Multiplexed analysis of glycan variation on native proteins captured by antibody microarrays

transcript

Multiplexed analysis of glycan variation on nativeproteins captured by antibody microarraysSongming Chen1, Tom LaRoche1,4, Darren Hamelinck1,4, Derek Bergsma1, Dean Brenner2, Diane Simeone2,Randall E Brand3 & Brian B Haab1

Carbohydrate post-translational modifications on proteins are

important determinants of protein function in both normal

and disease biology. We have developed a method to allow the

efficient, multiplexed study of glycans on individual proteins

from complex mixtures, using antibody microarray capture of

multiple proteins followed by detection with lectins or glycan-

binding antibodies. Chemical derivatization of the glycans on the

spotted antibodies prevented lectin binding to those glycans.

Multiple lectins could be used as detection probes, each

targeting different glycan groups, to build up lectin binding

profiles of captured proteins. By profiling both protein and

glycan variation in multiple samples using parallel sandwich

and glycan-detection assays, we found cancer-associated glycan

alteration on the proteins MUC1 and CEA in the serum of

pancreatic cancer patients. Antibody arrays for glycan detection

are highly effective for profiling variation in specific glycans on

multiple proteins and should be useful in diverse areas of

glycobiology research.

Glycan structures can be important determinants of many differentbiological processes, including protein-protein interactions, pro-tein trafficking and folding, immune recognition, cell adhesion andmigration, and inter-cellular signaling. Alterations to glycan struc-tures can contribute to the development and progression of cancerand other diseases1,2. The ability to efficiently profile the variationin glycosylation in complex biological samples would be useful for avariety of purposes, such as to characterize disease-associatedglycan alterations, to identify new diagnostic biomarkers or tostudy the factors that regulate glycan structures. Additionally, thetargeting of glycan structures is an increasingly important ther-apeutic strategy3, and the efficient characterization of the breadthand diversity of proteins carrying certain glycans could aid thosestudies. Established methods of studying glycan structures, such asenzymatic removal of glycans followed by chromatographic separa-tion or mass spectrometry, give detailed information about glycans,but are not suitable for studies requiring reproducible measure-ments over many different samples or proteins. Affinity-based

approaches, in which carbohydrate structures are detected byaffinity reagents that bind to specific glycans, could be useful forsuch studies. Multiplexed methods that allow glycan measurementson many different, specific proteins could further add to the valueof affinity-based glycan studies.

Lectins—plant and animal proteins with natural carbohydratebinding functionality—have been valuable glycan affinity reagentsin experimental formats such as affinity chromatography andelectrophoresis4, detection of blots of separated glycoproteins5

and in the capture or detection of proteins in microtiter plates toquantify glycans on specific proteins6. The use of multiple lectins inparallel can give a broad picture of the glycan structures present onproteins, as demonstrated in the use of microarrays of lectins tolook at lectin-binding profiles of purified proteins7–9. Lectin-basedglycan detection methods have been valuable for studying the rolesof glycans in disease. Cancer-associated glycan variants have beenfound on major serum proteins such as a-fetoprotein10, hapto-globin5,11, a-1-acid glycoprotein4 and a-1-antitrypsin12 usinglectin-affinity and immuno-affinity electrophoresis and blottingmethods. Antibodies raised to particular glycan groups, such as theThomsen-Friedenreich antigens13, the Lewis blood-group struc-tures14 and underglycosylated MUC1 (ref. 15), also have been usedto study the roles of glycans in cancer.

We have developed a method that complements and adds tothe existing glycan-detection technologies, based on the use oflectins to probe glycans on proteins captured by glycan-bindingantibody arrays. This method allows the study of glycans onmultiple, specific proteins captured directly from biological sam-ples. An essential preliminary step in the procedure is the chemicalderivatization of the glycans on the spotted capture antibodies toprevent lectin binding to those glycans. We fully optimized andcharacterized that step for the detection of a wide variety of glycanstructures. We demonstrate the use of multiple different lectins toobtain lectin-binding profiles of native transferrin captured under avariety of conditions, and we also demonstrate the characterizationof the glycan variation on two serum proteins in pancreatic cancerand control patients.

RECEIVED 5 DECEMBER 2006; ACCEPTED 12 MARCH 2007; PUBLISHED ONLINE 8 APRIL 2007; DOI:10.1038/NMETH1035

1Van Andel Research Institute, 333 Bostwick, Grand Rapids, Michigan 49503, USA. 2University of Michigan Medical Center, 1500 E. Hospital Drive, Ann Arbor, Michigan48109, USA. 3Evanston Northwestern Healthcare, 2100 Pfingstein Rd, Glenview, Illinois 60025, USA. 4Present addresses: Wayne State University Medical School, 540 E.Canfield, Detroit, MI 48201, USA (T.L.), McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L8 (D.H.). Correspondence should be addressedto B.B.H. (brian.haab@vai.org).

NATURE METHODS | VOL.4 NO.5 | MAY 2007 | 437

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RESULTSDetecting glycans on proteins captured by antibody arraysThe first step of this new method is the chemical derivatization ofthe glycans on the spotted antibodies to block lectin binding tothose glycans. The cis-hydroxyl groups of the glycans on the spottedantibodies are gently oxidized to convert them to aldehyde groups,then are reacted with a hydrazide-maleimide bifunctional cross-linking reagent, and the resulting product reacts with a Cys-Glydipeptide (Fig. 1a and Supplementary Fig. 1 online). The Cys-Glydipeptide adds bulk to the derivatized carbohydrates to hinderlectin binding. We attempted other strategies, including enzymaticremoval of the glycans and chemical derivatization in solutionbefore spotting, with less success.

Various lectins clearly bound to many of the underivatizedantibodies, but chemical derivatization of the spotted antibodiesgreatly reduced nonspecific lectin binding (Fig. 1b). After theincubation of serum on the derivatized antibodies, lectin bindingappeared at many of the antibody spots (Fig. 1b), indicating thatthe derivatized antibodies maintained the ability to bind proteinsfrom serum and that the lectins can bindproteins captured by the antibodies. Othercapping groups besides Cys-Gly also effec-tively blocked lectin binding, such as a 10-mer peptide and thiolated polyethyleneglycol (PEG-SH; MW, 2,000), althoughthe use of a 20-mer peptide resulted in anincrease in background (SupplementaryFig. 2 online). We chose the dipeptide forsubsequent experiments because of reducedlikelihood of inducing nonspecific bindingrelative to longer peptides, and because thelevel of blocking was slightly greater thanfor PEG-SH.

To establish that the lectins were specifi-cally binding to glycans and not nonspeci-fically interacting with the capturedproteins, we measured lectin binding tothe captured proteins in the presence ofvarying amounts of competing sugars. Thepre-incubation of the lectin wheat germagglutinin (WGA) with N,N-diacetyl chit-obiose (di-GlcNAc), a disaccharide ligandof WGA, resulted in a drastic reduction in

lectin binding to the arrays after serum incubation but we observedno reduction after pre-incubation with sucrose or L-fucose(Fig. 1c). The preincubation of Aleuria aurantia lectin (AAL)with a sugar it recognizes, L-fucose, but not with sucrose or N,N-diacetyl chitobiose, resulted in reduced binding to the arrays(Fig. 1c). The reduction of the binding of each lectin using onlytheir respectively targeted saccharides indicates the specific bindingof these lectins to glycans on the captured proteins.

Characterizing and optimizing lectin blockingAs the blocking of the lectin binding to the spotted antibodies iscritical for obtaining accurate results, we more fully characterizedand optimized this step using investigations of the binding of 16different lectins to antibody arrays prepared with a variety ofconditions (Fig. 2a). The 16 lectins had diverse glycan specificities(Supplementary Table 1 online) that had been defined in previousstudies16–18. All types of antibodies and lectins showed progres-sively reduced interaction at 25 and 150 mM NaIO4 while main-taining the detection of serum proteins captured by the arrays

Figure 1 | Detection of glycans on antibody

arrays. (a) Experimental scheme. SA-PE,

streptavidin-phycoerythrin. Antibodies 1 and 2

bind proteins 1 and 2, respectively. (b) Scanned

fluorescence images of antibody arrays showing

lectin binding to antibodies and captured serum

proteins. The antibodies are spotted in triplets

according to the order shown below the images.

(c) Blocking lectin binding with competing

sugars. The antibody arrays were incubated with

serum and detected with lectins that either had or

had not been preincubated with 100-fold molar

excess of a competing sugar. The WGA and AAL

lectins were prepared at 0.3 and 0.15 mM (10 mg/

ml), and the sugars were added to the respective

solutions at 30 and 15 mM.

438 | VOL.4 NO.5 | MAY 2007 | NATURE METHODS

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RCA120

LCAPSA

Jacalin

AB27AB21AB6AB4P1AB17AB23AB25AB24AB22AB10AB1AB12AB11AB7AB14AB19AB9AB18AB5AB16AB15AB26AB2AB20AB13AB3AB8

AB9AB2

AB6AB4

AB23AB19

AB17AB27

AB18AB24AB16AB15AB25AB21AB14

25,000

ConAAB2AB13AB26AB20AB3AB9AB19AB16AB22AB18P1AB25AB8AB27AB11AB12AB7AB24AB1AB14AB10AB17AB4AB23AB6AB15AB5AB21

0RCA120

AB16AB15

AB4AB5

AB16AB15

AB4AB5

AB16AB15

AB4AB5

AB3AB26AB13AB19AB2AB20P1 AB23AB22AB9AB21AB16AB5AB6AB4AB17AB1AB18AB10AB7AB12AB25AB11AB27AB8AB14AB15AB24

PBS incubation Serum incubation

Specificities:

Lectins:F

Rabbit

Chicken

RatSheep

Lectins

Figure 2 | Optimization and characterization of chemical derivatization. (a) Antibody arrays were derivatized with various concentrations of NaIO4, incubated

with either PBS or serum, and detected with various lectins. The antibodies on each array are indicated on the vertical axis, with color-coding indicating the

species of the antibody, and the lectins are indicated along the horizontal axis. The antibody rows were clustered by similarity within each NaIO4 condition, and

the lectin columns were manually grouped by specificity class. Each square represents one measurement from one array, with the color of the square indicating

fluorescence intensity according to the scale on the color bar. (b) Comparing rates of binding reduction between antibodies. Each cluster represents the binding

levels of the indicated lectin to each capture antibody, after incubation of the array with PBS and after derivatizing the antibodies with various concentrations

of NaIO4. Each data set was median-centered to increase the clarity of comparison between antibodies using the scale indicated by the color bar. The antibody

rows were clustered by similarity. (c) Comparing rates of binding reduction between lectins. The cluster presents the lectin binding averaged over all the

antibodies, for each lectin at various NaIO4 concentrations. The data were median-centered to increase the clarity of comparisons, using the indicated scale,

and the lectin rows were clustered by similarity.

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(Fig. 2a and Supplementary Fig. 3 online). The clustering ofantibodies did not show any grouping by species or class, revealingnotable heterogeneity in glycan structures within and betweenspecies and classes.

We investigated whether the level of oxidation required toeffectively block a particular lectin was variable between theantibodies (Fig. 2b). For some lectins, different capture antibodieshad different optimal levels of NaIO4 oxidation. For example, thelectins Bauhinia purpurea (BPL) and Ricinus communis agglutinin I(RCA120) required 150 mM NaIO4 to block binding to someantibodies but only 25 mM NaIO4 to block others. Other lectinsshowed more consistency between the antibodies, such as ConA,which needed 150 mM NaIO4 to block binding to all antibodies,and SNA, which was consistently blocked at lower concentrationswith a few exceptions. These analyses indicate that the oxidation ofcertain lectin epitopes is variable between antibodies, but that allantibodies could be effectively blocked at 150 mM NaIO4.

We also asked whether the optimal level of NaIO4 oxidation wasvariable between the lectins (Fig. 2c). The lectins ConA and Jacalinrequired the highest concentrations (150 mM) of NaIO4 to blockbinding to antibodies, but AAL and DSL could be effectively blockedat 50 mM NaIO4, and SNA could be completely blocked at 1 mM.We found no association between lectin affinity (measured for 24lectins binding to 47 antibodies using dose-response curves, Sup-plementary Table 2 online) and the concentration of NaIO4

required to block binding. The sialic acid targeted by SNA may berelatively easy to block as sialic acid is terminal and readily accessible,and because sialic acid oxidizes more easily than other saccharides19.

We sought to determine whether lectins targeting all types ofsugars could be blocked, even those that target monosaccharidesthat are not oxidized by NaIO4. Cis-diol groups or adjacent, freely

rotating alcohol groups (such as those found on sialic acid), arerequired for oxidation by NaIO4, so saccharides lacking those motifs,such as Gal, GalNAc and xylose, are not oxidized when in their ringconformation. The lectins Jacalin, BPL, Dolichos biflorus agglutinin(DBA), Erythrina cristagalli (ECL), RCA120 and Griffonia simplici-folia I (GSL I) target Gal or GalNAc, yet each of those lectins showeddecreased binding to the antibodies with increasing NaIO4 concen-trations (Fig. 2a,c). The broad blocking effect could be due to sterichindrance or changes to the overall oligosaccharide conformation.

The next characterization focused on the question of whether themodification of the glycans could negatively affect the affinities ofthe antibodies, as glycan structures on antibodies can be importantfor antibody structure and function. We investigated this questionby measuring antibody affinities using dilution curves of purifiedantigens, EGF, angiogenin and transferrin (Fig. 3). The affinities ofseveral tested antibodies dropped slightly after derivatization, butdid not observe a drop in antibody specificity, as binding tononspecific antibodies on the arrays did not increase after deriva-tization. The drop in antigen binding after derivatization was notdue to general loss of antibody on the surface, as the detection ofspotted, biotinylated antibodies showed no loss in signal afterderivatization (Supplementary Fig. 4 online). Background bindingto the nitrocellulose also did not change after derivatization (Fig. 3and Supplementary Fig. 4), which is important for maintainingdetection sensitivity. The slight loss in affinity may be a necessarytradeoff, in some cases, to specifically detect glycans, but should stillallow the specific detection of a wide range of proteins.

Lectin-binding profiles of captured transferrinOne application of this method will be to use multiple lectinsto build up a lectin-binding profile for each captured protein,

0.5 3240

15,000

30,000

45,000

EGFDerivatizedNo Yes

0.25 2 160

20,000

40,000Angiogenin

DerivatizedNo Yes

0.0625 642

25,000

50,000

DerivatizedNo Yes

Transferrin

Concentration of antigen (nM)

Not derivatized Derivatized

Concentration of antigen (nM)

Anti-EGF

Anti-angiogenin

Anti-transferrin

Figure 3 | The effect of derivatization on antibody

affinities. We incubated various concentrations of

recombinant angiogenin and EGF in PBST0.1 on

antibody arrays and detected binding by their

respective capture antibodies with biotinylated

detection antibodies followed by streptavidin-

phycoerythrin staining. For the detection of

transferrin, we incubated biotinylated, purified

transferrin at various-concentration antibody

arrays and detected them with streptavidin-

phycoerythrin. The scanned images present results

from the antigen concentrations of 8, 2 and

1 nM are for EGF, angiogenin and transferrin,

respectively. The graphs present the fluorescence

intensities from the respective antibody spots

(individual spots shown at far right) at each

antigen concentration (x axis on log scale, zero

not shown). Nonlinear curve fitting was performed

with the software Origin according to a sigmoidal

curve model (Boltzmann model). The binding

affinities were estimated as the antigen

concentrations at which the background-

subtracted fluorescence reached half maximum.

The estimated dissociation constant (Kd) values

of underivatized anti-transferrin, anti-angiogenin

and anti-EGF were 5, 2 and 1 nM, and of

the derivatized versions were 13, 8 and

2 nM, respectively.

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which would provide a picture of the types of glycan structurespresent on each protein. The serum protein transferrin containstwo N-glycosylation sites with biantennary, complex-type oligo-saccharides. The predominant structure in healthy individuals iscomposed of N-acetylglucosamine, tri-mannose, Galb1-4GlcNAcunits (known as LacNAc) and terminal a2-3–linked sialic acid20

(Fig. 4a). We obtained the binding patterns of 23 lectins to eitherpurified transferrin or pooled human serum that had been cap-tured on antibody arrays, and interpreted those profiles based onthe previously characterized glycan structures.

We showed the importance of derivatizing the antibodies bythe specific lectin binding to the targeted protein only usingderivatized arrays (Fig. 4b) and by a comparison of the lectinbinding profiles at the derivatized and underivatized antitransferrinspots (Fig. 4c). The lectin-binding profile of purified transferrincaptured by derivatized anti-transferrin showed substantial bindingmainly with the SNA lectin, consistent with transferrin’s sialic acidgroups. Transferrin captured from serum showed binding fromDSL and RCA120, which reflect the presence of exposed LacNAcgroups in transferrin, and ConA, which binds complex-typeN-glycans, particularly a-linked mannose. The LCA bindingcould be due to the a-mannose on transferrin, but it alsocould reflect the presence of fucosea1-6GlcNAc, which has beenoccasionally found on transferrin20.

The treatment of the samples with the enzyme neuraminidase,which removes terminal sialic acid groups, eliminated SNA bindingon both purified transferrin and transferrin captured from serum(Fig. 4a,c). The binding of three lectins that target LacNAc, RCA120,ECL and DSL substantially increased after enzymatic treatment,confirming the exposure of the LacNAc groups in transferrin, which

are more reactive to RCA120 and ECL if the capping sialic acid is notpresent7. It was interesting that BPL, which primarily binds astructure not found on the transferrin N-glycan, Galb1-3GalNAc(the T antigen), also showed greatly increased binding after sialicacid removal. The accuracy of this observation is supported by thebinding of the other T-antigen binders, PNA and Jacalin, afterremoval of sialic acid. This binding could arise from a protein that isinteracting with transferrin, such as soluble transferrin receptor, orfrom previously uncharacterized glycan structures on transferrin.

Glycan variation on serum proteins in cancer patientsAnother important application of this method is to measure thevariation in glycan structures across populations or conditions. CEAand MUC1 are heavily glycosylated proteins that have been asso-ciated with pancreatic cancer, and MUC1 is known to have glycanalterations associated with cancer21,22. We used parallel sandwichand lectin-detection assays to look at the variation over multiplesamples in the protein and glycan levels, respectively. Pooled MUC1and CEA detection antibodies provided multiplexed detection oftheir respective targets (Fig. 5a). We incubated a cohort of serumsamples (23 from cancer patients and 23 from control patients) onreplicate sets of arrays. The pooled detection antibodies measuredprotein levels on one set of arrays, and the lectins AAL and WGAmeasured glycan levels on two other sets of arrays. We used AAL andWGA because of previous associations of their binding levels withcancer. We also detected a set of arrays with the monoclonalantibody anti–CA 19-9, which targets a cancer-associated bloodgroup glycan, the sialyl Lewis acid structure.

Certain samples showed similar MUC1 and CEA protein levelsbetween the cancer and control patient sera, but higher glycan levels

10,000

Lectins

20,000

020,000

0Lectins

10,000

0Lectins

60,000

0Lectins

PBSPHAL

SBASNA

UEA1DSL

RCA 120

SJA BPL

ECLDBA

AALPSA

Transferrin

Digestedtransferrin

Serum pool

Digestedserum pool

Neuraminidase

GlcNAc

Antibodiesderivatized

Antibodiesnot derivatized

AB19AB15AB11AB1

Anti-transferrin

AB13AB20AB26AB2

AB14AB16AB23AB12

AB4AB5AB6AB7Biotin

Lectins

Antibodiesderivatized

Antibodiesnot derivatized

Figure 4 | Lectin binding profiles of native and enzyme-digested

protein. (a) The predominant glycan structure on transferrin, with the

indicated cleavage site for neuraminidase. (b) Images of antibody

arrays incubated with purified transferrin and detected with

biotinylated SNA, with and without antibody derivatization. (c) Lectin

binding profiles at the indicated conditions. Each column represents

the intensity of lectin detection at the anti-transferrin spot. The order

of the lectins is indicated at the bottom.

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on both proteins in the cancer patient sera (Fig. 5a). Comparisonsof the distributions of protein and glycan levels indicated somestatistical differences (P o 0.05) between the cancer and controlgroups (Fig. 5b). In the cancer patient samples, both the proteinand glycan levels of CEA were elevated, but only the glycan levels ofMUC1 were elevated. For both CEA and MUC1, the ratios of CA19-9 to total protein were increased in cancer relative to controlpatient sera (Fig. 5b), indicating that the carbohydrate structuretargeted by the anti–CA 19-9 was present at a higher level, permolecule, in the cancer sera. We confirmed the increased CA 19-9–reactive glycans on MUC1 using immunoprecipitation and westernblot analyses (Fig. 5c).

DISCUSSIONThe development of a new method to block lectin binding to glycangroups on the spotted antibodies permitted this approach. The factthat even lectins targeting glycans not oxidized by NaIO4 could beblocked is important for the general application of the method. Asthe optimal oxidation level was variable between certain lectins andantibodies, future applications could use tailored levels of oxidationto fit specific needs, although for practicality it may be desirable tosimply use a single NaIO4 concentration if multiple antibodies orlectins are to be used.

The glycan binding profile of the protein transferrin we deter-mined here faithfully represented the previously characterized

glycan structure on transferrin, both usingpurified transferrin and transferrin cap-tured directly from serum. Because thebinding of some lectins is enhanced afterthe enzymatic removal of certain terminalglycans, this approach could be expanded

by using multiple different enzymes, either serially or in parallel, ashas been used in previous glycoprotein studies. Enzymes thatspecifically cleave O-glycans could be useful to further investigatethe unexpected evidence that T-antigen glycan structures, which arenormally O-linked, are associated with transferrin.

The ability to analyze multiple samples efficiently, as demon-strated here, was useful for identifying glycosylation levels on CEAand MUC1 that were higher in serum samples from pancreaticcancer patients relative to control patients. Glycan alterations onMUC1 in cancer have been observed previously, including trunca-tions in O-glycosylation that lead to the exposure of core carbohy-drate structures such as the Thomsen-Friedenreich and sialyl Tnantigens21,22. It had been shown previously that biliary and pan-creatic mucins carry the sialyl-Lewis x and sialyl-Lewis a (the CA19-9 epitope) structures23–25. This study provided new evidencethat the CA 19-9–reactive structure is actually increased on MUC1in cancer patient sera. CEA family members have been shown tocarry Lewis x structures26–28, but cancer-associated elevations of theCA 19-9 structure were not demonstrated. As Lewis blood groupstructures are ligands that mediate binding to endothelial cellsthrough E-selectin and endothelial leukocyte adhesion molecule 1(ELAM-1), a possible role of the CA 19-9–reactive elevations wouldbe to modulate interactions between cell-surface receptors andcirculating proteins. Further experiments will be required to addressthe origins and functional consequences of the observed glycan

1 2 3 4 5 6 7 8 9

+1+1 +1 +1

AALCEA

anti–Pan-CEACAM

Protein levels

H C H C H C H C H C H C H C

H C H C H C H C H C H C

AAL WGA anti–CA19-9 (Ab#1)

anti–CA19-9 (Ab#1)

CA 19-9CEA

WGACEA

Glyan levels Protein:glycan ratio

***+1 +1 +1

MUC1CEA

anti–Pan-CEACAMand anti-MUC1

MUC1CEA

anti–Pan-CEACAM

anti-MUC1Detection: anti-CA 19-9 (Ab#1)

Serum pool Healthy serum Cancer serum Healthy serum Cancer serumSample:a

Detection:

Capture antibody: anti-CEA

Protein levels

anti-MUC1

* * *+1 +1

Glyan levels Protein:glycan ratio

AALMUC1

AAL WGA CA 19-9MUC1

WGAMUC1

Capture antibody: anti-MUC1

# Source Class Detection Ab1 MUC-1 IP Cancer anti-MUC-12 MUC-1 IP Healthy anti-MUC-13 Serum pool Cancer anti-MUC-14 Serum pool Healthy anti-MUC-15 MUC-1 IP Cancer anti-CA19-96 MUC-1 IP Healthy anti-CA19-97 Serum pool Cancer anti-CA19-98 Serum pool Healthy anti-CA19-99 MUC-1 IP Cancer nonspecific mouse IgG

Detection:

350–450 kDa

55 kDa

25 kDa

Figure 5 | Profiling protein and glycan variation in

cancer and control sera. (a) Representative array

images. A pool of 30 cancer sera was incubated on

the left pair of arrays, and a healthy patient serum

sample and a cancer patient serum sample were

incubated on the middle and right pairs of arrays

(same two samples in each pair). The arrays were

detected using the indicated antibodies. The spots

appearing at the lower right of each array were

biotinylated control proteins. The other spots that

showed signals in the array detected with CA 19-9

targeted proteins containing the CA 19-9 epitope.

(b) Distributions of glycan and protein levels. The

plots present the fluorescence at either the anti-

CEA capture antibody or the anti-MUC1 capture

antibody from sera from healthy subjects (H, n ¼23) or cancer patients (C, n ¼ 23). The boxes give

the upper and lower quartiles of the measurements

with respect to the median value (horizontal line

in each box). In the upper corner of each plot is

the number of outliers not shown, and the

asterisks indicate the measurements that were

statistically different (P o 0.05) between the

healthy and cancer groups. The right panels show

the ratios of glycan levels to total protein levels

calculated for each sample. (c) Western blots using

the indicated samples and antibodies. MUC1 was

immunoprecipitated from pooled sera from

pancreatic cancer patients and pooled sera from

healthy control subjects.

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alterations. Expanded studies could look at broader lectin profiles indisease and control samples for a wider variety of proteins.

The value of the experiments will be enhanced by the continuedcharacterization of the specificities of the lectins and the develop-ment of new antibodies against cancer-associated glycotopes.Glycan microarrays are a useful complementary method for thatpurpose18,29,30. The development of well-characterized controlglycans and proteins for the calibration and additional character-ization of these newly developed assays also will be valuable. Thesecontinued developments will further advance the ability to speci-fically measure glycan variation on multiple, native proteins overmultiple samples or conditions, which should be useful in a varietyof research areas relating to protein glycosylation.

METHODSAntibodies, lectins and proteins. The antibodies and lectins werepurchased from various sources (see Supplementary Table 3 onlinefor information on the antibodies and proteins, and Supplemen-tary Table 1 for information on the lectins). Information about thepreparation of the antibodies is available in Supplementary Meth-ods online. Neuraminidase and 10� G1 reaction buffer werepurchased from New England Biolabs.

Microarray fabrication and preparation. A piezoelectric non-contact printer (Biochip Arrayer; PerkinElmer Life Sciences)spotted approximately 350 pl of each antibody solution on thesurfaces of ultrathin nitrocellulose–coated microscope slides(PATH slides; GenTel Biosciences). We printed forty-eight identicalarrays on each slide, with each array consisting of 36–48 antibodiesand control proteins spotted in triplicate. We imprinted a waxborder around each of the arrays to define hydrophobic bound-aries, using a custom-built device.

The slides using chemical derivatization were treated as follows.We incubated the slides in a coupling buffer (0.1 M sodium acetate(pH 5.5) with 0.1% Tween-20) for 30 min, then submerged them ina NaIO4 solution (Pierce Biotechnology) at 4 1C for 30 min in thedark to oxidize the sugar groups. We rinsed the slides in couplingbuffer and then incubated 1 mM 4-(4-N-maleimidophenyl)butyricacid hydrazide hydrochloride (MPBH; Pierce Biotechnology) onthe slides for 2 h at room temperature (18–22 1C) to derivatize thecarbonyl groups. We rinsed the slides briefly with 1� PBS with0.1% Tween-20 (PBST0.1), incubated them with 1 mM Cys-Glydipeptide (Sigma Aldrich) in PBST0.1 overnight at 4 1C, thenrinsed them thoroughly in PBST0.1 and dried the slides bycentrifugation (Eppendorf 5810R, rotor A-4-62, 150g). We testedother reagents instead of Cys-Gly, including a 10-mer peptide(NRCSQGSCWN, reduced; Sigma Aldrich), a 20-mer peptide(HIV gp120 fragment 254–274; Sigma Aldrich) and PEG-SH(MW, 2,000 kDa; NEKTAR).

Microarray use. We diluted samples (either serum or purifiedproteins) into 1� TBS buffer containing 0.08% Brij, 0.08% Tween-20 and 50 mg/ml of protease inhibitor. We diluted serum samplestenfold and the purified proteins to various concentrations. Wewashed the microarray slides in PBST0.5 three times for 3 min eachto remove unbound antibodies and clean the surface, and placedthem in a blocking solution of PBST0.5 containing 1% BSA atroom temperature for 1 h. We washed the slides in three baths ofPBST0.1 and centrifuged them to dry; then we added 7 ml of sample

to each array and incubated them at room temperature for 1 h.After washing and drying the slides as above, we added 7 ml of10 mg/ml biotinylated lectin or 1 mg/ml of detection antibody inPBST0.1 containing 0.1% BSA to each array, and incubated them atroom temperature for 1 h. After washing the slides and drying them,we added 7 ml of streptavidin-phycoerythrin (Roche AppliedScience) to each array and incubated at room temperature for 1 h.After a final wash, we dried the slides and detected fluorescenceemission at 570 nm using a microarray scanner (ScanArray Lite;PerkinElmer Life Sciences). We scanned all arrays within an experi-ment set in one batch at a single laser power and detector gainsetting. We used the software program GenePix Pro 5.0 (MolecularDevices) to quantify the image data. We subtracted median localbackgrounds from the median intensity of each spot and averageddata from replicate spots. The data were not normalized.

Statistical analysis. We used the Mann-Whitney nonparametrictest to compare measurements from different patient groups, as themeasurements were non-normally distributed across the samples.Alpha ¼ 0.05 was used as the significance threshold.

Serum samples. We collected serum samples from two sites. AtEvanston Northwestern Healthcare, we collected serum samplesfrom patients with pancreatic adenocarcinoma (stage I to stage IV),and for the control, we collected samples from high-risk individualsfrom pancreatic-cancer-prone families undergoing surveillance withendoscopic ultrasound or endoscopic retrograde cholangiopancrea-tography. The control subjects had no pancreatic lesions. At theMultidisciplinary Pancreatic Tumor Clinic at the University ofMichigan Comprehensive Cancer Center, we obtained serum sam-ples from patients with a confirmed diagnosis of pancreatic adeno-carcinoma. We also obtained sera from healthy control individualsunder the auspices of the Early Detection Research Network. Allsamples were stored at each site at –80 1C and sent frozen on dry iceto the Van Andel Research Institute, where we stored them at–80 1C. Each aliquot had been thawed no more than two timesbefore use. All samples were coded to protect patient anonymity andwere collected under protocols approved by local InstitutionalReview Boards for human subjects research.

Additional methods. Other experimental methods, including theenzymatic digestion, immunoprecipitation and western blottingprotocols, are available in Supplementary Methods.

Note: Supplementary information is available on the Nature Methods website.

ACKNOWLEDGMENTSWe thank D. Mistry for assistance with the experiments and other members of theLaboratory of Cancer Immunodiagnostics at the Van Andel Research Institute forhelpful interactions. We thank A. Rai (Memorial Sloan Kettering Cancer Center) andI. Goldstein (University of Michigan) for valuable input. We gratefully acknowledgethe Van Andel Research Institute for support of this work.

COMPETING INTERESTS STATEMENTThe authors declare competing financial interests: details accompany the full-textHTML version of the paper at www.nature.com/naturemethods.

Published online at http://www.nature.com/naturemethods/Reprints and permissions information is available online athttp://npg.nature.com/reprintsandpermissions

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Multiplexed analysis of glycan variation on native proteins captured by antibody microarrays

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