addition, as a powerful tool for systems biology research, LC-MS can also be used to quantify post-translational modifications and metabolites that reflect biochemical pathway activity. This review discusses the different analytical techniques that use LC-MS for the quantification of proteins, their modifications and activities in a multiplex manner.