Related Articles

Notch Signaling has been demonstrated to have a central role in Glioblastoma (GBM) Cancer Stem Cells (CSCs) and we have demonstrated recently that Notch pathway blockade by γ-secretase inhibitor (GSI) depletes GBM CSCs and prevents tumor propagation both in vitro and in vivo. In order to understand the proteome alterations involved in this transformation, a dose-dependent quantitative mass spectrometry (MS) based proteomic study has been performed based on global proteome profiling and a target verification phase where both Immunoassay and a Multiple Reaction Monitoring (MRM) assay are employed. The selection of putative protein candidates for confirmation poses a challenge due to the large number of identifications from the discovery phase. A multilevel filtering strategy together with literature mining is adopted to transmit the most confident candidates along the pipeline. Our results indicate that treating GBM CSCs with GSI induces a phenotype transformation towards non-tumorigenic cells with decreased proliferation and increased differentiation, as well as elevated apoptosis. Suppressed glucose metabolism and attenuated NFR2-mediated oxidative stress response are also suggested from our data, possibly due to their crosstalk with Notch Signaling. Overall, this quantitative proteomic based dose-dependent work complements our current understanding of the altered signaling events occurring upon the treatment of GSI in GBM CSCs.

Proteomics technologies have revolutionized cell biology and biochemistry by providing powerful new tools to characterize complex proteomes, multiprotein complexes and post-translational modifications. Although proteomics technologies could address important problems in clinical and translational cancer research, attempts to use proteomics approaches to discover cancer biomarkers in biofluids and tissues have been largely unsuccessful and have given rise to considerable skepticism. The National Cancer Institute has taken a leading role in facilitating the translation of proteomics from research to clinical application, through its Clinical Proteomic Technologies for Cancer. This article highlights the building of a more reliable and efficient protein biomarker development pipeline that incorporates three steps: discovery, verification and qualification. In addition, we discuss the merits of multiple reaction monitoring mass spectrometry, a multiplex targeted proteomics platform, which has emerged as a potentially promising, high-throughput protein biomarker measurements technology for preclinical ‘verification’.

Purpose

The Quantitative Assay Database (QuAD), http://proteome.moffitt.org/QUAD/, facilitates widespread implementation of quantitative mass spectrometry in cancer biology and clinical research through sharing of methods and reagents for monitoring protein expression and modification.

Experimental Design

Liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM) assays are developed using SDS-PAGE fractionated lysates from cancer cell lines. Pathway maps created using GeneGO Metacore provide the biological relationships between proteins and illustrate concepts for multiplexed analysis; each protein can be selected to examine assay development at the protein and peptide level.

Results

The coupling of SDS-PAGE and LC-MRM screening has been used to detect 876 peptides from 218 cancer-related proteins in model systems including colon, lung, melanoma, leukemias, and myeloma, which has led to the development of 95 quantitative assays including stable-isotope labeled peptide standards. Methods are published online and peptide standards are made available to the research community. Protein expression measurements for heat shock proteins, including a comparison with ELISA and monitoring response to the HSP90 inhibitor, 17-DMAG, are used to illustrate the components of the QuAD and its potential utility.

Conclusions and Clinical Relevance

This resource enables quantitative assessment of protein components of signaling pathways and biological processes and holds promise for systematic investigation of treatment responses in cancer.

Multiple reaction monitoring mass spectrometry (MRM-MS) is a technique for high-sensitivity targeted analysis. In proteomics, MRM-MS can be used to monitor and quantify a peptide based on the production of expected fragment peaks from the selected peptide precursor ion. The choice of which fragment ions to monitor in order to achieve maximum sensitivity in MRM-MS can potentially be guided by existing MS/MS spectra. However, because the majority of discovery experiments are performed on ion trap platforms, there is concern in the field regarding the generalizability of these spectra to MRM-MS on a triple quadrupole instrument. In light of this concern, many operators perform an optimization step to determine the most intense fragments for a target peptide on a triple quadrupole mass spectrometer. We have addressed this issue by targeting, on a triple quadrupole, the top six y-ion peaks from ion trap-derived consensus library spectra for 258 doubly charged peptides from three different sample sets and quantifying the observed elution curves. This analysis revealed a strong correlation between the y-ion peak rank order and relative intensity across platforms. This suggests that y-type ions obtained from ion trap-based library spectra are well-suited for generating MRM-MS assays for triple quadrupoles and that optimization is not required for each target peptide.

Multiple reaction monitoring mass spectrometry (MRM-MS) with stable isotope dilution (SID) is increasingly becoming a widely accepted assay for the quantification of proteins and peptides. These assays have shown great promise in relatively high throughput verification of candidate biomarkers. While the use of MRM-MS assays is well established in the small molecule realm, their introduction and use in proteomics is relatively recent. As such, statistical and computational methods for the analysis of MRM-MS data from proteins and peptides are still being developed. Based on our extensive experience with analyzing a wide range of SID-MRM-MS data, we set forth a methodology for analysis that encompasses significant aspects ranging from data quality assessment, assay characterization including calibration curves, limits of detection (LOD) and quantification (LOQ), and measurement of intra- and interlaboratory precision. We draw upon publicly available seminal datasets to illustrate our methods and algorithms.

RP-122

Peptide quantitation using Multiple Reaction Monitoring (MRM) has been established as an important methodology for biomarker verification andvalidation.This requires high throughput combined with high sensitivity to analyze potentially thousands of target peptides in each sample.Dynamic MRM allows the system to only acquire the required MRMs of the peptide during a retention window corresponding to when each peptide is eluting. This reduces the number of concurrent MRM and therefore improves quantitation and sensitivity. MRM Selector allows the user to generate an MRM transition list with retention time information from discovery data obtained on a QTOF MS system.This list can be directly imported into the triple quadrupole acquisition software.However, situations can exist where a) the list of MRMs contain an excess of MRM transitions allowable under the ideal acquisition conditions chosen ( allowing for cycle time and chromatography conditions), or b) too many transitions in a certain retention time region which would result in an unacceptably low dwell time and cycle time.A new tool - MRM viewer has been developed to help users automatically generate multiple dynamic MRM methods from a single MRM list.In this study, a list of 3293 MRM transitions from a human plasma sample was compiled.A single dynamic MRM method with 3293 transitions results in a minimum dwell time of 2.18ms.Using MRM viewer we can generate three dynamic MRM methods with a minimum dwell time of 20ms which can give a better quality MRM quantitation.This tool facilitates both high throughput and high sensitivity for MRM quantitation.

Multiple Reaction Monitoring (MRM), commonly employed for the mass spectrometric detection of small molecules, is rapidly gaining ground in proteomics. Its high sensitivity and specificity makes this targeted approach particularly useful when sample throughput or proteome coverage limits global studies. Existing tools to design MRM assays rely exclusively on theoretical predictions, or combine them with previous observations on the same type of sample. The additional mass spectrometric experimentation this requires can pose significant demands on time and material. To overcome these challenges, a new MRM worksheet was introduced into The Global Proteome Machine database (GPMDB) that provided all of the information needed to design MRM transitions based solely on archived observations made by other researchers in previous experiments. This required replacing the precursor ion intensity by the number of peptide observations, which proved to be an adequate substitute if peptides did not occur in multiple forms. While the absence of collision energy information proved largely inconsequential, successful prediction of unique transitions depended on the type of fragment ion involved. The design of MRM assays for iTRAQ-labeled tryptic peptides obtained from human platelet proteins demonstrated the usefulness of the MRM worksheet also for quantitative applications. This workflow, which relies exclusively on experimental observations stored in data repositories, therefore represents an attractive alternative for the prediction of MRM transitions prior to experimental validation and optimization.

Discovery phase proteomics has generated numerous candidate protein markers for a wide variety of biological processes and disease types. To assess the viability of these protein expression changes requires the analysis of a larger number of samples, preferably in a targeted fashion, and hence the use of MRM has become routine. Specific peptides from the proteins of interest are targeted as surrogate markers for that protein, in a screening assay using a triple quadrupole mass spectrometer operating in the multiple reaction monitoring (MRM) mode. The MRM method which is used to detect specific ions from target molecules has the capability to simultaneously quantify large numbers of proteins with good limits of quantification (LOQ) and linear dynamic range. In this mode of analysis the sensitivity and dynamic range are improved and providing sufficient data points across a chromatographic peak are recorded then quantitation is accurate (CV 5-10%). This high sensitivity coupled with the specificity/selectivity afforded by MRM transitions allows extensive panels of peptide biomarkers to be monitored in a single experiment from complex mixtures. We will describe the development and implementation of novel high-sensitivity MRM assays for large scale peptide quantification.

Protein quantification with liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM) has emerged as a powerful platform for assessing panels of biomarkers. In this study, direct infusion, using automated, chip-based nanoelectrospray ionization, coupled with MRM (DI-MRM) is used for protein quantification. Removal of the LC separation step increases the importance of evaluating the ratios between the transitions. Therefore, the effects of solvent composition, analyte concentration, spray voltage, and quadrupole resolution settings on fragmentation patterns have been studied using peptide and protein standards. After DI-MRM quantification was evaluated for standards, quantitative assays for the expression of heat shock proteins (HSPs) were translated from LC-MRM to DI-MRM for implementation in cell line models of multiple myeloma. Requirements for DI-MRM assay development are described. Then, the two methods are compared; criteria for effective DI-MRM analysis are reported based on the analysis of HSP expression in digests of whole cell lysates. The increased throughput of DI-MRM analysis is useful for rapid analysis of large batches of similar samples, such as time course measurements of cellular responses to therapy.

Verification of candidate biomarkers relies upon specific, quantitative assays optimized for selective detection of target proteins, and is increasingly viewed as a critical step in the discovery pipeline that bridges unbiased biomarker discovery to preclinical validation. Although individual laboratories have demonstrated that multiple reaction monitoring (MRM) coupled with isotope dilution mass spectrometry can quantify candidate protein biomarkers in plasma, reproducibility and transferability of these assays between laboratories have not been demonstrated. We describe a multilaboratory study to assess reproducibility, recovery, linear dynamic range and limits of detection and quantification of multiplexed, MRM-based assays, conducted by NCI-CPTAC. Using common materials and standardized protocols, we demonstrate that these assays can be highly reproducible within and across laboratories and instrument platforms, and are sensitive to low µg/ml protein concentrations in unfractionated plasma. We provide data and benchmarks against which individual laboratories can compare their performance and evaluate new technologies for biomarker verification in plasma.

Multiple reaction monitoring mass spectrometry (MRM-MS) is a targeted analysis method that has been increasingly viewed as an avenue to explore proteomes with unprecedented sensitivity and throughput. We have developed a software tool, called MaRiMba, to automate the creation of explicitly defined MRM transition lists required to program triple quadrupole mass spectrometers in such analyses. MaRiMba creates MRM transition lists from downloaded or custom-built spectral libraries, restricts output to specified proteins or peptides, and filters based on precursor peptide and product ion properties. MaRiMba can also create MRM lists containing corresponding transitions for isotopically heavy peptides, for which the precursor and product ions are adjusted according to user specifications. This open-source application is operated through a graphical user interface incorporated into the Trans-Proteomic Pipeline, and it outputs the final MRM list to a text file for upload to MS instruments. To illustrate the use of MaRiMba, we used the tool to design and execute an MRM-MS experiment in which we targeted the proteins of a well-defined and previously published standard mixture.

Reaction monitoring mass spectrometry has emerged as a powerful tool for targeted detection and quantification of proteins in clinical samples. Here, we report the use of gel electrophoresis for protein fractionation and liquid chromatography coupled to multiple reaction monitoring mass spectrometry (LC-MRM) screening for quantitative analysis of components from the Wnt/β-catenin signaling pathway, which contributes to colon tumor formation and progression. In silico tools are used to design LC-MRM screens for each target protein. Following successful peptide detection, stable isotope labeled peptides are synthesized and developed as internal standards. Then, the assays are implemented in colon cancer cell lines to achieve detection in minimal amounts of cells, compatible with direct translation to clinical specimens. Selected assays are compared with qualitative results from immunoblotting (Westerns) and translated to individual frozen colon tissue sections and laser capture microdissected tumor cells. This LC-MRM platform has been translated from in vitro models to clinical specimens, forming the basis for future experiments in patient assessment.

Background

The multifunctional glycoprotein clusterin has been associated with late-onset Alzheimer’s disease (AD). Further investigation to define the role of clusterin in AD phenotypes would be aided by the development of techniques to quantify level, potential post-translational modifications, and isoforms of clusterin. We have developed a quantitative technique based on multiple reaction monitoring (MRM) mass spectrometry to measure clusterin in human postmortem brain tissues.

Results

A stable isotope-labeled concatenated peptide (QconCAT) bearing selected peptides from clusterin was expressed with an in vitro translation system and purified. This clusterin QconCAT was validated for use as an internal standard for clusterin quantification using MRM mass spectrometry. Measurements were performed on the human postmortem frontal and temporal cortex from control and severe AD cases. During brain tissues processing, 1% SDS was used in the homogenization buffer to preserve potential post-translational modifications of clusterin. However, MRM quantifications in the brain did not suggest phosphorylation of Thr393, Ser394, and Ser396 residues reported for clusterin in serum. MRM quantifications in the frontal cortex demonstrated significantly higher (P < 0.01) level of clusterin in severe AD group (39.1 ± 9.1 pmol/mg tissue protein) in comparison to control group (25.4 ± 4.4 pmol/mg tissue protein). In the temporal cortex, the clusterin levels were not significantly different, 29.0 ± 7.9 pmol/mg tissue protein and 28.0 ± 8.4 pmol/mg tissue protein in control and severe AD groups, respectively.

Conclusions

The proposed protocol is a universal quantitative technique to assess expression level of clusterin. It is expected that application of this protocol to quantification of various clusterin isoforms and potential post-translational modifications will be helpful in addressing the role of clusterin in AD.

Lung cancer is the leading cause of cancer deaths worldwide. Clinically, the treatment of non-small cell lung cancer (NSCLC) can be improved by the early detection and risk screening among population. To meet this need, here we describe the application of extensive peptide level fractionation coupled with label free quantitative proteomics for the discovery of potential serum biomarkers for lung cancer, and the usage of Tissue microarray analysis (TMA) and Multiple reaction monitoring (MRM) assays for the following up validations in the verification phase. Using these state-of-art, currently available clinical proteomic approaches, in the discovery phase we confidently identified 647 serum proteins, and 101 proteins showed a statistically significant association with NSCLC in our 18 discovery samples. This serum proteomic dataset allowed us to discern the differential patterns and abnormal biological processes in the lung cancer blood. Of these proteins, Alpha-1B-glycoprotein (A1BG) and Leucine-rich alpha-2-glycoprotein (LRG1), two plasma glycoproteins with previously unknown function were selected as examples for which TMA and MRM verification were performed in a large sample set consisting about 100 patients. We revealed that A1BG and LRG1 were overexpressed in both the blood level and tumor sections, which can be referred to separate lung cancer patients from healthy cases.

Selected reaction monitoring (SRM), sometimes called multiple reaction monitoring (MRM), is becoming the tool of choice for targeted quantitative proteomics in the plant science community. Key to a successful SRM experiment is prior identification of the distinct peptides for the proteins of interest and the determination of the so-called transitions that can be programmed into an LC-MS/MS to monitor those peptides. The transition for a given peptide comprises the intact peptide m/z and a high intensity product ion that can be monitored at a characteristic retention time (RT). To aid the design of SRM experiments, several online tools and databases have been produced to help researchers select transitions for their proteins of interest, but many of these tools are limited to the most popular model organisms such as human, yeast, and mouse or require the experimental acquisition of local spectral libraries. In this paper we present MRMaid1, a web-based SRM assay design tool whose transitions are generated by mining the millions of identified peptide spectra held in the EBI’s PRIDE database. By using data from this large public repository, MRMaid is able to cover a wide range of species that can increase as the coverage of PRIDE grows. In this paper MRMaid transitions for 25 Arabidopsis thaliana proteins are evaluated experimentally, and found capable of quantifying 23 of these proteins. This performance was found to be comparable with the more time consuming approach of designing transitions using locally acquired orbitrap data, indicating that MRMaid is a valuable tool for targeted Arabidopsis proteomics.

We compared the reproducibility of multiple reaction monitoring (MRM) mass spectrometry-based peptide quantitation in tryptic digests from formalin-fixed, paraffin-embedded (FFPE) and frozen clear cell renal cell carcinoma tissues. The analyses targeted a candidate set of 114 peptides previously identified in shotgun proteomic analyses, of which 104 were detectable in FFPE and frozen tissue. Although signal intensities for MRM of peptides from FFPE tissue were on average 66% of those in frozen tissue, median coefficients of variation (CV) for measurements in FFPE and frozen tissues were nearly identical (18–20%). Measurements of lysine C-terminal peptides and arginine C-terminal peptides from FFPE tissue were similarly reproducible (19.5% and 18.3% median CV, respectively). We further evaluated the precision of MRM-based quantitation by analysis of peptides from the Her2 receptor in FFPE and frozen tissues from a Her2 overexpressing mouse xenograft model of breast cancer and in human FFPE breast cancer specimens. We obtained equivalent MRM measurements of HER2 receptor levels in FFPE and frozen mouse xenografts derived from HER2-overexpressing BT474 cells and HER2-negative Sum159 cells. MRM analyses of 5 HER2-positive and 5 HER-negative human FFPE breast tumors confirmed the results of immunohistochemical analyses, thus demonstrating the feasibility of HER2 protein quantification in FFPE tissue specimens. The data demonstrate that MRM analyses can be performed with equal precision on FFPE and frozen tissues and that lysine-containing peptides can be selected for quantitative comparisons, despite the greater impact of formalin fixation on lysine residues. The data further illustrate the feasibility of applying MRM to quantify clinically important tissue biomarkers in FFPE specimens.

As the study of protein biomarkers increases in importance, technical limitations to the detection of low-abundance proteins and high-throughput, high-precision quantitation remain to be overcome. The complexity and dynamic range of the plasma proteome makes the task of specific, quantitative detection even more challenging. Multiple reaction monitoring (MRM) capabilities of triple quadrupole MS systems have been explored as solutions to this challenge due to their well-known sensitivity and selectivity for components in complex matrices such as plasma. Recently, a suite of >100 MRMs representing ~50 plasma protein markers were monitored quantitatively in a single assay using the MRM-based technique showing detection of proteins down to the level of L-selectin (~1μg/mL) with minimal sample preparation and no peptide or protein standards for most of the plasma protein markers.1

As more extensive candidate biomarker panels are being identified, MRM assays will need to be more rapidly developed to verify the expression changes of these proteins across larger clinical sample sets. To do this, the unique combination of triple-quadrupole and ion-trapping capabilities of the hybrid triple quadrupole–linear ion trap mass spectrometer have been utilized. A strategy for rapid MRM assay development for larger-scale profiling and qualification of biomarker candidates without having to first prepare synthetic peptide standards is currently being investigated and involves a chemical labeling strategy to create global reference standards to enable quantitative comparisons between clinical samples. Single assays consisting of ~500s of MRM transitions have been developed for this rapid qualification phase, facilitated by intelligent use of retention time windows during an LC analysis, while maintaining an optimum number of data points for improved precision of peak area and quantitative profiling. This presentation will demonstrate the details of this workflow with human plasma examples.

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves, quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1-D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μl serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.

We report an innovative multiplexed liquid chromatography-multiple reaction monitoring/mass spectrometry (LC-MRM/MS)-based assay for rapidly measuring a large number of disease specific protein biomarkers in human serum. Furthermore, this approach uses stable isotope dilution methodology to reliably quantify candidate protein biomarkers. Human serum was diluted using a stable isotope labeled proteome (SILAP) standard prepared from the secretome of pancreatic cell lines, subjected to immunoaffinity removal of the most highly abundant proteins, trypsin digested, and analyzed by LC-MRM/MS. The method was found to be precise, linear, and specific for the relative quantification of 72 proteins when analyte response was normalized to the relevant internal standard (IS) from the SILAP. The method made it possible to determine statistically different concentrations for three proteins (cystatin M, IGF binding protein 7, and villin 2) in control and pancreatic cancer patient samples. This method proves the feasibility of using a SILAP standard in combination with stable isotope dilution LC-MRM/MS analysis of tryptic peptides to compare changes in the concentration of candidate protein biomarkers in human serum.

A number of successful multiple reaction monitoring (MRM)-directed MS/MS methods for protein characterization and quantification have been published over the past couple of years. These methods have been created either by the generation of in silico MRM transitions or from taking discovery data generated by automated MS/MS analysis and formulating MRM transitions from this. However, such a workflow, where a vast amount of discovery data needs to be searched for idealized MS/MS to target peptides, is difficult and time consuming. Automation of this would simplify the whole workflow, and allowing methods to be created smarter by utilizing the data of peptides that have been previously identified, provides a better chance of success.

In this poster we highlight one possible workflow for the processing of a number of database search results that were generated during proteomic analysis of a complex sample. Proteins identified as of potential interest in these results were then added to a MRM method-building list, and all MS/MS associated with those proteins were extracted from the general proteomic search results.

These MS/MS are then automatically processed to create instrument methods for MRM-directed MS/MS quantification. After analysis of the sample by these methods, the data are processed, both from a sequence identification and a chromatographic LC-MRM peak signal-to-noise perspective. These data are associated with the original proteomic workflow data, allowing visualization of the results and construction of a method that can then undergo validation.

w4-1

Proteomics experiments are designed to provide useful information about the biological system under study. As mass spectrometry technology and methodology have improved, many or most of these studies now focus on relative or absolute quantitation of proteins and their posttranslational modifications under more than one experimental condition in order to do this. The goal of this workshop is to provide an overview of possible proteomic strategies for relative or absolute quantitation of proteins that are suitable for a given purpose. We also hope to provide practical advice for experimental design and sample preparation for quantitative studies and characterization of posttranslational modifications. Issues to be covered include requirements for protein sequence coverage, discovery vs. directed (verification) approaches, strategies for chemical and metabolic labeling as well as label free methods, introduction to relevant informatics approaches for quantitation studies, and sample preparation and enrichment for posttranslational modification studies.

Background

Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.

Result

We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.

This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.

Conclusions

Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html

There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in quantitation, are associated with a high cost, long lead time, and are fraught with drawbacks (e.g. heterophilic antibodies, autoantibody interference, 'hook-effect').1 An alternative technique is affinity enrichment of peptides coupled with quantitative mass spectrometry, commonly referred to as SISCAPA (Stable Isotope Standards and Capture by Anti-Peptide Antibodies).2 In this technique, affinity enrichment of peptides with stable isotope dilution and detection by selected/multiple reaction monitoring mass spectrometry (SRM/MRM-MS) provides quantitative measurement of peptides as surrogates for their respective proteins. SRM/MRM-MS is well established for accurate quantitation of small molecules 3, 4 and more recently has been adapted to measure the concentrations of proteins in plasma and cell lysates.5-7 To achieve quantitation of proteins, these larger molecules are digested to component peptides using an enzyme such as trypsin. One or more selected peptides whose sequence is unique to the target protein in that species (i.e. "proteotypic" peptides) are then enriched from the sample using anti-peptide antibodies and measured as quantitative stoichiometric surrogates for protein concentration in the sample. Hence, coupled to stable isotope dilution (SID) methods (i.e. a spiked-in stable isotope labeled peptide standard), SRM/MRM can be used to measure concentrations of proteotypic peptides as surrogates for quantification of proteins in complex biological matrices. The assays have several advantages compared to traditional immunoassays. The reagents are relatively less expensive to generate, the specificity for the analyte is excellent, the assays can be highly multiplexed, enrichment can be performed from neat plasma (no depletion required), and the technique is amenable to a wide array of proteins or modifications of interest.8-13 In this video we demonstrate the basic protocol as adapted to a magnetic bead platform.

Background

The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the identified proteins through their association with interaction networks, biological pathways, analysis of the effect of post-translational modifications, and other protein-related information.

Results

In this paper, we present an integrative visualization methodology that allows combining experimentally produced proteomic features with protein meta-features, typically coming from meta-analysis tools and databases, in synthetic Proteomic Feature Maps. Using three proteomics analysis scenarios, we show that the proposed visualization approach is effective in filtering, navigating and interacting with the proteomics data in order to address visually challenging biological questions. The novelty of our approach lies in the ease of integration of any user-defined proteomic features in easy-to-comprehend visual representations that resemble the familiar 2D-gel images, and can be adapted to the user's needs. The main capabilities of the developed VIP software, which implements the presented visualization methodology, are also highlighted and discussed.

Conclusions

By using this visualization and the associated VIP software, researchers can explore a complex heterogeneous proteomics dataset from different perspectives in order to address visually important biological queries and formulate new hypotheses for further investigation. VIP is freely available at http://pelopas.uop.gr/~egian/VIP/index.html.

Multiple reaction monitoring (MRM) is a highly sensitive method of targeted mass spectrometry (MS) that can be used to selectively detect and quantify peptides based on the screening of specified precursor peptide-to-fragment ion transitions. MRM-MS sensitivity depends critically on the tuning of instrument parameters, such as collision energy and cone voltage, for the generation of maximal product ion signal. Although generalized equations and values exist for such instrument parameters, there is no clear indication that optimal signal can be reliably produced for all types of MRM transitions using such an algorithmic approach. To address this issue, we have devised a workflow functional on both Waters Quattro Premier and ABI 4000 QTRAP triple quadrupole instruments that allows rapid determination of the optimal value of any programmable instrument parameter for each MRM transition. Here, we demonstrate the strategy for the optimizations of collision energy and cone voltage, but the method could be applied to other instrument parameters, such as declustering potential, as well. The workflow makes use of the incremental adjustment of the precursor and product m/z values at the hundredth decimal place to create a series of MRM targets at different collision energies that can be cycled through in rapid succession within a single run, avoiding any run-to-run variability in execution or comparison. Results are easily visualized and quantified using the MRM software package Mr. M to determine the optimal instrument parameters for each transition.