Optimization of mass spectrometry-compatible surfactants for shotgun proteomics

An optimization and comparison of trypsin digestion strategies for peptide/protein identifications by microLC-MS/MS with or without MS compatible detergents in mixed organic-aqueous and aqueous systems was carried out in this study. We determine that adding MS-compatible detergents to proteolytic digestion protocols dramatically increases peptide and protein identifications in complex protein mixtures by shotgun proteomics. Protein solubilization and proteolytic efficiency are increased by including MS-compatible detergents in trypsin digestion buffers. A modified trypsin digestion protocol incorporating the MS compatible detergents consistently identifies over 300 proteins from 5 microg of pancreatic cell lysates and generates a greater number of peptide identifications than trypsin digestion with urea when using LC-MS/MS. Furthermore, over 700 proteins were identified by merging protein identifications from trypsin digestion with three different MS-compatible detergents. We also observe that the use of mixed aqueous and organic solvent systems can influence protein identifications in combinations with different MS-compatible detergents. Peptide mixtures generated from different MS-compatible detergents and buffer combinations show a significant difference in hydrophobicity. Our results show that protein digestion schemes incorporating MS-compatible detergents generate quantitative as well as qualitative changes in observed peptide identifications, which lead to increased protein identifications overall and potentially increased identification of low-abundance proteins.     

Mass processing--an improved technique for protein identification with mass spectrometry data.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis following tryptic digestion of polyacrylamide gel pieces is a common technique used to identify proteins. This approach is rapid, sensitive, and user friendly, and is becoming widely available to scientists in a variety of biological fields. Here we introduce a simple and effective strategy called "mass processing" where the list of masses generated from a mass spectrometer undergoes two stages of data reduction before identification. Mass processing improves the ability to identify in-gel tryptic-digested proteins by reducing the number of nonsample masses submitted to protein identification database search engines. Our results demonstrate that mass processing improves the statistical score and rank of putative protein identifications, especially with low-quantity samples, thus increasing the ability to confidently identify proteins with mass spectrometry data.     

Prediction of missed cleavage sites in tryptic peptides aids protein identification in proteomics

Protein identification via peptide mass fingerprinting (PMF) remains a key component of high-throughput proteomics experiments in post-genomic science. Candidate protein identifications are made using bioinformatic tools from peptide peak lists obtained via mass spectrometry (MS). These algorithms rely on several search parameters, including the number of potential uncut peptide bonds matching the primary specificity of the hydrolytic enzyme used in the experiment. Typically, up to one of these "missed cleavages" are considered by the bioinformatics search tools, usually after digestion of the in silico proteome by trypsin. Using two distinct, nonredundant datasets of peptides identified via PMF and tandem MS, a simple predictive method based on information theory is presented which is able to identify experimentally defined missed cleavages with up to 90% accuracy from amino acid sequence alone. Using this simple protocol, we are able to "mask" candidate protein databases so that confident missed cleavage sites need not be considered for in silico digestion. We show that that this leads to an improvement in database searching, with two different search engines, using the PMF dataset as a test set. In addition, the improved approach is also demonstrated on an independent PMF data set of known proteins that also has corresponding high-quality tandem MS data, validating the protein identifications. This approach has wider applicability for proteomics database searching, and the program for predicting missed cleavages and masking Fasta-formatted protein sequence databases has been made available via http:// ispider.smith.man.ac uk/MissedCleave.     

Comprehensive proteomics in yeast using chromatographic fractionation, gas phase fractionation, protein gel electrophoresis, and isoelectric focusing

We have investigated the use of a variety of different techniques to identify as many proteins as possible in a yeast lysate, with the aim of investigating the overlap and complementarity of data from different approaches. A standard lysate was prepared from log phase yeast (Saccharomyces cerevisiae). This was then subjected to analysis via five different approaches aimed at identifying as many proteins as possible using an ion trap mass spectrometer. The total number of non-redundant protein identifications from each experiment was: 524 proteins by 2-D (SCX/C18) nanoflow liquid chromatography-liquid chromatography tandem mass spectrometry (nanoLC-LC MS/MS (MudPIT)); 381 proteins by nanoLC-MS/MS with gas phase fractionation by mass range selection; 390 proteins by nanoLC-MS/MS with gas phase fractionation by ion abundance selection; 898 proteins by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) separation of proteins, in-gel digestion, and nanoLC-MS/MS of gel slices; and 422 proteins by isoelectric focusing of proteins, in-gel digestion and nanoLC-MS/MS of gel slices. The total number of non-redundant protein identifications in the five experiments was 1204. Combining only the two best experiments, the SDS-PAGE gel slices and the Mudpit, produces 1024 proteins identified, more than 85% of the total. Clearly, combining a Mudpit analysis with an SDS-PAGE gel slice experiment gives the greatest amount of protein identification information from a limited amount of sample.     

In-gel isoelectric focusing of peptides as a tool for improved protein identification

In the analysis of proteins in complex samples, pre-fractionation is imperative to obtain the necessary depth in the number of reliable protein identifications by mass spectrometry. Here we explore isoelectric focusing of peptides (peptide IEF) as an effective fractionation step that at the same time provides the added possibility to eliminate spurious peptide identifications by filtering for pI. Peptide IEF in IPG strips is fast and sharply confines peptides to their pI. We have evaluated systematically the contribution of pI filtering and accurate mass measurements on the total number of protein identifications in a complex protein mixture (Drosophila nuclear extract). At the same time, by varying Mascot identification cutoff scores, we have monitored the false positive rate among these identifications by searching reverse protein databases. From mass spectrometric analyses at low mass accuracy using an LTQ ion trap, false positive rates can be minimized by filtering of peptides not focusing at their expected pI. Analyses using an LTQ-FT mass spectrometer delivers low false positive rates by itself due to the high mass accuracy. In a direct comparison of peptide IEF with SDS-PAGE as a pre-fractionation step, IEF delivered 25% and 43% more proteins when identified using FT-MS and LTQ-MS, respectively. Cumulatively, 2190 non redundant proteins were identified in the Drosophila nuclear extract at a false positive rate of 0.5%. Of these, 1751 proteins (80%) were identified after peptide IEF and FT-MS alone. Overall, we show that peptide IEF allows to increase the confidence level of protein identifications, and is more sensitive than SDS-PAGE.     

An Efficient In-gel Digestion Protocol for Mass Spectral Analysis by MALDI-TOF-MS and MS/MS and Its Use for Proteomic Analysis of Vigna mungo Leaves

An efficient protocol for in-gel digestion of Coomassie-stained protein spots has been established for mass analysis by matrix-assisted laser desorption/ionization-mass spectrometry (MS) and for tandem mass spectrometry (MS/MS). Identification of Vigna mungo leaf proteome from two-dimensional gel electrophoresis was done employing the protocol. About 300 proteins spots were consistently detected in three replicate gels. Optimization of the destaining process, digestion using 25 ng/μl trypsin in 20 μl trypsin buffer, and omission of peptide extraction step significantly increased the number of matched peptides and sequence coverage. Reliable characterization of 109 proteins by MS as well as tandem sequencing by MS/MS (PRIDE Accession no. 15318) suggests the potential application of the modified protocol for high throughput proteome analysis to unravel disputes in characterization of plant proteins in fundamental or applied research.     

Quantitative Assessment of In-solution Digestion Efficiency Identifies Optimal Protocols for Unbiased Protein Analysis

The majority of mass spectrometry-based protein quantification studies uses peptide-centric analytical methods and thus strongly relies on efficient and unbiased protein digestion protocols for sample preparation. We present a novel objective approach to assess protein digestion efficiency using a combination of qualitative and quantitative liquid chromatography-tandem MS methods and statistical data analysis. In contrast to previous studies we employed both standard qualitative as well as data-independent quantitative workflows to systematically assess trypsin digestion efficiency and bias using mitochondrial protein fractions. We evaluated nine trypsin-based digestion protocols, based on standard in-solution or on spin filter-aided digestion, including new optimized protocols. We investigated various reagents for protein solubilization and denaturation (dodecyl sulfate, deoxycholate, urea), several trypsin digestion conditions (buffer, RapiGest, deoxycholate, urea), and two methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate). Our data-independent quantitative liquid chromatography-tandem MS workflow quantified over 3700 distinct peptides with 96% completeness between all protocols and replicates, with an average 40% protein sequence coverage and an average of 11 peptides identified per protein. Systematic quantitative and statistical analysis of physicochemical parameters demonstrated that deoxycholate-assisted in-solution digestion combined with phase transfer allows for efficient, unbiased generation and recovery of peptides from all protein classes, including membrane proteins. This deoxycholate-assisted protocol was also optimal for spin filter-aided digestions as compared with existing methods.MS-based proteomics is an indispensable technology for the characterization of complex biological systems, including relative or absolute protein expression levels and protein post-translational modifications. The most popular method for analyzing medium to high complexity protein samples in large-scale proteomics relies on protein digestion by using the endoprotease trypsin. Analysis and sequencing of tryptic peptides by liquid chromatography-tandem MS (LC-MS/MS)¹ then enables identification and determination of protein expression levels based on the peptide ion abundance level or the (fragment) ion intensities of identified peptides. This peptide-centric approach thus strongly relies on efficient, unbiased and reproducible protein digestion protocols. Efficiency is required to maximize the number of detectable peptides per protein (coverage) to distinguish unique proteins within protein families with similar sequences and/or sequence variants, and to detect post-translational modifications. Unbiased generation of peptides is required for the resulting data set to most accurately reflect the relative (stoichiometry) and absolute protein abundance in a sample. A particular protocol should be unbiased with respect to abundance, molecular weight, hydrophobicity and protein class. Membrane proteins for example are often suspected to be underrepresented. For MS-based proteomics approaches several critical steps can be distinguished: (a) disruption and solubilization of cells and protein complexes, (b) protein denaturation and enzymatic proteolysis, (c) MS-compatible peptide recovery, which normally entails removal of reagent leftovers and desalting before MS analysis, (d) adequate peptide separation (achieved by liquid chromatography), and (e) MS peptide analysis and sequencing (MS/MS), including the chosen data acquisition strategy.Comparative evaluations of digestion protocols generally consist of qualitative studies using standard tandem mass spectrometry. These approaches may reveal efficiency (i.e. more identifications), but are unable to reveal digestion protocol induced bias with respect to peptide and protein abundance, including membrane proteins. In addition, most data-dependent acquisition workflows are intrinsically biased, which is detrimental for making comparisons. The aim of the present study was to systematically assess efficiency and bias of trypsin-based protocols applying both standard qualitative and label-free quantitative MS approaches.The in-gel digestion protocol for proteomics, established over 15 years ago (1), has been the cornerstone method affording robust protein identifications from many sample types. Although sodium dodecyl sulfate (SDS) interferes with trypsin digestion and hampers LC-MS analysis, this powerful detergent can still be used to achieve complete protein solubilization as gel-separation is an effective way to remove interfering substances. Gel-based approaches are however not optimal for protein samples of increasing complexity and dynamic range (2). Inherent and practical limitations include, for example, concentration-dependent, incomplete peptide recovery and error-prone handling procedures (3–6). This hampers throughput, reproducibility and unbiased protein analysis, which in recent years has prompted a shift toward the application and optimization of in-solution digestion procedures.Previous comparative studies revealed that for in-solution digestions, the acid labile and MS-compatible detergent RapiGest performed most favorably compared with buffer only, urea, other detergents and organic solvents (7–9). Sodium deoxycholate (SDC), naturally found in mammalian bile (10), has emerged as a cheaper MS-compatible detergent for in-solution digestion (11). Unlike other detergents, SDC was found to enhance trypsin activity almost fivefold at a concentration of 1% (12). Like RapiGest, SDC can also be removed by acidification, but potentially without detrimental peptide loss if a phase separation protocol involving organic solvent is applied (12).An alternative strategy is to perform protein digestion on spin filter devices, introduced a few years ago by Manza and co-workers (13), and further developed by Wisniewski et al. (14). This approach allows the use of SDS to first achieve complete protein solubilization followed by removal of the detergent through repeated washes with urea (14). This is an effective way to remove interfering chemicals and small molecules after protein solubilization, and before digestion, without substantial sample loss. Although this protocol is touted to be a highly effective and universal method for any type of sample, digestion is performed using urea or buffer only and has so far not been evaluated in combination with detergents such as SDC.For our comparative study we selected protocols and methods based on spin filter-aided and standard in-solution digestion that were previously reported optimal and we also report novel optimized protocols. We investigated several experimental parameters including reagents for protein solubilization and denaturation (SDS, SDC, urea), spin filter aided removal of SDS before digestion (urea, SDC, buffer), trypsin digestion conditions (buffer, RapiGest, SDC, urea), and methods for removal of detergents before analysis of peptides (acid precipitation or phase separation with ethyl acetate).Mitochondria are organelles carrying out key metabolic processes fundamental for cellular function (15). The mitochondrial proteome is predicted to contain up to a thousand proteins (16) and is very heterogeneous with a wide range of protein pI, molecular weight and hydrophobicity values (17). We selected mitochondrial preparations to serve as model sample of medium complexity, containing a favorable combination of peptide and protein classes, including soluble and insoluble membrane-anchored or integral proteins.Using standard qualitative as well as data-independent quantitative LC-MS/MS workflows we demonstrate that SDC-based protocols combined with phase separation are the most optimal for both in-solution and filter-aided tryptic digestion, yielding the highest efficiency and lowest bias. This workflow enabled quantitative and objective assessment of various protein digestion conditions, identifying optimal protocols for efficient and unbiased protein analysis.     

Determination of the complete amino acid sequence for the coat protein of brome mosaic virus by time-of-flight mass spectrometry. Evidence for mutations associated with change of propagation host

Time-of-flight mass spectrometry (TOFMS) has been applied to determine the complete coat protein amino acid sequences of a number of distinct brome mosaic virus (BMV) isolates. Ionization was carried out by both electrospray ionization and matrix-assisted laser desorption/ionization (MALDI). After determining overall coat protein masses, the proteins were digested with trypsin or Lys-C proteinases, and the digestion products were analyzed in a MALDI QqTOF mass spectrometer. The N terminus of the coat protein was found to be acetylated in each BMV isolate analyzed. In one isolate (BMV-Valverde), the amino acid sequence was identical to that predicted from the cDNA sequence of the "type" isolate, but deviations from the predicted amino acid sequence were observed for all the other isolates analyzed. When isolates were propagated in different host taxa, modified coat protein sequences were observed in some cases, along with the original sequence. Sequencing by TOFMS may therefore provide a basis for monitoring the effects of host passaging on a virus at the molecular level. Such TOFMS-based analyses assess the complete profiles of coat protein sequences actually present in infected tissues. They are therefore not subject to the selection biases inherent in deducing such sequences from reverse-transcribed viral RNA and cloning the resulting cDNA.     

Processing of high-titer prions for mass spectrometry inactivates prion infectivity

Prions represent a class of universally fatal and transmissible neurodegenerative disorders that affect humans and other mammals. The prion agent contains a pathologically aggregated form of the host prion protein that can transmit infectivity without any bacterial or viral component and is thus difficult to inactivate using disinfection protocols designed for infectious microorganisms. Methods for prion inactivation include treatment with acids, bases, detergents, bleach, prolonged autoclaving and incineration. During these procedures, the sample is often either destroyed or damaged such that further analysis for research purposes is compromised. In this study we show that a straightforward denaturation and in-gel protease digestion protocol used to prepare prion-infected samples for mass spectroscopy leads to the loss of at least 7 logs of prion infectivity, yielding a final product that fails to transmit prion disease in vivo. We further show that the resultant sample remains suitable for mass spectrometry-based protein identifications. Thus, the procedure described can be used to prepare prion-infected samples for mass spectrometry analysis with greatly reduced biosafety concerns.     

Three-layer sandwich gel electrophoresis: a method of salt removal and protein concentration in proteome analysis

Sample preparation plays a critical role in successful proteomic applications. Features of electrospray mass spectrometry impose limits on the types of buffers, detergents and other reagents that can be used in sample preparation. Unfortunately, many of these mass spectrometry incompatible reagents significantly enhance protein recoveries from complex matrices. This problem prompted our search for a better cleanup protocol. Our data suggest that the Three-layer Sandwich Gel Electrophoresis (TSGE) protocol can solve this problem and provide near quantitative recovery of extremely low concentration proteins from harsh solutions, a feature not available from other cleanup protocols. The hallmark of the TSGE protocol is the combination of the properties of agarose gels (that serve as the matrix to immobilize the proteins of interest) with low- and high-percentage polyacrylamide gels (that serve as the concentration and sealing layers, respectively). By electrophoretically driving the proteins of interest from the agarose matrix into the concentration layer, the TSGE protocol simultaneously concentrates the sample in the concentration layer and provides an environment amenable to downstream buffer exchange and proteolytic digestion. In combination with 2D-LC-MS/MS, the TSGE protocol was evaluated in the analysis of a whole cell extract from the protozoan parasite Toxoplasma gondii. Comparison of our experimental proteomic results with in silico predictions from gene data indicated that TSGE did not bias the protein identification.     

KYSS: Mass spectrometry data quality assessment for protein analysis and large-scale proteomics

We introduce the computer tool “Know Your Samples” (KYSS) for assessment and visualisation of large scale proteomics datasets, obtained by mass spectrometry (MS) experiments. KYSS facilitates the evaluation of sample preparation protocols, LC peptide separation, and MS and MS/MS performance by monitoring the number of missed cleavages, precursor ion charge states, number of protein identifications and peptide mass error in experiments. KYSS generates several different protein profiles based on protein abundances, and allows for comparative analysis of multiple experiments. KYSS was adapted for blood plasma proteomics and provides concentrations of identified plasma proteins. We demonstrate the utility of the KYSS tool for MS based proteome analysis of blood plasma and for assessment of hydrogel particles for depletion of abundant proteins in plasma. The KYSS software is open source and is freely available at http://kyssproject.github.io/.     

"Top Down" characterization is a complementary technique to peptide sequencing for identifying protein species in complex mixtures

At present, mass spectrometry provides a rapid and sensitive means for making conclusive protein identifications from complex mixtures. Sequencing tryptic peptides derived from proteolyzed protein samples, also known as the "Bottom Up" approach, is the mass spectrometric gold standard for identifying unknowns. An alternative technology, "Top Down" characterization, is emerging as a viable option for protein identifications, which involves analyzing the intact unknowns for accurate mass and amino acid sequence tags. In this paper, both characterization methods were employed to more comprehensively differentiate two early-eluting peaks in a process-scale size-exclusion chromatography (SEC) step for a recombinant, immunoglobulin gamma-1 (IgG-1) fusion protein. The contents of each SEC peak were enzymatically digested, and the resulting peptides were mapped using reversed-phase (RP) HPLC-ion trap MS. Many low-level UV signals were observed among the fusion protein-related peptide peaks. These unknowns were collected, concentrated, and analyzed using nanoelectrospray (nanoES) collision-induced dissociation (CID) tandem (MS/MS) mass spectrometry for identification. The peptide sequencing experiments resulted in the identification of twenty host cell-related proteins. Following peptide mapping, the contents of the two SEC peaks were protein mass profiled using on-line RP HPLC coupled to a high-resolution, quadrupole time-of-flight (Qq/TOF) MS. Unknown proteins were also collected, concentrated, and dissociated using nanoES CID MS/MS. Intact protein CID experiments and accurate molecular weight information allowed for the identification of three full length host cell-derived proteins and numerous clips from these and additional proteins. The accurate molecular weight values allowed for the assignment of N- and C-terminal processing, which is difficult to conclusively access from peptide mapping data. The peptide-mapping experiments proved to be far more effective for making protein identifications from complex mixtures, whereas the protein mass profiling was useful for assessing modifications and distinguishing protein clips from full length species.     

Accelerated identification of proteins by mass spectrometry by employing covalent pre-gel staining with Uniblue A

Background

The identification of proteins by mass spectrometry is a standard method in biopharmaceutical quality control and biochemical research. Prior to identification by mass spectrometry, proteins are usually pre-separated by electrophoresis. However, current protein staining and de-staining protocols are tedious and time consuming, and therefore prolong the sample preparation time for mass spectrometry.

Methodology and Principal Findings

We developed a 1-minute covalent pre-gel staining protocol for proteins, which does not require de-staining before the mass spectrometry analysis. We investigated the electrophoretic properties of derivatized proteins and peptides and studied their behavior in mass spectrometry. Further, we elucidated the preferred reaction of proteins with Uniblue A and demonstrate the integration of the peptide derivatization into typical informatics tools.

Conclusions and Significance

The Uniblue A staining method drastically speeds up the sample preparation for the mass spectrometry based identification of proteins. The application of this chemo-proteomic strategy will be advantageous for routine quality control of proteins and for time-critical tasks in protein analysis.     

Comparison of extraction methods for the comprehensive analysis of mouse brain proteome using shotgun-based mass spectrometry

This study compares 16 different extraction methods for the comprehensive extraction of mouse brain proteome in combination with "shotgun"-based mass spectrometry (MS). Membrane proteins (MPs) are responsible for a large part of the regulatory functions of the cell and are therefore of great interest to extract and analyze. Sixteen protein extraction protocols were evaluated in regards to protein yield and number of identified proteins with emphasis on MPs. The extracted proteins were delipidated, on-filter digested, and analyzed by reversed phase nanoliquid chromatography (RP-nanoLC) in combination with electrospray ionization (ESI) tandem mass spectrometry (MS/MS) using a 7 T hybrid LTQ-FT mass spectrometer. Detergent-based lysis buffers showed higher efficiencies and yields in the extraction of proteins from the brain tissue compared to solubilization with organic solvents or organic acids. The detergent octyl-β-D-glucopyranoside gave the highest number of identified proteins (541) as well as numbers and percentages of identified MPs (29%). Detergent-based protocols are the best sample preparation tools for central nervous system (CNS) tissue and can readily be applied to screen for candidate biomarkers of neurological diseases.     

The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: I. Statistically annotated datasets for peptide sequences and proteins identified via the application of ICAT and tandem mass spectrometry to proteins copurifying with T cell lipid rafts

Lipid rafts were prepared according to standard protocols from Jurkat T cells stimulated via T cell receptor/CD28 cross-linking and from control (unstimulated) cells. Co-isolating proteins from the control and stimulated cell preparations were labeled with isotopically normal (d0) and heavy (d8) versions of the same isotope-coded affinity tag (ICAT) reagent, respectively. Samples were combined, proteolyzed, and resultant peptides fractionated via cation exchange chromatography. Cysteine-containing (ICAT-labeled) peptides were recovered via the biotin tag component of the ICAT reagents by avidin-affinity chromatography. On-line micro-capillary liquid chromatography tandem mass spectrometry was performed on both avidin-affinity (ICAT-labeled) and flow-through (unlabeled) fractions. Initial peptide sequence identification was by searching recorded tandem mass spectrometry spectra against a human sequence data base using SEQUEST software. New statistical data modeling algorithms were then applied to the SEQUEST search results. These allowed for discrimination between likely "correct" and "incorrect" peptide assignments, and from these the inferred proteins that they collectively represented, by calculating estimated probabilities that each peptide assignment and subsequent protein identification was a member of the "correct" population. For convenience, the resultant lists of peptide sequences assigned and the proteins to which they corresponded were filtered at an arbitrarily set cut-off of 0.5 (i.e. 50% likely to be "correct") and above and compiled into two separate datasets. In total, these data sets contained 7667 individual peptide identifications, which represented 2669 unique peptide sequences, corresponding to 685 proteins and related protein groups.     

Evaluation of three different protocols of protein extraction for Arabidopsis thaliana leaf proteome analysis by two-dimensional electrophoresis

This work was performed to compare three precipitation protocols of protein extraction for 2-DE proteomic analysis using Arabidopsis leaf tissue: TCA-acetone, phenol, and TCA-acetone-phenol. There were no statistically significant differences in protein yield between the three methods. Samples were subjected to 2-DE in the 5 to 8 pH and 14-80 kDa ranges. The TCA-acetone-phenol protocol provided the best results in terms of spot focusing, resolved spots, spot intensity, unique spots detected, and reproducibility. In all, 93 qualitative or quantitative statistically significant differential spots were found between the three protocols. The 2-DE map of TCA-acetone-phenol extracts presented more resolved spots above 40 kDa, with no pI-dependent differences observed between the three protocols. 54 spots were selected for trypsin digestion, and the peptides were analyzed by MALDI-TOF-TOF MS. After database search using peptide mass fingerprinting, and MS/MS combined search, 30 proteins were identified, the proteins from chloroplastic photosynthetic and carbohydrate metabolism being those most highly represented. From these data, we were able to conclude that each extraction protocol had its main features. Considering this, the workflow of any standard comparative proteomic experiment should include the optimization and adaptation of the protein extraction protocol to the plant tissue and to the particular objective pursued.     

Proteomic characterization of wheat amyloplasts using identification of proteins by tandem mass spectrometry

We describe the initial characterization of the wheat amyloplast proteome, consisting of the identification and classification of 171 proteins. Whole amyloplasts and purified amyloplast membranes were prepared from wheat (Triticum aestivum). Protein extracts were examined by one-dimensional and two-dimensional electrophoresis, followed by high performance liquid chromatography-tandem mass spectrometry of separated proteins. Tandem mass spectrometry data of individual peptides was then searched by SEQUEST, using a database containing known protein sequences from both wheat and other homologous cereal crops. Using this approach we identified 108 proteins from whole amyloplasts and 63 proteins from purified amyloplast membranes. The majority of protein identifications were derived from protein sequences from cereal crops other than wheat, for which relatively little gene sequence data is available. The highest percentage of protein identifications obtained from any individual species was 46% of the total number of proteins identified, using sequence data found in our proprietary rice (Oryza sativa) genome database.     

Label-free mass spectrometry-based relative quantification of proteins separated by one-dimensional gel electrophoresis

Here we present a matrix-assisted laser desorption/ionization tandem time-of-flight (MALDI–TOF/TOF)-based label-free relative protein quantification strategy that involves sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS–PAGE) separation of proteins followed by in-gel trypsin digestion. The main problem encountered in gel-based protein quantification is the difficulty in achieving complete and consistent proteolytic digestion. To solve this problem, we developed a high-pressure-assisted in-gel trypsin digestion method that is based on pressure cycling technology (PCT). The PCT approach performed at least as well as the conventional overnight in-gel trypsin digestion approach in parameters such as number of peaks detected, number of peptides identified, and sequence coverage, and the digestion time was reduced to 45 min. The gel/mass spectrometry (MS)-based label-free protein quantification method presented in this work proved the applicability of the signal response factor concept for relative protein quantification previously demonstrated by other groups using the liquid chromatography (LC)/MS platform. By normalizing the average signal intensities of the three most intense peptides of each protein with the average intensities of spiked synthetic catalase tryptic peptides, which we used as an internal standard, we observed spot-to-spot and lane-to-lane coefficients of variation of less than 10 and 20%, respectively. We also demonstrated that the method can be used for determining the relative quantities of proteins comigrating during electrophoretic separation.     

Profiling of myelin proteins by 2D-gel electrophoresis and multidimensional liquid chromatography coupled to MALDI TOF-TOF mass spectrometry

The myelin sheath is an electrically insulating layer that consists of lipids and proteins. It plays a key role in the functioning of the nervous system by allowing fast saltatory conduction of nerve pulses. Profiling of the proteins present in myelin is an indispensable prerequisite to better understand the molecular aspects of this dynamic, functionally active membrane. Two types of protein, the myelin basic protein and the proteolipid protein, account for nearly 85% of the protein content in myelin. Identification and characterization of the other "minor" proteins is, in this respect, a real challenge. In the present work, two proteomic strategies were applied in order to study the protein composition of myelin from the murine central nervous system. First, the protein mixture was separated by 2D-gel electrophoresis and, after spot excision and in-gel digestion, samples were analyzed by mass spectrometry. Via this approach, we identified 57 protein spots, corresponding to 38 unique proteins. Alternatively, the myelin sample was digested by trypsin and the resulting peptide mixture was further analyzed by off-line 2D-liquid chromatography. After the second-dimension separation (nanoLC), the peptides were spotted "on-line" onto a MALDI target and analyzed by MALDI TOF-TOF mass spectrometry. We identified 812 peptides by MALDI MS/MS, representing 93 proteins. Membrane proteins, low abundant proteins, and highly basic proteins were all represented in this shotgun proteomic approach. By combining the results of both approaches, we can present a comprehensive proteomic map of myelin, comprising a total of 103 protein identifications, which is of utmost importance for the molecular understanding of white matter and its disorders.     

Analysis of membrane proteins from human chronic myelogenous leukemia cells: comparison of extraction methods for multidimensional LC-MS/MS

An important strategy for "shotgun proteomics" profiling involves solution proteolysis of proteins, followed by peptide separation using multidimensional liquid chromatography and automated sequencing by mass spectrometry (LC-MS/MS). Several protocols for extracting and handling membrane proteins for shotgun proteomics experiments have been reported, but few direct comparisons of different protocols have been reported. We compare four methods for preparing membrane proteins from human cells, using acid labile surfactants (ALS), urea, and mixed organic-aqueous solvents. These methods were compared with respect to their efficiency of protein solubilization and proteolysis, peptide and protein recovery, membrane protein enrichment, and peptide coverage of transmembrane proteins. Overall, approximately 50-60% of proteins recovered were membrane-associated, identified from Gene Ontology annotations and transmembrane prediction software. Samples extracted with ALS, extracted with urea followed by dilution, or extracted with urea followed by desalting yielded comparable peptide recoveries and sequence coverage of transmembrane proteins. In contrast, suboptimal proteolysis was observed with organic solvent. Urea extraction followed by desalting may be a particularly useful approach, as it is less costly than ALS and yields satisfactory protein denaturation and proteolysis under conditions that minimize reactivity with urea-derived cyanate. Spectral counting was used to compare datasets of proteins from membrane samples with those of soluble proteins from K562 cells, and to estimate fold differences in protein abundances. Proteins most highly abundant in the membrane samples showed enrichment of integral membrane protein identifications, consistent with their isolation by differential centrifugation.