Toward the complete yeast mitochondrial proteome: multidimensional separation techniques for mitochondrial proteomics

Proteomic analyses of different subcellular compartments, so-called organellar proteomics, facilitate the understanding of cellular functions on a molecular level. In this work, various orthogonal multidimensional separation techniques both on the protein and on the peptide level are compared with regard to the number of identified proteins as well as the classes of proteins accessible by the respective methodology. The most complete overview was achieved by a combination of such orthogonal techniques as shown by the analysis of the yeast mitochondrial proteome. A total of 851 different proteins (PROMITO dataset) were identified by use of multidimensional LC-MS/MS, 1D-SDS-PAGE combined with nano-LC-MS/MS and 2D-PAGE with subsequent MALDI-mass fingerprinting. Our PROMITO approach identified the 749 proteins, which were found in the largest previous study on the yeast mitochondrial proteome, and additionally 102 proteins including 42 open reading frames with unknown function, providing the basis for a more detailed elucidation of mitochondrial processes. Comparison of the different approaches emphasizes a bias of 2D-PAGE against proteins with very high isoelectric points as well as large and hydrophobic proteins, which can be accessed more appropriately by the other methods. While 2D-PAGE has advantages in the possible separation of protein isoforms and quantitative differential profiling, 1D-SDS-PAGE with nano-LC-MS/MS and multidimensional LC-MS/MS are better suited for efficient protein identification as they are less biased against distinct classes of proteins. Thus, comprehensive proteome analyses can only be realized by a combination of such orthogonal approaches, leading to the largest dataset available for the mitochondrial proteome of yeast.     

Quantitative proteomics using 16O/18O labeling and linear ion trap mass spectrometry

Quantitative proteomics using stable isotopic 16O/18O labeling has emerged as a very powerful tool, since it has a number of advantages over other methods, including the simplicity of chemistry, the constant mass tag at the C termini and its general applicability. However, due to the small mass difference between labeled and unlabeled peptide species, this approach has usually been restricted to high-resolution mass spectrometers. In this study we explored whether the high-resolution scanning mode, together with the extremely high scanning speed of the linear IT allows the 16O/18O-labeling method to be used for accurate, large-scale quantitative analysis of proteomes. A protocol, including digestion, desalting, labeling, MS and quantitative analysis was developed and tested using protein standards and whole proteome extracts. Using this method we were able to identify and quantify 140 proteins from only 10 mug of a proteome extract from mesenchymal stem cells. Relative expression changes larger than twofold can be identified with this method at the 95% confidence level. Our results demonstrate that accurate quantitative analysis using 16O/18O labeling can be performed in the practice using linear IT MS, without compromising large-scale peptide identification efficiency.     

Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry

A main objective of proteomics research is to systematically identify and quantify proteins in a given proteome (cells, subcellular fractions, protein complexes, tissues or body fluids). Protein labeling with isotope-coded affinity tags (ICAT) followed by tandem mass spectrometry allows sequence identification and accurate quantification of proteins in complex mixtures, and has been applied to the analysis of global protein expression changes, protein changes in subcellular fractions, components of protein complexes, protein secretion and body fluids. This protocol describes protein-sample labeling with ICAT reagents, chromatographic fractionation of the ICAT-labeled tryptic peptides, and protein identification and quantification using tandem mass spectrometry. The method is suitable for both large-scale analysis of complex samples including whole proteomes and small-scale analysis of subproteomes, and allows quantitative analysis of proteins, including those that are difficult to analyze by gel-based proteomics technology.     

The EIPeptiDi tool: enhancing peptide discovery in ICAT-based LC MS/MS experiments

Background  

Isotope-coded affinity tags (ICAT) is a method for quantitative proteomics based on differential isotopic labeling, sample digestion and mass spectrometry (MS). The method allows the identification and relative quantification of proteins present in two samples and consists of the following phases. First, cysteine residues are either labeled using the ICAT Light or ICAT Heavy reagent (having identical chemical properties but different masses). Then, after whole sample digestion, the labeled peptides are captured selectively using the biotin tag contained in both ICAT reagents. Finally, the simplified peptide mixture is analyzed by nanoscale liquid chromatography-tandem mass spectrometry (LC-MS/MS). Nevertheless, the ICAT LC-MS/MS method still suffers from insufficient sample-to-sample reproducibility on peptide identification. In particular, the number and the type of peptides identified in different experiments can vary considerably and, thus, the statistical (comparative) analysis of sample sets is very challenging. Low information overlap at the peptide and, consequently, at the protein level, is very detrimental in situations where the number of samples to be analyzed is high.     

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.     

High-coverage quantitative proteomics using amine-specific isotopic labeling

Peptide dimethylation with isotopically coded formaldehydes was evaluated as a potential alternative to techniques such as the iTRAQ method for comparative proteomics. The isotopic labeling strategy and custom-designed protein quantitation software were tested using protein standards and then applied to measure proteins levels associated with Alzheimer's disease (AD). The method provided high accuracy (10% error), precision (14% RSD) and coverage (70%) when applied to the analysis of a standard solution of BSA by LC-MS/MS. The technique was then applied to measure protein abundance levels in brain tissue afflicted with AD relative to normal brain tissue. 2-D LC-MS analysis identified 548 unique proteins (p<0.05). Of these, 349 were quantified with two or more peptides that met the statistical criteria used in this study. Several classes of proteins exhibited significant changes in abundance. For example, elevated levels of antioxidant proteins and decreased levels of mitochondrial electron transport proteins were observed. The results demonstrate the utility of the labeling method for high-throughput quantitative analysis.     

Combined chemical and enzymatic stable isotope labeling for quantitative profiling of detergent-insoluble membrane proteins isolated using Triton X-100 and Brij-96

Effective quantitative profiling of detergent-insoluble membrane proteins using high-throughput mass spectrometry (MS)-based proteomics would allow a better understanding of physiological and pathological processes that take place at the cell surface. To increase the coverage of proteins present in detergent-resistant membrane microdomains (DRMMs), a combination of 16O/18O and isotope coded affinity tags (ICAT) labeling was used in a comparative analysis of detergent-insoluble membrane proteins isolated from rat basophilic leukemia cells (RBL-2H3), with either Triton X-100 or Brij-96. The analysis resulted in the quantification of 738 unique proteins from Triton X-100 and Brij-96 isolated DRMMs, significantly exceeding the number of proteins quantified from either single labeling technique. Twenty-five noncysteine-containing proteins were quantified, as well as 32 cysteine-containing proteins that would have been missed if either 16O/18O or ICAT labeling had been used exclusively, which illustrate better proteome coverage and enhanced ability to quantitate. The comparative analysis revealed that proteins were more readily extracted using Triton X-100 than Brij-96; however, Triton X-100 also extracted larger quantities of non-DRMMs-associated proteins. This result confirms previous, targeted studies suggesting that DRMMs isolated using Triton X-100 and Brij-96 differ in their protein content.     

CysTRAQ - A combination of iTRAQ and enrichment of cysteinyl peptides for uncovering and quantifying hidden proteomes

Shotgun proteomics is capable of characterizing differences in both protein quality and quantity, and has been applied in various biomedical applications. Unfortunately, the high complexity and dynamic range of proteins in studied samples, clinical in particular, often hinders the identification of relevant proteins. Indeed, information-rich, low abundance proteins often remain undetected, whereas repeatedly reported altered concentrations in high abundance proteins are often ambiguous and insignificant. Several techniques have therefore been developed to overcome this obstacle and provide a deeper insight into the proteome. Here we report a novel approach, which enables iTRAQ reagent quantitation of peptides fractionated based on presence of a cysteine residue (thus CysTRAQ). For the first time, we prove that iTRAQ quantitation is fully compatible with cysteinyl peptide enrichment and is not influenced by the fractionation process. Moreover, the employment of the method combined with high-resolution TripleTOF 5600 mass spectrometer for very fast MS/MS acquisition in human amniotic fluid analysis significantly increased the number of identified proteins, which were simultaneously quantified owing to the introduction of iTRAQ labeling. We herein show that CysTRAQ is a robust and straightforward method with potential application in quantitative proteomics experiments, i.e. as an alternative to the ICAT reagent approach.     

Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations

Researchers have several options when designing proteomics experiments. Primary among these are choices of experimental method, instrumentation and spectral interpretation software. To evaluate these choices on a proteome scale, we compared triplicate measurements of the yeast proteome by liquid chromatography tandem mass spectrometry (LC-MS/MS) using linear ion trap (LTQ) and hybrid quadrupole time-of-flight (QqTOF; QSTAR) mass spectrometers. Acquired MS/MS spectra were interpreted with Mascot and SEQUEST algorithms with and without the requirement that all returned peptides be tryptic. Using a composite target decoy database strategy, we selected scoring criteria yielding 1% estimated false positive identifications at maximum sensitivity for all data sets, allowing reasonable comparisons between them. These comparisons indicate that Mascot and SEQUEST yield similar results for LTQ-acquired spectra but less so for QSTAR spectra. Furthermore, low reproducibility between replicate data acquisitions made on one or both instrument platforms can be exploited to increase sensitivity and confidence in large-scale protein identifications.     

Physiological proteomics: cells, organs, biological fluids, and biomarkers

Proteomic research is accelerating rapidly because of marked advances in protein labeling techniques, mass spectrometry (MS), and bioinformatics. Two-dimensional difference gel electrophoresis (2D-DIGE) is being used effectively in conjunction with liquid chromatography tandem MS (LC-MS/MS) and/or matrix-assisted laser desorption/ionization time-of-flight MS (MALDI-ToF MS) and database search software to quantify relative changes in the levels of proteins in two samples. It is now possible in a single study to identify and quantify large numbers of proteins and their posttranslational modifications in different biological samples. Comparisons can be made between groups of animals in different physiological states or in response to experimental treatment. Differences between normal individuals and those in disease states can form the foundation for elucidation of causative factors of disease and the identification of biomarkers for the diseased state. This symposium includes original research that compares the erythrocyte plasma membrane proteome in the normal and the sickle cell state, evaluates the anterior pituitary gland proteome in the ovariectomized rat in response to estrogen, and assesses proteomic methodology employed to identify potentially useful biomarkers in human cells and fluids for clinical medicine. It is directed not only to investigators working in these fields but also to a diverse group of scientists working in the biological and biomedical fields to stimulate cross-disciplinary awareness, interest, and collaboration.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

Quantitative proteomics using stable isotope labeling with amino acids in cell culture

Stable isotope labeling with amino acids in cell culture (SILAC) is a simple in vivo labeling strategy for mass spectrometry-based quantitative proteomics. It relies on the metabolic incorporation of nonradioactive heavy isotopic forms of amino acids into cellular proteins, which can be readily distinguished in a mass spectrometer. As the samples are mixed before processing in the SILAC methodology, the sample handling errors are also minimized. Here we present protocols for using SILAC in the following types of experiments: (i) studying inducible protein complexes, (ii) identification of Tyr kinase substrates, (iii) differential membrane proteomics and (iv) studying temporal dynamics using SILAC 5-plexing. Although the overall time is largely dependent on the rate of cell growth and various sample processing steps employed, a typical SILAC experiment from start to finish, including data analysis, should take anywhere between 20 and 25 d.     

A metal-coded affinity tag approach to quantitative proteomics

The quantitative analysis of protein mixtures is pivotal for the understanding of variations in the proteome of living systems. Therefore, approaches have been recently devised that generally allow the relative quantitative analysis of peptides and proteins. Here we present proof of concept of the new metal-coded affinity tag (MeCAT) technique, which allowed the quantitative determination of peptides and proteins. A macrocyclic metal chelate complex (1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (DOTA)) loaded with different lanthanides (metal(III) ions) was the essential part of the tag. The combination of DOTA with an affinity anchor for purification and a reactive group for reaction with amino acids constituted a reagent that allowed quantification of peptides and proteins in an absolute fashion. For the quantitative determination, the tagged peptides and proteins were analyzed using flow injection inductively coupled plasma MS, a technique that allowed detection of metals with high precision and low detection limits. The metal chelate complexes were attached to the cysteine residues, and the course of the labeling reaction was followed using SDS-PAGE and MALDI-TOF MS, ESI MS, and inductively coupled plasma MS. To limit the width in isotopic signal spread and to increase the sensitivity for ESI analysis, we used the monoisotopic lanthanide macrocycle complexes. Peptides tagged with the reagent loaded with different metals coelute in liquid chromatography. In first applications with proteins, the calculated detection limit for bovine serum albumin for example was 110 amol, and we have used MeCAT to analyze proteins of the Sus scrofa eye lens as a model system. These data showed that MeCAT allowed quantification not only of peptides but also of proteins in an absolute fashion at low concentrations and in complex mixtures.     

Bacterial membrane proteomics

About one quarter to one third of all bacterial genes encode proteins of the inner or outer bacterial membrane. These proteins perform essential physiological functions, such as the import or export of metabolites, the homeostasis of metal ions, the extrusion of toxic substances or antibiotics, and the generation or conversion of energy. The last years have witnessed completion of a plethora of whole-genome sequences of bacteria important for biotechnology or medicine, which is the foundation for proteome and other functional genome analyses. In this review, we discuss the challenges in membrane proteome analysis, starting from sample preparation and leading to MS-data analysis and quantification. The current state of available proteomics technologies as well as their advantages and disadvantages will be described with a focus on shotgun proteomics. Then, we will briefly introduce the most abundant proteins and protein families present in bacterial membranes before bacterial membrane proteomics studies of the last years will be presented. It will be shown how these works enlarged our knowledge about the physiological adaptations that take place in bacteria during fine chemical production, bioremediation, protein overexpression, and during infections. Furthermore, several examples from literature demonstrate the suitability of membrane proteomics for the identification of antigens and different pathogenic strains, as well as the elucidation of membrane protein structure and function.     

Identification of human whole saliva protein components using proteomics

The determination of salivary biomarkers as a means of monitoring general health and for the early diagnosis of disease is of increasing interest in clinical research. Based on the linkage between salivary proteins and systemic diseases, the aim of this work was the identification of saliva proteins using proteomics. Salivary proteins were separated using two-dimensional (2-D) gel electrophoresis over a pH range between 3-10, digested, and then analyzed by matrix assisted laser desorption/ionization-time of flight (MALDI-TOF)-TOF mass spectrometry (MS) and tandem mass spectrometry (MS/MS). Proteins were identified using automated MS and MS/MS data acquisition. The resulting data were searched against a protein database using an internal Mascot search routine. Ninety spots give identifications with high statistical reliability. Of the identified proteins, 11 were separated and identified in saliva for the first time using proteomics tools. Moreover, three proteins that have not been previously identified in saliva, PLUNC, cystatin A, and cystatin B were identified.     

A high content in lipid-modified peripheral proteins and integral receptor kinases features in the arabidopsis plasma membrane proteome

The proteomics of plasma membrane has brought to date only scarce and partial information on the actual protein repertoire. In this work, the plant plasma membrane proteome of Arabidopsis thaliana was investigated. A highly purified plasma membrane fraction was washed by NaCl and Na2CO3 salts, and the insoluble fractions were further analyzed by nano-LC-MS/MS. With 446 proteins identified, we hereby describe the largest plasma membrane proteome diversity reported so far. Half of the proteins were predicted to display transmembrane domains and/or to be anchored to the membrane, validating a posteriori the pertinence of the approach. A fine analysis highlighted two main specific and novel features. First, the main functional category is represented by a majority of as yet unreported signaling proteins, including 11% receptor-like kinases. Second, 16% of the identified proteins are predicted to be lipid-modified, specifically involving double lipid linkage through N-terminal myristoylation, S-palmitoylation, C-terminal prenylation, or glycosylphosphatidylinositol anchors. Thus, our approach led for the first time to the identification of a large number of peripheral proteins as part of the plasma membrane and allowed the functionality of the plasma membrane in the cell context to be reconsidered.     

Optimization of the isotope-coded affinity tag-labeling procedure for quantitative proteome analysis

The combination of isotope coded affinity tag (ICAT) reagents and tandem mass spectrometry constitutes a new method for quantitative proteomics. It involves the site-specific, covalent labeling of proteins with isotopically normal or heavy ICAT reagents, proteolysis of the combined, labeled protein mixture, followed by the isolation and mass spectrometric analysis of the labeled peptides. The method critically depends on labeling protocols that are specific, quantitative, general, robust, and reproducible. Here we describe the systematic evaluation of important parameters of the labeling protocol and describe optimized labeling conditions. The tested factors include the ICAT reagent concentration, the influence of the protein, SDS, and urea concentrations on the labeling reaction, and the reaction time. We demonstrate that using the optimized conditions specific and quantitative labeling was achieved on standard proteins as well as in complex protein mixtures such as a yeast cell lysate.     

Proteomic discovery of protease substrates

Elucidation of in vivo substrate degradomes of a protease is a daunting endeavor because of the large number of proteins in a proteome and often minute and transient amounts of key substrates. Proteomic substrate screens for proteases are currently experiencing impressive progress. Mass spectrometry-based global proteome analysis, interfaced with liquid-chromatography and together with stable isotope labeling strategies, has provided increased coverage and sensitivity for quantitative proteomics. ICAT and iTRAQ labeling have been used to identify a plethora of new matrix metalloproteinase substrates. Emerging techniques focus on the quantitative analysis of proteolytically generated neo amino-termini, which we call terminopes, on a system-wide basis. In vivo SILAC pulse-chase experiments have also enabled the study of individual protein turnover and global proteome dynamics in cells and whole organisms. Together with activity-based probes for the profiling of functional proteases, there is now in place an array of complementary technologies to dissect the 'protease web' and its distortion in pathology.