MINIREVIEW Applications of diagonal chromatography for proteome- wide characterization of protein modifications and activity-based analyses Kris Gevaert 1,2 , Francis Impens 1,2 , Petra Van Damme 1,2 , Bart Ghesquie ` re 1,2 , Xavier Hanoulle 3 and Joe ¨ l Vandekerckhove 1,2 1 Department of Medical Protein Research, VIB, Ghent, Belgium 2 Department of Biochemistry, Ghent University, Belgium 3 UMR 8576 CNRS ) University of Sciences and Technologies of Lille, Structural and Functional Glycobiology Unit, Villeneuve d’Ascq, France Introduction Proteomics refers to a qualitative, differential and quantitative estimation of a proteome. Proteomes can be extremely complex, often encompassing more than 10 000 different components per cell. Two-dimensional gel electrophoresis [1] followed by electroblotting and microsequencing [2–4] or in-gel digestion combined with Edman sequencing [5] of the generated peptides or peptide mass fingerprinting [6–10] have been the methods of choice to reproducibly separate and iden- tify complex protein mixtures. Although large-scale 2D gel electrophoresis separates thousands of proteins [11,12], probably no more than a few hundred different proteins have been identified from such gels. To obtain better proteome coverage, alternative methods were introduced. Groundbreaking methodologies became available when high-throughput genome sequencing started to cover the entire genetic information of several species. This information is now available for a Keywords activity-based probe; ATP-binding proteins; COFRADIC; diagonal chromatography; N-terminal peptides; peptide sorting; protein N-glycosylation; protein processing Correspondence K. Gevaert, Department of Biochemistry, Faculty of Medicine and Health Sciences, Ghent University, A. Baertsoenkaai 3, B-9000 Ghent, Belgium Fax: +32 92649496 Tel: +32 92649274 E-mail: kris.gevaert@ugent.be Website: http://www.proteomics.be (Received 24 April 2007, revised 10 Septem- ber 2007, accepted 17 October 2007) doi:10.1111/j.1742-4658.2007.06149.x Numerous gel-free proteomics techniques have been reported over the past few years, introducing a move from proteins to peptides as bits of informa- tion in qualitative and quantitative proteome studies. Many shotgun pro- teomics techniques randomly sample thousands of peptides in a qualitative and quantitative manner but overlook the vast majority of protein modifi- cations that are often crucial for proper protein structure and function. Peptide-based proteomic approaches have thus been developed to profile a diverse set of modifications including, but not at all limited, to phosphory- lation, glycosylation and ubiquitination. Typical here is that each modifica- tion needs a specific, tailor-made analytical procedure. In this minireview, we discuss how one technique ) diagonal reverse-phase chromatogra- phy ) is applied to study two different types of protein modification: pro- tein processing and protein N-glycosylation. Additionally, we discuss an activity-based proteome study in which purine-binding proteins were pro- filed by diagonal chromatography. Abbreviations ABP, activity-based probe; COFRADIC, combined fractional diagonal chromatography; FSBA, 5¢-p-fluorosulfonylbenzoyladenosine; FSBG, 5¢-p-fluorosulfonylbenzoylguanosine; iTRAQ, isobaric tags for relative and absolute quantification; MudPIT, multidimensional protein identification technology; PNGaseF, peptide N-glycosidase F; SB, sulfobenzoyl; SILAC, stable isotope labeling by amino acids in cell culture; Nbs 2 , 2,4,6-trinitrobenzenesulfonic acid. FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS 6277 large number of species, and it now suffices to generate partial protein sequence information with which to access entire (predicted) protein sequences stored in expressed sequence tag, gene and protein sequence databases. This brought the dawn of novel strategies for pro- tein identification. Measured masses of peptides pro- duced by cleaving a protein with a protease with well-known specificity (e.g. trypsin) were searched against a database of peptide masses calculated from protein sequences derived from genome sequences [6– 10]. When these peptides are derived from a mixture of proteins, they are subjected to MS ⁄ MS fragmenta- tion for identification [13]. Recently, top-down pro- tein sequencing combining ESI MS and highly accurate FT MS [14] was shown to match proteins larger than 200 kDa to sequences in databases [15]. Such strategies only became possible following the availability of massive numbers of DNA sequences, recent developments in MS, and bioinformatics tools that link DNA and protein sequences to information generated by different types of mass spectrometers [16–18]. Recently, peptides have increasingly become the center of analysis: protein mixtures, either partially purified by prefractionation or as such, are digested with trypsin, and the generated peptide mixture is analyzed. When cell or tissue lysates, or even isolated organelles, are analyzed, the number of peptides becomes so high that mass spectrometers can no longer analyze all of the peptides. This results in poor sample coverage, generally referred to as ran- dom sampling or undersampling [19], and it became crucial to add peptide prefractionation before MS analysis. Yates’ group introduced separation of pep- tides based on two parameters [20] ) net charge and hydrophobicity – and called their technique multi- dimensional protein identification technology (MudPIT [21]). MudPIT has since then been used in several studies and has demonstrated its value, but it still suffers from undersampling [19]. Selecting a lower number of peptides representative of each protein originally present in the mixture may alleviate this problem. These so-called signature pep- tides [22] are then the only analyzed components, and in this way a less complex peptide mixture is presented to the mass spectrometer. The first reports using this strategy were selective for cysteinyl peptides, allowed quantification (differential analysis), and used biotin tagging for consecutive capture by immobilized avidin [23]. Later on, affinity selection was used to isolate, for instance, phosphopeptides [24], N-glycosylated peptides [25], ubiquitinated peptides [26], and N-terminal pep- tides [27]. COFRADIC as a peptide-sorting tool Our peptide-centric proteome approach [28,29] sorts signature peptides and selects the part of a proteome containing the information of biological interest. Our technique is based on diagonal chromatography [30,31] consisting of two repeated, identical peptide separa- tions with a specific modification reaction (sorting step) in between. Peptides that remain unchanged elute at the same position in the two chromatographic runs, whereas peptides that acquire a modification segregate from the unchanged peptides either in earlier or in later fractions. To reduce the number of repetitive chromatographic runs, several fractions from the pri- mary run can be combined and subjected to the sort- ing reaction (Fig. 1). For this reason, we call this adapted version of diagonal chromatography com- bined fractional diagonal chromatography (COFRAD- IC [32]). It should be clear from the peptide-sorting principle that any chemical or enzymatic modification that is highly specific, is quantitative and produces a suffi- ciently large chromatographic shift can be imple- mented in COFRADIC. This is illustrated by applications in which selection for methionyl or cyste- inyl peptides was carried out in tryptic digests of total cellular lysates [33,34], or where the N-terminal pep- tides of the proteins present in the mixture were selected [33–36]. Similarly, as we can select peptides based on the specific chemical nature of their amino acid side chains, we can also select peptides carrying post-translational modifications, either by removing this modification (e.g. by dephosphorylation of phos- phopeptides [37]), or by converting it into a moiety with altered properties (e.g. by reducing nitrotyrosine to aminotyrosine [38]). An overview of the COFRADIC sorting protocols that have been developed is given in Table 1. We here concentrate on applications of COFRADIC in studying selected post-translational modifica- tions ) protein processing [34,36] and N-glycosylation [39] – and describe the use of COFRADIC for study- ing interactions between small molecules and proteins. The latter is a particular application of ‘post-transla- tional COFRADIC’, by which a small molecule is covalently linked to a target protein and the corre- sponding modified tryptic peptide is then sorted using the principles of diagonal chromatography. The exam- ple given here is a global activity-based proteome COFRADIC and protein modifications K. Gevaert et al. 6278 FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS analysis of purine-binding proteins in a total lysate of human Jurkat T-cells [40]. COFRADIC analysis of protein processing ) protease degradomics Protein processing introduces novel protein fragments that may be visualized on 2D polyacrylamide gels. For example, Canals et al. used the fluorescent 2D differ- ence gel electrophoresis technique [41] to catalog quan- titative differences in the protein composition of conditioned media of cells either expressing the metal- loproteinase ADAMTS1 at physiological levels or overexpressing it [42]. The latter scenario led to an increase of fragments of proteins shed by ADAMTS1 into the medium that were picked by difference gel electrophoresis and identified by MS. In fact, this study led to the identification of five potential ADAM- TS1 substrates, two of which (nidogens 1 and 2) were further validated. Gel-free proteomic approaches have been introduced for ‘degradomics’ [43] research as well. The group of Overall used isotope-coded affinity tag [23] combined with LC-MS ⁄ MS to quantify the levels of secreted extracellular matrix proteins in breast carcin- oma cell cultures overexpressing a membrane type 1 matrix metalloproteinase [44] and, more recently, they multiplexed their analyses using isobaric tags for relative and absolute quantification (iTRAQ) reagents for the identification of matrix metalloproteinase-2 substrates in fibroblasts [45]. Clearly, both gel-based and gel-free approaches point to potential protease substrates; however, at this stage it is important to note that the characterization of the actual protein cleavage site has typically remained elusive. Nonetheless, the latter information is highly valuable, as it can lead to more rational design of protease inhibitors [46], it is vital for constructing precise algorithms that predict protease substrates [47], and, after all, protein processing is a post-translational modification that should preferably be characterized before any assumption concerning the protease sub- strate potential is made. Protein processing produces a novel C-terminal peptide (from the N-terminal frag- ment of a substrate) and a novel N-terminal peptide (from the C-terminal fragment). Hence, identifying either one of these ‘reporter peptides’ directly points to the actual processing site. As recently reviewed [29], in a whole proteomic background, C-terminal peptides are only poorly isolated. On the other hand, N-termi- nal COFRADIC [33], and the more or less ‘single-step’ isolations of N-terminal peptides by protein sequence tags [48] and positional proteomics [27] were shown to isolate N-terminal peptides from complex mixtures. min 20 30 40 50 60 70 80 mAU 0 200 400 600 800 1000 1200 1400 primary separation combine primary fractions COFRADIC sorting reaction LC-MS/MS analysis min 20 30 40 50 60 70 80 mAU 0 100 200 300 400 500 600 700 secondary separation Fig. 1. The COFRADIC peptide sorting scheme. A peptide mixture is first separated by RP-HPLC (the primary COFRADIC separation). Here, the UV absorbance profile at 214 nm of a tryptic digest of a proteome preparation from human Jurkat T-cells is shown. Primary fractions (indicated in light gray boxes) are combined ) here, four primary fractions (each 1 min wide) that are separated by a 13 min window – and undergo a chemical or enzymatic reaction (the COFRADIC sorting reaction). In this particular case, the side chains of methionines were oxidized by hydrogen peroxide, leading to the formation of methione-sulfoxide. During a second, identical separa- tion (the secondary COFRADIC separation), such oxidized methionyl peptides undergo a hydrophilic shift and segregate away from the bulk of nonmethionyl peptides. Methionyl peptides are thus col- lected (dark gray boxes) and analyzed by LC-MS ⁄ MS. K. Gevaert et al. COFRADIC and protein modifications FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS 6279 However, only the N-terminal COFRADIC approach has thus far been applied to protease degradomics research [36,38] and is discussed here (potential draw- backs of the two affinity-based peptide isolation proto- cols are discussed in Conclusions). In essence, N-terminal COFRADIC segregates pep- tides containing the protein N-termini from internal peptides. This is achieved following an initial acetyla- tion or trideutero-acetylation reaction on a complete proteome prior to trypsin digestion. This blocks all free a-amines and e-amines and, further down, distin- guishes between in vivo blocked (acetylated) and in vivo free (trideutero-acetylated) protein N-termini. Trypsin no longer recognizes acetylated lysines, and, conse- quently, upon digestion, Arg-C type peptides are generated. In fact, two types of peptides are now apparent: N-terminal peptides with a blocked, acety- lated ⁄ trideutero-acetylated a-amine, and internal pep- tides carrying a free a-amine. This peptide mixture is first separated by RP-HPLC and collected in a small number of primary fractions. Then, internal peptides present in each fraction are reacted with 2,4,6-trinitro- benzenesulfonic acid, which is known to efficiently and quantitatively modify primary amines [49]. Internal peptides thereby acquire a trinitrophenyl group at their N-terminus and thus become very hydrophobic. Run- ning such TNBS-modified primary fractions a second time on the same column and under identical chro- matographic conditions will now segregate TNBS-non- reactive N-terminal peptides (all their amino groups were already blocked) from TNBS-reacted internal peptides, which underwent a very strong hydrophobic shift (Table 1). Following metabolic or postmetabolic labeling, N-terminal peptides of two (or more) proteo- mes can be weighed against each other and, impor- tantly, neo-N-termini originating from protein processing are readily distinguished [34,36]. The characterization of protease substrates by such a differential N-terminal COFRADIC approach is illustrated in Fig. 2. In an ongoing project, host cell substrates of the HIV-1 protease are catalogued in human Jurkat T-cells grown in stable isotope labeling by amino acids in cell culture (SILAC) medium supple- mented with either natural, light 12 C 6 -arginine or heavy 13 C 6 -arginine [50]. Arginine is clearly the essen- tial amino acid of choice, as all N-terminal peptides isolated by COFRADIC, by the nature of the process, will end on an arginine residue. This metabolic labeling introduces a mass spacing of 6 Da between light and heavy N-terminal peptides. Cells are typically lysed by repeated freeze–thawing, and the lysate is either incubated with recombinant HIV-1 protease or left untreated (control). Following protease incubation, both proteomes are S-alkylated and acetylated, and equal amounts are then mixed and subjected to N-terminal COFRADIC. In the setup depicted in Fig. 2, neo-N-termini generated by the ret- roviral protease are expected in the ‘light proteome’ and will only be present in the light 12 C 6 -arginine form. Almost identical numbers of pre-existing N-ter- mini (i.e. the N-termini of intact proteins), on the other hand, should appear as couples of light and heavy labeled peptides in ratios close to 1 : 1. This is illustrated by taking b-actin as an example: its acety- lated N-terminal peptide is present in a near 1 : 1 ratio (Fig. 2B), whereas a second, now trideutero-acetylated peptide is only present in the light proteome (Fig. 2C). Following MS ⁄ MS analysis (Fig. 2D), the latter peptide is identified as TEAPLNPKANR(106-116) and constitutes a neo-N-terminus indicative of HIV-1- mediated protein processing. Processing of b-actin by the HIV-1 protease between Leu105 and Thr106 was already identified in previous studies [51], thereby vali- dating our findings. Table 1. Overview of the different COFRADIC procedures that have been developed. The type of peptide, the sorting agent used in between the two consecutive RP-HPLC separation steps and the type of evoked shift are indicated. References to our original papers, in which full technical details can be found, are given. Sorted peptide Sorting agent RP shift Reference Methionyl peptide Hydrogen peroxide Hydrophilic [32] Cysteinyl peptide Reduction of nitrothiobenzoic acid-modified cysteine Hydrophilic [80] N-terminal peptide TNBS reaction on internal, free a-amine peptides Hydrophobic (internal peptides) [33] Phosphorylated peptide Cocktail of phosphatases Hydrophobic [37] N-glycosylated peptide PNGaseF Hydrophilic or hydrophobic [39] ATP-binding peptide NaOH treatment Hydrophilic [40] 3-Nitrotyrosinyl peptide Reduction of NO group Hydrophilic [38] COFRADIC and protein modifications K. Gevaert et al. 6280 FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS A similar approach but now with postmetabolic, trypsin-mediated 18 O-labeling [52] was used to charac- terize in vivo protein processing in Fas-induced apopto- tic Jurkat cells [34]. In this study, 93 cleavage sites in 71 different proteins were characterized in a ‘proteomic background’ of more than 1800 proteins. At the time of reporting these results, the overall majority of the identified cleavage sites were uncharacterized. An anal- ogous setup was used for an in vitro analysis of the substrates of the HrtA2 ⁄ Omi protease [36]. In that human Jurkat T-cells SILAC medium 12 C 6 -arginine human Jurkat T-cells SILAC medium 13 C 6 -arginine freeze-thaw lysate recombinant HIV-1 protease A B D C control combine N-terminal COFRADIC analysis 651.39 651.88 652.37 650.91 650 651 652 653 m/z 947.49 948.06 948.29 949.50 949.80 950.06 950.39 947 948 949 950 m/z 947.71 630.43; y5 744.46; y6 954.66; y8 200 400 600 800 1000 m/z 347.24; b3 444.41; b4 557.42; b5 671.37; b6 1012.66; b9 300 500 700 900 1100 Fig. 2. HIV-1 protease processes b-actin in vitro at Leu105. The experimental route is sketched in (A). Following N-terminal COFRADIC, two different peptides from b-actin were identified. Its N-terminal peptide, DDDIAALVVDNGSGMCKAGFAGDDAPR(2–28) (N-terminus acetylated, lysine trideuteroacetylated, methionine oxidized and cysteine carbamidomethylated) was present in both proteome digests [ion trap MS spectrum of triply charged precursor in (B)], whereas a second peptide was only present in the proteome treated with the HIV-1 protease [ion trap MS spectrum of doubly charged precursor in (C)]. Following MS ⁄ MS analysis [(D), b and y fragment ions indicated), this peptide was identified as TEAPLNPKANR(106–116) (N-terminus and lysine were both trideuteroacetylated), pointing to a previously characterized cleavage site of the HIV-1 protease in b-actin]. K. Gevaert et al. COFRADIC and protein modifications FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS 6281 study, we identified 50 different cleavage events in 15 human proteins, and further validated these Omi substrates by nonproteomic methods. Finally, as our method directly points to the actual site of proteolytic cleavage, data interpretation and the design of follow- up analyses are straightforward. COFRADIC-based sorting of N-glycosylated peptides Glycosylation of asparagines in the Asn-Xaa-Ser ⁄ Thr acceptor motif [53] is a widespread protein modifica- tion: a survey in the UniProtKB ⁄ Swiss-Prot database (release 52.2, 3 April 2007) indicates that 3694 human protein entries (i.e. about 23% of all human protein entries) have at least one feature key pointing to an N-glycosylation event. Different methods have been used to isolate and identify N-glycosylated proteins and characterize their glycosylation sites. In general, glycosylated proteins and peptides are affinity-isolated or chemically trapped prior to further analysis. Affinity-based isolation of N-glycosylated proteins is rather simple and is based on lectin-affinity chromatography. Lectins are proteins or glycoproteins that recognize oligosaccharides but generally favor certain classes of oligosaccharides [54]. Thus, to increase the overall coverage of N-glycosylat- ed proteins, several lectins were combined in multilec- tin affinity chromatography [55,56]. Alternatively, the lectins’ glycan bias was exploited in a serial lectin approach separating N-glycosylated (concanavalin A) from O-glycosylated peptides (Jacalin) [57]. Chemical trapping and release of N-glycosylated peptides was introduced by the group of Aebersold in 2003 [25]. In their approach, aldehydes are first introduced into the glycan by periodate oxidation. These aldehydes then covalently bind to immobilized hydrazide groups by which glycosylated proteins are retained and all non- glycosylated proteins are removed. Immobilized gly- cosylated proteins are then further trimmed by trypsin such that only tryptic peptides carrying glycans remained fixed. Such peptides are finally recovered by peptide N-glycosidase F (PNGaseF), which efficiently removes N-glycans from conjugated asparagines while converting these to aspartic acids [58]. The potential of this chemical trapping approach is evident from recent studies [59–62]; however, it requires several chemical and enzymatic modification steps, and it is therefore more complex than lectin-affinity methods; this could potentially obstruct its widespread introduction in proteomics laboratories. We recently showed that N-glycosylated peptides can be isolated by diagonal chromatography [39]. In our approach, a protein mixture containing N-glycosylated proteins is digested with trypsin, and the resulting pep- tide mixture is separated by RP-HPLC. N-glycosylated peptides are then specifically targeted by PNGaseF and thus deglycosylated (COFRADIC sorting step). When separated a second time by RP-HPLC, deglycosylated peptides shift out of the primary interval of nongly- cosylated peptides and are thereby isolated. Impor- tantly, the shift evoked in this way can be both hydrophilic and hydrophobic, reflecting the nature of the glycan. Indeed, N-glycans can contain negatively charged sugars such sialic acid [63] and sulfated carbo- hydrates [64], and removing such glycans with PNG- aseF evokes a hydrophobic shift analogous to that observed for dephosphorylated peptides [37]. Following MS ⁄ MS analysis, former N-glycosylated asparagines in the Asn-Xaa-Ser ⁄ Thr motif are deamidated to aspartic acids. This mass signature in the consensus N-glycosyl- ation motif is used to distinguish deglycosylated pep- tides from artificially deamidated peptides, especially in Asn-Gly and Asn-Ser motifs [65], undergoing small hydrophilic shifts [39]. Our COFRADIC procedure was applied to a trypsin digest of 10 lL of mouse serum depleted for its three most abundant proteins (albumin, IgGs and transfer- rin), and resulted in the characterization of 127 differ- ent N-glycosylation sites (comprising 10 novel sites) in 82 proteins estimated to span a concentration range of at least five orders of magnitude [39]. Several N-glyco- sylation sites of the large subunit of mouse carboxy- peptidase N (UniProtKB ⁄ Swiss-Prot entry Q9DBB9) were identified in this study (Table 2). This protein binds to the catalytic subunit of carboxypeptidase N, which functions in protecting organisms from circulat- ing vasoactive and inflammatory peptides containing C-terminal arginine or lysine [66]. The large subunit of this complex binds and stabilizes the catalytic subunit and thereby keeps the complex in circulation. In silico predictions indicate that this protein potentially has nine different targets for N-glycosylation, six of which were identified in our study: the asparagines at posi- tions 74, 111, 119, 348, 359 and 367 (Table 2). Three other asparagines at positions 266, 311 and 520 were missed and, as is evident from the annotations in the UniProtKB ⁄ Swiss-Prot database, have hitherto not been experimentally characterized. A closer look at the sequences of the tryptic peptides harboring the poten- tial glycosylation sites at positions 266 and 311 clearly indicates that these peptides are very large (66 and 36 amino acids long, respectively). Therefore, they could have been missed either because they are insoluble or because our mass spectrometers, which have an empiri- cal upper mass limit close to 3000 Da for producing COFRADIC and protein modifications K. Gevaert et al. 6282 FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS MS ⁄ MS spectra that are unambiguously identified by mascot [67], could not detect them. One obvious way to overcome this is by using proteases with nontryptic specificities such as proteinase K that generally pro- duce smaller peptides [68] and thus increase the chance that more glycopeptides will be finally identified. However, such protease digests sharply augment the complexity of the analyte mixture. Activity-based proteome-wide profiling of purine-binding proteins In order to assign functions to the many uncharacter- ized (hypothetical) proteins that genome sequencing projects provide, several small compounds occupying and modifying active sites of enzymes have recently found their way into functional proteomics [69,70]. Quite a lot of these so-called activity-based probes (ABPs) are natural protein-reactive products or syn- thetic analogs [71]. ABPs in functional proteome stud- ies generally consist of four parts: a reactive group targeting amino acids within the enzyme’s binding pocket, a structural moiety that is recognized by this binding pocket, a linker, and a tag for visualization and ⁄ or isolation of modified proteins [72]. Different classes of enzymes have already been studied using activity-based proteomics. Examples include biotinyl- ated fluorophosphonates for monitoring serine hydrolases [73], and biotinylated a-bromobenzyl- phosphonates for detecting protein tyrosine phosphata- ses [74]. ATP, ADP and AMP are important sensors for the energy status of cells, interacting with and thereby reg- ulating the activities of key enzymes in cellular metab- olism. In addition, ATP and, to a lesser extent, GTP are known as carriers of high-energy phosphoryl groups that can be covalently linked to proteins and metabolites. Here, kinases play a pivotal role and transiently interact with triphospho derivatives before the b–c phosphodiester bond is cleaved. To character- ize ATP-binding and GTP-binding proteins in cells, we profiled purine-binding proteins on a proteome scale [40]. For this purpose, we used 5¢- p-fluoro- sulfonylbenzoyladenosine (FSBA) (Fig. 3B), a known reactive homolog of ATP (Fig. 3A) that binds proteins in their nucleotide-binding region and then covalently modifies nucleophilic amino acids (especially tyrosine and lysine) in its proximity [75]. In the past, FSBA was mainly used to profile the ATP-binding features of selected, individual proteins. However, in 2004, Moore et al. published a study in which FSBA and 5¢-p-fluoro- sulfonylbenzoylguanosine (FSBG) were used to profile ATP-binding and GTP-binding proteins, respectively, in the proteomes of different lymphoid cells [76]. In their approach, proteins were labeled with FSBA or FSBG in cell extracts, separated by 2D PAGE and electrotransferred onto a poly(vinylidene difuoride) membrane. Subsequent treatment of sulfobenzoyl adenosine ⁄ sulfobenzoyl guanosine (SBA ⁄ SBG)-labeled proteins with NaOH hydrolyzed the ester bond between the adenosine or guanosine and the sulfo- benzoyl (SB) group and exposed the latter. Antibodies to SB were then used to immunodetect FSBA-targeted or FSBG-targeted proteins. Overlaying an image of the immunoblot with the 2D pattern of silver-stained proteins pointed to candidate ATP-binding or GTP- binding proteins that were selected from the 2D gel and identified by MS. In this way, 12 different proteins could be identified as FSBA-labeled proteins. Given the fact that a mild alkaline treatment as used by Moore et al. [76] hydrolyzes the rather unstable benzoate ester bond between the adenosine and the SB group, we recently developed a COFRADIC protocol sorting for SBA-labeled peptides [40]. The central sort- ing reaction is shown in Fig. 3C and consists of a 25 min incubation of SBA-labeled peptides in 50 mm Table 2. N-glycosylation sites in the large subunit of mouse carboxypeptidase N. Both N-glycosylation sites characterized in our study [39] and those that were missed are given. Known or potential glycosylation sites are in bold type. [M +H] + , mass of the singly protonated peptide ion. Position Tryptic peptide sequence [M +H] + Characterized N-glycosylation sites 74 AFSGSPNLTK(68–77) 1021.53 111, 119 LQDLEITGSPVSNLSAHIFSNLSSLEK(99–125) 2899.50 348, 359 LSLDSNNLTALHPALFHNLSR(342–362) 2333.24 367 LQLLNLSR(363–370) 956.59 Unidentified N-glycosylation sites 266 LPEGALGSLSSLQELFLDGNAITELSPHLFSQLFSLEMLWLQHNAICHLPVSLFSSLHNLTFLSLK(208–273) 7316.82 311 TLPEGLFAHNQGLLHLSLSYNQLETIPEGAFTNLSR(279–314) 3981.05 520 DGSDSAAMVYNSSQEWGLR(510–528) 2072.90 K. Gevaert et al. COFRADIC and protein modifications FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS 6283 NaOH. We first tested our protocol on a tryptic digest of SBA-labeled recombinant Chinese hamster a-protein kinase A, and noted that removing the adenosine group in between the two COFRADIC separations resulted in a strong hydrophilic shift of only one peptide that was identified as HKETGNHYAMK*ILDK(62–76) (K* indicates the SB-labeled lysine). This peptide har- bors the site known to be involved in the catalytic transfer of c-phosphate from ATP to protein kinase A substrates [77]. When this sorting procedure was applied to a whole proteome ) here, a human Jurkat T-cell proteome depleted of small compounds like ATP and GTP, which could compete with FSBA ) 185 sites in 132 proteins were identified. Clearly, this is a significantly higher number of proteins than were detected in the previous gel-based study [76]. Therefore, our COFRADIC technique allows the functional interpre- tation of a larger part of a sampled proteome. More importantly, our approach directly points to the actual site that was modified and might thereby aid in inter- preting structural features of ATP-binding proteins. As expected, the majority of FSBA-labeled Jurkat proteins were known binders of small nucleotides, cofactors, or DNA and RNA molecules. However, several proteins and sites were not readily explained by the known affinity of FSBA for purine-binding pock- ets. Closer inspection revealed that at least 23 of such unexplainable sites were previously characterized as tyrosine phosphorylation sites. Therefore, we assume that when FSBA is recognized by an ATP-binding site, there are two options for SBA labeling: either the fluorosulfonyl group reacts with a target side chain located on the protein carrying the ATP-binding site (homo-reaction), or, through lack of a suitable reac- tion partner, it may react with a side chain present on proteins that interact with the protein carrying the actual ATP-binding site (crossover reaction). An illus- tration of the second case is observed for kinases that can transfer the SBA group onto their substrate pro- teins by a pseudocatalytic mechanism. In this way, the SBA group can be linked to proteins that have no ATP-binding site. We have verified this assumption by incubating a Src substrate peptide with FSBA in the presence or absence of Src; it was shown that Src ‘catalyzed’ the labeling of the substrate peptides by a factor of more than 20 [40]. Hence, we concluded that care must be taken when interpreting the results of activity-based proteome studies, as not all identified proteins will actually carry out the function that was assessed by the used ABP. Conclusions As compared to other gel-free proteomics techniques [72], COFRADIC has a number of unique properties. As COFRADIC is essentially a peptide-sorting tech- nology by which only a set of peptides representative of the proteomic problem is withdrawn from the com- plex analyte mixture, the sample-to-sample reproduc- ibility is much higher than in shotgun approaches [78]. For instance, although MudPIT uses a powerful chromatographic technology combining two basic sep- aration principles (peptide net charge and hydro- phobicity), peptide separation still takes place on the entire, complex mixture. COFRADIC eliminates a O HO OH O O S O O PEPTIDE A C B N N N N NH 2 OH O S O O PEPTIDE N N N N NH 2 O HO OH O P O P O P O O O O O O O N N O HO OH O O S O O F N N NH 2 50 mM NaOH 25 min @ 25°C Fig. 3. FSBA COFRADIC. The structures of ATP and its reactive homolog FSBA are shown in (A) and (B), respectively. The COFRADIC reaction sorting for SBA-labeled peptides is shown in (C). COFRADIC and protein modifications K. Gevaert et al. 6284 FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS large number of peptides that are irrelevant to the biological problem under consideration, thereby reduc- ing the complexity of the problem without losing much information. Unlike targeted peptide-centric approaches such as isotope-coded affinity tag [23], COFRADIC is not based on affinity procedures, which are limited at two levels: first, the chemistries used to convert sets of peptides into affinity probes; and second, the limitations of mass transfer that are inherently to liquid–solid state chemistries [79]. At the first level, COFRADIC has a fundamental advantage because its chemistries do not need to create different affinity labels. For instance, an affinity tag specific for methionyl peptides is extremely difficult to establish; in contrast, a simple oxidation step by hydrogen peroxide will specifically produce methionyl-sulfoxide derivatives showing significant hydrophilic shifts in diagonal reverse-phase chromatography [32]. At the second level, affinity-based experiments [23,27,48] have limita- tions either at the level of incomplete or variable incor- poration of the tag (for example, linking a biotinyl group to a specific set of peptides can be incomplete and partly unspecific) or at the level of interactions of tagged peptides with the affinity resin, where the high- est affinities and avidities are not always reached. In contrast, using COFRADIC, we select subsets of pep- tides related to the biological question under investiga- tion. For instance, for the study of the oxidation of protein methionines during oxidative stress, cells can be differentially labeled with [ 13 C]methionine or [ 12 C]methionine. With COFRADIC, we sort for methi- onine-containing peptides only: thus, we select out of the mixture only those peptides containing the differ- ential information, while all other peptides, which are of no relevance, are discarded. All kinds of peptide selections can be done with- out, each time, modifying or adapting the sorting apparatus itself. The latter is, in principle, an auto- mated HPLC apparatus equipped with an auto- sampler, and can be purchased from a variety of companies; and, at least in our hands, HPLC solvent gradients and flow rates can nowadays be controlled such that the overall reproducibility of HPLC runs is very high, allowing efficient peptide sorting by COFRADIC. The only parameter that needs chang- ing is the nature of the COFRADIC sorting reaction, which can be chemical or enzymatic, but should under all circumstances be highly specific and prefer- entially quantitative. Together with a sufficiently large chromatographic shift (to segregate altered and unal- tered peptides to the highest degree), the specificity and quantitative nature of the COFRADIC sorting reaction are clearly crucial for efficient peptide sort- ing. Unspecific sorting reactions and only slight alter- ations in peptide column retention will yield ‘impure’ sorted peptides, whereas nonquantitative sorting reac- tions will lead to irreproducible peptide sorting. In Table 1, the chemical or enzymatic modification reactions that have been used successfully in a COFRADIC-based approach are listed. They cover sorting methods varying from modifications to spe- cific side chains, such as cysteinyl [80] and methionyl [32] moieties, to post-translational modifications by phosphatase [37] and PNGaseF [39] treatments. In another application, peptides located at the N-termini of proteins or of their fragments are sorted [33]. In this way, we have successfully analyzed protein pro- cessing in highly complex proteomes by the target proteins and identified the exact cleavage site(s), cre- ating the basis for fundamental protease degradomics [34,36]. As mentioned above, it is also possible to set up spe- cific covalent interactions between proteins and small molecules such as drugs or mimetic molecules of natu- ral metabolites such that chromatographic shifts can be evoked, thus allowing sorting of the conjugated peptides by COFRADIC. The example shown relates to a study with an ATP analog [40]; however, it can, in principle, be extended to drugs that covalently inter- act with their target protein, either directly or after being metabolized in the tissue or organism to form reactive products. One of the drawbacks of COFRADIC relates to the segmentation of the peptide separation flow during the primary run: many peptides may end up in two con- secutive fractions for their secondary analyses. When the same separation is repeated a second time or fur- ther times, peptides eluting at the boundaries of the primary selected time intervals may show a slight drift, thus ending up in different secondary fractions. By the same effect, peptides that are differentially labeled by isotopes, such as hydrogen and deuterium, the deriva- tives of which display slightly different chromato- graphic properties, may be artificially enriched in certain fractions. Such situations could impose a hin- drance on any type of quantitative differential analyses performed with COFRADIC. In addition, if eluting peptide peaks are cut, the remaining material is diluted, imposing limitations on the overall sensitivity. This sensitivity issue remains one of the limitations of the technology; however, it is very well compensated by the efficiency of the other steps in the system: lim- ited losses during consecutive chromatographic separa- tions, more freedom in the selection of efficient reaction systems and better reaction conditions, which are performed in a homogeneous phase, and, finally, K. Gevaert et al. COFRADIC and protein modifications FEBS Journal 274 (2007) 6277–6289 ª 2007 The Authors Journal compilation ª 2007 FEBS 6285 the fact that at the end only a selection of peptides is presented for analysis to mass spectrometers. The sta- bility of the peptide elution profile, particularly in the primary runs of COFRADIC approaches, has not been found to be a big problem as long as the buffer conditions in which the sample has been prepared are kept constant. One general drawback of signature peptides for characterizing protein modifications is the fact that only those peptides that can be separated by RP- HPLC, ionize well in mass spectrometers and yield informative MS ⁄ MS spectra can be identified. An interesting, recent development is top-down protein sequencing, which enables researchers to focus on an increasing set of protein modifications [81,82]. Such top-down techniques focus on complete proteins, allow detection of normally labile protein modifications, and avoid several problems associated with signature pep- tides (see above). However, proteins of interest need to be rather pure (the number of contaminating proteins should be low), which may currently hinder the routine applicability of such approaches. This review has shown that the COFRADIC tech- nology is extremely versatile and flexible and provides profound insights into biological questions, often much more than what could be obtained by alterna- tive proteomics procedures such as 2D gels or shotgun proteomics. Its strong point is its high flexibility in selecting specific chemistries or enzymatic modifica- tions oriented towards the biological question(s) under consideration. 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MINIREVIEW Applications of diagonal chromatography for proteome- wide characterization of protein modifications and activity-based analyses Kris Gevaert 1,2 ,. genetic information of several species. This information is now available for a Keywords activity-based probe; ATP-binding proteins; COFRADIC; diagonal chromatography; N-terminal