A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS

A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.     

Systematic discovery of ectopic pregnancy serum biomarkers using 3-D protein profiling coupled with label-free quantitation

Ectopic pregnancy (EP) and normal intrauterine pregnancy (IUP) serum proteomes were quantitatively compared to systematically identify candidate biomarkers. A 3-D biomarker discovery strategy consisting of abundant protein immunodepletion, SDS gels, LC-MS/MS, and label-free quantitation of MS signal intensities identified 70 candidate biomarkers with differences between groups greater than 2.5-fold. Further statistical analyses of peptide quantities were used to select the most promising 12 biomarkers for further study, which included known EP biomarkers, novel EP biomarkers (ADAM12 and ISM2), and five specific isoforms of the pregnancy specific beta-1-glycoprotein family. Technical replicates showed good reproducibility and protein intensities from the label-free discovery analysis compared favorably with reported abundance levels of several known reference serum proteins over at least 3 orders of magnitude. Similarly, relative abundances of candidate biomarkers from the label-free discovery analysis were consistent with relative abundances from pilot validation assays performed for five of the 12 most promising biomarkers using label-free multiple reaction monitoring of both the patient serum pools used for discovery and the individual samples that constituted these pools. These results demonstrate robust, reproducible, in-depth 3-D serum proteome discovery, and subsequent pilot-scale validation studies can be achieved readily using label-free quantitation strategies.     

Quantitative proteome analysis using differential stable isotopic labeling and microbore LC-MALDI MS and MS/MS

We demonstrate an approach for global quantitative analysis of protein mixtures using differential stable isotopic labeling of the enzyme-digested peptides combined with microbore liquid chromatography (LC) matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS). Microbore LC provides higher sample loading, compared to capillary LC, which facilitates the quantification of low abundance proteins in protein mixtures. In this work, microbore LC is combined with MALDI MS via a heated droplet interface. The compatibilities of two global peptide labeling methods (i.e., esterification to carboxylic groups and dimethylation to amine groups of peptides) with this LC-MALDI technique are evaluated. Using a quadrupole-time-of-flight mass spectrometer, MALDI spectra of the peptides in individual sample spots are obtained to determine the abundance ratio among pairs of differential isotopically labeled peptides. MS/MS spectra are subsequently obtained from the peptide pairs showing significant abundance differences to determine the sequences of selected peptides for protein identification. The peptide sequences determined from MS/MS database search are confirmed by using the overlaid fragment ion spectra generated from a pair of differentially labeled peptides. The effectiveness of this microbore LC-MALDI approach is demonstrated in the quantification and identification of peptides from a mixture of standard proteins as well as E. coli whole cell extract of known relative concentrations. It is shown that this approach provides a facile and economical means of comparing relative protein abundances from two proteome samples.     

A review of quantitative methods for proteomic studies

An overview is provided of six strategies for relative or absolute quantitation of protein abundances that are widely used in proteomic studies. Strengths and limitations are discussed. Four of these involve stable isotope labeling and isotope ratio measurements by mass spectrometry. In another, mass spectra are used to deconvolute overlapping peptide HPLC peaks to provide relative quantitation based on peak areas. The sixth provides relative abundances of proteins based on 2-D gel arrays. It should be noted that these strategies measure peptide and protein abundances, and cannot directly assess changes in regulation or expression.     

Isobaric Labeling and Data Normalization without Requiring Protein Quantitation

Isobaric multiplexed quantitative proteomics can complement high-resolution sample isolation techniques. Here, we report a simple workflow exponentially modified protein abundance index (emPAI)-MW deconvolution (EMMOL) for normalizing isobaric reporter ratios within and between experiments, where small or unknown amounts of protein are used. EMMOL deconvolutes the isobaric tags for relative and absolute quantification (iTRAQ) data to yield the quantity of each protein of each sample in the pool, a new approach that enables the comparison of many samples without including a channel of reference standard. Moreover, EMMOL allows using a sufficient quantity of control sample to facilitate the peptide fractionation (isoelectric-focusing was used in this report), and mass spectrometry MS/MS sequencing yet relies on the broad dynamic range of iTRAQ quantitation to compare relative protein abundance. We demonstrated EMMOL by comparing four pooled samples with 20-fold range differences in protein abundance and performed data normalization without using prior knowledge of the amounts of proteins in each sample, simulating an iTRAQ experiment without protein quantitation prior to labeling. We used emPAI,¹ the target protein MW, and the iTRAQ reporter ratios to calculate the amount of each protein in each of the four channels. Importantly, the EMMOL-delineated proteomes from separate iTRAQ experiments can be assorted for comparison without using a reference sample. We observed no compression of expression in iTRAQ ratios over a 20-fold range for all protein abundances. To complement this ability to analyze minute samples, we report an optimized iTRAQ labeling protocol for using 5 μg protein as the starting material.     

Novel approach for peptide quantitation and sequencing based on 15N and 13C metabolic labeling

Here we describe a method for protein identification and quantification using stable isotopes via in vivo metabolic labeling of the hyperthermophilic crenarchaeon Sulfolobus solfataricus. Stable isotope labeling for quantitative proteomics is becoming increasingly popular; however, its usefulness in protein identification has not been fully exploited. We use both 15N and 13C labeling to create three different versions of the same peptide, corresponding to the unlabeled, 15N and 13C labeled versions. The peptide then appears as three different peaks in a TOF-MS scan and three corresponding sets of MS/MS spectra are obtained. With this information, the elemental carbon and nitrogen compositions for each peptide and each fragment can be calculated. When this is used as a constraint in database searching and/or de novo sequencing, the confidence of a match is increased (for an example intact peptide from 34 choices to 1). This makes the method a useful proteomic tool for both sequenced and unsequenced organisms. Furthermore, it allows for accurate protein quantitation (standard deviations over >4 peptides per protein were within 10%) of three phenotypes in one MS experiment. Abundances for each peptide are calculated by determining the relative areas of each of the three peaks in the TOF-MS spectrum.     

Comparative evaluation of label-free SINQ normalized spectral index quantitation in the central proteomics facilities pipeline

Normalized spectral index quantification was recently presented as an accurate method of label‐free quantitation, which improved spectral counting by incorporating the intensities of peptide MS/MS fragment ions into the calculation of protein abundance. We present SINQ, a tool implementing this method within the framework of existing analysis software, our freely available central proteomics facilities pipeline (CPFP). We demonstrate, using data sets of protein standards acquired on a variety of mass spectrometers, that SINQ can rapidly provide useful estimates of the absolute quantity of proteins present in a medium‐complexity sample. In addition, relative quantitation of standard proteins spiked into a complex lysate background and run without pre‐fractionation produces accurate results at amounts above 1 fmol on column. We compare quantitation performance to various precursor intensity‐ and identification‐based methods, including the normalized spectral abundance factor (NSAF), exponentially modified protein abundance index (emPAI), MaxQuant, and Progenesis LC‐MS. We anticipate that the SINQ tool will be a useful asset for core facilities and individual laboratories that wish to produce quantitative MS data, but lack the necessary manpower to routinely support more complicated software workflows. SINQ is freely available to obtain and use as part of the central proteomics facilities pipeline, which is released under an open‐source license.     

Quantitative proteome analysis of breast cancer cell lines using 18O-labeling and an accurate mass and time tag strategy

Proteome comparison of cell lines derived from cancer and normal breast epithelium provide opportunities to identify differentially expressed proteins and pathways associated with specific phenotypes. We employed 16O/18O peptide labeling, FT-ICR MS, and an accurate mass and time (AMT) tag strategy to simultaneously compare the relative abundance of hundreds of proteins in non-cancer and cancer cell lines derived from breast tissue. A cell line reference panel allowed relative protein abundance comparisons among multiple cell lines and across multiple experiments. A peptide database generated from multidimensional LC separations and MS/MS analysis was used for subsequent AMT tag-based peptide identifications. This peptide database represented a total of 2299 proteins, including 514 that were quantified in five cell lines using the AMT tag and 16O/18O strategies. Eighty-six proteins showed at least a threefold protein abundance change between cancer and non-cancer cell lines. Hierarchical clustering of protein abundance ratios revealed that several groups of proteins were differentially expressed between the cancer cell lines.     

Quantitative proteome analysis of human plasma following in vivo lipopolysaccharide administration using 16O/18O labeling and the accurate mass and time tag approach

Identification of novel diagnostic or therapeutic biomarkers from human blood plasma would benefit significantly from quantitative measurements of the proteome constituents over a range of physiological conditions. Herein we describe an initial demonstration of proteome-wide quantitative analysis of human plasma. The approach utilizes postdigestion trypsin-catalyzed 16O/18O peptide labeling, two-dimensional LC-FTICR mass spectrometry, and the accurate mass and time (AMT) tag strategy to identify and quantify peptides/proteins from complex samples. A peptide accurate mass and LC elution time AMT tag data base was initially generated using MS/MS following extensive multidimensional LC separations to provide the basis for subsequent peptide identifications. The AMT tag data base contains >8,000 putative identified peptides, providing 938 confident plasma protein identifications. The quantitative approach was applied without depletion of high abundance proteins for comparative analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Accurate quantification of changes in protein abundance was demonstrated by both 1:1 labeling of control plasma and the comparison between the plasma samples following LPS administration. A total of 429 distinct plasma proteins were quantified from the comparative analyses, and the protein abundances for 25 proteins, including several known inflammatory response mediators, were observed to change significantly following LPS administration.     

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

The peptide‐based quantitation accuracy and precision of LC‐ESI (QSTAR Elite) and LC‐MALDI (4800 MALDI TOF/TOF) were compared by analyzing identical Escherichia coli tryptic digests containing iTRAQ‐labeled peptides of defined abundances (1:1, 2.5:1, 5:1, and 10:1). Only 51.4% of QSTAR spectra were used for quantitation by ProteinPilot Software versus 66.7% of LC‐MALDI spectra. The average protein sequence coverages for LC‐ESI and LC‐MALDI were 24.0 and 18.2% (14.9 and 8.4 peptides per protein), respectively. The iTRAQ‐based expression ratios determined by ProteinPilot from the 57 467 ESI‐MS/MS and 26 085 MALDI‐MS/MS spectra were analyzed for measurement accuracy and reproducibility. When the relative abundances of peptides within a sample were increased from 1:1 to 10:1, the mean ratios calculated on both instruments differed by only 0.7–6.7% between platforms. In the 10:1 experiment, up to 64.7% of iTRAQ ratios from LC‐ESI MS/MS spectra failed S/N thresholds and were excluded from quantitation, while only 0.1% of the equivalent LC‐MALDI iTRAQ ratios were rejected. Re‐analysis of an archived LC‐MALDI sample set stored for 5 months generated 3715 MS/MS spectra for quantitation, compared with 3845 acquired originally, and the average ratios differed by only 3.1%. Overall, MS/MS‐based peptide quantitation performance of offline LC‐MALDI was comparable with on‐line LC‐ESI, which required threefold less time. However, offline LC‐MALDI allows the re‐analysis of archived HPLC‐separated samples.     

Differential expression analysis of Escherichia coli proteins using a novel software for relative quantitation of LC-MS/MS data

The study of changes in protein levels between samples derived from cells representing different biological conditions is a key to the understanding of cellular function. There are two main methods available that allow both for global scanning for significantly varying proteins and targeted profiling of proteins of interest. One method is based on 2-D gel electrophoresis and image analysis of labelled proteins. The other method is based on LC-MS/MS analysis of either unlabelled peptides or peptides derived from isotopically labelled proteins or peptides. In this study, the non-labelling approach was used involving a new software, DeCyder MS Differential Analysis Software (DeCyder MS) intended for automated detection and relative quantitation of unlabelled peptides in LC-MS/MS data.Total protein extracts of E. coli strains expressing varying levels of dihydrofolate reductase and integron integrase were digested with trypsin and analyzed using a nanoscale liquid chromatography system, Ettan MDLC, online connected to an LTQTM linear ion-trap mass spectrometer fitted with a nanospray interface. Acquired MS data were subjected to DeCyder MS analysis where 2-D representations of the peptide patterns from individual LC-MS/MS analyses were matched and compared.This approach to unlabelled quantitative analysis of the E. coli proteome resulted in relative protein abundances that were in good agreement with results obtained from traditional methods for measuring protein levels.     

Quantitative analysis of modified proteins by LC-MS/MS of peptides labeled with phenyl isocyanate

Stable isotope tagging methods have enabled relative quantitation of proteins between samples in LC-MS/MS analyses. However, most such methods are not applicable to the differential quantitation of modified proteins because the isotope tagging reagents only react with certain peptides or because the reagents incorporate a mass increment that is too small to allow reliable quantitation on low resolution ion trap MS instruments. Here, we describe the use of d0- and d5-phenyl isocyanate (PIC) as N-terminal reactive tags for essentially all peptides in proteolytic digests. PIC reacts quantitatively with peptide N-terminal amines within minutes at neutral pH and the PIC-labeled peptides undergo informative MS/MS fragmentation. Ratios of d0- and d5-PIC-labeled derivatives of several model peptides were linear across a 10000-fold range of peptide concentration ratios, thus indicating a wide dynamic range for quantitation. Application of PIC labeling enabled relative quantitation of several styrene oxide adducts of human hemoglobin in LC-MS/MS analyses. PIC labeling offers a versatile means of quantifying changes in modified or variant protein forms in paired samples.     

Hydroponic isotope labelling of entire plants (HILEP) for quantitative plant proteomics; an oxidative stress case study

Hydroponic isotope labelling of entire plants (HILEP) is a cost-effective method enabling metabolic labelling of whole and mature plants with a stable isotope such as (15)N. By utilising hydroponic media that contain (15)N inorganic salts as the sole nitrogen source, near to 100% (15)N-labelling of proteins can be achieved. In this study, it is shown that HILEP, in combination with mass spectrometry, is suitable for relative protein quantitation of seven week-old Arabidopsis plants submitted to oxidative stress. Protein extracts from pooled (14)N- and (15)N-hydroponically grown plants were fractionated by SDS-PAGE, digested and analysed by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). Proteins were identified and the spectra of (14)N/(15)N peptide pairs were extracted using their m/z chromatographic retention time, isotopic distributions, and the m/z difference between the (14)N and (15)N peptides. Relative amounts were calculated as the ratio of the sum of the peak areas of the two distinct (14)N and (15)N peptide isotope envelopes. Using Mascot and the open source trans-proteomic pipeline (TPP), the data processing was automated for global proteome quantitation down to the isoform level by extracting isoform specific peptides. With this combination of metabolic labelling and mass spectrometry it was possible to show differential protein expression in the apoplast of plants submitted to oxidative stress. Moreover, it was possible to discriminate between differentially expressed isoforms belonging to the same protein family, such as isoforms of xylanases and pathogen-related glucanases (PR 2).     

Integrating titania enrichment,iTRAQ labeling,and Orbitrap CID‐HCD for global identification and quantitative analysis of phosphopeptides

Recent advances in MS instrumentation and progresses in phosphopeptide enrichment, in conjunction with more powerful data analysis tools, have facilitated unbiased characterization of thousands of site‐specific phosphorylation events. Combined with stable isotope labeling by amino acids in cell culture metabolic labeling, these techniques have made it possible to quantitatively evaluate phosphorylation changes in various physiological states in stable cell lines. However, quantitative phosphoproteomics in primary cells and tissues remains a major technical challenge due to the lack of adequate techniques for accurate quantification. Here, we describe an integrated strategy allowing for large scale quantitative profiling of phosphopeptides in complex biological mixtures. In this technique, the mixture of proteolytic peptides was subjected to phosphopeptide enrichment using a titania affinity column, and the purified phosphopeptides were subsequently labeled with iTRAQ reagents. After further fractionation by strong‐cation exchange, the peptides were analyzed by LC‐MS/MS on an Orbitrap mass spectrometer, which collects CID and high‐energy collisional dissociation (HCD) spectra sequentially for peptide identification and quantitation. We demonstrate that direct phosphopeptide enrichment of protein digests by titania affinity chromatography substantially improves the efficiency and reproducibility of phosphopeptide proteomic analysis and is compatible with downstream iTRAQ labeling. Conditions were optimized for HCD normalized collision energy to balance the overall peptide identification and quantitation using the relative abundances of iTRAQ reporter ions. Using this approach, we were able to identify 3557 distinct phosphopeptides from HeLa cell lysates, of which 2709 were also quantified from HCD scans.     

Advanced mass spectrometric methods for the rapid and quantitative characterization of proteomes

Progress is reviewed towards the development of a global strategy that aims to extend the sensitivity, dynamic range, comprehensiveness and throughput of proteomic measurements based upon the use of high performance separations and mass spectrometry. The approach uses high accuracy mass measurements from Fourier transform ion cyclotron resonance mass spectrometry (FTICR) to validate peptide 'accurate mass tags' (AMTs) produced by global protein enzymatic digestions for a specific organism, tissue or cell type from 'potential mass tags' tentatively identified using conventional tandem mass spectrometry (MS/MS). This provides the basis for subsequent measurements without the need for MS/ MS. High resolution capillary liquid chromatography separations combined with high sensitivity, and high resolution accurate FTICR measurements are shown to be capable of characterizing peptide mixtures of more than 10(5) components. The strategy has been initially demonstrated using the microorganisms Saccharomyces cerevisiae and Deinococcus radiodurans. Advantages of the approach include the high confidence of protein identification, its broad proteome coverage, high sensitivity, and the capability for stableisotope labeling methods for precise relative protein abundance measurements.Abbreviations: LC, liquid chromatography; FTICR, Fourier transform ion cyclotron resonance; AMT, accurate mass tag; PMT, potential mass tag; MMA, mass measurement accuracy; MS, mass spectrometry; MS/MS, tandem mass spectrometry; ppm, parts per million.     

An accurate mass tag strategy for quantitative and high-throughput proteome measurements

We describe and demonstrate a global strategy that extends the sensitivity, dynamic range, comprehensiveness, and throughput of proteomic measurements based upon the use of peptide "accurate mass tags" (AMTs) produced by global protein enzymatic digestion. The two-stage strategy exploits Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry to validate peptide AMTs for a specific organism, tissue or cell type from "potential mass tags" identified using conventional tandem mass spectrometry (MS/MS) methods, providing greater confidence in identifications as well as the basis for subsequent measurements without the need for MS/MS, and thus with greater sensitivity and increased throughput. A single high resolution capillary liquid chromatography separation combined with high sensitivity, high resolution and accurate FT-ICR measurements has been shown capable of characterizing peptide mixtures of significantly more than 10(5) components with mass accuracies of < 1 ppm, sufficient for broad protein identification using AMTs. Other attractions of the approach include the broad and relatively unbiased proteome coverage, the capability for exploiting stable isotope labeling methods to realize high precision for relative protein abundance measurements, and the projected potential for study of mammalian proteomes when combined with additional sample fractionation. Using this strategy, in our first application we have been able to identify AMTs for >60% of the potentially expressed proteins in the organism Deinococcus radiodurans.     

Result-driven strategies for protein identification and quantitation--a way to optimize experimental design and derive reliable results

Uni- or multidimensional microcapillary liquid chromatography (microLC) matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry (MS/MS) approaches have gained significant attention for quantifying and identifying proteins in complex biological samples. The off-line coupling of microLC with MS quantitation and MS/MS identification methods makes new result-dependent workflows possible. A relational database is used to store the results from multiple high performance liquid chromatography runs, including information about MALDI plate positions, and both peptide and protein quantitations, and identifications. Unlike electrospray methodology, where all the decisions about which peptide to fragment, must be made during peptide fractionations, in the MALDI experiments the samples are effectively "frozen in time". Therefore, additional MS and MS/MS spectra can be acquired, to promote more accurate quantitation or additional identifications until reliable results are derived that meet experimental design criteria. In the case of what can be designated the expression-dependent workflow, quantitation can be detached from identification and only peak pairs with biological relevant expression changes can be selected for further MS/MS analyses. Alternatively, additional MS/MS data can be acquired to confirm tentative peptide mass fingerprint hits in what is designated a search result-dependent workflow. In the MS data-dependent workflow, the goal is to collect as many meaningful spectra as possible by judiciously adjusting the acquisition parameters based on characteristics of the parent masses. This level of sophistication requires the development of innovative algorithms for these three result-dependent workflows that make MS and MS/MS analysis more efficient and also add confidence to experimental results.     

Stable isotope labeling tandem mass spectrometry (SILT): integration with peptide identification and extension to data-dependent scans

Quantitation of relative or absolute amounts of proteins by mass spectrometry can be prone to large errors. The use of MS/MS ion intensities and stable isotope labeling, which we term stable isotope labeling tandem mass spectrometry (SILT), decreases the effects of contamination from unrelated compounds. We present a software package (SILTmass) that automates protein identification and quantification by the SILT method. SILTmass has the ability to analyze the kinetics of protein turnover, in addition to relative and absolute protein quantitation. Instead of extracting chromatograms to find elution peaks, SILTmass uses only scans in which a peptide is identified and that meet an ion intensity threshold. Using only scans with identified peptides, the accuracy and precision of SILT is shown to be superior to precursor ion intensities, particularly at high or low dilutions of the isotope labeled compounds or with low amounts of protein. Using example scans, we demonstrate likely reasons for the improvements in quantitation by SILT. The appropriate use of variable modifications in peptide identification is described for measurement of protein turnover kinetics. The combination of identification with SILT facilitates quantitation without peak detection and helps to ensure the appropriate use of variable modifications for kinetics experiments.