BAD-Lectins: Boronic Acid-Decorated Lectins with Enhanced Binding

Jul 29, 2013 - The weak and variable binding affinities exhibited by lectin–carbohydrate interactions have often compromised the practical utility o...
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BAD-Lectins: Boronic Acid-Decorated Lectins with Enhanced Binding Affinity for the Selective Enrichment of Glycoproteins Ying-Wei Lu,† Chih-Wei Chien,† Po-Chiao Lin,‡ Li-De Huang,† Chang-Yang Chen,§ Sz-Wei Wu,∥ Chia-Li Han,⊥ Kay-Hooi Khoo,∥ Chun-Cheng Lin,*,† and Yu-Ju Chen*,⊥,¶ †

Department of Chemistry, National Tsing Hua University, Hsinchu 300-71, Taiwan Department of Chemistry, National Sun Yat-sen University, Kaohsiung 804, Taiwan § Department of Chemistry, National Taiwan Normal University, Taipei 106, Taiwan ∥ Institute of Biological Chemistry, Academia Sinica, Taipei 115, Taiwan ⊥ Institute of Chemistry, Academia Sinica, Taipei 115, Taiwan ¶ Department of Chemistry, National Taiwan University, Taipei 106, Taiwan ‡

S Supporting Information *

ABSTRACT: The weak and variable binding affinities exhibited by lectin−carbohydrate interactions have often compromised the practical utility of lectin in capturing glycoproteins for glycoproteomic applications. We report here the development and applications of a new type of hybrid biomaterial, namely a boronic acid-decorated lectin (BAD-lectin), for efficient bifunctional glycoprotein labeling and enrichment. Our binding studies showed an enhanced affinity by BAD-lectin, likely to be mediated via the formation of boronate ester linkages between the lectin and glycan subsequent to the initial recognition process and thus preserving its glycan-specificity. Moreover, when attached to magnetic nanoparticles (BAD-lectin@MNPs), 2 to 60-fold improvement on detection sensitivity and enrichment efficiency for specific glycoproteins was observed over the independent use of either lectin or BA. Tested at the level of whole cell lysates for glycoproteomic applications, three different types of BADlectin@MNPs exhibited excellent specificities with only 6% overlapping among the 295 N-linked glycopeptides identified. As many as 236 N-linked glycopeptides (80%) were uniquely identified by one of the BAD-lectin@MNPs. These results indicated that the enhanced glycan-selective recognition and binding affinity of BAD-lectin@MNPs will facilitate a complementary identification of the under-explored glycoproteome.

P

HCC, even in the early stage,9,10 and this discovery highlights the abundant opportunities for identifying new biomarkers if distinct glycoforms of proteins can be effectively differentiated. However, to fully exploit the potential clinical applications of glycoproteins in diagnosis and prognosis, we must first develop more robust tools with the specificity required for the identification of undiscovered disease-associated glycoforms and the methods for their enrichment and detection in human sera. In the past decade, many strategies have been developed to improve the specificity of labeling and recognition or the subsequent isolation of glycoproteins and glycoforms. These strategies include affinity column chromatography, glycosyltransferase-based modification,11 oxidative cleavage labeling, and metabolic uptake strategies.12 Among these methods, the

rotein glycosylation is a ubiquitous post-translational modification (PTM) that plays a crucial role in the quality control and regulation of protein folding, stability, functional efficiency, and trafficking.1,2 Consequently, glycosylation affects diverse biological processes, such as gene expression, cell adhesion, signal transduction, and immune responses.3 Indeed, alterations in the level and in the types of glycoproteins expressed during various cellular stages serve as informative biomarkers for the detection of cancers,4,5 diabetes mellitus,6 and rheumatoid arthritis.7 Additionally, many FDA approved biomarkers for diagnosis, monitoring, or therapy selection are glycoproteins.8 For example, α-fetoprotein (AFP) is the most widely used clinical marker for hepatocellular carcinoma (HCC) staging. However, AFP is not overexpressed in HCC alone: elevated serum AFP can be also detected in individuals with pregnancy, hepatitis, and liver cirrhosis, illustrating the need for more specific biomarkers. Several studies have since shown that AFP glycoforms bearing core fucosylated biantennary N-glycans are indeed very specific markers for © 2013 American Chemical Society

Received: May 20, 2013 Accepted: July 29, 2013 Published: July 29, 2013 8268

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Figure 1. Schematic illustration of the dual binding of a BAD-lectin to a glycoprotein. (i) A BAD-lectin. (ii) A glycoprotein captured by the lectin by noncovalent glycan-specific recognition. (iii) A glycoprotein captured by both lectin and BA; the latter mediates boronate ester to form a stable covalent lectin-glycoprotein complex. (iv) A glycoprotein captured by a BA ligand alone.

compounds to form stable boronate compounds under basic aqueous conditions.25 BAs have long been exploited as glycan probes in numerous applications, including the isolation and recognition of glycoproteins,26−28 and the use of fluorescencebased chemosensors for toxic heavy metal sensing,29 However, unlike lectins, which recognize specific carbohydrates, BAs do not possess affinity selectivity for interactions with different glycoforms. In this study, we fabricated a hybrid biomaterial for bifunctional glycoprotein labeling and enrichment. The material is a boronic acid-decorated lectin (BAD-lectin) (Figure 1), which exploits the initial lectin carbohydrate recognition process (i → ii) to facilitate the formation of a boronate ester mediated stable covalent lectin-glycoprotein complex (ii → iii), where the equilibrium between complexes (iii and iv) represents the association/disassociation of the lectin from the glycoprotein. As a proof of concept, we utilized three lectins [concanavalin A (ConA), Aleuria aurantia lectin (AAL), and Sambucus nigra lectin (SNA)], which are known to recognize the high-mannose core of N-glycans, fucosylated glycoproteins, and glycoproteins containing sialic acid linkages (especially (α2,6) linkages),30 respectively, as model systems to detect distinct types of target glycoproteins. The application of BADlectin for glycoprotein enrichment and glycoproteomics study was demonstrated on the fabrication of BAD-lectin conjugated magnetic nanoparticle (BAD-lectin@MNP). We anticipate that the bifunctional BAD-lectin concept will offer advantages over the independent use of lectin for specific N-glycan recognition and the use of boronic acid for the formation of boronate esters for glycoproteomic applications.

affinity-based separation approaches (such as those using carbohydrate-binding proteins (lectins)) possess selectivity but are restricted by their dependence on noncovalent interactions in addition to the relatively weak binding affinities of lectins for the surface glycans of glycoproteins.13,14 Chemical glycan-modification methods are usually performed under harsh conditions and therefore alter the native structures of the glycoproteins, potentially resulting in the loss of glycan recognition and glycoprotein bioactivity. Although glycosyltransferase-mediated modification and metabolic oligosaccharide engineering have been successfully used to identify glycoproteins, this method may alter the glycan sequence of the native form and cannot be applied to clinical human specimen analysis. To circumvent the aforementioned limitations, a new affinity method is required for glycoprotein detection; this method must offer stable covalent conjugation while preserving the protein structure and activity. Lectins are widely utilized as affinity probes for the efficient detection of glycan in complex biological fluids by virtue of their selective carbohydrate−protein interactions.15,16 Additionally, lectin-based glycoprotein enrichment combining with mass spectrometric identification has been widely adapted for glycoproteomic profiling to identify disease-associated alterations of glycoprotein as potential biomarker.17,18 For example, Aleuria aurantia lectin (AAL) and Lens culinaris agglutinin (LCA) provide a robust means for targeting aberrant fucosylation.19 Sambucus nigra agglutinin (SNA) has been used to detect the aberrant sialylation of cancer cells, a modification that is characteristic of invasiveness and metastatic potential.20,21 However, these lectins only provide weak and variable affinities for glycoproteins (millimolar to micromolar),22 which may result in sample loss and which usually requires the use of a specially optimized protocol to enhance the binding affinity.23,24 Alternatively, boronic acids (BAs), which are ligands with chemical affinity for carbohydrates, are known to react covalently but reversibly with cis-diol

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EXPERIMENTAL SECTION

Marterials and Reagents. Concanavalin A (ConA), peroxidase from horseradish (HRP), albumin bovine serum (BSA), myoglobin equine heart (Myo), ribonuclease B from bovine pancreas (RNB), and lactoferrin (LF) were purchased 8269

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from Sigma-Aldrich (St. Louis, MO, U.S.A.). Aleuria aurantia lectin (AAL,), and Sambucus nigra lectin (SNA) were purchased from Vector Laboratories (CA, U.S.A.). 3-Aminophenyl boronic acid monohydrate (APBA) was purchased from Acros (NJ, U.S.A.). Bis[sulfosuccinimidyl]suberate (BS3), BCA protein assay kit were obtained from Pierce (Rockford, IL, U.S.A.). All chemicals were obtained at the highest available grade from commercial supplier and were used as received. Preparation of Boronic Acid Decorated Lectins (BADlectins). As shown in Scheme S-1, Supporting Information, 1 mg of lectin was suspended in 140 μL of sodium bicarbonate buffer (NaHCO 3 , 50 mM, pH 8.5) and 140 μL of bis[sulfosuccinimidyl]suberate (BS3, 25 mM in sodium bicarbonate buffer) for 1 h by gently rotating at 4 °C. The excess BS3 was removed by using NAP-5 column to give OSuactivated lectin (OSu-lectin). Five hundred microliters of 3amino-phenylboronic acid (APBA) solution (100 mM in sodium bicarbonate buffer) was added to 500 μL of the activated lectin solution (2 μg/μL in sodium bicarbonate buffer) and the resulting mixture was gently rotating at 4 °C for 1 h. Then, ethanolamine (10.2 μL, 2 M in deionized H2O) was added to the reaction mixture followed by rotating at 4 °C for 12 h. After dialysis, the resulting solution was concentrated using a centrifugal filter device (Vivaspin, GE Healthcare) to obtain BAD-lectin which was divided into aliquots and stored at 4 °C. Fabrication of BAD-Lectin Conjugated Magnetic Nanoparticles (BAD-lectin@MNPs). The syntheses of the core magnetic nanoparticles (MNP) and their protein immobilization as antibody-conjugated MNP (Ab@MNP) were performed by following previously reported procedures.31 As shown in Scheme S-1, Supporting Information, synthesis procedure started from aminated MNPs (NH2@MNP) were followed by reported protocol to yield Lectin@MNP. For further BA-decoration, Lectin@MNP (5 mg) was suspended in sodium bicarbonate buffer (140 μL) and reacted with BS3 (25 mM in sodium bicarbonate buffer, 140 μL) for 1 h by gently rotating at 4 °C. The resulting activated Lectin@MNPs were washed with sodium bicarbonate buffer (50 mM, 500 μL) for three times to remove excess amount of BS3. APBA solution (100 μL) was incubated with the above black particles and reacted at 4 °C for 1 h. Then, ethanolamine (100 mM in deionized H2O, 100 μL) was added to the reaction mixture followed by for 12 h. After magnetic separation, the black nanoparticles were washed with sodium bicarbonate buffer for five times to give BAD-lectin@MNP. Analysis of Binding Affinity by Surface Plasmon Resonance (SPR). The affinities between lectins and carbohydrates were measured by using a BIAcore T200 instrument (GE Healthcare). The senor chip Au (GE Healthcare) was modified with carbohydrate derivative ligands by injecting a mixture contained 20% carbohydrate derivative ligands and 80% the corresponding thiolylated matrices in deionized water for 15 min (1 μL/min) for four times. Each binding experiment was performed at 25 °C with a constant flow (30 μL/min) of HBS (20 mM HEPES, 90 mM NaCl, pH 7.2). Samples of lectins or BAD-lectins, prepared in HBS containing 1 mM of MnCl2 and CaCl2, were injected across the immobilized biosensor surface during the association phase and dissociation was affected by injecting HBS only. The surface was regenerated by injection of 120 μL of phosphoric acid (H3PO4, 0.1 M) and a final wash with 75 μL of HBS. A set of SPR response curves were obtained after different concen-

trations of sample solution were applied. Kinetic measurements were carried out using standard procedures. All the response data were analyzed with BIAevaluation software, and the best fitting was obtained using a 1:1 binding model. The sensorgram was fitted globally over the association and dissociation phases. Equilibrium dissociation constants (binding affinity) were calculated from the rate constants (KD = koff/kon). Glycoprotein Enrichment by BAD-lectin@MNPs. Glycoproteins (0.001, 0.005, 0.05, 0.5, and 2.5 μg/μL in 50 mM ammonium bicarbonate, pH 8.7) were incubated with 60 μg of MNPs (BAD-ConA@MNP, BAD-AAL@MNP, and BADSNA@MNP) under vortex for 1 h. The MNPs were separated using a magnet and then MNPs were washed with 500 μL of incubation buffer for three times. The captured glycoproteins were released from MNPs by using a solution containing 0.1 M sorbitol and 0.2 M corresponding carbohydrate (methyl-α-Dmannoside, fucose, or sialic acid in 50 mM ammonium bicarbonate, pH 8.7). The eluent was dried under vacuum and reconstituted in 1% (v/v) trifluoroacetic acid (30 μL) in deionized H2O and then was desalted with C4 ZipTip (Millipore, Billerica, MA, U.S.A.). The desalted eluent (0.5 μL) was mixed with matrix solution (0.5 μL, 10 mg/mL αcyano-4-hydroxycinnamic acid in 50% acetonitrile and 0.1% trifluoroacetic acid in deionized H2O and then was spotted onto stainless steel plate followed by air-dried before subsequent MALDI-TOF MS analysis. Data were processed and analyzed by Data Explorer software. Glycoproteomic Analysis in HeLa Cell by Using BADlectin@MNPs and LC-MS/MS. Purified membrane proteins from HeLa cell were digested by trypsin.32 The resulting tryptic peptides (100 μg) were incubated with 200 μg of BAD-ConA@ MNP, BAD-AAL@MNP, and BAD-SNA@MNP, respectively, in 300 μL of ammonium bicarbonate buffer (50 mM, pH 8.7) under vortex for 1 h. The MNPs were collected by using a magnet and washed with incubation buffer containing 30% acetonitrile for three times. The captured glycopeptides were released from MNPs with a solution containing 50% acetonitrile and 0.1% (v/v) trifluoroacetic acid in deionized H2O. The eluent was divided into two parts and dried under vacuum. One part of intact glycopeptides was reconstituted in 30 μL of 50 mM ammonium bicarbonate buffer and PNGase F was applied to remove the carbohydrate moiety. The glycopeptides and deglycopeptides were desalted by C18 ZipTip (Millipore, Billerica, MA, U.S.A.) for subsequent analysis. For LC-MS/MS analysis under precursor ion discovery (PID) mode,33 the intact glycopeptides were analyzed by a SYNAPT G2 HDMS mass spectrometer (Waters, U.K.) coupled with a nanoACQUITY UPLC System (Waters). The LC mobile phase system consists of water with 0.1% formic acid (buffer A) and acetonitrile with 0.1% formic acid (buffer B). In the PID mode, alternate low (6 eV) and ramping high energy (25−45 eV) MS survey scans were employed. When glycan-specific oxonium ion fragments, m/z 204.08 (HexNAc+) and m/z 366.13 (HexHexNAc+) were detected at the highenergy survey scans, the three most intense ions observed in the corresponding low-energy survey scans were triggered for their MS/MS acquisition with 2 scans in maximum. If the oxonium ions were not monitored in MS/MS, the acquisition was terminated after a single scan and switched to next target. For LC-MS/MS analysis under information-dependent acquisition (IDA) mode, the deglycopeptide samples were analyzed by TripleTOF 5600 system (AB SCIEX, Concord, 8270

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Table 1. Summary of the Estimated Number of BA Molecules on the Three Different Lectins Determined by the Mass Difference between the Free Lectin and the BAD-Lectin as Measured Using MALDI-TOF MSa lectin

MW (Da)

mass difference

estimated number of BAb

exposed lysine

abbreviation of sugar on chip

ConA BAD-ConA AAL BAD-AAL SNA BAD-SNA

25837 27623 33846 36164 43534 44989

1786

7

10

Man-chipc

2318

8

13

Fuc-chipc

1455

5

7

Sia-chipc

KD (M) 8.05 1.43 9.00 4.01 2.12 7.13

× × × × × ×

10−8 10−8 10−8 10−8 10−7 10−8

a c

The KD values for binding to the corresponding carbohydrate SAMs are also shown. bNumber of BA-substituent per lectin unit. BA: boronic acid. Assembled by mannose, fucose, and sialic acid derivatives and their corresponding thiolylated matrices.

Figure 2. SPR sensing of the affinity of the BAD-lectin probe for a carbohydrate-functionalized self-assembled monolayer (SAM). (a) Mannosefunctionalized molecules and the corresponding matrices for immobilization on sensor chips. SPR sensorgrams for the binding of (b) ConA and (c) BAD-ConA at a series of concentrations (from 10 to 1000 nM; bottom to top) to a mannose-functionalized SAM chip.

modification, the decorated ConA exhibited a positive mass shift of 1786 Da with respect to native ConA, revealing the addition of approximately seven boronic acid molecules (MW 276 Da) to the lectin. Likewise, eight and five BA moieties were conjugated to the surfaces of single AAL and SNA units, respectively (Table 1). The BAD-ConA complexes were also further characterized using FTIR, revealing a unique B−O stretch signal at 1342 cm−1 and a phenyl vibration signal at 1573 cm−1 derived from the addition of BA (Figure S-2, Supporting Information).34 Enhanced Lectin−Carbohydrate Affinity by BADLectins. The most critical factor in the design of BAD-lectin probes is whether the addition of BA can enhance the binding affinity of the lectin for its cognate glycan. To compare the binding affinity to their cognate glycan ligand of BAD-lectins with that of the free lectins, surface plasmon resonance (SPR) imaging was used for real-time, label-free analysis of the lectin− carbohydrate interactions.35 For ConA, a mannose derivative (1) and the corresponding thiolylated matrix (2) (Figure 2a) were synthesized and assembled (molar ratio 1/2 = 1:4) onto gold SPR chips.36 The affinities of ConA and BAD-ConA for

ON, Canada) equipped with a nanoACQUITY UPLC (Waters Corporation, Milford, MA, U.S.A.). The samples were loaded and separated by a 15 cm column with 100 μm inner diameter, packed in-house with 3 μm C18 particles (Dr. Maisch, Ammerbuch, Germany). The LC mobile phase system consists of water with 0.1% acetic acid (buffer A) and acetonitrile with 0.1% acetic acid (buffer B). The MS survey scan range was m/z 300−1500 and acquired in 250 ms and the top 10 precursor ions were selected for MS/MS scans performed with 200 ms each.

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RESULTS AND DISCUSSION Characterization of the BAD-Lectin Probe. To precisely characterize the conjugation of BA and the density of BA on the lectin’s surface, the masses of the BAD-lectin and the free lectin were measured using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The molecular weight (MW) differences between the BA-conjugated and free lectins in the mass spectra of ConA versus BAD-ConA, AAL versus BAD-AAL, and SNA versus BAD-SNA are shown in Figure S-1, Supporting Information. After BA 8271

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Figure 3. MALDI-TOF mass spectra of a) the intact RNB glycoprotein, containing its five glycosylated forms with the heterogeneous structure GlcNAc2Man5−9 and b) RNB enrichment by BAD-BSA@MNPs, BA@MNPs, ConA@MNPs, and BAD-ConA@MNPs with 2.5−0.001 μg/μL RNB on glycoprotein capture.

the mannose-functionalized chip were determined using various concentrations (10 nM to 1 μM) of lectin to generate multiple SPR response curves. The association rate constant (ka), determined with a rectangular hyperbolic equation,37 for ConA was 6.37 ± 0.31 × 104 M−1S−1, which is consistent with the previously reported values (2.0 × 10 4 M −1 S −1 ). 38 In comparison, the ka of BAD-ConA was slightly lower (5.25 ± 0.79 × 104 M−1S−1). Additionally, as shown in Figures 2b and 2c, the steeper association curve for ConA in comparison to BAD-ConA is indicative of a faster initial association, whereas the shallower curve in the dissociation phase for BAD-ConA in comparison to ConA is indicative of a slower dissociation event. Subsequently, the equilibrium dissociation constants (KD), calculated from the rate constants (KD = ka/kd)39,40 for ConA and BAD-ConA, which quantitatively measure the binding strengths of ConA and BAD-ConA to the mannose-functionalized surface, were determined to be 80.5 and 14.3 nM, respectively. The comparison indicated that BAD-ConA had a 5.63-fold lower equilibrium dissociation constant than ConA. We hypothesize that the presence of BA on the protein’s surface might have reduced the initial association between the lectin and the glycan. However, once the lectin binds to the glycan, the subsequent formation of the boronate decreases the rate of dissociation, resulting in an enhanced overall affinity. Table 1 shows the KD values of various lectins and BAD-lectins for the corresponding sugar-modified surfaces (details in the Supporting Information, Schemes S-4−7). For other BADlectins, BAD-AAL had a 2.24-fold lower KD (40.1 nM) for fucose-derivatized surfaces in comparison to AAL, and BADSNA had a 2.97-fold lower K D (71.3 nM) for Nacetylneuraminic acid-derivatized surfaces than SNA. The difference in the enhancement of the lectin− carbohydrate affinity using the BAD-lectin probe may be explained by the distance between the carbohydrate binding sites (CBSs) of the lectins and the nearest immobilized boronic acid moiety. Vector NTI 9.0 (Invitrogen, U.S.A.) was used to visualize the tertiary structures of the lectins and the exposed lysine residues, which are the probable positions of boronic acid immobilization (Figure S-3, Supporting Information). The shortest distances between the lectin-binding site and the closest adjacent BA moiety for ConA (pdb code 3QLQ), AAL (pdb code 1IUC), and SNA (pdb code 3CA3) were 11.6, 15.1,

and 15.6 Å, respectively. The analysis of the distance between the CBS and BA indicated that BA was closer to the CBS on the surface of ConA in comparison to the BA-CBS distance on the surfaces of AAL and SNA. Thus, it is conceivable the surface BA moieties on AAL and SNA may not be sufficiently close to form boronates with the captured glycoproteins on the CBSs. Additionally, an increased number of exposed BAs on BAD-lectin could play a role in enhancing the binding affinity on a statistical basis. BAD-lectin@MNPs for Glycoprotein Purification and Identification with Enhanced Sensitivity and Preserved Glycan-specific Recognition. Because of their high surface area-to-volume ratio and magnetic properties, magnetic nanoparticles (MNPs) have emerged as a promising platform for cell imaging,41 recognition,42 and enrichment and for the analysis of biomacromolecules.43 Previously, we developed an immunoassay that integrates a nanoparticle-based affinity probe with a mass spectrometry technique (NBAMS) for the rapid purification, identification, and quantification of target protein(s) from complex biological systems. With the inherent advantages of the accurate measurement of molecule weights and the quantitative analysis by mass spectrometry analysis, we have demonstrated its potential for discriminating among disease-related protein post-translational modifications in clinical settings.44 In an attempt to use BAD-lectin probes to discover the aberrant protein surface glycosylation associated with disease, we fabricated BAD-lectin-functionalized magnetic nanoparticles (BAD-lectin@MNPs) for further glycoproteomic studies. To evaluate the enrichment performance for different glycoproteins, three types of BAD-lectin@MNPs were prepared, including BAD-ConA@MNP, BAD-AAL@MNP, and BAD-SNA@MNP. The protein amounts of BAD-lectin@ MNPs were determined by bicinchoninic acid (BCA) protein assay to be 139, 136, and 90 μg/mg for BAD-ConA@MNP, BAD-AAL@MNP, and BAD-SNA@MNP, respectively. Evidence of the presence of BA on the surface of BAD-lectin@ MNPs was measured by Alizarin Red S (ARS, a catechol dye) (Figure S-4, Supporting Information).45 In the proof-of-concept experiment, ribonuclease B (RNB), a high-mannose (Man) glycoprotein that possesses a single Nlinked glycosylation site with several glycoforms (denoted Man5GlcNAc2 to Man9GlcNAc2),46 was chosen to evaluate the 8272

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MNPs exhibited 5- and 60-fold enhancements in comparison with the use of BA@MNPs and AAL@MNPs, respectively. Relatively reduced enhancement (2-fold) was observed for the detection of LF using the BAD-SNA@MNPs. In comparison to the binding affinity enhanced by BAD-ConA (5.63 fold), BADAAL (2.24 fold), and BAD-SNA (2.97 fold), the extent of improvement on glycoprotein enrichment shows different trend: BAD-AAL > BAD-ConA ≫ BAD-SNA. We speculate that such discrepancy may be attributed to the interaction of BA with hydroxyls of sugar units, which possibly overrides or impedes the lectin-glycan binding. Compared with exposed multiple mannoses or sialic acid required for ConA or SNA, core fucose is an embedded moiety of the glycan to be minimally proceeded in the BA−OH bindings, and thus may be free from impediment of AAL-recognition. Overall, our results demonstrate the superior glycoprotein extraction capacity of the bifunctional BAD-lectin@MNPs in comparison with the conventional BA or lectin affinity extraction. Because BA possesses nonspecific binding activity with cisdiol-containing molecules, such as glycans, an intriguing question regarding the design of the BAD-lectin probe is whether the BA on the lectin will decrease the specificity of the recognition of glycans by the lectin. Thus, the specificity of each type of BAD-lectin@MNP was evaluated using a protein mixture composed of RNB (mannose-rich), HRP (containing fucose), LF (containing sialic acid), and two nonglycoproteins, myoglobin (MYO) and bovine serum albumin (BSA), using a molar ratio of 1:50 (glycoprotein/nonglycoprotein). Without nanoprobe enrichment, the presence of high concentrations of MYO and BSA significantly suppressed the signals for the glycoproteins (Figure 4a). After enrichment using BADConA@MNPs, BAD-AAL@MNPs, and BAD-SNA@MNPs, the mass spectra revealed the specific enrichment of their corresponding glycoproteins, RNB, HRP, and LF, respectively

enrichment performance when using BAD-ConA@MNPs. As shown in Figure 3a, RNB exhibited a characteristic MALDITOF mass spectrum before enrichment, in which five major glycosylated forms from Man5NAc2Glc to Man9NAc2Glc were clearly distinguishable. Following respective extractions using BAD-ConA@MNPs, ConA@MNPs, and BA@MNPs, the purified extracts for each type of MNP exhibited unique glycoprotein profiles in the MALDI mass spectra. When ConA@MNPs were used, two glycoforms of RNB (Man8GlcNAc2, m/z 15373 ± 1 and Man9GlcNAc2, m/z 15532.3 ± 1.9) were present as the two most prominent peaks. The BA@MNPs probe possessed the glycoform profile of RNB, with the most intense peak at m/z 14889 ± 1 (Man5), similar to the natural distribution of RNB glycoforms (Figure 3a in comparison to 3b). BAD-ConA@MNPs displayed synergic effect of the distribution of the glycan profile compared to ConA@MNPs and BA@MNPs. Additionally, with the enrichment step, BAD-ConA@MNPs enhanced the signal intensity 100-fold with preserved good spectral resolution of RNB in comparison with that obtained using the unenriched RNB (Figure S-5, Supporting Information). The sensitivities of the BAD-lectin@MNP nanoprobes for the simultaneous extraction and detection of low-abundance glycoproteins were also evaluated by MALDI-TOF-MS analysis using various concentrations (2.5, 0.5, 0.05, 0.005, and 0.001 μg/μL) of ribonuclease B (RNB, a mannose-rich protein),47 horseradish peroxidase (HRP, containing fucose),48 and lactoferrin (LF, containing sialic acid)49,50 (for the detailed comparison see Figure S-6, Supporting Information). As shown in Figure 3b, the BA@MNPs were able to extract RNB at the lowest concentration (0.05 μg/μL) but were not sufficiently sensitive to enrich RNB at 0.001 μg/μL. The ConA@MNPs provided significant improvement in the detection sensitivity for the RNB signal at 0.005 μg/μL. Considering that the number of immobilized ConA molecules was significantly lower than the number of BA molecules on the MNP surface, the results suggest that the lectin had a superior extraction efficiency compared to that of BA. This observation agreed with the findings of previous reports, which indicated that fewer RNB molecules were isolated by BA in comparison with ConA when using a magnetic bead strategy.51 As expected, the BADConA@MNPs showed the best enrichment of RNB (in comparison with the BA@MNPs and ConA@MNPs). The BAD-ConA@MNPs exhibited a 7-fold improvement over the BA@MNPs at high concentration (2.5 μg/μL), and a 29-fold improvement was obtained at low concentration (0.05 μg/μL). Furthermore, at 0.005 and 0.001 μg/μL, the BAD-ConA@ MNPs exhibited 2- to 3-fold signal enhancement, respectively, in comparison with the ConA@MNPs, and no signal was observed when using the BA@MNPs. To investigate the role of lectin in the BAD-ConA@MNPs, ConA was replaced with bovine serum albumin (BSA) to yield BAD-BSA@MNPs, which were used as a negative control. The BAD-BSA@MNPs presented a glycoform pattern of RNB similar to that observed when using BA@MNPs but with a 1.4to 1.8-fold lower intensity at various concentrations (0.05−2.5 μg/μL, Figure 3b). These results suggest that ConA plays a major role in the enrichment of RNB and may promote the subsequent interaction between BA and the carbohydrate, forming a stable boronate. Superior extraction performances of other BAD-lectin@MNPs were also observed for the other two glycoproteins, LF and HRP (Figure S-6b−c, Supporting Information). The extraction of HRP using BAD-AAL@

Figure 4. Enrichment specificity for various types of glycoproteins by BAD-lectin@MNPs. (a) A pool of standard glycoproteins containing equal moles of RNB, HRP, and LF (glycoproteins), combined with Myo and BSA (nonglycoproteins) at the ratio of 1:50 (glycoprotein/ nonglycoprotein). Enrichment using (b) BAD-ConA@MNPs, (c) BAD-AAL@MNPs, and (d) BAD-SNA@MNPs. 8273

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MS spectra containing the oxonium ions at m/z 204 and 366 were filtered and assumed to be hits of glycopeptide spectra. In addition to these two ubiquitous oxonium ions, Table S-1, Supporting Information, also lists the numbers of the spectra with glycan-specific fragment ions at m/z 163 (Hex+), 512 (HexHexNAcFuc+), and 657 (NeuAcHexHexNAc+) derived from high-mannose type, core-fucosylated, and sialylated glycopeptides, respectively. The spectra for each type of BAD-lectin@MNP (BAD-ConA@MNPs, BAD-AAL@MNPs, and BAD-SNA@MNPs) contained a majority of the expected characteristic fragments derived from the cognate glycans recognized by the lectin; 177 (88%), 34 (85%), and 29 (78%) of the spectra contained the fragment ions at m/z 163.06, 512.2, and 657.23, respectively, among all of the BAD-lectin enriched glycopeptide hits. These glycoproteomic results demonstrate the advantages of specific enrichment using the different BAD-lectin@MNPs. Additionally, the specificity of the BAD-lectin@MNPs, defined as the percentage of glycopeptides containing lectin-specific glycan-epitopes among the total glycopeptides identified by each BAD-lectin@MNP, was also examined. In total, 95%, 72%, and 43% of the spectra contained fragment ions at m/z 163, 512, and 657, respectively, among the total glycopeptide spectra containing the fragment ion at m/z 204, demonstrating the enrichment by each BAD-lectin@ MNP type. In summary, the results for the identified glycopeptides and their spectra containing glycan contents show that the enrichments using the BAD-ConA@MNPs and the BAD-AAL@MNPs were more efficient and specific than enrichment by the BAD-SNA@MNPs, in agreement with the observations that high-mannose and fucosylated glycans are predominant in HeLa cells and that fewer sialylated glycans have been captured by SNA using a lectin-array strategy.56,57 On the basis of topology and functional analysis by Gene Ontology (www.geneontology.org), 95% of the identified Nlinked glycoproteins were classified as membrane proteins that are known to be related to cancer development and metastasis, including cadherins, integrins, and CD markers (Table S-2, Supporting Information).

(Figures 4b−d). These results demonstrated that the specific recognition was not inhibited by BA. Application of BAD-Lectin@MNP for Complementary Glycoproteomic Analysis. To further evaluate the performance of BAD-lectin@MNPs in the glycoproteomic studies, three types of BAD-lectin@MNPs were used to capture glycopeptides from a complex biological sample. Briefly, BAD-ConA@MNPs, BAD-AAL@MNPs, and BAD-SNA@ MNPs were separately incubated with a peptide pool obtained from the tryptic digestion of purified membrane proteins from HeLa cells. One captured fraction was initially analyzed as unmodified glycopeptides, and the other fraction was analyzed after de-N-glycosylation with PNGase F. The comparison afforded data on both the peptide sequence and glycan type (see workflow in Figure S-7, Supporting Information). Treatment with PNGase F to remove the entire N-glycan moiety resulted in the conversion of Asn to Asp (deamidation) in the consensus N-glycosylation sequon, which can be identified as an N-glycopeptide using a shotgun proteomic approach. For intact glycopeptides, the precursor ion discovery (PID) approach, which performs product ion (glycan fragment ion in this study)-dependent data acquisition and has been successfully used in the selective detection of glycosylated proteins,33,52,53 was used to facilitate the discovery of glycan information. These results were then utilized to compare the selectivity for glycopeptide enrichment when using each type of BAD-lectin@MNP and to estimate the ratio of glycopeptides containing the lectin-specific glyco-epitope. As shown in Figure 5, the BAD-ConA@MNPs, BAD-AAL@ MNPs, and BAD-SNA@MNPs enriched 201, 110, and 60 de-

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CONCLUSION Overall, the newly developed BAD-lectin@MNPs not only demonstrated enhanced affinity for lectin−carbohydrate interaction but also exhibited glycan-selective recognition for glycoprotein detection. The 6% overlap among 295 N-linked glycopeptides enriched from HeLa cells with three BADlectin@MNPs further revealed the glycan-specific enrichment on the proteome scale. Consequently, we anticipate that the production of various bifunctional BAD-lectin@MNPs will facilitate the complementary enrichment of different glycoproteins, thereby facilitating the efficient identification of the under-explored glycoproteome in various biological samples.

Figure 5. Venn diagram showing the differences in the identified (a) glycopeptides and (b) glycoproteins when using three types of BADlectin@MNPs.

N-glycopeptides, respectively, with deamidation occurring at the consensus sequon. For the combined identification results (295 unique glycopeptides containing 301 N-linked glycosylation sites from 189 glycoproteins), the Venn diagram in Figure 5 shows that the three types of BAD-lectin@MNP nanoprobes enriched different glycopeptides/glycoproteins from the heterogeneous glycoproteome in a complementary manner. As many as 236 glycopeptides (80%) were uniquely identified by one of the BAD-lectin@MNPs, and only 17 glycopeptides (6%) were identified by all three nanoprobes. The low degree of overlap among the identified glycopeptides indicated the degree of specific enrichment by each type of BAD-lectin@MNP. To further evaluate the selective glycan-specific enrichment for each BAD-lectin@MNP, the characteristic oxonium ions of HexNAc+ (m/z 204) and HexHexNAc+ (m/z 366) from the fragmentation of all glycopeptides in MS/MS54,55 were selected in PID mode in Q-TOF mass spectrometry analysis. The MS/

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ASSOCIATED CONTENT

S Supporting Information *

Additional material as described in the text. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Y.-J.C.: E-mail [email protected]; fax +886-227831237. C.-C.L.: E-mail [email protected]; fax +8863-5711082. 8274

dx.doi.org/10.1021/ac401581u | Anal. Chem. 2013, 85, 8268−8276

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Notes

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The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was financially supported by the National Tsing Hua University, Academia Sinica, and the National Science Council, Taiwan.

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