A comparison of MS/MS-based, stable-isotope-labeled, quantitation performance on ESI-quadrupole TOF and MALDI-TOF/TOF mass spectrometers

Exploring Exercise- and Context-Induced Peptide Changes in Mice by Quantitative Mass Spectrometry

Recent research suggests that exercise may help facilitate abstinence from cocaine addiction, though the mechanisms are not well understood. In mice, wheel running accelerates the extinction of conditioned place preference (CPP) for cocaine, providing an animal model for evaluating potential neurological mechanisms. The objective of this study was to quantify dynamic changes in endogenous peptides in the amygdala and dentate gyrus of the hippocampus in mice exposed to a context paired with the effects of cocaine, and in response to exercise. Male C57BL/6J mice conditioned to cocaine were housed with or without running wheels for 30 days. Following a CPP test and final exposure to either a cocaine- or saline-associated context, peptides were measured in brain tissue extracts using label-free matrix-assisted laser desorption/ionization mass spectrometry (MS) and stable isotopic labeling with liquid chromatography and electrospray ionization MS. CPP in mice was significantly reduced with running, which correlated to decreased myelin basic protein derivatives in the dentate gyrus extracts, possibly reflecting increased unmyelinated granule neuron density. Exposure to a cocaine-paired context increased hemoglobin-derived peptides in runners and decreased an actin-derived peptide in sedentary animals. These results allowed us to characterize a novel set of biomarkers that are responsive to exercise in the hippocampus and in a cocaine-paired context in the amygdala.

The comparison of CHCA solvent compositions for improving LC-MALDI performance and its application to study the impact of aflatoxin B1 on the liver proteome of diabetes mellitus type 1 mice

In nanoflow liquid chromatography-matrix-assisted laser desorption/ionization tandem time-of-flight (nanoLC-MALDI-TOF/TOF) approaches, it is critical to directly apply small amounts of the sample elutes on the sample target using a nanoLC system due to its low flow rate of 200 ~ 300 nl/min. It is recommended to apply a sheath liquid containing a matrix with a several μL/min flow rate at the end of the nanoLC column to ensure a larger co-eluted droplet for more reproducible sample spotting and avoid the laborious task of post-manual matrix spotting. In this study, to achieve a better nanoLC-MALDI performance on sample spotting, we first compared α-Cyano-4-hydroxycinnamic acid (CHCA) solvent composition for efficiently concentrating nanoLC elutes on an anchor chip. The solvent composition of isopropanol (IPA): acetonitrile (ACN):acetone:0.1% Trifluoroacetic acid (TFA) (2:7:7:2) provided strong and homogeneous signals with higher peptide ion yields than the other solvent compositions. Then, nanoLC-MALDI-TOF/TOF was applied to study the impact of aflatoxin B1 on the liver proteome from diabetes mellitus type 1 mice. Aflatoxin B1 (AFB1), produced by Aspergillus flavus and Aspergillus parasiticus is a carcinogen and a known causative agent of liver cancer. To evaluate the effects of long-term exposure to AFB1 on type 1 diabetes mellitus (TIDM), the livers of T1DM control mice and mice treated with AFB1 were analyzed using isotope-coded protein labeling (ICPL)-based quantitative proteomics. Our results showed that gluconeogenesis, lipid, and oxidative phosphorylation mechanisms, normally elevated in T1DM, were disordered following AFB1 treatment. In addition, major urinary protein 1 (MUP1), an indicator of increased insulin sensitivity, was significantly decreased in the T1DM/AFB1 group and may have resulted in higher blood glucose levels compared to the T1DM group. These results indicate that T1DM patients should avoid the AFB1 intake, as they could lead to increased blood glucose levels and disorders of energy-producing mechanisms.

Microfluidic Superheating for Peptide Sequence Elucidation

Herein, we introduce microfluidic superheating as a new method for peptide fragmentation prior to mass spectrometric analysis. The superheating conditions were found to be stable up to 240 °C for more than 30 min without elevated pressure or boiling of the aqueous sample. As proof of principle, we exposed the peptides ACTH1-10 and OVA257-264 to various superheating conditions, causing different degrees of decomposition. Optimized superheating conditions resulted in the entire peptide ladder sequence of the y-ions, allowing the amino acid sequence to be deduced from a single-stage mass spectrum. Thus, obtaining information in the same quality as from tandem mass spectrometry can be achieved by a single superheating step.

A proteomic analysis of transplanted liver in a rat model of chronic rejection

BACKGROUND

Chronic rejection (CR) is an important cause of liver allograft failure. In the latter condition, re-transplantation of the liver (ReLT) is the only option for survival. Unfortunately, with the current state of knowledge, it is difficult to diagnose and treat early CR.

OBJECTIVE

To explore the biomarkers of the chronic rejection in orthotopic liver transplantation (OLT).

METHODS

A rat model of chronic liver allograft rejection was established, and the differential protein expression in chronic allograft rejection (CR) was analyzed by iTRAQ-MALDI-TOF/TOF.

RESULTS

Expression of sixty-two proteins was found to be significantly changed in CR rats. In the present study, CLU, Lcn2 and Krt19 were identified and quantified as early and reliable biomarkers for chronic rejection.

CONCLUSION

Analysis of differential protein expression by iTRAQ-MALDI-TOF/TOF is a potentially effective method to help understand the mechanism of CR in orthotopic liver transplantation. The proteins CLU, Lcn2 and Krt19 might be potential prognostic markers for predicting chronic rejection after liver transplantation.

Absolute quantification of norovirus capsid protein in food, water, and soil using synthetic peptides with electrospray and MALDI mass spectrometry

Norovirus infections are one of the most prominent public health problems of microbial origin in the U.S. and other industrialized countries. Surveillance is necessary to prevent secondary infection, confirm successful cleanup after outbreaks, and track the causative agent. Quantitative mass spectrometry, based on absolute quantitation with stable-isotope labeled peptides, is a promising tool for norovirus monitoring because of its speed, sensitivity, and robustness in the face of environmental inhibitors. In the current study, we present two new methods for the detection of the norovirus genogroup I capsid protein using electrospray and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. The peptide TLDPIEVPLEDVR was used to quantify norovirus-like particles down to 500 attomoles with electrospray and 100 attomoles with MALDI. With MALDI, we also demonstrate a detection limit of 1 femtomole and a quantitative dynamic range of 5 orders of magnitude in the presence of an environmental matrix effect. Due to the rapid processing time and applicability to a wide range of environmental sample types (bacterial lysate, produce, milk, soil, and groundwater), mass spectrometry-based absolute quantitation has a strong potential for use in public health and environmental sciences.

In-depth comparative proteomic analysis of yeast proteome using iTRAQ and SWATH based MS

SWATH is capable of quantifying proteins of lower abundance as compared to iTRAQ.

Optimization of plasma sample pretreatment for quantitative analysis using iTRAQ labeling and LC-MALDI-TOF/TOF

Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy.

Somatic mosaicism for the p.His1047Arg mutation in PIK3CA in a girl with mesenteric lipomatosis

We describe a patient who presented with a localized growth of mature fat tissue, which was surgically removed. MRI imaging identified diffuse increase in visceral adipose tissue. Targeted deep sequencing of the resected tissue uncovered a p.H1047R variant in PIK3CA, which was absent in blood. This report expands the phenotypic spectrum of mosaic PIK3CA mutations.

Post-translational modifications and mass spectrometry detection

In this review, we provide a comprehensive bibliographic overview of the role of mass spectrometry and the recent technical developments in the detection of post-translational modifications (PTMs). We briefly describe the principles of mass spectrometry for detecting PTMs and the protein and peptide enrichment strategies for PTM analysis, including phosphorylation, acetylation and oxidation. This review presents a bibliographic overview of the scientific achievements and the recent technical development in the detection of PTMs is provided. In order to ascertain the state of the art in mass spectrometry and proteomics methodologies for the study of PTMs, we analyzed all the PTM data introduced in the Universal Protein Resource (UniProt) and the literature published in the last three years. The evolution of curated data in UniProt for proteins annotated as being post-translationally modified is also analyzed. Additionally, we have undertaken a careful analysis of the research articles published in the years 2010 to 2012 reporting the detection of PTMs in biological samples by mass spectrometry.

Global relative quantification with liquid chromatography-matrix-assisted laser desorption ionization time-of-flight (LC-MALDI-TOF)--cross-validation with LTQ-Orbitrap proves reliability and reveals complementary ionization preferences

Quantitative LC-MALDI is an underrepresented method, especially in large-scale experiments. The additional fractionation step that is needed for most MALDI-TOF-TOF instruments, the comparatively long analysis time, and the very limited number of established software tools for the data analysis render LC-MALDI a niche application for large quantitative analyses beside the widespread LC-electrospray ionization workflows. Here, we used LC-MALDI in a relative quantification analysis of Staphylococcus aureus for the first time on a proteome-wide scale. Samples were analyzed in parallel with an LTQ-Orbitrap, which allowed cross-validation with a well-established workflow. With nearly 850 proteins identified in the cytosolic fraction and quantitative data for more than 550 proteins obtained with the MASCOT Distiller software, we were able to prove that LC-MALDI is able to process highly complex samples. The good correlation of quantities determined via this method and the LTQ-Orbitrap workflow confirmed the high reliability of our LC-MALDI approach for global quantification analysis. Because the existing literature reports differences for MALDI and electrospray ionization preferences and the respective experimental work was limited by technical or methodological constraints, we systematically compared biochemical attributes of peptides identified with either instrument. This genome-wide, comprehensive study revealed biases toward certain peptide properties for both MALDI-TOF-TOF- and LTQ-Orbitrap-based approaches. These biases are based on almost 13,000 peptides and result in a general complementarity of the two approaches that should be exploited in future experiments.

Plasma proteomics can discriminate isolated early from dual responses in asthmatic individuals undergoing an allergen inhalation challenge

PURPOSE

This proteomics study was designed to determine the utility of iTRAQ MALDI-TOF/TOF technology to compare plasma samples from carefully phenotyped mild, atopic asthma subjects undergoing allergen inhalation challenge.

EXPERIMENTAL DESIGN

Eight adult subjects with mild, allergic asthma (four early responders (ERs) and four dual responders (DRs)) participated in the allergen inhalation challenge. Blood samples were collected prior to and 2 h after the inhalation challenge. Sixteen plasma samples (two per subject), technical replicates, and pooled controls were analyzed using iTRAQ. Technical validation was performed using LC-MRM/MS. Moderated robust regression was used to determine differentially expressed proteins.

RESULTS

Although this study did not show significant differences between pre- and post-challenge samples, discriminant analysis indicated that certain proteins responded differentially to allergen challenge with respect to responder type. At pre-challenge, fibronectin was significantly elevated in DRs compared to ERs and remained significant in the multiple reaction monitoring validation.

CONCLUSIONS AND CLINICAL RELEVANCE

This proof of principle demonstration has shown that iTRAQ can uncover differences in the human plasma proteome between two endotypes of asthma and merits further application of iTRAQ to larger cohorts of asthma and other respiratory diseases.

Differential quantitative proteomic profiling of Leishmania infantum and Leishmania mexicana density gradient separated membranous fractions

Leishmaniasis, caused by infection with Leishmania, is a major public health concern affecting more than 20million people globally. Leishmania has a digenetic lifecycle consisting of an extracellular flagellated promastigote, adapted to live in the mid-gut of the sand fly host and an aflagellated intracellular amastigote that resides within the macrophage of the mammalian host. Leishmania mexicana and Leishmania infantum are causative agents of cutaneous and visceral leishmaniasis, respectively. Membrane proteins play a pivotal role in host-pathogen interactions and in regulatory pathways. As the genome of Leishmania is essentially constitutively expressed, regulation of protein expression during differentiation occurs post-transcriptionally and/or post-translationally. Quantitative mass spectrometry using iTRAQ labeling identified differences in the proteomes of density gradient separated membranous fractions of promastigote and amastigote life-stages. We identified 189 L. infantum and 107 L. mexicana non-redundant proteins of which 20-40% showed differential expression levels between promastigote and amastigote lifecycle stages. Differentially expressed proteins mapped to several pathways including cell motility, metabolism, and infectivity as well as virulence factors such as eEF-1α, amastin and leishmanolysin (GP63). Western blot analysis validated iTRAQ quantitation for leishmanolysin. Focusing on differentially expressed proteins essential for pathogenesis, may ultimately lead to the identification of novel potential therapeutic targets.

BIOLOGICAL SIGNIFICANCE

Leishmania, protozoan parasites of the Trypanosomatidae family, are the causative agents of leishmaniasis that represents a major public health concern affecting more than 20million people globally Membrane associated proteins play a pivotal role in host-pathogen interactions and in regulatory pathways. Quantitative proteomic analysis of the membranous fractions from L. mexicana and L. infantum (causative agents of cutaneous and visceral leishmaniasis, respectively) identified a number of proteins that may have important stage-specific functions in either the sand fly or mammalian host. The function of these proteins includes roles in virulence, as well as differences in metabolic process between life stages. Many of the proteins identified may act as virulence factors playing significant roles in parasite invasion, host-parasite interaction or parasite survival and thus may have therapeutic potential as drug target candidates.

On protein abundance distributions in complex mixtures

Mass spectrometry, an analytical technique that measures the mass-to-charge ratio of ionized atoms or molecules, dates back more than 100 years, and has both qualitative and quantitative uses for determining chemical and structural information. Quantitative proteomic mass spectrometry on biological samples focuses on identifying the proteins present in the samples, and establishing the relative abundances of those proteins. Such protein inventories create the opportunity to discover novel biomarkers and disease targets. We have previously introduced a normalized, label-free method for quantification of protein abundances under a shotgun proteomics platform (Griffin et al., 2010). The introduction of this method for quantifying and comparing protein levels leads naturally to the issue of modeling protein abundances in individual samples. We here report that protein abundance levels from two recent proteomics experiments conducted by the authors can be adequately represented by Sichel distributions. Mathematically, Sichel distributions are mixtures of Poisson distributions with a rather complex mixing distribution, and have been previously and successfully applied to linguistics and species abundance data. The Sichel model can provide a direct measure of the heterogeneity of protein abundances, and can reveal protein abundance differences that simpler models fail to show.

Standardized protocols for quality control of MRM-based plasma proteomic workflows

Mass spectrometry (MS)-based proteomics is rapidly emerging as a viable technology for the identification and quantitation of biological samples, such as human plasma--the most complex yet commonly employed biofluid in clinical analyses. The transition from a qualitative to quantitative science is required if proteomics is going to successfully make the transition to a clinically useful technique. MS, however, has been criticized for a lack of reproducibility and interlaboratory transferability. Currently, the MS and plasma proteomics communities lack standardized protocols and reagents to ensure that high-quality quantitative data can be accurately and precisely reproduced by laboratories across the world using different MS technologies. Toward addressing this issue, we have developed standard protocols for multiple reaction monitoring (MRM)-based assays with customized isotopically labeled internal standards for quality control of the sample preparation workflow and the MS platform in quantitative plasma proteomic analyses. The development of reference standards and their application to a single MS platform is discussed herein, along with the results from intralaboratory tests. The tests highlighted the importance of the reference standards in assessing the efficiency and reproducibility of the entire bottom-up proteomic workflow and revealed errors related to the sample preparation and performance quality and deficits of the MS and LC systems. Such evaluations are necessary if MRM-based quantitative plasma proteomics is to be used in verifying and validating putative disease biomarkers across different research laboratories and eventually in clinical laboratories.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

An insight into iTRAQ: where do we stand now?

The iTRAQ (isobaric tags for relative and absolute quantification) technique is widely employed in proteomic workflows requiring relative quantification. Here, we review the iTRAQ literature; in particular, we focus on iTRAQ usage in relation to other commonly used quantitative techniques e.g. stable isotope labelling in culture (SILAC), label-free methods and selected reaction monitoring (SRM). As a result, we identify several issues arising with respect to iTRAQ. Perhaps frustratingly, iTRAQ's attractiveness has been undermined by a number of technical and analytical limitations: it may not be truly quantitative, as the changes in abundance reported will generally be underestimated. We discuss weaknesses and strengths of iTRAQ as a methodology for relative quantification in the light of this and other technical issues. We focus on technical developments targeted at iTRAQ accuracy and precision, use of 4-plex over 8-plex reagents and application of iTRAQ to post-translational modification (PTM) workflows. We also discuss iTRAQ in relation to label-free approaches, to which iTRAQ is losing ground.

Comprehensive comparison of iTRAQ and label-free LC-based quantitative proteomics approaches using two Chlamydomonas reinhardtii strains of interest for biofuels engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approaches--iTRAQ and label-free--were implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two Chlamydomonas reinhardtii strains in the context of alternative biofuels production. The strain comparison includes sta6 (a starch-less mutant of cw15) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain cw15 (a cell wall-deficient C. reinhardtii strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between cw15 and sta6 reveals already known but also new mechanisms likely responsible for the production of lipids in sta6 and sets the baseline for future studies aimed at engineering these strains for high oil production.

Identification of differentially expressed proteins from Burkholderia pseudomallei isolated during primary and relapsing melioidosis

Burkholderia pseudomallei causes septicemic melioidosis with a high rate of relapse, however microbial determinants of relapse are unknown. Proteins were analyzed from sequential B. pseudomallei isolates from primary and relapsing melioidosis. Analysis by isotope tagging for relative and absolute quantitation revealed that factors required for nitric oxide detoxification (HmpA) and necessary for anaerobic growth (ArcA, ArcC and ArcB) were highly expressed in the relapse isolate. Two-dimensional gel electrophoresis revealed up-regulation of a putative hemolysin-coregulated protein in the primary isolate, and flagellin and HSP20/alpha crystalline in the relapse isolate. These observations provide targets for further analysis of latency and virulence of melioidosis.

Quantification of proteins using data-independent analysis (MSE) in simple andcomplex samples: a systematic evaluation

A MS-based method for the quantification of proteins termed data-independent analysis (or MS(E)) has been introduced recently. Although this method has been applied to the analysis of various types of biological samples, a thorough evaluation to assess the performance of this approach has yet to be conducted. Presented here is the first systematic and comprehensive study investigating the MS(E) approach for quantitative analysis of low-, medium-, and high-complexity samples. We demonstrate that this method has a linear dynamic range spanning three orders of magnitude with a limit of quantification of 61 amol/uL in low-complexity samples and 488 amol/uL in high-complexity samples. In addition, comprehensive sequence coverage was obtained and accurate quantification achieved for expression ratios ranging from 1:1.5 to 1:6. However, underestimation of ratios was detected independent of sample type, consistent with other quantitative proteomic methods. The present study provides validation of the MS(E) approach for accurate quantitative proteomic analysis of biological samples while, at the same time, proving high sequence coverage of target proteins.

Differential protein expression throughout the life cycle of Trypanosoma congolense, a major parasite of cattle in Africa

Trypanosoma congolense is an important pathogen of livestock in Africa. To study protein expression throughout the T. congolense life cycle, we used culture-derived parasites of each of the three main insect stages and bloodstream stage parasites isolated from infected mice, to perform differential protein expression analysis. Three complete biological replicates of all four life cycle stages were produced from T. congolense IL3000, a cloned parasite that is amenable to culture of major life cycle stages in vitro. Cellular proteins from each life cycle stage were trypsin digested and the resulting peptides were labeled with isobaric tags for relative and absolute quantification (iTRAQ). The peptides were then analyzed by tandem mass spectrometry (MS/MS). This method was used to identify and relatively quantify proteins from the different life cycle stages in the same experiment. A search of the Wellcome Trust's Sanger Institute's semi-annotated T. congolense database was performed using the MS/MS fragmentation data to identify the corresponding source proteins. A total of 2088 unique protein sequences were identified, representing 23% of the ∼9000 proteins predicted for the T. congolense proteome. The 1291 most confidently identified proteins were prioritized for further study. Of these, 784 yielded annotated hits while 501 were described as "hypothetical proteins". Six proteins showed no significant sequence similarity to any known proteins (from any species) and thus represent new, previously uncharacterized T. congolense proteins. Of particular interest among the remainder are several membrane molecules that showed drastic differential expression, including, not surprisingly, the well-studied variant surface glycoproteins (VSGs), invariant surface glycoproteins (ISGs) 65 and 75, congolense epimastigote specific protein (CESP), the surface protease GP63, an amino acid transporter, a pteridine transporter and a haptoglobin-hemoglobin receptor. Several of these surface disposed proteins are of functional interest as they are necessary for survival of the parasites.

Improved precision of iTRAQ and TMT quantification by an axial extraction field in an Orbitrap HCD cell

Improving analytical precision is a major goal in quantitative differential proteomics as high precision ensures low numbers of outliers, a source of false positives with regard to quantification. In addition, higher precision increases statistical power, i.e., the probability to detect significant differences. With chemical labeling using isobaric tags for relative and absolute quantitation (iTRAQ) or tandem mass tag (TMT) reagents, quantification is based on the extraction of reporter ions from tandem mass spectrometry (MS/MS) spectra. We compared the performance of two versions of the LTQ Orbitrap higher energy collisional dissociation (HCD) cell with and without an axial electric field with regard to reporter ion quantification. The HCD cell with the axial electric field was designed to push fragment ions into the C-trap and this version is mounted in current Orbitrap XL ETD and Orbitrap Velos instruments. Our goal was to evaluate whether the purported improvement in ion transmission had a measurable impact on the precision of MS/MS based quantification using peptide labeling with isobaric tags. We show that the axial electric field led to an increased percentage of HCD spectra in which the complete set of reporter ions was detected and, even more important, to a reduction in overall variance, i.e., improved analytical precision of the acquired data. Notably, adequate precision of HCD-based quantification was maintained even for low precursor ion intensities of a complex biological sample. These findings may help researchers in their design of quantitative proteomics studies using isobaric tags and establish HCD-based quantification on the LTQ Orbitrap as a highly precise approach in quantitative proteomics.

LTQ-iQuant: A freely available software pipeline for automated and accurate protein quantification of isobaric tagged peptide data from LTQ instruments

Pulsed Q dissociation enables combining LTQ ion trap instruments with isobaric peptide tagging. Unfortunately, this combination lacks a technique which accurately reports protein abundance ratios and is implemented in a freely available, flexible software pipeline. We developed and implemented a technique assigning collective reporter ion intensity-based weights to each peptide abundance ratio and calculating a protein's weighted average abundance ratio and p-value. Using an iTRAQ-labeled standard mixture, we compared our technique's performance to the commercial software MASCOT, finding that it performed better than MASCOT's nonweighted averaging and median peptide ratio techniques, and equal to its weighted averaging technique. We also compared performance of the LTQ-Orbitrap plus our technique to 4800 MALDI TOF/TOF plus Protein Pilot, by analyzing an iTRAQ-labeled stem cell lysate. We found highly correlated protein abundance ratios, indicating that the LTQ-Orbitrap plus our technique yields results comparable to the current standard. We implemented our technique in a freely available, automated software pipeline, called LTQ-iQuant, which is mzXML-compatible; supports iTRAQ 4-plex and 8-plex LTQ data; and can be modified for and have weights trained to a user's LTQ and other isobaric peptide tagging methods. LTQ-iQuant should make LTQ instruments and isobaric peptide tagging accessible to more proteomic researchers.

A chemical genetic screen for modulators of asymmetrical 2,2'-dimeric naphthoquinones cytotoxicity in yeast

Background

Dimeric naphthoquinones (BiQ) were originally synthesized as a new class of HIV integrase inhibitors but have shown integrase-independent cytotoxicity in acute lymphoblastic leukemia cell lines suggesting their use as potential anti-neoplastic agents. The mechanism of this cytotoxicity is unknown. In order to gain insight into the mode of action of binaphthoquinones we performed a systematic high-throughput screen in a yeast isogenic deletion mutant array for enhanced or suppressed growth in the presence of binaphthoquinones.

Methodology/Principal findings

Exposure of wild type yeast strains to various BiQs demonstrated inhibition of yeast growth with IC₅₀s in the µM range. Drug sensitivity and resistance screens were performed by exposing arrays of a haploid yeast deletion mutant library to BiQs at concentrations near their IC₅₀. Sensitivity screens identified yeast with deletions affecting mitochondrial function and cellular respiration as having increased sensitivity to BiQs. Corresponding to this, wild type yeast grown in the absence of a fermentable carbon source were particularly sensitive to BiQs, and treatment with BiQs was shown to disrupt the mitochondrial membrane potential and lead to the generation of reactive oxygen species (ROS). Furthermore, baseline ROS production in BiQ sensitive mutant strains was increased compared to wild type and could be further augmented by the presence of BiQ. Screens for resistance to BiQ action identified the mitochondrial external NAD(P)H dehydrogenase, NDE1, as critical to BiQ toxicity and over-expression of this gene resulted in increased ROS production and increased sensitivity of wild type yeast to BiQ.

Conclusions/Significance

In yeast, binaphthoquinone cytotoxicity is likely mediated through NAD(P)H:quonine oxidoreductases leading to ROS production and dysfunctional mitochondria. Further studies are required to validate this mechanism in mammalian cells.

Proteomic signatures in plasma during early acute renal allograft rejection

Acute graft rejection is an important clinical problem in renal transplantation and an adverse predictor for long term graft survival. Plasma biomarkers may offer an important option for post-transplant monitoring and permit timely and effective therapeutic intervention to minimize graft damage. This case-control discovery study (n = 32) used isobaric tagging for relative and absolute protein quantification (iTRAQ) technology to quantitate plasma protein relative concentrations in precise cohorts of patients with and without biopsy-confirmed acute rejection (BCAR). Plasma samples were depleted of the 14 most abundant plasma proteins to enhance detection sensitivity. A total of 18 plasma proteins that encompassed processes related to inflammation, complement activation, blood coagulation, and wound repair exhibited significantly different relative concentrations between patient cohorts with and without BCAR (p value <0.05). Twelve proteins with a fold-change >or=1.15 were selected for diagnostic purposes: seven were increased (titin, lipopolysaccharide-binding protein, peptidase inhibitor 16, complement factor D, mannose-binding lectin, protein Z-dependent protease and beta(2)-microglobulin) and five were decreased (kininogen-1, afamin, serine protease inhibitor, phosphatidylcholine-sterol acyltransferase, and sex hormone-binding globulin) in patients with BCAR. The first three principal components of these proteins showed clear separation of cohorts with and without BCAR. Performance improved with the inclusion of sequential proteins, reaching a primary asymptote after the first three (titin, kininogen-1, and lipopolysaccharide-binding protein). Longitudinal monitoring over the first 3 months post-transplant based on ratios of these three proteins showed clear discrimination between the two patient cohorts at time of rejection. The score then declined to baseline following treatment and resolution of the rejection episode and remained comparable between cases and controls throughout the period of quiescent follow-up. Results were validated using ELISA where possible, and initial cross-validation estimated a sensitivity of 80% and specificity of 90% for classification of BCAR based on a four-protein ELISA classifier. This study provides evidence that protein concentrations in plasma may provide a relevant measure for the occurrence of BCAR and offers a potential tool for immunologic monitoring.

Use of a combination of isotopically coded cross-linkers and isotopically coded N-terminal modification reagents for selective identification of inter-peptide crosslinks

Cross-linking combined with mass spectrometry has great potential for determining three-dimensional structures of proteins and protein assemblies. One of the main analytical challenges of this method is the specific detection and identification of the inter-peptide crosslinks in the peptide mixture after enzymatic digestion of the cross-linked protein complex. These inter-peptide crosslinks are important because they provide the critical distance information needed for structural proteomics studies. In this paper, we demonstrate the use of isotopically coded N-terminal modification (ICNTM) in combination with isotopically coded cross-linkers (ICCL) for specific detection of inter-peptide crosslinks. Inter-peptide crosslinks contain two amino termini, compared to one in the case of free peptides, dead-end crosslinks, or intra-peptide crosslinks. Therefore, N-terminal modification with a 1:1 mixture of heavy and light isotopically coded reagents produces inter-peptide crosslinks with a distinct isotopic signature (a 1:2:1 ratio). Modification also occurs at the epsilon-amino groups of non-cross-linked lysine residues, resulting in two modifications per free lysine-containing peptide. However, if ICCL and ICNTM are used together, inter-peptide crosslinks can be distinguished from free lysine-containing peptides. Specialized software has also been developed for the analysis of ICCL + ICNTM experimental data. This procedure, combined with software for data analysis, provides a simple and rapid method for specific detection of inter-peptide crosslinks.

A comparison of the accuracy of iTRAQ quantification by nLC-ESI MSMS and nLC-MALDI MSMS methods

The accuracy of quantification obtained using the iTRAQ labelling methodology for measuring protein ratios more extreme than 1:1 was investigated. A comparison of nLC-ESI MSMS and nLC-MALDI MSMS analysis routes was performed. A fixed concentration of a standard six protein mix was spiked with two proteins at a range of concentrations. The two data analysis programmes, Mascot and ProteinPilot Paragon, were also compared. Whilst the lower ratios could be measured accurately, greater discrepancies were seen for the higher ratios, particularly by nLC-ESI MSMS. Filtering out the weaker reporter ion signals improved the accuracy of the ratios: this is likely due to several factors which are explored in more detail. Overall, analysis by nLC-MALDI MSMS followed by Mascot interpretation gave the most accurate results.

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.

Interaction proteomics of synapse protein complexes

The brain integrates complex types of information, and executes a wide range of physiological and behavioral processes. Trillions of tiny organelles, the synapses, are central to neuronal communication and information processing in the brain. Synaptic transmission involves an intricate network of synaptic proteins that forms the molecular machinery underlying transmitter release, activation, and modulation of transmitter receptors and signal transduction cascades. These processes are dynamically regulated and underlie neuroplasticity, crucial to learning and memory formation. In recent years, interaction proteomics has increasingly been used to elucidate the constituents of synaptic protein complexes. Unlike classic hypothesis-based assays, interaction proteomics detects both known and novel interactors without bias. In this trend article, we focus on the technical aspects of recent proteomics to identify synapse protein complexes, and the complementary methods used to verify the protein–protein interaction. Moreover, we discuss the experimental feasibility of performing global analysis of the synapse protein interactome.