The utility of proteases in proteomics,from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.     

基于马尔科夫链的胰蛋白酶肽段蛋白酶切位点概率预测

在基于质谱技术的蛋白质鉴定过程中,数据库搜索是主要的方法。漏切位点和酶切规则决定了图谱候选肽段的范围,是数据库搜索算法的重要参数。对于常用的胰蛋白酶切来说,除了局部构象、三维结构、实验条件,以及其它偶然因素会影响赖氨酸K或者精氨酸R后的位点能否被酶切外,该位点附近的其它氨基酸也会影响蛋白水解酶的酶切效果。从质谱图谱中时常会鉴定出包含漏切位点的肽段,因此,预测蛋白质的酶切位点能够为数据库搜索算法提供更为可靠的模型,也能够为了解和分析蛋白质的酶切规律提供依据。本文提出了一种基于马尔科夫(Markov)链的预测方法,能够利用蛋白质的序列信息来预测候选酶切位点的酶切概率,在蛋白酶切过程中,预测肽段的覆盖率可以达到85%以上。     

Systematic and quantitative comparison of digest efficiency and specificity reveals the impact of trypsin quality on MS-based proteomics

Trypsin is the most frequently used proteolytic enzyme in mass spectrometry-based proteomics. Beside its good availability, it also offers some major advantages such as an optimal average peptide length of ~ 14 amino acids, and typically the presence of at least two defined positive charges at the N-terminus as well as the C-terminal Arg/Lys, rendering tryptic peptides well suited for CID-based LC-MS/MS. Here, we conducted a systematic study of different types of commercially available trypsin in order to qualitatively and quantitatively compare cleavage specificity, efficiency as well as reproducibility and the potential impact on quantitation and proteome coverage. We present a straightforward strategy applied to complex digests of human platelets, comprising (1) digest controls using a monolithic column HPLC-setup, (2) SCX enrichment of semitryptic/nonspecific peptides, (3) targeted MRM analysis of corresponding full cleavage/missed cleavage peptide pairs as well as (4) LC-MS analyses of complete digests with a three-step data interpretation. Thus, differences in digest performance can be readily assessed, rendering these procedures extremely beneficial to quality control not only the trypsin of choice, but also to effectively compare as well as optimize different digestion conditions and to evaluate the reproducibility of a dedicated digest protocol for all kinds of quantitative proteome studies.     

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.     

Proteomic analysis of striated muscle

The techniques collectively known as proteomics are useful for characterizing the protein phenotype of a particular tissue or cell as well as quantitatively identifying differences in the levels of individual proteins following modulation of a tissue or cell. In the area of striated muscle research, proteomics has been a useful tool for identifying qualitative and quantitative changes in the striated muscle protein phenotype resulting from either disease or physiological modulation. Proteomics is useful for these investigations because many of the changes in the striated muscle phenotype resulting from either disease or changes in physiological state are qualitative and not quantitative changes. For example, modification of striated muscle proteins by phosphorylation and proteolytic cleavage are readily observed using proteomic technologies while these changes would not be identified using genomic technology. In this review, I will discuss the application of proteomic technology to striated muscle research, research designed to identify key protein changes that are either causal for or markers of a striated muscle disease or physiological condition.     

A clean, more efficient method for in-solution digestion of protein mixtures without detergent or urea

Proteolytic digestion of a complicated protein mixture from an organelle or whole-cell lysate is usually carried out in a dilute solution of a denaturing buffer, such as 1-2 M urea. Urea must be subsequently removed by C18 beads before downstream analysis such as HPLC/MS/MS or complete methylation followed by IMAC isolation of phosphopeptides. Here we describe a procedure for digesting a complicated protein mixture in the absence of denaturants. Proteins in the mixture are precipitated with trichloroacetic acid/acetone for denaturation and salt removal and resuspended in NH4HCO3 buffer. After trypsinolysis, the resulting peptides are not contaminated by urea or other nonvolatile salts and can be dried in a SpeedVac to remove NH4HCO3. When this protocol was applied to an extract of A431 cells, 96.8% of the tryptic peptides were completely digested (i.e., had no missed cleavage sites), in contrast to 87.3% of those produced by digestion in urea buffer. We successfully applied this digestion method to analysis of the phosphoproteome of adiposomes from HeLa cells, identifying 33 phosphorylation sites in 28 different proteins. Our digestion method avoids the need to remove urea before HPLC/MS/MS analysis or methylation and IMAC, increasing throughput while reducing sample loss and contamination from sample handling. We believe that this method should be valuable for proteomics studies.     

Improvement of an in-gel tryptic digestion method for matrix-assisted laser desorption/ionization-time of flight mass spectrometry peptide mapping by use of volatile solubilizing agents

The combination of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), in-gel enzymatic digestion of proteins separated by two-dimensional gel electrophoresis and searches of molecular weight in peptide-mass databases is a powerful and well established method for protein identification in proteomics analysis. For successful protein identification by MALDI-TOF mass spectrometry of peptide mixtures, critical parameters include highly specific enzymatic cleavage, high mass accuracy and sufficient numbers and sequence coverage of the peptides which can be analyzed. For in-gel digestion with trypsin, the method employed should be compatible both with enzymatic cleavage and subsequent MALDI-TOF MS analysis. We report here an improved method for preparation of peptides for MALDI-TOF MS mass fingerprinting by using volatile solubilizing agents during the in-gel digestion procedure. Our study clearly demonstrates that modification of the in-gel digestion protocols by addition of dimethyl formamide (DMF) or a mixture of DMF/N,N-dimethyl acetamide at various concentrations can significantly increase the recovery of peptides. These higher yields of peptides resulted in more effective protein identification.     

Computational prediction of proteotypic peptides for quantitative proteomics

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Although such analyses typically assume that a protein's peptide fragments are observed with equal likelihood, only a few so-called 'proteotypic' peptides are repeatedly and consistently identified for any given protein present in a mixture. Using >600,000 peptide identifications generated by four proteomic platforms, we empirically identified >16,000 proteotypic peptides for 4,030 distinct yeast proteins. Characteristic physicochemical properties of these peptides were used to develop a computational tool that can predict proteotypic peptides for any protein from any organism, for a given platform, with >85% cumulative accuracy. Possible applications of proteotypic peptides include validation of protein identifications, absolute quantification of proteins, annotation of coding sequences in genomes, and characterization of the physical principles governing key elements of mass spectrometric workflows (e.g., digestion, chromatography, ionization and fragmentation).     

Optimized nLC-MS workflow for laser capture microdissected breast cancer tissue

Reliable sample preparation is of utmost importance for comparative proteome analysis, particularly when investigating minute amounts of clinical specimens, such as laser capture microdissected tumor tissue. In this study, we present an optimized nanoLC-MS workflow specifically for the analysis of laser capture microdissected breast cancer tissue. Analytical performance of different laser capture microdissection (LCM) functions available on the PALM system, time dependent trypsin digestion efficiency, effect of sample preparation and digestion time on peptide modification, semi-tryptic peptides and missed cleavages were evaluated. Our results show that microdissection from uncoated glass slides results in protein degradation; that protease and phosphatase inhibitors do not result in detectable improvement in number of peptides or semi-tryptic peptides; and that digestion time longer than four hours drastically reduces the number of missed cleavages, but also increases the number of unexpectedly modified peptides. Overalkylation was the most dominant side-reaction, which significantly increased overnight (P=0.05). The latter effect could almost completely be reverted by the use of a quenching agent (P=0.001). Taken together, our results show that it is of importance to carefully control sample handling steps so that reliable protein identification and quantitation can be performed within comparative proteomics studies using LCM. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

Bacterial proteins with cleaved or uncleaved signal peptides of the general secretory pathway

Correct protein compartmentalization is a key step for molecular function and cell viability, and this is especially true for membrane and externalized proteins of bacteria. Recent proteomic reports of Bacillus subtilis have shown that many proteins with Sec-like signal peptides and absence of a transmembrane helix domain are still observed in membrane-enriched fractions, but further evidence about signal peptide cleavage or soluble protein contamination is still needed. Here we report a proteomic screening of identified peptides in culture filtrate, membrane fraction and whole cell lysate of Mycobacterium tuberculosis. We were able to detect peptide sequencing evidence that shows that the predicted signal peptide was kept uncleaved for several types of proteins such as mammalian cell entry (Mce) proteins and PE or PE-PGRS proteins. Label-free quantitation of all proteins identified in each fraction showed that the majority of these proteins with uncleaved signal peptides are, indeed, enriched in the Triton X-114 lipid phase. Some of these proteins are likely to be located in the inner membrane while others may be outer membrane proteins.     

MRMaid 2.0: Mining PRIDE for Evidence-Based SRM Transitions

Abstract Selected reaction monitoring (SRM) is becoming the tool of choice for targeted quantitative proteomics. The fundamental principle of proteomic SRM is that, for a given protein of interest, there is a set of peptides that are unique to that protein. The characteristic retention time (RT), and intact peptide m/z of these so-called proteotypic peptides are then programmed into the mass spectrometer, along with the m/z of high-intensity product ions for targeted quantitation. The particular combination of RT, peptide m/z, and product m/z for a given peptide is referred to as a transition. Selection of the most appropriate set of transitions for a given set of proteins is crucial to any SRM experiment. We previously developed the web-based MRMaid tool, which suggested the optimal transitions for a given human protein by mining spectral evidence from a small in-house database. In this article we present a completely new implementation of MRMaid, which offers substantial improvements over the original. The new version, MRMaid 2.0, uses spectra from the EBI's PRIDE database, which massively increases the coverage and quality of transitions. Transition lists can now be generated for multiple proteins simultaneously, edited within the web browser, and exported for laboratory use.     

18O-labeling quantitative proteomics using an ion trap mass spectrometer

We describe a method for simultaneous identification and quantitation of proteins within complex mixtures. The method consists of 18O-labeling, a simple stable isotope-coding that requires merely enzymatic digestion in 18O-water, in combination with a capillary-liquid chromatography electrospray ion-trap mass spectrometer. In a separate experiment using the same sample and a spike test, we demonstrate that the difference ration was calculated accurately using the 18O-labeling method even if the protein was part of a complex mixture. Our data also suggest that the accuracy of the quantitation can be improved by averaging the difference ratios of several peptides. In comparing our method with the isotope-coded affinity tag (ICAT) method, we show that the 18O-labeling method has the advantages of better recovery and fewer isotope effects. Therefore, the 18O-labeling method is a powerful tool for large-scale proteomics applications.     

Perfluorooctanoic acid for shotgun proteomics

Here, we describe the novel use of a volatile surfactant, perfluorooctanoic acid (PFOA), for shotgun proteomics. PFOA was found to solubilize membrane proteins as effectively as sodium dodecyl sulfate (SDS). PFOA concentrations up to 0.5% (w/v) did not significantly inhibit trypsin activity. The unique features of PFOA allowed us to develop a single-tube shotgun proteomics method that used all volatile chemicals that could easily be removed by evaporation prior to mass spectrometry analysis. The experimental procedures involved: 1) extraction of proteins in 2% PFOA; 2) reduction of cystine residues with triethyl phosphine and their S-alkylation with iodoethanol; 3) trypsin digestion of proteins in 0.5% PFOA; 4) removal of PFOA by evaporation; and 5) LC-MS/MS analysis of the resulting peptides. The general applicability of the method was demonstrated with the membrane preparation of photoreceptor outer segments. We identified 75 proteins from 1 μg of the tryptic peptides in a single, 1-hour, LC-MS/MS run. About 67% of the proteins identified were classified as membrane proteins. We also demonstrate that a proteolytic (18)O labeling procedure can be incorporated after the PFOA removal step for quantitative proteomic experiments. The present method does not require sample clean-up devices such as solid-phase extractions and membrane filters, so no proteins/peptides are lost in any experimental steps. Thus, this single-tube shotgun proteomics method overcomes the major drawbacks of surfactant use in proteomic experiments.     

PatternLab for proteomics: a tool for differential shotgun proteomics

Background  

A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen et al. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.     

Rapid analysis of tryptically digested cerebrospinal fluid using capillary electrophoresis-electrospray ionization-Fourier transform ion cyclotron resonance-mass spectrometry

Mass spectrometry has in recent years been established as the method of choice for protein identification and characterization in proteomics. Capillary electrophoresis (CE) is a fast and efficient method for the separation of peptides and proteins. The on-line combination of CE with Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) has been shown to be a powerful tool in the analysis of complex mixtures of proteins. This paper presents the first results from a proteomic analysis of human cerebrospinal fluid proteins by tryptic digestion and CE-FTICR-MS, where 30 proteins could be identified on a 95% confidence level with mass measurement errors less than 5 ppm.     

Comparison of the electron capture dissociation fragmentation behavior of doubly and triply protonated peptides from trypsin, Glu-C, and chymotrypsin digestion

In bottom-up proteomics, proteolytically derived peptides from proteins of interest are analyzed to provide sequence information for protein identification and characterization. Electron capture dissociation (ECD), which provides more random cleavages compared to "slow heating" techniques such as collisional activation, can result in greater sequence coverage for peptides and proteins. Most bottom-up proteomics approaches rely on tryptic doubly protonated peptides for generating sequence information. However, the effectiveness, in terms of peptide sequence coverage, of tryptic doubly protonated peptides in ECD remains to be characterized. Herein, we examine the ECD fragmentation behavior of 64 doubly- and 64 triply protonated peptides (i.e., a total of 128 peptide ions) from trypsin, Glu-C, and chymotrypsin digestion in a Fourier transform ion cyclotron resonance mass spectrometer. Our findings indicate that when triply protonated peptides are fragmented in ECD, independent of which proteolytic enzyme was used for protein digestion, more c- and z-type product ions are observed, and the number of complementary fragment pairs increases dramatically (44%). In addition, triply protonated peptides provide an increase (26%) in peptide sequence coverage. ECD of tryptic peptides, in both charge states, resulted in higher sequence coverage compared to chymotryptic and Glu-C digest peptides. The peptide sequence coverage we obtained in ECD of tryptic doubly protonated peptides (64%) is very similar to that reported for electron transfer dissociation of the same peptide type (63%).     

Analyzing protease specificity and detecting in vivo proteolytic events using tandem mass spectrometry

Although trypsin remains the most commonly used protease in MS, other proteases may be employed for increasing peptide coverage or generating overlapping peptides. Knowledge of the accurate specificity rules of these proteases is helpful for database search tools to detect peptides, and becomes crucial when label‐free MS is used to discover in vivo proteolytic cleavages. Since in vivo cleavages are inferred by subtracting digestion‐induced cleavages from all observed cleavages, it is important to ensure that the specificity rule used to identify digestion‐induced cleavages are broad enough to capture even minor cleavages produced in digestion, to avoid erroneously identifying them as in vivo cleavages. In this study, we describe MS‐Proteolysis, a software tool for identifying putative sites of in vivo proteolytic cleavage using label‐free MS. The tool is used in conjunction with digestion by trypsin and three other proteases, whose specificity rules are revised and extended before inferring proteolytic cleavages. Finally, we show that comparative analysis of multiple proteases can be used to detect putative in vivo proteolytic sites on a proteome‐wide scale.