Glycosylation for biopharmaceutical drugs

Ricky Connolly Biotechnology, Dublin City University; email: ricky.connolly2@mail.dcu.ie

Abstract Since the mid 2000s, the patents for many blockbuster drugs have begun to expire. This

is the driving force behind the current great development in the biopharmaceutical

industry, the ‘second generation’ biopharmaceuticals. This new trend is focussed on

modifying existing protein therapeutics in order to enhance their pharmacological,

biological, and structural properties. These modifications include but are not limited to:

generation of fusion conjugates, incorporation of chemical modifications such as

pegylation, and, crucially for this paper, modification of glycosylation profiles. The goal

of this paper is to outline the chemical and biological basis of protein glycosylation, to

examine the pharmacological and structural implications of glycosylation, to compare

and evaluate the current production strategies, and to survey the current range of

analytical methods available to characterise glycoprotein therapeutics.

Abstract | DCU

Table of Contents Introduction ................................................................................................................................. 3

Overview ...................................................................................................................................... 3

Glycan synthesis ........................................................................................................................... 4

Stability .......................................................................................................................................... 6

Aggregation .................................................................................................................................. 6

Crosslinking ................................................................................................................................. 7

Proteolysis .................................................................................................................................... 7

Oxidation ..................................................................................................................................... 7

pH ................................................................................................................................................ 7

Kinetic Denaturation ................................................................................................................... 8

Chemical Denaturation ............................................................................................................... 8

Temperature ................................................................................................................................ 8

Pharmacology .............................................................................................................................. 9

Receptor Binding ......................................................................................................................... 9

Circulatory lifetime .................................................................................................................... 10

Bioavailability ............................................................................................................................. 10

Distribution ................................................................................................................................ 11

Clearance rates ........................................................................................................................... 12

Antibody function ...................................................................................................................... 12

Immunogenicity ......................................................................................................................... 12

Glycosylation and host cells .................................................................................................. 13

Mammalian Cells ....................................................................................................................... 14

Yeasts .......................................................................................................................................... 15

Bacteria....................................................................................................................................... 16

Analytical methods ................................................................................................................... 18

Mass spectrometric .................................................................................................................... 18

Chromatographic ....................................................................................................................... 19

Electrophoretic .......................................................................................................................... 20

Bioaffinity methods .................................................................................................................... 20

Bioinformatics ........................................................................................................................... 22

Complexity of glycan structures ................................................................................................ 22

Prediction tools .......................................................................................................................... 22

Glycobiology databases .............................................................................................................. 23

References ................................................................................................................................... 24

DCU | Introduction

Introduction The human genome contains at least 30,000 protein-coding genes, and through

alternative mRNA splicing, these give rise to over 100,000 proteins (Venter, 2001). The

diversity of the human proteome is further

magnified by post-translational modification of

proteins. At least 50 percent of mammalian

proteins are glycosylated (Zafar, 2011). More

than two thirds of the 200 or so biopharma-

ceutical products licenced for sale in the

United States and European Union are

recombinant human proteins (Li, 2010). In

2010, five of the top ten selling pharmaceutical

products were recombinant human proteins

and this is projected to rise to eight of the top

ten by 2014 (Hirschler, 2010). Additionally,

over 70 percent of the therapeutics currently in

clinical trials are glycosylated human proteins (Sethuraman, 2006).

Overview

Glycosylation is defined as the covalent attachment of oligosaccharide moieties (glycans)

to the side chains of amino acid residues of proteins. There are at least five different

classes of glycosylation, each defined by

the amino acid the glycan in linked to and

the type of linkage used. By far the most

common of these are N-linked and O-

linked glycosylation (Apweilier, 1999).

This review will focus solely on N-linked

glycosylation because it is more common

type found in human therapeutic protein

therapeutics (Pandhal, 2010). N-linked

glycosylation involves the enzymatic attachment of the N-Acetylglucosamine residue at

the terminal end of the glycan to the amide group of an asparagine residue by means of a

β1 glycosidic linkage (Geyer, 2006).

Introduction | DCU

The asparagine must be located within the three residue sequence Asparagine-X-

Serine/Threonine, where X represents any amino acid except proline, which inhibits

attachment of the N-glycan through stearic hindrance caused by its rotationally-locked

side group (Shyama, 2010). There are further structural requirements in addition to the

Asp-X-Ser/Thr sequon, mostly concerning the three-dimensional localisation and

accessibility of the sequon within the folded protein (Apweilier, 1999).

Glycan synthesis

N-glycosylation takes place in the endoplasmic reticulum, at the same sites as protein

translation. The first step in glycan synthesis involves the addition of two GlcNAc

residues and five mannose residues to the membrane-anchored dolichol-PP. The

dolichol-PP-Man5GlcNAc2 group is then flipped to the inner membrane side of the

endoplasmic reticulum by the enzyme RFT1 (Pandhal, 2010).

The core oligosaccharide (Glc3Man9GlcNAc2) is constructed on the GlcNAc residue by

a series of glycosyltransferases. After this, the glycan is transferred to a sequon-labelled

asparagine residue on the protein chain as it emerges from the ribosome (Pandhal, 2010).

DCU | Introduction

The glycan is trimmed by glucosidase I and II to remove the α1,2-linked (Shailubhai,

1987) and α1,3-linked (Saxena, 1987) glucose residues, respectively. This leaves us with a

Man9GlcNAc2 structure. Next, α1,2-mannosidase removes one of the α1,2-linked

mannose residues. The Man8GlcNAc2 glycan is then exported to the Golgi apparatus.

Here, more α1,2-mannosidases remove several mannose residues, producing

Man5GlcNAc2. After this, the glycosylation pathway diverges into different patterns of

residue trimming and addition, catalysed by a series of glycosidases and

glycosyltransferases (Pandhal, 2010).

This results in three distinct prototypic classes of glycan structure into which the

majority of glycans fall: complex, hybrid, and oligomannose (Kornfeld, 1985).

Oligomannose glycans contain only mannose residues in addition to their core structures.

Hybrid glycans can contain a diverse range of residues including galactose, glucoronic

acid, and xylose (in plants). Complex glycans resemble hybrid glycans but they come

with varying degrees of fucosylation and sialylation (Pandhal, 2010). Sialylation is often

vital for correct protein function, this will be discussed later.

Glycans are constructed from monosaccharide units linked together with glycosidic

bonds. Unlike peptides and nucleic acids, one monosaccharide unit can be linked to

multiple other units. This is called branching. Biantennary glycans are the most common,

but triantennary and tetrantennary glycans are not unheard of (Campion, 1989). Another

common structural feature is to have a single (β1,4) GlcNAc residue linked to the first

branching point mannose unit. This bisecting GlcNAc residue is often involved in

signalling (Yoshimura, 1998). The molecular structures, branching types and families of

Stability | DCU

glycans attached to a protein describe its microheterogeneity in terms of glycosylation.

This is distinct from the macroheterogeneity, which is described by the total number of

glycans attached to the protein and their positions.

Stability

A protein instability is defined as a physical or chemical vulnerability that is prone to

altering the structural conformation or activity in a detrimental way. Although they have

high therapeutic efficacy, the main drawback to pharmaceutical use of proteins is their

inherent structural and chemical instabilities. These impose limitations on the protein

production and purification stages, product formulation, storage and transport, and half-

life in the body. Glycosylation has been shown to ameliorate many of these instabilities.

In this section, the major protein instabilities will be outlined, and the efficacy of

glycosylation on these will be investigated.

Aggregation

Proteins are very complex molecules with hundreds if not thousands of exposed

functional groups. This makes non-native aggregation a very common problem for

protein biopharmaceuticals. Aggregation can be caused by relatively small changes in the

protein structure (Saluja, 2008). Aggregation can drastically reduce the biological

function of a protein (Philo, 2009) and in some cases can induce an immunogenic

reaction in patients (Rosenberg, 2006). Glycosylation has been shown to prevent the

formation of protein aggregates (Kayser, 2011). The likely explanation is that the bulky

spatial nature of glycan moieties provides a level of stearic repulsion between proteins

(Imperiali, 1999), reducing the likelihood of aggregation (Hoiberg-Nielsen, 2006).

Precipitation

Precipitation is the ultimate effect of protein aggregation. Eventually, the proteins form

aggregates so large that they become insoluble (Chi, 2003). Precipitation is a major

problem for biotherapeutic product formulation because it is desirable to store protein

solutions at relatively high concentrations, but at high enough concentrations most

proteins will form aggregates and precipitate out of solution (Wang, 2005).

Glycosylation decreases the propensity to form insoluble precipitates for many proteins

(Kayser, 2011). It has been shown that the decrease in insolubility is directly

DCU | Stability

proportional to the size and number of glycans present (Tams, 1999). One possible

explanation for this phenomenon is that glycans are more soluble than peptides, and they

confer some of this solubility to the glycoprotein as a whole.

Crosslinking

Crosslinking, also known as polymerisation-induced inactivation, occurs primarily when

the methionine residues of two different proteins form a disulphide linkage. This leads

to the formation of protein oligomers which have diminished biological activity (Wang,

1999). Glycosylation has been shown to prevent chemical crosslinking between proteins

(Runkel, 1998). The mechanism is probably the same as that of aggregation, the mutual

stearic repulsion between glycosylated proteins.

Proteolysis

Proteolysis is the degradation of the peptide backbone through hydrolytic reactions.

These reactions are carried out by the ubiquitous protease enzymes found in all tissues.

They are a major problem from a drug administration perspective because protease-

sensitivity can drastically reduce the level of therapeutic that reaches the site of action

(Tang, 2004). Glycosylation has been shown to inhibit proteolytic degradation (Vegarud,

1975). The most likely mechanism is through stearic blockage of the protease cleavage

sites by the glycan (Russell, 2009).

Oxidation

Proteins are susceptible to oxidative degradation at the level of their primary structure.

This is of particular concern for proteins rich in the more reactive amino acids such as

His, Met, Cys, Tyr and Trp (Manning, 2010), which are prone to accepting free radicals.

Since free radicals are basically unavoidable at all stages of the pipeline from cell culture

to drug administration (even exposure to stray light can be harmful (Kerwin, 2007)),

oxidation poses a serious threat to the stability and functionality of therapeutic proteins.

Glycosylation has been shown to reduce the effects of oxidative damage in at least one

commercial therapeutic (Uchida, 1997). One proposed mechanism for this protection is

that the glycans are ‘soaking up’ the radicals, thus preventing them from reaching the

protein itself (Pristov, 2011).

pH

Proteins are only stable within a limited pH range. pH denaturation begins when the ion

balance disrupts the hydrogen- and ion-bonding capacity of the amino acids. This affects

the tertiary structure of the protein and leads to the formation of non-native chemical

Stability | DCU

bonds as the peptide reconfigures into a more thermodynamically-stable state (Solá,

2009). Glycosylation has been shown to improve the pH stability of protein therapeutics

by up to a 13-fold increase (Masarova, 2001). This marked improvement is due to the

fact that attached glycans decrease the solvent accessible surface area of the protein,

acting as a molecular buffer between the electrostatic forces of the solvent and those of

the protein.

Kinetic Denaturation

Due to their complex nature, protein molecules have several three-dimensional states in

which they are thermodynamically stable, but usually have only state in which they are

functionally active. This means that proteins can undergo kinetic inactivation even at

low temperatures by ‘flipping’ to another stable but inactive state (Arakawa, 2001). It has

been demonstrated that glycosylation increases the kinetic stability of proteins.

Specifically, the level of stability conferred seems to be correlated to the number of

glycans present, their positioning on the protein, and their size (Solá, 2007). This is most

likely because a folded, glycosylated protein has a lower free-energy profile compared to

both the unfolded protein and to the folded-unglycosylated protein (Shental-Bechor,

2008).

Chemical Denaturation

Chemical denaturation can be defined as the loss of structural integrity of a protein in

response to exposure to a chemical agent. One of the primary reasons for chemical

destabilisation is that the protein often has high Van der Waals affinity to the denaturant.

This allows the chemical molecule to intrude into the tertiary structure of the protein,

disrupting the global conformation and reducing functionality (Hual, 2008).

Glycosylation has been shown to promote conformational stability in opposition to

chemical denaturants (Sytkowski, 1991). The probable explanation for this effect is that

glycosylation essentially ‘compacts’ the protein, increasing the strength of its internal

ionic, hydrogen and Van der Waals bonds and reducing the peptide’s affinity for outside

chemical molecules (Solá, 2007).

Temperature

All of the bonds within a protein are sensitive to thermal fluctuations. Outside of a small

temperature range, these bonds will break or form non-native bonds, destroying the

biological activity of the protein (Vogt, 1997). The effects of freezing are less well

studied compared to those of heating, but some comprehensive studies of the

phenomena exist (Bhatnagar, 2007). Glycosylation has been shown to improve the

DCU | Pharmacology

thermal stability range for several therapeutically important proteins including EPO,

alpha 1-antitrypsin, interferon-β, and follicle-stimulating hormone (Solá, 2009). It is

likely that these increases in stability are due to the constraint of peptide mobility caused

by glycan attachment (Wormald, 1999). The magnitude of thermal stabilisation is

proportional to the number and size of the glycan attachments (Wang, 1996).

Pharmacology

Pharmacology is divided into two fields of study: pharmacokinetics and

pharmacodynamics. Pharmacokinetics examines the action of drugs within the body over

a given period of time; profiling distribution, metabolism, and excretion.

Pharmacodynamics studies the mechanisms of action of drugs within the body, studying

the drug-receptor interactions and dose/response profiles. In other words,

pharmacokinetics studies what the body does to the drug, while pharmacodynamics

studies what the drug does to the body (Benet, 1984).

Proteins tend to have poor pharmacokinetic profiles because they are very quickly

cleared by proteolytic degradation pathways, hepatic and renal elimination, and

receptor-mediated endocytosis (Tang, 2004). They have sharp pharmacodynamics

profiles due to their exceptionally high binding affinities with receptors compared to

small molecule drugs and have high turnover rates of their substrates. Glycosylation

strongly affects the pharmacological properties of a protein. In this section, the major

intrinsic pharmacokinetic and pharmacodynamic limitations of proteins are reviewed.

For each, the impact of glycosylation on these limitations are examined.

Receptor Binding

One of the most characteristic traits of proteins is the extraordinarily high affinity with

which they bind to their receptors. This is both as blessing and a curse. A high receptor

association rate allows the design of therapeutics with strong biological efficacy, but it

often means the protein has a very blunt therapeutic response curve (Solá, 2010). This

leads to dosage schemes that require multiple injections per day, with widely fluctuating

levels of drug in the body over the course of the day. For this reason, it is often desirable

to ‘smooth out’ the response curve to a protein therapeutic. In practise, this means

reducing receptor affinity of the protein.

Pharmacology | DCU

Glycosylation has been used to reduce the receptor affinity for several commercially

important protein therapeutics. Darling et al showed that EPO-IRS (the standard form

of human erythropoietin recognized European Pharmacopoeia) showed a 20-fold lower

receptor association rate compared with artificially deglycosylated EPO (Darling, 2002).

Similarly, another study compared the relative receptor binding affinities of several

isoforms of erythropoietin. The EPO isoforms are defined by the total number of sialic

acid residues found on their glycocomponent. The experiment involved measuring the

quantity of each isoform needed to displace inactive EPO from receptors expressed on

the surface of human erythroleukemia cells. There was a direct inverse relationship

between sialic acid content and receptor binding affinity (Egrie, 2001).

The most likely mechanisms by which this reduction in binding affinity can be explained

is that electrostatic repulsion between the sialic acid residues of the glycans and the

receptor serve to decrease the liklihood of receptor binding (Elliott, 2004).

Circulatory lifetime

Glycosylation can have a dramatic effect on the circulatory lifetime of a therapeutic

protein. Comparing the serum half-life of the enzyme ceruloplasmin in it’s a natively-

glycosylated state with that of an artificially deglycosylated variant, the circulatory

lifetime of the deglycosylated variant was found to be an order of magnitude lower

(Morell, 1968). Similarly, the addition of extra glycans (hyperglycosylation) has been

shown to decrease the clearance rate of proteins.

Perlman et al (2003) observed a 4-fold increase in serum half-life of a variant of human

follicle stimulating hormone (FSH) with two addition N-linked glycosylation sites. The

sialic acid content of attached glycans has been shown to be of high importance to

extending the serum half-life of a protein. Sialic residues have a net negative charge at

biological pH. This electrostatic repulsion confers protection from both renal (Kanwar,

1984) and hepatic (Morell, 1971) clearence mechanisms.

Bioavailability

Today the vast majority of protein therapeutics are delivered by parenteral injection

(Soltero 2001). This contrasts with small molecule drugs, which are typically delivered

through oral routes (Nandita, 2003). From a clinical standpoint, it would be very

desirable to have oral-administered protein therapeutics. Unfortunately, there are several

barriers to making this technology a reality.

DCU | Pharmacology

Unless injected directly into the bloodstream, drugs must pass through several

membrane barriers before they can begin systemic circulation, and if the target of the

drug is intracellular, the peptide must pass through the lipid membrane of the cell.

There are four mechanisms by which a protein therapeutic may pass through a

membrane: passive and facilitated diffusion, active transport, and receptor mediated

endocytosis (Kopacek, 2011). The rate at which a drug absorbs in the body is determined

by the rate at which the drug is transported across these barriers.

Glycosylation has been shown to improve protein absorption in several cases. Egleton et

al (2001) demonstrated that the addition of an O-linked glycan to an opioid peptide

icreased its blood brain barrier permeability from 1.0 μl/(min·g) to 2.2 μl/(min·g), with a

comparable increase in measured analgesic activity. Albert et al (1993) produced a

glycosylated, orally-active version of octreotide, a regulatory peptide that inhibits the

production of somatropin and other growth hormones, which had ten times greater oral

bioavailability compared to the parent molecule. Nomoto et al (1998) significantly

improved intestinal uptake of a peptide by the sodium ion-dependent D-glucose

transporter through the addition of a small glycan moiety.

Distribution

Drug distribution throughout the tissues of the body is controlled by blood perfusion,

plasma protein and tissue binding affinity, pH, and membrane permeability (Kopacek,

2011). Controlling the distribution of a drug is vital to ensuring that the drug reaches

the target tissue and that it does not end up in the wrong tissue, where it will have no (or

even adverse) biological effects.

Glycosylation has been shown to improve the tissue distribution of therapeutic drugs.

Sasayama et al (2000) chemically glycosylated human interleukin-1ɑ with an N-

acetylneuraminic acid moiety and monitored the in vivo tissue distribution in rats

following intraperitoneal (IP) injection. Up to five-fold greater levels of the glycosylated

variant were observed in the kidney, spleen, lung, and blood. Similarly, Ceaglio et al

(2008) created a mutant version of interferon-ɑ with four additional N-glycans which

displayed a ten-fold increase in distribution half-life (t1/2β) after ten hours post-injection,

and levels remained detectable 96 hours after injection. The most likely explanations for

the increase in tissue distribution are that the glycoproteins are protected from

proteolytic and immune-inactivation pathways or that the more soluble glycans reduce

the hydrophobicity of the peptide, increasing the rate of transport.

Pharmacology | DCU

Clearance rates

Drug clearance studies measure the rate of removal of drug from circulation. This

mainly takes place in the liver and kidneys. The drugs are carried along by the flow of

blood until they reach the liver, where they are taken up by hepatocytes and are broken

down by nonspecific proteases, before the amino acids are recycled back into the body’s

metabolic cycle (Kahn, 2011). It is advantageous to attempt to reduce the clearance rates

of protein biopharmaceuticals to a minimum so that expensive drug is not wasted. Any

effective reduction of the level of clearance of a therapeutic will be valuable from a

clinical and economic point of view, and glycosylation has shown to be an efficient

strategy to achieve this reduction.

A novel hyperglycosylated variant of human EPO, darbepoetin alfa (DA), was

engineered to display two additional N-linked glycans. In a double-blind, randomized,

cross-over clinical trial in humans, DA showed a 2.5-fold lower rate of clearance (1.6

mL/h·kg versus 4.0 mL/h·kg) (Macdougall, 1999). The reduction in clearance rate

observed for hyperglycosylated proteins has been attributed to the increased sialic acid

content of the introduced glycans (Egrie, 1993).

Antibody function

IgG antibodies have two large biantennary N-linked carbohydrate moities attached to

the Fc effector region . The structure of these glycans has an effect on the chain

orientation, chain spacing and surface residue exposure (Kaneko, 2006). These

differences in structure can alter antibody effector function (Burton, 2006). It has been

shown that IgG antibodies engineered to remove fucose residues from their glycan

component have a much stronger antibody-dependent cell-mediated cytotoxicity profile

compared to wild-type IgGs (Yamane-Ohnuki, 2004). This is of clinical importance

because higher activation of immune system cells can stimulate the body to fight a wide

range of conditions, including cancer (Satoh, 2006).

Immunogenicity

Glycosylation has been shown to help prevent the generation of neutralizing antibodies

against therapeutic drugs. There are several theories which attempt to explain this effect.

One explanation is that, as outlined earlier, glycosylation inhibits the formation of

protein aggregates. Antibodies are often raised more efficiently against aggregates than

individual proteins, so it stands to reason that glycosylation prevents the development of

an immune reaction by inhibiting aggregation of the drug in circulation (Moore 1980).

Another possible explanation of the inhibition of immune response is that the bulky

DCU | Glycosylation and host cells

nature of the carbohydrate moieties provide a degree of stearic hindrance, shielding the

peptide chain below from immune cells (Casadevall, 2002). A further theory is that the

terminal sialic acid residues of glycans provide a degree of electrostatic repulsion, again

preventing immune cell surface receptors from binding (Fernandes, 2002).

Glycosylation and host cells

It is estimated that well over 50 percent of human proteins are glycosylated (Apweiler,

1999), although this figure is disputed (Khoury, 2011). Nevertheless, almost 40 percent

of all approved biopharmaceutical

products are glycosylated (Walsh,

2010). Therefore, for an organism to

become widely used as a producer

strain, it must be able to perform

glycosylation to some extent. Between

2006 and 2010, 58 new

biopharmaceuticals gained approval.

32 of these were produced in

mammalian cell lines and of these, 24

were produced in Chinese hamster

ovary (CHO) cells. It is clear that

CHO cells are still the workhorse of

the biopharmaceutical industry.

Other common host cell systems

include the various mouse myeloma

strains, including NS0 and sp2/0, as

well as yeast cells, mostly Pichia

pastoris and Saccharomyces cerevisiae.

Despite its lack of mammalian

glycosylation machinery, E. coli is still widely used for smaller proteins and antibody

fragments, and E. coli-produced biopharmaceuticals accounted for 30 percent of newly

approved products during the period from 2006 to 2010 (Walsh, 2010).

55%

29%

10%

2% 2% 2% a.

Mammalian

E. coli

Yeast

Insect

Animals

Synthetic

75%

7% 3% 3% 6%

3% 3% b. CHO

NS0

Sp2/0

 rat-mouse hybridhybridomaMurine hybridoma

Murine myeloma

Immortalizedhuman

Glycosylation and host cells | DCU

Mammalian Cells

The obvious choice for producing recombinant human proteins are mammalian cells.

The major advantage of mammalian cells is that they possess the ability to produce

proteins with fully human-type glycosylation (Butler, 2005). Additionally, they are able

to produce large molecular weight proteins, and natively possess the machinery to

conduct correct folding, quality control, and secretion (Demain, 2009).

There are several major limitations to mammalian cells as a producer strain. Mammalian

cells have extraordinarily high cost of culture, mostly due their fastidious media

requirements. A fully validated production process using these cells can cost $2-4 million

per year in growth media alone (Demain, 2009). They also have a slower growth cycle

than microbial producer strains, with doubling times of 12-20 hours, approximately ten

times slower than that of E. coli strains (Sunstrom, 2000).

Mammalian cell lines are susceptible to infection by viruses which are potentially

pathogenic to humans. Infection of a production process can be disastrous and can cause

the entire production facility to be shut down by regulators (Berting, 2010). Whole

batches of product have been lost to viral contamination (Bethencourt, 2009). Their

media requirements are notoriously fastidious. Mammalian cells produce their own

glycosylated proteins, which makes downstream separation of the target glycoprotein

much more difficult.

Historically, mammalian cell culture processes have suffered from low product yields,

but through advances in media and production optimization, gene amplification and

plasmid engineering, this productivity has increased markedly, often reaching expression

levels of 10-15 g/L for some products in CHO cells (Huang, 2010).

In addition to these advances, new producer strains have been developed. The PER.C6

cell line is derived from human retinal tissue and looks to have a future as a major

producer cell line. PER.C6 cells can tolerate very high cell densities in culture; up to 150

x 106 cells/mL have been reported (Golden, 2009), they show robust scale up

characteristics (Xie, 2003), and can produce recombinant protein at very high titres of at

least to 25 g/L (Schirmer, 2010).

DCU | Glycosylation and host cells

Yeasts

Like humans, yeasts belong to the eukaryotic domain. This being so, many of the

metabolic pathways and molecular machinery are conserved between both species,

including much of the glycosylation apparatus (Rich, 2009). The two most common

strains used for industrial production of recombinant proteins are Saccharomyces

cerevisiae and Pichia pastoris. Both strains have had their genomes thoroughly

characterized (Goffeau, 1996) (De Schutter, 2009).

Yeasts have properties that make them attractive as a biopharmaceutical production

system for several reasons. Yeast cells enjoy both the fast growth rates of microbes and

the complex enzymatic machinery of eukaryotes (Verma, 1998). They offer reasonable

yields of recombinant product, yields of up to 9 g/L have been reported (Valdivieso-

Ugarte, 2006). Their growth kinetics and nutritional requirements are well characterized,

so scale-up from lab bench to industrial fermentation is a relatively simple procedure

(Hamilton, 2007).

Yeasts can tolerate very high cell densities, as high as 130 g/L in some strains (Gellison,

1992), magnifying the product yield attainable per litre of culture volume (Cregg, 2009).

Additionally, yeasts can be induced to secrete expressed recombinant therapeutics into

the culture media, simplifying the downstream processing, which typically accounts for

50-80 percent of the total cost associated with a production process (Roque, 2004). Yeast

cells are capable of carrying out N-linked glycosylation at the Asn-X-Ser/Thr motif, but

there are differences between native yeast-produced N-glycans and those produced in

human cells.

Both yeast and human cells share the same initial steps in their N-linked glycosylation

pathways. The Glc3Man9GlcNAc2 glycan precursor is constructed on a membrane

bound dolichol-PP on the endoplasmic reticulum. This precursor is then transferred to

an Asn residue on the peptide as it emerges from the ribosome (Jigami, 2008). This is

carried out by an oligosaccharyltransferase complex consisting of eight subunits; which

differ structurally between humans and yeast, but which carry out the same function

(Kelleher, 2006). After this, the glycan is trimmed by three glucose units and one

mannose unit, leaving a Man8GlcNAc2 structure, which is then exported to the Golgi

apparatus (Jigami, 2008).

Glycosylation and host cells | DCU

It is after this step that human and yeast N-glycosylation diverge. In human cells, the

glycan is trimmed and extended with a series of glycosidases and glycosyltransferases to

yield the final glycan structure, which is often capped with sialic acid residues (Hamilton,

2007). In yeast cells, the core Man8GlcNAc2 is extended, adding numerous mannose

units, leaving the glycan comparatively hypermannosylated (Gemmill, 1999).

The major technical hurdle with using yeast cells as a host for producing recombinant

human therapeutics is the inactivation of the endogenous machinery that leads to

hypermannosylation and the introduction of glycosyltransferases and glycosidases that

lead to the production of human-like glycans. The first objective has been achieved in S.

cerevisiae by eliminating the Och1 gene, which codes for the first enzyme in the

mannose-extension pathway, thereby preventing hypermannosylation (Nakanishi-

Shindo, 1993).

On the second objective, progress has been made towards producing human-type

glycans. By introducing the Mns-II and Gnt-II genes, minimal human complex-type

glycans (GlcNAc2Man3GlcNAc2) have been produced in P. pastoris (Hamilton, 2003).

Combined, these advances pave the way towards the use of yeast cells to produce

functionl, homogeneous human therapeutic glycoproteins.

Bacteria

Although once dismissed as lacking the ability to perform complex glycosylation, it is

now known that many bacterial strains can produce even more complex and diverse

glycan structures than even mammalian cells (Abu-Qarn, 2008). This opens the door to

the possibility of using bacterial cells as production vectors. This is an extremely

desirable goal from an economic standpoint for several reasons. Bacteria have much

shorter generation times than the currently used CHO cells. Given optimal growth

conditions, an E. coli population can double in as little as 18-20 minutes (Irwin, 2010),

while a mammalian culture will take 12-20 hours (Nakahara, 2002) (Sunstrom, 2000).

Bacterial hosts tend to be quite easy to modify genetically, and there are strains available

to meet any number of specific culture and production conditions (Bachmann, 1972).

DCU | Glycosylation and host cells

They can grow to quite high cell densities in culture (20 to 175 g/l dry biomass) (Lee,

1996), with recombinant target protein accounting for up to 30 percent of total cellular

protein by weight (Suzuki, 2006). Yields as high as 0.5 mg/mL have been achieved by

optimizing many conditions simultaneously (Sivashanmugam, 2009).

One of the main intrinsic limitations to bacterial expression systems is the tendency of

recombinant proteins to crash out into aggregates and inclusion bodies. This is partly

because bacteria lack the specific charaponins which aid in the folding of mammalian

proteins. This problem has been theoretically mitigated by coexpressing the chaperone

with the target protein (Lin, 2001).

There are large differences between bacterial and mammalian glycosylation patterns.

The mammalian core glycan is attached to the asparagine residues by an N-

acetylglucosamine-β(1-4) linkage, whereas C. jejuni, the model organism for studying

bacterial glycosylation, utilises an N-acetylgalactosamine-α(1-3)-bacillosamine linkage

(Stanley, 2009) (Young, 2002). Bacillosamine is a rare amino sugar found in bacteria.

Additionally, the recognition sequence differs between human and bacterial systems.

Human cells utilise the three residue Asn-X-Ser/Thr sequon, while bacteria use a longer

five residue Asp/Glu -X-Asp-X-Ser/Thr sequon (Rich, 2009), where x represents any

amino acid except proline, which inhibits attachment of the N-glycan through stearic

hindrance (Shyama, 2010). Additionally, human glycosylation occurs during protein

translation as the peptide emerges from the ribosome, while bacterial glycosylation

occurs after translation and folding as a true post-translational modification (Kowarik,

2006).

Taking into account these differences, a putative roadmap can be built. First, it will be

necessary to manipulating the bacterial host cells into utilising the mammalian GlcNAc

peptide linkage. Then it will be necessary to deal with the sequon problem. This can be

solved in two ways. The bacterial machinery can be modified to utilise the human-type

sequon or the target protein sequence can be modified to include the bacterial N-

glycosylation sequon. Ideally, the glycosylation apparatus will need to be transferred into

a more ideal production host such as E. coli or B. subtilis.

Analytical methods | DCU

All three of these goals have been achieved to an extent. By transferring pglB, an

oligosaccharyltransferase with relaxed substrate specificity, into bacterial expression

systems, human-type glycans with GlcNAc at their non-reducing can be linked to

proteins (Wacker, 2006).

Considering the problem of consensus sequences, Kowarik (2006) et al were able to

engineer additional Asp/Glu-X-Asp-X-Ser/Thr sequons into AcrA, a component of a

multi-drug efflux complex, from C. jejuni, and achieved functional glycosylation at these

sites. Thus there is no theoretical reason why human therapeutic proteins could not be

engineered to replace their N-gylcosylation sequons with bacterial versions, or to add

additional sequons to noncatalytic loops, where they are less likely to interfere with

protein function.

Considering the host strain issue, once the mechanics of C. jejuni glycosylation were

elucidated in detail, it was relatively easy to transfer this system into other bacterial

species, including E. coli (Wacker, 2002). Furthermore, this system has been used to

produce functional, correctly folded, glycosylated murine single-chain antibody

fragments, proteins with high therapeutic potential (Lizak, 2011).

Analytical methods

To analyse a pool glycan structures extracted from a cell or protein sample, two steps are

needed. Firstly, the glycans must be separated and secondly, the individual glycans must

be identified. To date, three major classes of glycan analysis have emerged;

electrophoresis, chromatography and mass spectrometry (MS) (Pabst, 2011). Note than

in practise, many of these techniques are used in tandem to achieve higher-resolution

separation or more comprehensive analysis.

Mass spectrometric

Within mass spectrometry, there are two methods which have dominated. Matrix-

assisted laser desorption/ionization – time of flight (MALDI-TOF) is suited to the

analysis of biological structures because the method of ionization is less hard, meaning

DCU | Analytical methods

fragile biological structures are less likely to fragment. The glycans are embedded in a

matrix composed of crystallised low molecular weight molecules. 2,5-dihydroxy benzoic

acid (DHB) and its derivatives are the most widely-used matrices (Harvey, 2005). The

matrix is irradiated with a high-powered UV laser, causing some of the matrix molecules

to vaporise into a hot cloud of gas. Through a series of reactions, the glycans become

bound to charged species, usually sodium cations (Morelle, 2007). The charged glycans

are then sent to a mass analyser.

The mass analyser generates a defined electric filed which accelerates the glycans

towards a detector. This ‘time of flight’ is determined by the mass-to-charge ratio (m/z)

of the glycan. The analyser outputs a mass spectrum, where each peak represents a

charged fragment of the original glycan (Morelle, 2009). By comparing the output

spectrum to a database of such spectra, the glycan can be identified.

The other major MS technique is electrospray ionization (ESI).Instead of embedding the

sample in a molecular matrix; the ions are formed directly from solution (Chait, 2011).

The solution containing the glycans is forced through a thin capillary tube. At the tip of

the tube, a strong electric field is applied. As the glycans leave the tube, they are exposed

to this field and ionized. This creates a spray of charged particles. The ions are then

detected by a TOF analyser, or other equivalent apparatus (Loo, 2000).

MS techniques can be coupled into tandem arrays. These can be used, for example, to

first separate a pool of glycans by their mass charge ratio, then selecting a set of glycans

within a specific range of (m/z) vales to go on to a second stage where they are

fragmented by collision-induced dissociation (CID) and analysed again, providing

further structural information (Harvey, 2000).

Chromatographic

In chromatographic methods, the glycan solution is pumped through a densely-packed

stationary phase. The glycans are slowed down on their passage through the column by

the stationary phase particles. The samples elute from the column at different times, this

is the retention time. The retention time is directly dependant on the glycan mass, so

with a properly calibrated column the mass of each glycan can be determined from the

retention time.

Analytical methods | DCU

Within the glycobiology field, several chromatographic techniques have dominated.

High pH anion exchange chromatography (HPAEC) has been one of the most widely-

used techniques to date (Townsend, 1991). HPAEC is sensitive to branching patterns

and oligosaccharide compositions. The glycans bind to the stationary phase which is

loaded with negatively-charged functional groups. The glycans are then displaced and

eluted by the introduction of a positively charged eluent (Dionex, 1997).

Another method used for smaller proteins is reverse-phase high-performance liquid

chromatography (RP-HPLC). RP-HPLC uses a non-polar stationary phase. The

glycans are derivatised (tagged) with a highly hydrophobic molecule that allows the

glycan to be selectively eluted (Wuhrer, 2005). This method can provide detailed

information about glycan structure and isomeric configuration (Gillmeister, 2009).

Another advantage of HPLC-based systems is that there exist large databases of peak

positions for glycans, making identification much easier (Campbell, 2008).

Electrophoretic

The major electrophoretic method used in the characterization of glycans is capillary

electrophoresis (CE). Like all electrophoretic methods, CE separation is based on the

size-to-charge ratio of a sample. Protein glyco-isoforms tend to be structurally very

similar. The differences may be difficult to detect using chromatographic or

spectrometric methods (Zamfir, 2008). The major advantage of CE is that it has

unrivalled separation power (Mechref, 2009). The sample is introduced into a chamber

where it is taken up by a capillary tube. An electric field is applied over the tube. As the

glycans travel through the tube, they are separated out by the slight differences in their

mass-to-charge ratios (Landers, 1995).

Bioaffinity methods

Bioaffinity methods are the newest breakthrough in the field of glycobiology applications.

It is defined as the separation of molecules based on their reversible interaction with

biological macromolecules. These separations involve highly-specific interactions

between the glycoligand and a carbohydrate-binding protein (Tetala, 2010). The

advantage of bioaffinity chromatography is that it allows highly-selective one step

DCU | Analytical methods

purification of glycoproteins, meaning less sample needs to be used. It can be used for

analytical, preparatory and diagnostic applications.

Lectins are proteins involved in carbohydrate-based recognition. Given their high-

specificity for distinct oligosaccharide epitopes, lectins are the logical solution for the

stationary-phase ligand. They are able to select for not only overall glycan structure, but

also for the configuration of the linkages between the monosaccharide units (Mechref,

2002). This allows them to isolate a target from a pool of glycans or glycoproteins.

Several lectin-affinity based techniques have been developed. The first is the standard

chromatographic column approach, where the lectins are immobilised onto a stationary

phase and the pool of glycoproteins are washed through the column (Tetala, 2010). The

target glycoproteins bind to the lectins and can be eluted and fractionated. This

approach can be improved by adding multiple lectins to the same column, allowing

simultaneous selection of multiple targets at one time (Yang, 2004). Another approach is

to immobilize the lectins onto the surface of a microtiter plate. This allows simultaneous

analysis of an even greater number of glycoproteins in a rapids and high-throughput

fashion (Kuno, 2005).

A modification of this approach is the enzyme-linked lectin assay (ELLA) (Wu, 2009).

Similar to the standard ELISA assay, the target glycoprotein is bound to the surface of a

microtiter plate, before a blocking solution is added to prevent nonspecific binding.

Then lectins are added to the wells, and bind to the target glycoprotein, if present. The

lectins are detected by the addition of labelled antibodies raised to bind to antigens on

the lectin. The label is detected and the quantity of label is proportional to the quantity

of target glycoprotein.

A similar technique is the carbohydrate array, in which glycans themselves are

immobilized to the plate and their interaction with a target protein is assayed (Oyelaran,

2007).

Bioinformatics | DCU

Bioinformatics

The primary goal of glycomics is to profile the expression and activity of all of the

glycosyltransferases, glycosidases, and other glycosylation apparatus, as well as the entire

glycan component within a cell under specific conditions (Aoki-Kinoshita, 2008). The

glycoprofiles of cells under different conditions can be compared. From this, we will

begin to deduce to conditions which lead to specific glycosylation events and, ultimately,

have the ability to rationally design the glycosylation machinery of producer cell lines.

Bioinformatic methods will be the key to achieving this goal.

Complexity of glycan structures

Computationally speaking, glycomics is a much more daunting field than proteomics and

genomics. Unlike genes and proteins, the glycoprofile of a cell is not encoded directly

by the genome but indirectly through the compliment of glycosylation enzymes active in

the cell. This means that to predict the glycosylation state of a newly-translated protein,

one would need to have full knowledge of the entire spectrum of glycosylation enzymes

expressed at the time as well as their substrate specificities, kinetic rates, their cofactors

and inhibitors, and a plethora of other variables.

Additionally, glycans themselves are structurally highly complex molecules. Unlike the

linear sequence of nucleic acids or amino acids which describe genes and proteins,

glycans are composed of sugar monosaccharaides. These can be linked together by

different types of bonds, and a residue can be linked to more than one other residue

(branching), and each branch can be linked in a number of different ways. Other

structural variables include anomeric configuration, epimeric configuration, and

reducing terminal attachments (Laine, 1994).

These structural traits magnify enormously the number of possible unique structures

that can be built from a given set of residues. To put this into perspective, the four DNA

bases can give rise to 256 possible four-unit combinations, and the twenty amino acids

can give rise to 160,000 possible four-unit arrangements, while a four-unit glycan can

potentially be assembled in 15 million different combinations (Von der Leith, 2004).

Prediction tools

N-glycosylation only occurs at sites which carry the specific Asn-XSer/Thr motif. If this

motif occurs in a given peptide sequence, it represents a potential glycosylation site.

DCU | Bioinformatics

Bioinformaticians have taken advantage of this knowledge to uncover information about

the ubiquity of glycoproteins in nature. Zafar et al (2011) used a computer algorithm to

scan all of the sequence data available on the ExPASy protein database and flag any

sequences which contained the signature motif. They found that more than 50 percent

of all proteins (prokaryotic and eukaryotic) contain at least one copy of the motif. This

overturns previously held assumptions about the exclusivity of glycosylation machinery

to eukaryotes (Nothaft, 2010).

A similar experiment conducted by Thanka et al applied statistical analysis to the

sequences of 992 experimentally-confirmed O-linked glycoproteins in an effort to

discover a signature O-linked motif analogous to the Asn-XSer/Thr motif of N-

glycosylation (Christlet, 2001). They found that the presence of a proline residue at

either the +3 or -1 position relative to the serine/threonine site strongly promotes

glycosylation and that aromatic amino acids near the site strongly inhibit glycosylation.

Glycobiology databases

To aid to experiments like these, several online tools and databases have been developed

to identify signature motifs for different types of glycosylation within an uploaded

sequence (Kamath, 2011). NetNGlyc is an artificial neural network trained not only to

find N-glycosylation sequence motifs, but to look at them in the context of the

surrounding amino acids whose influence on the local topology and physiochemical

properties may affect the glycosylation state of the biding site (Gupta, 2004).

Similarly, NetOGlyc parses the local sequence surrounding serine/threonine sites to find

probable O-linked glycosylation sites (Julenius, 2005). Several databases have emerged

which attempt to catalogue and document glycoproteins. Each has a different specialty.

GlycoBase records the HPLC elution data for N-linked glycans (Campbell, 2008), while

GlycosuiteDB contains over 3200 unique entries from 245 different species,

documenting the glycan structure, peptide linkage type and host protein (Cooper, 2003).

O-GlycBase contains detailed information on O- and C- linked glycans and was the

dataset used to train the NetOGlyc neural net mentioned above.

An enormous amount of data is being produced by glycobiology labs around the world

and the bottleneck has now shifted to the computational analysis and interpretation of

this data. To fully take advantage of the possibilities that this field offers, it will be

necessary to build and utilise new bioinformatics tools, algorithms and databases.

References | DCU

References Abu-Qarn M (2008). Not just for Eukarya anymore: protein glycosylation in Bacteria and

Archaea. Curr Opin Struct Biol. 18(5):544-50.

Albert R (1993). SDZ CO 611: a highly potent glycated analog of somatostatin with improved

oral activity. Life Sci. 53(6), 517-25.

Aoki-Kinoshita KF (2008). An Introduction to Bioinformatics for Glycomics Research. PLoS

Comput Biol. 4(5), e1000075.

Apweiler R (1999). On the frequency of protein glycosylation, as deduced from analysis of the

SWISS-PROT database. Biochim. Biophys. Acta. 1473, 4–8.

Arakawa T (2001). Factors affecting short-term and long-term stabilities of proteins. Adv Drug

Deliv Rev. 46(1−3), 307–326.

Bachmann BJ (1972). Pedigrees of some mutant strains of Escherichia coli K-12. Bacteriol Rev.

36(4), 525–557.

Benet L (1984). Pharmacokinetics: Basic Principles and Its Use as a Tool in Drug Metabolism.

In: Drug Metabolism and Drug Toxicity (Mitchell JR and Horning MG) Raven Press, New

York, 199.

Berting A (2010). Virus susceptibility of Chinese hamster ovary (CHO) cells and detection of

viral contaminations by adventitious agent testing. Biotechnol Bioeng. 106(4), 598-607.

Bethencourt V (2009). Virus stalls Genzyme plant. Nature Biotechnology. 27, 681.

Bhatnagar BS (2007). Protein stability during freezing: separation of stresses and mechanisms of

protein stabilization. Pharm Dev Technol. 12(5), 505-23.

build and utilise new bioinformatics tools, algorithms and databases.

Burton D (2006). Sugar Determines Antibody Activity. 313(5787), 627-628.

Butler M (2005). Animal cell cultures: recent achievements and perspectives in the production of

biopharmaceuticals. Appl Microbiol Biotechnol. 68, 283–91.

Campbell M (2008). GlycoBase and autoGU: tools for HPLC-based glycan analysis.

Bioinformatics. 24(9), 1214-1216.

Campbell MP (2008). GlycoBase and autoGU: tools for HPLC-based glycan analysis.

Bioinformatics. 24 (9), 1214-1216

Campion B (1989). Presence of fucosylated triantennary, tetraantennary and pentaantennary

glycans in transferrin synthesized by the human hepatocarcinoma cell line Hep G2. Eur J

Biochem. 184(2), 405-13.

DCU | References

Casadevall N (2002). Pure red-cell aplasia and antierythropoietin antibodies in patients treated

with recombinant erythropoietin. N. Engl. J. Med. 346(7), 469-75.

Ceaglio N (2008). Novel long-lasting interferon alpha derivatives designed by glycoengineering.

Biochimie. 90(3), 437–49

Chait BT (2011). Mass Spectrometry in the Postgenomic Era. Annu Rev Biochem. 80, 239-46.

Chi EY (2003). Physical stability of proteins in aqueous solution: mechanism and driving forces

in non-native protein aggregation. Pharm. Res. 20, 1325–1336.

Christlet HT (2001). Database Analysis of O-Glycosylation Sites in Proteins. Biophysical journal.

80(2), 952-960

Cooper C (2003). GlycoSuiteDB: a curated relational database of glycoprotein glycan structures

and their biological sources. Nucl. Acids Res. 31(1), 511-513.

Cregg JM (2009). Expression in the yeast Pichia pastoris. Methods Enzymol. 463, 169-89.

Darling RJ (2002). Glycosylation of erythropoietin affects receptor binding kinetics: role of

electrostatic interactions. Biochemistry. 41, 14524-14531.

De Schutter K (2009). Genome sequence of the recombinant protein production host Pichia

pastoris. Nat Biotechnol. 27(6), 561-6.

Demain AL (2009). Production of recombinant proteins by microbes and higher organisms.

Biotechnol Adv. 27(3), 297-306.

Dionex Corporation (1997) Glycoprotein Oligosaccharide Analysis Using High-performance

Anion-Exchange Chromatograph. Dionex Technical Note 42.

Egleton RD (2001). Improved blood-brain barrier penetration and enhanced analgesia of an

opioid peptide by glycosylation. J. Pharmacol. Exp. Ther. 299(3), 967-72.

Egrie JC (1993). The role of carbohydrate on the biological activity of erythropoietin.

Glycoconjugate J. 10, 263.

Egrie JC (2001). Development and characterization of novel erythropoiesis stimulating protein

(NESP). Br. J. Cancer. 1, 3-10.

Elliott S (2004). Control of rHuEPO biological activity: the role of carbohydrate. Exp. Hematol.

32, 1146-1155.

Fernandes AI (2001). The effect of polysialylation on the immunogenicity and antigenicity of

asparaginase: implication in its pharmacokinetics. Int. J. Pharm. 217(1-2), 215-24.

Gellison G (1992). High-level expression of foreign genes in Hansenula polymorpha. Biotech

Adv. 10, 179–89

References | DCU

Gemmill TR (1999). Overview of N- and O-linked oligosaccharide structures found in various

yeast species. Biochim. Biophys. Acta. 1426, 227-237.

Geyer H (2006). Strategies for analysis of glycoprotein glycosylation. Biochim Biophys Acta.

1764(12), 1853-69.

Gillmeister MP (2009). An HPLC-MALDI MS method for N-glycan analyses using smaller size

samples: application to monitor glycan modulation by medium conditions. Glycoconj J. 26(9),

1135-49.

Goffeau A (1996). Life with 6000 genes. Science. 274(5287), 563-7.

Golden K (2009). The XD Process: Development of a High-Titer Process for PER.C6 Cells.

21st Meeting of the European Society of Animal Cell Technology, Dublin, Ireland, 7–10 June

2009.

Gupta R (2004). Prediction of N-glycosylation sites in human proteins. [In preparation].

Hamilton SR (2003). Production of complex human glycoproteins in yeast. Science. 301(5637),

1244-6.

Hamilton SR (2007). Glycosylation engineering in yeast: the advent of fully humanized yeast.

Curr Opin Biotechnol. 18(5), 387-92.

Harvey DJ (2000). Collision‐induced fragmentation of underivatized N‐linked carbohydrates

ionized by electrospray. J Mass Spectrom. 35(10), 1178-90.

Harvey DJ (2005). Structural determination of N-linked glycans by matrix-assisted laser

desorption/ionization and electrospray ionization mass spectrometry. Proteomics. 5(7), 1774-86.

Hirschler B (2010). World's top-selling drugs in 2014 vs 2010. Thomson Reuters research

[Online]. Available from: http://www.reuters.com/article/2010/04/13/roche-avastin-drugs-

idUSLDE63C0BC20100413 [Accessed 22 November 2011].

Hoiberg-Nielsen R (2006). Interrelationships of glycosylation and aggregation kinetics for

Peniophora lycii phytase. Biochemistry. 45(15), 5057–5066.

Hual L (2008). Urea denaturation by stronger dispersion interactions with proteins than water

implies a 2-stage unfolding. Proc Natl Acad Sci U S A. 105(44), 16928-33.

Huang YM (2010). Maximizing productivity of CHO cell-based fed-batch culture using

chemically defined media conditions and typical manufacturing equipment. Biotechnol Prog. 26,

1400–10.

Imperiali B (1999). Effect of N-linked glycosylation on glycopeptide and glycoprotein structure.

Curr Opin. Chem. Biol. 3(6), 643-9.

DCU | References

Irwin P (2010). Evidence for a bimodal distribution of Escherichia coli doubling times below a

threshold initial cell concentration. BMC Microbiol. 10, 207.

Jigami Y (2008). Yeast glycobiology and its application. Biosci Biotechnol Biochem. 72(3), 637-

48.

Julenius K (2005). Prediction, conservation analysis and structural characterization of

mammalian mucin-type O-glycosylation sites. Glycobiology. 15, 153-164.

Kahn CM (2011). Drug Distribution. The Merck Veterinary Manual, 9th Edition. [Online].

Available from: http://www.merckvetmanual.com/mvm/index.jsp?cfile=htm/bc/190110.htm

[Accessed 16 November 2011].

Kamath KS (2011). Proteomic databases and tools to decipher post-translational modifications. J

Proteomics. [Epub ahead of print].

Kaneko Y (2006). Anti-Inflammatory Activity of Immunoglobulin G Resulting from Fc

Sialylation. Science. 313(5787), 670-673.

Kanwar YS (1984). Biophysiology of glomerular filtration and proteinuria. Lab. Invest. 51, 7–21.

Kayser V (2011). Glycosylation influences on the aggregation propensity of therapeutic

monoclonal antibodies. Biotechnology Journal. 6, 38–44.

Kelleher DJ (2006). An evolving view of the eukaryotic oligosaccharyltransferase. Glycobiology.

16(4), 47-62.

Kerwin BA (2007). Protect from light: photodegradation and protein biologics. J Pharm Sci. 96,

1468–79.

Khoury GA (2011). Proteome-wide post-translational modification statistics: frequency analysis

and curation of the swiss-prot database. Sci Rep. 13, 1.

Kopacek KB (2011). Drug Adsorption. The Merck Manual of Diagnosis and Therapy, 19th

Edition [Online]. Available from:

http://www.merckmanuals.com/professional/clinical_pharmacology/pharmacokinetics/drug_abso

rption.html#v1108980 [Accessed 16 November 2011].

Kopacek KB (2011). Drug Distribution. The Merck Manual of Diagnosis and Therapy, 19th

Edition [Online]. Available from:

http://www.merckmanuals.com/professional/clinical_pharmacology/pharmacokinetics/drug_abso

rption.html#v1108980 [Accessed 16 November 2011].

Kornfeld R (1985). Assembly of asparagine-linked oligosaccharides. Annu Rev Biochem. 54, 631-

664.

References | DCU

Kowarik M (2006). Definition of the bacterial N-glycosylation site consensus sequence. EMBO J.

25(9), 1957–1966.

Kowarik M (2006). N-Linked glycosylation of folded proteins by the bacterial

oligosaccharyltransferase. Science. 314, 1148–1150

Kuno A (2005). Evanescent-field fluorescence-assisted lectin microarray: a new strategy for

glycan profiling. Nat. Methods. 2, 851–856.

Laine RA. (1994). A calculation of all possible oligosaccharide isomers both branched and linear

yields 1.05 3 10(12) structures for a reducing hexasaccharide. Glycobiology. 4: 759–767.

Landers JP (1995). Clinical capillary electrophoresis. Clinical Chemistry. 41, 495-509.

Lee SY (1996). High cell density culture of Escherichia coli. Trends Biotechnol. 14, 98-105

Li H (2010). Pharmacological significance of glycosylation in therapeutic proteins. Curr Opin

Biotechnol. 20(6), 678-84.

Lin WJ (2001). DegP-coexpression minimizes inclusion-body formation upon overproduction of

recombinant penicillin acylase in Escherichia coli. Biotechnol Bioeng. 73(6), 484-92.

Lizak C (2011). N-Linked glycosylation of antibody fragments in Escherichia coli. Bioconjug

Chem. 22(3), 488-96.

Loo, J. (2000). Electrospray ionization mass spectrometry: a technology for studying

noncovalent macromolecular complexes. International Journal of Mass Spectrometry. 200(1-3),

175-186.

Macdougall I (1999). Pharmacokinetics of Novel Erythropoiesis Stimulating Protein Compared

with Epoetin Alfa in Dialysis Patients. J. Am. Soc. Nephrol. 10, 2392–2395.

Manning MC (2010). Stability of protein pharmaceuticals: an update. Pharm Res. 27(4), 544-75.

Masarova J (2001). Stability enhancement of Escherichia coli penicillin G acylase by

glycosylation with yeast mannan. Biotechnol Appl Biochem. 34, 127–133.

Mechref T (2002). Structural Investigations of Glycoconjugates at High Sensitivity. Chem. Rev.

102(2), 321–370

Mechref Y (2009) Glycomic analysis by capillary electrophoresis-mass spectrometry. Mass

Spectrom Rev. 28(2):207-22.

Moore WV (1980). Role of aggregated human growth hormone (hGH) in development of

antibodies to hGH. J. Clin. Endocrinol. Metab. 51(4), 691-7.

Morell AG (1968). Physical and chemical studies on ceruloplasmin. V. Metabolic studies on

sialic acid-free ceruloplasmin in vivo. J. Biol. Chem. 243(1), 155–9.

DCU | References

Morell AG (1971). The role of sialic acid in determining the survival of glycoproteins in the

circulation. J. Biol. Chem. 246, 1461–1467.

Morelle W (2007). Analysis of protein glycosylation by mass spectrometry. Nat. Protoc. 2(7),

1585-602.

Morelle W (2009). Analysis of N- and O-linked glycans from glycoproteins using MALDI-TOF

mass spectrometry. Methods Mol Biol. 534, 5-21.

Nakahara T (2002). Effects of exposure of CHO-K1 cells to a 10-T static magnetic field.

Radiology. 224(3), 817-22.

Nandita GD (2003). Controlled-release of oral dosage forms. Formulation, Fill and Finish. 10-

16.

Nomoto M (1998). Improvement of intestinal absorption of peptide drugs by glycosylation:

transport of tetrapeptide by the sodium ion-dependent D-glucose transporter. J. Pharm. Sci.

87(3), 326-32.

Nothaft H (2010). Protein glycosylation in bacteria: sweeter than ever. Nature Reviews

Microbiology. 8, 765-778.

Oyelaran O (2007). Application of carbohydrate array technology to antigen discovery and

vaccine development. Expert Rev Vaccines. 6(6), 957-69.

Pabst M (2011). Glycan analysis by modern instrumental methods. Proteomics. 11, 631–643

Pandhal J (2010). N-Linked glycoengineering for human therapeutic proteins in bacteria.

Biotechnol Lett. 32(9), 1189-98.

Perlman S (2003). Glycosylation of an N-terminal extension prolongs the half-life and increases

the in vivo activity of follicle stimulating hormone. J. Clin. Endocrinol. Metab. 88(7), 3227-35.

Philo JS (2009). Mechanisms of protein aggregation. Curr Pharm Biotechnol. 10, 348–51.

Pristov JB (2011). A comparative study of antioxidative activities of cell-wall polysaccharides.

Carbohydr Res. 346(14), 2255-9.

Rich JR (2009). Emerging methods for the production of homogeneous human glycoproteins.

Nat Chem Biol. 5(4), 206-15.

Roque AC (2004). Antibodies and genetically engineered related molecules: production and

purification. Biotechnol Prog. 20(3), 639-54.

Rosenberg AS (2006). Effects of protein aggregates: an immunologic perspective. AAPS J. 8,

501–7.

References | DCU

Runkel L (1998). Structural and functional differences between glycosylated and non-

glycosylated forms of human interferon-beta (IFN-beta). Pharm Res. 15(4), 641–649.

Russell D (2009). Site-selective chemical protein glycosylation protects from autolysis and

proteolytic degradation. Carbohydr Res. 344(12), 1508-14

Saluja A (2008). Nature and consequences of protein-protein interactions in high protein

concentration solutions. International Journal of Pharmaceutics. 358, 1-15

Sasayama S (2000). Glycosylated human interleukin-1alpha, neoglyco IL-1alpha, coupled with

N-acetylneuraminic acid exhibits selective activities in vivo and altered tissue distribution.

Glycoconj. J. 17(6), 353-9.

Satoh M (2006). Non-fucosylated therapeutic antibodies as next-generation therapeutic

antibodies. Expert Opin. Biol. Ther. 6(11), 1161-73.

Saxena S (1987). Purification and characterization of glucosidase II involved in N-linked

glycoprotein processing in bovine mammary gland. Biochem J. 247(3), 563–570.

Schirmer EB (2010). Primary clarification of very high-density cell culture harvests by enhanced

cell settling. BioProcess Int. 8, 32–9.

Sethuraman N (2006). Challenges in therapeutic glycoprotein production. Curr Opin

Biotechnol.17, 341–346

Shailubhai K (1987). Purification and characterization of glucosidase I involved in N-linked

glycoprotein processing in bovine mammary gland. Biochem J. 247(3), 555–562.

Shental-Bechor D (2008). Effect of glycosylation on protein folding: A close look at

thermodynamic stabilization. PNAS. 105(24), 8256-8261.

Shyama R (2010). Evolutionary Pattern of N-Glycosylation Sequon Numbers in Eukaryotic

ABC Protein Superfamilies. Bioinform. Biol. Insights. 4, 9–17.

Sivashanmugam A (2009). Practical protocols for production of very high yields of recombinant

proteins using Escherichia coli. Protein Sci. 18(5), 936–948.

Solá RJ (2007). Modulation of protein biophysical properties by chemical glycosylation:

biochemical insights and biomedical implications. Cell Mol Life Sci. 64(16), 2133–2152.

Solá RJ (2009). Effects of glycosylation on the stability of protein pharmaceuticals. J Pharm Sci.

98(4), 1223-45.

Solá RJ et al (2010). Glycosylation of therapeutic proteins: an effective strategy to optimize

efficacy. BioDrugs. 24(1), 9-21.

DCU | References

Soltero R (2001). The oral delivery of protein and peptide drugs. Innov. Pharmacol. Technol. 1,

106–110

Stanley P (2009). N-Glycans. In: Source Essentials of Glycobiology. (Varki A, Cummings RD,

Esko JD, Freeze HH, Stanley P, Bertozzi CR, Hart GW, Etzler ME, eds.). 2nd edition. Cold

Spring Harbor (NY): Cold Spring Harbor Laboratory Press, Chapter 8.

Sunstrom NA (2000). Regulated autocrine growth of CHO cells. Cytotechnology. 34(1-2), 39-

46.

Suzuki M (2006). Bacterial bioreactors for high yield production of recombinant protein. J Biol

Chem. 281(49), 37559-65.

Sytkowski AJ (1991). Biological activity and structural stability of N-deglycosylated recombinant

human erythropoietin. Biochem Biophys Res Commun. 176(2), 698-704.

Tams JW (1999). Adapting protein solubility by glycosylation. N-glycosylation mutants of

Coprinus cinereus peroxidase in salt and organic solutions. Biochim Biophys Acta. 1432(2), 214–

221.

Tang L (2004). Pharmacokinetic aspects of biotechnology products, J. Pharm. Sci. 93, 2184–

2204.

Tetala KK (2010). Bioaffinity chromatography on monolithic supports. J Sep Sci. 33(3), 422-38.

Townsend RR (1991). Analysis of glycoprotein oligosaccharides using high-pH anion exchange

chromatography. Glycobiology. 1(2), 139-47.

Uchida E (1997). Effect of active oxygen radicals on protein and carbohydrate moieties of

recombinant human erythropoietin. Free Radic Res. 27(3), 311–323.

Valdivieso-Ugarte M (2006). Expression of an Aspergillus niger glucose oxidase in

saccharomyces cerevisiae and its use to optimize fructo-oligosaccharides synthesis. Biotechnol

Prog. 22(4), 1096-101.

Vegarud G (1975). The resistance of glycoproteins to proteolytic inactivation. Acta Chem Scand

B. 29(8), 887–888.

Venter JC (2001). The sequence of the human genome. Science. 291, 1304–1351.

Verma R (1998). Antibody engineering: comparison of bacterial, yeast, insect and mammalian

expression systems. J Immunol Methods. 216(1-2), 165-81.

Vogt G (1997). Protein thermal stability, hydrogen bonds, and ion pairs. J Mol Biol. 269(4), 631-

43.

References | DCU

Von der Lieth CW (2004). Bioinformatics for glycomics: status, methods, requirements and

perspectives. Brief Bioinform. 5(2), 164-78.

Wacker M (2002). N-Linked glycosylation in Campylobacter jejuni and its functional transfer

into E. coli. Science 298, 1790–1793.

Wacker M (2006). Substrate specificity of bacterial oligosaccharyltransferase suggests a common

transfer mechanism for the bacterial and eukaryotic systems. Proc. Natl. Acad. Sci. USA. 103,

7088–7093.

Walsh G (2010). Biopharmaceutical benchmarks 2010. Nat Biotechnol. 28(9), 917-24.

Wang C (1996). Influence of the carbohydrate moiety on the stability of glycoproteins.

Biochemistry. 35(23), 7299–7307.

Wang W (1999). Instability, stabilization, and formulation of liquid protein pharmaceuticals. Int

J Pharm. 185(2), 129–188.

Wang W (2005). Protein aggregation and its inhibition in biopharmaceutics. Int J Pharm. 289(1-

2), 1-30.

Wormald MR (1999). Glycoproteins: glycan presentation and protein-fold stability. Structure

Fold Des. 7(7), 155–160.

Wu AM (2009). Lectins as tools in glycoconjugate research. Glycoconj J. 26(8), 899-913.

Wuhrer M (2005). Protein glycosylation analysis by liquid chromatography–mass spectrometry.

J Chromatogr B Analyt Technol Biomed Life Sci. 825(2), 124-33.

Xie L (2003). Large-scale propagation of a replication-defective adenovirus vector in stirred-tank

bioreactor PER.C6 cell culture under sparging conditions. Biotechnol Bioeng. 83(1), 45-52.

Yamane-Ohnuki N (2004). Establishment of FUT8 knockout Chinese hamster ovary cells: an

ideal host cell line for producing completely defucosylated antibodies with enhanced

antibodydependent cellular cytotoxicity. Biotechnol. Bioeng. 87, 614–622.

Yang Z (2004). Approach to the comprehensive analysis of glycoproteins isolated from human

serum using a multi-lectin affinity column. J. Chromatogr. A. 1053, 79–88

Yoshimura M (1998). Bisecting GlcNAc structure is implicated in suppression of stroma-

dependent haemopoiesis in transgenic mice expressing N-acetylglucosaminyltransferase III.

Biochem J. 331(3), 733–742.

Young NM (2002). Structure of the N-linked glycan present on multiple glycoproteins in the

Gram-negative bacterium, Campylobacter jejuni. J Biol Chem. 277(45), 42530-9

DCU | References

Zafar S (2011). Computational analysis reveals abundance of potential glycoproteins in Archaea,

Bacteria and Eukarya. Bioinformation. 6(9), 352-5.

Zamfir AD (2008). Glycosylation analysis of glycoproteins and proteoglycans using capillary

electrophoresis-mass spectrometry strategies. ELECTROPHORESIS. 29, 2485–2507.