N-glycan analysis by CGE–LIF: Profiling influenza A virus ...

Research Article

N-glycan analysis by CGE–LIF:Profiling influenza A virus hemagglutininN-glycosylation during vaccine production

Glycoproteins, such as monoclonal antibodies as well as recombinant and viral proteins

produced in mammalian cell culture play an important role in manufacturing of many

biopharmaceuticals. To ensure consisting quality of the corresponding products, glyco-

sylation profiles have to be tightly controlled, as glycosylation affects important properties

of the corresponding proteins, including bioactivity and antigenicity. This study describes

the establishment of a method for analyzing N-glycosylation patterns of mammalian cell

culture-derived influenza A virus glycoproteins used in vaccine manufacturing. It

comprises virus purification directly from cell culture supernatant, protein isolation,

deglycosylation, and clean-up steps as well as ‘‘fingerprint’’ analysis of N-glycan pools by

CGE-LIF, using a capillary DNA-sequencer. Reproducibility studies of CGE-LIF, virus

purification, and sample preparation have been performed. For demonstrating its

applicability, the method was exemplarily used for monitoring batch-to-batch reprodu-

cibility in vaccine production, with respect to the glycosylation pattern of the membrane

protein hemagglutinin of influenza A/PR/8/34 (H1N1) virus. This method allows

characterization of variations in protein glycosylation patterns, directly by N-glycan

‘‘fingerprint’’ alignment.

Keywords:

CGE-LIF / DNA-sequencer / Hemagglutinin / influenza virus / N-glycosylationDOI 10.1002/elps.200800042

1 Introduction

Glycosylation is a common and highly diverse post-

translational modification of proteins in eukaryotic cells

[1]. Various cellular processes were described, involving

carbohydrates on the protein surface. Previous studies have

shown, e.g., the importance of glycans in protein stability,

protein folding, and protease resistance [2, 3]. In addition,

the role of glycans in cellular signaling, regulation [4, 5]

and developmental processes [2] was demonstrated. The

oligosaccharides are mainly attached to the protein back-

bone, either by N- (via Asn) or O- (via Ser/Thr) glycosidic

bonds, with N-linkage representing the more common

modification [6]. N-glycans share a common trimannosyl

chitobiose core, from which a large number of structural

variants can extend, branched into two or more antennae.

Additionally, they are subgrouped into complex, high

mannose or hybrid type N-linked glycans, depending on

the sugar residues of the antennae [7]. Variations in

glycosylation site occupancy (macroheterogeneity), as well

as variations in sugar residues attached to one glycosylation

site (microheterogeneity) result in a set of different protein

glycoforms. These glycoforms have different physical and

biochemical properties, which results in additional func-

tional diversity [8]. In manufacturing of therapeutic proteins

in mammalian cell cultures, macro- and microheterogeneity

were shown to affect properties like protein solubility,

structural stability, protease resistance, or biological and

clinical activity [9–11]. This is, for instance, of relevance

for the therapeutic profile of monoclonal antibodies [12].

N-glycan biosynthesis is a non-template-driven process,

involving the cell glycosylation machinery [13]. In glycopro-

tein manufacturing, N-glycan structures not only depend on

protein structure and host-cell glycosylation machinery [13,

14], but also on cultivation conditions and extracellular

environment. Culture parameters affecting glycosylation

include temperature, pH, aeration, supply of substrates, or

Jana Schwarzer1

Erdmann Rapp1

Udo Reichl1,2

1Max Planck Institute forDynamics of Complex TechnicalSystems, Magdeburg, Germany

2Otto-von-Guericke-University,Chair of BioprocessEngineering, Magdeburg,Germany

Received January 16, 2008Revised May 16, 2008Accepted May 16, 2008

Abbreviations: APTS, 8-amino-1,3,6-pyrenetrisulfonic acid;

bp, base pair; DSP, downstream processing; HA, influenzavirus hemagglutinin; hpi, hours post infection; MDCK,

Madin-Darby canine kidney; NA, influenza virusneuraminidase; NP, influenza virus nucleoprotein; SED,

sequential exoglycosidase digestion; USP, upstreamprocessing

Correspondence: Dr. Erdmann Rapp, Max Planck Institute forDynamics of Complex Technical Systems, SandtorstraXe 1,39106 Magdeburg, GermanyE-mail: [email protected]: 149-391-6110535

& 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.electrophoresis-journal.com

Electrophoresis 2008, 29, 4203–4214 4203

accumulation of by-products such as ammonia and lactate

[11, 15]. In contrast to recombinant glycoprotein or antibody

manufacturing [11, 12, 14, 16–18], characterization of

glycosylation profiles of antigens in vaccine production has

not attracted much attention so far. To some extent this is

certainly due to the complexity in analyzing glycosylation

profiles of one or more viral antigens during upstream

processing (USP) and downstream processing (DSP). In

addition, it is difficult to assess the possible impact of

changes in glycosylation patterns on efficacy or safety of

vaccines. However, with respect to increasing efforts to

ensure consistency in vaccine production and to evaluate the

influence of process modifications or process perturbations

on quality of the final product, monitoring of glycosylation

could serve as a very useful tool. However, the high

complexity of N-glycans, rises a challenging problem for

separation and detection of these carbohydrates. Being more

diverse in their structural features than, e.g. proteins or

nucleic acids, this task is as complex as the glycans

themselves [6]. Over the last 30 years, a wide range of

strategies and analytical techniques for analyzing intact

glycoproteins, glycopeptides, and released N-glycans have

been established. This includes, e.g., 2-D-HPLC profiling

[19, 20], MS [21, 22], NMR [23], and lectin affinity

chromatography [24], recently reviewed by Geyer and Geyer

[25]. Due to their superior separation performance and

efficiency compared with other liquid phase separation

techniques, CE techniques [26], in particular CGE, are

considered for complex carbohydrate separation [27, 28]

despite their poor reputation concerning robustness. Meth-

ods for automated carbohydrate profiling using a single

capillary column instrument or a 96-capillary array electro-

phoresis system are described in literature for bioindustrial

approaches [29–31]. To point out changes in glycosylation

patterns, these analysis methods are mainly used to obtain

structural data of enzymatically or chemically released

N-glycans. This is conventionally done by sequential

exoglycosidase treatment steps, described by Edge et al.[32]. Resulting degraded glycostructures are nowadays either

analyzed by MS or NMR [25], which is generally laborious

and time-consuming regarding sample preparation and data

interpretation. However, in many cases an N-glycan analysis

method that allows to rapidly monitor alterations in

glycosylation patterns without the need for complex data

evaluation is desired. Therefore, a straightforward tool,

allowing to visualize N-glycan pools of glycoproteins would

be sufficient without further structural analysis of the

N-glycans, omitting highly expensive and complex equip-

ment such as MS/MS- and NMR instruments. Within this

work a method is described, which allows glycosylation

pattern profiling of any glycoprotein. It involves protein

purification, protein separation, deglycosylation, and clean-

up steps. The N-glycan pools obtained are separated and

detected by CGE-LIF. The method is sensitive and

reproducible enough to point out potential variations in

the glycosylation patterns without requiring complex

structural investigations. As an example, glycosylation

pattern profiling of Madin Darby canine kidney (MDCK)

cell culture-derived influenza A virus hemagglutinin (HA)

(human influenza A/PR/8/34 (H1N1)) is shown [33–35].

The influenza A virus envelope is spiked with two integral

membrane glycoproteins: HA and neuraminidase (NA). For

HA it is known that 3–9 N-linked glycans are attached to the

intact protein backbone [36]. The number and the type of the

attached oligosaccharides depend on the virus subtype

[37–39], as well as the virus strain [40]. Although the

biological function of HA-glycans is still not completely

understood, their importance in, e.g., shielding the HA from

protease activity [41, 42] and the impact of HA glycosylation

on the efficiency of virus replication and during virus

virus purification & concentration bycentrifugation

protein separation (SDS-PAGE)

removing N-glycans from HA(in-gel-deglycosylation with PNGaseF)

extractions of N-glycansprotein oligosaccharides

tryptic digest

nanoHPLC-nanoESI-MS/MS

fluorescent labeling of N-glycans (APTS)

removal of dye excess & desalting (SEC)

Identification of N-glycan containing SEC-fractions

N-glycan profiling (CGE-LIF)

Figure 1. Workflow for protein identificationand N-glycan analysis of mammalian cellculture-derived influenza A virus HA.

Electrophoresis 2008, 29, 4203–42144204 J. Schwarzer et al.


particle assembly [43, 44] was demonstrated. Further studies

showed the important role of HA glycans for antigenic

activity [45] and their impact on protein conformation and

intracellular transport [46].

This work describes a fast workflow for N-glycan profil-

ing of influenza virus HA out of a complex cell

culture medium, using a combination of methods including

a new application of the a CE method. The presented work-

flow (Fig. 1) was specifically developed for analysis

of virus containing cell culture supernatants obtained

during USP. It describes a relatively simple and robust,

but nevertheless highly sensitive and quite reproducible

N-glycan analysis method with high separation performance.

After processing of samples, HA glycome ‘‘fingerprints’’ are

generated, by using a capillary DNA-sequencer, based on a

method originally developed by Callewaert et al. [27, 47, 48].

2 Materials and methods

2.1 Cells and virus

Influenza A virus was produced in mammalian cell culture

according to [33]. In brief, MDCK cells (ECACC No.

841211903) were grown in T175 flasks and roller bottles at

371C in Glasglow minimum essential medium (GMEM)

(Gibco ]22100-093, UK) supplemented with 10% fetal calf

serum (Gibco ]10270-106), 2 g/L peptone (autoclaved 20%

solution, International Diagnostics Group ]MC33), 5.5 g/L

glucose (499.5%, Sigma-Aldrich, Taufkirchen, Germany)

and 4.0 mg/mL NaHCO3 (p.a., Merck, Darmstadt, Germany).

Human influenza A/PR/8/34 (H1N1) was obtained from

Robert Koch Institute (Amp. 3138; Berlin, Germany).

Confluently grown cells were infected with a multiplicity of

infection of 0.01 (based on TCID50 (tissue culture infectious

dose/mL) after medium exchange to GMEM with the same

supplements except fetal calf serum and the addition of

trypsin (final concentration 5 U/mL; Gibco). For all experi-

ments samples were taken 72 hours post infection (hpi) for

N-glycan analysis.

2.2 Virus purification and concentration

Virus harvest (72 hpi) was purified and concentrated by

consecutive stepwise ‘‘g-force gradient centrifugation’’. There-

fore, approximately 50 mL virus containing cultivation broth

was stepwise clarified by applying 100 g for 20 min, 4000 g for

35 min and 10 000 g for 45 min (41C) using a Heraeus Biofuge

primo R (Thermo Electron, Dreiech, Germany). At each step,

supernatants were transferred into a new centrifuge tube and

pellets were discarded. As the final step, virus particles

were pelletized out of 30 mL clarified cultivation broth at

58 000 g for 90 min (41C) using an OptimaTM LE-80 K

Ultracentrifuge (Beckman Coulter, Krefeld, Germany). After-

wards, virus pellets were dissolved in 50–100 mL 100 mM Tris

(Ultra Quality, Roth, Karlsruhe, Germany), pH 7.0. Virus

proteins were separated by SDS-PAGE.

2.3 SDS-PAGE

Ten percent Tris-HCl SDS-gels were obtained from Bio-Rad

Laboratories GmbH (]161-1101EDU, Germany). Virus and

IgG (from bovine serum, reagent grade, Sigma-Aldrich)

samples, containing 10 mg total protein, were mixed pre-run

with 4� non-reducing sample buffer containing a final

concentration of 125 mM Tris (Ultra Quality, Roth), 4% SDS

(for electrophoresis, Roth), 20% glycerol (p.a., Merck) and

8 M urea (Ph. Eur., Roth), and heated for 5 min at 1001C.

As molecular weight standard, 5 mL of Roti-Mark

PRESTAINED (Roth) were loaded in a separate lane.

Gels were run using a Mini-PROTEAN 3 cell (Bio-Rad

Laboratories GmbH, Germany) at constant current (20 mA/

gel). Proteins were visualized by colloidal Coomassie

(for electrophoresis, Merck) staining overnight.

2.4 Identification of the viral proteins by tryptic in-

gel-digestion and nanoHPLC-nanoESI-MS/MS

After SDS-PAGE separation, viral proteins were digested

enzymatically in gel and identified by nanoHPLC-nanoESI-

MS/MS. Fully automated online pre-concentration and

separation of the tryptic digested samples were performed

utilizing a set of capillary and nanoHPLC instruments of the

1100 Series (Agilent, Waldbronn, Germany) operated in

series. Mass spectrometric detection was carried out by

online coupling nanoHPLC with nanoESI-MS/MS. MS and

MS/MS spectra were recorded on a QSTAR XLTM (QqTOF)

mass spectrometer (Applied Biosystems/MDS/Sciex, Darm-

stadt, Germany) equipped with an online nano-electrospray

ion source (NanoSpray s II Source) and upgraded with a

heated interface. Data processing and interpretation of

online acquired ESI-MS/MS peptide spectra were

performed via automatic database search of product-ion

spectra of the nanoHPLC-nanoESI-MS/MS analysis.

MASCOTTM [49] (version 2.2, Matrix Science, London,

UK) was used to identify the corresponding peptides. For

final protein confirmation at least two product-ion spectra of

different peptides of each identified protein were verified

manually. A detailed description of the procedure for

identification of the viral proteins is given online in a

Supporting Information.

2.5 In-gel-deglycosylation and N-glycan extraction

In-gel-deglycosylation was performed according to Kuster

et al. [50]. Briefly, HA0 protein bands excised from SDS-gels,

were washed twice for 30 min with 20 mM NaHCO3

(Fluka BioUltra, Sigma-Aldrich), pH 7.0. Gel pieces were

covered with 300 mL fresh 20 mM NaHCO3, pH 7.0 and

Electrophoresis 2008, 29, 4203–4214 CE and CEC 4205


incubated for 30 min at 601C after adding 20 mL of 45 mM

DTT (Fluka BioUltra, Sigma-Aldrich). Samples were cooled

to RT, afterwards 20 mL of 100 mM iodacetamide (SigmaUl-

tra, Sigma-Aldrich, Taufkirchen, Germany) were added.

Alkylation took place at RT for 30 min in the dark. Removal

of reducing and alkylating reagents was followed by

incubation in a 1:1 mixture of acetonitrile (HPLC Ultra

Gradient Grade, Roth) and 20 mM NaHCO3, pH 7.0 for

60 min. Shrunken pieces were completely dried (Integrated

SpeedVac System ISS100, Savant, USA). For deglycosyla-

tion, 6 mL of PNGase F (500 U/mL; Proteomics Grade,

Sigma-Aldrich) were added. After reswelling, the gel pieces

were covered with 124 mL 20 mM NaHCO3, pH 7.0 and

incubated overnight at 371C.

Following, the supernatant, containing already some

N-glycans, was removed and stored at 41C. N-glycans were

extracted from gel pieces using three changes of 200 mL Milli

Q water with sonication in an ice cooled water bath for

30 min. The three extracts were pooled with the incubation

solution and completely dried (ISS100).

2.6 Fluorescent labeling of N-glycans and desalting

by SEC

Glycans were fluorescently labeled according to the method

of Callewaert et al. [27] with 8-amino-1,3,6-pyrenetrisulfonic

acid (APTS) (496.0%, Sigma-Aldrich) by reductive amina-

tion. Therefore, 5 mL 20 mM APTS and 5 mL 1 M NaBH3CN

(reagent grade, Sigma-Aldrich) were added to the dried N-

glycans. Derivatization was allowed for 18 h at 371C. Both,

the excess of not reacted APTS and the salts were removed

by SEC. Therefore, MultiScreen Deep Well Solvinert Filter

Plates (Millipore ]MDRL N04, Germany) were packed with

SEC material. Different size exclusion materials, e.g.,Sephadex G-10 and G-25 (Sigma ]G10120; Sigma ]G2580,

Germany), Bio-Gel P-2 Gel (Bio-Rad ]150-4114, Germany)

and Toyopearl HW-40F (Tosoh Bioscience ]19808,

Germany) were screened for the best separation of the

conjugated N-glycans from the surplus dye. Use of

Sephadex resulted in comparatively large batch-to-batch

variations and additional peaks within the electrophero-

grams (data not shown). Best results were achieved with

modified methacrylate polymer based Toyopearl HW-40F

regarding reproducibility and recovery. The slurry was

washed six times with Milli Q water in 50 mL centrifuge

tubes. Deep wells were packed with 2 mL washed slurry

and washed again with three column volumes Milli Q

water. After sample application, N-glycans were eluted with

Milli Q water by centrifugation (50 g/step). Up to 25

fractions were collected (each in one black 96 well clear-

bottom plate, Corning ]3615, Germany) and screened for

N-glycan content by scanning with a Typhoon TRIO

Variable Mode Imager (GE Healthcare, Germany). The

extinction wavelength of the laser was set to 488 nm and

emission was measured at 520 nm with normal sensitivity.

Images were evaluated and N-glycan containing fractions

identified with respect to the intensity of the fluorescence

signal.

2.7 CGE-LIF

CGE-LIF was performed according to Callewaert

et al. [47] on an Applied Biosystems ABI PRISM 3100-Avant

genetic analyzer (class B argon laser emitting at 488 nm),

equipped with an Applied Biosystems 3100-Avant

Genetic Analyzer Capillary Array (four capillaries in

parallel cut to an effective capillary length of 50 cm and

neutrally coated with a permanent coating, not specified by

Applied Biosystems). Due to the fixed instruments

setup the inlet side represents the cathode while the anode

is at the outlet side. Undiluted POP-6 polymer

(Applied Biosystems ]4316357) was used as separation

matrix. Samples were diluted 1:10 in Hi-Di Formamide

(Applied Biosystems ]4311320C) and injected for 5 s at

15 kV. Separation was performed for 130 min at 15 kV and

301C without modifications in hardware and software.

For method validation a defined amount of GeneScan-500

ROX Standard (Applied Biosystems ]401734E) was added to

the samples after diluting with Hi-Di Formamide.

This standard, containing 15 base pair (bp) fragments of

defined lengths, was used for normalizing migration

times by linear regression (polynomial 2nd order). There-

fore, obtained migration times of bp standard peaks were

plotted against their individual size in bp. Migration time of

each N-glycan peak was converted into migration time

in bp with respect to this linear regression (polynomial 2nd

order).

To determine the LOD a dilution series of the fluor-

escent dye APTS was analyzed by CGE-LIF using the

same instrument setting as used for glycan samples. For

spiking experiments the N-glycans NA2 and A2F were

purchased from Sigma-Aldrich. These N-glycans were

fluorescently labeled and purified as described above.

Additional structures for spiking experiments were obtained

by sequential exoglycosidase digestion (SED) of these

standards.

2.8 SED

For sequential trimming of N-glycans, released from

the influenza A virus HA, the following exoglycosidases

were used: Glyco a(1–3,4,6) galactosidase, Glyco sialidase A,

Glyco b(1–4,6) galactosidase, Glyco b-N-acetylhexosamini-

dase, Glyco a(1–2,3,6) mannosidase (all purchased

from Europa Bioproducts, Cambridge, UK). Aliquots of

the HA0 N-glycan pool were incubated overnight at

371C with the exoglycosidases (single and in combination)

in a total reaction volume of 10 mL. SED was

performed according to the protocols of the supplier.

Subsequently, the digested N-glycans were analyzed by

CGE-LIF.



3 Results

The aim of the present study was the establishment of a

simple, robust, and reproducible, but also sensitive N-glycan

analysis method. The membrane glycoprotein HA of

mammalian cell culture-derived influenza A virus was used

for method establishment and validation. The method should

be applicable as a tool for monitoring HA N-glycosylation

pattern during influenza A vaccine production.

3.1 Illustration and verification of the method work-

flow

A schematic overview of the method is shown in Fig. 1. The

first step of the workflow is sample preparation, in which a

fast and easy purification and concentration of mammalian

cell culture-derived influenza A virus is required. Therefore,

a consecutive stepwise ‘‘g-force gradient centrifugation’’

method was established. The optimum g-force was deter-

mined for each step of centrifugation, removing consecu-

tively cells and cell debris from finally pelletized virus

particles.

Afterwards, viral proteins were separated by SDS-PAGE.

The purification success was verified by visual inspection of

the gels (Fig. 3). By applying the optimized consecutive

centrifugation steps, almost no host-cell proteins were

observed beside viral proteins on the gels. This method was

applied for all further experiments. Viral proteins were

identified after separation on SDS-PAGE by tryptic digestion

and LC-MS/MS (Fig. 3 and Table 1). The gels show clear

bands of viral proteins, whereas the first band contains, due

to their similar molecular weight, not separated NA tetra-

mers and HA0 trimers. As next steps in N-glycan analysis,

deglycosylation [50], labeling and finally N-glycan separation

(adapted from Callewaert et al. [27, 47] for influenza A virus

HA0) were established. In addition, sensitivity and dynamic

range of the LIF detector, along with run-to-run reproduci-

bility concerning signal intensities and migration times,

were investigated. With a dilution series of the fluorescent

dye APTS, the LOD was determined to be at least 5 fmol/L.

The measurements showed a linear dynamic range of three

orders of magnitude from 2 pmol/L up to 2 nmol/L. Data

from samples with APTS concentration above 5 nmol/L

could not be evaluated due to the detector cut-off at

approximately 9000 RFU. For establishment of the degly-

cosylation, labeling, and N-glycan separation method,

bovine IgG was deglycosylated in gel. Extracted N-glycans

were labeled with APTS, desalted and analyzed by CGE-LIF.

The resulting electropherogram (Fig. 2B) was compared

with previously published data of bovine IgG N-glycosyla-

tion pattern [51] (Fig. 2A). Identical N-glycan structures are

marked with I–IV in the corresponding electropherograms.

A schematic overview of corresponding structures is shown

in Fig. 2B. To confirm identity of these peaks, N-glycans

with known structure typically attached to bovine IgG

N-glycans (I–IV) were spiked to the sample. Resulting

electropherograms were evaluated regarding migration

times. As an example, results for one spiking experiment

are shown in Fig. 2C. Reproducibility of the CGE-LIF

method was evaluated by measuring the same bovine IgG

N-glycan sample three times independently. For data

evaluation the four identified peaks from literature and one

additional peak (Fig. 2B and C) were numbered serially.

Peak heights of the five considered peaks and SD were

calculated in % of total peak height (viz.: heights of the

peaks taken into account were added-up and set to 100%)

(data not shown). SD of peak heights range from 0.3 to

1.18%. In addition reproducibility of migration times was

analyzed for these five peaks (SD range from 0.0125 to

0.0296 min). With a mean SD for peak heights of 70.67%

and for the migration times of 70.0194 min, high short-

term reproducibility of CGE-LIF could be demonstrated.

Long-term reproducibility was investigated by repeated

preparations and measurements of the bovine IgG N-glycan

pool over a period of several months (bovine IgG was used

as a control in each new sample preparation of HA

N-glycans). Analysis of the corresponding set of electro-

pherograms and collected data (not shown) indicated a long-

term SD for tmigo0.08 min. The long-term SD for peak

heights was less than 0.5% and the long-term SD for peak

areas less than 0.65%, respectively.

Subsequently, the whole workflow (Fig. 1) was applied for

N-glycan analysis of mammalian cell culture-derived

influenza A virus HA0. First, reproducibility of sample

preparation was verified. For that, MDCK cells were cultivated

in a roller bottle and infected with influenza A/PR/8/34

(H1N1). Virus containing supernatant (72 hpi) was aliquoted

into three samples of equal volumes of approximately

50 mL. The three aliquots were processed in parallel as

described before. Virus purification was checked by

SDS-PAGE (Fig. 3), which indicated a sufficient virus

purification quality. Although some host cell proteins

remained in the samples, virus protein bands are dominant.

HA0 bands were assigned according to their molecular weight

(Fig. 3 and Table 1). HA0 bands were excised and processed

for N-glycan analysis as described above. To confirm

protein identity, deglycosylated bands were additionally

analyzed by LC-MS/MS (data not shown). MS/MS spectra

also confirmed that deglycosylated HA0 bands only contained

the HA protein and no other co-migrating host-cell proteins.

Table 1. Proteins identified by LC-MS/MS

Protein Molecular

weight (Da)

NCBInr

number

MASCOT

protein score

4�NA 4� 50 111 gi|8486128 256

3�HA0 3� 63 341 gi|8486126 95

2�HA0 2� 63 341 gi|8486126 126

HA0 63 341 gi|8486126 174

NA 50 111 gi|8486128 205

NP 56 134 gi|8486126 252

Matrix protein 1 27 875 gi|8486126 467



After fluorescent labeling, samples were desalted and APTS

conjugated HA0 N-glycans were separated from dye excess

by SEC. Pooling of APTS conjugated HA0 N-glycan

containing SEC-fractions was based on examination by

fluorescence scanning with the Typhoon Imager.

After concentration, N-glycan pools were analyzed by

CGE-LIF as described above. Exemplarily, a CGE-LIF

electropherogram of a HA0 N-glycan pool is shown in

Fig. 4A. In the following, these electropherograms are

termed as ‘‘fingerprints’’. To characterize N-glycan

structures related to these peaks, the HA0 N-glycan pool was

digested sequentially with exoglycosidases as described

above. To facilitate interpretation of the data obtained,

all major peaks in the HA0 fingerprint were serially

numbered (Fig. 4B). Digestion of the HA N-glycan pool

with a-galactosidase resulted in the reduction of the

total number of peaks in the electropherogram (data not

shown). Peaks with higher migration times (Nos. 7 and

9–15) were no longer present while peaks 1–6 and 8

remained in the new electropherogram or showed increased

intensities (data not shown). Additional incubation

with b-galactosidase, b-N-acetylhexosaminidase and

a-mannosidase caused further shifts to lower migration

times of these remaining peaks. Data from this sequential

exoglycosidase digestion clearly indicated the presence of

complex N-glycans, some with a terminal a-galactose (Nos. 7

245 kDa

123 kDa

42 kDa

77 kDa

30 kDa

25.4 kDa

1 2 3

HA0

remaininghost cellproteins

M1

NA, NP

4 x NA, 3 x HA0

2 x HA0

2 x NA

Figure 3. SDS-PAGE of viral proteins from mammalian cellculture-derived influenza A/PR/8/34 (H1N1) virus. Samplealiquots 1, 2 and 3 were taken from a single roller bottle, 72 hpi. The cultivation broth was purified and concentrated byconsecutive stepwise ‘‘g-force gradient centrifugation’’. Proteinswere identified after tryptic digestion by LC-MS/MS (neuramini-dase (NA), neuraminidase tetramer (4�NA), hemagglutinin(HA0), hemagglutinin trimer (3�HA0), hemagglutinin dimer(2�HA0), nucleoprotein (NP), matrix protein 1 (M1) and remain-ing host-cell proteins). HA0 bands excised for N-glycan analysisindicated by rectangle.

B

C

A

Figure 2. Electropherograms of APTS labeled bovineIgG N-glycans. (A) CE-LIF electropherogram; correspondingN-glycan structures are marked with I–IV. Reprinted from[51], with permission. (B) CGE-LIF electropherogram obtainedafter in-gel-deglycosylation; corresponding N-glycanstructures are marked with I-IV. Symbols indicating themonomers: J, b-D-galactose; & , b-D-N-acetylglucosamine;�, b-D-mannose, ., a-L-fucose. (C) CGE-LIF electropherogramobtained after in-gel-deglycosylation; spiked and unspikedwith N-glycan I; corresponding N-glycan structures aremarked with I–IV. The increase in peak height due tospiking is indicated by the dashed arrow; � additional peakconsidered for reproducibility testing.



and 9–15), others with a terminal b-galactose (Nos. 1–6

and 8). Besides the HA0 N-glycans, an APTS peak and some

APTS impurities [6] are present in the fingerprints. In

between these two sets of signals, low-intensity peaks of

some smaller oligosaccharides could be observed. These

small N-glycans (see Fig. 4A) are most likely fragments of

the more complex N-glycans, which represent the major

peaks in the electropherogram (see Fig. 4B, peak-nos. 1–15).

For verification of this assumption, standards (purchased

directly or obtained via SED of these standards) of such

small N-glycans (e.g. trimannosylchitobiose core with or

without fucose and fucosylated chitobiose) were APTS-

labeled and spiked to the HA0 N-glycan pool, as described

for identification of bovine IgG N-glycans. These standards

co-migrated with some of the peaks, indicating that these

small N-glycans of the HA0 glycan pool consist of one to

eight monomers. Structures of some of the small glycans

identified are included in Fig. 4A (a-l). Reproducibility of

HA0 N-glycan fingerprints from the three roller bottle

aliquots was investigated concerning number, height, area

and migration time of the peaks. Data for peak height, peak

area, and migration time were obtained by analyzing the raw

data with respect to the GenScan bp size standard using the

GenMapper Software. Heights and areas of the serially

numbered peaks were added and set to 100% total peak

height and total peak area, respectively. For each of these

peaks, height and area are presented in percentage of total

peak height or area, respectively. The average peak heights

(data not shown) and peak areas of the three roller bottle

aliquots were plotted over the peak number and error bars

were included, indicating the calculated SD of peak areas

(Fig. 5A). Mean SD was calculated as the average SD of

these 15 major peak SDs. For evaluation of migration time,

raw data of HA0 N-glycans were normalized with respect to

the peaks of the GenScan bp size standard by linear

regression (polynomial 2nd order). Therefore, migration

times of bp standard peaks were plotted against their indi-

vidual size in bp (data not shown). Migration time of each

HA0 N-glycan peak was converted into migration time in bp

with respect to this linear regression. Overall, an excellent

sample preparation reproducibility regarding peak height

and peak area (Fig. 5A) was obtained. An even better repro-

ducibility is given for the normalized migration times with a

mean SD of 70.26 bp. For visual inspection the HA0 N-glycan

fingerprints were overlaid (Fig. 5B). After testing the repro-

ducibility of the sample preparation using samples from a

single batch of mammalian cell-culture derived influenza A

virus, the developed method was used for profiling HA0

N-glycosylation patterns produced in different batches.

3.2. Characterization of batch-to-batch

reproducibility in USP

MDCK cells were cultivated in three T175 cultivation flasks

and infected with influenza A/PR/8/34 (H1N1) virus in

parallel as described above. One sample from each flask was

taken 72 hpi and processed in parallel, as described for the

roller bottle aliquots. Virus purification by ‘‘g-force step

gradient centrifugation’’, SDS-PAGE and identification of

fractions containing APTS conjugated HA0 N-glycan after

SEC gave comparable results to those obtained for the roller

bottle aliquots (data not shown). Again, HA0 N-glycan

fingerprints from the three parallel batches (T175 flasks)

were compared concerning peak number, peak height, peak

area, and migration times. Data evaluation was performed

as described before (Fig. 6A and B). Similar to the results

obtained for reproducibility of sample preparation, a good

RF

U

tmig in mintmig in min

750

00 70

APTS and itsimpurities

small N-glycans HA0N-glycans

1 2

3

4

5

6

7

89

10

11

12

13

15

35 550

RF

U

500 14

a

bc def

g

h i jk l

a

A B

b

c

d

e

f

g

h

i

j

k

l

Figure 4. HA0 N-glycan fingerprint of mammalian cell culture-derived influenza A/PR/8/34 (H1N1) virus sample of a roller bottle. (A) APTSpeak marked by an arrow; braces indicate peaks of small N-glycans and more complex HA0 N-glycans (structures of some of theidentified small N-glycans (a-l) are given, for symbols indicating the monomers see Fig 2B); dashed circle indicates zoomed area of HA0

N-glycan fingerprint shown in Fig. 4B. (B) Zoom of HA0 N-glycan fingerprint; major N-glycan peaks serially numbered (1–15).



batch-to-batch reproducibility of the USP could be shown

regarding peak height (mean SD70.47%) and peak

area (mean SD70.93%). Again, excellent reproducibility

was given for the normalized migration times, with a mean

SD of 70.19 bp. Compared with the results obtained

from the three roller bottle aliquots, SDs are comparable

and differences are negligible. Moreover, data analysis

indicated that influenza A virus produced in roller bottles

and in T175 resulted in identical and reproducible HA0

N-glycan fingerprints. With respect to sample preparation,

reproducibility of CGE-LIF equipment and workflow for

influenza A virus HA0 N-glycan analysis were more than

satisfactory.

4 Discussion

It is well known for recombinant glycoprotein and antibody

production [11, 14, 15, 17, 18] that selection of host cells and

cell culture conditions affect the N-glycosylation pattern. In

contrast, comparatively little information is available for

manufacturing of glycosylated antigens used as animal and

human vaccines. To some extent this is related to the

complexity in vaccine manufacturing, where typically whole

virus particles containing the immunogenic target mole-

cules have to be produced and purified rather than

individual recombinant proteins. Also, initiation of an

immune response while avoiding negative side effects is

an extremely challenging task depending on a variety of

factors, including the glycosylation of antigens. However,

systematic studies have also been impeded by the lack of a

fast, simple, and robust method for analysis of glycan

profiles during USP but also DSP. A wide range of strategies

(chromatographic profiling, MS, NMR, and capillary separa-

tion techniques) for analyzing N-glycosylation has been

established [19–24, 26–28]. Each of these techniques has

advantages as well as drawbacks. Choosing one, respectively,

a set of these methods for a given problem can become a

time- and labor-intensive task. For example, NMR provides

detailed structural information, but is a relatively insensitive

A

B

Figure 5. Average peak areas of major peaks in HA0 N-glycanfingerprints of three roller bottle aliquots. (A) Average peak areaagainst peak number (mean SD70.63 %), (B) HA0 N-glycanfingerprints of three roller bottle aliquots.

A

B

Figure 6. Average peak areas of major peaks in HA0 N-glycanfingerprints of three T175 flask samples. (A) Average areaagainst peak number (mean SD70.93%). (B) HA0 N-glycanfingerprints of three T175 flask samples.



method (nmol), which cannot be used as a high-throughput

method. Using MS is more sensitive (fmol) than NMR and

applicable for high-throughput analysis. However, quantifi-

cation can be difficult and only unspecific structural

information could be obtained without addressing linkages

of monomeric sugar compounds. Both techniques require

extensive sample preparation and also fractionation of

complex glycan mixtures before analysis to allow evaluation

of the corresponding spectra. Furthermore, a staff of highly

skilled scientists is required to ensure that these

two techniques can be performed properly. HPLC and

2-D-HPLC profiling is also quite sensitive (fmol, depending

on the detection method) and allows high sample through-

put as well as quantification, but no direct structural

information is given. Techniques based on enzymatical

treatment can be very sensitive and result in detailed

structural information, but require a combination with other

methods like HPLC and MS. Other techniques like lectin or

monoclonal antibody affinity only provide preliminary data

without giving definitive structural information [25, 52]. Use

of CE techniques for glycan separation provides automated

sample handling, short-run times, and high resolution [53].

In combination with LIF-detection of fluorescently labeled

glycans, CE separation techniques seem to be superior to

HPLC and PAGE, by providing higher separation efficien-

cies, yielding relatively short analysis times and requiring

lower amounts of sample, reagents, and solvents [54, 55]. In

particular, these advantages become apparent in CGE

separation using a capillary DNA-sequencer, which is

constructed for high-throughput analysis with high repro-

ducibility and high sensitivity. Furthermore, these instru-

ments are relatively simple to operate in routine applications

and allow the analysis of up to 96 samples in parallel.

Depending on parameter settings, an analysis time of about

1 min per sample can be achieved in high-throughput mode.

The use of such a 96-capillary array DNA-sequencer based

on CE-LIF technology for large-scale carbohydrate analysis

of enzymatically digested cellohexaose and lignocellulosic

biomass is described by Khandurina et al. [29, 31]. The

electrokinetic separation system of the ABI PRISM 3100-

Avant genetic analyzer, used in the present work, is based

on a neutrally coated fused-silica capillary array (four in

parallel), filled with a linear polyacrylamid-gel/borate buffer

system, where the charged solutes migrate in terms of their

electrophoretic mobilities along the applied electric field.

According to several publications [56–60], it can be

speculated, about competing separation mechanisms within

this system. Most likely, the separation is not only

dependent on the mass-to-charge ratio, which is for sure

the major effect, but also influenced by the sieving effect of

the polymer gel matrix and the borate complexation of the

glycans due to the buffer system. In addition to the sieving

effect, the viscosity of the gel matrix (increases exponentially

with its concentration [60]) positively influences band

dispersion. That is due to the reduced diffusion phenomena

and velocity dispersion compared with open tubular systems

[58]. This means, neutrally coated and gel filled capillaries

show almost no peak distortion. The borate complexation

modulates retention and migration of carbohydrates [56, 57,

59] by providing additional, partial negative charges. This is

clearly indicated by the quality of data obtained for bovine

IgG N-glycosylation compared with those previously

published by Raju et al. [51] (Fig. 2A). In particular, peaks

of low-abundant N-glycans of the bovine IgG N-glycan pool

are, in contrast to Raju et al. [51], clearly detectable and

structures could be assigned easily by spiking experiments

(data only partially shown, cf. Fig. 2). Data evaluation

showed a higher peak capacity (increased by a factor of 2.5)

and better resolution for N-glycans, separated in CGE mode

by the DNA-sequencer compared with CZE mode separa-

tion of Raju et al. [51]. Recently, Domann et al. [61]

compared normal phase chromatography and CGE. Their

findings did not match the results reported here. In contrast

to their work, the presented workflow and the instrumenta-

tion resulted not only in better reproducibility (regarding

peak heights, peak areas, and normalized migration times –

even for real samples), but also in better peak resolution and

sensitivity. However, as Domann et al. used a ‘‘ProteomLab

PA800 CE’’ system and a ‘‘ProteomeLab Carbohydrate

Labelling and Analysis Kit’’ (both from Beckman-Coulter;

Fullerton, CA, USA), their set of samples including work-

flow and instrumentation were different. Therefore, their

results may not be directly comparable to those presented

here.

Compared with the findings of Raju and Domann, the

use of the capillary DNA-sequencer allows the establish-

ment of a relatively simple and robust, but sensitive and

reproducible N-glycan analysis method. Using LIF detec-

tion, known for high sensitivity [62, 63], a LOD down to the

low femtomolar range was obtained. The workflow was

developed as a quality control tool for analysis of glycosy-

lated viral membrane proteins, to characterize variations in

the N-glycosylation due to the production process. Repro-

ducibility studies have been conducted regarding virus

purification and sample preparation (Figs. 3 and 5). Virus

purification directly from complex cell culture supernatant

by consecutive stepwise ‘‘g-force gradient centrifugation’’,

resulted in dominant virus protein bands and some less

intense bands of remained host-cell proteins on the SDS-

gels (Fig. 3). In spite of multiple centrifugation steps, this is

most likely due to co-purification, respectively, co-pelleting,

because of their interactions with virus particles. As already

mentioned in the Results section, it was determined by

LC-MS/MS that the deglycosylated band only contained the

HA protein and no other co-migrating host-cell proteins.

Regarding the complete CGE-LIF electropherogram of the

HA0 N-glycan pool (Fig. 4), an APTS peak and some

impurities can be seen. To ensure that all signals were due

to the HA N-glycans, the background of CGE-LIF was

checked by blank injections of sample buffer. No signals

showed up in the electropherograms (data not shown).

Additionally, the background of the whole sample prepara-

tion workflow was determined by processing, blank SDS-gel

bands and bands close to the HA protein band. Again, no



N-glycan signals showed up in the corresponding electro-

pherograms (data not shown). Although SEC was optimized

regarding bed length and SEC material, this indicates that

excessive APTS dye was not completely removed. Reasons

could be the column geometry (square deep-well plates), and

still insufficient separation length. The availability of well

plates with increased height and of alternative SEC materi-

als with smaller particles and smaller intraparticle pores

(both increasing separation efficiency) would help to over-

come the imperfect separation. Signals of small oligo-

saccharides (up to eight monosaccharide units) in the

electropherograms of the HA0 N-glycan pool (Fig. 4A), do

not appear in the bovine IgG N-glycan fingerprints (Fig. 2B

and C). The appearance of such signals in the cell culture-

derived samples can be caused by the microheterogeneity of

N-glycans attached to, or by degradation of N-glycans, as a

consequence of the sample preparation process. Due to the

fact that all viruses rely on the host-cell glycosylation

machinery during viral protein synthesis and assembly [64],

smaller oligosaccharides in the HA0 glycosylation pattern

could also reflect a breakdown of N-glycan biosynthesis of

infected and stressed cells at the end of the virus production

phase. Currently, the developed method is being used to

analyze HA0 N-glycosylation patterns at several consecutive

timepoints during virus replication. Data evaluation of the

electropherograms of the three roller bottle aliquots with

respect to peak number, peak height, peak area, and

migration times (Fig. 5) revealed excellent reproducibility

with marginal average SDs. For monitoring and

interpretation of glycan profiles during USP in vaccine

manufacturing, batch-to-batch reproducibility has to be

considered. In particular, changes during the time course of

infection are to be expected, e.g. differences in glycan

fingerprints in between early and late stage of intracellular

virus replication or differences due to unspecific degrada-

tion of glycans and glycoproteins taking place towards the

cultivations. Obviously, significant batch-to-batch alterations

in the HA0 N-glycosylation pattern performed under similar

conditions would result in significant problems to distin-

guish between deliberate modifications in USP conditions

or the impact of process failures and batch-to-batch variation

of standard runs. Therefore, in a first step, reproducibility of

HA0 N-glycan fingerprints from samples of different

upstream cultivation batches, was investigated (Fig. 6).

Surprisingly, a high reproducibility of HA0 N-glycosylation

patterns was observed in three parallel batches for similar

cell culture conditions. Due to the intrinsic complexity of

mammalian cell culture-based vaccine production processes

this constancy in glycosylation pattern was not expected and

more detailed investigations in other cultivation systems

need to be performed to confirm this result. In case similar

results would be obtained, glycan fingerprints will be a

powerful tool to monitor cell culture-based vaccine manu-

facturing under GMP guidelines, to investigate the impact

of process failures on product quality, or to characterize the

influence of modifications in process design and scale-up.

Minor modifications of the workflow would in addition

allow the analysis of samples accumulating in DSP of viral

vaccines and, therefore, significantly extending the range of

possible applications. Of course, characterization of glyco-

sylation patterns of recombinant therapeutic glycoproteins

and antibodies would also be feasible with minor adaptation

of the presented method. Also in other fields of application

the method has great potential. Starting with the separation

of complex protein mixtures by 1-D/2-D gel electrophoresis,

this method could be used for N-glycan analysis of any other

glycoprotein. Moreover, pre-purified glycoproteins, e.g. by

chromatography or affinity capturing, can be handled as

well by the method, substituting the gel separation and in-

gel-deglycosylation step with in-solution-deglycosylation and

continuing after protein and enzyme precipitation, as

described above. Therefore, a wide range of potential

applications for the developed method is given ranging from

medical diagnosis, e.g., in chronic inflammation recogni-

tion, to early cancer diagnostics, where changes in the

glycosylation patterns of proteins are strong indicators for

disease [65, 66]. Here, variations in the N-glycosylation

pattern could simply be identified by comparing the

obtained fingerprints regarding peak numbers, heights, and

migration times. Another option would be the establish-

ment of a ‘‘glycome fingerprint’’ approach analogous to the

promising proteomics approach published recently by

Keidel et al. [67]. Instead of using proteins as disease

markers, by comparing the proteomes of one individual

(one genome) at consecutive timepoints (before and after

occurrence of the disease), the glycome of individuals would

be analyzed as indicator for disease or identification of risk

patients.

5 Conclusion and outlook

A method is described, which allows glycosylation pattern

profiling of glycoproteins. The method is relatively simple

and robust, but nevertheless highly sensitive and reprodu-

cible. It presents a powerful tool to monitor variations in

the glycosylation pattern of proteins without requiring

complex structural investigations. For fluorescently labeled

glycans, the LIF detection allows an LOD down to the low

femtomolar range. N-glycans were analyzed via generation

and comparison of glycome ‘‘fingerprints’’. For the genera-

tion of these fingerprints a capillary DNA-sequencer was

used. Examples are shown for monitoring HA glycosylation

of influenza A/PR/8/34 (H1N1) produced in mammalian

cell culture. The developed workflow is applicable, however,

for characterization of any other influenza virus strain or

subtype for both viral membrane glycoproteins (HA, NA).

Therefore, it allows the evaluation and monitoring of USP

and – with minor modifications – DSP of influenza A virus

vaccine production. Future work will be directed towards

generation and extension of a ‘‘glycan-fingerprint-library’’,

where structural information of known N-glycans is stored

together with corresponding normalized data like migration

times. This database will allow fast and straightforward



structural identification of N-glycans of real samples by

simple assignment of peaks of those fingerprints to

N-glycans with known structures. This can be done fully

automated via migration time matching of real samples with

normalized migration times of N-glycans from correspond-

ing database in high-throughput mode using a 96-CGE

system.

We would like to acknowledge Liane Geisler for the assis-tance in analyzing the samples with the capillary DNA-sequen-cer. Furthermore, we thank Dr. Michael Wolff for fruitfuldiscussions.

The authors declare no conflict of interest.

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