Glycosylation literature survey ricky connolly 091211
1. 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.
3. 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).
DCU | Introduction
4. 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).
Introduction | DCU
5. 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
DCU | Introduction
6. 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
Stability | DCU
7. 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
DCU | Stability
8. 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
Stability | DCU
9. 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.
DCU | Pharmacology
10. 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.
Pharmacology | DCU
11. 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.
DCU | Pharmacology
12. 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
Pharmacology | DCU
13. 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
2% 55% a.
products are glycosylated (Walsh, 2% 2%
2010). Therefore, for an organism to Mammalian
10%
become widely used as a producer
E. coli
strain, it must be able to perform
Yeast
glycosylation to some extent. Between
2006 and 2010, 58 new Insect
biopharmaceuticals gained approval. Animals
32 of these were produced in 29% Synthetic
mammalian cell lines and of these, 24
CHO
were produced in Chinese hamster
3% 3%
75%
b.
ovary (CHO) cells. It is clear that 6% NS0
3%
CHO cells are still the workhorse of Sp2/0
3%
the biopharmaceutical industry.
7% rat-mouse hybrid
hybridoma
Other common host cell systems Murine hybridoma
include the various mouse myeloma
Murine myeloma
strains, including NS0 and sp2/0, as
Immortalized
well as yeast cells, mostly Pichia human
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).
DCU | Glycosylation and host cells
14. 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).
Glycosylation and host cells | DCU
15. 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).
DCU | Glycosylation and host cells
16. 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).
Glycosylation and host cells | DCU
17. 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.
DCU | Glycosylation and host cells
18. 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
Analytical methods | DCU
19. 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.
DCU | Analytical methods
20. 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
Analytical methods | DCU
21. 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).
DCU | Analytical methods
22. 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.
Bioinformatics | DCU
23. 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 + or -1 position relative to the serine/threonine site strongly promotes
3
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.
DCU | Bioinformatics
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