Synthesis/degradation ratio mass spectrometry for measuring relative dynamic protein turnover

One of the major unanswered questions in quantitative proteomics is that of dynamic protein turnover in the cell. Here we present a new approach to quantitative proteomics that measures the relative dynamic turnover of proteins in cellular systems. In this approach, termed synthesis/degradation ratio mass spectrometry, stable isotope labeling is employed to calculate a relative synthesis/degradation ratio that reflects the relative rate at which 13C is incorporated into individual proteins in the cell. This synthesis/degradation ratio calculation is based on a Poisson distribution model that is designed to support high-throughput analysis. Protein separation and analysis is accomplished by utilizing one-dimensional SDS-PAGE gel electrophoresis followed by cutting the gel into a series of bands for in-gel digestion. The resulting peptide mixtures are analyzed via solid-phase MALDI LC-MS and LC-MS/MS using a tandem time-of-flight mass spectrometer. A portion of the soluble protein fraction from an E. coli K-12 strain was analyzed with synthesis/degradation ratios varying from approximately 0.1 to 4.4 for a variety of different proteins. Unlike other quantitative techniques, synthesis/degradation ratio mass spectrometry requires only a single cell culture to obtain useful biological information about the processes occurring inside a cell. This technique is highly amenable to shotgun proteomics-based approaches and thus should allow relative turnover measurements for whole proteomes in the future.     

Automated quantification tool for high-throughput proteomics using stable isotope labeling and LC-MSn

LC-MSn has become a popular option for high-throughput quantitative proteomics, thanks to the availability of stable-isotope labeling reagents. However, the vast quantity of data generated from LC-MSn continues to make the postacquisition quantification analyses challenging, especially in experiments involving multiple samples per experimental condition. To facilitate data analysis, we developed a computer program, QUIL, for automated protein quantification. QUIL accounts for the dynamic nature of spectral background and subtracts this background accordingly during ion chromatogram reconstruction. For elution profile identification, QUIL minimizes the inclusion of coeluted neighbor peaks, yet tolerates imperfect peak shapes. Outlier-resistant methods have been implemented for better protein ratio estimation. The utility of QUIL was validated by quantitative analyses of a standard protein as well as complex protein mixtures, which were labeled with cICAT or 18O and analyzed using LCQ, LTQ, or FT-ICR instruments. For samples that no prior knowledge of relative protein quantities was available, Western blotting was performed for confirmation. For the standard protein, the coefficient of variation (CV) of peptide ratio estimation was 6%. For complex mixtures, the median CV for protein ratio calculations was less than 10%. Computed protein abundance ratios exhibited a relatively high degree of correlation with those obtained from Western blot analyses. Compared with a widely used commercial software tool, QUIL showed improvement in ion chromatogram construction and peak integration and significantly reduced relative errors in abundance ratio assessment.     

Quantitative proteomic analysis using a MALDI quadrupole time-of-flight mass spectrometer

We describe an approach to the quantitative analysis of complex protein mixtures using a MALDI quadrupole time-of-flight (MALDI QqTOF) mass spectrometer and isotope coded affinity tag reagents (Gygi, S. P.; et al. Nat. Biotechnol. 1999, 17, 994-9.). Proteins in mixtures are first labeled on cysteinyl residues using an isotope coded affinity tag reagent, the proteins are enzymatically digested, and the labeled peptides are purified using a multidimensional separation procedure, with the last step being the elution of the labeled peptides from a microcapillary reversed-phase liquid chromatography column directly onto a MALDI sample target. After addition of matrix, the sample spots are analyzed using a MALDI QqTOF mass spectrometer, by first obtaining a mass spectrum of the peptides in each sample spot in order to quantify the ratio of abundance of pairs of isotopically tagged peptides, followed by tandem mass spectrometric analysis to ascertain the sequence of selected peptides for protein identification. The effectiveness of this approach is demonstrated in the quantification and identification of peptides from a control mixture of proteins of known relative concentrations and also in the comparative analysis of protein expression in Saccharomyces cerevisiae grown on two different carbon sources.     

Tandem mass tag protein labeling for top-down identification and quantification

Top-down mass spectrometry holds tremendous potential for characterization and quantification of intact proteins. So far, however, very few studies have combined top-down proteomics with protein quantification. In view of the success of isobaric mass tags in quantitative bottom-up proteomics, we applied the tandem mass tag (TMT) technology to label intact proteins and examined the feasibility to directly quantify TMT-labeled proteins. A top-down platform encompassing separation via ion-pair reversed-phase liquid chromatography using monolithic stationary phases coupled online to an LTQ-Orbitrap Velos electron-transfer dissociation (ETD) mass spectrometer (MS) was established to simultaneously identify and quantify TMT-labeled proteins. The TMT-labeled proteins were found to be readily dissociated under high-energy collision dissociation (HCD) activation. The liberated reporter ions delivered expected ratios over a wide dynamic range independent of the protein charge state. Furthermore, protein sequence tags generated either by low-energy HCD or ETD activation along with the intact protein mass information allow for confident identification of small proteins below 35 kDa. We conclude that the approach presented in this pilot study paves the way for further developments and numerous applications for straightforward, accurate, and multiplexed quantitative analysis in protein chemistry and proteomics.     

Optimizing identification and quantitation of 15N-labeled proteins in comparative proteomics

Comparative proteomics has emerged as a powerful approach to determine differences in protein abundance between biological samples. The introduction of stable-isotopes as internal standards especially paved the road for quantitative proteomics for comprehensive approaches to accurately determine protein dynamics. Metabolic labeling with (15)N isotopes is applied to an increasing number of organisms, including Drosophila, C. elegans, and rats. However, (15)N-enrichment is often suboptimal (<98%), which may hamper identification and quantitation of proteins. Here, we systematically investigated two independent (15)N-labeled data sets to explore the influence of heavy nitrogen enrichment on the number of identifications as well as on the error in protein quantitation. We show that specifically larger (15)N-labeled peptides are under-represented when compared to their (14)N counterparts and propose a correction method, which significantly increases the number of identifications. In addition, we developed a method that corrects for inaccurate peptide ratios introduced by incomplete (15)N enrichment. This results in improved accuracy and precision of protein quantitation. Altogether, this study provides insight into the process of protein identification and quantitation, and the methods described here can be used to improve both qualitative and quantitative data obtained by labeling with heavy nitrogen with enrichment less than 100%.     

Method for quantitative proteomics research by using metal element chelated tags coupled with mass spectrometry

The mass spectrometry-based methods with a stable isotope as the internal standard in quantitative proteomics have been developed quickly in recent years. But the use of some stable isotope reagents is limited by the relative high price and synthetic difficulties. We have developed a new method for quantitative proteomics research by using metal element chelated tags (MECT) coupled with mass spectrometry. The bicyclic anhydride diethylenetriamine-N,N,N',N' ',N' '-pentaacetic acid (DTPA) is covalently coupled to primary amines of peptides, and the ligand is then chelated to the rare earth metals Y and Tb. The tagged peptides are mixed and analyzed by LC-ESI-MS/MS. Peptides are quantified by measuring the relative signal intensities for the Y and Tb tag pairs in MS, which permits the quantitation of the original proteins generating the corresponding peptides. The protein is then identified by the corresponding peptide sequence from its MS/MS spectrum. The MECT method was evaluated by using standard proteins as model sample. The experimental results showed that metal chelate-tagged peptides chromatographically coeluted successfully during the reversed-phase LC analysis. The relative quantitation results were accurate for proteins using MECT. DTPA modification of the N-terminal of peptides promoted cleaner fragmentation (only y-series ions) in mass spectrometry and improved the confidence level of protein identification. The MECT strategy provides a simple, rapid, and economical alternative to current mass tagging technologies available.     

Top-down identification and quantification of stable isotope labeled proteins from Aspergillus flavus using online nano-flow reversed-phase liquid chromatography coupled to a LTQ-FTICR mass spectrometer

Online liquid chromatography-mass spectrometric (LC-MS) analysis of intact proteins (i.e., top-down proteomics) is a growing area of research in the mass spectrometry community. A major advantage of top-down MS characterization of proteins is that the information of the intact protein is retained over the vastly more common bottom-up approach that uses protease-generated peptides to search genomic databases for protein identification. Concurrent to the emergence of top-down MS characterization of proteins has been the development and implementation of the stable isotope labeling of amino acids in cell culture (SILAC) method for relative quantification of proteins by LC-MS. Herein we describe the qualitative and quantitative top-down characterization of proteins derived from SILAC-labeled Aspergillus flavus using nanoflow reversed-phase liquid chromatography directly coupled to a linear ion trap Fourier transform ion cyclotron resonance mass spectrometer (nLC-LTQ-FTICR-MS). A. flavus is a toxic filamentous fungus that significantly impacts the agricultural economy and human health. SILAC labeling improved the confidence of protein identification, and we observed 1318 unique protein masses corresponding to 659 SILAC pairs, of which 22 were confidently identified. However, we have observed some limiting issues with regard to protein quantification using top-down MS/MS analyses of SILAC-labeled proteins. The role of SILAC labeling in the presence of competing endogenously produced amino acid residues and its impact on quantification of intact species are discussed in detail.     

Quantification and identification of components in solution mixtures from 1D proton NMR spectra using singular value decomposition

One-dimensional proton NMR spectra of complex solutions provide rich molecular information, but limited chemical shift dispersion creates peak overlap that often leads to difficulty in peak identification and analyte quantification. Modern high-field NMR spectrometers provide high digital resolution with improved peak dispersion. We took advantage of these spectral qualities and developed a quantification method based on linear least-squares fitting using singular value decomposition (SVD). The linear least-squares fitting of a mixture spectrum was performed on the basis of reference spectra from individual small-molecule analytes. Each spectrum contained an internal quantitative reference (e.g., DSS-d6 or other suitable small molecules) by which the intensity of the spectrum was scaled. Normalization of the spectrum facilitated quantification based on peak intensity using linear least-squares fitting analysis. This methodology provided quantification of individual analytes as well as chemical identification. The analysis of small-molecule analytes over a wide concentration range indicated the accuracy and reproducibility of the SVD-based quantification. To account for the contribution from residual protein, lipid or polysaccharide in solution, a reference spectrum showing the macromolecules or aggregates was obtained using a diffusion-edited 1D proton NMR analysis. We demonstrated this approach with a mixture of small-molecule analytes in the presence of macromolecules (e.g., protein). The results suggested that this approach should be applicable to the quantification and identification of small-molecule analytes in complex biological samples.     

Selective detection of proteins in mixtures using electrospray ionization mass spectrometry: influence of instrumental settings and implications for proteomics

We studied the effects of electrospray mass spectrometric instrumental settings on the relative and absolute detection of individual proteins in a five-component mixture. Conditions that were effective for a given protein could be very poor for the others, and vice versa, such that to a good approximation it was possible to find conditions for selective detection of individual proteins in a complex mixture without prior analytical separation. Some of these could be rationalized on the basis of the known biophysical properties of the individual proteins. The ability to vary the conditions of a mass spectrometric detection method on-line provides an important degree of freedom for the selective detection, and hence discrimination, of individual proteins and peptides in complex mixtures and has implications in proteomics, in particular with respect to top-down strategies for proteomic characterizations.     

IsoQuant: a software tool for stable isotope labeling by amino acids in cell culture-based mass spectrometry quantitation

Accurate protein identification and quantitation are critical when interpreting the biological relevance of large-scale shotgun proteomics data sets. Although significant technical advances in peptide and protein identification have been made, accurate quantitation of high-throughput data sets remains a key challenge in mass spectrometry data analysis and is a labor intensive process for many proteomics laboratories. Here, we report a new SILAC-based proteomics quantitation software tool, named IsoQuant, which is used to process high mass accuracy mass spectrometry data. IsoQuant offers a convenient quantitation framework to calculate peptide/protein relative abundance ratios. At the same time, it also includes a visualization platform that permits users to validate the quality of SILAC peptide and protein ratios. The program is written in the C# programming language under the Microsoft .NET framework version 4.0 and has been tested to be compatible with both 32-bit and 64-bit Windows 7. It is freely available to noncommercial users at http://www.proteomeumb.org/MZw.html .     

Proteomic complex detection using sedimentation

Protein-protein interactions are important in many cellular processes, but there are still relatively few methods to screen for novel protein complexes. Here we present a quantitative proteomics technique called ProCoDeS (Proteomic Complex Detection using Sedimentation) for profiling the sedimentation of a large number of proteins through a rate zonal centrifugation gradient. Proteins in a putative complex can be identified since they sediment faster than predicted from their monomer molecular weight. Using solubilized mitochondrial membrane proteins from Arabidopsis thaliana, the relative protein abundance in fractions of a rate zonal gradient was measured with the isotopic labeling reagent ICAT and electrospray mass spectrometry. Subunits of the same protein complex had very similar gradient distribution profiles, demonstrating the reproducibility of the quantitation method. The approximate size of the unknown complex can be inferred from its sedimentation rate relative to known protein complexes. ProCoDeS will be of use in screening extracts of tissues, cells, or organelle fractions to identify specific proteins in stable complexes that can be characterized by subsequent targeted techniques such as affinity tagging.     

N-terminal isotope tagging strategy for quantitative proteomics: results-driven analysis of protein abundance changes

Comparing the relative abundance of each protein present in two or more complex samples can be accomplished using isotope-coded tags incorporated at the peptide level. Here we describe a chemical labeling strategy for the incorporation of a single isotope label per peptide, which is completely sequence-independent so that it potentially labels every peptide from a protein including those containing posttranslational modifications. It is based on a gentle chemical labeling strategy that specifically labels the N-terminus of all peptides in a digested sample with either a d5- or d0-propionyl group. Lysine side chains are blocked by guanidination prior to N-terminal labeling to prevent the incorporation of multiple labels. In this paper, we describe the optimization of this N-terminal isotopic tagging strategy and validate its use for peptide-based protein abundance measurements with a 10-protein standard mixture. Using a results-driven strategy, which targets proteins for identification based on MALDI TOF-MS analysis of isotopically labeled peptide pairs, we also show that this labeling strategy can detect a small number of differentially expressed proteins in a mixture as complex as a yeast cell lysate. Only peptides that show a difference in relative abundance are targeted for identification by tandem MS. Despite the fact that many peptides are quantitated, only those few showing a difference in abundance are targeted for protein identification. Proteins are identified by either targeted LC-ES MS/MS or MALDI TOF/TOF. Identifications can be accomplished equally well by either technique on the basis of multiple peptides. This increases the confidence level for both identification and quantitation. The merits of ES MS/MS or MALDI MS/MS for protein identification in a results-driven strategy are discussed.     

High-throughput comparative proteome analysis using a quantitative cysteinyl-peptide enrichment technology

A new quantitative cysteinyl-peptide enrichment technology (QCET) was developed to achieve higher efficiency, greater dynamic range, and higher throughput in quantitative proteomics that use stable-isotope labeling techniques combined with high-resolution liquid chromatography (LC)-mass spectrometry (MS). This approach involves (18)O labeling of tryptic peptides, high-efficiency enrichment of cysteine-containing peptides, and confident protein identification and quantification using the accurate mass and time tag strategy. Proteome profiling of na?ve and in vitro-differentiated human mammary epithelial cells using QCET resulted in the identification and quantification of 603 proteins in a single LC-Fourier transform ion cyclotron resonance MS analysis. Advantages of this technology include the following: (1) a simple, highly efficient method for enriching cysteinyl-peptides; (2) a high-throughput strategy suitable for extensive proteome analysis; and (3) improved labeling efficiency for better quantitative measurements. This technology enhances both the functional analysis of biological systems and the detection of potential clinical biomarkers.     

Identification of protein vaccine candidates from Helicobacter pylori using a preparative two-dimensional electrophoretic procedure and mass spectrometry

Helicobacter pylori is an important human gastric pathogen for which the entire genome sequence is known. This microorganism displays a uniquely complex pattern of binding to complex carbohydrates presented on host mucosal surfaces and other tissues, through adhesion molecules (adhesins) on the microbial cell surface. Adhesins and other membrane-associated proteins are important targets for vaccine development. The identification and characterization of cell-surface proteins expressed by H. pylori is a prerequisite for the development of vaccines designed to interfere with bacterial colonization of host tissues. However, identification of membrane proteins is difficult using a traditional proteomics approach employing 2D-PAGE. We have used a novel approach in the identification of microbial proteins that employs a rapid preparative two-dimensional electrophoretic separation followed by mass spectrometry and database searches. No pre-enrichment of bacterial membranes was required. The entire process, from sample preparation to protein identification, can be completed in less than 18 hours, and the presence of proteins can be monitored after both the first- and second-dimensional separations using mass spectrometry. We were able to identify 40 proteins from a detergent-solubilized H. pylori preparation; over one-third of these were membrane or membrane-associated proteins. A functionally characterized low-abundance membrane protein, the Leb-binding adhesin, was found in this group. The use of this rapid 2D electrophoretic separation in proteomic studies of H. pylori is expected to speed up the identification of expressed virulence proteins and vaccine targets in this and other microbial pathogens.     

Integrated sample processing system involving on-column protein adsorption, sample washing, and enzyme digestion for protein identification by LC-ESI MS/MS

An automated system has been developed for protein identification using mass spectrometry that incorporates sample cleanup, preconcentration, and protein digestion in a single stage. The procedure involves the adsorption of a protein or a protein mixture from solution onto a hydrophobic medium that is contained within a microcolumn. The protein is digested while still bound to the hydrophobic support. The peptides are then eluted from surface digestion to an electrospray ionization mass spectrometer for detection and sequencing. The entire system is fully automated wherein the mass spectrometer is collecting data continuously. We demonstrate that this system is capable of identifying standard protein samples at concentrations down to 100 nM. Further development of this technique may offer a potential solution for proteomics applications that require unattended operation, such as on-line monitoring and identification of microorganisms on the basis of the detection of their protein biomarkers.     

Label-free comparative analysis of proteomics mixtures using chromatographic alignment of high-resolution muLC-MS data

Label-free relative quantitative proteomics is a powerful tool for the survey of protein level changes between two biological samples. We have developed and applied an algorithm using chromatographic alignment of microLC-MS runs to improve the detection of differences between complex protein mixtures. We demonstrate the performance of our software by finding differences in E. coli protein abundance upon induction of the lac operon genes using isopropyl beta-D-thiogalactopyranoside. The use of our alignment gave a 4-fold decrease in mean relative retention time error and a 6-fold increase in the number of statistically significant differences between samples. Using a conservative threshold, we have identified 5290 total microLC-MS regions that have a different abundance between these samples. Of the detected difference regions, only 23% were mapped to MS/MS peptide identifications. We detected 74 proteins that had a greater relative abundance in the induced sample and 21 with a greater abundance in the uninduced sample. We have developed an effective tool for the label-free detection of differences between samples and demonstrate an increased sensitivity following chromatographic alignment.     

Identification of protein ligands in complex biological samples using intensity-fading MALDI-TOF mass spectrometry

The easy detection of biomolecular interactions in complex mixtures using a minimum amount of material is of prime interest in molecular and cellular biology research. In this work, a mass spectrometry MALDI-TOF based approach, which we call intensity-fading (IF MALDI-TOFMS), and which was designed for just such a purpose, is reported. This methodology is based on the use of the MALDI ion intensities to detect quickly the formation of complexes between nonimmobilized biomolecules in which a protein is one of the partners (protein-protein, protein-peptide, protein-organic molecule, and protein-nucleic acid complexes). The complex is detected through the decrease (fading) of the molecular ion intensities of the partners as directly compared to the MALDI mass spectrum of the mixture (problem and control molecules) following the addition of the target molecule. The potential of the approach is examined in several examples of model interactions, mainly involving small nonprotein and protein inhibitors of proteases, at both the qualitative and semiquantitative levels. Using this method, different protein ligands of proteolytic enzymes in total extracts of invertebrate organisms have been identified in a simple way. The proposed procedure should be easily applied to the high-throughput screening of biomolecules, opening a new experimental strategy in functional proteomics.     

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.     

Analysis of quantitative proteomic data generated via multidimensional protein identification technology

We describe the analysis of quantitative proteomic samples via multidimensional protein identification technology (MudPIT). Ratio amounts of the soluble portion of the S. cerevisiae proteome from cultures of S. cerevisiae strain S288C grown in either 14N minimal media or 15N-enriched minimal media were mixed and digested into a complex peptide mixture. A 1 x 14N/1 x 15N complex peptide mixture was analyzed by single-dimensional reversed-phase chromatography and electrospray ionization quadrapole time-of-flight mass spectrometry in order to demonstrate the replacement of 14N by 15N under the growth conditions used. After conformation of the incorporation of 15N into the labeled sample, three separate samples consisting of a 1 x 14N/1 x 15N complex peptide mixture, a 5 x 14N/1 x 15N complex peptide mixture, and a 10 x 14N/1 x 15N complex peptide mixture were analyzed via MudPIT. We demonstrate the dynamic range of the system by analyzing a 1:1, 5:1, and 10:1 data set using the soluble portion from S. cerevisiae grown in either 14N or 15N-enriched minimal media. The method described provides an accurate way to undertake a large-scale quantitative proteomic study.