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DOI 10.1002/pmic.201300344

REVIEW

The next level of complexity: Crosstalk of posttranslational modifications A. Saskia Venne∗ , Laxmikanth Kollipara∗ and Rene´ P. Zahedi ¨ Analytische Wissenschaften – ISAS – e.V., Dortmund, Germany Leibniz-Institut fur

Beside gene expression and translational control, which are relatively slow, PTM of proteins represents the major level of regulation, from very fast and reversible to slow or irreversible processes. PTMs affect protein structure and act as molecular switches, which regulate the interaction of proteins with DNA, cofactors, lipids, and other proteins. In the past few years, evidence for extensive crosstalk between PTMs has accumulated. The combination of different PTMs on protein surfaces can create a “PTM code,” which can be recognized by specific effectors to initiate/inhibit downstream events, only inducing/retaining a signal once the complementary incoming signals are present at the same time and place. Although MS-based proteomics has substantially improved our knowledge about PTMs, currently sensitive and dedicated analytical strategies are available only for few different types of PTM. Several recent studies focused on the combinatorial analysis of PTMs, but preferentially utilized peptide-centric bottom-up strategies might be too restricted to decipher complex PTM codes. Here, we discuss the current state of PTM crosstalk research and how proteomics may contribute to understanding PTM codes, representing the next level of complexity and one of the biggest challenges for future proteomics research.

Received: August 6, 2013 Revised: November 6, 2013 Accepted: November 21, 2013

Keywords: Cell biology / Crosstalk / Interplay / Phosphorylation / PTM code / Ubiquitination

1

Introduction

Living cells are constantly exposed to stimuli from their environment and thus have to adapt to rapidly changing conditions. Owing to the mostly static nature of the genome, a highly dynamic and well-regulated system is required to maintain cellular homeostasis. Beside gene expression and translational control, which are relatively slow (within minutes to hours), PTMs of proteins represent the major level of regulation, from very fast and reversible processes such as phosphorylation (seconds) to slower and irreversible ones such as certain forms of glycosylation. Through PTM of a protein, a multitude of different protein species [1] can be generated, compensating for the incongruity between the relatively low number of encoded ¨ AnaCorrespondence: Dr. Rene´ P. Zahedi, Leibniz-Institut fur lytische Wissenschaften – ISAS – e.V., Otto-Hahn-Str. 6b, 44227 Dortmund, Germany E-mail: [email protected] Fax: +49-231-1392-4850 Abbreviation: SCX, strong cation exchange chromatography

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genes and the high number of variable regulators required in complex organisms [2, 3]. Currently, more than 450 PTMs are listed in the Uniprot database [4, 5]—with phosphorylation, lysine acetylation, ubiquitination, and proteolytic processing being the most prominent ones [6, 7]. Indeed, more than 5% of the human genome encode for enzymes that are dedicated to the assembly of these modifications [8] and these enzymes are often strictly controlled by PTM themselves [9, 10]. In contrast to gene expression, which merely controls the abundance of proteins, PTMs usually affect their three-dimensional structures, revealing or concealing active sites and interfaces for protein–protein interaction and thus modulating, e.g. subcellular localization, stability, and activity [11, 12]. They act as molecular switches and may initiate and inhibit the interaction of proteins with DNA, cofactors, lipids, as well as other proteins. In the past few years, evidence for extensive crosstalk between PTMs has accumulated, with the competitive interplay between O-GlcNac and O-phosphorylation being ∗ These

authors contributed equally to this work. Colour Online: See the article online to view Fig. 4 in colour.

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Figure 1. Classification of PTM crosstalk. Short linear motifs on protein surfaces enable protein–protein interaction and can be processed by different regulatory domains. Depending on their function they are classified as writers, readers, and erasers (green, blue, and red rows). In general, positive and negative crosstalk can be distinguished. (A) A writer attaches a PTM to an amino acid (aa) on a target protein. (B) This PTM can attract a reader and trigger the addition of a second PTM, e.g. by recruitment of another writer, or induced by a conformational change of the reader protein itself. (C) Vice versa, a PTM can be read and removed by an eraser protein. Negative crosstalk can be subdivided in direct competition and indirect effects. (D) Two different PTM compete for the same residue. (E) Two PTM have different binding sites but upon initial attachment of the first PTM, the second binding site is indirectly masked. (F) The first PTM leads to a conformational change, which conceals the second PTM binding site from its writer. (G) Depending on which PTM is bound to the respective site different downstream events are initiated: After PTM of the target protein, a protein complex is recruited and the corresponding pathway is triggered. (H) Another PTM can block the respective site such that the pathway is inhibited instead. (I, J) Attached PTM can be removed by an eraser.

one of the first and best-established examples [13]. The advent of highly sensitive MS-based strategies for large-scale PTM analysis substantially improved our knowledge about PTM and the co-occurrence/crosstalk of PTMs. This crosstalk between PTMs and the potential existence of a so-called “PTM code,” regulating protein functions and cellular signaling, represent just another level of complexity and pose a major challenge to ongoing and future PTM research.

2

Different types of PTM crosstalk

Protein function is largely destined by three-dimensional and surface structure, and respective structural subunits can be divided into longer (>30 amino acids) modular domains and shorter (more than ten amino acids) linear motifs. Both participate in generating, transmitting, and processing cellular signals [14]. Linear motifs present modifiable sequence

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stretches that can be “read” and processed by modular domains. Depending on whether these modular domains recognize, transfer, or remove a PTM, they are termed “readers,” “writers,” or “erasers” [15, 16], as illustrated in Fig. 1. In case of phosphorylation, kinases act as writers, whereas domains which recognize the respective residues (e.g. SH2 domains in case of pTyr) are considered as readers and phosphatases as erasers. Which proteins, in particular, act as readers, writers, and erasers depends on the existing PTM pattern of the target protein. For instance, in histone H3, acetylation of Lys9 and Lys14 can be recognized by bromodomains, whereas trimethylation of Lys9 triggers the interaction with the chromodomain of HP1 [17]. This interaction, however, is inhibited in case of Ser10 phosphorylation via aurora B, such that HP1 fails to function as a reader [18, 19]. According to Hunter, PTM crosstalk can be principally classified into positive and negative forms [2]. In positive crosstalk, the initial PTM serves as an active trigger for the

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addition or removal of a second PTM, or as a recognition site for other proteins, as, for instance, in phosphorylationdependent ubiquitination [20, 21] and SUMOylation [22]. In contrast, negative crosstalk can include direct competition of two PTMs for the same amino acid or indirect effects when a specific PTM masks the recognition site for second PTM, thus preventing its addition and/or removal [2].

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First evidences for crosstalk between PTMs—the PTM code

Almost 20 years ago, Hart and colleagues proposed the “yin-yang hypothesis” to describe the direct competitive crosstalk between O-phosphorylation and O-linked N-acetylglucosamine (O-GlcNac) [13], since these PTMs could be found on the same Ser/Thr residues. Furthermore, O-GlcNAc transferase, the enzyme that adds O-GlcNAc to proteins, associates with Ser/Thr phosphatases PP1beta and PP1gamma to form a complex that can remove phospho- and attach O-GlcNac moieties to Ser/Thr residues [23]. In the past few years, it has been shown that O-GlcNac also interacts with other PTMs such as acetylation, methylation, and ubiquitination [24–26]. Another PTM shown to be involved in crosstalk is reversible palmitoylation (S-acylation), which plays an important role in the regulation of diverse ion channels [27]. For instance, the inhibition of the voltage-gated potassium (BK) channel by protein kinase A depends on the palmitoylation of the cysteine abundant stress-regulated exon (STREX) motif on its C-terminus [28]. In addition, important regulatory processes such as irreversible protein processing and degradation can be controlled by PTM crosstalk [24,29–33], as demonstrated, e.g. for phosphodegrons in ubiquitin-mediated protein degradation [34, 35]. Further prominent examples for PTM crosstalk are histones and the tumor suppressor protein p53 [36]. Thus, transcriptional regulation in mammalian cells depends directly on the modification state of histone H3: to achieve its transcriptionally active state by GCN5-mediated acetylation of Lys14, preceding phosphorylation of Ser10 is required [37,38]. In recent years, many more cases for interplay of different PTMs were discovered so that histones are among the most meaningful examples for extensive crosstalk with a high density and variety of diverse PTMs, for instance Lys acetylation, mono-, di-, or trimethylation, phosphorylation, ubiquitination, SUMOylation, and Arg methylation [2, 19]. Many studies postulated that in p53 diverse PTMs might occur at identical amino acid positions [39, 40]. For instance, ubiquitination of Lys372 leads to proteasomal degradation, whereas methylation of Lys372 induced by DNA damage initiates either repression or enhancement of p53 function by facilitating or inhibiting subsequent acetylation on nearby Lysresidues [41]. Moreover, it was demonstrated that the molecular functions of p53 (e.g. nuclear export, stabilization, and transcriptional suppression) depend on its distinct modifi C 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

515 cation patterns [42]. As Sims and Reinberg demonstrated, such PTM patterns seemingly initiate similar downstream effects in different proteins [43]. Thus, histone H3 and p53 are methylated on a specific lysine residue (Lys4 and Lys372, respectively) followed by recruitment of an acetyltransferase complex and subsequent acetylation of another lysine residue ten amino acids C-terminal of the first one (Lys14 and Lys382). In spite of different molecular functions of histones and p53, this mechanism triggers downstream events in both proteins. In this context, the presence of a general PTM code, which might enable co-regulation and fine-tuning of many eukaryotic proteins, is under debate [44]. Although strong context dependence and poor predictability of PTM patterns still argue against the existence of a generally readable code, it nevertheless might be a versatile tool to modulate protein properties, representing a general rule of biochemical regulation. Through the combination of different PTMs on proteins, a highly regulated interface is provided that can be recognized by specific effectors for the dedicated initiation of downstream pathways and interplay with diverse binding partners [45]. Consequently, PTM of those effectors could be a kind of “anti code” enabling a well-defined response only in case of properly matching PTM patterns [42]. These delicate networks might be essential to prevent artificially induced signals and to promote only those signals that are triggered by different sources, thus contributing substantially to the vast complexity required in cellular organisms. This evolutionary strategy enables a versatile regulation of cellular mechanisms from a comparatively limited number of genes and consequently signaling molecules and pathways. Thus, a certain PTM code can only induce and retain a signal once the complementary incoming signals are present at the same time and place [44], and hierarchical ranking of PTM-initiated messages might be essential to prioritize incoming signals according to their importance (see Fig. 2). Indeed, such examples can be found throughout nature, e.g. in nucleic import and export. FOXO4, a member of the forkhead box protein family of transcription factors, can be phosphorylated on Thr28, Ser193, and Ser258 inhibiting nucleic import. However, phosphorylation of Thr447 and Thr451 by a stress-induced Jun N-terminal kinase allows relocalization of the transcription factor into the nucleus— independent of the phosphorylation states of Thr28, Ser193, and Ser258 [46]. Recently, several studies focused on deciphering such potential PTM codes and the conservation of PTMs in general. van Noort et al. studied the crosstalk between lysine acetylation and O-phosphorylation in the genome-reduced prokaryote Mycoplasma pneumoniae [47] and demonstrated that upon deletion of the two existing kinases and its unique phosphatase, not only phosphorylation but also acetylation profiles and protein abundances were affected, whereas mRNA levels remained unchanged; conversely, deletion of two putative N-acetyltransferases affected protein phosphorylation. Notably, 23% of the acetylated lysine residues are conserved across species, from Mycoplasma to eukaryotes, while PTMs www.proteomics-journal.com

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Figure 2. Examples for combinatorial crosstalk of PTM in proteins. (A) A distinct PTM pattern on a first protein ensures the proper binding of a second protein to the associated binding motif, whereas another pattern may actively hinder binding. (B) This PTM-mediated binding can induce a conformational change in one of the proteins, e.g. by allosteric conversion of its binding pocket and therefore affect protein function and interaction. (C) Although single PTM can be assigned to individual molecular functions, hierarchical ranking of PTM can modulate the final function independent of these.

that are highly conserved (>60% in >80 eukaryotes) can be mostly found on metabolic enzymes. In a more global study, Minguez et al. assembled the 13 most frequent PTMs from open databases such as Uniprot [4], dbPTM [48], and Phosida [49], and compared PTM pairs often co-occurring within one protein among eight eukaryotic species [50]. This systematic study revealed that, within the same protein, phosphorylation sites co-exist rather with SUMOylation (∼70% of all phosphorylation sites) than with acetylation sites (∼40%). Indeed, 37% of all modified proteins carry at least two different PTMs, whereas another 61% showed associations with the same type of PTM. Associated PTM pairs were conserved rather than random, and also individual PTMs revealed a  C 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

high conservation across all eight analyzed species. Not surprisingly, the best concordance was found between phylogenetically close species such as mouse and human, whereas PTMs can play similar roles even in very distant species, as well. Notably, such results are highly dependent on the existing data sets, so that currently for mouse and human more information and more potential hits are available when compared to other species. Similar findings were observed by Beltrao et al. who compared the phosphoproteomes of eleven different species, including plants and fungi [51]. They found that the level of conservation of the O-phosphoacceptor sites Ser, Thr, and Tyr was no higher than random, whereas experimentally verified phosphorylation sites are two to three www.proteomics-journal.com

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times more conserved. The level of conservation was lower (up to 18%) for evolutionarily distant species compared to closely related species such as mouse and human (∼40%) and correlates with the time between the origins of the respective species. Thus, for species that evolved one billion years apart, such as Saccharomyces cerevisiae, Candida albicans, Arabidopsis thaliana, and Oryza sativa, a conservation rate of at least 18% could be determined. These three recent studies represent only a share of the extensive effort spent worldwide to get more insights into the highly complex mechanisms of PTM crosstalk, a potentially existing PTM code, and the conservation of PTMs across species. As it stands, PTMs are conserved even across highly divergent species and are often functionally associated with certain other PTMs. These PTM pairs co-occur more likely within the same subcellular localization, e.g. acetylation, methylation, ubiquitination, SUMOylation, and phosphorylation are often co-observed in the nucleus, whereas carboxylation, glycosylation, and nitrosylation seem to preferentially co-occur in cytoplasmic pathways [16,50]. Seemingly, most PTMs show a high co-occurrence with other PTM types as well as a high level of conservation, so that they can compose regulatory centers in which several PTMs are clustered on a limited space to produce highly specific responses upon incoming signals. For histones, two recent studies demonstrated a strong interaction between different PTMs [52, 53]. Thus, mutation of a modified amino acid on a core histone not only inhibited the formation of its final modification pattern, but also affected PTM sites on the other core histones [52]. Moreover, so-called modification quadruplets (i.e. four co-occurring PTMs within a 20 amino acid sequence, such as K9, K23, K27, and K36) can be frequently observed, along with their precursors (di- and triplets) [53]. These findings indicate a hierarchical formation of the final PTM cluster, allowing the addition of further PTMs depending on the presence of the correct precursor PTM pattern. Recently, Peng et al. identified crosstalk motifs from a large human data set, which they extracted from the PhosphoSitePlus database [54] and mapped those to their respective biochemical functions [55]. These short motifs contained one phosphorylation site co-occurring with another PTM (phosphorylation, SUMOylation, or acetylation) within a five amino acid sequence. A comprehensive network analysis of the corresponding proteins suggested putative functional roles for such motifs [55]. These examples demonstrate that the delicate regulation of cellular signaling is indeed coordinated by the combinatorial interplay (and therefore also concentrations) of different PTMs and interaction partners and thus strongly influenced by the cellular context. However, even for state-of-the-art MS approaches, the analysis of such complex networks is still extremely challenging. In principle, current bottom-up strategies usually applied for PTM analysis might be too limited to comprehensively characterize such complex patterns, and therefore the increasingly powerful top-down [56–59] or middle-down [60, 61] MS approaches might be the key to  C 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

understanding PTM codes in the future [62]. In this regard, the group of Kelleher recently described the use of the novel protease OmpT from Escherichia coli, which cleaves at less frequently occurring K/R-K/R sequence motifs and consequently is ideal for middle-down proteomics [60]. In spite of these recent improvements, for top-down and middle-down approaches, proteome coverage and depth are still not comparable with bottom-up strategies. This can be attributed to several factors such as (i) the impaired separation of proteins when compared to peptides, particularly with regard to LC, (ii) reduced MS sensitivity, also due to the presence of different charge states per protein, (iii) the complexity of MS/MS spectra and their identification, and (iv) reduced sensitivity and identification rates for high molecular weight and hydrophobic proteins.

4

Analyzing PTM crosstalk using MS-based proteomics

The importance of PTMs in biological systems is clearly reflected in the increasing number of studies dealing with MS-based PTM analysis, which is not only one of the major strengths of MS, but also one of its biggest challenges [63]. Thus, a wide range of different methods have been developed (i) to identify proteins/peptides carrying specific PTMs, (ii) to correctly map the modified residues onto the protein sequence, and (iii) to quantify significant changes in their abundance between different cellular states [64–69]. For the identification of PTMs by MS certain criteria have to be met: (i) The modification has to be stable during sample preparation and (ii) LC-MS analysis. (iii) The modification has to introduce a mass shift on the parent ion and/or derived fragment ions, so that it can be detected by MS. (iv) In case of low-abundant PTMs, the usage of specific enrichment techniques to remove the bulk of nonmodified peptides can help to overcome the inherent limitations of sensitivity and dynamic range in LCMS. Notably, enrichment techniques can induce a bias toward certain subsets of the respective modified peptide class. If otherwise a PTM is not directly accessible, chemical and enzymatic derivatization procedures can facilitate its indirect stabilization, enrichment, and detection [70]. Improvements and new developments of enrichment strategies [63, 65, 71–75], LC-MS instrumentation and conditions [76–81], as well as search algorithms/strategies [82–85] paved the way for the increasingly sensitive, comprehensive, and confident analysis of a variety of PTMs, currently with a clear focus on phosphorylation [86], glycosylation [87], acetylation [88], ubiquitination [89], and methylation [90,91], mostly due to availability of well-established and robust strategies. Quantitative studies employing stable isotope labeling techniques but also labelfree quantitation enabled the differential analysis of changes in PTM levels and thus revealed important new insights into complex biochemical processes [92–94]. However, the sheer explosion of data and knowledge [95] about PTM-related regulation in health and disease reveals that the associated www.proteomics-journal.com

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Figure 3. Peptide-centric nature of bottom-up proteomics. The peptide-centric analysis is potentially prone to misleading results. (A) The different isoforms of a given peptide are equally distributed. (B) Theoretically, the upregulation of one particular modification site can lead to different changes in signal intensities, depending on whether this increase affects (i) the previously nonmodified version of the peptide, or (ii and iii) already modified versions of the peptide.

processes seem to be much more complex than originally anticipated. Moreover, the detection of multiple PTMs in close proximity within numerous proteins might also indicate that changes eventually detected in studies focusing on a single PTM could be the result of changes of another, unanticipated PTM within the same peptide (see Fig. 3). Notably, this is one of the inherent limitations of the peptide-centric rather than site-centric nature of bottom-up PTM analysis, which is further complicated by the presence of missed- and miscleaved as well as in-source fragmented peptides [96–98]. An improved understanding and deciphering of PTM codes might require three complementary approaches. First, extensive and large-scale bottom-up studies can help to identify and localize numerous PTMs and their changes in signaling processes with high sensitivity—however in a peptide-centric manner. Second, dedicated middle-down and top-down approaches have to be utilized to comprehensively characterize the complex PTM patterns in specific proteins. Third, respective PTM stoichiometries (or rather PTM code stoichiometries) have to be determined. This applies not only to the analysis and quantification of peptides and proteins bearing multiple modifications, but also to the quantitative integration of the generated data, which in case of bottom-up approaches, tackling different PTMs might be extremely challenging [99–101]. Thus, the combined characterization of different PTMs within the same sample(s) for analyzing potential crosstalk and deciphering potential PTM codes [44, 102, 103] will be one of the future goals of proteomics. So far, most large-scale studies have focused on analyzing a single PTM as only for few enrichment strategies, such as strong cation exchange chromatography (SCX) [104,105], titanium dioxide (TiO2 ) [106, 107], hydrophilic interaction liquid chromatography [108], and electrostatic repulsion hydrophilic interaction chromatography [109, 110], specificities for different PTMs have been demonstrated [104, 106, 109]. Thus, the combinatorial analysis of PTMs still requires the use of multiple complementary enrichment strategies. For phosphorylation [65], glycosylation [111], and redox-modifications [112, 113], chromatographic methods are well-established, whereas Lys-acetylated and ubiquitinated peptides are en C 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

riched using specific antibodies [74, 114, 115]. Especially in case of ubiquitination and glycosylation, the characterization of complex patterns remains challenging and large-scale studies are limited to the mere identification of PTM sites rather than elucidating the very structure of the modification. Moreover, the analysis of both PTMs can be prone to artifacts, depending on the applied conditions during sample preparation [75,116], which can also affect the analysis of further modifications [117]. Notably, the systematic study and comparison of established enrichment strategies revealed that with each and every method (and basically also enrichment condition), only a share of the corresponding subproteome is accessible [118]. This is further complicated by the protease-bias typically accompanying bottom-up proteomics approaches, rendering a considerable set of potentially interesting PTMs inaccessible for specific analytical strategies [119–121]. Nevertheless, the continuous technological progress of LC-MS and data interpretation leads to the identification of increasing numbers of PTMs and PTM peptides. Moreover, existing online databases provide a platform to store, merge, and spread the vast amount of data from labs worldwide helping to map PTM sites within protein sequences [49, 54, 122–125]. Thus, it emerged that different PTMs have an extensive overlap and can either occur at the identical amino acid residues or influence other downstream PTMs [126]. Recently, several studies focused on the combined analysis of different PTMs, representing promising examples for the current and future capabilities of MS-based proteomics in revealing complex PTM patterns [47, 94, 100, 101, 106, 127] (see Table 1 and Fig. 4). All these studies involved (i) the concurrent analysis of different PTMs in the same biological sample, (ii) differential labeling (metabolic or chemical) on protein or peptide level, (iii) usage of specific enrichment strategies, and (iv) orthogonal fractionation techniques (IEF, SCX, high-pH-how-pH RP [128], hydrophilic interaction liquid chromatography) for reducing sample complexity and enhancing proteome coverage. Notably, performing successive enrichment steps can be accompanied by sample losses [129], requiring the use of higher amounts of starting material when compared to www.proteomics-journal.com

519 2012 2012 2013 2013 Beli et al. [94] Trinidad et al. [127] Mertins et al. [100] Swaney et al. [101] 10 mg 30 mg 2–15 mg 90–200 mg

5

a) Co-occurring PTM sites.

2078–15 408 2189a)

317–3190 –

O-GlcNac:1750 1848

11 509–11 540 16 500 5466–20 800 2100a)

719 3588 7915 93

Homo sapiens Mus musculus Mycoplasma pneumoniae Homo sapiens Mus musculus Homo sapiens Saccharomyces cerevisiae 200 ␮g 400 ␮g 1.5–5 mg

Organism

studies targeting a single PTM. Consequently, except for the study by Palmisano et al. [106], all these approaches required relatively high amounts of starting material (milligram range) and the overall LC-MS analysis time could be roughly estimated to several hours [47] to few days [100]. Trinidad et al. studied the interplay between O-GlcNac and phosphorylation in mouse synaptic membranes by combining lectin weak affinity chromatography, titanium dioxide enrichment, and high-pH-low-pH RP chromatography [127]. Using this workflow, they found 135 sites that were common for both O-GlcNac and phosphorylation and additionally 66 peptides containing both PTMs. In total, approximately 8% of all identified O-GlcNac modifications occurred on residues that were also found to be O-phosphorylated, indicating the competitive nature of these two PTMs. Mertins et al. employed serial enrichment of PTMs to consecutively enrich phosphorylated, ubiquitinated, and acetylated peptides from SILAC-labeled [130, 131] Velcade-treated Jurkat cells [100] using IMAC [132], diGly-lysine, and acetyllysine antibodies, respectively. Depending on the amount of starting material (2–15 mg), they could quantify several thousand different PTMs peptides using SILAC (see Table 1); extensive prefractionation prior to LC-MS analysis considerably increased the number of identifications, particularly for ubiquitinated and acetylated peptides [133]. Despite having identified approximately 8000 co-modified proteins, this approach did not specifically enrich peptides with two or more different PTMs, which was evident by the low number (less than 0.5%) of multiple PTM peptides identified after MS/MS searches. In contrast, while investigating the crosstalk between phosphorylation and ubiquitination in S. cerevisiae, Swaney et al. [101] specifically enriched peptides containing two different PTMs in close proximity. Thus, using two alternative approaches based on SCX, IMAC, and diGly antibody enrichment, they could identify a total of 1008 ubiquitinated phosphopeptides and suggest the presence of a global crosstalk directionality in which phosphorylation frequently precedes ubiquitination.

P, A P, G P, U, A P, U

2012 2012 2012 Palmisano et al. [106] Palmisano et al. [106] van Noort et al. [47] P, G P, G P, A 1809 3246

NGlycosylation (G) LysAcetylation (A) Ubiquitination (U) O-Phosphorylation (P) Starting material

PTM sites identified/quantified

Table 1. Overview of current MS-based approaches to co-analyze phosphorylation, ubiquitination, acetylation, and glycosylation

PTM coanalyzed

Reference

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Future directions

For a deep understanding of PTM-mediated control of cellular processes, the field still needs to tackle the major challenges, namely (i) time-resolved quantitative changes of PTM and protein levels, (ii) absolute quantification to determine PTM stoichiometry, (iii) improved sensitivity, (iv) robustness of the established workflows to enable applications beside cell culture-based studies, e.g. for the analysis of clinical samples, and (v) finally, the integration of the vast amounts of data to allow a reasonable interpretation and matching of PTMs to functions. For the analysis of PTM crosstalk, targeted MS approaches such as MRM, “high-resolution, accurate mass”, or targeted-MS/MS might be powerful tools for the specific analysis of a defined set of interactions/peptides, whereas www.proteomics-journal.com

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Figure 4. Strategies employed for the combinatorial analysis of PTM. In bottom-up approaches, enzymatically digested samples can be subjected to (A) parallel or (B) serial enrichment of different PTMs. (C) Alternatively, PTM analysis can be conducted top-down by analyzing intact proteins. All these approaches have specific advantages and shortcomings. Serial enrichment of PTMs can be prone to a more pronounced sample loss during the experimental procedure, whereas the parallel enrichment requires a greater amount of starting material. Top-down analysis can yield unique insights into PTM patterns as it is not peptide-centric, nevertheless, it has a lower sensitivity and is experimentally challenging.

data-independent acquisition or novel bioinformatics strategies, such as PTMeta by Nahnsen et al., might help to identify novel PTMs [134]. Vandermarliere and Martens proposed to consider protein structure when evaluating MS-derived PTM annotations [135], in order to improve confidence, but in principle this approach might also be beneficial to identify PTMs that are most critical for conformational changes. Moreover, public repositories provide a rich source for so far unanticipated PTMs, which can be identified by researching available MS/MS data [136, 137]. Recent studies impressively demonstrated that PTM crosstalk can be analyzed by proteomic approaches, however transferring such approaches to clinical samples such as primary tissue to analyze complex PTM patterns in health and disease will require further improvements with regard to robustness and sensitivity [138]. In general, it should be kept in mind that many differences in expression patterns detected with current proteomic technologies base on the observation of only few peptides per protein and thus might rather represent changes in PTMs of single peptides than actual changes of protein abundance. Although still confined to a limited number of established PTM interactions, our current knowledge in conjunction with the number of known but not yet readily accessible PTMs implies the next level of complexity, future proteomics research has to tackle. The financial support by the Ministerium f¨ur Innovation, Wissenschaft und Forschung des Landes Nordrhein-Westfalen is gratefully acknowledged. The authors have declared no conflicts of interest.

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