Current trends and challenges in proteomic

Biochimie 122 (2016) 77e87

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Review

Current trends and challenges in proteomic identification of protease substrates Matej Vizovisek a, 1, Robert Vidmar a, c, 1, Marko Fonovi c a, b, *, Boris Turk a, b, d, ** Department of Biochemistry and Molecular and Structural Biology, Jozef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins, Jamova cesta 39, SI-1000 Ljubljana, Slovenia c International Postgraduate School Jozef Stefan, Jamova cesta 39, SI-1000 Ljubljana, Slovenia d Faculty of Chemistry and Chemical Technology, University of Ljubljana, Askerceva cesta 5, SI-1000 Ljubljana, Slovenia a

b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 23 July 2015 Accepted 23 October 2015 Available online 26 October 2015

Proteolytic cleavage is a ubiquitous, irreversible, posttranslational modification that changes protein structure and function and plays an important role in numerous physiological and pathological processes. Over the last decade, proteases have become increasingly important clinical targets because many of their inhibitors are already used in the clinic or in various stages of clinical testing. Therefore, a better understanding of protease action and their repertoires of physiological substrates can not only provide an important insight into their mechanisms of action but also open a path toward novel drug design. Historically, proteases and their substrates were mainly studied on a case-by-case basis, but recent advancements in mass spectrometry-based proteomics have enabled proteolysis studies on a global scale. Because there are many different types of proteases that can operate in various cellular contexts, multiple experimental approaches for their degradomic characterization had to be developed. The present paper reviews the mass spectrometry-based approaches for determining the proteolytic events in complex biological samples. The methodologies for substrate identification and the determination of protease specificity are discussed, with a special focus on terminomic strategies, which combine peptide labeling and enrichment. te Française de Biochimie et Biologie Mole culaire (SFBBM). All rights © 2015 Elsevier B.V. and Socie reserved.

Keywords: Proteomics Proteases Degradomics Substrates Terminomics

Contents 1. 2. 3.

4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Proteomic identification of protease substrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79 Proteomic determination of cleavage sites and characterization of protease specificities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 3.1. N-terminomic strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 3.2. C-terminomic strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 Perspectives and future challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Conflict of interests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85

1. Introduction * Corresponding author. Department of Biochemistry and Molecular and Structural Biology, Jo zef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia. ** Corresponding author. Department of Biochemistry and Molecular and Structural Biology, Jo zef Stefan Institute, Jamova cesta 39, SI-1000 Ljubljana, Slovenia. E-mail addresses: [email protected] (M. Fonovi c), [email protected] (B. Turk). 1 Both authors contributed equally to this manuscript.

The human genome encodes approximately 600 proteases that have important roles in vital physiological and pathological processes, such as proliferation, the immune response, physiological homeostasis, cell death, inflammation, cancer, cardiovascular and

http://dx.doi.org/10.1016/j.biochi.2015.10.017 te Française de Biochimie et Biologie Mole culaire (SFBBM). All rights reserved. 0300-9084/© 2015 Elsevier B.V. and Socie

M. Vizovisek et al. / Biochimie 122 (2016) 77e87

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Abbreviations 2D-PAGE two-dimensional polyacrylamide electrophoresis 2D-DIGE two-dimensional difference gel electrophoresis CLiPS cellular libraries of peptide substrates ChaFRADIC charge-based fractional diagonal chromatography COFRADIC combined fractional diagonal chromatography (d)N-TOP (double) TMMP labeling approach FPPS fast profiling of protease specificity ICAT isotope-coded affinity tags iTRAQ Isobaric tags for relative and absolute quantitation LC-MS/MS liquid chromatography coupled with tandem mass spectrometry MMP matrix metalloprotease N-CLAP N-terminalomics by Chemical Labeling of the a-Amine of Proteins NHS N-Hydroxysuccinimide PICS Proteomic Identification of Protease Cleavage Sites

PITC phenyl isothiocyanate PROTOMAP protein topography and migration analysis platform PS-SCL positional scanning-substrate combinatorial assays PTAG phospho tagging PTM posttranslational modification SAX strong anion exchanger SCX strong cation exchanger SDS-PAGE sodium dodecyl sulphate polyacrylamide electrophoresis SILAC stable isotope labeling by amino acid in cell culture SPECS secretome protein enrichment using click sugars TAILS terminal amine isotopic labeling of substrates TMMP trimethoxphenylphopshonium TMMP-Ac-OSu (N-succinimidyloxycarbonylmethyl) tris (2,4,6trimethoxyphenyl) TopFIND Terminus Oriented Protein Function Inferred database TOPPR the online protein processing resource TRAIL TNF-related apoptosis-inducing ligand

Fig. 1. Nomenclature of protease-substrate interaction. The substrate binding sites downstream of the cleavage site are numbered S1eSn towards the N-terminus of the substrate (non-primed sites) and S10 eSn0 towards the C-terminus (primed sites). The substrate residues are numbered P1ePn, and P10 ePn0 [5]. In either case, the numbering starts at the scissile bond.

neurodegenerative diseases, and infections [1,2]. Based on their catalytic mechanism, proteases are classified into serine, cysteine, metallo, aspartic, threonine and glutamyl proteases, and proteases of an unknown catalytic mechanism (MEROPS database, reviewed in Refs. [3,4]). Proteases can be further divided into endopeptidases, which cleave proteins inside the polypeptide chain, and exopeptidases, which cleave at the N- or C-terminus (aminopeptidases or carboxypeptidases). Accordingly, the cleavage results in the formation of two novel protein fragments or, in the case of exopeptidase, N- or C-terminally trimmed proteins. Thus proteolytic processing is an irreversible posttranslational modification (PTM) that changes the structure and function of their protein substrates. Protease-substrate interactions play a major role in the specificity of the proteolytic cleavage [1]. Schechter-Berger nomenclature (Fig. 1) is used to annotate the positions upstream or downstream of the cleavage site, with the substrate binding subsites on the surface of the protease numbered S1eSn towards the N-terminus of the substrate (the so called non-primed sites) and S10 eSn0 towards the C-terminus of the substrate (the so called primed sites), whereas the substrate residues they bind are numbered P1ePn, and P10 ePn0 , respectively. In both cases, the numbering begins at the scissile bond [5]. Proteases with narrow specificity generally execute limited proteolysis (e.g., caspases during apoptosis), while proteases with broad specificity, such as cysteine cathepsins or the proteasome, often have major roles in general protein degradation and

clearance, thereby governing the proteome composition of a cell [1]. In addition, the efficiency of the cleavage in vivo is determined by several other factors. First, the protease and the target substrate must be present in sufficient concentrations and must interact in the cellular environment under the favourable conditions required for protease activity (e.g., pH and redox state). Second, the presence of posttranslational modifications, endogenous inhibitors, allosteric effectors and other proteases can also significantly impact substrate processing in vivo [1,6e10]. Moreover, because even a small quantity of an active protease can trigger a physiological response, their in vivo activity is tightly regulated on several levels, including transcription (different expression levels of a protease), activation (synthesis as inactive zymogens), inhibition by endogenous inhibitors, compartmentalization [11]) and protease half-life [1,2,12]. It is crucial to identify a protease's physiological substrates to understand its action and position inside the proteolytic web [13]. However, although a substantial amount of data on proteases has been gathered over the past decade, we have still only identified a very limited subset of true physiological substrates. During the last 15 years, mass spectrometry has become an indispensable tool for identifying protease substrates in complex biological samples but also for determining protease specificities. However, a single experimental design is generally not sufficient for the study of complex proteolytic pathways, and various methodological approaches for proteomic studies of proteases had to be developed.


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Table 1 Degradomic methodologies and some examples of their applications. Method

Reported examples of tested proteases

Enrichment strategy

Labeling

Identification of cleavage sites

Selected references

2D-PAGE

No enrichment

Label-free

NO

[14,17e19]

2D-DIGE

MMP-14, Pim1, CED-3, serine protease 1 Granzyme B

No enrichment

Chemical labeling with NHS-reactive fluorescent labels

NO

[15]

CLiPS

Caspase 3; enterokinase

No enrichment

a

[37]

PS-SCL

Caspases, granzyme B

No enrichment

a

PICS

MMP-2; caspase 3, 7; cathepsin B, G, K, L, S; elastase; thrombin; HIV protease 1; collagenases; serine proteases; Cathepsin G; neutrophil elastase; proteinase 3

Positive selection of N-termini; selected via biotinylation

Chemical labelling of the neo N-termini with NHS-biotin

NO (the cleavage site is known before the assay) NO (the cleavage site is known before the assay) YES

[69e72]

Label-free

YES

[45,46]

Chemical labeling of the neo N-termini with NHS-D3-acetate Chemical with NHS-D3-acetate and later TNBS (þmetabolic labeling using isotopically labeled lysine and arginine) Chemical biotinylation

YES

[81]

YES

[58,59,61,64,102,103]

YES

[55,68,104]

Chemical biotinylation

YES

[74,105]

Chemical dimethylation

YES

[106,107]

Chemical labeling with isobaric NHS-reactive esters

YES

[76,77,108,109]

Label-free or metabolic (SILAC)

NO (only the appx. position of the cleavage site can be estimated) YES

[21e23,25,26]

[30]

YES

[79,80]

YES

[65e67]

YES

[75]

YES

[32,33]

MSP-MS

FPPS

Cathepsin K, L, S

A library of chemically diverse peptides is used to profile protease specificity No enrichment

COFRADIC (þSILAC)

Granzyme A, B, K; caspases; HtrA2/Omi; cathepsin D, E; MMPs

Negative selection of the internal peptides via TNBS labeling

Biotinylation

TAILS

Methionine aminopeptidase; caspase 3 Caspases, methionine aminopeptidase MMP-2, MMP-11

iTRAQ-TAILS

MMP-2, MMP-9, MMP-10

PROTOMAP

Caspases

Positive or negative selection of N-termini Positive selection of N-termini Negative enrichment (depletion of the internal peptides on aldehyde polymers) Negative enrichment (depletion of the internal peptides on aldehyde polymers) No enrichment

iTRAQ

MMP-2

No enrichment

dN-TOP

N-terminome of Herminiimonas arsenicoxydans Icp55

No enrichment

N-CLAP

ChaFRADIC

PTAG

SPECS a

N-terminome of Neisseria meningitidis and Saccharomyces cerevisiae BACE1, SPPL3

Charge-based negative enrichment of the N-termini Negative enrichment of the protease-generated N-termini Positive enrichment

Chemical labeling with isobaric NHS-reactive esters Chemical labeling of the N-termini with TMMP Chemical labeling of the neo N-termini with NHS-D3-acetate Chemical phospho tagging

Chemical labeling using click sugars

[40e42]

The peptides contain an appropriate fluorescent reporter to detect protease processing; the cleavage site is previously known.

Unfortunately, despite these numerous advancements, it is still a major challenge to ascribe a cleavage event to a single protease at the organism-wide level. Moreover, even if a protein is identified as a true physiological substrate of a given protease, it still does not explain the biological relevance of the cleavage event, which requires further validation. This paper provides an overview of the proteomic approaches that were developed over the past decade to study proteolysis in vitro and in vivo (the approaches discussed in this paper are summarized in Table 1), ranging from chemical and isotopic labeling to label-free approaches. Specific cases that applied substrate and cleavage identification techniques are discussed, with an emphasis on the current limitations and emerging trends in the protease field.

2. Proteomic identification of protease substrates Because proteolytic cleavage irreversibly changes a protein's size and structure, gel-based methods, such as 2D-PAGE coupled to mass spectrometry, were the first methods of choice for detecting substrate cleavage events in cellular or tissue extracts. In this approach, proteins are separated in two dimensions according to their mass and charge. After staining the gel, the cleaved proteins are visualized by a positional shift or changes in intensity when the sample is compared to the untreated control. The proteins in these spots are then identified by mass spectrometry. This approach was first reported in 2004 when Hwang and co-workers treated the human plasma proteome with the metalloprotease MMP-14 and identified 16 cleaved proteins [14]. In this approach, two different gels must be

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compared and this can be problematic, due to the low reproducibility of 2D-PAGE. This problem can be alleviated by the introduction of two dimensional difference gel electrophoresis 2D-DIGE, which uses samples that are labelled with fluorescent dyes, enabling the comparison of two different samples on a single gel. This methodology was first applied to the identification of granzyme B substrates [15]. However, a downside of both approaches remains the low resolving power for very large or very small proteins and the inability to separate membrane proteins as well as very acidic or basic proteins. 2D-PAGE also has a limited sensitivity, which affects the detection of low abundance proteins [16]. Despite its numerous shortcomings, 2D-PAGE coupled to mass spectrometry enabled the identification of numerous protease substrates, including those of the serine protease-1 from Bacillus subtilis, the mitochondrial matrix protease Pim1 and of the cysteine proteases CED-3 and cathepsin X [17e20]. In 2008, a novel approach, based on the detection of shifts in the 1D gel migration of proteins, was introduced. This approach was termed PROTOMAP (Protein Topography and Migration Analysis Platform) and, although it is conceptually similar to 2D-DIGE, it resolves many of its shortcomings [21]. In a PROTOMAP experiment, the control and treated sample are separated by 1D-PAGE and both gel lanes are excised and cut into evenly spaced bands. The bands are then digested with trypsin and identified by mass spectrometry. Using a special algorithm, the SDS-PAGE and LC-MS/ MS data are finally integrated into a “peptograph”, from which a shift in the protein's gel position following protease cleavage and the change in protein abundance can be evaluated. This methodology was successfully applied to global studies of proteolytic events during physiological processes, such as apoptosis, metastasis and erythrocyte rupture during malaria infection [21e23]. Although it is not the best-suited technique for cleavage site analysis, PROTOMAP can determine the approximate location of protease cleavage sites by correlating the identified peptides with their position in the gel lane. The relative changes in the protein abundance in the gel bands were initially performed by non-labelled quantification (spectral counting), where MS/MS spectral counts between samples were compared [24]. This was further improved by combining PROTOMAP with SILAC, which was used for the study of proteolytic events during TRAIL-induced apoptosis and for studying the crosstalk between proteolysis and phosphorylation in apoptotic cells [25,26]. SILAC or metabolic labeling was first introduced in 2002 and is based on cell cultures that grow in the presence of isotopically labelled essential amino acids in growth medium (Lys and Arg e light or heavy versions) [27]. During cell proliferation, the light or heavy isotopes of these amino acids are incorporated into the proteins as they are synthesized. The treated and control samples are then combined and the peptides that are generated by proteolytic processing appear in the MS spectra as singlets or as doublets with a significantly changed H/L ratio, whereas the background peptides usually appear as doublets with an H/L ratio of approx. 1. Therefore, the introduction of SILAC into PROTOMAP removed the need for parallel processing of samples, which improved the reproducibility of the experiment and reduced the labour time. In contrast to spectral counting, which can only reliably detect large differences (at least two-fold) [28], SILAC is able to detect small differences in protein abundance. In some experimental conditions, including studies of protease sheddase activity (proteolytic release of membrane protein ectodomains), “gel-shift” based methods such as 2D-PAGE and PROTOMAP are not required because the cleaved proteins are selectively released from the cell surface. Therefore, membrane protein substrates are identified according to their presence in the cell supernatant. This approach was used to identify the membrane-anchored substrates of metalloproteinases and cysteine cathepsins [29e31]. The shed

membrane proteins can also be enriched by affinity chromatography, as was recently utilized in a click chemistry-based approach called SPECS (secretome protein enrichment using click sugars). In the SPECS protocol, the oligosaccharides present on the membraneanchored and secreted proteins are metabolically labelled with an azide group, which is then further modified by click-chemistrybased biotinylation, enabling the enrichment of the secreted proteins and shed substrates from cell culture medium. This approach was successfully used to identify the BACE1 and SPPL3 substrates [32,33]. 3. Proteomic determination of cleavage sites and characterization of protease specificities In addition to understanding of how proteolytic cleavage could affect the substrate's function, pinpointing the exact cleavage site can also provide important information about the protease specificity. In the early days, when proteases were primarily isolated and purified from tissues, their specificity was commonly studied using known peptides, such as oxidised insulin beta chain, thus providing some basic information about their specificities [34e36]. This was followed by the small-scale synthesis of small synthetic substrates, which was further advanced with the help of combinatorial chemistry that was used to develop synthetic substrates and small peptide inhibitors to study proteases [1]. A further advance was made by approaches such as cellular libraries of peptide substrates (CLiPS) [37], phage display peptidic libraries [38], combinatorial fluorescent substrate libraries [39] and positional scanningsubstrate combinatorial libraries (PS-SCL) [40e42]. The latter approach was recently complemented by the addition of unnatural amino acids, which has been successfully applied to substantially improve the specificity of the substrates of several proteases [43,44]. Another approach reported by O0 Donoghue et al. is based on a multiplex substrate profiling method using a physicochemically diverse library of peptides [45,46]. The method, which is basically a direct cleavage assay that detects cleavage products in a mixture of synthetic peptides, was successfully applied to study the specificity of several exopeptidases and endopeptidases using LCMS/MS analysis [45,46]. However, while these approaches are ideal for developing highly sensitive protease activity assays and even activity-based probes for cellular and in vivo imaging, they are less useful for the identification of extended substrate specificities and particularly for the identification of physiological protein substrates. The major reason is that the small synthetic substrates exhibit different binding in the protease active site than the long protein substrates [1]. In contrast, the proteomic methods for the identification of proteolytic cleavage sites rely on the identification of proteolytically generated neo N- and C-termini. Accordingly, terminomics is aimed at identifying the highest possible number of proteolytic events generated by an active protease in the sample, which are used for cleavage site identification [47e49]. In this experiment, a typical proteome is usually composed of peptides generated by the protease being evaluated and the peptides generated by trypsin in the next stage of the sample preparation procedure. However, the tryptic peptides can easily comprise well over 90% of all peptides in the sample, indicating that only a minority of the peptides in the sample are truly of interest. Therefore, one of the main challenges in their proteomic identification is to increase the relative content of those peptides and reduce the content of the internal tryptic peptides [50e52] (Fig. 2). To achieve this, the neo protein termini exposed after the proteolytic cleavages are chemically labelled prior to tryptic digestion. In the next step, the labelled peptides are enriched and identified by mass spectrometry. Based on the chemical modification site in


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Fig. 2. Generation of peptide termini. Proteolytic cleavage creates a neo N-terminus and a neo C-terminus that account only for a minor portion of the proteomic sample. Because the majority of the sample is internal peptides, different strategies must be employed to increase the success rate in identifying the peptides with neo N- or C-termini.

the peptide, these approaches are classified as N-terminomic and C-terminomic (this division scheme is also used in the following sections to discuss the different terminomic strategies). On the other hand, depending on the selection strategies employed for peptide enrichment, the methods can also be divided into positive selection strategies (enrichment of the terminal peptides cleaved by the tested protease) and negative selection strategies (removal of the tryptic peptides) [47].

3.1. N-terminomic strategies Among the first methods developed for labeling and selecting the peptide N-termini were chemical acetylation or biotinylation of the peptide samples [53e57]. Of these, COmbined FRactional DIagonal Chromatography (COFRADIC) was the first positional proteomics approach that enabled the global analysis of protease cleavage sites [57]. The use of deuteroacetylation reagents [50,56,57] has opened new possibilities, including distinguishing natural from chemical acetylation. Moreover, use of specific chemical labels (Fig. 3), such as NHS-based deuteroacetylation, can reduce the sample complexity because trypsin, a serine protease commonly used in downstream proteomic applications, cannot cleave after acetylated lysines, thereby reducing the complexity of

the bioinformatic space needed for sample interpretation [56,57]. The method itself is based on separating the chemically diversified peptide groups that were labelled using different strategies to introduce chromatographic shifts that enable the separation and enrichment of peptides with labelled neo N-termini [48] using sequential ion-exchange and reverse-phase chromatography cycles [50,56,57] (Fig. 3). In its first round, the method employs chemical acetylation using the D3-acetyl-NHS reagent, thus labeling all free amino groups in the sample. After trypsinisation, the free N-termini of the internal peptides are labelled with TNBS, which increases the hydrophobicity of the tryptic peptides. Hydrophobic labeling introduces a major chromatographic shift between the proteasegenerated neo N-terminal peptides and the internal tryptic peptides, enabling efficient negative enrichment of the N-terminal peptides [48,50,56,57]. To achieve relative quantification of the labelled neo N-termini, COFRADIC was also combined with stable isotopic labeling, such as trypsin-catalysed C-terminal 18O exchange and SILAC [58e60]. The efficiency of COFRADIC was further improved by introducing additional steps, such as SCX fractionation and the removal of pyroglutamyl residues, which minimized the presence of background tryptic peptides [51]. COFRADIC was successfully used for physiological studies of proteolysis during Fasand taxol-induced cell death [58,60]. In addition to identifying the

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Fig. 3. N-terminomic strategies for peptide selection. There are several N-terminomic strategies that can be employed to enrich the protease-generated neo N-termini. (a) Biotinylation and (b) enzymatic biotinylation are based on selective labeling of the free N-termini, thus enabling the efficient selection of the protease-generated peptides using streptavidin beads. (c) TAILS uses N-terminal labeling of the free amino groups prior to proteolytic digestion and the subsequent capture of the internal peptides on polymers, thereby negatively enriching for the labelled peptides. (d) COFRADIC employs D3-acetylation of the free amino groups before the first chromatography step and derivatization with TNBS before the second chromatography step for efficient negative selection of the protease-generated neo N-termini.

substrates, COFRADIC can also provide information about the substrate specificity of the tested protease, which can be elucidated by a global analysis of all cleaved protein regions in a complex proteome, such as a cell lysate. The substrate specificities of granzymes, caspase-3, apoptosis-related protease HtrA2/Omi, and cathepsins D and E were determined using this approach [61e64]. A few years ago, a method similar to COFRADIC termed ChaFRADIC was introduced [65]. In this approach, the free protein Ntermini and lysine residues are dimethylated prior to trypsin digestion. In the next step, the peptides are fractionated according

to their charge state by strong cation exchange chromatography (SCX). The obtained fractions are treated with NHS-trideutero acetate, which blocks the N-termini of the tryptic peptides, resulting in their earlier elution in the subsequent SCX fractionation step. Therefore, the second SCX fractionation effectively separates the dimethylated N-terminal peptides from the deuteroacetylated tryptic peptides, enabling their selective enrichment. ChaFRADIC was successfully applied to identify novel substrates of the mitochondrial peptidase Icp55 and to a proteolysis study in Arabidopsis thaliana [65e67].


Biotinylation is another N-terminal modification that can be used for the labeling and positive enrichment of the newly formed N-terminal peptides (Fig. 3). In this approach, the lysine side chains are blocked prior to biotinylation to limit biotinylation to the Nterminal amine groups. The N-termini are then labelled with a cleavable biotinylation reagent, such as NHS-SS-biotin, and enriched through binding and subsequent elution from immobilised streptavidin. This approach was used for the substrate profiling of methionine aminopeptidase, caspase 3 and staphylococcal glutamyl endopeptidase [55,68]. Another proteomic approach based on biotinylation is PICS (Proteomic Identification of Protease Cleavage Sites) [69,70]. In this approach, a peptide library is prepared from a whole cell lysate by treating it with a specific protease, such as trypsin or GluC, and the free amines are blocked by reductive methylation. Next, the library is treated with the protease of interest and the newly formed peptide N-termini are biotinylated, enriched and identified by mass spectrometry. The identity of the cleavage sites is then deduced from the amino acid sequence of the cleaved regions, similar to the other approaches. The drawback of PICS is that a number of putative cleavage sites are lost due to the proteolytic digestion required for the library preparation, which may lead to substantial bias if the tested protease has a similar specificity as the protease used to generate the peptide library (e.g., trypsin and cysteine cathepsins). Therefore, several specific proteases must be used to prepare the initial libraries to avoid this bias. Nevertheless, this approach is highly suitable for determining protease specificities and designing specific protease inhibitors and substrates. It was successfully applied to the specificity profiling of caspases, cathepsins, thrombin, elastase, serine proteases and various metalloproteases [69e72]. Biotinylation of N-terminal peptides can also be performed enzymatically (Fig. 3). In 2008, Mahrus and coworkers prepared a peptide ligase (subtiligase) that was used to selectively ligate the Nterminal amines to a biotinylated peptide ester containing a TEV protease cleavage site [73]. After trypsin digestion and positive selection on avidin resin, the labelled peptides are selectively eluted by the TEV protease. The authors used this method to study apoptosis and reported the identification of 333 caspase-like cleavage sites in 292 substrates. A somewhat different biotinylation-related approach termed N-CLAP (N-terminalomics by Chemical Labeling of the a-Amine of Proteins) was reported in 2009. In this approach, all free amines are first blocked by phenyl isothiocyanate (PITC), which is commonly used in Edman degradation. In the next step, the N-terminal amines are selectively unblocked by TFA so that they can be biotinylated for positive selection [74]. Recently, other approaches for selecting peptides that employ different strategies and chemistries were reported. Phosphopeptides were bound to TiO2 beads to enrich the protein N-termini using phospho tagging (PTAG) [75]. Accordingly, reductive dimethylation is used to label the N-terminal peptides prior to tryptic digestion, followed by modification of the free N-termini of the internal peptides with glyceraldehyde-3-phosphate. These newly derived phosphopeptides can then be efficiently captured using TiO2, thereby drastically reducing the content of the internal peptides in the sample. This approach was successfully applied to identify the unique N-terminal peptides in Neisseria meningitidis and in Saccharomyces cerevisiae [75]. In addition to acetylation, dimethylation, biotinylation and phospho tagging, the N-terminal peptides can be labelled also with isotopic mass tags such as iTRAQ, which uses NHS-reactive esters to label the terminal amines [30]. The combination of this approach with negative selection of tryptic peptides was used in TAILS (Terminal Amine Isotopic Labeling of Substrates), which was

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introduced in 2010. The major advantage of TAILS is the removal of the tryptic peptides by covalent binding to dendritic polyglycerol aldehyde polymers. Using this approach, several hundred matrix metalloproteinase cleavage sites were identified in complex biological samples [76,77]. The important benefit of iTRAQ is that it enables the simultaneous comparison of up to eight samples [78]. However, a disadvantage of TAILS is the nonselective binding of peptides with free lysines to the polymer. Other approaches, such as the trimethyloxyphenyl phosphonium labeling (TMPP) used in the N-TOP approach and in the derived doublet oriented N-terminal proteomics (dN-TOP), were also developed to profile the N-terminome [79,80]. The N-TOP method is based on labeling the protein's N-terminus with TMPPAc-OSu and allows the identification of the N-terminal and internal peptides in a single experiment. The method was successfully applied to a large variety of samples and represents an interesting alternative to other well-established N-terminomic approaches [79,80]. Several N-terminomic approaches that utilise peptide enrichment using positive or negative selection were first introduced when mass spectrometers still had slower cycle times and lower detection limits. The rapid advancement in mass spectrometry in the last decade diminished the importance of peptide enrichment in proteomic profiling of protease specificity. This feature was used to develop FPPS (Fast Profiling of Protease Specificity), which combines N-terminal deuteroacetylation of the protease-treated proteome with peptide separation using stage tips containing a strong anion exchange resin (SAX) [81]. Using this approach, a reliable substrate specificity of cysteine cathepsins was determined, although the neo N-terminal peptides were not separated from the tryptic peptides. Thus, a direct comparison of FPPS with COFRADIC showed only minor differences in the determined cathepsin specificities. However, the reliability of FPPS for profiling highly specific proteases, which generate a substantially lower number of cleavage events than the cathepsins that are known for their broad specificity, is still unclear. 3.2. C-terminomic strategies The terminomic approaches have largely focused on the more reactive N-termini, which can be efficiently labelled using different strategies (see above). Nevertheless, it is also possible to label the Ctermini, although there are fewer strategies. One of these is labeling the neo C-termini with ethanolamine, which has potential applicability, as demonstrated by Schilling and co-workers [82,83]. In the first step, they employed reductive dimethylation to protect the primary amino groups, whereas in the second step, the C-terminal carboxy groups were protected by carbodiimide-mediated coupling of ethanolamine to the C-termini. Using a similar strategy, TAILS was also modified to enable C-terminal labeling using carbodiimide coupling reactions after the methylation procedure [82], see Fig. 4. Although originally reported as an N-terminomic method, COFRADIC was also later modified for the simultaneous enrichment of N- and C-terminal peptides. This modified method includes the derivatization of the primary amines on the C-terminal peptides with an N-hydroxysuccinimide ester of butyrate, which enables the segregation of the N- and C-terminal peptides (Fig. 4). The use of isotopic variants of butyrate also allows the simultaneous differential analysis of up to three different proteomes [84]. Using CTAILS, 131 GluC cleavage sites were identified in an E. coli lysate, while C-terminal COFRADIC was used to profile granzymes and human carboxypeptidases [83e87]. As a C-terminal strategy, H2O18 labeling is also available in several workflows that are focused on either protease-catalysed labeling of the proteolytic products or postdigestion labeling of the internal peptides [88,89]. However,

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Fig. 4. C-terminomic strategies for peptide selection. (a) While it is identical to N-terminal COFRADIC in the first step of derivatization and chromatographic separation, C-terminal COFRADIC uses derivatization with NHS-butyrate before the second round of chromatography, thus enabling the efficient separation of the protease-generated neo N-terminal and neo C-terminal peptides from the internal peptides. (b) Prior to the proteolytic processing, C-TAILS uses reductive dimethylation to protect the N-termini before the C-termini are labelled with ethanolamine in an EDC coupling reaction. Subsequently, the internal peptides with free C-termini are captured on polymers, thereby negatively enriching for the protease-generated neo C-terminal peptides.

the carboxyl groups can also be labelled under acidic conditions where the carboxyl oxygen exchange reaction is known to occur [88,89]. Moreover, the exchange can also be catalysed by endopeptidases [90,91], resulting in a reverse exchange of O18 to O16 during the downstream processing step. Therefore, one has to be very cautious when using H2O18 labeling as the protease cleavage site identification approach.

4. Perspectives and future challenges Degradomic methodologies have led to the discovery of a large number of substrates and potential cleavage sites, but the determination of their physiological relevance still remains a significant challenge. Many degradomic experiments have been performed by adding exogenous (usually recombinant) proteases to the


proteome, and, although such approaches provide relevant data about protease specificities, they do not necessarily reveal the relevant physiological substrates because exogenously added proteases cannot reliably simulate the in vivo conditions. Therefore, the substrate candidates identified in these experiments must be rigorously validated in cell-based assays or animal models. This can be extremely time consuming due to the high number of substrate candidates obtained in a single degradomic experiment. Thus, a preferred alternative is an analysis performed on a model organism or in cells where the endogenous protease activity has been selectively modified by genetic manipulation. In such “gain of function-loss of function” type of experiments, gene overexpression, knock-out, silencing or selective chemical inhibition of proteases is used instead of the addition of exogenous proteases [92]. This approach better simulates the in vivo conditions and can lead to the identification of more relevant physiological substrates. Degradomic analysis performed on protease knockout animal models is often considered as the best option for reliable confirmation of proteaseesubstrate interactions in vivo. However, it should be noted that the samples originating from different animal subjects can be very diverse. This diversity can hinder the reproducibility of the proteomic analysis because it is often hard to distinguish between the differences that result from protease action and those originating from the variability between individual test animals. An additional drawback of experiments involving genetic manipulation is that the ablation (or insertion) of a single protease gene can cause a ripple of secondary effects, which may hinder detection of the actual proteolytic events. The reliable identification of the relevant proteolytic events on organism-wide level would be strongly enhanced by degradomic databases, where data from various sources and experimental conditions would be compiled, compared and available for data mining. Although large proteomic datasets became available in proteomic repositories such as ProteomeXchange, where they are deposited according to standardized criteria [93], substantial amount of the degradomic data still remains scattered and sometimes even inaccessible. Among the most popular and widely used protease databases is MEROPS, where the information on peptidases and their inhibitors from different species is archived and curated [3,4]. Unfortunately, the MEROPS database often does not include the current proteomic data because it depends on the good will of the researchers to provide their results. Other degradomic databases, including CutDB [94], TopFIND [95e97] and TOPPR [98], were created by different research groups; however, they are often specific to a particular methodology, which limits their general applicability and the availability of the data for further processing (different groups use different proteomic pipelines and data processing software). We believe that the true future challenge will be integration of all available degradomic data, which would enable data mining and the determination of common rules and denominators of proteolytic processes. Further data integration from different datasets (proteolysis, phosphoproteomics, genomics, etc.), together with novel data analysis and interpretation platforms, will expand our knowledge of proteases, their substrates and their role in health and disease. Although 5e10% of all current drug targets are proteolytic enzymes, the incomplete understanding of proteolysis and its regulation, including knowledge of proteasedependent biomarkers, makes it very challenging to develop efficient therapeutic inhibitors [99]. Thus, several protease inhibitors have failed during preclinical and clinical development, but there were also stories of success, where several protease inhibitors were successfully implemented in therapy; the prime examples include the ACE inhibitors for the treatment of hypertension and HIV protease inhibitors for treating AIDS [2,100,101]. Recent advances in mass spectrometry, sample preparation,

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enrichment and labeling techniques enabled the shift from in vitro to more in vivo-like research. With clever use of animal disease models and clinical samples, the gap between the in vitro and in vivo protease research is constantly narrowing, thus providing new insights into the key proteolytic events in different physiological and pathological conditions. Conflict of interests The authors declare no conflicts of interest. Acknowledgements This work was supported by grants from the Slovenian Research Agency (P1-0140 and J1-3602 to B.T.; J1-0185 and J1-5449 to M. F.). References [1] B. Turk, D. Turk, V. Turk, Protease signalling: the cutting edge, Embo. J. 31 (2012) 1630e1643. [2] B. Turk, Targeting proteases: successes, failures and future prospects, Nat. Rev. Drug Discov. 5 (2006) 785e799. [3] N.D. Rawlings, A.J. Barrett, A. Bateman, MEROPS: the database of proteolytic enzymes, their substrates and inhibitors, Nucleic Acids Res. 40 (2012) D343eD350. [4] N.D. Rawlings, D.P. Tolle, A.J. Barrett, MEROPS: the peptidase database, Nucleic Acids Res. 32 (2004) D160eD164. [5] I. Schechter, A. Berger, On the active site of proteases. 3. Mapping the active site of papain; specific peptide inhibitors of papain, Biochem. Biophys. Res. Commun. 32 (1968) 898e902. [6] A. Doucet, G.S. Butler, D. Rodriguez, A. Prudova, C.M. Overall, Metadegradomics: toward in vivo quantitative degradomics of proteolytic posttranslational modifications of the cancer proteome, Mol. Cell Proteomics 7 (2008) 1925e1951. [7] V. Quesada, G.R. Ordonez, L.M. Sanchez, X.S. Puente, C. Lopez-Otin, The Degradome database: mammalian proteases and diseases of proteolysis, Nucleic Acids Res. 37 (2009) D239eD243. [8] C. Lopez-Otin, J.S. Bond, Proteases: multifunctional enzymes in life and disease, J. Biol. Chem. 283 (2008) 30433e30437. [9] C. Lopez-Otin, C.M. Overall, Protease degradomics: a new challenge for proteomics, Nat. Rev. Mol. Cell Biol. 3 (2002) 509e519. [10] A. Doucet, C.M. Overall, Protease proteomics: revealing protease in vivo functions using systems biology approaches, Mol. Asp. Med. 29 (2008) 339e358. [11] V. Turk, V. Stoka, O. Vasiljeva, M. Renko, T. Sun, B. Turk, D. Turk, Cysteine cathepsins: from structure, function and regulation to new frontiers, Biochim. Biophys. Acta 1824 (2012) 68e88. [12] B. Turk, V. Stoka, Protease signalling in cell death: caspases versus cysteine cathepsins, FEBS Lett. 581 (2007) 2761e2767. [13] K. Plasman, P. Van Damme, K. Gevaert, Contemporary positional proteomics strategies to study protein processing, Curr. Opin. Chem. Biol. 17 (2013) 66e72. [14] I.K. Hwang, S.M. Park, S.Y. Kim, S.T. Lee, A proteomic approach to identify substrates of matrix metalloproteinase-14 in human plasma, Biochim. Biophys. Acta 1702 (2004) 79e87. [15] A.J. Bredemeyer, R.M. Lewis, J.P. Malone, A.E. Davis, J. Gross, R.R. Townsend, T.J. Ley, A proteomic approach for the discovery of protease substrates, Proc. Natl. Acad. Sci. U. S. A. 101 (2004) 11785e11790. [16] S.P. Gygi, G.L. Corthals, Y. Zhang, Y. Rochon, R. Aebersold, Evaluation of twodimensional gel electrophoresis-based proteome analysis technology, Proc. Natl. Acad. Sci. U. S. A. 97 (2000) 9390e9395. [17] A.Y. Lee, S. Goo Park, C.W. Kho, S. Young Park, S. Cho, S.C. Lee, D.H. Lee, P.K. Myung, B.C. Park, Identification of the degradome of Isp-1, a major intracellular serine protease of Bacillus subtilis, by two-dimensional gel electrophoresis and matrix- assisted laser desorption/ionization-time of flight analysis, Proteomics 4 (2004) 3437e3445. [18] T. Major, B. von Janowsky, T. Ruppert, A. Mogk, W. Voos, Proteomic analysis of mitochondrial protein turnover: identification of novel substrate proteins of the matrix protease pim1, Mol. Cell Biol. 26 (2006) 762e776. [19] R.C. Taylor, G. Brumatti, S. Ito, M.O. Hengartner, W.B. Derry, S.J. Martin, Establishing a blueprint for CED-3-dependent killing through identification of multiple substrates for this protease, J. Biol. Chem. 282 (2007) 15011e15021. [20] U.P. Fonovic, Z. Jevnikar, M. Rojnik, B. Doljak, M. Fonovic, P. Jamnik, J. Kos, Profilin 1 as a target for cathepsin X activity in tumor cells, Plos One 8 (2013) e53918. [21] M.M. Dix, G.M. Simon, B.F. Cravatt, Global mapping of the topography and magnitude of proteolytic events in apoptosis, Cell 134 (2008) 679e691. [22] C. Shen, Y. Yu, H. Li, G. Yan, M. Liu, H. Shen, P. Yang, Global profiling of

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