Identification of proteolytic cleavage sites by quantitative proteomics

NHS-Ester Tandem Labeling in One Pot Enables 48-Plex Quantitative Proteomics

Stable-isotope labeling strategies are extensively used for multiplex quantitative proteomics. Hybrid-isotope labeling strategies that combine the use of isotopic mass difference labeling and isobaric tags can greatly increase sample multiplexity. In this work, we present a novel hybrid-isotope labeling approach that we termed NHS-ester tandem labeling in one pot (NETLOP). We first optimized 16-plex isobaric TMTpro labeling of lysine residues followed by 2-plex or 3-plex isotopic mTRAQ labeling of peptide N-termini, both of which with commercially available NHS-ester reactive reagents. We then demonstrated the utility of the NETLOP approach by labeling HeLa cell samples and performing proof-of-principle quantitative 32-plex and 48-plex proteomic analyses, each in a single LC-MS/MS experiment. Compared to current hybrid-isotope labeling methods, our NETLOP approach requires no sample cleanup between different labeling steps to minimize sample loss, induces no retention time shifts that compromise quantification accuracy, can be adapted to other NHS-ester isotopic labeling reagents to further increase multiplexity, and is compatible with samples from any origin in a wide array of biological and clinical proteomics applications.

An automated protocol for modelling peptide substrates to proteases

BACKGROUND

Proteases are key drivers in many biological processes, in part due to their specificity towards their substrates. However, depending on the family and molecular function, they can also display substrate promiscuity which can also be essential. Databases compiling specificity matrices derived from experimental assays have provided valuable insights into protease substrate recognition. Despite this, there are still gaps in our knowledge of the structural determinants. Here, we compile a set of protease crystal structures with bound peptide-like ligands to create a protocol for modelling substrates bound to protease structures, and for studying observables associated to the binding recognition.

RESULTS

As an application, we modelled a subset of protease-peptide complexes for which experimental cleavage data are available to compare with informational entropies obtained from protease-specificity matrices. The modelled complexes were subjected to conformational sampling using the Backrub method in Rosetta, and multiple observables from the simulations were calculated and compared per peptide position. We found that some of the calculated structural observables, such as the relative accessible surface area and the interaction energy, can help characterize a protease's substrate recognition, giving insights for the potential prediction of novel substrates by combining additional approaches.

CONCLUSION

Overall, our approach provides a repository of protease structures with annotated data, and an open source computational protocol to reproduce the modelling and dynamic analysis of the protease-peptide complexes.

Synthetic and biological approaches to map substrate specificities of proteases

Proteases are regulators of diverse biological pathways including protein catabolism, antigen processing and inflammation, as well as various disease conditions, such as malignant metastasis, viral infection and parasite invasion. The identification of substrates of a given protease is essential to understand its function and this information can also aid in the design of specific inhibitors and active site probes. However, the diversity of putative protein and peptide substrates makes connecting a protease to its downstream substrates technically difficult and time-consuming. To address this challenge in protease research, a range of methods have been developed to identify natural protein substrates as well as map the overall substrate specificity patterns of proteases. In this review, we highlight recent examples of both synthetic and biological methods that are being used to define the substrate specificity of protease so that new protease-specific tools and therapeutic agents can be developed.

H., Li YM, Wang YF, Liu YH, Lu FP. Evaluation of the site-unspecified peptide identification method for proteolytic peptide mapping

The site-unspecific method could successfully identify most of the peptides from tryptic hydrolysates revealed by site-specific identification.

Identification of Protease Specificity Using Biotin-Labeled Substrates

BACKGROUND

Proteolysis constitutes a major post-translational modification. For example, proteases regulate the activation or inactivation of various proteins, such as enzymes, growth factors, and peptide hormones. Proteases have substrate specificity, and protease expression regulates the specific and regional activation or inactivation of several functional proteins.

METHODS

We demonstrate a novel method for determining protease specificity through the use of MALDI-TOF mass spectrometry with biotin-labeled substrates.

RESULTS

This method was able to determine the specificity of TPCK-trypsin, V8 protease, elastase and cyanogen bromide cleavage, and the results were similar to previous reports. In addition, the method can be used to measure crude samples, such as tumor extracts.

CONCLUSION

We demonstrated that this method could identify protease specificity after simple processing, even for crude samples.

Protease Substrate Profiling by N-Terminal COFRADIC

Detection of (neo-)N-terminal peptides is essential for identifying protease cleavage sites . We here present an update of a well-established and efficient selection method for enriching N-terminal peptides out of peptide mixtures: N-terminal COFRADIC (COmbined FRActional DIagonal Chromatography). This method is based on the old concept of diagonal chromatography, which involves a peptide modification step in between otherwise identical chromatographic separations, with this modification step finally allowing for the isolation of N-terminal peptides by longer retention of non-N-terminal peptides on the resin. N-terminal COFRADIC has been successfully applied in many protease-centric studies, as well as for studies on protein alpha-N-acetylation and on characterizing alternative translation initiation events.

p53 regulates cytoskeleton remodeling to suppress tumor progression

Cancer cells possess unique characteristics such as invasiveness, the ability to undergo epithelial-mesenchymal transition, and an inherent stemness. Cell morphology is altered during these processes and this is highly dependent on actin cytoskeleton remodeling. Regulation of the actin cytoskeleton is, therefore, important for determination of cell fate. Mutations within the TP53 (tumor suppressor p53) gene leading to loss or gain of function (GOF) of the protein are often observed in aggressive cancer cells. Here, we highlight the roles of p53 and its GOF mutants in cancer cell invasion from the perspective of the actin cytoskeleton; in particular its reorganization and regulation by cell adhesion molecules such as integrins and cadherins. We emphasize the multiple functions of p53 in the regulation of actin cytoskeleton remodeling in response to the extracellular microenvironment, and oncogene activation. Such an approach provides a new perspective in the consideration of novel targets for anti-cancer therapy.

Label-free quantitative proteomics and N-terminal analysis of human metastatic lung cancer cells

Proteomic analysis is helpful in identifying cancer-associated proteins that are differentially expressed and fragmented that can be annotated as dysregulated networks and pathways during metastasis. To examine meta-static process in lung cancer, we performed a proteomics study by label-free quantitative analysis and N-terminal analysis in 2 human non-small-cell lung cancer cell lines with disparate metastatic potentials-NCI--H1703 (primary cell, stage I) and NCI-H1755 (metastatic cell, stage IV). We identified 2130 proteins, 1355 of which were common to both cell lines. In the label-free quantitative analysis, we used the NSAF normalization method, resulting in 242 differential expressed proteins. For the N-terminal proteome analysis, 325 N-terminal peptides, including 45 novel fragments, were identified in the 2 cell lines. Based on two proteomic analysis, 11 quantitatively expressed proteins and 8 N-terminal peptides were enriched for the focal adhesion pathway. Most proteins from the quantitative analysis were upregulated in metastatic cancer cells, whereas novel fragment of CRKL was detected only in primary cancer cells. This study increases our understanding of the NSCLC metastasis proteome.

Solid-phase N-terminal peptide enrichment study by optimizing trypsin proteolysis on homoarginine-modified proteins by mass spectrometry

RATIONALE

Proteolytic cleavages generate active precursor proteins by creating new N-termini in the proteins. A number of strategies have recently been published regarding the enrichment of original or newly formed N-terminal peptides using guanidination of lysine residues and amine-reactive reagents. For effective enrichment of N-terminal peptides, the efficiency of trypsin proteolysis on homoarginine (guanidinated) modified proteins must be understood and simple and versatile solid-phase N-terminal capture strategies should be developed.

METHODS

We present here a mass spectrometry (MS)-based study to evaluate and optimize the trypsin proteolysis on a guanidinated-modified protein. Trypsin proteolysis was studied using different amounts of trypsin to modified protein ratios. To capture the original N-termini, after guanidination of proteins, original N-termini were acetylated and the proteins were digested with trypsin. The newly formed N-terminal tryptic peptides were captured with a new amine reactive acid-cleavable solid-phase reagent. The original N-terminal peptides were then collected from the supernatant of the solution.

RESULTS

We demonstrated a detailed study of the efficiency of enzyme trypsin on homoarginine-modified proteins. We observed that the rate of hydrolysis of homoarginine residues compared to their lysine/arginine counterparts were slower but generally cleaved after an overnight digestion period depending on the protein to protease concentration ratios. Selectivity of the solid-phase N-terminal reagent was studied by enrichment of original N-terminal peptides from two standard proteins, ubiquitin and RNaseS.

CONCLUSIONS

We found enzyme trypsin is active in the guanidinated form of the protein depending on the enzyme to protein concentrations, time and the proximity of arginine residues in the sequence. The novel solid-phase capture reagent also successfully enriched N-terminal peptides from the standard protein mixtures. We believe this trypsin proteolysis study on homoarginine-modified proteins and our simple and versatile solid-phase capture strategy could be very useful for enrichment and sequence determination of proteins N-termini by MS.

p53-mediated activation of the mitochondrial protease HtrA2/Omi prevents cell invasion

Oncogenic Ras induces cell transformation and promotes an invasive phenotype. The tumor suppressor p53 has a suppressive role in Ras-driven invasion. However, its mechanism remains poorly understood. Here we show that p53 induces activation of the mitochondrial protease high-temperature requirement A2 (HtrA2; also known as Omi) and prevents Ras-driven invasion by modulating the actin cytoskeleton. Oncogenic Ras increases accumulation of p53 in the cytoplasm, which promotes the translocation of p38 mitogen-activated protein kinase (MAPK) into mitochondria and induces phosphorylation of HtrA2/Omi. Concurrently, oncogenic Ras also induces mitochondrial fragmentation, irrespective of p53 expression, causing the release of HtrA2/Omi from mitochondria into the cytosol. Phosphorylated HtrA2/Omi therefore cleaves β-actin and decreases the amount of filamentous actin (F-actin) in the cytosol. This ultimately down-regulates p130 Crk-associated substrate (p130Cas)-mediated lamellipodia formation, countering the invasive phenotype initiated by oncogenic Ras. Our novel findings provide insights into the mechanism by which p53 prevents the malignant progression of transformed cells.

Cascleave 2.0, a new approach for predicting caspase and granzyme cleavage targets

MOTIVATION

Caspases and granzyme B (GrB) are important proteases involved in fundamental cellular processes and play essential roles in programmed cell death, necrosis and inflammation. Although a number of substrates for both types have been experimentally identified, the complete repertoire of caspases and granzyme B substrates remained to be fully characterized. Accordingly, systematic bioinformatics studies of known cleavage sites may provide important insights into their substrate specificity and facilitate the discovery of novel substrates.

RESULTS

We develop a new bioinformatics tool, termed Cascleave 2.0, which builds on previous success of the Cascleave tool for predicting generic caspase cleavage sites. It can be efficiently used to predict potential caspase-specific cleavage sites for the human caspase-1, 3, 6, 7, 8 and GrB. In particular, we integrate heterogeneous sequence and protein functional information from various sources to improve the prediction accuracy of Cascleave 2.0. During classification, we use both maximum relevance minimum redundancy and forward feature selection techniques to quantify the relative contribution of each feature to prediction and thus remove redundant as well as irrelevant features. A systematic evaluation of Cascleave 2.0 using the benchmark data and comparison with other state-of-the-art tools using independent test data indicate that Cascleave 2.0 outperforms other tools on protease-specific cleavage site prediction of caspase-1, 3, 6, 7 and GrB. Cascleave 2.0 is anticipated to be used as a powerful tool for identifying novel substrates and cleavage sites of caspases and GrB and help understand the functional roles of these important proteases in human proteolytic cascades.

AVAILABILITY AND IMPLEMENTATION

http://www.structbioinfor.org/cascleave2/.

Caspase substrates and inhibitors

Caspases are proteases at the heart of networks that govern apoptosis and inflammation. The past decade has seen huge leaps in understanding the biology and chemistry of the caspases, largely through the development of synthetic substrates and inhibitors. Such agents are used to define the role of caspases in transmitting life and death signals, in imaging caspases in situ and in vivo, and in deconvoluting the networks that govern cell behavior. Additionally, focused proteomics methods have begun to reveal the natural substrates of caspases in the thousands. Together, these chemical and proteomics technologies are setting the scene for designing and implementing control of caspase activity as appropriate targets for disease therapy.

Glycocapture-based proteomics for secretome analysis

Protein glycosylation represents the most abundant extracellular posttranslational modification in multicellular organisms. These glycoproteins unequivocally comprise the major biomolecules involved in extracellular processes, such as growth factors, signaling proteins for cellular communication, enzymes, and proteases for on- and off-site processing. It is now known that altered protein glycosylation is a hallmark event in many different pathologies. Glycoproteins are found mostly in the so-called secretome, which comprises classically and nonclassically secreted proteins and protein fragments that are released from the cell surface through ectodomain shedding. Due to biological complexity and technical difficulty, comparably few studies have taken an in-depth investigation of cellular secretomes using system-wide approaches. The cellular secretomes are considered to be a valuable source of therapeutic targets and novel biomarkers. It is not surprising that many existing biomarkers, including biomarkers for breast, ovarian, prostate, and colorectal cancers are glycoproteins. Focused analysis of secreted glycoproteins could thus provide valuable information for early disease diagnosis, and surveillance. Furthermore, since most secreted proteins are glycosylated and glycosylation predominantly targets secreted proteins, the glycan/sugar moiety itself can be used as a chemical "handle" for the targeted analysis of cellular secretomes, thereby reducing sample complexity and allowing detection of low abundance proteins in proteomic workflows. This review will focus on various glycoprotein enrichment strategies that facilitate proteomics-based technologies for the quantitative analysis of cell secretomes and cell surface proteomes.

PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites

The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s). Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database) with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate sequence using machine learning techniques. It is freely available at http://lightning.med.monash.edu.au/PROSPER/.

Qualitative improvement and quantitative assessment of N-terminomics

Proteolysis represents one of the most tightly controlled physiological processes, as proteases create events that will typically commit pathways in an irreversible manner. Despite their implication in nearly all biological systems, our understanding of the role of proteases in disease pathology is often limited. Several approaches to studying proteolytic activity as it relates to biology, pathophysiology, and drug therapy have been published, including the recently described terminal amine isotopic labeling of substrates (TAILS) strategy by Kleifeld and colleagues. Here, we investigate TAILS as a methodology based on targeted enrichment and mass spectrometric detection of endogenous N-terminal peptides from clinically relevant biological samples and its potential to provide quantitative information on proteolysis and elucidation of the protease cleavage sites. While optimizing the most current protocol, by switching to a streamlined one-tube format and simplifying the reagents' removal steps, we demonstrate the advantages over previously published methods and provide solutions to some of the technical challenges presented in the Kleifeld publication. We also identify some of the current and unresolved limitations. We use human plasma as a model system to provide data, which illustrates some of the key analytical parameters of the modified TAILS procedure, including specificity, sensitivity, quantitative precision, and accuracy.

Degradomics reveals that cleavage specificity profiles of caspase-2 and effector caspases are alike

Caspase-2 is considered an initiator caspase because its long prodomain contains a CARD domain that allows its recruitment and activation in several complexes by homotypic death domain-fold interactions. Because little is known about the function and specificity of caspase-2 and its physiological substrates, we compared the cleavage specificity profile of recombinant human caspase-2 with those of caspase-3 and -7 by analyzing cell lysates using N-terminal COmbined FRActional DIagonal Chromatography (COFRADIC). Substrate analysis of the 68 cleavage sites identified in 61 proteins revealed that the protease specificities of human caspases-2, -3, and -7 largely overlap, revealing the DEVD↓G consensus cleavage sequence. We confirmed that Asp(563) in eukaryotic translation initiation factor 4B (eIF4B) is a cleavage site preferred by caspase-2 not only in COFRADIC setup but also upon co-expression in HEK 293T cells. These results demonstrate that activated human caspase-2 shares remarkably overlapping protease specificity with the prototype apoptotic executioner caspases-3 and -7, suggesting that caspase-2 could function as a proapoptotic caspase once released from the activating complex.

N- and C-terminal degradomics: new approaches to reveal biological roles for plant proteases from substrate identification

Proteolysis is an irreversible post-translational modification that regulates many intra- and intercellular processes, including essential go/no-go decisions during cell proliferation, development and cell death. Hundreds of protease-coding genes have been identified in plants, but few have been linked to specific substrates. Conversely, proteolytic processes are frequently observed in plant biology but rarely have they been ascribed to specific proteases. In mammalian systems, unbiased system-wide proteomics analyses of protease activities have recently been tremendously successful in the identification of protease substrate repertoires, also known as substrate degradomes. Knowledge of the substrate degradome is key to understand the role of proteases in vivo. Quantitative shotgun proteomic studies have been successful in identifying protease substrates, but while simple to perform they are biased toward abundant proteins and do not reveal precise cleavage sites. Current degradomics techniques overcome these limitations by focusing on the information-rich amino- and carboxy-terminal peptides of the original mature proteins and the protease-generated neo-termini. Targeted quantitative analysis of protein termini identifies precise cleavage sites in protease substrates with exquisite sensitivity and dynamic range in in vitro and in vivo systems. This review provides an overview of state-of-the-art methods for enrichment of protein terminal peptides, and their application to protease research. These emerging degradomics techniques promise to clarify the elusive biological roles of proteases and proteolysis in plants.

Protease signalling: the cutting edge

Protease research has undergone a major expansion in the last decade, largely due to the extremely rapid development of new technologies, such as quantitative proteomics and in-vivo imaging, as well as an extensive use of in-vivo models. These have led to identification of physiological substrates and resulted in a paradigm shift from the concept of proteases as protein-degrading enzymes to proteases as key signalling molecules. However, we are still at the beginning of an understanding of protease signalling pathways. We have only identified a minor subset of true physiological substrates for a limited number of proteases, and their physiological regulation is still not well understood. Similarly, links with other signalling systems are not well established. Herein, we will highlight current challenges in protease research.

Profiling protease activities by dynamic proteomics workflows

Proteases play prominent roles in many physiological processes and the pathogenesis of various diseases, which makes them interesting drug targets. To fully understand the functional role of proteases in these processes, it is necessary to characterize the target specificity of the enzymes, identify endogenous substrates and cleavage products as well as protease activators and inhibitors. The complexity of these proteolytic networks presents a considerable analytic challenge. To comprehensively characterize these systems, quantitative methods that capture the spatial and temporal distributions of the network members are needed. Recently, activity-based workflows have come to the forefront to tackle the dynamic aspects of proteolytic processing networks in vitro, ex vivo and in vivo. In this review, we will discuss how mass spectrometry-based approaches can be used to gain new insights into protease biology by determining substrate specificities, profiling the activity-states of proteases, monitoring proteolysis in vivo, measuring reaction kinetics and defining in vitro and in vivo proteolytic events. In addition, examples of future aspects of protease research that go beyond mass spectrometry-based applications are given.

Mass spectrometry-based proteomics strategies for protease cleavage site identification

Protease-catalyzed hydrolysis of peptide bonds is one of the most pivotal post-translational modifications fulfilling manifold functions in the regulation of cellular processes. Therefore, dysregulation of proteolytic reactions plays a central role in many pathophysiological events. For this reason, understanding the molecular mechanisms in proteolytic reactions, in particular the knowledge of proteases involved in complex processes, expression levels and activity of protease and knowledge of the targeted substrates are an indispensable prerequisite for targeted drug development. The present review focuses on mass spectrometry-based proteomic methods for the analysis of protease cleavage sites, including the identification of the hydrolyzed bonds as well as of the surrounding sequence. Peptide- and protein-centric approaches and bioinformatic tools for experimental data interpretation will be presented and the major advantages and drawbacks of the different approaches will be addressed. The recent applications of these approaches for the analysis of biological function of different protease classes and potential future directions will be discussed.

New approaches for dissecting protease functions to improve probe development and drug discovery

Proteases are well-established targets for pharmaceutical development because of their known enzymatic mechanism and their regulatory roles in many pathologies. However, many potent clinical lead compounds have been unsuccessful either because of a lack of specificity or because of our limited understanding of the biological roles of the targeted protease. In order to successfully develop protease inhibitors as drugs, it is necessary to understand protease functions and to expand the platform of inhibitor development beyond active site-directed design and in vitro optimization. Several newly developed technologies will enhance assessment of drug selectivity in living cells and animal models, allowing researchers to focus on compounds with high specificity and minimal side effects in vivo. In this review, we highlight advances in the development of chemical probes, proteomic methods and screening tools that we feel will help facilitate this paradigm shift in drug discovery.

Caspase substrates and cellular remodeling

The caspases are unique proteases that mediate the major morphological changes of apoptosis and various other cellular remodeling processes. As we catalog and study the myriad proteins subject to cleavage by caspases, we are beginning to appreciate the full functional repertoire of these enzymes. Here, we examine current knowledge about caspase cleavages: what kinds of proteins are cut, in what contexts, and to what end. After reviewing basic caspase biology, we describe the technologies that enable high-throughput caspase substrate discovery and the datasets they have yielded. We discuss how caspases recognize their substrates and how cleavages are conserved among different metazoan organisms. Rather than comprehensively reviewing all known substrates, we use examples to highlight some functional impacts of caspase cuts during apoptosis and differentiation. Finally, we discuss the roles caspase substrates can play in medicine. Though great progress has been made in this field, many important areas still await exploration.

Identifying and quantifying proteolytic events and the natural N terminome by terminal amine isotopic labeling of substrates

Analysis of the sequence and nature of protein N termini has many applications. Defining the termini of proteins for proteome annotation in the Human Proteome Project is of increasing importance. Terminomics analysis of protease cleavage sites in degradomics for substrate discovery is a key new application. Here we describe the step-by-step procedures for performing terminal amine isotopic labeling of substrates (TAILS), a 2- to 3-d (depending on method of labeling) high-throughput method to identify and distinguish protease-generated neo-N termini from mature protein N termini with all natural modifications with high confidence. TAILS uses negative selection to enrich for all N-terminal peptides and uses primary amine labeling-based quantification as the discriminating factor. Labeling is versatile and suited to many applications, including biochemical and cell culture analyses in vitro; in vivo analyses using tissue samples from animal and human sources can also be readily performed. At the protein level, N-terminal and lysine amines are blocked by dimethylation (formaldehyde/sodium cyanoborohydride) and isotopically labeled by incorporating heavy and light dimethylation reagents or stable isotope labeling with amino acids in cell culture labels. Alternatively, easy multiplex sample analysis can be achieved using amine blocking and labeling with isobaric tags for relative and absolute quantification, also known as iTRAQ. After tryptic digestion, N-terminal peptide separation is achieved using a high-molecular-weight dendritic polyglycerol aldehyde polymer that binds internal tryptic and C-terminal peptides that now have N-terminal alpha amines. The unbound naturally blocked (acetylation, cyclization, methylation and so on) or labeled mature N-terminal and neo-N-terminal peptides are recovered by ultrafiltration and analyzed by tandem mass spectrometry (MS/MS). Hierarchical substrate winnowing discriminates substrates from the background proteolysis products and non-cleaved proteins by peptide isotope quantification and bioinformatics search criteria.

Selecting protein N-terminal peptides by combined fractional diagonal chromatography

In recent years, procedures for selecting the N-terminal peptides of proteins with analysis by mass spectrometry have been established to characterize protease-mediated cleavage and protein α-N-acetylation on a proteomic level. As a pioneering technology, N-terminal combined fractional diagonal chromatography (COFRADIC) has been used in numerous studies in which these protein modifications were investigated. Derivatization of primary amines--which can include stable isotope labeling--occurs before trypsin digestion so that cleavage occurs after arginine residues. Strong cation exchange (SCX) chromatography results in the removal of most of the internal peptides. Diagonal, reversed-phase peptide chromatography, in which the two runs are separated by reaction with 2,4,6-trinitrobenzenesulfonic acid, results in the removal of the C-terminal peptides and remaining internal peptides and the fractionation of the sample. We describe here the fully matured N-terminal COFRADIC protocol as it is currently routinely used, including the most substantial improvements (including treatment with glutamine cyclotransferase and pyroglutamyl aminopeptidase to remove pyroglutamate before SCX, and a sample pooling scheme to reduce the overall number of liquid chromatography-tandem mass spectrometry analyses) that were made since its original publication. Completion of the N-terminal COFRADIC procedure takes ~5 d.

Bioinformatic approaches for predicting substrates of proteases

Proteases have central roles in "life and death" processes due to their important ability to catalytically hydrolyze protein substrates, usually altering the function and/or activity of the target in the process. Knowledge of the substrate specificity of a protease should, in theory, dramatically improve the ability to predict target protein substrates. However, experimental identification and characterization of protease substrates is often difficult and time-consuming. Thus solving the "substrate identification" problem is fundamental to both understanding protease biology and the development of therapeutics that target specific protease-regulated pathways. In this context, bioinformatic prediction of protease substrates may provide useful and experimentally testable information about novel potential cleavage sites in candidate substrates. In this article, we provide an overview of recent advances in developing bioinformatic approaches for predicting protease substrate cleavage sites and identifying novel putative substrates. We discuss the advantages and drawbacks of the current methods and detail how more accurate models can be built by deriving multiple sequence and structural features of substrates. We also provide some suggestions about how future studies might further improve the accuracy of protease substrate specificity prediction.

Mass spectrometry-driven proteomics: an introduction

Proteins are reckoned to be the key actors in a living organism. By studying proteins, one engages into deciphering a complex series of events occurring during a protein's life span. This starts at the creation of a protein, which is tightly controlled on both a transcriptional (Williams and Tyler, 2007, Curr Opin Genet Dev 17, 88-93) and a translational level (Van Der Kelen et al., 2009, Crit Rev Biochem Mol Biol 44, 143-168). During translation, a primary strand of amino acids undergoes a complex folding process in order to obtain a native three-dimensional protein structure (Gross et al., 2003, Cell 115, 739-750). Proteins take on a plethora of functions, such as complex formation, receptor activity, and signal transduction, which ultimately adds up to a cellular phenotype. Consequently, protein analysis is of major interest in molecular biology and involves annotating their presence and localization, as well as their modification state and biochemical context. To accomplish this, many methods have been developed over the last decades, and their general principles and important recent advances in large-scale protein analysis or proteomics are discussed in this review.

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.

Probing the efficiency of proteolytic events by positional proteomics

Several mass spectrometry-driven techniques allow to map the substrate repertoires and specificities of proteases. These techniques typically yield long lists of protease substrates and processed sites with (potential) physiological relevance, but in order to understand the primary function of a protease, it is important to discern bystander substrates from critical substrates. Because the former are generally processed with lower efficiency, data on the actual substrate cleavage efficiency could assist in categorizing protease substrates. In this study, quantitative mass spectrometry following metabolic proteome labeling (SILAC), combined with the isolation of N-terminal peptides by Combined Fractional Diagonal Chromatography, was used to monitor fluxes in the concentration of protease-generated neo-N-termini. In our experimental setup, a Jurkat cell lysate was treated with the human serine protease granzyme B (hGrB) for three different incubation periods. The extensive list of human granzyme B substrates previously catalogued by N-terminal Combined Fractional Diagonal Chromatography (1) was then used to assign 101 unique hGrB-specific neo-N-termini in 86 proteins. In this way, we were able to define several sites as getting efficiently cleaved in vitro and consequently recognize potential physiologically more relevant substrates. Among them the well-known hGrB substrate Bid was confirmed as being an efficient hGrB substrate next to several other potential regulators of hGrB induced apoptosis such as Bnip2 and Akap-8. Several of our proteomics results were further confirmed by substrate immunoblotting and by using peptide substrates incubated with human granzyme B.

Who gets cut during cell death?

The recent introduction of positional proteomics made it possible to screen for protease processing events on a proteome-wide scale. As a highly regulated and protease-dependent process, cell death has been particularly well-studied with these emerging technologies. This review provides an overview of the results obtained at the exciting interface between proteomics, protease biology and cell death.

MS-driven protease substrate degradomics

Proteolytic processing has recently received increased attention in the field of signal propagation and cellular differentiation. Because of its irreversible nature, protein cleavage has been associated with committed steps in cell function. One aspect of protease biology that boomed the past few years is the detailed characterization of protease substrates by both shotgun as well as targeted MS-driven proteomics techniques. The most promising techniques are discussed in this review and we further elaborate on the bioinformatics challenges that accompany mainly qualitative, MS-driven protease substrate degradome studies.

Proteomic techniques and activity-based probes for the system-wide study of proteolysis

Proteolysis constitutes a major post-translational modification but specificity and substrate selectivity of numerous proteases have remained elusive. In this review, we highlight how advanced techniques in the areas of proteomics and activity-based probes can be used to investigate i) protease active site specificity; ii) protease in vivo substrates; iii) protease contribution to proteome homeostasis and composition; and iv) detection and localization of active proteases. Peptide libraries together with genetical or biochemical selection have traditionally been used for active site profiling of proteases. These are now complemented by proteome-derived peptide libraries that simultaneously determine prime and non-prime specificity and characterize subsite cooperativity. Cell-contextual discovery of protease substrates is rendered possible by techniques that isolate and quantitate protein termini. Here, a novel approach termed Terminal Amine Isotopic Labeling of Substrates (TAILS) provides an integrated platform for substrate discovery and appropriate statistical evaluation of terminal peptide identification and quantification. Proteolytically generated carboxy-termini can now also be analyzed on a proteome-wide level. Proteolytic regulation of proteome composition is monitored by quantitative proteomic approaches employing stable isotope coding or label free quantification. Activity-based probes specifically recognize active proteases. In proteomic screens, they can be used to detect and quantitate proteolytic activity while their application in cellular histology allows to locate proteolytic activity in situ. Activity-based probes - especially in conjunction with positron emission tomography - are also promising tools to monitor proteolytic activities on an organism-wide basis with a focus on in vivo tumor imaging. Together, this array of methodological possibilities enables unveiling physiological protease substrate repertoires and defining protease function in the cellular- and organism-wide context.

A statistics-based platform for quantitative N-terminome analysis and identification of protease cleavage products

Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed.

Isotopic labeling of terminal amines in complex samples identifies protein N-termini and protease cleavage products

Effective proteome-wide strategies that distinguish the N-termini of proteins from the N-termini of their protease cleavage products would accelerate identification of the substrates of proteases with broad or unknown specificity. Our approach, named terminal amine isotopic labeling of substrates (TAILS), addresses this challenge by using dendritic polyglycerol aldehyde polymers that remove tryptic and C-terminal peptides. We analyze unbound naturally acetylated, cyclized or labeled N-termini from proteins and their protease cleavage products by tandem mass spectrometry, and use peptide isotope quantification to discriminate between the substrates of the protease of interest and the products of background proteolysis. We identify 731 acetylated and 132 cyclized N-termini, and 288 matrix metalloproteinase (MMP)-2 cleavage sites in mouse fibroblast secretomes. We further demonstrate the potential of our strategy to link proteases with defined biological pathways in complex samples by analyzing mouse inflammatory bronchoalveolar fluid and showing that expression of the poorly defined breast cancer protease MMP-11 in MCF-7 human breast cancer cells cleaves both endoplasmin and the immunomodulator and apoptosis inducer galectin-1.

Cascleave: towards more accurate prediction of caspase substrate cleavage sites

MOTIVATION

The caspase family of cysteine proteases play essential roles in key biological processes such as programmed cell death, differentiation, proliferation, necrosis and inflammation. The complete repertoire of caspase substrates remains to be fully characterized. Accordingly, systematic computational screening studies of caspase substrate cleavage sites may provide insight into the substrate specificity of caspases and further facilitating the discovery of putative novel substrates.

RESULTS

In this article we develop an approach (termed Cascleave) to predict both classical (i.e. following a P(1) Asp) and non-typical caspase cleavage sites. When using local sequence-derived profiles, Cascleave successfully predicted 82.2% of the known substrate cleavage sites, with a Matthews correlation coefficient (MCC) of 0.667. We found that prediction performance could be further improved by incorporating information such as predicted solvent accessibility and whether a cleavage sequence lies in a region that is most likely natively unstructured. Novel bi-profile Bayesian signatures were found to significantly improve the prediction performance and yielded the best performance with an overall accuracy of 87.6% and a MCC of 0.747, which is higher accuracy than published methods that essentially rely on amino acid sequence alone. It is anticipated that Cascleave will be a powerful tool for predicting novel substrate cleavage sites of caspases and shedding new insights on the unknown caspase-substrate interactivity relationship.

AVAILABILITY

http://sunflower.kuicr.kyoto-u.ac.jp/ approximately sjn/Cascleave/

CONTACT

jiangning.song@med.monash.edu.au; takutsu@kuicr.kyoto-u.ac.jp; james; whisstock@med.monash.edu.au

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Overview of quantitative LC-MS techniques for proteomics and activitomics

LC-MS is a useful technique for protein and peptide quantification. In addition, as a powerful tool for systems biology research, LC-MS can also be used to quantify post-translational modifications and metabolites that reflect biochemical pathway activity. This review discusses the different analytical techniques that use LC-MS for the quantification of proteins, their modifications and activities in a multiplex manner.

Caspase substrates: easily caught in deep waters?

Caspases are key players in various cellular processes, such as apoptosis, proliferation and differentiation, and in pathological conditions including cancer and inflammation. Although caspases preferentially cleave C-terminal of aspartic acid residues, their action is restricted generally to one or a few sites per protein substrate. Caspase-specific substrate recognition appears to be determined by the substrate sequences adjacent to the scissile bond. Knowledge of these substrates and the generated fragments is crucial for a thorough understanding of the functional implications of caspase-mediated proteolysis. In addition, insight into the cleavage specificity might assist in designing inhibitors that target disease-related caspase activities. Here, we critically review recently published procedures used to generate a proteome-wide view of caspase substrates.

Recent advances in mass spectrometry-based peptidome analysis

The peptidome, which is the low-molecular-weight subset of the proteome, has attracted increasing attention in recent years. However, with the interference of high-abundance protein components in complex biological mixtures (e.g., serum), selective extraction of endogenous peptides is the first and most important step before analyzing the peptidome. A number of methods and technologies have now been developed for the selective enrichment, fractionation, quantitative analysis of the endogenous peptides and their application in the potential biomarker discovery. This review will cover the methods and technologies developed in recent years for the peptidome analysis on the selective extraction, multidimensional separation and quantitative analysis, as well as their application for clinical diagnosis and biomarker discovery. The future prospects of the peptidome are also discussed.