Glycosylation Signatures in Drosophila: Fishing with Lectins Gianni Vandenborre,†,‡ Els J. M. Van Damme,‡ Bart Ghesquie`re,§,| Gerben Menschaert,⊥ Mohamad Hamshou,†,‡ Rameshwaram Nagender Rao,†,‡ Kris Gevaert,§,| and Guy Smagghe*,† Laboratory of Agrozoology, Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, B-9000 Ghent, Belgium, Laboratory of Biochemistry and Glycobiology, Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, B-9000 Ghent, Belgium, Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium, Department of Biochemistry, Ghent University, B-9000 Ghent, Belgium, and Laboratory for Bioinformatics and Computational Genomics, Faculty of Bioscience Engineering, Ghent University, Coupure links 653, B-9000 Ghent, Belgium Received February 26, 2010
Glycosylation is a co- and/or post-translational protein modification that generates enormous structural diversity among glycoproteins. In this study, immobilized lectins were used to capture glycoproteins with different glycan profiles from Drosophila melanogaster extracts. On the basis of previous results from glycan array analyses, the snowdrop (Galanthus nivalis) agglutinin (GNA), the tobacco (Nicotiana tabacum) lectin (Nictaba) and the Rhizoctoni solani agglutinin (RSA) were used to select for a broad range of N- and O-glycan structures. After different lectin affinity chromatographies, the glycoproteome of Drosophila was analyzed using LC-MS/MS and glycoprotein abundances were calculated by different label-free methods. Bioinformatics tools were used to annotate the identified glycoproteins and the glycoproteins were classified according to their molecular function or their involvement in a biological process. Subsequent enrichment analysis (using the DAVID database) was employed to find biological processes or molecular functions in Drosophila in which a particular glycan signature is overrepresented. The results presented here clearly demonstrate that next to the presence of high-mannose and paucimannose N-glycans, Drosophila is capable of synthesizing glycoproteins carrying extended hybrid and complex N-linked glycans. Furthermore, it was demonstrated that a specific glycosylation signature can be associated with a functionally related group of glycoproteins in Drosophila, both in terms of biological process and molecular function. Keywords: Drosophila melanogaster glycan profiles • glycoproteins • lectins
1. Introduction
glycans can regulate intercellular recognition and are important for a plethora of biological signaling processes.2-9
Many proteins produced by multicellular organisms carry carbohydrate structures called glycans that mediate important roles in several biological processes. The two major forms of this protein modification are N-glycans and O-glycans, referring to the type of glycosidic linkage of this carbohydrate structure to the amino acids Asn and Ser/Thr, respectively. The repertoire of proteins carrying glycans is very diverse, including enzymes involved in a wide variety of metabolic processes and cellular functions. During protein biosynthesis, these glycan structures can be involved in protein folding, quality control, or targeting.1 As constituents of the cell membrane and extracellular matrix,
In recent years, glycan research has focused on the development of highly sensitive and rapid mass spectrometric screening strategies for defining a multitude of glycosylated proteins in Caenorhabditis elegans,10,11 the fruit fly Drosophila melanogaster,12 mammalian cells,13 or specific tissues in knockout mice.14,15 Despite the availability of the complete Drosophila genome sequence and a broad range of efficient technical tools for molecular, genetic, and cellular studies, relatively little is known about the variety in protein-linked glycan structures in Drosophila. Studies of N-linked glycans in Drosophila have documented the abundance of the high-mannose oligosaccharides and core fucosylated pauci-mannose glycans.12,16,17 Interestingly, the N-glycan profile of the fly changes as development proceeds, suggesting specific regulation of the glycosylation machinery and roles for certain glycan structures during different stages of development.17-19 Recent studies in Drosophila have also identified proteins modified by mucin type O-linked glycosylation.20,21 Although many types of O-glycosylation are known to exist, the mucin type O-glycosylation which involves the addition of N-acetylgalactosamine (GalNAc)
* To whom correspondence should be addressed. E-mail: guy.smagghe@ ugent.be. † Department of Crop Protection, Faculty of Bioscience Engineering, Ghent University. ‡ Department of Molecular Biotechnology, Faculty of Bioscience Engineering, Ghent University. § Department of Medical Protein Research, VIB. | Department of Biochemistry, Ghent University. ⊥ Laboratory for Bioinformatics and Computational Genomics, Faculty of Bioscience Engineering, Ghent University. 10.1021/pr1001753
2010 American Chemical Society
Journal of Proteome Research 2010, 9, 3235–3242 3235 Published on Web 04/13/2010
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ships) database was used. Additionally, gene annotation enrichment analysis was performed using the DAVID (Database for Annotation, Visualization and Integrated Discovery) resources to extract biologically valuable information from different glycan-associated proteomes.30 For the first time, a comparative analysis was made between several identified Drosophila glycoproteins and the available information on glycosylation in Drosophila was employed to evaluate the use of lectins to select for subsets of glycosylated proteins.
2. Materials and Methods
Figure 1. Schematic diagram of glycoprotein purification using lectin chromatography and mass spectrometry analysis. A series of lectin affinity chromatography steps were employed for enrichment of Drosophila proteins with different glycosylated modifications. Glycan specificity of each lectin employed is illustrated in boxes.
to Ser/Thr, often extended with galactose (Gal), is the most abundant O-glycan structure in Drosophila.21 Lectins are a diverse group of proteins from nonimmune origin that specifically bind with different carbohydrate structures. Although lectins have been used in glycoprotein analysis for decades, it is only recently that they are being applied to glycoproteomics. Lectins can interact with a specific structural motif in a particular glycan, and depending on the specificity of the lectin, a selection for different glycan structures can be made. Nowadays, the use of lectin affinity chromatography is an established method to selectively enrich certain glycan containing proteins.20,22,23 Previously, lectin chromatography with immobilized concanavalin A (ConA) and the elderberry (Sambucus nigra) lectin SNA resulted in the enrichment of high-mannose and complex N-glycosylated proteins from human serum and urine, respectively.22,24 In this study, a similar approach was utilized to explore the full diversity of glycan structures in Drosophila by enrichment of glycoproteins containing both N- or O-glycan structures using the snowdrop (Galanthus nivalis) agglutinin (GNA), the tobacco (Nicotiana tabacum) lectin (Nictaba), and the Rhizoctonia solani agglutinin (RSA) (Figure 1). Glycan array analyses revealed that GNA has a high specificity for oligomannosidic structures and highmannose N-glycans,25 while Nictaba recognizes high-mannose and more processed N-glycans with terminal Gal, N-acetylglucosamine (GlcNAc), and GalNAc structures.26 A detailed glycan array analysis suggests that the binding site of Nictaba is most complementary to the Man3GlcNAc2 core of N-glycans (Figure 1). Finally, RSA was employed to broaden the range of captured glycoproteins, displaying a high affinity for certain mucin type O-linked glycans along with terminal Gal/GalNAc residues on complex N-glycans.27 After purification of Drosophila glycoproteins based on their interaction with immobilized lectins, their identity was determined using LC-MS/MS and the corresponding protein abundance was estimated using established label-free methods.28 To subdivide the identified proteins into functional groups, the PANTHER (Protein ANalysis THrough Evolutionary Relation3236
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2.1. Insects and Lectins. D. melanogaster was maintained on a corn meal-based diet31 under standard conditions of 23-25 °C, 65-70% relative humidity, and a 16:8 (light/dark) photoperiod. GNA was purified from the bulbs of snowdrop (G. nivalis) using a combination of affinity chromatography and ion exchange chromatography as described previously.32 Nictaba was purified from the tobacco plant (N. tabacum cv Samsun NN) after exposure to the plant hormone jasmonic acid methyl ester.33 RSA was obtained from sclerotes of the plant pathogenic fungus R. solani using several rounds of affinity chromatography and anion exchange chromatography.34 The carbohydrate binding specificity of GNA, Nictaba, and RSA was studied using glycan array screening provided by the Consortium for Functional Glycomics (www.functionalglycomics.org). 2.2. Affinity Purification of Drosophila Glycoproteins. Homogenates of D. melanogaster were made in liquid nitrogen using a chilled mortar and pestle. The extraction buffer (0.1 M phosphate buffer (pH 7.6) containing 2.1% of the EDTA-free Halt protease inhibitor cocktail (Pierce, Rockford, IL)) was added at a ratio of 2 mL/g of tissue. The extract was homogenized at 4 °C using a glass and Teflon homogenizer (10 strokes at 2000 rpm). Afterward, the homogenates were transferred into plastic tubes, sonicated for 4 min in an ice water bath, frozen at -80 °C overnight, and thawed at 4 °C the next day. Finally, the homogenates were centrifuged at 9500g for 1 h at 4 °C, and the supernatants were collected. Before loading the extract onto the GNA-Sepharose, NictabaSepharose, or RSA-Sepharose columns, the extract was adjusted to 0.2 M NaCl. After washing the columns with 0.2 M NaCl, the lectin-binding proteins were eluted with 20 mM unbuffered 1,3-propanediamine. Peak fractions were pooled, adjusted to 0.2 M NaCl and pH 7.6, and rechromatographed on the same lectin column. The eluate and flow through after lectin chromatography were analyzed by SDS-PAGE. Protein concentrations were determined with the Bradford method using bovine serum albumin (Sigma-Aldrich) as standard. 2.3. Preparation of Peptides for LC-MS/MS Analysis. Purified proteins (approximately 300 µg) from each lectin affinity column were completely dried and redissolved in freshly prepared 50 mM ammonium bicarbonate buffer (pH 7.8). Prior to digestion, protein mixtures were boiled for 10 min at 95 °C followed by cooling down on ice for 15 min. Sequencing-grade trypsin (Promega, Benelux, Leiden, The Netherlands) was added in a 1:100 (trypsin/substrate) ratio (w/w) and digestion was allowed overnight at 37 °C. The sample was acidified with 10% acetic acid and loaded for RP-HPLC separation on a 2.1 mm internal diameter ×150 mm 300SB-C18 column (Zorbax, Agilent technologies, Waldbronn, Germany) using an Agilent 1100 Series HPLC system. Following a 10 min wash with 10 mM ammonium acetate (pH 5.5) in water/acetonitrile (98/2 (v/v), both solvents were “Baker HPLC analyzed” (Mallinckrodt Baker B.V., Deventer, The Netherlands)), a linear gradient to
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Glycosylation Signatures in Drosophila 10 mM ammonium acetate (pH 5.5) in water/acetonitrile (30/ 70, v/v) was applied over 100 min at a constant flow rate of 80 µL/min. Eluting peptides were collected in 48 fractions between 20 and 68 min. To reduce the number of LC-MS/MS runs, fractions separated by 16 min were pooled and vacuum-dried for further LC-MS/MS analysis. In this way, 16 (and not 48) LC-MS/MS runs were performed to analyze all peptide fractions. 2.4. Mass Spectrometric Analysis. The fractions were redissolved in 80 µL of 2.5% acetonitrile (HPLC solvent A). Eight microliters of this peptide mixture was applied for nanoLCMS/MS analysis on an Ultimate (Dionex, Amsterdam, The Netherlands) in-line connected to an Esquire HCT mass spectrometer (Bruker, Bremen, Germany). The sample was first trapped on a trapping column (PepMap C18 column, 0.3 mm i.d. × 5 mm, Dionex (Amsterdam, The Netherlands)). After back-flushing from the trapping column, the sample was loaded on a 75 µm i.d. × 150 mm reverse-phase column (PepMap C18, Dionex (Amsterdam, The Netherlands)) The peptides were eluted with a linear gradient of 3% solvent B (0.1% formic acid in water/acetonitrile (3/7, v/v)) increase per minute at a constant flow rate of 0.2 µL/min. Using datadependent acquisition, multiply charged ions with intensities above threshold (adjusted for each sequence according to the noise level) were selected for fragmentation. During MS/MS analysis, a MS/MS fragmentation amplitude of 0.7 V and a scan time of 40 ms were used. 2.5. Protein Identification and Bioinformatics. The fragmentation spectra were converted to mgf files using the Automation Engine software (version 3.2, Bruker) and were searched using the MASCOT database search engine (version 2.2.0, Matrix Science, http://www.matrixscience.com) against the Flybase database (release FB2010_01). Peptide mass tolerance was set at 0.5 Da and peptide fragment mass tolerance at 0.5 Da, with the ESI-IT as selected instrument for peptide fragmentation rules. Peptide charge was set to 1+, 2+, 3+. Variable modifications were set to methionine oxidation, pyroglutamate formation of amino terminal glutamine, acetylation of the N-terminus, deamidation of glutamine or asparagines. The enzyme was set on trypsin. Only peptides that were ranked one and scored above the threshold score set at 95% confidence were withheld. The peptide-identification results were made publicly accessible at the proteomics identification (PRIDE) database (experiment accession number 12011) (http://www.ebi.ac.uk/pride). Several label-free methods were employed to quantify peptide and protein amount.35,36 First, the emPAI index was calculated to estimate the abundance of the glycoproteins based on the number of identified tryptically cleaved peptides (Supporting Information Tables S1-S3).28 Second, a spectral count method was applied to quantify the proteins based on the number of identified MS/MS spectra (Supporting Information Tables S1-S3). For this purpose, a clustering step was introduced to group highly similar fragmentation spectra.37 The cluster parameters and score calculations are outlined in the Supporting Information. In addition, the occurrence of potential N-glycosylation sites present on the glycoproteins was determined by counting the number of consensus sequences Asn-X-Ser/Thr (where X is any amino acid except proline). To subdivide the identified glycoproteins into functionally related subfamilies, the PANTHER database (http://www.pantherdb.org) was used.29,38 Enrichment of annotation terms for the glycoproteins captured with the different lectins were analyzed using the Database for Annotation, Visualization and
Table 1. Number of Putative N-Glycosylated Drosophila Proteins Achieved from ESI-MS Analysis of the Peptides by Different Lectin-Affinity Chromatography
lectin
no. of peptides identified
no. of proteins identified
putative N-glycosylated proteins
GNA Nictaba RSA
553 635 754
138 185 148
124 160 121
Integrated Discovery (DAVID) (http://david.abcc.ncifcrf.gov/ ).30 Fold enrichment analysis was performed between the identified glycoproteins and a complete adult Drosophila proteome data set provided by the DAVID resources (based on the Flybase database). Statistically overrepresented annotation terms were detected using the Benjamini statistics for multiple comparison corrections to calculate the false discovery rate (FDR).
3. Results and Discussion 3.1. Lectin Affinity Chromatography. To study the diversity in glycoproteins present in Drosophila, lectin chromatography was used to capture different sets of proteins depending on their glycan profile (Supporting Information Figure S1). Identification of the Drosophila glycoproteins that specifically bind to GNA, Nictaba, or RSA was achieved by in-solution digestion of purified proteins using trypsin and subsequent LC-MS/MS analysis of the resulting peptide mixture using an electrospray ionization-ion trap mass spectrometer. Using the Mascot search algorithm and the Flybase database, 138, 185, and 148 glycoproteins from Drosophila that bound to GNA, Nictaba, and RSA, respectively, were identified (Supporting Information Tables S1-S3). Putative N-glycosylation sites were present on 92.0%, 86.5%, and 81.8% of the glycoproteins recognized by GNA, Nictaba, and RSA, respectively, indicating that at least 8.0%, 13.5%, and 18.2% of the glycoproteins were captured exclusively through interaction with O-glycans on the GNA-, Nictaba-, and RSA-column, respectively (Table 1). Since the available data from Drosophila embryos, larvae, adults, and cultured cells indicated that especially high-mannose and pauci-mannose N-glycans are dominant,18,39 it was expected that GNA should capture the majority of N-glycosylated glycoproteins. However, comparison of the different glycoproteomes obtained after selective enrichment on the different lectin columns revealed that many proteins were only recognized by Nictaba and RSA (and not by GNA), indicating that complex N-glycans and
Figure 2. Venn diagram of the identified Drosophila proteins captured by GNA (n ) 138), Nictaba (n ) 185), or RSA (n ) 148) illustrating the number of lectin-specific glycoproteins or glycosylated proteins recognized by more than one lectin. Journal of Proteome Research • Vol. 9, No. 6, 2010 3237
research articles O-glycans were more abundant than expected. Identification of the different glycoproteins indicated that 69, 73, and 71 of the proteins were unique for GNA, Nictaba, and RSA, respectively (Figure 2). In addition, many glycoproteins were identified that were trapped by more than one lectin column. For example, 22 proteins were captured by GNA, Nictaba, as well as RSA (Figure 2), suggesting that multiple glycan structures are present on these proteins. Taking into account the results of the glycan array analyses of the three different lectins,25,26 it can be expected that GNA selects for high-mannose glycosylated proteins, whereas Nictaba targets both glycoproteins carrying high-mannose as well as more complex glycans. Since both GNA and Nictaba will target high-mannose N-glycans, it is not surprising that 63 common proteins are retrieved from both lectin columns (Figure 2). Glycan array analysis for RSA lectin revealed specificity toward N-glycans with terminal galactose sugars along with the mucin-type O-glycans. A comparative analysis of the proteins retained on the RSA and Nictaba columns yielded 71 glycoproteins that were recognized by both lectins (Figure 2). Only 6 fly proteins were found to bind to both GNA and RSA (Figure 2). To study the relative abundances of the identified proteins in the different protein mixtures, the individual exponential modified protein abundance index (emPAI) and an abundance index based on spectral counting were calculated (Supporting Information Tables S1-S3). Although independently calculated, both abundance indexes were correlated with each other for the majority of the glycoproteins. Interestingly, the presence of a higher number of putative N-glycosylation sites is not correlated with a higher abundance index. Another interesting observation is the occurrence of several glycoproteins with relatively high abundance indexes like arginine kinase, actin 5C, or aconitase that were captured by both Nictaba and RSA, while these proteins were not identified in the protein mixture retained on the GNA column. The ATP synthase β-subunit is an example of a protein present in the mixtures derived from all three lectin columns with a relatively high emPAI in the glycoproteome captured by especially RSA, but also after enrichment by GNA and Nictaba affinity chromatography. These results offer a remarkably rich source of information that will allow more detailed questions to be asked about the specific roles of glycans in Drosophila. 3.2. Functional Distribution of Glycosylated Proteins. Using the PANTHER database, the putatively glycosylated proteins resolved from Drosophila were subdivided into different functional protein families according to their involvement in a specific biological process or PANTHER protein class (Supporting information Figures S2 and S3). Hereby, it was clear that the captured glycoproteins for all three lectins are involved in a broad range of biological processes such as metabolism, cell communication, developmental processes, immune system, cell adhesion, cell cycle, or transport (Supporting information Figure S2). However, differences were detected in the relative amount of glycoproteins associated with a certain biological process between glycoprotein fractions obtained from different lectin columns. For example, the group of glycoproteins with a metabolic function accounted up to 26.7%, 34.8%, and 40.5% in GNA, Nictaba, and RSA captured proteins, respectively. Glycoproteins important for cell adhesion were more abundant in the glycoprotein fraction retained on a GNA column compared to the glycoproteins bound on Nictaba while absent in the RSA binding glycoproteins. 3238
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Vandenborre et al. Next to classifying the glycoproteins into subfamilies based on their involvement in a biological process, the PANTHER classification database was also used to assign the proteins into groups according to their known or predicted molecular function (Supporting information Figure S3). For the GNAbinding proteins, the largest groups were hydrolases (23.8%), proteases (13.4%), proteins associated with nucleic acid binding (8.5%), receptor proteins (6.7%), defense/immunity proteins (6.1%), proteins important for cell adhesion (5.5%), or signaling (5.5%). Proteins with other molecular functions represented less than 5% of the total protein. The Nictaba-binding glycoproteins were classified as nucleic acid binding (14.1%), hydrolases (14.1%), oxidoreductases (12.2%), transferases (9.8%), cytoskeletal proteins (5.4%), or enzyme modulators (5.4%). Classification of the RSA binding proteins according to molecular function revealed nucleic acid binding proteins (14.7%), transferases (11.5%), hydrolases (10.9%), oxidoreductases (9.6%), chaperones (8.3%), and enzyme modulators (5.8%) as the major categories (>5%). Interestingly, hydrolases, proteases, and receptor proteins were more abundant in the GNA binding proteins compared to the glycoproteins retained on Nictaba and RSA. In contrast, oxidoreductases and transferases are more specific for Nictaba and RSA suggesting the presence of especially complex N-glycans with terminal Gal/GalNAc on these enzymes. It is striking that the classification of glycoproteins bound to Nictaba and RSA is very similar. 3.3. Enrichment Analysis for Lectin Captured Glycoproteins. For a detailed study of the different glycoproteomes, the DAVID resources were used to highlight the most overrepresented (enriched) GO annotation terms (>2-fold enrichment compared to a Drosophila background; p < 0.05; FDR < 0.05) for biological processes in the different protein lists. This analysis resulted in only three general gene ontology terms associated with cell adhesion for the GNA-binding glycoproteins (Table 2). When enrichment analysis searches based on ontology terms related to molecular function for the GNA binding glycoproteins was complete, galactose-specific C-type lectin activity and aminopeptidase activity were enriched most (>15-fold) (Table 3). Both molecular activities are associated with membrane proteins which is also in agreement with the enriched terms for biological processes. Also hydrolase activity and ribosomal proteins are annotation terms that are overrepresented (>5-fold) in the protein fraction retained on the GNA column. For the Nictaba bound glycoproteins, 28 ontology term entries were identified as significantly enriched biological processes (p < 0.05; FDR < 0.05) (Table 2). Pyruvate metabolism, acetyl-CoA metabolism, tricarboxylic acid cycle, and glycolysis are >10-fold enriched compared to the general Drosophila background. Moreover, almost all enriched ontology terms belong to the general cellular respiration activity. When the same analyses were performed to search for enriched annotations for molecular function in the glycoprotein fraction from the Nictaba column, enzymes with oxidoreductase activity, coenzyme binding, hydrolase activity, and pyrophosphatase activity were found (Table 3) which is in agreement with the annotation terms found for biological processes (Table 2). Also ribosomal proteins were found to be enriched (>5-fold). When the same enrichment analysis for biological processes was performed on the list of proteins that bound to RSA, 40 term entries were significantly enriched (p < 0.05; FDR < 0.05) (Table 2). Similar to Nictaba, most of the annotation terms were associated with cellular respiration. The enrichment analysis
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Table 2. Enrichment Analysis Using DAVID for the Annotation Terms Associated with Biological Processes for GNA-, Nictaba-, and RSA-Captured Glycoproteins term
fold enrichmenta
Glycoproteome with GNA-Specific Glycans 1 2 3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 a
cell-cell adhesion cell adhesion biological adhesion
8.5 4.3 4.1
Glycoproteome with Nictaba-Specific Glycansc pyruvate metabolic process acetyl-CoA metabolic process acetyl-CoA catabolic process aerobic respiration cellular respiration tricarboxylic acid cycle coenzyme catabolic process cofactor catabolic process glycolysis alcohol catabolic process glucose catabolic process hexose catabolic process monosaccharide catabolic process glucose metabolic process hexose metabolic process monosaccharide metabolic process coenzyme metabolic process cellular carbohydrate metabolic process cofactor metabolic process monocarboxylic acid metabolic process cellular catabolic process catabolic process carbohydrate metabolic process generation of precursor metabolites and energy organic acid metabolic process carboxylic acid metabolic process biosynthetic process cellular biosynthetic process Glycoproteome with RSA-Specific Glycansc pyruvate metabolic process glycolysis acetyl-CoA metabolic process cellular respiration tricarboxylic acid cycle aerobic respiration acetyl-CoA catabolic process translational elongation coenzyme catabolic process alcohol catabolic process cofactor catabolic process response to unfolded protein response to protein stimulus hexose catabolic process monosaccharide catabolic process glucose catabolic process glucose metabolic process cellular carbohydrate catabolic process response to heat response to temperature stimulus carbohydrate catabolic process hexose metabolic process monosaccharide metabolic process protein folding cellular catabolic process cellular carbohydrate metabolic process catabolic process cellular macromolecule catabolic process alcohol metabolic process coenzyme metabolic process response to abiotic stimulus cofactor metabolic process macromolecule catabolic process carbohydrate metabolic process response to stress carboxylic acid metabolic process organic acid metabolic process generation of precursor metabolites and energy cellular biosynthetic process biosynthetic process
Enrichment factor (fold change >2; FDR < 0.05).
b
p-valueb
c
4.50 × 10-4 1.40 × 10-2 1.50 × 10-2
20.8 17.7 17.3 17.3 17.3 17.3 16.5 16.1 10.1 9.5 9.0 9.0 9.0 8.7 6.8 6.4 6.0 5.5 5.5 5.4 4.8 4.4 4.1 3.7 3.7 3.7 2.1 2.1
8.00 5.50 3.50 3.50 3.50 3.50 3.00 3.70 1.30 1.50 8.10 8.10 8.10 8.50 2.20 3.40 7.40 2.80 2.90 1.40 3.00 7.00 4.30 7.50 2.20 2.20 2.60 5.20
× × × × × × × × × × × × × × × × × × × × × × × × × × × ×
10-4 10-10 10-9 10-9 10-9 10-9 10-9 10-9 10-3 10-4 10-4 10-4 10-4 10-5 10-4 10-4 10-9 10-10 10-8 10-3 10-9 10-9 10-10 10-8 10-5 10-5 10-4 10-4
26.5 21.0 21.0 20.4 20.4 20.4 20.4 19.9 19.4 19.3 18.9 18.5 18.5 17.8 17.8 17.8 15.0 13.2 12.7 11.4 11.0 10.8 10.2 7.8 7.3 6.7 6.5 6.5 6.5 6.3 6.1 5.8 5.3 4.4 4.0 3.7 3.7 3.4 2.2 2.1
1.80 1.60 1.60 1.80 1.80 1.80 1.80 7.40 2.60 1.20 3.30 1.50 1.50 2.30 2.30 2.30 2.00 4.60 8.00 1.90 4.40 1.20 2.40 5.40 6.00 1.00 1.50 7.30 7.30 1.30 1.40 4.20 1.20 1.60 3.40 2.40 2.40 7.90 6.60 2.10
× × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × × ×
10-4 10-10 10-10 10-9 10-9 10-9 10-9 10-4 10-9 10-12 10-9 10-4 10-4 10-10 10-10 10-10 10-10 10-9 10-6 10-5 10-8 10-8 10-8 10-8 10-17 10-12 10-15 10-7 10-7 10-7 10-5 10-7 10-5 10-9 10-4 10-4 10-4 10-5 10-4 10-3
Benjamini p-value. c Enrichment analysis for annotation terms using the DAVID resources.
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Table 3. Enrichment analysis using DAVID for the annotation terms associated with molecular function for GNA-, Nictaba- and RSA-captured glycoproteins fold enrichmenta
term
p-valueb
c
1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 2 3 4 5 6 7 8 9 10 11 12 13 a
Glycoproteome with GNA-Specific Glycans galactose binding alanine aminopeptidase activity membrane alanyl aminopeptidase activity aminopeptidase activity exopeptidase activity hydrolase activity, acting on glycosyl bonds structural constituent of ribosome structural molecule activity peptidase activity hydrolase activity
Glycoproteome with Nictaba-Specific Glycansc oxidoreductase activity, acting on the aldehyde or oxo group of donors oxidoreductase activity, acting on the CH-OH group of donors, NAD or NADP as acceptor cofactor binding coenzyme binding oxidoreductase activity, acting on CH-OH group of donors structural constituent of ribosome structural molecule activity nucleoside-triphosphatase activity pyrophosphatase activity hydrolase activity, acting on acid anhydrides, in phosphorus-containing anhydrides hydrolase activity, acting on acid anhydrides oxidoreductase activity Purine nucleotide binding nucleotide binding Purine ribonucleotide binding ribonucleotide binding Glycoproteome with RSA-Specific Glycansc oxidoreductase activity, acting on the aldehyde or oxo group of donors unfolded protein binding structural constituent of ribosome structural molecule activity nucleoside-triphosphatase activity pyrophosphatase activity hydrolase activity, acting on acid anhydrides, in phosphorus-containing anhydrides hydrolase activity, acting on acid anhydrides oxidoreductase activity purine nucleotide binding purine ribonucleotide binding ribonucleotide binding nucleotide binding
Enrichment factor (fold change >2; FDR < 0.05).
b
10-3 10-3 10-3 10-3 10-5 10-3 10-5 10-5 10-4 10-5
3.30 5.90 5.90 5.60 6.00 5.30 7.50 2.80 6.00 7.00
16.1
6.70 × 10-4
9.7
1.90 × 10-5
8.1 8.1 6.4 5.1 3.4 2.9 2.8 2.8
1.10 7.20 4.80 1.50 1.60 7.50 9.40 1.20
× × × × × × × ×
10-5 10-5 10-4 10-4 10-6 10-4 10-4 10-3
2.8 2.6 2.5 2.3 2.3 2.3
1.20 2.00 6.70 5.90 5.80 5.80
× × × × × ×
10-3 10-4 10-5 10-5 10-4 10-4
19.9
3.00 × 10-4
9.2 6.6 4.3 3.3 3.2 3.2
3.40 3.10 1.60 3.80 4.50 5.40
× × × × × ×
10-3 10-6 10-9 10-4 10-4 10-4
3.2 2.8 2.7 2.6 2.6 2.3
5.10 5.50 9.00 2.20 2.20 1.00
× × × × × ×
10-4 10-4 10-5 10-4 10-4 10-3
Benjamini p-value. c Enrichment analysis for annotation terms using the DAVID resources.
for molecular function among the RSA-binding proteins also revealed annotation terms similar to those for glycoproteins binding to Nictaba (Table 3). 3.4. Interesting Drosophila Glycoproteins. One interesting example of a glycoprotein identified in the present study is the retinoid- and fatty acid-binding glycoprotein (RFABG), a major component of the retinal extracellular matrix, which binds exogenous retinol and palmitic acid, and exhibits endogenous binding of both fatty acids and retinoids.40 In this report, RFABG was shown to be the second most abundant protein in the RSA captured glycoproteins (using both the emPAI index and the abundance index based on spectral counting). In contrast, RFABG was more than 15 times less abundant after running on a Nictaba column while it was not captured at all 3240
× × × × × × × × × ×
34.7 16.7 16.7 12.4 9.3 7.7 6.7 3.9 3.1 2.2
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by GNA. These results suggest the presence of especially O-glycans or more complex N-glycans with terminal GalNAc residues, while the high-mannose N-glycans are absent. Because 18 putative N-glycosylation sites were found in the protein sequence, probably the complex N-glycans are the most prominent carbohydrate modifications on RFABG. Unfortunately, no data are available in the literature to verify our observation concerning the glycosylation pattern of RFABG. The N-glycan profile for the glycoprotein chaoptin was recently studied in detail.41 This photoreceptor protein is a member of the leucine-rich repeat family. Although highmannose type glycans, pauci-mannose, and complex type glycans were detected on the chaoptin polypeptide, the highmannose and pauci-mannose were the most abundant N-
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Glycosylation Signatures in Drosophila glycan-types on this glycoprotein which explains its high abundant ranking in the glycoproteins captured by GNA. As expected, chaoptin was also captured by Nictaba, but its abundance was 2.3 times less than on the GNA-column. In contrast, no chaoptin was bound to RSA, supporting the recently published N-glycan profile data on chaoptin.41 Laminin is a large heterotrimeric glycoprotein which is a prominent component of the basement membrane and is involved in important biological roles, including tissue development and cell differentiation, survival, adhesion, and migration. Laminin is a heavily glycosylated molecule and it has been reported that between 13% and 30% of the total molecular weight of laminin is due to N-linked glycans.42 In our study, two subunits of laminin were captured by both GNA and Nictaba, whereas these glycoproteins were not present among the RSA binding proteins. Both lamininA and B were present among the 10 most abundant GNA-binding proteins. These observations enable us to predict that the laminin subunits are mainly decorated with high-mannose N-glycan structures. Genetic studies have shown that null mutations in the Drosophila laminin R3,5 chain lead to embryonic lethality with visible defects in mesodermally derived tissues leading to dissociated cell groups in the various organs.43 In the light of these findings, it is interesting to mention an earlier hypothesis about the possible role of lectin-type interaction between heterophilic cell adhesion molecules that involve oligomannosidic glycans on these molecules.44 The protein called NUCB1 was one of the most abundant proteins among the RSA-binding glycoproteins, while this protein was not captured by the other lectins. Moreover, no putative N-glycosylation site was found in the NUCB1 polypeptide (Supporting Information Table S3), suggesting that binding to RSA is the result of interactions with putative O-glycan structures on NUCB1. NUCB1 is associated with the Golgi apparatus, but its exact role remains unknown in Drosophila.45 In agreement with its RSA specific interaction, it was shown that Drosophila generates the mucin-type T-antigen (Galβ13GalNAcR-Ser/Thr) as predominant O-glycan structure on glycoproteins.21 Mutations in one member of the enzymes responsible for mucin-type O-glycosylation (pgant35A) was even shown to abrogate enzymatic activity with death occurring throughout development,19 illustrating the crucial role for this type of O-glycans during development of Drosophila.
4. Conclusion In conclusion, the data presented in this paper illustrate a methodology to select for specific glycoproteins based on the use of several lectins with different carbohydrate specificities. Comparing the glycoproteins captured by GNA, Nictaba, and RSA allowed assigning glycan profiles of the Drosophila proteins to high-mannose or pauci-mannose N-glycans, complex Nglycans, or O-glycosylated proteins. Moreover, the results presented here demonstrate that Drosophila is capable of expressing extended hybrid and complex N-linked glycans, in addition to the expected family of abundant high-mannose and paucimannose oligosaccharides. A recent publication corroborates the existence of complex glycans in Drosophila.39 Furthermore, it was demonstrated that a specific glycosylation signature can be associated with a functionally related group of glycoproteins in Drosophila, both in terms of biological process and molecular function. However, it is worth emphasizing that, although the large number of identified glycoproteins from Drosophila is unprecedented, this is not an exhaus-
tive database of glycosylated proteins expressed in Drosophila. Low-abundance glycopeptides might have fallen below the detection threshold of the MS or generated MS/MS fragmentation patterns of insufficient robustness, and hence could not be identified. In addition, although GNA, Nictaba, and RSA are perhaps among the most suitable lectins to recover the largest proportion of N- and O-glycosylated proteins, there will be other glycoproteins with glycan structures that do not bind efficiently to any of the lectins utilized in our study.
Acknowledgment. This research was supported by the Research Council of Ghent University (project BOF10/GOA/ 003), the Fund for Scientific Research-Flanders (3G016306, G. Smagghe, and E. J. M. Van Damme). B.G. is a Postdoctoral Research Fellow of the Fund for Scientific Research - Flanders (Belgium). The UGent/VIB lab acknowledges support by research grants from the Fund for Scientific Research - Flanders (Belgium) (project G015605, G007706, G004207), the Concerted Research Actions from the Ghent University and the Inter University Attraction Poles (project BOF07/GOA/012 and IUAP06). We also want to thank the Consortium for Functional Glycomics for glycan array analyses. Supporting Information Available: The cluster parameters, emPAI calculation, and spectral count score calculations. Table S1: annotation of the identified proteins bound to the GNA column. List is characterized by accession number, two abundance indexes (emPAI and spectral count) and the number of putative N-glycosylation sites. Table S2: annotation of the identified proteins bound to the Nictaba column. List is characterized by accession number, two abundance indexes (emPAI and spectral count) and the number of putative N-glycosylation sites. Table S3: annotation of the identified proteins bound to the RSA column. List is characterized by accession number, two abundance indexes (emPAI and spectral count) and the number of putative N-glycosylation sites. Figure S1: Coomassie stained SDS-PAGE analysis of eluate and flow through after GNA, Nictaba, and RSA affinity chromatography. Lanes 1 and 9 were loaded with a protein marker (Pageruler Prestained Protein Ladder, Fermentas), lane 2 was loaded with the Drosophila extract, lanes 3-5 with the peak fraction of the eluate after GNA, Nictaba, and RSA chromatography, respectively, and lanes 6-8 with the flow through after GNA, Nictaba, and RSA chromatography, respectively. Figure S2: functional classification according to biological process of the glycoproteins of Drosophila captured by GNA (A), Nictaba (B), or RSA (C) using PANTHER. The numbers on the figure refer to the percentage of identified proteins within each category. Figure S3: functional classification of Drosophila glycoproteins according to PANTHER. Proteins were captured by GNA (A), Nictaba (B), or RSA (C). The numbers on the figure refer to the percentage of identified proteins within each category. This material is available free of charge via the Internet at http:// pubs.acs.org. References (1) Helenius, A.; Aebi, M. Intracellular functions of N-linked glycans. Science 2001, 291, 2364–2369. (2) Dell, A.; Morris, H. R.; Easton, R. L.; Patankar, M.; Clark, G. F. The glycobiology of gametes and fertilisation. Biochim. Biophys. Acta 1999, 1473, 196–205. (3) Hooper, L. V.; Gordon, J. I. Glycans as legislators of host-microbial interactions: spanning the spectrum from symbiosis to pathogenicity. Glycobiology 2001, 11, 1–10.
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PR1001753
