U.S. patent application number 11/107982 was filed with the patent office on 2006-03-16 for methods and products related to the improved analysis of carbohydrates.
This patent application is currently assigned to Massachusetts Institute of Technology. Invention is credited to Carlos Bosques, Pankaj Gandhe, Nishla Keiser, Sasi Raguram, Ram Sasisekharan, Aravind Srinivasan.
Application Number | 20060057638 11/107982 |
Document ID | / |
Family ID | 34981344 |
Filed Date | 2006-03-16 |
United States Patent
Application |
20060057638 |
Kind Code |
A1 |
Bosques; Carlos ; et
al. |
March 16, 2006 |
Methods and products related to the improved analysis of
carbohydrates
Abstract
The invention relates, in part, to the improved analysis of
carbohydrates. In particular, the invention relates to the analysis
of carbohydrates, such as N-glycans and O-glycans found on
proteins. Improved methods, therefore, for the study of
glycosylation patterns on cells, tissue and body fluids are also
provided. Information regarding the analysis of glycans, such as
the glycosylation patterns on cells, tissues and in body fluids,
can be used in diagnostic and treatment methods as well as for
facilitating the study of the effects of glycosylation/altered
glycosylation on protein function. Such methods are also provided.
Methods are also provided to assess protein production processes,
to assess the purity of proteins produced, and to select proteins
with the desired glycosylation.
Inventors: |
Bosques; Carlos; (Cambridge,
MA) ; Keiser; Nishla; (Cambridge, MA) ;
Srinivasan; Aravind; (Malden, MA) ; Sasisekharan;
Ram; (Bedford, MA) ; Gandhe; Pankaj;
(Sayreville, NJ) ; Raguram; Sasi; (Hillsborough,
NJ) |
Correspondence
Address: |
WOLF GREENFIELD & SACKS, PC;FEDERAL RESERVE PLAZA
600 ATLANTIC AVENUE
BOSTON
MA
02210-2211
US
|
Assignee: |
Massachusetts Institute of
Technology
Cambridge
MA
|
Family ID: |
34981344 |
Appl. No.: |
11/107982 |
Filed: |
April 15, 2005 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
60562874 |
Apr 15, 2004 |
|
|
|
Current U.S.
Class: |
435/7.1 ; 506/19;
506/8; 506/9; 536/53; 702/19 |
Current CPC
Class: |
G01N 2400/10 20130101;
G01N 33/6803 20130101; G01N 33/6842 20130101; Y10T 436/143333
20150115; G01N 33/6851 20130101 |
Class at
Publication: |
435/007.1 ;
702/019 |
International
Class: |
G01N 33/53 20060101
G01N033/53; G06F 19/00 20060101 G06F019/00 |
Goverment Interests
GOVERNMENT SUPPORT
[0002] Aspects of the invention may have been made using funding
from National Institutes of Health Grant number GM 57073.
Accordingly, the Government may have rights in the invention.
Claims
1. A method of analyzing a sample containing glycoconjugates,
comprising: (a) separating the glycans from the sample containing
the glycoconjugates, (b) determining the glycosylation sites and
glycosylation site occupancy of the glycoconjugates, (c) analyzing
the glycans to characterize the glycans, and (d) determining the
glycoforms of the glycoconjugates in the sample with the results
obtained from steps (b) and (c) with a computational method.
2.-10. (canceled)
11. The method of claim 1, wherein the glycoconjugates comprise a
peptide and wherein the step of determining the glycosylation sites
and glycosylation site occupancy, comprises cleaving the backbone
of the glycoconjugates, cleaving and labeling with a first label
the glycoconjugates of a first portion of the sample at their
glycosylation sites, cleaving the glycoconjugates of a second
portion of the sample at their glycosylation sites, analyzing the
first and second portions of the sample of glycoconjugates, and
quantifying the results of the analysis step.
12.-31. (canceled)
32. A method of analyzing a sample containing glycoconjugates,
comprising: separating the glycans from the sample containing the
glycoconjugates, determining the glycosylation sites and
glycosylation site occupancy of the glycoconjugates, and analyzing
the glycans to characterize the glycans, wherein determining the
glycosylation sites and glycosylation site occupancy comprises
cleaving and labeling with a first label the glycoconjugates at
their glycosylation sites of a first portion of the sample,
cleaving the glycoconjugates at their glycosylation sites of a
second portion of the sample, analyzing the first and second
portions of the sample of glycoconjugates, and quantifying the
results.
33.-46. (canceled)
47. A method of determining the glycosylation site occupancy of
glycoconjugates in a sample, comprising: cleaving and labeling with
a first label the glycoconjugates at their glycosylation sites of a
first portion of the sample, cleaving the glycoconjugates at their
glycosylation sites of a second portion of the sample, analyzing
the first and second portions of the sample of glycoconjugates, and
quantifying the results.
48.-54. (canceled)
55. A method of analyzing a sample containing glycans, comprising:
separating neutral from charged glycans, and analyzing the neutral
and charged glycans separately to characterize the glycan.
56. (canceled)
57. A method of analyzing a glycan, comprising: analyzing the
glycan in the presence of Nafion and ATT.
58. The method of claim 1, wherein the method is a method of
analyzing the purity of a sample containing glycans.
59. The method of claim 1, wherein the method is a method of
analyzing the glycans of a sample of one or more cells, a tissue or
body fluid from a subject.
60. A high-throughput method of claim 1, wherein more than one
sample is analyzed.
61.-62. (canceled)
63. A method of generating a glycopeptide library, comprising:
cleaving the backbone of the glycopeptides in a sample and labeling
the glycopeptide fragments generated with a labeling agent, and
cleaving the glycans in the sample.
64.-68. (canceled)
69. A library of glycopeptides generated with the method of claim
63.
70. A method of analyzing a sample of glycopeptides, comprising:
characterizing the glycopeptides in the sample, and comparing the
characterized glycopeptides with the library of glycopeptides of
claim 69.
71. A method of generating a list of glycoconjugate properties,
comprising: measuring two or more properties of the glycoconjugate,
and recording a value for the two or more properties of the
glycoconjugate to generate a list, wherein the value of the two or
more properties is recorded in a computer-generated data
structure.
72.-77. (canceled)
78. A database, tangibly embodied in a computer-readable medium,
for storing information descriptive of one or more glycoconjugates,
the database comprising: one or more data units corresponding to
the one or more glycoconjugates, each of the data units including
an identifier that includes two or more fields, each field for
storing a value corresponding to one or more properties of the
glycoconjugates.
79. A method of analyzing the total glycome of a sample of body
fluid, comprising: (a) analyzing the glycans of the sample, and (b)
determining a profile of the glycans of the sample.
80. The method of claim 79, wherein the method further comprises
performing a pattern analysis on the results from (a) using a
computational method.
81.-85. (canceled)
86. A method of analyzing the total glycome of a sample of body
fluid, comprising: (a) analyzing the glycans of a sample of body
fluid, and (b) comparing the results from (a) with a known
pattern.
87.-100. (canceled)
101. A method of determining the purity of a sample, comprising:
(a) analyzing the total glycans of the sample, (b) identifying the
glycan pattern of the sample, and (b) comparing the pattern with a
known pattern of a sample of predetermined purity to assess the
purity of the sample.
102. A method of generating the complete glycan profile of a body
fluid, comprising: (a) analyzing the glycans in the sample, and (b)
identifying the complete glycan profile of the sample.
103.-104. (canceled)
105. A method of analyzing the total glycome of a sample,
comprising: determining the glycosylation site and glycosylation
site occupancy of all glycoconjugates in the sample, characterizing
components of the glycoconjugates and all glycans of the glycome in
the sample, and matching specific glycans to glycoconjugates with a
computational method.
106. A method of analyzing a sample of glycoconjugates, comprising:
analyzing the glycans of the sample with an analytical method, and
determining the glycoforms of the sample with a computational
method.
107. (canceled)
Description
RELATED APPLICATIONS
[0001] This application claims priority under 35 U.S.C. .sctn.119
from U.S. provisional application Ser. No. 60/562,874, filed Apr.
15, 2004, the entire contents of which is herein incorporated by
reference.
FIELD OF THE INVENTION
[0003] The invention relates to the improved analysis of
carbohydrates. In particular, the invention relates to the analysis
of carbohydrates, such as N-glycans and O-glycans found on proteins
and lipids. The invention also relates to the analysis of
glycoconjugates, such as glycoproteins, glycolipids and
proteoglycans. Methods for the study of glycosylation patterns on
cells, tissues and in body fluid, such as serum, are also provided.
Information regarding the glycosylation patterns on cells can be
used in diagnostic and treatment methods as well as for
facilitating the study of the effects of glycosylation/altered
glycosylation on diseases, protein or lipid function and function
of medical treatments. Information regarding the glycosylation of
glycoconjugates can also be used in the quality control analysis of
glycoconjugate production and/or therapeutics.
BACKGROUND OF THE INVENTION
[0004] Asparagine-linked glycosylation (N-glycosylation) is the
most common co-translational modification found in eukaryotic
proteins. As proteins are synthesized by the ribosome, the
polypeptide enters the endoplasmic reticulum, where oligosaccharyl
transferase (OT) attaches a branched carbohydrate (N-glycan) to the
side chain of certain asparagine residues [Hirschberg, C. B.,
Snider, M. D. (1987) Topography of glycosylation in the rough
endoplasmic reticulum and Golgi apparatus. Annu Rev Biochem 56,
63-87.] This process requires an Asn-X-Ser/Thr consensus sequence
in the peptide substrate, where X is any amino acid except proline
[Bause, E. (1983) Structural requirements of N-glycosylation of
proteins. Studies with proline peptides as conformational probes.
Biochem J 209, 331 -6; Marshall, R. D. (1972) Glycoproteins. Annu
Rev Biochem 41, 673-702.] After the attachment of the glycans, the
carbohydrate moiety is extensively modified by a complex array of
glycosidases and glycosyl transferases in the ER and golgi
apparatus. The attached N-glycans are very important in protein
folding, as well as directing the protein to the appropriate
location within the cell [Dwek, R. A. (1996) Glycobiology: Toward
Understanding the Function of Sugars. Chem Rev 96, 683-720;
O'Connor, S. E., Imperiali, B. (1996) Modulation of protein
structure and function by asparagine-linked glycosylation. Chem
Biol 3, 803-12.] Outside the cell, the sugars aid in
protein-protein interactions, often modulating the activity of the
protein to which they are attached. Depending on the glycan
composition, they can also protect against or facilitate protein
degradation in circulation, as well as target the protein to a
specific organ [Crocker, P. R., Varki, A. (2001) Siglecs in the
immune system. Immunology 103, 137-45; Helenius, A., Aebi, M.
(2001) Intracellular functions of N-linked glycans. Science 291,
2364-9; Imperiali, B., O'Connor, S. E. (1999) Effect of N-linked
glycosylation on glycopeptide and glycoprotein structure. Curr Opin
Chem Biol 3, 643-9.]
[0005] N-glycans also have an essential role in normal biology, as
evidenced by the high lethality in cases of defective
glycosylation. In mouse knockout models, disrupting even one of the
biosynthetic enzymes can lead to enormous multisystemic disorders,
and several result in embryonic lethality [Furukawa, K., Takamiya,
K., Okada, M., Inoue, M., Fukumoto, S. (2001) Novel functions of
complex carbohydrates elucidated by the mutant mice of
glycosyltransferase genes. Biochim Biophys Acta 1525, 1-12.] There
are currently six recognized human congenital disorders of
glycosylation (CDGs), all resulting in patients with multiple organ
abnormalities, developmental delay and immune problems, among
others [Jaeken, J., Matthijs, G. (2001) Congenital disorders of
glycosylation. Annu Rev Genomics Hum Genet 2, 129-51; Freeze, H.
H., Aebi, M. (1999) Molecular basis of carbohydrate-deficient
glycoprotein syndromes type I with normal phosphomannomutase
activity. Biochim Biophys Acta 1455, 167-78; Carchon, H., Van
Schaftingen, E., Matthijs, G., Jaeken, J. (1999)
Carbohydrate-deficient glycoprotein syndrome type IA
(phosphomannomutase-deficiency). Biochim Biophys Acta 1455,
155-65.] In fact, the immune system is one of the most commonly
studied systems where N-glycans have been shown to play an
important physiological role. For example, specific carbohydrate
structures are recognized by selectins, a family of proteins
expressed on endothelial cells or lymphocytes that can trigger the
immune system upon activation [Powell, L. D., Sgroi, D., Sjoberg,
E. R., Stamenkovic, I., Varki, A. (1993) Natural ligands of the B
cell adhesion molecule CD22 beta carry N-linked oligosaccharides
with alpha-2,6-linked sialic acids that are required for
recognition. J Biol Chem 268, 7019-27; Sgroi, D., Varki, A.,
Braesch-Andersen, S., Stamenkovic, I. (1993) CD22, a B
cell-specific immunoglobulin superfamily member, is a sialic
acid-binding lectin. J Biol Chem 268, 7011-8.] The same class of
structures that are necessary for proper immune function can also
provide a binding site for certain viruses, bacteria or tumor cells
in the body [Karlsson, K. A. (1998) Meaning and therapeutic
potential of microbial recognition of host glycoconjugates. Mol
Microbiol 29, 1-11; Pritchett, T. J., Brossmer, R., Rose, U.,
Paulson, J. C. (1987) Recognition of monovalent sialosides by
influenza virus H3 hemagglutinin. Virology 160, 502-6.]
[0006] Viral infection is mediated by the interaction of viral
proteins with N-glycans on the cell surfaces of the host [Van Eijk,
M., White, M. R., Batenburg, J. J., Vaandrager, A. B., Van Golde,
L. M., Haagsman, H. P., Hartshorn, K. L. (2003) Interactions of
Influenza A virus with Sialic Acids present on Porcine Surfactant
Protein D. Am J Respir Cell Mol Biol.] Despite the increasing
evidence associating glycans to different pathogenic conditions, in
multiple instances it is unclear whether changes in N-glycan
structure are a cause or a symptom of the disorder. In cystic
fibrosis, increased antennary fucosylation (.alpha.1-3 linked to
GlcNAc) is observed on surface membrane glycoproteins of airway
epithelial cells [Glick, M. C., Kothari, V. A., Liu, A., Stoykova,
L. I., Scanlin, T. F. (2001) Activity of fucosyltransferases and
altered glycosylation in cystic fibrosis airway epithelial cells.
Biochimie 83, 743-7; Scanlin, T. F., Glick, M. C. (2000) Terminal
glycosylation and disease: influence on cancer and cystic fibrosis.
Glycoconj J 17, 617-26.]
[0007] There have also been many reports of alterations in N-glycan
composition on cancer cell proteins. For example, there are
indications that prostate cancer cells produce prostate specific
antigen (PSA) with more glycan branching than non-cancer cells
[Peracaula, R., Tabares, G., Royle, L., Harvey, D. J., Dwek, R. A.,
Rudd, P. M., de Llorens, R. (2003) Altered glycosylation pattern
allows the distinction between prostate-specific antigen (PSA) from
normal and tumor origins. Glycobiology 13, 457-70; Belanger, A.,
van Halbeek, H., Graves, H. C., Grandbois, K., Stamey, T. A.,
Huang, L., Poppe, I., Labrie, F. (1995) Molecular mass and
carbohydrate structure of prostate specific antigen: studies for
establishment of an international PSA standard. Prostate 27,
187-97; Prakash, S., Robbins, P. W. (2000) Glycotyping of prostate
specific antigen. Glycobiology 10, 173-6.] Melanoma and bladder
cancer cells produce proteins with highly branched glycans due to
an overexpression of the biosynthetic enzyme
.beta.1,6-N-acetyl-glucosaminyltransferase V (GnT-V) [Chakraborty,
A. K., Pawelek, J., Ikeda, Y., Miyoshi, E., Kolesnikova, N.,
Funasaka, Y., Ichihashi, M., Taniguchi, N. (2001) Fusion hybrids
with macrophage and melanoma cells up-regulate
N-acetylglucosaminyltransferase V, beta1-6 branching, and
metastasis. Cell Growth Differ 12, 623-30; Przybylo, M.,
Hoja-Lukowicz, D., Litynska, A., Laidler, P. (2002) Different
glycosylation of cadherins from human bladder non-malignant and
cancer cell lines. Cancer Cell Int 2, 6.] Increased sialylation and
additional branching have also been observed in cells from human
breast and colon neoplasia [Lin, S., Kemmner, W., Grigull, S.,
Schlag, P. M. (2002) Cell surface alpha 2,6 sialylation affects
adhesion of breast carcinoma cells. Exp Cell Res 276, 101-10;
Nemoto-Sasaki, Y., Mitsuki, M., Morimoto-Tomita, M., Maeda, A.,
Tsuiji, M., Irimura, T. (2001) Correlation between the sialylation
of cell surface Thomsen-Friedenreich antigen and the metastatic
potential of colon carcinoma cells in a mouse model. Glycoconj J
18, 895-906; Dennis, J. W., Granovsky, M., Warren, C. E. (1999)
Glycoprotein glycosylation and cancer progression. Biochim Biophys
Acta 1473, 21-34; Fernandes, B., Sagman, U., Auger, M., Demetrio,
M., Dennis, J. W. (1991) Beta 1-6 branched oligosaccharides as a
marker of tumor progression in human breast and colon neoplasia.
Cancer Res 51, 718-23.]
SUMMARY OF THE INVENTION
[0008] This invention provides, in part, methods related to the
analysis of carbohydrates. In particular, the invention relates to
the analysis of carbohydrates, such as N-glycans and O-glycans
found on proteins and lipids. The invention also relates to the
analysis of glycoconjugates, such as glycoproteins, glycolipids and
proteoglycans.
[0009] In an aspect of the invention, methods of analyzing a sample
containing glycoconjugates are provided. The methods include (a)
separating the carbohydrates (e.g., glycans) from the sample
containing the glycoconjugates, (b) determining the glycosylation
site and/or occupancy of the glycoconjugates, (c) analyzing the
carbohydrates (e.g., glycans) for characterization and/or
quantification, and (d) determining the glycoforms and/or glycan
profile of the glycoconjugates in the sample with the results
obtained from steps (b) and (c) with a computational approach. In
certain embodiments, the methods also include determining the
occupancy of each glycan at each glycosylation site.
[0010] In an embodiment of the invention, step (a) includes
denaturing the glycoconjugates. In a second embodiment, the
glycoconjugates are denatured with a denaturing agent. In another
embodiment, the denaturing agent is detergent, urea, guanidium
hydrochloride or heat. In a further embodiment, the glycoconjugates
are reduced following their denaturation. In yet another
embodiment, the glycoconjugates are reduced with a reducing agent.
The reducing agent in certain embodiments is DTT,
.beta.-mercaptoethanol or TCEP. In a further embodiment, the
glycoconjugates are alkylated with an alkylating agent following
their reduction. The alkylating agent in certain embodiments is
iodoacetic acid or iodoacetamide.
[0011] In certain embodiments of the foregoing methods, the step of
determining the glycosylation sites and/or glycosylation site
occupancy includes analyzing the glycoconjugates, preferably with
2D-NMR. In one embodiment, the step of determining the
glycosylation site and glycosylation site occupancy includes
cleaving the peptide backbone of the glycoconjugates (and
optionally analyzing the cleaved fragments), cleaving and labeling
with a first label the glycoconjugates at their glycosylation sites
of a first portion of the sample, cleaving the glycoconjugates at
their glycosylation sites of a second portion of the sample,
analyzing the first and second portions of the sample of
glycoconjugates, and quantifying the results. The analysis of the
first and second portions of the sample can be performed separately
or mixed in any ratio.
[0012] In one embodiment, the glycoconjugates of the first portion
are labeled with a label. Preferably the label is an isotope of C,
N, H, S or O. More preferably, the label is O.sup.18. In another
embodiment, the glycoconjugates of the second portion are
unlabeled. In a further embodiment, the glycoconjugates of the
second portion are labeled. In yet another embodiment, the first
and second portions of the sample of glycoconjugates are analyzed
separately. In still another embodiment, the first and second
portions of the sample of glycoconjugates are analyzed as a
mixture. In another embodiment, the glycosylation site occupancy is
quantified from ratios of the masses of cleaved glycoconjugates of
the first and second portions of the sample.
[0013] In a further embodiment, the first and second portions of
the sample are analyzed with a mass spectrometric method.
Preferably, the mass spectrometric method is LC-MS, LC-MS/-MS,
MALDI-MS, MALDI-TOF, TANDEM-MS or FTMS.
[0014] In still another embodiment, the step further includes
generating a list of possible glycoconjugates and/or and peptides,
e.g., using databases. In a second embodiment, the step further
includes generating a list of possible glycans.
[0015] The step of analyzing the glycans includes, in certain
embodiments, analyzing the glycans with a mass spectrometric
method, an electrophoretic method, NMR, a chromatographic method or
a combination thereof. In a further embodiment, the mass
spectrometric method is LC-MS, LC-MS/MS, MALDI-MS, MALDI-TOF,
TANDEM-MS or FTMS. Preferably, the mass spectrometric method is a
quantitiative MALDI-MS or MALDI-FTMS using optimized conditions. In
yet another embodiment, the MALDI-MS is MALDI-MS optimized with a
mixture of 6-aza-2-thiothymine (ATT) and Nafion.RTM. coating. In
still another embodiment, the electrophoretic method is CE-LIF.
[0016] In additional embodiments, the step further includes
contacting the glycans with one or more glycan-degrading enzymes.
In another embodiment, the one or more glycan-degrading enzymes is
sialidase, galactosidase, mannosidase, N-acetylglucosaminidase or a
combination thereof. In yet another embodiment, the step of
analyzing the glycans includes quantifying the glycans using
calibration curves of known glycan standards. In still another
embodiment, the method further includes determining a peptide
sequence of the glycoconjugate.
[0017] In further embodiments of the foregoing methods, low
abundance species are detected due to the low detection limits,
which preferably extend to lower than about 5 fmol. Low abundance
species include, but are not limited to, fucoses, sialic acids,
galactoses, mannoses and sulfate groups.
[0018] According to another aspect of the invention, methods of
analyzing a sample containing glycoconjugates are provided. The
methods include separating glycans from the sample containing the
glycoconjugates, determining the glycosylation sites and
glycosylation site occupancy of the glycoconjugates, and analyzing
the glycans to characterize and/or quantify the glycans.
Determining the glycosylation sites and glycosylation site
occupancy includes cleaving and labeling with a first label the
glycoconjugates of a first portion of the sample at their
glycosylation sites, cleaving the glycoconjugates of a second
portion of the sample at their glycosylation sites, analyzing the
first and second portions of the sample of glycoconjugates, and
quantifying the results.
[0019] In an embodiment, the glycoconjugates of the first portion
are labeled. In a second embodiment, the glycoconjugates of the
second portion are unlabeled. In another embodiment, the
glycoconjugates of the second portion are labeled. In yet another
embodiment, the first and second portions of the sample of
glycoconjugates are analyzed with a mass spectrometric method.
Preferably, the mass spectrometric method is LC-MS, LC-MS/MS,
MALDI-MS, MALDI-TOF, TANDEM-MS or FTMS.
[0020] In certain embodiments, determining the glycosylation sites
and glycosylation site occupancy further includes generating a list
of possible glycoconjugates. In other embodiments, the step of
separating the glycans from the sample includes denaturing the
glycoconjugates with a denaturing agent. Preferably, the
glycoconjugates are reduced with a reducing agent following their
denaturation. More preferably, the glycoconjugates are alkylated
with an alkylating agent following their reduction.
[0021] In further embodiments, the step of analyzing the glycans
includes analyzing the glycans with a mass spectrometric method, an
electrophoretic method, NMR, a chromatographic method or a
combination thereof. The mass spectrometric method preferably is
LC-MS, LC-MS/MS, MALDI-MS, MALDI-TOF, TANDEM-MS or FTMS. The
electrophoretic method preferably is CE-LIF. In still further
embodiments, the step further includes contacting the glycans with
one or more glycan-degrading enzymes. Preferably the one or more
glycan-degrading enzymes is sialidase, galactosidase, mannosidase,
N-acetylglucosaminidase or a combination thereof. In another
embodiment, the method further includes determining a peptide
sequence of the glycoconjugate.
[0022] According to still another aspect of the invention, methods
of determining the glycosylation site occupancy of glycoconjugates
in a sample are provided. The methods include cleaving and labeling
with a first label the glycoconjugates at their glycosylation sites
of a first portion of the sample, cleaving the glycoconjugates at
their glycosylation sites of a second portion of the sample,
analyzing the first and second portions of the sample of
glycoconjugates, and quantifying the results. In an embodiment, the
method further includes determining the possible fragments of the
glycoconjugate.
[0023] In other embodiments, the glycoconjugates of the first
portion are labeled with an isotope of C, N, H, S or O. Preferably
the label is O.sup.18. In a further embodiment, the glycoconjugates
of the second portion are unlabeled. In another embodiment, the
glycoconjugates of the second portion are labeled. In a further
embodiment, the first and second portions of the sample of
glycoconjugates are analyzed with a mass spectrometric method. In
yet a further embodiment, the mass spectrometric method is LC-MS,
LC-MS/MS, MALDI-MS, MALDI-TOF, TANDEM-MS or FTMS.
[0024] In further embodiments of the foregoing methods, low
abundance species are detected due to the low detection limits,
which preferably extend to lower than about 5 fmol. Low abundance
species include, but are not limited to, fucoses, sialic acids,
galactoses, mannoses and sulfate groups.
[0025] According to yet another aspect of the invention, methods of
analyzing a sample containing glycans are provided. The methods
include separating neutral from charged glycans, and analyzing the
neutral and charged glycans separately to analyze the glycan. In
preferred embodiments, the analysis of the glycans is performed
with MALDI-MS.
[0026] In a further aspect of the invention, methods of analyzing a
glycan are provided. The methods include analyzing the glycan in
the presence of Nafion.RTM. and 6-aza-2-thiothymine (ATT).
[0027] Certain embodiments of the foregoing methods are methods of
analyzing the purity of a sample containing glycans. Other
embodiments of the foregoing methods are methods of analyzing the
glycans of a sample of a cell, a group of cells, a tissue or serum
or other body fluid from a subject. Still other embodiments of the
foregoing methods are high-throughput methods, in which more than
one sample of glycoconjugates is analyzed. In some preferred
embodiments, the more than one sample of glycoconjugates are in a
96-well plate. In other preferred embodiments, the more than one
sample of glycoconjugates are on a membrane.
[0028] In other embodiments of the high-throughput methods,
carbohydrate cleavage is performed using enzymes such as PNGase F,
endoglycosydase H, or endoglycosydase F, or chemical methods such
as hydrazinolisis or alkali borohydrate cleavage. Preferably,
cleavage is performed in a high-throughput manner in 96-well plates
or in solution. In certain other embodiments, purification is
performed using solid phase extraction cartridges such as
graphitized carbon columns and C-18 columns. Preferably,
purification is performed in a high-throughput manner in 96-well
plates. All of the foregoing steps, particularly the step of
separation, can be performed with the use of robotics.
[0029] According to another aspect of the invention, methods of
generating a glycoconjugate, (preferably glycopeptide) library are
provided. The methods include cleaving the backbone of the
glycoconjugate (preferably the peptides of the glycopeptides) in a
sample and labeling the fragments generated with a first labeling
agent, and cleaving the glycans in the sample and labeling the
fragments generated in the sample with a second labeling agent.
Preferably the library represents all possible glycoform fragments
of the sample containing the glycoconjugates. The glycoconjugates
preferably are glycopeptides, glycolipids or proteoglycans.
[0030] In certain embodiments, the first and second labeling agent
is the same labeling agent. In other embodiments, the labeling
agent is an isotope of C, N, H, S or O, preferably O.sup.18. In
still other embodiments, the method further includes characterizing
the fragments generated from the cleavage of the glycopeptides. In
some embodiments, the characterization is performed with LC-MS,
LC-MS/MS, MALDI-MS, MALDI-TOF, TANDEM-MS or FTMS. In further
embodiments, the characterizing includes characterizing the
glycosylation sites, characterizing the peptides of the
glycopeptides and/or characterizing the glycans.
[0031] According to a further aspect of the invention, a library of
glycopeptides generated with the foregoing methods is
generated.
[0032] The library can be used as an internal standard to analyze
new batches of glycoconjugates by direct comparison to each labeled
standard from the library. For example, the backbones of new
batches of glycoconjugates can be cleaved and mixed with the
labeled fragments from the library to characterize all the
glycoforms present in the new batch from the ratios of labeled and
unlabeled fragments. Thus, in a further aspect of the invention,
methods of analyzing a sample of glycopeptides are provided. The
methods include analyzing the glycopeptides, and comparing the
analyzed glycopeptides with the foregoing library of glycopeptides
of the foregoing embodiments. In certain embodiments, it is
preferred that comparative characterization is performed using
LC-MS, LC-MS/MS, MALDI-MS, MALDI-TOF, TANDEM-MS or FTMS.
[0033] According to another aspect of the invention, methods of
generating a list of glycoconjugate properties are provided. The
methods include measuring two or more properties of the
glycoconjugate, and recording a value for the two or more
properties of the glycoconjugate to generate a list, wherein the
value of the two or more properties is recorded in a
computer-generated data structure. In some embodiments, one of the
two or more properties of the glycoconjugates is the number of one
or more types of monosaccharides of the glycoconjugate. In other
embodiments, one of the two or more properties of the
glycoconjugates is the total mass of the glycans of the
glycoconjugate. In still other embodiments, the glycoconjugate is a
glycoprotein or proteoglycan, and one of the two or more properties
of the glycoconjugate is the mass of the peptide of the
glycoconjugate. In yet other embodiments, the glycoconjugate is a
glycolipid, and one of the two or more properties of the
glycoconjugate is the mass of the lipid of the glycoconjugate. In
further embodiments, one of the two or more properties of the
glycoconjugate is the mass of the glycoconjugate. In other
embodiments, one of the two or more properties of the
glycoconjugate is the mass of permethylated glycans.
[0034] In a further aspect of the invention, a database, tangibly
embodied in a computer-readable medium, for storing information
descriptive of one or more glycoconjugates is provided. The
database includes one or more data units corresponding to the one
or more glycoconjugates, each of the data units including an
identifier that includes two or more fields, each field for storing
a value corresponding to one or more properties of the
glycoconjugates.
[0035] According to still another aspect of the invention, methods
of analyzing the total glycome of a sample of body fluid, cells or
tissues are provided. The methods include (a) analyzing all the
glycans of the sample, and (b) determining a profile of the glycans
of the sample. In some embodiments, the sample is optionally
fractionated and/or the glycans are separated from the
glycoconjugates. The cleavage, fractionation, purification and/or
separation steps described elsewhere herein are optionally included
in the methods.
[0036] In certain embodiments, the method further includes
performing a pattern analysis on the results from (a) using
computational tools. The pattern can be described as (but is not
limited to) relative amounts of the components of the pattern,
absolute amounts of the components of the pattern, ratios between
the components of the pattern, combinations of different components
of the pattern, presence or absence of any of the components of the
pattern or combination of the above. In certain embodiments, the
identification of the glycome pattern and the pattern analysis can
be performed using computational methods. Preferably this includes
an iterative process, which optionally includes one of more of the
following: incorporation of all experimental data sets from the
glycome analysis and other glycan characterization, generation of
theoretical glycan structures, incorporation of glycan composition,
incorporation of structure and property information from databases,
incorporation of glycan biosynthetic pathway information,
incorporation of patient (or sample origin) information such as
patient history and demographics, extract features from the
experimental data sets, generation of data sets with specific
features, submitting the combined information to data mining
analysis, establishing relationship rules and validating the
patterns.
[0037] In other embodiments, step (a) includes quantifying the
glycans using calibration curves of known glycan standards. In
another embodiment, the method further includes recording the
pattern in a computer-generated data structure. In yet another
embodiment, the method is a method for diagnostic or prognostic
purposes. In a further embodiment, the method is a method for
assessing the purity of the sample. In yet another embodiment, the
sample is a sample of serum, plasma, blood, urine, saliva, sputum,
tears, CSF, seminal fluid, feces, tissues or cells.
[0038] According to another aspect of the invention, methods of
analysis are provided. The methods include (a) analyzing all of the
glycans of a sample of body fluid, cells and/or tissues and (b)
comparing the results from (a) with a known pattern. In an
embodiment, the sample is a sample of serum, plasma, blood, urine,
saliva, sputum, tears, CSF, seminal fluid, feces, tissues or
cells.
[0039] In some embodiments, the methods are methods of diagnosis
and the pattern is associated with a diseased state. In one
preferred embodiment, the pattern associated with a diseased state
is a pattern associated with cancer, such as prostate cancer,
melanoma, bladder cancer, breast cancer, lymphoma, ovarian cancer,
lung cancer, colorectal cancer or head and neck cancer. In other
preferred embodiments, the pattern associated with a diseased state
is a pattern associated with an immunological disorder; a
neurodegenerative disease, such as a transmissible spongiform
encephalopathy, Alzheimer's disease or neuropathy; inflammation;
rheumatoid arthritis; cystic fibrosis; or an infection, preferably
viral or bacterial infection. In other embodiments, the method is a
method of monitoring prognosis and the known pattern is associated
with the prognosis of a disease. In yet another embodiment, the
method is a method of monitoring drug treatment and the known
pattern is associated with the drug treatment. In particular, the
methods (e.g., analysis of glycome profiles) are used for the
selection of population-oriented drug treatments and/or in
prospective studies for selection of dosing, for activity
monitoring and/or for determining efficacy endpoints.
[0040] In another aspect of the invention, methods of determining
the purity of a sample are provided. The methods include (a)
analyzing total glycans of the sample, (b) identifying the glycan
pattern of the sample, and (c) comparing the pattern with a known
pattern to assess the purity of the sample. Similar methods are
provided in which glycoconjugates in sample are analyzed.
[0041] In an aspect of the invention, a method of generating the
complete glycan pattern of a body fluid, cells and/or tissue is
provided. The method includes, (a) analyzing the glycans in a
sample of the body fluid, cells and/or tissue, and (b) identifying
the complete glycan pattern of the sample. In an embodiment,
neutral, charged, N-linked and O-linked glycans are included in the
pattern. In other embodiments, glycosaminoglycans and glycolipids
are included in the pattern. In a second embodiment, the sample is
a sample of serum, plasma, blood, urine, saliva, sputum, tears,
CSF, seminal fluid, feces, tissues or cells.
[0042] In a further aspect of the invention, methods of analyzing
the total glycome of a sample are provided. The methods include
determining the glycosylation site and glycosylation site occupancy
of all glycoconjugates in the sample, characterizing components of
the glycoconjugates and all glycans of the glycome in the sample,
and matching specific glycans to glycoconjugates with a
computational method.
[0043] According to another aspect of the invention, methods of
analyzing a sample of glycoconjugates are provided. The methods
include analyzing the glycans of the sample with an analytical
method, and determining the glycoforms of the sample with a
computational method. In certain embodiments of the foregoing
methods, the methods include generating constraints from the
experimental analysis and solving them.
[0044] A further method for matching each carbohydrate in the
glycome to its glycoconjugate includes characterization of
glycosylation sites and occupancy of all glycoconjugates from body
fluids, determination of possible glycans at each site by comparing
unlabeled, glycoconjugate fragments to labeled, deglycosylated
fragments, characterization of the entire glycome from body fluids,
and combination of the different datasets into the iterative
computational analysis to match the glycans to the
glycoconjugates.
[0045] Each of the limitations of the invention can encompass
various embodiments of the invention. It is, therefore, anticipated
that each of the limitations of the invention involving any one
element or combinations of elements can be included in each aspect
of the invention.
BRIEF DESCRIPTION OF THE FIGURES
[0046] FIG. 1 shows the conserved N-glycan pentasaccharide
core.
[0047] FIG. 2 illustrates classes of N-linked glycans. High-mannose
structures contain up to 9 mannose residues (FIG. 2A). Complex type
glycans are modified with hexosamines, galactoses, sialic acids
and/or fucose, among other residues (FIG. 2B). Complex type chains
can occur as mono-, bi-, tri-, and tetra-antennary structures.
Also, the amount and type of sialylation differs. Hybrid structures
contain characteristics of both high-mannose and complex types
(FIG. 2C).
[0048] FIG. 3 provides the detailed pathway of N-glycan
biosynthesis
(http://www.genome.ad.jp/kegg/pathway/map/map00510.html).
[0049] FIG. 4 shows the cleavage sites of EndoH, EndoF and PNGaseF.
EndoH can only act on high mannose and hybrid structures, while
EndoF is effective at cleaving all classes of N-glycans. PNGaseF
also cleaves all mammalian N-glycan structures.
[0050] FIG. 5 provides the MALDI-MS spectra of N-glycans from
RNaseB samples prepared by various methods. Glycans after
GlycoClean S (Table 2, Sample 12), with the expected high mannose
peaks and significant contamination of unknown identity (FIG. 5A).
A small amount of sample (10 .mu.g) was prepared using a 25 mg
GlycoClean H column (Table 2, Sample 17), which showed only
detergent peaks (FIG. 5B). A larger amount of protein (50 .mu.g)
was prepared (Table 2, Sample 18), yielding the expected glycan
peaks but still containing detergent contamination (FIG. 5C). Using
a 200 mg GlycoClean H column to purify N-glycans from 150 .mu.g of
RNaseB (Table 2, Sample 20), only the high mannose saccharides were
observed (FIG. 5D).
[0051] FIG. 6 shows the spectra from MALDI-MS of N-glycans from
ovalbumin. Each labeled peak corresponds to a previously reported
structure listed in Table 3.
[0052] FIG. 7 provides results from a study of N-glycans from
antibody samples. FIGS. 7A and 7B are for samples from Applikon
bioreactors, with DO=50%, pH=7 and DO=90%, pH uncontrolled,
respectively. FIGS. 7C-7E are for samples from Wave reactors. FIG.
7C represents the results for DO controlled, pH uncontrolled, and
NaOH in the media, while FIG. 7D represents the results with
NaHCO.sub.3 in the media instead of NaOH. The results shown in FIG.
7E are for DO uncontrolled with pH=7.
[0053] FIG. 8 shows the structures and theoretical masses of
N-glycans released from antibodies.
[0054] FIG. 9 MALDI-MS spectra of glycans released from serum
proteins using PNGaseF and EndoF. Serum samples were treated with
PNGaseF (FIG. 9A) or EndoF (FIG. 9B) and purified. While glycans
were observed, the samples did not produce clean results. The peak
cluster indicated by an arrow represents detergent
contamination.
[0055] FIG. 10 shows a separation of neutral and acidic glycans
using GlycoClean H cartridge. (a) The original mix of standards is
shown in positive mode. A3 and SC1840 are additional highly
charged, and do not ionize well. (b) Neutral glycans eluted off the
GlycoH cartridge ionize well in positive mode, while only the
charged sugars are present in (c), allowing them to be observed in
negative mode. The multiple peaks in (c) arise from sodium adducts,
typically one adduct per sialic acid residue.
[0056] FIG. 11 provides the results from MALDI-MS of N-glycans from
human serum in neutral (left) and acidic (right) fractions. (a) and
(b) represent neutral glycans prepared from two different IMPATH
normal male human serum samples, while (d) and (e) show the acidic
fraction. (c) and (f) are the neutral and acidic fractions of a
normal human sample from Biomedical Resources.
[0057] FIG. 12 provides the results of serum glycans separated by
ConA. (a) SDS-PAGE of ConA flow through (Lane 2) and elution (Lane
3). vLane 1 shows molecular weight standards. vMALDI-MS of (b)
neutral and (c) acidic sugars obtained from ConA elution.
[0058] FIG. 13 provides the results from protein A separation of
IgG from serum. (a) Glycoblot of Protein A flow-through (Lane 3)
and elution (Lane 4). Lane 1 contains protein standards, while Lane
2 (negative control) contains human serum albumin (* marks where
albumin would run on an SDS-PAGE gel). Only glycosylated proteins
are observed in the glycoblot, so the albumin does not stain.
MALDI-MS of glycans harvested from the elution fraction are shown
in (b) neutral and (c) acidic. Total serum glycans are pictured in
(d) neutral and (e) acidic.
[0059] FIG. 14 shows the permethylation of N-glycans. All OH and NH
groups can be permethylated. For complete reaction, it is essential
that the reaction vessel is free of air and water.
[0060] FIG. 15 shows the results of MALDI-MS of permethylated
glycan standards. (a) Unmodified standards ionized unevenly.
Permethylated standards (b) showed more uniform ionization, but
generally did not have higher signal-to-noise ratios.
[0061] FIG. 16 shows the aminooxyacetyl peptide and its conjugation
to N-glycans. The aminooxyacetate end of the synthetic peptide
(top) reacts with the open form of the reducing end GlcNAc of
N-glycans (bottom).
[0062] FIG. 17 shows the results of MALDI-MS of peptide-conjugated
N-linked standards. (a) Unmodified glycans ionize unevenly,
especially charged glycans f and g. After conjugation with
aminooxyacetyl peptide (b), ionization is much more uniform.
[0063] FIG. 18 shows the identification of serum N-glycans from
MALDI-MS spectra. (a) shows neutral glycans, while (b) shows acidic
glycans. Labeled peak numbers correspond to entries in Table 7.
[0064] FIG. 19 shows the results of neutral N-glycans from PVDF
digest. Only the most abundant glycans are observed.
[0065] FIG. 20 provides a MALDI spectra of glycans before (A) and
after (B) applying new recipe with optimized conditions.
[0066] FIG. 21 provides results from glycan quantification using
optimized matrix recipe for MALDI-MS
[0067] FIG. 22 provides a schematic of an example of a methodology
for analysis.
[0068] FIG. 23 provides a flowchart illustration of one example of
a combined analytical-computational method for glycan analysis.
[0069] FIG. 24 provides a scheme for an exemplary method for
glycoprotein analysis--glycan site occupancy analysis.
[0070] FIG. 25 provides results from glycan site occupancy analysis
for ribonuclease B. MS data for peptide eluting at 7.8 minutes for
unlabeled sample (A) and for the 16O/18O labeled 1:1 mixture (B).
The expected [M+H]+ for the unlabeled peptide fragment is 476.29
Da.
[0071] FIG. 26 provides MALDI-MS spectra of N-glycans from RNaseB
with the expected high mannose structures.
[0072] FIG. 27 provides results from MALDI-MS of N-glycans from
ovalbumin. Each labeled peak corresponds to a previously reported
structure listed below.
[0073] FIG. 28 provides structures and theoretical masses of
N-glycans released from antibodies.
[0074] FIG. 29 shows the results from an analysis of depletion of
serum albumin and IgGs from serum. A) SDS gel stained with Simply
blue before (lane 7 and 14) and after removal of serum albumin and
IgG using different conditions (lanes 1-6 and 8-13). B) Western
blot (using protein A-HRP detection) used for quantifying the
removal of IgGs. Lanes 7 and 14 are without depletion and 1-6 and
8-13 are using different conditions for the removal. C)
Quantification of IgG removal.
[0075] FIG. 30 shows the results of protein A separation of IgG
from serum. (a) Glycoblot of Protein A flow-through (Lane 3) and
elution (Lane 4). Lane 1 contains protein standards, while Lane 2
(negative control) contains human serum albumin (* marks where
album would run on an SDS-PAGE gel). Only glycosylated proteins are
observed in the glycoblot, so the albumin does not stain.
[0076] FIG. 31 shows the identification of serum N-glycans from
MALDI-MS spectra. (a) shows neutral glycans, while (b) shows acidic
glycans.
[0077] FIG. 32 provides the results from LC-MS (A) and CE-LIF(B)
analysis of neutral glycome from serum.
[0078] FIG. 33 provides the MALDI-MS acidic glycome profile of
saliva (A) and urine (B).
[0079] FIG. 34 provides quantitative neutral glycome profile for
serum with normal (A) and low (B) IgG levels.
[0080] FIG. 35 provides alterations in serum glycomic patterns
between matched healthy (A) and cancer (B) patients
[0081] FIG. 36 provides a schematic representation of an example of
the computational strategy for the analysis of glycoprofile
patterns.
DETAILED DESCRIPTION
[0082] It has been recognized that carbohydrates play a signficant
role in a variety of biological and pathological processes.
However, information regarding which carbohydrates are important
and how they affect biological functions is limited. Therefore,
additional methods for analyzing carbohydrates are desirable. Some
of the methods provided herein provide better limits of detection
of glycans and/or glycoconjugates that, in some examples, can
extend to lower than 5 fmol.
[0083] Methods are provided herein which are directed to improved
methods of analyzing carbohydrates. As used herein, the term
"carbohydrate" is intended to include any of a class of aldehyde or
ketone derivatives of polyhydric alcohols. Therefore, carbohydrates
include starches, celluloses, gums and saccharides. Although, for
illustration, the term "saccharide" or "glycan" is used below, this
is not intended to be limiting. It is intended that the methods
provided herein can be directed to any carbohydrate, and the use of
a specific carbohydrate is not meant to be limiting to that
carbohydrate only.
[0084] As used herein, the term "saccharide" refers to a polymer
comprising one or more monosaccharide groups. Saccharides,
therefore, include mono-, di-, tri- and polysaccharides (or
glycan). Glycans can be branched or branched. Glycans can be found
covalently linked to non-saccharide moieties, such as lipids or
proteins (as a glycoconjugate). These covalent conjugates include
glycoproteins, glycopeptides, peptidoglycans, proteoglycans,
glycolipids and lipopolysaccharides. The use of any one of these
terms also is not intended to be limiting as the description is
provided for illustrative purposes. In addition to the glycans
being found as part of a glycoconjugate, the glycans can also be in
free form (i.e., separate from and not associated with another
moiety). The use of the term peptide is not intended to be
limiting. The method provided herein are also intended to include
proteins where "peptide" is recited.
[0085] The methods, therefore, provided can be used to analyze
glycans that are found as part of a glyconjugate or are found in
free form. The methods provided are also directed to the analysis
of the total glycome of a sample. The sample can be of a cell,
group of cells, tissue or serum. The "total glycome" refers to all
of the glycans that can found in a sample. For instance, the
glycans can be in free form or they can be part of one or more
glycoconjugates in the sample. The total glycome, therefore,
represents all of the glycans (in free form, as part of
glycoconjugates or both) in the sample. Likewise the use of the
phrase "a sample of glycans" or the like is intended to include a
sample containing free glycans and/or glycans as part of
glycoconjugates. The sample can be, for instance, a sample of body
fluid. Samples of body fluid include serum, plasma, blood, urine,
saliva, sputum, tears, CSF, seminal fluid, feces, etc. The sample,
can also be, as an example, a sample of a cell, group of cells or
tissue.
[0086] Glycans include N- and O-glycans. For illustration, but not
intended to be limiting, N-glycans are classified into three types
based on their structure: high mannose, hybrid and complex [Sears,
P., Wong, C. H. (1998) Enzyme action in glycoprotein synthesis.
Cell Mol Life Sci 54, 223-52.] All N-glycans contain a conserved
pentasaccharide core composed of two N-acetylglucosamine residues
followed by three mannose saccharides (FIG. 1). High mannose
structures contain up to six more mannoses on both branches (FIG.
2A), while complex structures have no additional mannoses on either
arm (FIG. 2B). Instead, they are composed of additional hexosamines
and/or galactose. Hybrid structures are mixes of both high mannose
and complex structures (FIG. 2C). Additionally, branch termini can
be capped with sialic acid (a charged monosaccharide), and the core
or branches can be fucosylated. Many other rare modifications
exist, including sulfate, phosphate and xylose, but these are
typically not found in humans. As provided herein, the methods of
analyzing glycans may include the analysis of any glycan including
glycans with any of the structures described herein. The term
"glycan" is also intended to include glycans that are intact (i.e.,
as they were originally found in a sample) or have been digested
(i.e., fragment of the original glycan).
[0087] Glycans can be analyzed with a number of different methods
that include different steps and different experimental techniques.
The glycans can be, for example, those displayed on proteins or
lipids, on the surface of cells or any of the glycans that are
present in a body fluid. In general, when the glycans in a sample
are part of a glycoconjugate, the sample of glycoconjugates can be
first denatured with a denaturing agent.
[0088] A "denaturing agent" is an agent that alters the structure
of a molecule, such as a protein. Denaturing agents, therefore,
include agents that cause a molecule, such as a protein to unfold.
Denaturing can be accomplished with any of a number of methods that
are known in the art. Denaturing can be accomplished, for instance,
with heat, with heat denaturation in the presence of
.beta.-mercaptoethanol and/or SDS, by reduction followed by
carboxymethylation (or alkylation), etc. Reduction can be
accomplished with reducing agent, such as, dithiothreitol (DTT).
Carboxymethylation or alkylation can be accomplished with, for
example, iodoacetic acid or iodoacetamide. Denaturation can, for
example, be accomplished by reducing with DTT,
.beta.-mercaptoethanol or tri(2-carboxyethyl)phosphine (TCEP)
followed by carboxymethylation with iodoacetic acid. When the
glycoconjugate sample is a sample of a body fluid, such as serum,
the denaturation can be accomplished with EndoF. The
glycoconjugates can also be denatured with denaturing agents, such
as detergent, urea or guanidium hydrochloride.
[0089] In some methods following denaturation the sample of
glycoconjugates is reduced with a reducing agent. As provided
above, reducing agents include DTT, .beta.-mercaptoethanol and
tri(2-carboxyethyl)phosphine (TCEP). In other methods the sample of
glycoconjugates is alkylated after being reduced, such as, for
example, with iodoacetic acid or iodoacetamide.
[0090] Methods of analyzing glycans of glycoconjugates can also
include cleaving the glycans from the non-saccharide moiety using
any chemical or enzymatic methods or combinations thereof that are
known in the art. An example of a chemical method for cleaving
glycans from glycoconjugates is hydrazinolysis or alkali
borohydrate. Enyzmatic methods include methods that are specific to
N- or O-linked sugars. These enzymatic methods include the use of
Endoglycosidase H (Endo H), Endoglycosidase F (EndoF), N-Glycanase
F (PNGaseF) or combinations thereof. In some preferred embodiments,
PNGaseF is used when the release of N-glycans is desired. When
PNGaseF is used for glycan release the proteins is, for example,
first unfolded prior to the use of the enzyme. The unfolding of the
protein can be accomplished with any of the denaturing agents
provided above.
[0091] The glycans analyzed by the methods provided herein can also
be contacted with a glycan-degrading enzyme. Examples of
glycan-degrading enzymes are known in the art and include
sialidase, galactosidase, mannosidase, N-acetylglucosaminidase or a
combination thereof. The methods provided herein also include the
use of a carbohydrate-degrading enzyme. As used herein
"carbohydrate-degrading enzymes" or "glycan-degrading enzymes" are
enzymes that can modify a carbohydrate or glycan in some way. Some
examples of glycan-degrading enzymes include sialidase,
galactosidase, mannosidase, N-acetylglucosaminidase or some
combination thereof
[0092] After the release of the glycan from the protein core, or
when the glycans were already in free form (not part of a
glycoconjugate), the sample can be purified, for instance, by
precipitating the proteins with ethanol and removing the
supernatant containing the glycans. Other experimental methods for
removing the proteins, detergent (from a denaturing step) and salts
include any methods known in the art. These methods include
dialysis, chromatographic methods, etc. In one example, the
purification is accomplished with a porous graphite column. In some
preferred embodiments, everything but the glycans are removed from
the sample. Samples can also be purified with commercially
available resins and cartridges for clean-up after chemical
cleavage or enzymatic digestion used to separate glycans from
protein. Such resins and cartridges include ion exchange resins and
purification columns, such as GlycoClean H, S, and R cartridges.
Preferably, in some embodiments GlycoClean H is used for
purification.
[0093] Purification can also include the removal of high abundance
proteins, such as the removal of albumin and/or antibodies, from a
sample containing glycans. In some methods the purification can
also include the removal of unglycosylated molecules, such as
unglycosylated proteins. Removal of high abundance proteins can be
a desirable step for some methods, such as some high-throughput
methods described elsewhere herein. In some embodiments of the
methods provided, abundant proteins, such as albumin or antibodies,
can be removed from the samples prior to the final composition
analysis.
[0094] Prior to the analysis of a sample of glycans as provided
herein the sample of glycans can also be fractionated. The sample
can be fractionated so as to obtain a sample of glycans with
specific subgroups of molecules. "Subgroups of molecules" include
molecules of specific properties, such as charge, molecular weight,
size, binding properties to other molecules or materials, acidity,
basicity, pI, hydrophobicity, hydrophilicity, etc. In one
embodiment the subgroup of molecules of a sample is the low
abundance species, and it is the low abundance species that are
analyzed with the methods. The low abundance species can contain
fucoses, sialic acids, galactoses, mannoses or sulfate groups.
[0095] The fractionation can be performed using any methods known
in the art. Such methods include using solid supports with
immobilized proteins, organic molecules, inorganic molecules,
lipids, carbohydrates, nucleic acids, etc. The fractionation can
also be performed with filters, such as molecular weight cutoff
filters, resions, such as cation or anion exchange resins, etc.
Therefore, the method provided herein can be used for the analysis
of the glycans of a subgroup of molecules.
[0096] Glycans can be charged or uncharged. They can be acidic,
basic or neutral. It has now been found that separately analyzing
charged and uncharged glycans of a sample can provide an
improvement in the analysis of glycans. Therefore, the charged and
uncharged glycans can be separated prior to the analysis of the
glycans, such as with an analytic method. As described further in
the Examples provided below, such a method has now been found to
clearly discriminate the glycans present in the sample. Therefore,
any of the methods provided herein can include a step of separating
neutral and charged glycans, such as acidic glycans. Such
separation can be achieved using purification methods. For
instance, in a preferred embodiment, the separation is accomplished
with a porous carbon purification cartridge by eluting glycan pools
with different concentrations of acetonitrile. Other methods will
be known to those of skill in the art. Analysis of these separate
glycan pools can then be undertaken. For instance, when using
MALDI-MS, the acidic glycans can be analyzed in negative ion mode,
while the neutral glycans are analyzed in positive ion mode.
[0097] In other embodiments, the glycans can be modified to improve
ionization of the glycans, particularly when MALDI-MS is used for
analysis. Such modifications include permethylation. An other
method to increase glycan ionization is to conjugate the glycan to
a peptide. Examples of the methods are described further in the
Examples below. In other embodiments, spot methods can be employed
to improve signal intensity.
[0098] Any analytic method for analyzing the glycans so as to
characterize them can be performed on any sample of glycans, such
analytic methods include those described herein. As used herein, to
"characterize" a glycan or other molecule means to obtain data that
can be used to determine its identity, structure, composition or
quantity. When the term is used in reference to a glycoconjugate,
it can also include determining the glycosylation sites, the
glycosylation site occupancy, the identity, structure, composition
or quantity of the glycan and/or non-saccharide moiety of the
glycoconjugate as well as the identity and quantity of the specific
glycoform. These methods include, for example, mass spectrometry,
NMR (e.g., 2D-NMR), electrophoresis and chromatographic methods.
Examples of mass spectrometic methods include FAB-MS, LC-MS,
LC-MS/-MS, MALDI-MS, MALDI-TOF, TANDEM-MS, FTMS, etc. NMR methods
can include, for example, COSY, TOCSY, NOESY. Electrophoresis can
include, for example, CE-LIF. In one embodiment the glycans can be
quantified using calibration curves of known glycan standards. More
details regarding examples of these methods are provide below in
the Examples.
[0099] Other methods that can be used to analyze the saccharide
composition of the glycans once released from the protein include
procedures involving the labeling of the saccharides with chemical
or fluorescent tags. Such methods include fluorescence assisted
carbohydrate electrophoresis (FACE), HPLC or capillary
electrophoresis (CE). A method for the compositional analysis of
oligosaccharides using CE has been described (Rhomberg, A. J.,
Ernst, S., Sasisekharan, R. & Biemann, K. (1998) Proc Natl Acad
Sci USA 95, 4176-81).
[0100] In some embodiments, the analytic method for the
characterization of the glycans includes the use of MALDI-MS.
Matrix-assisted laser desorption ionization mass spectrometry
(MALDI-MS) techniques for the analysis of oligosaccharides have
also been described (Juhasz, P. & Biemann, K. (1995) Carbohydr
Res 270, 131-47 and Juhasz, P. & Biemann, K. (1994) Proc Natl
Acad Sci USA 91, 4333-7; Venkataraman, G., Shriver, Z., Raman, R.
& Sasisekharan, R. (1999) Science 286, 537-42; Rhomberg, A. J.,
Shriver, Z., Biemann, K. & Sasisekharan, R. (1998) Proc Natl
Acad Sci USA 95, 12232-7; Ernst, S., Rhomberg, A. J., Biemann, K.
& Sasisekharan, R. (1998) Proc Natl Acad Sci USA 95, 4182-7;
and Rhomberg, A. J., Ernst, S., Sasisekharan, R. & Biemann, K.
(1998) Proc Natl Acad Sci USA 95, 4176-81). Optimized MALDI-MS
analytic methods are also provided herein.
[0101] Analytic methods can also comprise the use of carbohydrate-
or glycan-degrading enzymes. Following enzymatic degradation the
sample of degraded glycans can be further analyzed with an analytic
method as described above or otherwise known in the art.
[0102] The characterization of one or more glycoconjugates with an
analytic method can also include determining the identity,
structure or sequence of the non-saccharide moiety of the
glycoconjugate. As an example, the characterization with an
analytic method can include determining the peptide (or lipid)
sequence of a glycopeptide (or glycolipid). Such methods are known
in the art and examples are provided in the Examples section
below.
[0103] In some methods, such as with MALDI-MS, the matrix in which
the sample of glycans is suspended may affect the quality of
compositional analysis. In some embodiments the matrix preparation
is caffeic acid with or without spermine. In other embodiments, the
matrix preparation is DHB with or without spermine. In preferred
embodiments the matrix preparation is spermine with DHB. The
spermine, for example, can be in the matrix preparation at a
concentration of 300 mM. The matrix preparation can also be a
combination of DHB, spermine and acetonitrile. MALDI-MS can also be
performed in the presence of Nafion and ATT. Additionally, when
using MALDI-MS to analyze the samples, instrument parameters can
also be modified. These parameters may include guide wire voltage,
accelerating voltage, grid values and negative versus positive
mode.
[0104] The samples of glycans can be analyzed separately or they
can be analyzed as a mixture. The methods provided include methods
for the analysis of glycosylation of a single protein (or lipid) in
a sample or a mixture of proteins (or lipids or a mixture of
proteins and lipids). Such mixtures can contain glycosylated and
non-glycosylated proteins and/or lipids.
[0105] A glycoconjugate, such as a glycoprotein, can exist in many
glycoforms; that is, each glycosylation site may (or may not) be
occupied by a specific glycan all the time. The methods provided
comprise or consist of steps for determining the glycosylation site
occupancy of the glycoconjugates of a sample. As used herein, the
term "glycosylation site occupancy" refers to the frequency
(percentage) in which one or more specific glycosylation sites on a
lipid, protein or peptide is occupied by a glycan. The
glycosylation site can be determined using the methods provided
below in the Examples as well as methods that are known in the art.
In one embodiment the glycosylation site occupancy is the "total
glycosylation site occupancy", which refers to the frequencies in
which all of the specific glycosylation sites on a lipid, protein
or peptide are occupied by a glycan. The specific glycans that
occupy each specific glycosylation site can also be characterized
using one or more analytic techniques.
[0106] 2D-NMR provides a reliable method for the identification of
N-linked and O-linked glycan site occupancy. A combination of COSY,
TOCSY, NOESY experiments are first conducted on a specific quantity
of a glycoprotein. Using COSY and TOCSY data, all the spin systems
(amino acids) are assigned. NOESY experiments are subsequently used
to determine the specific amino acid sequence. This information
allows the specific identification of all the asparagines (Asn) and
serine (Ser) or threonine (Thr) residues in the sample. More
importantly, since NOES between the protons of the Asn, Ser or Thr
side chains and proximal carbohydrate residues can be easily
monitored, this allows the monitoring and quantification of site
glycan occupancy at each glycosylation site. This is particularly
useful for high abundance glycosylation sites.
[0107] Also provided in one aspect of the invention is a method for
determining glycosylation site occupancy of a glycoconjugate. For
the determination of the glycan site occupancy, such as for lower
abundance glycoforms, concepts from phosphoproteomics were adapted.
FIG. 24 provides one embodiment of a method for determining
glycosylation site occupancy. Briefly, a well characterized batch
of the glycoprotein under study is used to generate a library of
labeled peptides and glycopeptides by trypsin digest. In order to
order to facilitate the determination of the glycosylation sites,
each glycosylated amino acid is differentially labeled. The labels
that can be used include isotopes of C, N, H, S, or O. In one
embodiment the glycosylated amino acids are labeled with O.sup.18
and O.sup.16 using methods known in the art. [Kaji, 2003]. After
the labeling, the samples can be further analyzed. In one
embodiment the glycan site occupancy is quantified from the ratios
of the masses of the labeled and unlabeled fragments. In one
examples, determining the glycosylation site and its occupancy can
include cleaving and labeling with a first label the
glycoconjugates at the glycosylation sites of a portion of the
sample, cleaving the glycoconjugates at the glycosylation sites of
another portion of the sample and analyzing the portion of the
sample. The portions of the sample can be analyzed separately or as
a mixture in any ratio. First instance, when there are two portions
of the sample, the two portions can be mixed in a 1:1, 1:2, 1:3,
1:4, or 1:5 ratio. The glycosylation site occupancy method can be
used to determine the identity and number of glycoforms in the
sample. Therefore, a method of determining the identity and number
of glycoforms in a sample comprising determining the glycosylation
site occupancy of a glycoconjugate and analysis to characterize the
glycoconjugates so as to determine the identity and number of
glycoforms is also provided.
[0108] As illustrated in the Examples below, the fragment
containing the partner peak with a molecular weight 2 Da heavier is
identified as the peptide containing the glycosylation site. By
comparing the data between the glycosylated and deglycosylated
samples, a preliminary identification all the peptides (or lipids
when the glycoconjugate is a glycolipid) and glycopeptides (or
glycolipid) are identified and a preliminary identification of the
glycans is obtained. This quantitative information can be combined
with a glycan analysis and used as constraints in a computational
analysis, such as the one described below, to arrive at the
complete characterization of the glycoprotein.
[0109] "Constraints" as used herein are one or more values or
relationships to which results obtained from an analysis of a
sample containing glycans can be compared to or evaluated. The
constraints can, for example, be one or more mathematical equations
that can be solved with the data obtained from an analysis of a
sample containing glycans and/or other data obtained from other
sources, such as databases or with other analytical tools. The
constraints can, for example, be generated from the one or more of
the results obtained from an analysis of a sample of glycans and/or
with other glycan/glycoconjugate information, such as the
information regarding glycan synthesis or from databases.
[0110] The labels that can be used in any of the methods provided
include isotopes of C, N, H, S, or O. In one embodiment the
glycosylated amino acids are labeled with O.sup.18.
[0111] Also provided is a method of generating a library. The
library consists of labeled glycoconjugates and fragments of the
glycoconjugates, the fragments being the non-saccharide portions of
the glycoconjugates. In one example, a library is generated by
cleaving the backbone of the glycoconjugate and labeling the
non-saccharide fragments and and the non-saccharide portions of the
glycoconjugates that result with a labeling agent. This example
also includes the step of cleaving the glycans from the
glycoconjugate. The glycans can then be removed from the sample.
The libraries so produced can be analyzed with the methods provided
herein. The libraries can also be used as a standard once
characterized and methods of using such libraries are also
provided. In one example, a method of analyzing a sample with
glycoconjugates includes cleaving the glycoconjugates,
enzymatically removing the glycans from the glycoconjugates and
mixing the sample with a standard. The sample mixed with the
standard can then be analyzed. In one embodiment, the amounts of
the glycoconjugates and non-saccharide moieties of the sample and
standard are compared. In one aspect of the invention the standards
are also provided.
[0112] The methods provided can also comprise or consist of the
steps of generating a list of glycan properties. One example of
such a method includes measuring 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or
more properties of the glycan, recording a value for the one or
more properties to generate a list of the glycan properties. The
method also is intended to refer to generating a list of
glycoconjugate properties. A "property" as used herein is a
characteristic (e.g., structural characteristic) of the glycan or
glycoconjugate that provides information (e.g., structural
information) about the glycan or glycoconjugate. Examples of
properties include charge, chirality, nature of substituents,
quantity of substituents, molecular weight, molecular length,
compositional ratios of substituents or units, type of basic
building blocks (saccharide, amino acid, lipid constituents),
hydrophobicity, enzymatic sensitivity, hydrophilicity, secondary
structure and conformation, ratio of one set of modifications to
another set of modifications, etc. In one embodiment the list
comprises the number of one or more types of monosaccharides. The
list can also include the total mass of the glycan or
glycoconjugate, the mass of the non-saccharide moiety of a
glycoconjugate, the mass of one and/or more modified glycans, etc.
The list in one embodiment can be a data structure tangibly
embodied in a computer-readable medium, such as computer hard
drive, floppy disk, CD-ROM, etc. Table 6 represents an examples for
such a data structure. The data structure of Table 6 has a
plurality of entries, where each entry encodes a value of a
property. The values encoded can be encoded by any kind of value,
for example, as single-bit values, single-digit hexadecimal values,
or decimal values.
[0113] Therefore, also provided is a database, tangibly embodied in
a computer-readable medium, wherein the database stores information
descriptive of one or more glycans and/or glycoconjugates. The
database comprises data units that correspond to the glycan and/or
glycoconjugate. The data units include an identifier that includes
one or more fields, each field storing a value corresponding to one
or more properties of the glycans and/or glycoconjugates. In one
embodiment the identifier includes 2, 3, 4, 5, 6, 7, 8, 9, 10 or
more fields. The database, for example, can be a database of all
possible glycoconjugates, glycans or can be a database of values
representing a glycome profile or pattern for one or more samples.
Methods of analyzing and characterizing a glycome profile or
pattern is described further below.
[0114] Herein, improved methods for analyzing samples containing
glycans are provided, which include a combined
analytical-computational platform to achieve a thorough
characterization of glycans. Therefore, any of the methods provided
can be combined with computational methods. Non-limiting examples
of the computational methods that can be used are illustrated in
detail in the Examples. Briefly, the diverse information gathered
from the different experimental techniques can be used to generate
constraints. This can be done in combination with a panel of
proteomics and glycomics based bioinformatics tools and databases
for the efficient characterization (glycosylation site occupancy,
quantification, glycan structure, etc.) of the
glycan/glycoconjugate mixture of interest. The databases can be
those known in the art or can be generated with the methods
provided. As an example, a method of analyzing glycans with the
combined analytic and computational techniques can include the
steps of performing an experiment on a sample containing glycans,
analyzing the results of the experiment, generating constraints and
solving them. The constraints can be generated and/or solved with
the data obtained from experimental results as well as other known
information, such as information from databases that contain
information about glycans or glycoconjugates and with other tools
that analyze the properties of glycans, glycoconjugates or the
non-saccharide moieties thereof, such as mass and enzyme
action.
[0115] The constraints can be generated using, for instance, what
is known of the biosythetic pathway of glycan synthesis. Unlike DNA
or protein synthesis, which are template-driven processes, glycan
biosynthesis is a complex process involving a multitude of enzymes.
A detailed scheme of N-glycan biosynthesis is shown in FIG. 3 and
the biosynthetic enzymes and their EC numbers are listed in Table
1. The process is initiated in the cytoplasm, with the nascent
sugar attached to the ER membrane through a lipid anchor. After a
glycan core of two glucosamines followed by five mannose residues
is constructed, the orientation of the growing glycan is flipped to
face the lumen of the ER. There, four more mannose residues are
added by .alpha.-mannosyltransferase, and one branch is capped with
three glucoses. At this point, oligosaccharyl transferase catalyzes
the removal of the naive glycan from its lipid anchor, and attaches
it to a glycosylation site on a protein undergoing synthesis in the
ER [Varki, A. (1999) Essentials of glycobiology. Cold Spring Harbor
Laboratory Press, Cold Spring Harbor, N.Y.]
[0116] To ensure that the glycan can play its proper role in
protein folding and transport, the three terminal glucose residues
and one mannose are removed. This trimming is required for the
glycan to interact with the chaperone proteins calnexin and
calreticulin [Helenius, A., Aebi, M. (2001) Intracellular functions
of N-linked glycans. Science 291, 2364-9; Parodi, A. J. (2000)
Protein glucosylation and its role in protein folding. Annu Rev
Biochem 69, 69-93.] As the correctly folded protein passes through
the Golgi on its way either to secretion or the cell membrane,
further glycan modifications can take place. Specifically,
mannosidases can trim more mannoses off the core sugar, while a
host of glycosyltransferases can add further GlcNAc, fucose,
galactose, and sialic acid moieties, among others [Sears, P., Wong,
C. H. (1998) Enzyme action in glycoprotein synthesis. Cell Mol Life
Sci 54, 223-52.] TABLE-US-00001 TABLE 1 Common enzymes involved in
N-glycan biosynthesis EC # Enzyme name 2.4.1.- Hexosyltransferases
(ALG 6, 8, 10, 11) 2.4.1.38 Glycoprotein
.beta.-galactosyltransferase 2.4.1.68 Glycoprotein
6-.alpha.-L-fucosyltransferase 2.4.1.83 Dolichyl phosphate mannose
transferase 2.4.1.101 .alpha.-1,3-mannosyl-glycoprotein
2-.beta.-N-acetylglucosaminyl transferase 2.4.1.117 Dolichyl
phosphate .beta.-glucosyltransferase 2.4.1.119 Oligomannosyl
transferase 2.4.1.130 Oligomannosyl synthase (ALG 3, 9, 12)
2.4.1.132 Glycolipid 3-.alpha.-mannosyltransferase 2.4.1.141
N,N'-diacetylchitobiosyl pyrophosphoryldolichol synthase 2.4.1.142
chitobiosyldiphosphodolichol .beta.-mannosyltransferase 2.4.1.143
.alpha.-1,6-mannosyl-glycoprotein 2-.beta.-N-acetylglucosaminyl
transferase 2.4.1.144 .beta.-1,4-mannosyl-glycoprotein
4-.beta.-N-acetylglucosaminyl transferase 2.4.1.145
.alpha.-1,3-mannosyl-glycoprotein 4-.beta.-N-acetylglucosaminyl
transferase 2.4.1.155 .alpha.-1,6-mannosyl-glycoprotein
6-.beta.-N-acetylglucosaminyl transferase 2.4.1.201
.beta.-1,6-mannosyl-glycoprotein 4-.beta.-N-acetylglucosaminyl
transferase 2.4.99.1 .beta.-galactoside
.alpha.-2,6-sialyltransferase 2.5.1.- Transferring alkyl or aryl
groups, other than methyl groups 2.7.1.108 Dolichol kinase 2.7.8.15
Chitobiosylpyrophosphoryl dolichol synthase 3.1.3.51
Dolichyl-phosphatase 3.1.4.48 dolichylphosphate-glucose
phosphodiesterase 3.2.1.- Hydrolyzing O- and S-glycosyl compounds
3.2.1.106 Mannosyl-oligosaccharide glucosidase 3.2.1.113
mannosyl-oligosaccharide 1,2-.alpha.-mannosidase 3.2.1.114
mannosyl-oligosaccharide 1,3-1,6-.alpha.-mannosidase 3.6.1.43
Dolichol diphosphatase
[0117] The constraints are solved using mathematical and heuristic
approaches known to art such as linear programming and search
techniques. A more detailed illustration of one embodiment of an
analytical and computational method is provided in FIG. 23. One of
skill in the art will appreciate, however, that there are a number
of ways in which experimental analytic methods can be combined with
computational methods to achieve the desired characterization. It
is the combination which provides more efficient analysis of
samples of glycans. The examples provided are not intended to be
limiting in any way.
[0118] In some embodiments, the methods provided herein also
include generating a list of the possible compositions of glycans
and their theoretical masses. The list can be based on the
biosynthetic pathways for glycosylation (FIG. 3). An example of
such a list is provided herein. The list can also be recorded in a
computer-readable medium. The list can be generated with other
means, such as with the results from the use of any of the methods
provided herein or known in the art. In one embodiment, the method
can include the use of exoenzymes to cleave the glycans in order to
analyze the composition of the glycans. The list can be used in any
of the methods provided in order to characterize glycans. Methods
that include the use of a list are also provided herein.
[0119] Protein glycosylation can affect the function of proteins or
be indicative of a cause or symptom of a disease state. For many
proteins, N- and O-linked glycans are an important factor for
determining proper folding, stability and resistance to degradation
(which affects the half-life of the protein). In some proteins, N-
and O-linked glycans play a role in the activity and/or function of
the protein. In some proteins, N- and O-linked glycans are
indicative of a normal or disease state. Therefore, methods are
provided herein to analyze the glycosylation of a protein for a
variety of reasons. The methods, therefore, provided above can be
used in diagnosis.
[0120] Also provided is the method described below, which can also
be used for diagnostic or prognostic purposes. In this method the
total profile of carbohydrates from body fluids or tissues can be
examined, and in some embodiments this can be done in a
high-throughput format. The examination of total glycan profiles
are now exceedingly accessible thanks to the recent advances in
proteomic pattern diagnostics. This approach should be useful in
sensing susceptible physiological alterations to the body's natural
homeostasis. This method should not only serve as a fast diagnostic
tool but should also help to understand the function of specific
carbohydrate modifications in some diseases.
[0121] Before developing a method to study N-glycans from body
fluids, it was important to understand the types of molecules
present. For example, proteins comprise an enormous portion of
serum, approximately 7% of the total wet weight [Vander, 2001]. Of
this amount, over half is albumin (.about.50 mg/ml), a protein that
can be non-enzymatically glycosylated, but not N-glycosylated
[Rohovec, 2003]. Although the overwhelming amounts of albumin can
obscure analysis for proteomics, it may not interfere with N-glycan
profiling. There are also large amounts of glycosylated antibodies,
which have a number of glycan structures [Bihoreau, 1997;Watt,
2003]. However, simple methods exist to separate these abundant
antibodies from the less abundant glycoproteins.
[0122] When working with serum, there are several issues to
consider that are not relevant for single protein systems. Because
the proteins in the sample are so concentrated, they can easily
precipitate out of solution. Also, even though albumin does not
have N-linked sugars, the sheer quantity present may interfere with
glycan release or purification. There are several other major
proteins in serum (i.e. immunoglobulins) that are N-glycosylated,
which may overshadow the signals from less abundant proteins.
However, alterations in immunoglobulin glycosylation may also be
correlated with changes in physiological state. To determine the
contributions and/or interference from major serum proteins,
several options for separating serum proteins into fractions before
analysis were explored.
[0123] Identifying glycan structures with complex protein mixtures
can be somewhat difficult. By generating a master list of all
possible compositions and their theoretical masses based on
biosynthetic pathways for glycosylation, all possible
monosaccharide composition was assigned to each peak observed in a
MALDI-MS spectrum. Such lists and databases comprising these lists
are provided herein. In most cases, each mass peak corresponds
uniquely to a monosaccharide assignment. However, in some instances
there can be more than one potential composition. If necessary, the
correct composition can be determined by coupling different
separation and characterization techniques with commercially
available exoenzymes that cleave the glycans only at particular
linkages.
[0124] The method provided allows fast and sensitive spectrometric
analysis of patterns for the total composition of glycans in body
fluids such as serum, saliva, urine, tears, seminal fluid, feces,
etc. Specifically the use of the analysis of these patterns can be
extended for the purpose of diagnosis, prognosis and monitoring the
effects of therapeutics. Using optimized methods described above,
the total content of serum, saliva and urine glycome was analyzed
and it was shown that specific and reproducible MALDI-MS patterns
which are dependent on the source (patient) of the sample and state
could be obtained. Since every signal inside the pattern
corresponds to specific glycans, the alteration of these patterns
are easily determined and correlated with the expression levels of
the carbohydrates. These alterations can be easily determined
manually or more efficiently with the help of computational
analysis. Since specific alterations in these glycan patterns are
associated with disease state, this method serve as reliable
platform for diagnosis, prognosis and the analysis associated with
therapeutics. The methods provided can also be used to profile
populations to aid the development and application of
patient-oriented treatments.
[0125] Methods, therefore, are provided for the determining the
glycome profile of a sample. The total glycome and/or patterns
deduced therefrom can be used for studying the effects of
glycosylation on protein activity and/or function as in the case of
glycoprotein therapeutics. Likewise, the total glycome and/or
patterns deduced therefrom can also be used in methods for
diagnosis, assessing prognosis and assessing drug treatment,
etc.
[0126] A "glycome profile" refers to the number and kind of glycans
found in a sample. The sample can contain one or more glycans
and/or one or more glycoconjugates. The glycome profile can be, for
example, the number and kind of a specific type of glycan (e.g.,
N-glycan, O-glycan, etc.). Each component of a glycome profile can
correspond to a glycan or fragment thereof or a glycoconjugate or
fragment thereof. The number refers to the amount and can be an
actual or a relative amount. The "total glycome profile" as used
herein the absolute or relative number and kind of all glycans in a
sample. The sample can be a sample of cells, tissue or body
fluid.
[0127] To assess the glycome profile of a sample any analytic
methods can be used. Some of these methods are described above;
others are known in the art. For example, the analytic method can
be MALDI-MS, LC-MS, LC-MS/MS, MALDI-TOF, TANDEM-MS, FTMS, NMR,
HPLC, electrophoresis, capillary electrophoresis, microfluidic
devices or nanofluidic devices. In a preferred embodiment the
glycome profile is determined using a quantitative MALDI-MS or
MALDI-FTMS in the presence of ATT and Nafion coating. To quantify
the glycans, in one example, calibration curves of known glycan
standards can be used.
[0128] Prior to analyzing the glycans of the sample, the sample can
be fractionated. The sample can be fractionated based on properties
of the glycans and/or glycoconjugates, such as but not limited to,
charge, size, molecular weight, binding properties to other
molecules or materials, acidity, basicity, pI, hydrophobicity and
hydrophilicity. As an example, the fractionation can be performed
using solid supports with immobilized proteins, organic molecules,
inorganic molecules, lipids, carbohydrates, nucleic acids, etc. As
a further example, the fractionation can be performed using
filters, such as molecular weight cutoff filters. The fractionation
can also be performed using resins, such as, cation or anion
exchange resins. Any method of fractionation known in the art can
be used. In one embodiment, however, the sample is not fractionated
before it is analyzed.
[0129] Prior to analysis the sample, the sample can also be
degraded with a chemical or enzymatic method to cleave the glycans
from any glycoconjugates in the sample. Examples of enzymatic
methods are provided above and include, for example, the use of
PNGase F, endoglycosydase H and endoglycosydase F or combinations
thereof. Chemical methods have also been described above and
include hydrazinolisis or alkali borohydrate.
[0130] After chemical or enzymatic degradation the sample can then
be performed in some embodiments. Purification methods were also
provided above. Examples of particular purification methods include
using solid phase extraction cartridges, such as graphitized carbon
columns and C-18 columns.
[0131] Once a glycome profile is determined, a glycome pattern can
be identified. As used herein "glycome pattern" refers to a glycome
profile or subset of the profile that has been associated with a
certain function (of a lipid or protein), cellular state, or
pathological condition (i.e., a disease condition). A glycome
pattern can be identified using a computational method. An glycome
pattern, like, the profile, can be represented by the relative or
absolute amounts of components of the pattern or ratios between the
components of the pattern. The glycome pattern can also be
represented by combinations of different components or the presence
or absence of a component. The pattern can also be any combination
of respresentations, such as those provided herein.
[0132] The pattern can be determined using a computational method.
Examples of such computational methods are provided herein in the
Examples. The computational method can, for example, incorporate
one or more of the following to determine a glycome pattern:
experimental data from analytic methods of glycome and/or glycan
analysis; theoretical glycan structures; glycan composition,
structure, property information from databases, glycan biosynthetic
pathway information, patient or sample origin information, such as
patient history, demographics; extracting features from the
experimental data sets, generating all possible data sets with
specific features, submitting the combined information to a data
mining analysis, establish the relationship rules and validating
the pattern. The computational method can be an iterative process.
One detailed example is provided in FIG. 3.
[0133] The patterns that are ultimately validated can be recorded
in a computer-generated data structure. A database of validated
glycome patterns is, therefore, also provided herein.
[0134] The patterns can be subsequently used for, for example,
diagnostic and prognostic purposes and for determining the purity
of a sample.
[0135] The methods provided herein include methods for determining
the glycosylation of a protein and its effects on the protein's
activity and/or function. The protein glycosylation can be studied
with the methods provided to determine the proper folding of the
protein or to determined the influence of the protein's
glycosylation on the stability/and or degradation resistance of the
protein (indicative of the protein's half-life). Changing the
composition or the degree of glycosylation of a protein can greatly
influence its half-life in circulation, as well as its activity
[Chang, G. D., Chen, C. J., Lin, C. Y., Chen, H. C., Chen, H.
(2003) Improvement of glycosylation in insect cells with mammalian
glycosyltransferases. J Biotechnol 102, 61-71; Perlman, S., van den
Hazel, B., Christiansen, J., Gram-Nielsen, S., Jeppesen, C. B.,
Andersen, K. V., Halkier, T., Okkels, S., Schambye, H. T. (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, 3227-35.] For example, erythropoietin
(EPO) is a glycoprotein that has been developed as a therapeutic
due to its ability to stimulate red blood cell production in the
bone marrow. It has been determined that increased sialylation of
EPO greatly increases its half-life in circulation[Darling, R. J.,
Kuchibhotla, U., Glaesner, W., Micanovic, R., Witcher, D. R.,
Beals, J. M. (2002) Glycosylation of erythropoietin affects
receptor binding kinetics: role of electrostatic interactions.
Biochemistry 41, 14524-31.] Thus, by understanding the role of EPO
glycosylation, it is possible to manufacture a more potent
drug.
[0136] Similarly, methods are provided for identifying glycosylated
proteins with a desired activity and/or function. In
immunoglobulins, glycosylation plays an important role in the
structure of the Fc region, which is important for activation of
leukocytes expressing Fc receptors. When glycans on the IgG Fc
region are truncated, the resulting conformational changes reduce
the ability of the IgG to bind to the Fc receptor[Krapp, S.,
Mimura, Y., Jefferis, R., Huber, R., Sondermann, P. (2003)
Structural analysis of human IgG-Fc glycoforms reveals a
correlation between glycosylation and structural integrity. J Mol
Biol 325, 979-89.] In addition, IgG glycosylation is species
specific, making it essential to choose the appropriate production
method for protein therapeutics [Raju, T. S., Briggs, J. B., Borge,
S. M., Jones, A. J. (2000) Species-specific variation in
glycosylation of IgG: evidence for the species-specific sialylation
and branch-specific galactosylation and importance for engineering
recombinant glycoprotein therapeutics. Glycobiology 10, 477-86.]
For example, a human protein produced in a mouse cell line may not
have the necessary glycans for optimal function in human patients.
Therefore, the immune recognition of an antibody can be assessed
with the methods of analysis provided herein.
[0137] One of the major challenges during the production of
glycoprotein therapeutics is to control the generation of a
specific glycoform and the subsequent characterization for quality
control of the product. Therefore, methods that can efficiently
characterize new batches of glycoprotein therapeutics are of great
value to the pharmaceutical industry. For a complete
characterization of glycoprotein therapeutics, information such as
glycan site occupancy, carbohydrate composition and structure at
each site and quantity of each carbohydrate is required.
[0138] As described below in the Examples, the methods for
analyzing glycans found on proteins, which can include antibodies,
can be used to assess the quality and variability of protein
production. With the recently increased focus on protein-based
therapeutics by pharmaceutical companies and research laboratories,
it has become important to understand how glycosylation composition
is influenced by protein production methods. In the field of
bioprocess engineering, there are many different types of
bioreactors available for protein production. Depending on the
model, parameters such as pH and dissolved oxygen (DO) can be
controlled in several ways, and agitation methods can result in
wide variations in shear stress. In addition, the cell-feeding
process during fermentation can be altered to change the cell
growth profile. All of these variables can affect protein
glycosylation--even using identical conditions in two different
bioreactors causes changes in glycan patterns [Kunkel, J. P., Jan,
D. C., Butler, M., Jamieson, J. C. (2000) Comparisons of the
glycosylation of a monoclonal antibody produced under nominally
identical cell culture conditions in two different bioreactors.
Biotechnol Prog 16, 462-70; Zhang, F., Saarinen, M. A., Itle, L.
J., Lang, S. C., Murhammer, D. W., Linhardt, R. J. (2002) The
effect of dissolved oxygen (DO) concentration on the glycosylation
of recombinant protein produced by the insect cell-baculovirus
expression system. Biotechnol Bioeng 77, 219-24; Senger, R. S.,
Karim, M. N. (2003) Effect of Shear Stress on Intrinsic CHO Culture
State and Glycosylation of Recombinant Tissue-Type Plasminogen
Activator Protein. Biotechnol Prog 19, 1199-209; Muthing, J.,
Kemminer, S. E., Conradt, H. S., Sagi, D., Nimtz, M., Karst, U.,
Peter-Katalinic, J. (2003) Effects of buffering conditions and
culture pH on production rates and glycosylation of clinical phase
I anti-melanoma mouse IgG3 monoclonal antibody R24. Biotechnol
Bioeng 83, 321-34.] Therefore, provided herein are methods for
analyzing the glycosylation of proteins to assess protein
production methods and to determine the purity or homogeneity of
glycosylated proteins produced.
[0139] Therefore, methods are provided for the direct
characterization of subsequent samples of the proteins under study
(as in the cases of new batches of glycoprotein therapeutics).
Examples of this is described herein. One example is as follows. A
well characterized batch of the glycoprotein under study is used to
generate a library of backbone-labeled peptides and glycopeptides
by enzymatic digest using methods know in the art [Gehrmann,
2004;Yao, 2003;Reynolds, 2002;Yao, 2001]. Trypsin proteolytic
digest cleavage can be employed before and after glycan cleavage in
order to expand the peptide library. Peptide labeling can be
performed using methods know to experts in the art. Each
characterized and quantified peptide and glycopeptide can be used
to generate calibration curves using LC-MS or LC-MS/MS techniques.
These peptides and glycopeptides can then be mixed (in known
concentrations) with the petide/glycopeptide mixture resulting from
the trypsin proteolytic cleavage digest of the new sample batch
under study. The co-elution of the labeled peptides with the
unknown peptides followed by the co-detection (the ratio between
labeled and unlabeled peptides) using mass spectrometry allows the
quantification of each peptide (and therefore the different
glycoforms) in the unknown sample. In addition to the
peptide/glycopeptide analysis, by splitting the flow from LC column
(before entering the electrospray source) to a collection plate,
the respective glycans from the eluted glycopeptides can be
analyzed using the methods described herein. The use of other well
established methods (e.g., hydrazide column, peptide) for the
determination of glycan site occupancy can also be used [Cointe,
2000, Hui, 2002, An, 2003].
[0140] The methods provided, where the amount or type of glycans on
proteins can be determined, can be used to analyze the purity of a
protein sample. As used herein the term "purity" refers to the
proportion of a protein sample that contains a particular glycan or
a particular glycosylation pattern. In some embodiments, the
protein sample is determined to be at least 10%, 20%, 30%, 40%,
50%, 60%, 70%, 80%, 90% or more pure. In some embodiments the
method is used to assess the amount of a particular glycan in a
protein sample. In some instances, it may be desired that the
proteins are selected depending on the particular glycosylation
pattern they exhibit. As used herein, "glycosylation" is meant to
include the pattern or a subset or even one particular glycan,
while "glycosylation pattern" refers to the number and kind of
glycans present on the protein. In other aspects of the invention
the methods provided herein can be used to evaluate a process of
producing proteins and/or compare a process with another to
evaluate the types of proteins produced. The "types of proteins
produced" includes not only the protein itself but also its
glycosylation pattern.
[0141] As stated above, the glycosylation of a protein may be
indicative of a normal or a disease state. Therefore, methods are
provided for diagnostic purposes based on the analysis of the
glycosylation of a protein or set of proteins, such as the total
glycome. The methods provided herein can be used for the diagnosis
of any disease or condition that is caused or results in changes in
protein glycosylation. For example, the methods provided can be
used in the diagnosis of cancer, inflammatory disease, benign
prostatic hyperplasia (BPH), etc.
[0142] The diagnosis can be carried out in a person with or thought
to have a disease or condition. The diagnosis can also be carried
out in a person thought to be at risk for a disease or condition.
"A person at risk" is one that has either a genetic predisposition
to have the disease or condition or is one that has been exposed to
a factor that could increase his/her risk of developing the disease
or condition. In some embodiments, the person can have, be thought
to have or is at risk of cancer, cystic fibrosis, mad cow disease,
etc.
[0143] Detection of cancers at an early stage is crucial for its
efficient treatment. Despite advances in diagnostic technologies,
many cases of cancer are not diagnosed and treated until the
malignant cells have invaded the surrounding tissue or metastasized
throughout the body. Although current diagnostic approaches have
significantly contributed to the detection of cancer, they still
present problems in sensitivity and specificity.
[0144] Cancers or tumors also include but are not limited to
adrenal gland cancer, biliary tract cancer; bladder cancer, brain
cancer; breast cancer; cervical cancer; choriocarcinoma; colon
cancer; endometrial cancer; esophageal cancer; extrahepatic bile
duct cancer; gastric cancer; head and neck cancer; intraepithelial
neoplasms; kidney cancer; leukemia; lymphomas; liver cancer; lung
cancer (e.g. small cell and non-small cell); melanoma; multiple
myeloma; neuroblastomas; oral cancer; ovarian cancer; pancreas
cancer; prostate cancer; rectal cancer; sarcomas; skin cancer;
small intestine cancer; testicular cancer; thyroid cancer; uterine
cancer; urethral cancer and renal cancer, as well as other
carcinomas and sarcomas.
[0145] Protein samples, therefore, may include samples from a
subject. The samples can, for example, be serum or saliva
samples.
[0146] The methods can also be used to determine whether or not
cells are undergoing dramatic change or are "stressed cells".
Stressed cells are cells that are undergoing a stress response that
alters the cell's protein production. The stress response can be
any change that causes altered protein production or causes the
cell to deviate from its normal state. Stressed cells can be
identified by analyzing the glycans exhibited by the proteins on
the cell's surface. Such glycans can be found in, for example, a
glycoprotein. In some embodiments, the methods provided are used to
detect changes in glycosylation that occur under growth conditions
or inflammation.
[0147] In other aspects of the invention methods for analyzing
blood type antigens are also provided.
[0148] In other aspects of the invention methods are provided for
therapeutics. The glycosylation of proteins can be assessed to
evaluate treatment regimens and/or to select specific
therapies.
[0149] A subject is any human or non-human vertebrate, e.g., dog,
cat, horse, cow, pig. A sample includes any sample obtained from
any of these subjects.
[0150] High-throughput methods are also provided. "High-throughput"
methods refer to the ability to process and/or analyze multiple
samples at one time. High-throughput methods provided herein can
include the use of a membrane-based method, such as a PVDF membrane
in a 96-well plate, for high throughput sample processing (i.e.,
digestion and/or denaturation steps, etc.) In some preferred
embodiments membrane based high-throughput methods may also include
the removal of abundant proteins such as albumin. In one aspect of
the invention, therefore, the methods of analysis provided are
high-throughput methods. Any step or steps of any of the methods
provided herein can be performed as a high-throughput step. For
instance purification, degradation, etc. can be performed in a
high-throughput manner in some embodiments.
[0151] Robotics can be used in one or more steps of the methods
provided herein. In one embodiment robotics is used for
separation.
[0152] The present invention is further illustrated by the
following Examples, which in no way should be construed as further
limiting. The entire contents of all of the references (including
literature references, issued patents, published patent
applications, and co-pending patent applications) cited throughout
this application are hereby expressly incorporated by
reference.
EXAMPLES
Example 1
N-Glycan Analysis
Materials and Methods
PNGaseF Digest of N-Glycans from Protein Cores
[0153] Between 10 and 100 .mu.g of protein was denatured for 10
minutes at 90.degree. C. with 0.5% SDS and 1%
.beta.-mercaptoethanol. Since SDS (and other ionic detergents)
inhibits enzyme activity, 1% NP-40 was added to counteract these
effects. The enzyme reaction was performed overnight with 2 .mu.l
of PNGaseF at 37.degree. C. in a 50 mM sodium phosphate buffer, pH
7.5.
Purification of Released N-Glycans
[0154] Proteins were precipitated with a 3.times. volume of 100%
ethanol on ice for 1 hour. After centrifugation to remove the
proteins, the supernatant containing the N-glycans was evaporated
by vacuum (SpeedVac, TeleChem International, Inc., Sunnyvale,
Calif.). Dried glycans were resuspended in 50 .mu.l of water.
[0155] Samples were desalted using 1 ml ion exchange column of
AG50W X-8 beads (Bio-Rad, Hercules, Calif.). The resin was charged
with 150 mM acetic acid and washed with water. Glycan samples were
loaded onto the column in water and washed through with 3 ml
H.sub.2O. This flow through was collected and lyophilized to obtain
the desalted sugars.
[0156] GlycoClean R and S cartridges were purchased from Prozyme
(San Leandro, Calif.; formerly Glyko). GlycoClean R cartridges were
primed with 3 ml of 5% acetic acid, and the samples were loaded in
water. Sugars were eluted with 3 ml of water passed through the
column. For GlycoClean S, the membrane was primed with 1 ml water
and 1 ml 30% acetic acid, followed by 1 ml acetonitrile. The glycan
sample was loaded (in a maximum volume of 10 .mu.l) onto the disc,
and the glycans were allowed to adsorb for 15 minutes. After
washing the disc with 1 ml of 100% acetonitrile and 5.times.1 ml of
96% acetonitrile, glycans were eluted with 3.times.0.5 ml
water.
[0157] GlycoClean H cartridges were purchased from Prozyme (200 mg
bed) or ThermoHypersil (25 mg bed). To prepare the GlycoClean H
cartridge, the column (containing 200 mg of matrix) was washed with
3 ml of 1M NaOH, 3 ml H.sub.2O, 3 ml 30% acetic acid, and 3 ml
H.sub.2O to remove impurities. The matrix was primed with 3 ml 50%
acetonitrile with 0.1% TFA (Solvent A) followed by 3 ml 5%
acetonitrile with 0.1% TFA (Solvent B). After loading the sample in
water, the column was washed with 3 ml H.sub.2O and 3 ml Solvent B.
Finally, the sugars were eluted using 4.times.0.5 ml of Solvent A.
GlycoClean H cartridges can be reused after washing with 100%
acetonitrile and re-priming with 3 ml of Solvent A followed by 3 ml
of Solvent B. For the 25 mg cartridge, wash volumes were reduced to
0.5 ml. Eluted fractions were lyophilized and the isolated glycans
were resuspended in 10-40 .mu.l H.sub.2O.
MALDI-MS of N-Glycans
[0158] Several MALDI-MS matrix compounds were tested in this study.
First, caffeic acid was added to 30% acetonitrile to make a
saturated solution, with or without 300 mM spermine. Alternatively,
a saturated solution of dihydroxybenzoic acid (DHB) in water was
used with or without 300 mM spermine. To prepare the sample spots,
three methods were used. For the crushed spot method, 1 .mu.l of
matrix was spotted on the stainless steel MALDI-MS sample plate and
allowed to dry. After crushing the spot with a glass slide, 1 .mu.l
of matrix mixed 1:1 with sample was spotted on the seed crystals
and allowed to dry. Alternatively, 1 .mu.l of matrix was applied
followed by 1 .mu.l of sample, or vice versa. All spectra were
taken with the following instrument parameters: accelerating
voltage 22000V, grid voltage 93%, guide wire 0.15% and extraction
delay time of 150nsec (unless otherwise noted). All N-glycans were
detected in linear mode with delayed type extraction and positive
polarity.
Results
[0159] With an IgG-producing mouse hybridoma cell line, the effects
of DO and pH control on cell metabolism and growth kinetics using
two different reactor types was investigated. It was determined
whether the IgG glycan profile was altered by the different reactor
conditions. For a complete glycan analysis, the procedure for
glycan isolation was optimized. The purification and analysis was
performed using two known N-glycosylated standards with different
properties, ribonuclease B (RNaseB), a glycoprotein that only
contains high mannose structures [29], and ovalbumin, which
contains both hybrid and complex glycan structures at just one
glycosylation site [30]. After finding the best methods for glycan
analysis, the procedure was applied to samples (Hamel laboratory,
MIT Bioprocess Engineering Center, Cambridge, Mass.) produced under
various conditions.
[0160] There are several required steps for N-glycan analysis from
proteins. While it is possible to study both the intact
glycoprotein and glycopeptides from digested proteins, these types
of analysis make it difficult to determine the exact composition of
the glycan structures. Therefore, the intact glycan was removed
from the core protein. Then, the sugar structures were separated
from the protein core, purified and analyzed using methods that can
provide specific saccharide compositions in an accurate manner.
Release and Purification of N-Glycans from Protein Standards
[0161] There are several methods, both enzymatic and chemical, to
separate glycans from their protein cores. Of the chemical methods,
hydrazinolysis provides the most efficient release of glycans [31].
However, both N- and O-linked glycans are released using this
method, and must be separated afterwards. The sample must be very
clean, with no residual salts, and the reaction does not proceed
efficiently in air or water, making hydrazinolysis somewhat
undesirable as a quick measure of quality control.
[0162] Several enzymatic methods are available that are specific to
N-linked sugars. Endoglycosidases H and F (EndoH and EndoF) cleave
between the two interior GlcNAc residues of the glycan core, while
protein N-glycanase F (PNGaseF) cleaves between the interior GlcNAc
and the asparagine side chain of the protein core [32-34].
[0163] EndoH only acts on high mannose or hybrid structures, while
EndoF can cleave complex glycans. With EndoH and EndoF, information
about fucosylation on the reducing end GlcNAc is lost since this
residue remains attached to the protein core. On the other hand,
PNGaseF releases the entire glycans and can cleave all classes of
N-glycans, making it a tool of choice for N-glycan release.
[0164] For optimal enzyme activity, proteins should be unfolded
prior to digestion with PNGaseF. Typically, a protein sample can be
denatured by heating in the presence of .beta.-mercaptoethanol
and/or SDS. After PNGaseF cleavage, samples contain a mixture of
free glycans, protein, detergent (from the denaturing step), and
salts. In some instance it is preferred that everything except the
glycans are removed from the sample. To achieve this, the proteins
were first precipitated with ethanol and the supernatant containing
the glycans was then dried under vacuum (SpeedVac) and resuspended
in water. At this point, the most difficult component to get rid of
was the detergent, which interferes with some types of analytical
techniques.
[0165] There are several commercially available resins and
cartridges for N-glycan clean-up after PNGaseF digest. In addition
to an ion exchange resin (AG50W X-8 from Bio-Rad), three types of
purification columns from Prozyme (formerly Glyko) were tested--the
GlycoClean H, S and R cartridges (Glyco H, S and R). Glyco R
contains a reverse phase material that allows glycans to flow
through, while retaining peptides and detergents. Glyco S is a
small membrane that adsorbs the sugars in >90% acetonitrile,
while hydrophobic molecules are washed away. The glycans can then
be eluted with water. Glyco H, on the other hand, is a porous
graphitic carbon matrix which retains both neutral and charged
sugars, while allowing salts to be washed away with a low
concentration of acetonitrile. The sugars can then be eluted with
higher acetonitrile concentrations. Proteins and detergents
typically remain on the Glyco H column. Overall, the Glyco H
cartridge yielded the best results in these studies (Table 2).
Glycan Analysis by MALDI-MS
[0166] Numerous analytical techniques have been applied to study
N-glycans, including mass spectrometry, NMR, electrophoresis, and
chromatographic methods. NMR, for instance, can provide detailed
structural information in a single experiment. Due to the lack of
natural chromophores in N-linked carbohydrates, many of the
procedures require the labeling of saccharides with chemical tags
or fluorescent labels to facilitate detection. In fluorescence
assisted carbohydrate electrophoresis (FACE), glycans are
fluorescently labeled and run on a polyacrylamide gel [35]. Glycan
bands can then be excised for further structural analysis. Similar
methods use HPLC or capillary electrophoresis (CE) for greater
sensitivity and better separation. However, these techniques merely
yield migration times of a sample's components, giving limited
structural information.
[0167] One of the simplest and most sensitive glycan analysis
methods is MALDI-MS, which has detection limits in the femto- to
picomole range. In addition, many samples can be analyzed in a
single experiment within minutes. MALDI-MS is a soft ionization
technique that utilizes an organic matrix to absorb and transfer
the ionizing energy from the laser. This technique is useful for
many applications, from small molecules to large proteins over 100
kDa. However, sample ionization is sensitive to instrument
conditions as well as sample preparation.
[0168] In particular, the matrix used to suspend the sample is
important for good ionization. The efficiency of a particular
matrix can vary widely, depending on the nature of the sample.
Multiple matrix preparations were tested, namely caffeic acid
(saturated solution in 30% acetonitrile) with or without spermine,
and DHB (saturated solution in water) with or without spermine. In
addition, several spotting methods were evaluated: spotting 1 .mu.l
of sample followed by 1 .mu.l of matrix, spotting matrix followed
by sample, or mixing the two before spotting. Whether using the
crushed spot method to promote matrix crystallization would improve
signal intensity [36] was also investigated. When acquiring the
MALDI-MS data, the data collection was optimized by varying
instrument parameters such as guide wire voltage, accelerating
voltage, grid values, as well as negative vs. positive mode.
[0169] To evaluate the MALDI-MS conditions and calibrate the
masses, commercially available N-glycan standards (NGA2 and NGA3)
were used. In addition, we used RNaseB and ovalbumin as model
glycoproteins to determine the effects of sample preparation on
spectra quality and to optimize glycan release.
[0170] MALDI conditions for N-glycan analysis were optimized using
the matrix and sample preparation conditions shown in Table 2.
Among the matrix preparations used, DHB with spermine displayed the
best results. Typically, spermine is used to allow glycans to be
detected in negative mode, but it enhanced the glycan signals even
in positive mode. The neutral glycans had poor signals in negative
mode. Using the crushed spot method did not make a significant
difference in signal intensity. TABLE-US-00002 TABLE 2 Optimization
of conditions for MALDI-MS and N-glycan clean-up. Sample Matrix
Sample info Results and comments 1. NGA2, DHB, saturated 1 .mu.l
matrix on Signal okay. Not too much noise NGA3 solution in
H.sub.2O, plate, add 1 .mu.l 300 mM spermine sample 2. NGA2, DHB,
saturated 1 .mu.l sample on Better signal than Sample 1 or 3. This
NGA3 solution in H.sub.2O, plate, add 1 .mu.l method used in all
subsequent samples 300 mM spermine matrix unless otherwise noted.
3. NGA2, DHB, saturated Mix sample and Lower signal than Sample 1
NGA3 solution in H.sub.2O, matrix, spot 300 mM spermine 1 .mu.l. 4.
NGA3 Caffeic acid, 30% Good signal intensity but significant ACN,
saturated unidentified adduct solution 5. NGA3 Caffeic acid, 30%
Large unidentified contamination peak ACN, 300 mM spermine 6. NGA3
Caffeic acid, 30% Crushed spot Good signal intensity but also more
noise ACN method than Sample 2 7. NGA3 DHB, saturated Low signal
intensity compared to Sample 2 solution in H.sub.2O or 5 8. NGA3
DHB, saturated Acc voltage Comparable to Sample 7 solution in
H.sub.2O 18000, guide wire 0.1%. 9. NGA3 DHB, saturated Good signal
solution in H.sub.2O, 300 mM spermine 10. NGA3 DHB, saturated Acc
voltage solution in H.sub.2O, 18000, guide 300 mM spermine wire
0.1%. 11. NGA3 DHB, saturated Negative mode Very low signal, almost
undetectable solution in H.sub.2O, 300 mM spermine 12. 500 .mu.g
DHB, saturated GlycoS Some high mannose peaks, many RNaseB solution
in H.sub.2O, unidentified peaks 300 mM spermine 13. 500 .mu.g DHB,
saturated AG50W X-8 Both spots spread a lot, no signal RNaseB
solution in H.sub.2O, Column and 300 mM spermine batch mode 14. 500
.mu.g DHB, saturated Glyco R Spot does not dry properly RNaseB
solution in H.sub.2O, 300 mM spermine 15. 500 .mu.g DHB, saturated
Glyco H Good signal, Man-5 through Man-9 RNaseB solution in
H.sub.2O, (200 mg) 300 mM spermine 16. 500 .mu.g DHB, saturated
Glyco H Good signal, 30 peaks that match published Ovalbumin
solution in H.sub.2O, (200 mg) reports 300 mM spermine 17. 10 .mu.g
DHB, saturated Glyco H Spots spread, mostly contamination peaks
RNaseB or solution in H.sub.2O, (25 mg) in 1000-1300 Da range.
Probably detergent. ovalbumin 300 mM spermine 18. 50 .mu.g DHB,
saturated Glyco H Spot spreads a lot, significant detergent RNaseB
solution in H.sub.2O, (25 mg) contamination peaks. 300 mM spermine
19.15 .mu.g DHB, saturated Glyco H Good signal, very slight
contamination that RNaseB solution in H.sub.2O, (200 mg) does not
interfere with signal. GlycoH 300 mM spermine column used for
future experiments. 20. 150 .mu.g DHB, saturated Glyco H Good
signal, very clean RNaseB solution in H.sub.2O, (200 mg) 300 mM
spermine
[0171] Using commercially available glycans and known protein
standards, it was determined that the optimal method for purifying
glycans after PNGaseF release was to use GlycoClean H cartridges
containing 200 mg of the stationary material. This method allowed
resulted in MALDI-MS spectra of N-glycans from RNaseB and ovalbumin
that were consistent with published reports. The ion exchange resin
did not remove all the detergents from the sample, causing the
sample spots to spread on the MALDI-MS target and not crystallize
properly. GlycoClean R, on the other hand, removed detergents but
did not completely remove salt, which subsequently interfered with
matrix crystallization and spectra quality. GlycoClean S yielded
acceptable sample spots on the MALDI-MS target, but failed to
remove all contamination.
[0172] FIG. 5 shows spectra of some of the representative RNaseB
samples from Table 2, with glycans purified under different
conditions. In the cleanest samples, all glycan masses correspond
with high mannose structures (Man-5 through Man-9).
[0173] To validate the reproducibility of the method, ovalbumin was
used as a protein standard with complex type N-glycans. Optimized
purification and MALDI-MS conditions were used (Glyco H 200 mg, DHB
matrix with spermine). The MALDI-MS data displayed results
comparable to previously published reports [30]. FIG. 6 shows the
MALDI-MS spectrum of ovalbumin glycans, and Table 3 lists the
observed peaks and their structures. TABLE-US-00003 TABLE 3
N-glycan structures from ovalbumin (Harvey et al, 2000) Theoretical
Peak Structure Mass 1 ##STR1## 1136.4 2 ##STR2## 1298.5 3a ##STR3##
1339.5 3b ##STR4## 1339.5 4 ##STR5## 1460.5 5 ##STR6## 1501.5 6a
##STR7## 1542.6 6b ##STR8## 1542.6 7 ##STR9## 1663.6 8 ##STR10##
1704.6 9a ##STR11## 1745.6 9b ##STR12## 1745.6 10a ##STR13## 1866.7
10b ##STR14## 1866.7 11a ##STR15## 1907.7 11b ##STR16## 1907.7 12a
##STR17## 1948.7 12b ##STR18## 1948.7 13 ##STR19## 2028.7 14a
##STR20## 2069.7 14b ##STR21## 2069.7 15a ##STR22## 2110.8 15b
##STR23## 2110.8 16 ##STR24## 2151.8 17 ##STR25## 2272.8 18
##STR26## 2313.9 19 ##STR27## 2475.9 20 ##STR28## 2638.0
MALDI-MS Analysis of N-Glycans from Antibodies Produced in Applikon
and Wave Reactors
[0174] Two antibody samples produced by mouse-mouse hybridoma cells
(Biokit SA, Barcelona, Spain) grown in an Applikon stirred tank
reactor (STR) were analyzed, along with three samples produced in
Wave reactors. The reactor conditions used are shown in Table 4.
TABLE-US-00004 TABLE 4 Reactor conditions used to produce antibody
samples. Sample Reactor Type DO pH Other 1 Applikon STR 50% 7 2
Applikon STR 90% Not controlled 3 Wave Controlled Not controlled 4
Wave Controlled 7 NaHCO.sub.3 for pH control 5 Wave Not 7 Fresh
media controlled for pH control
[0175] In the Applikon STR reactor, pH can be controlled
automatically by the instrument, which dispenses CO.sub.2,
NaHCO.sub.3 and O.sub.2 as needed. In the Wave reactor, however,
measurements must be taken manually and pH adjusted by hand. The pH
in this reactor can be controlled by either adding fresh media as
the cells grow, or adding NaHCO.sub.3 for increased buffering
capacity, and CO.sub.2 as needed. The main difference between the
reactor types is the mode of agitation. In the Applikon STR, a
blade stirrer keeps the cell suspension in motion, while a sparger
introduces oxygen to the system in a controlled manner. In the Wave
reactor, a rocking motion generates waves that mix the components
of the system and aids the transfer of oxygen and other gases into
the system.
[0176] The purified antibodies were processed according to the
optimized method described above. For each sample, 100 .mu.g of
protein was used as the starting material. Both positive and
negative ion modes were used in the MALDI-MS to determine whether
there were charged sugars present. No signal was observed in the
negative mode, indicating that only neutral sugars were obtained
from the antibodies. The positive ion mode MALDI-MS data of the
five antibody samples are shown in FIG. 7. Glycoproteins produced
using different conditions are shown in Table 4. All fractions
contained the same six glycans at 1317 Da, 1463 Da, 1478 Da, 1625
Da, 1641 Da and 1787 Da. The structures corresponding to these
peaks are shown in FIG. 8 with their theoretical masses.
[0177] These results indicate that the production method did not
significantly alter the occurrence of the glycans; rather, the
ratios between glycans seemed to be affected. Notably, samples
prepared in the Wave reactor had a lower amount of the 1625.4 Da
glycan with respect to the other glycans, as well as significant
reductions in the relative peak heights at 1640.9 and 1787.7 Da.
Altering the culture conditions within a reactor type did not
affect the relative abundance of the N-glycans.
[0178] While the exact mechanisms for producing these changes are
not known, it is interesting that the largest changes occurred due
to reactor type, not reactor conditions such as pH, DO or media
composition. In previous studies, pH above 7.2 was shown to affect
glycosylation composition [28]. However, for the two samples in
this study with pH uncontrolled, the pH was between 6.8 and 7.2
throughout the culture period. Studies of DO effects on
glycosylation demonstrated the largest differences at extremes (10%
or 190%) [26], while the samples studied here were produced under
moderate DO conditions (between 50% and 90%). Because the Applikon
STR and the Wave reactors differ most in their method of agitation,
reactor configuration is therefore the most likely source of glycan
variation.
[0179] Differences in protein glycosylation have been linked to
shear stress, as can be generated by the stirring blade or the gas
sparger in an STR reactor. However, the turbulence created in the
Wave reactor also generates shear stress. One hypothesis for the
shear stress effect is that cells must increase their overall
protein production in response to membrane and/or cytoskeletal
damage. As a consequence, the biosynthetic enzymes for
glycosylation are diverted away from the protein of interest
[27].
[0180] Although most observed parameters, including total antibody
production, were similar in Applikon STR and Wave cultures, cells
from the Wave reactor had slight increases in metabolic rates.
Changes in cell metabolism may yield effects similar to those
caused by shear stress, as all glycoproteins synthesized in the
cell must compete for the same machinery in the ER and golgi.
Example 1 References
[0181] 1. Hirschberg, C. B., Snider, M. D. (1987) Topography of
glycosylation in the rough endoplasmic reticulum and Golgi
apparatus. Annu Rev Biochem 56, 63-87. [0182] 2. Bause, E. (1983)
Structural requirements of N-glycosylation of proteins. Studies
with proline peptides as conformational probes. Biochem J 209,
331-6. [0183] 3. Marshall, R. D. (1972) Glycoproteins. Annu Rev
Biochem 41, 673-702. [0184] 4. Dwek, R. A. (1996) Glycobiology:
Toward Understanding the Function of Sugars. Chem Rev 96, 683-720.
[0185] 5. O'Connor, S. E., Imperiali, B. (1996) Modulation of
protein structure and function by asparagine-linked glycosylation.
Chem Biol 3, 803-12. [0186] 6. Crocker, P. R., Varki, A. (2001)
Siglecs in the immune system. Immunology 103, 137-45. [0187] 7.
Helenius, A., Aebi, M. (2001) Intracellular functions of N-linked
glycans. Science 291, 2364-9. [0188] 8. Imperiali, B., O'Connor, S.
E. (1999) Effect of N-linked glycosylation on glycopeptide and
glycoprotein structure. Curr Opin Chem Biol 3, 643-9. [0189] 9.
Furukawa, K., Takamiya, K., Okada, M., Inoue, M., Fukumoto, S.
(2001) Novel functions of complex carbohydrates elucidated by the
mutant mice of glycosyltransferase genes. Biochim Biophys Acta
1525, 1-12. [0190] 10. Jaeken, J., Matthijs, G. (2001) Congenital
disorders of glycosylation. Annu Rev Genomics Hum Genet 2, 129-51.
[0191] 11. Freeze, H. H., Aebi, M. (1999) Molecular basis of
carbohydrate-deficient glycoprotein syndromes type I with normal
phosphomannomutase activity. Biochim Biophys Acta 1455, 167-78.
[0192] 12. Carchon, H., Van Schaftingen, E., Matthijs, G., Jaeken,
J. (1999) Carbohydrate-deficient glycoprotein syndrome type IA
(phosphomannomutase-deficiency). Biochim Biophys Acta 1455, 155-65.
[0193] 13. Powell, L. D., Sgroi, D., Sjoberg, E. R., Stamenkovic,
I., Varki, A. (1993) Natural ligands of the B cell adhesion
molecule CD22 beta carry N-linked oligosaccharides with
alpha-2,6-linked sialic acids that are required for recognition. J
Biol Chem 268, 7019-27. [0194] 14. Sgroi, D., Varki, A.,
Braesch-Andersen, S., Stamenkovic, I. (1993) CD22, a B
cell-specific immunoglobulin superfamily member, is a sialic
acid-binding lectin. J Biol Chem 268, 7011-8. [0195] 15. Karlsson,
K. A. (1998) Meaning and therapeutic potential of microbial
recognition of host glycoconjugates. Mol Microbiol 29, 1-11. [0196]
16. Pritchett, T. J., Brossmer, R., Rose, U., Paulson, J. C. (1987)
Recognition of monovalent sialosides by influenza virus H3
hemagglutinin. Virology 160, 502-6. [0197] 17. Sears, P., Wong, C.
H. (1998) Enzyme action in glycoprotein synthesis. Cell Mol Life
Sci 54, 223-52. [0198] 18. Varki, A. (1999) Essentials of
glycobiology. Cold Spring Harbor Laboratory Press, Cold Spring
Harbor, N.Y. [0199] 19. Parodi, A. J. (2000) Protein glucosylation
and its role in protein folding. Annu Rev Biochem 69, 69-93. [0200]
20. Chang, G. D., Chen, C. J., Lin, C. Y., Chen, H. C., Chen, H.
(2003) Improvement of glycosylation in insect cells with mammalian
glycosyltransferases. J Biotechnol 102, 61-71. [0201] 21. Perlman,
S., van den Hazel, B., Christiansen, J., Gram-Nielsen, S.,
Jeppesen, C. B., Andersen, K. V., Halkier, T., Okkels, S.,
Schambye, H. T. (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, 3227-35.
[0202] 22. Darling, R. J., Kuchibhotla, U., Glaesner, W.,
Micanovic, R., Witcher, D. R., Beals, J. M. (2002) Glycosylation of
erythropoietin affects receptor binding kinetics: role of
electrostatic interactions. Biochemistry 41, 14524-31. [0203] 23.
Krapp, S., Mimura, Y., Jefferis, R., Huber, R., Sondermann, P.
(2003) Structural analysis of human IgG-Fc glycoforms reveals a
correlation between glycosylation and structural integrity. J Mol
Biol 325, 979-89. [0204] 24. Raju, T. S., Briggs, J. B., Borge, S.
M., Jones, A. J. (2000) Species-specific variation in glycosylation
of IgG: evidence for the species-specific sialylation and
branch-specific galactosylation and importance for engineering
recombinant glycoprotein therapeutics. Glycobiology 10, 477-86.
[0205] 25. Kunkel, J. P., Jan, D. C., Butler, M., Jamieson, J. C.
(2000) Comparisons of the glycosylation of a monoclonal antibody
produced under nominally identical cell culture conditions in two
different bioreactors. Biotechnol Prog 16, 462-70. [0206] 26.
Zhang, F., Saarinen, M. A., Itle, L. J., Lang, S. C., Murhammer, D.
W., Linhardt, R. J. (2002) The effect of dissolved oxygen (DO)
concentration on the glycosylation of recombinant protein produced
by the insect cell-baculovirus expression system. Biotechnol Bioeng
77, 219-24. [0207] 27. Senger, R. S., Karim, M. N. (2003) Effect of
Shear Stress on Intrinsic CHO Culture State and Glycosylation of
Recombinant Tissue-Type Plasminogen Activator Protein. Biotechnol
Prog 19, 1199-209. [0208] 28. Muthing, J., Kemminer, S. E.,
Conradt, H. S., Sagi, D., Nimtz, M., Karst, U., Peter-Katalinic, J.
(2003) Effects of buffering conditions and culture pH on production
rates and glycosylation of clinical phase I anti-melanoma mouse
IgG3 monoclonal antibody R24. Biotechnol Bioeng 83, 321-34. [0209]
29. Joao, H. C., Dwek, R. A. (1993) Effects of glycosylation on
protein structure and dynamics in ribonuclease B and some of its
individual glycoforms. Eur J Biochem 218, 239-44. [0210] 30.
Harvey, D. J., Wing, D. R., Kuster, B., Wilson, I. B. (2000)
Composition of N-linked carbohydrates from ovalbumin and
co-purified glycoproteins. J Am Soc Mass Spectrom 11, 564-71.
[0211] 31. Patel, T., Bruce, J., Merry, A., Bigge, C., Wormald, M.,
Jaques, A., Parekh, R. (1993) Use of hydrazine to release in intact
and unreduced form both N- and O-linked oligosaccharides from
glycoproteins. Biochemistry 32, 679-93. [0212] 32. Tarentino, A.
L., Plummer, T. H., Jr., Maley, F. (1974) The release of intact
oligosaccharides from specific glycoproteins by
endo-beta-N-acetylglucosaminidase H. J Biol Chem 249, 818-24.
[0213] 33. Tarentino, A. L., Maley, F. (1974) Purification and
properties of an endo-beta-N-acetylglucosaminidase from
Streptomyces griseus. J Biol Chem 249, 811-7. [0214] 34. Tarentino,
A. L., Gomez, C. M., Plummer, T. H., Jr. (1985) Deglycosylation of
asparagine-linked glycans by peptide:N-glycosidase F. Biochemistry
24, 4665-71. [0215] 35. Hu, G. F. (1995) Fluorophore-assisted
carbohydrate electrophoresis technology and applications. J
Chromatogr A 705, 89-103. [0216] 36. Rhomberg, A. J., Ernst, S.,
Sasisekharan, R., Biemann, K. (1998) Mass spectrometric and
capillary electrophoretic investigation of the enzymatic
degradation of heparin-like glycosaminoglycans. Proc Natl Acad Sci
USA 95, 4176-81.
Example 2
Profiling of N-Glycans from Human Serum
[0216] Materials and Methods
Cleavage of N-Glycans from Serum Glycoproteins
(Reduction/Carboxymethylation Method)
[0217] Human male normal serum samples were obtained from IMPATH
(Franklin, Mass.) and Biomedical Resources (Hatboro, Pa.), and
stored at -85.degree. C. For each experiment, 50 .mu.l of serum was
used to harvest N-glycans. Serum samples were first diluted 1:4
with water, then DTT was added to a final concentration of 80 mM.
After incubation for 30 minutes at 37.degree. C., iodoacetic acid
was added to a final concentration of 400 mM and incubated for 1
hour more at 37.degree. C. The sample was dialyzed against 10 mM
Tris acetate pH 8.3 overnight and concentrated to .about.200 .mu.l
in a spin column with a 3000 Da MWCO filter. To cleave the sugars
from the protein, 5 .mu.l (1,000 U) of PNGaseF (New England
Biolabs, Beverly, Mass.) was added and allowed to react overnight
at 37.degree. C.
Purification of N-Glycans
[0218] After glycans were cleaved from the protein, the sample was
dialyzed against water to remove excess salts and glycerol (from
PNGaseF formulation). Samples were then spun for 5 minutes at
6000.times.g to remove most proteins and the supernatant
lyophilized to <500 .mu.l. A C18 cartridge (Waters Corporation,
Milford, Mass.) was primed with 3 ml methanol, then 3 ml water, and
3 ml 5% acetonitrile with 0.1% TFA. The supernatant from the spun
down sample was applied to the cartridge, and 3 ml of 5%
acetonitrile with 0.1% TFA was added to elute the glycans, while
unwanted proteins were retained on the column.
[0219] GlycoClean H cartridges (Prozyme, formerly Glyko) were first
primed with 3 ml 1M NaOH, 3 ml H.sub.2O, 3 ml 30% acetic acid, and
3 ml H.sub.2O to clean the column of any impurities. Then the
cartridges were washed with 3 ml Solution A (50% acetonitrile, 0.1%
TFA), 6 ml Solution B (5% acetonitrile, 0.1% TFA), and 3 ml of
water. Glycan samples were loaded in a minimal volume of water
(<100 .mu.l), and the column was washed with 3 ml H.sub.2O
followed by 3 ml Solution B. Neutral glycans were eluted with 3 ml
of 15% acetonitrile, 0.1% TFA, and acidic glycans were eluted with
3 ml of Solution A. For the trials with glycan standards, the six
glycans listed in Table 5 were mixed in equimolar amounts (1 .mu.l
of 100 .mu.M each), and the mixture was applied to the GlycoClean H
cartridge and processed as described above. Each fraction was
dried, then redissolved in 40 .mu.l H.sub.2O for MALDI-MS analysis.
All MALDI-MS spectra were calibrated using the six glycan standards
in Table 5. Separate calibration files were used for positive and
negative modes.
Fractionation of Serum Proteins
[0220] Concanavalin A-agarose beads were purchased from Vector
Laboratories (Burlingame, Calif.). To prepare the column, 3 ml
ConA-agarose slurry was washed with ConA buffer (20 mM Tris, 1 mM
MgCl.sub.2, 1 mM CaCl.sub.2, 500 mM NaCl, pH 7.4). Before loading,
500 .mu.l of serum was mixed with 150 .mu.l of 5.times. ConA
buffer. After washing with 3 ml ConA buffer, glycoproteins were
eluted with 2 ml of 500 mM .alpha.-methyl-mannoside and dialyzed
against 10 mM phosphate pH 7.2 overnight at 4.degree. C.
[0221] Protein A-agarose beads were purchased from Calbiochem (La
Jolla, Calif.). Before use, 1 ml beads were washed 3.times. with
PBS. To separate IgG from other serum proteins, samples were
diluted 1:4 with PBS and incubated with protein A-agarose overnight
at 4.degree. C. Non-IgGs were collected by loading the slurry into
a column and washing with 2 ml PBS. IgGs were eluted with 2 ml of
0.2M glycine pH 2.5 and neutralized in 200 .mu.l Tris-HCl, pH
6.3.
SDS-PAGE and Glycoblotting of Serum Samples
[0222] Protein samples were prepared for SDS-PAGE by diluting 1:1
with 2.times. denaturing buffer (40 .mu.g/ml SDS, 20% glycerol, 30
.mu.g/ml DTT and 10 .mu.g/ml bromophenol blue in 125 mM Tris, pH
6.8), and boiling for 2 min. Pre-cast Nu-PAGE 10% Bis-Tris protein
gels were obtained from Invitrogen (Carlsbad, Calif.). Each lane
was loaded with a maximum of 10 .mu.l of sample, and run for 50 min
at 200V. After electrophoresis was complete, the gel was stained
with Invitrogen SafeStain (1 hour in staining solution, then washed
overnight with water).
[0223] The GlycoTrack glycoprotein detection kit was obtained from
Prozyme (formerly Glyko). All reagents except buffers were supplied
with the kit. Two methods were attempted--either biotinylating
glycoproteins after blotting (a) or before blotting (b). For both
methods, samples were first diluted 1:1 with 200 mM sodium acetate
buffer, pH 5.5. The membrane was blocked by incubating overnight at
4.degree. C. with blocking reagent, then washed 3.times.10 minutes
with TBS.
[0224] For method (a), samples were denatured with SDS sample
buffer, and subjected to SDS-PAGE and blotting to nitrocellulose.
After washing the membrane with PBS, the proteins were oxidized
with 10 ml of 10 mM sodium periodate in the dark at room
temperature for 20 minutes. The membrane was washed 3 times with
PBS, and 2 .mu.l of biotin-hydrazide reagent was added in 10 ml of
100 mM sodium acetate, 2 mg/ml EDTA for 60 minutes at room
temperature. After 3 washes with TBS, the membrane was blocked
overnight at 4.degree. C. with blocking reagent. Before adding 5
.mu.l of streptavidin-alkaline phosphatase (S-AP) conjugate, the
membrane was washed again with TBS. The S-AP was allowed to
incubate for 60 minutes at room temperature, and excess was washed
off with TBS. To develop the blot, 50 .mu.l of nitro blue
tetrazolium (50 mg/ml) and 37.5 .mu.l of 5-bromo-4-chloro-3-indolyl
phosphate p-toluidine (50 mg/ml) were added in 10 ml TBS, 10 mg/ml
MgCl.sub.2. After 60 minutes, the blot was washed with distilled
water and allowed to air dry.
[0225] In method (b), 20 .mu.l of sample was mixed with 10 .mu.l of
10 mM periodate in 100 mM sodium acetate, 2 mg/ml EDTA and
incubated in the dark at room temperature for 20 minutes. To
destroy excess periodate 10 .mu.l of a 12.5 mg/ml sodium bisulfite
solution in 200 mM NaOAc, pH 5.5 was added for 5 minutes at room
temperature. Biotinylation was performed by adding 5 .mu.l of
biotin amidocaproyl hydrazide solution in DMF. After incubating at
room temperature for 60 minutes, the sample was mixed with SDS
denaturing buffer and boiled for 2 minutes. Samples were run on
SDS-PAGE gels as described above, then transferred to a
nitrocellulose membrane (2 hrs, 30V). At this point, blocking and
developing steps were identical to method (a).
Chemical Modification of N-Glycans
[0226] For permethylation, glycans in water were placed in a
round-bottomed flask and lyophilized overnight. A slurry of NaOH in
DMSO (0.5 ml) was added to the glycan sample, along with 0.5 ml
methyl iodide and incubated for 15 minutes. The sample was then
diluted with water and extracted 2.times. with CHCl.sub.3,
collecting the organic phase. After drying the organic phase with
MgSO.sub.4, it was filtered through glass wool and dried under
vacuum. Samples were then redissolved in methanol for MALDI-MS
analysis.
[0227] To conjugate N-glycans to synthetic aminooxyacetyl peptide,
glycans were dried and resuspended in aqueous peptide solution (240
.mu.M). After adding 1 .mu.l of 500 mM NaOAc pH 5.5 and 20 .mu.l of
acetonitrile, the sample was incubated overnight at 40.degree. C.
Before MALDI-MS analysis, glycopeptides were purified by C18, 0.6
.mu.l bed ZipTip (Millipore, Billerica, Mass.). Specifically, the
tip was washed with 5 .mu.l of 100% acetonitrile, followed by water
and 5% acetonitrile, 0.1% TFA. To load the sample, 2 .mu.l of
sample was drawn into the tip, and discarded after 5 seconds. After
washing 3.times. with 5 .mu.l H.sub.2O, glycopeptides were eluted
with 10% acetonitrile.
PNGaseF Digestion on PVDF Membrane
[0228] PVDF-coated wells in a 96-well plate were washed with 200
.mu.l MeOH, 3.times.200 .mu.p H.sub.2O and 200 .mu.l RCM buffer (8M
urea, 360 mM Tris, 3.2 mM EDTA, pH 8.3). The protein samples (50
.mu.l) were then loaded in the wells along with 300 .mu.l RCM
buffer. After washing with wells two times with fresh RCM buffer,
500 .mu.l of 0.1M DTT in RCM buffer was added for 1hr at 37.degree.
C. To remove the excess DTT, the wells were washed three times with
H.sub.2O. For the carboxymethylation, 500 .mu.l of 0.1M iodoacetic
acid in RCM buffer was added for 30 minutes at 37.degree. C. in the
dark. The wells were washed again with water, then the membrane was
blocked with 1 ml polyvinylpyrrolidone (360,000 AMW, 1% solution in
H.sub.2O) for 1 hr at room temperature. Before adding the PNGaseF,
the wells were washed again with water. To release the glycans, 4
.mu.l of PNGaseF was added in 300 .mu.l of 50 mM Tris, pH 7.5 and
incubated overnight at 37.degree. C. Released glycans were pipetted
from the wells and purified by C18 and GlycoClean H as described
above.
Results
[0229] Building on the work with single protein systems, the
purpose of this study was to isolate and purify N-glycans from
human serum, generating a total N-glycan profile. Serum was chosen
as the diagnostic medium because many disease markers are released
into circulation[16, 17], and obtaining serum is a relatively
simple procedure.
[0230] Before being able to develop a method to study N-glycans
from serum, it was important to understand the types of molecules
present. Proteins comprise an enormous portion of serum,
approximately 7% of the total wet weight [18]. Of this amount, over
half is albumin (.about.50 mg/ml), a protein that can be
non-enzymatically glycosylated, but not N-glycosylated [19].
Although the overwhelming amounts of albumin can obscure analysis
for proteomics, it may not interfere with N-glycan profiling. There
are also large amounts of glycosylated antibodies, which have a
number of glycan structures [20, 21]. However, simple methods exist
to separate these abundant antibodies from the less abundant
glycoproteins.
[0231] When working with serum, there are several issues to
consider that are not relevant for single protein systems. Because
the proteins in the sample are so concentrated, they can easily
precipitate out of solution. Also, even though albumin does not
have N-linked sugars, the sheer quantity present may interfere with
glycan release or purification. There are several other major
proteins in serum (i.e. immunoglobulins) that are N-glycosylated,
which may overshadow the signals from less abundant proteins.
However, alterations in immunoglobulin glycosylation may also be
correlated with changes in physiological state. To determine the
contributions and/or interference from major serum proteins,
several options for separating serum proteins into fractions before
analysis were explored.
[0232] There are both neutral and charged sugars on serum
glycoproteins. Acidic glycans generally do not ionize well in the
positive ion mode of MALDI-MS, and also suffer loss of sialic
acids. On the other hand, neutral sugars ionize extremely poorly in
negative mode, which is commonly used for charged glycans.
Therefore, a method where the neutral and acidic structures were
assayed separately was compared to two chemical modification
methods that allow the glycans to ionize more uniformly.
[0233] Identifying glycan structures with complex protein mixtures
can be rather difficult. By generating a master list of all
possible compositions and their theoretical masses based on
biosynthetic pathways for glycosylation, all possible
monosaccharide composition was assigned to each peak observed in a
MALDI-MS spectrum. In most cases, each mass peak corresponds
uniquely to a monosaccharide assignment. However, in some instances
there can be more than one potential composition. If necessary, the
correct composition can be determined by using commercially
available exoenzymes that cleave the glycans only at particular
linkages.
Sample Preparation
[0234] Serum samples generally contained upwards of 120 mg/ml of
protein, making heat denaturing less ideal. Even when diluted, the
proteins in these samples precipitated rapidly, giving the sample a
gel-like consistency. This could prevent the PNGaseF from accessing
all the N-glycan sites on the proteins. One set of samples was
processed using the traditional heat-denaturation method after
diluting the serum samples 1:10 in water (FIG. 9A). A number of
glycan peaks were observed in the MALDI-MS spectrum, but there
clearly was residual detergent contamination from the denaturing
step. On a separate sample, EndoF was used since the enzyme can act
on folded proteins (FIG. 9B).
[0235] However, as discussed above, EndoF cleaves between the first
and second GlcNAc on the glycan core, causing a loss of information
on core fucosylation. After EndoF digestion the samples were
purified as usual. As shown in FIG. 9, glycans could indeed be
obtained using both methods. EndoF spectra had a relatively high
level of baseline noise, and signal intensities were relatively low
(.about.1000), leaving room for improvement.
[0236] As an alternative to heat denaturation, the proteins were
reduced with dithiothreitol (DTT) followed by carboxymethylation
with iodoacetic acid to denature the proteins [22]. Reduction
disrupts the disulfide bonds in proteins, while carboxymethylation
prevents the proteins from re-folding. After dialysis to remove
excess iodoacetic acid and DTT, PNGaseF was added to the denatured
proteins for overnight cleavage. An additional advantage to this
method over the regular SDS/.beta.-mercaptoethanol
heat-denaturation method was that the absence of detergents
facilitated purification. After the glycans were cleaved from the
core protein, the sample was dialyzed against water overnight and
lyophilized. Exchanging the sample into water prepared it to be
passed through a C18 cartridge (Waters Corporation) to remove
remaining protein. At this stage, both neutral and acidic sugars
were present in the same sample, potentially complicating the
assignment of glycan peaks in the MALDI-MS spectrum.
[0237] Because serum contains proteins with a wide variety of
neutral and charged N-glycans, analysis was facilitated by
separating the neutral sugars from the acidic carbohydrates. This
allowed each pool to be analyzed using methods particularly suited
to the chemical properties of neutral vs. charged molecules. The
GlycoClean H purification cartridge (Prozyme) was used for this
purpose by eluting glycan pools with different concentrations of
acetonitrile. Neutral sugars were eluted with 15% acetonitrile,
0.1% TFA, while acidic sugars were eluted with 50% acetonitrile,
0.1% TFA. To test the separation of neutral and acidic sugars, six
known glycan standards were used (Table 5). TABLE-US-00005 TABLE 5
Glycan standards used to test GlycoClean H separation of neutral
and acidic sugars. Commercial Charge state name Structure
description Mass (# sialic acids) NGA2 Asialo, agalacto biantennary
1317.2 0 NA2 Asialo, galactosylated, 1641.5 0 biantennary NA3
Asialo, galactosylated, 2006.0 0 triantennary SC1223 Disialylated,
2370.2 2 galactosylated, fucosylated biantennary A3 Trisialylated,
galactosylated, 2879.9 3 triantennary SC1840 Tetrasialylated,
galactosylated, 3683.4 4 tetrantennary
[0238] The neutral sugars were analyzed in positive ion mode in the
MALDI-MS, while acidic sugars were examined in negative mode (FIG.
10). To confirm that no neutral sugars were present in the acidic
glycan sample, the positive mode spectrum was checked for charged
glycans. When this method was applied to human serum N-glycans, the
spectra appeared much cleaner than those obtained from a mixed
sample, since each group of sugars could be analyzed under optimal
conditions (FIG. 11).
[0239] This process was repeated multiple times with the same serum
sample to ensure reproducibility (three aliquots were purified in
parallel on one day, and another two on two different days). In
addition, multiple normal serum samples were processed by this
method to determine the degree of glycan variation between serum
samples. Five normal male human samples from each of two different
sources (IMPATH tissue bank and Biomedical Resources) were used to
assess whether observed glycan profiles were consistent across
suppliers. As expected, there was some variation in the spectra
from different normal samples in both the neutral and acidic
fraction (FIG. 11), while aliquots from the same serum sample
appeared very similar even when they were purified on different
days. The samples from different serum banks showed similar
profiles and major peak clusters.
Most Abundant Proteins
[0240] Although serum samples can be analyzed with all proteins
present, including non-glycosylated species, it was determined
whether better results could be obtained by removing proteins such
as albumin. Concanavalin A (ConA) is a lectin that binds to
.alpha.-linked mannose, as contained in all N-glycans [23]. A serum
sample was passed through a column of agarose-bound ConA. Proteins
containing N-glycans bound to the column while non-glycosylated
proteins were washed off (this sample was collected as the ConA
flow through). The glycoproteins were then eluted with a 500 mM
.alpha.-methyl-mannoside solution, which competes for the ConA
binding sites.
[0241] To evaluate the separation of the serum sample into
glycosylated and non-glycosylated proteins, the ConA flow through
and elution samples were run on an SDS-PAGE gel (FIG. 12A). In the
gel, the albumin fraction is clearly visible in the flow through
from the ConA column, while multiple bands in the elution lane
represent glycoproteins. In addition, the glycan profiles of both
the flow through and the elution fraction were analyzed. After
dialyzing the samples against 10 mM phosphate buffer, they were
processed with PNGaseF and purified by C18 cartridge and GlycoH as
described above. There were no observable glycans present in the
flow-through fraction, while neutral and acidic sugars from the
elution fraction are shown in FIGS. 12B and 12C. The results from
total serum digests, however, yield MALDI-MS data with
signal-to-noise ratio and signal intensity that are as good as or
better than from ConA elution. Therefore, in some cases there will
be little to no advantage to removing non-glycosylated proteins
before analysis.
[0242] Serum samples were also depleted of antibodies through a
Protein A column to determine how many major peaks in the final
spectra came from IgG. The presence of glycoproteins in both the
flow through and elution fractions were determined by GlycoTrack
glycoprotein detection kit (Prozyme/Glyko) (FIG. 13A). The Protein
A elution fraction containing IgGs was treated with PNGaseF and
purified as described above. FIGS. 13B-13E show a comparison of the
glycans from IgG (Protein A elution) to the total glycan profile.
Although several of the major peaks in the spectra indeed come from
this antibody population, they do not appear for these samples to
be in large enough quantities to interfere with the signals from
other glycans.
MALDI-MSAnalysis of Serum N-Glycans
[0243] Neutral and acidic sugars require different treatment when
being analyzed by MALDI-MS. In particular, neutral sugars ionize
well in the positive ion mode, but not well in negative mode, while
the opposite is true for charged sugars. Three different matrix
formulations were tested to determine the best one for these
samples. All formulations contained DHB and spermine, as this had
yielded the best results with single-protein studies. The three
matrix preparations were 1) saturated DHB in water with 300 mM
spermine, 2) 20 mg/ml DHB in acetonitrile and 25 mM spermine in
water in a 1:1 ratio and 3) 20 mg/ml DHB in methanol and 25 mM
spermine in water in a 1:1 ratio. Preparation 2 yielded MALDI-MS
spectra with the highest signal-to-noise ratio in both positive and
negative mode, and was used for all experiments.
[0244] There are several reported methods for increasing the
sensitivity and ionization efficiency of mass spectrometry data in
the analysis of glycans. With these methods, it is sometimes
possible to analyze glycan pools as a mixture of neutral and acidic
glycans, as the chemical properties of the glycans are modified to
allow for more uniform ionization. Two types of chemical
modifications were tested to determine whether the MALDI-MS results
could be improved upon.
[0245] N-glycan samples are commonly permethylated to protect each
OH and NH.sub.2 or amide group in the carbohydrate [24]. This is
particularly useful for MS techniques such as fast atom bombardment
(FAB-MS), since permethylated glycans fragment in a much more
predictable manner than underivatized glycans. Permethylation can
also increase sensitivity in electrospray (ES-MS) and MALDI-MS. The
schematic of the permethylation reaction is shown in FIG. 14. Some
drawbacks to permethylation are that the sample has to be extremely
clean for the reaction to go to completion, and the sample requires
clean-up after the reaction. In the current study, although this
method slightly improved the ionization of N-glycan standards in
MALDI-MS over non-modified glycans, the increase in signal-to-noise
ratio was not significant (FIG. 15).
[0246] A newer method for increasing N-glycan ionization, as well
as allowing the glycans to ionize more uniformly across species is
to conjugate it to a peptide [25]. The structure of the peptide and
its glycan conjugation reaction are shown in FIG. 16. Before
MALDI-MS, it was necessary to clean up the reaction mixture using a
C18 ZipTip in order to eliminate the buffer (NaOAc) used in the
reaction. The ZipTip flowthrough, water wash and 10% acetonitrile
elution were all spotted on the plate. The glycopeptide conjugates
(in the 10% elution fraction) were readily observed in the
MALDI-MS, and neutral and acidic sugars ionized more evenly in the
positive mode as compared to unmodified glycans (FIG. 17). While
the glycan-peptide conjugation reaction is simple, the free peptide
is particularly unstable. Specifically, the peptide's active
hydroxylamine group readily reacts with any aldehydes or ketones
present, thus preventing it from conjugating to the glycans.
Although the reaction with glycan standards displayed promising
results, it was difficult to obtain a complete reaction with serum
samples. Even after several attempts to label serum glycans with
varying amounts of peptide, free glycan peaks in the spectra were
observed from flow-through and water wash spots. Because there may
be excess aldehydes or ketones remaining in serum samples, peptide
conjugation was not used, and the samples were analyzed as separate
neutral and acidic fractions.
Identifying Composition of Glycans from MALDI-MS Data
[0247] In a MALDI-MS spectrum, the main information obtained is
mass of the parent ion. With just this data, it was indeed possible
to deduce the monosaccharide composition of each peak (number of
hexNAc, hexose, fucose and sialic acid residues). Using our
knowledge of biosynthetic rules, as well as whether each glycan is
charged or uncharged, we can significantly limit the number of
possible structures for each mass peak observed. A spreadsheet to
use as a lookup table for unknown peaks was created. In addition to
unmodified masses, entries for permethylated masses were included
as well as peptide-conjugated glycans, according to the following
equations: TABLE-US-00006 n = HexNAc h = hexose f = fucose s =
sialic acid MW-H.sub.2O = 203.1 162.1 146.1 291.3 Unmodified
glycans mass = 203.1n + 162.1h + 146.1f + 291.3s + 18 Permethylated
glycans perm = mass + 51 + 14[3(n + h) + 2f + 5s]
Peptide-conjugated glycans peptide = mass + 1527.1
[0248] Using this table, regardless of the analytical methods,
MALDI-MS peaks can be associated with specific monosaccharide
compositions. Sample entries from this database are shown in Table
6. TABLE-US-00007 TABLE 6 Table of sample entries for identifying
N-glycan composition from MALDI-MS data. HexNAc Hexose Fucose
Sialic Acid mass perm peptide 2 3 1 0 1056.6 1345.6 2583.7 2 4 0 0
1072.6 1375.6 2599.7 3 3 0 1 1404.9 1777.9 2932 4 3 0 1 1608 2023
3135.1 4 3 2 0 1608.9 2009.9 3136 5 3 1 0 1665.9 2080.9 3193 6 3 0
0 1722.9 2151.9 3250 3 6 1 0 1746 2203 3273.1 4 3 1 1 1754.1 2197.1
3281.2 4 3 0 2 1899.3 2384.3 3426.4 4 3 2 1 1900.2 2371.2
3427.3
[0249] Using the table almost all the peaks in MALDI-MS serum
profiles could be identified as glycans of known composition (FIG.
18). Many of the unidentified peaks are ammonium or sodium adducts.
The composition and mass of each labeled peak are listed in Table
7. A few peaks in the acidic glycan spectrum correspond to more
than one composition. This is more common in the higher mass range
since there are a larger number of possible monosaccharide
compositions. Many of the glycans observed in these spectra were
also present in other serum samples; there are typically between
25-30 neutral glycans as well as 25-30 acidic glycans present in a
given sample. TABLE-US-00008 TABLE 7 Composition and mass of serum
glycans observed in FIG. 18 Peak HexNAc Hexose Fucose Sialic Acid
Mass Neutral glycans (FIG. 18A) 1 2 3 1 0 1056.6 2 2 4 0 0 1072.6 3
2 5 0 0 1234.7 4 3 3 1 0 1259.7 5 3 4 0 0 1275.5 6 4 3 0 0 1316.7 7
2 6 0 0 1396.8 8 3 4 1 0 1421.8 9 3 5 0 0 1437.8 10 4 3 1 0 1642.8
11 4 4 0 0 1478.8 12 5 3 0 0 1519.8 13 2 7 0 0 1558.9 14 3 6 0 0
1599.9 15 4 4 1 0 1624.9 16 4 5 0 0 1640.9 17 5 3 1 0 1665.9 18 5 4
0 0 1681.9 19 4 5 1 0 1787.0 20 4 6 0 0 1803.0 21 5 4 1 0 1828.0 22
5 5 0 0 1844.0 23 2 9 0 0 1883.1 24 5 5 1 0 1990.1 25 5 6 0 0
2006.1 26 5 5 2 0 2136.2 27 5 6 1 0 2152.2 28 5 7 0 0 2168.2 Acidic
glycans (FIG. 18B) 1 4 4 0 1 1770.1 2 3 6 0 1 1891.2 3 4 4 1 1
1916.2 4 4 5 0 1 1932.2 5 5 4 0 1 1973.2 6 3 7 0 1 2053.3 7 4 5 1 1
2078.3 8 5 4 1 1 2119.3 9 5 5 0 1 2135.3 10 4 5 0 2 2223.5 11 4 5 2
1 2224.4 12 5 3 1 2 2248.5 13 5 4 0 2 2264.5 14 5 5 1 1 2281.4 15 5
6 0 1 2297.4 16 4 5 1 2 2369.6 17 4 5 3 1 2370.5 18 5 6 1 1 2443.5
19 5 5 1 2 2572.7 20 5 6 0 2 2588.7 21 5 6 2 1 2589.6 22 6 4 1 2
2613.7 23 5 6 1 2 2734.8 24 5 6 3 1 2735.7 25 5 6 2 2 2880.9 26 5 6
4 1 2881.8
Alternative Sample Preparation Methods
[0250] Besides performing PNGaseF digests in solution, a
membrane-based method was tested with the potential for high
throughput sample processing. Proteins were adsorbed onto a PVDF
membrane in a 96-well plate, followed by reduction,
carboxymethylation and digestion in the wells[26]. While this
method works well with single glycoproteins, very few glycans were
observed when serum was used. An explanation for this result is
that albumin most likely saturated the membrane binding capacity,
and most of the glycoproteins were washed away before the PNGaseF
was added. Without removing albumin, only a few glycans were
observed in the neutral fraction, and no acidic glycans were
present (FIG. 19). Although time saved by performing the experiment
in a 96-well format may be negated by the extra steps required to
remove albumin, using the PVDF membrane as a platform for digestion
may be extremely useful for the development of a high-throughput
glycomics methodology for serum samples. All samples in this study
were, however, processed with the PNGaseF digest in solution.
[0251] It has been demonstrated that a complete N-glycan profile
from human serum proteins can be obtained. By separating glycans
into neutral and acidic pools, it was possible to clearly identify
glycans directly from MALDI-MS without chemical modification. In
addition, it was shown that albumin and IgGs do not need to be
removed from serum samples prior to analysis. With the ability to
profile all glycans from serum, it becomes possible to apply
bioinformatics approaches to search for patterns that define normal
or disease states.
[0252] Furthermore, a glycomics approach may be even more sensitive
than what can be achieved with proteomics. Even in cases where
protein expression does not change, the types of N-glycans present
on these proteins can indicate a change in physiological condition.
Already, proteomics technologies are being explored as diagnostic
tools. Examining glycosylation patterns may enable more precise
characterization of certain disease states, such as the
differentiation between benign and malignant tumors. Thus, in
combination with a bioinformatics platform, serum glycan profiling
could advance the utility of glycomics data for the early diagnosis
of currently undetectable disease states.
Example 2 References
[0253] 1. Jaeken, J., Matthijs, G. (2001) Congenital disorders of
glycosylation. Annu Rev Genomics Hum Genet 2, 129-51. [0254] 2.
Freeze, H. H., Aebi, M. (1999) Molecular basis of
carbohydrate-deficient glycoprotein syndromes type I with normal
phosphomannomutase activity. Biochim Biophys Acta 1455, 167-78.
[0255] 3. Van Eijk, M., White, M. R., Batenburg, J. J., Vaandrager,
A. B., Van Golde, L. M., Haagsman, H. P., Hartshorn, K. L. (2003)
Interactions of Influenza A virus with Sialic Acids present on
Porcine Surfactant Protein D. Am J Respir Cell Mol Biol. [0256] 4.
Glick, M. C., Kothari, V. A., Liu, A., Stoykova, L. I., Scanlin, T.
F. (2001) Activity of fucosyltransferases and altered glycosylation
in cystic fibrosis airway epithelial cells. Biochimie 83, 743-7.
[0257] 5. Scanlin, T. F., Glick, M. C. (2000) Terminal
glycosylation and disease: influence on cancer and cystic fibrosis.
Glycoconj J 17, 617-26. [0258] 6. Peracaula, R., Tabares, G.,
Royle, L., Harvey, D. J., Dwek, R. A., Rudd, P. M., de Llorens, R.
(2003) Altered glycosylation pattern allows the distinction between
prostate-specific antigen (PSA) from normal and tumor origins.
Glycobiology 13, 457-70. [0259] 7. Belanger, A., van Halbeek, H.,
Graves, H. C., Grandbois, K., Stamey, T. A., Huang, L., Poppe, I.,
Labrie, F. (1995) Molecular mass and carbohydrate structure of
prostate specific antigen: studies for establishment of an
international PSA standard. Prostate 27, 187-97. [0260] 8. Prakash,
S., Robbins, P. W. (2000) Glycotyping of prostate specific antigen.
Glycobiology 10, 173-6. [0261] 9. Chakraborty, A. K., Pawelek, J.,
Ikeda, Y., Miyoshi, E., Kolesnikova, N., Funasaka, Y., Ichihashi,
M., Taniguchi, N. (2001) Fusion hybrids with macrophage and
melanoma cells up-regulate N-acetylglucosaminyltransferase V,
betal-6 branching, and metastasis. Cell Growth Differ 12, 623-30.
[0262] 10. Przybylo, M., Hoja-Lukowicz, D., Litynska, A., Laidler,
P. (2002) Different glycosylation of cadherins from human bladder
non-malignant and cancer cell lines. Cancer Cell Int 2, 6. [0263]
11. Lin, S., Kemmner, W., Grigull, S., Schlag, P. M. (2002) Cell
surface alpha 2,6 sialylation affects adhesion of breast carcinoma
cells. Exp Cell Res 276, 101-10. [0264] 12. Nemoto-Sasaki, Y.,
Mitsuki, M., Morimoto-Tomita, M., Maeda, A., Tsuiji, M., Irimura,
T. (2001) Correlation between the sialylation of cell surface
Thomsen-Friedenreich antigen and the metastatic potential of colon
carcinoma cells in a mouse model. Glycoconj J 18, 895-906. [0265]
13. Dennis, J. W., Granovsky, M., Warren, C. E. (1999) Glycoprotein
glycosylation and cancer progression. Biochim Biophys Acta 1473,
21-34. [0266] 14. Fernandes, B., Sagman, U., Auger, M., Demetrio,
M., Dennis, J. W. (1991) Beta 1-6 branched oligosaccharides as a
marker of tumor progression in human breast and colon neoplasia.
Cancer Res 51, 718-23. [0267] 15. Petricoin, E. F., Ardekani, A.
M., Hitt, B. A., Levine, P. J., Fusaro, V. A., Steinberg, S. M.,
Mills, G. B., Simone, C., Fishman, D. A., Kohn, E. C., Liotta, L.
A. (2002) Use of proteomic patterns in serum to identify ovarian
cancer. Lancet 359, 572-7. [0268] 16. Pujol, J. L., Quantin, X.,
Jacot, W., Boher, J. M., Grenier, J., Lamy, P. J. (2003)
Neuroendocrine and cytokeratin serum markers as prognostic
determinants of small cell lung cancer. Lung Cancer 39, 131-8.
[0269] 17. Gadducci, A., Cosio, S., Carpi, A., Nicolini, A.,
Genazzani, A. R. (2004) Serum tumor markers in the management of
ovarian, endometrial and cervical cancer. Biomed Pharmacother 58,
24-38. [0270] 18. Vander, A. J., Sherman, J. H., Luciano, D. S.
(2001) Human physiology: the mechanisms of bodyfunction.
McGraw-Hill, Boston, Mass. [0271] 19. Rohovec, J., Maschmeyer, T.,
Aime, S., Peters, J. A. (2003) The structure of the sugar residue
in glycated human serum albumin and its molecular recognition by
phenylboronate. Chemistry 9, 2193-9. [0272] 20. Bihoreau, N.,
Ramon, C., Lazard, M., Schmitter, J. M. (1997) Combination of
capillary electrophoresis and matrix-assisted laser desorption
ionization mass spectrometry for glycosylation analysis of a human
monoclonal anti-Rhesus(D) antibody. J Chromatogr B Biomed Sci Appl
697, 123-33. [0273] 21. Watt, G. M., Lund, J., Levens, M., Kolli,
V. S., Jefferis, R., Boons, G. J. (2003) Site-specific
glycosylation of an aglycosylated human IgG1-Fc antibody protein
generates neoglycoproteins with enhanced function. Chem Biol 10,
807-14. [0274] 22. Lacko, A. G., Reason, A. J., Nuckolls, C.,
Kudchodkar, B. J., Nair, M. P., Sundarrajan, G., Pritchard, P. H.,
Morris, H. R., Dell, A. (1998) Characterization of recombinant
human plasma lecithin: cholesterol acyltransferase (LCAT): N-linked
carbohydrate structures and catalytic properties. J Lipid Res 39,
807-20. [0275] 23. Bryce, R. A., Hillier, I. H., Naismith, J. H.
(2001) Carbohydrate-protein recognition: molecular dynamics
simulations and free energy analysis of oligosaccharide binding to
concanavalin A. Biophys J 81, 1373-88. [0276] 24. Fukuda, M.,
Kobata, A. (1993) Glycobiology: a practical approach. IRL Press at
Oxford University Press, Oxford; N.Y. [0277] 25. Zhao, Y., Kent, S.
B., Chait, B. T. (1997) Rapid, sensitive structure analysis of
oligosaccharides. Proc Natl Acad Sci USA 94, 1629-33. [0278] 26.
Papac, D. I., Briggs, J. B., Chin, E. T., Jones, A. J. (1998) A
high-throughput microscale method to release N-linked
oligosaccharides from glycoproteins for matrix-assisted laser
desorption/ionization time-of-flight mass spectrometric analysis.
Glycobiology 8, 445-54.
Example 3
Glycan Analysis
[0278] Release of Glycans from Proteins
[0279] Several methods were used to cleave the carbohydrates from
proteins:
[0280] A) Glycoproteins were denatured with 0.5% SDS and 1%
.beta.-mercaptoethanol. Since SDS (and other ionic detergents)
inhibits enzyme activity, 1% NP-40 was added to counteract these
effects. The enzymatic cleavage was performed overnight with
PNGaseF (New England Biolabs, Beverly, Mass.) at 37.degree. C. in
sodium phosphate buffer, pH 7.5 or Tris acetate buffer pH 8.3.
[0281] B) Samples were reduced with DTT followed by alkylation with
either iodoacetic acid or iodoacetamide. The sample was dialyzed
against phosphate buffer, pH 7.5 or Tris acetate pH 8.3 overnight
and concentrated to .about.200 .mu.l in a spin column with a 3000
Da MWCO filter. To cleave the sugars from the protein between 100
and 2,000 U of PNGaseF (New England Biolabs, Beverly, Mass.) were
used.
[0282] C) Glycoproteins were denatured using a buffer containing 8M
urea, 3.2 mM EDTA and 360 mM Tris, pH 8.6 [Papac, 1998]. Reduction
and carboxymethylation of the glycoproteins was then achieved using
DTT and iodoacetic acid (or iodoacetamide), respectively. After
removal of denaturing, reducing and alkylating reagents, N-glycans
were selectively released from the glycoproteins by incubation with
PNGase F.
[0283] D) The steps for protein denaturing, protein alkylation and
glycan release were also performed with the proteins bound to a
solid support [Papac, 1998]. PVDF-coated wells in a 96-well plate
were washed with 200 .mu.l MeOH, 3.times.200 .mu.l H.sub.2O and 200
.mu.l RCM buffer (8M urea, 360 mM Tris, 3.2 mM EDTA, pH 8.3). The
protein samples (10 to 50 .mu.l) were then loaded in the wells
along with 300 .mu.l RCM buffer. After washing with wells two times
with fresh RCM buffer, 300 .mu.l of 0.1M DTT in RCM buffer was
added for 1 hr at 37.degree. C. To remove the excess DTT, the wells
were washed three times with H.sub.2O. For the carboxymethylation,
300 .mu.l of 0.1M iodoacetic acid in RCM buffer was added for 30
minutes at 37.degree. C. in the dark. The wells were washed again
with water, the membrane was then blocked with 1 ml
polyvinylpyrrolidone (360,000 AMW, 1% solution in H.sub.2O) for 1
hr at room temperature. Before adding the PNGaseF, the wells were
washed again with water. To release the glycans, 100 to 1,000 U of
PNGaseF were added in 3001 .mu.l of 50 mM Tris, pH 7.5 and
incubated overnight at 37.degree. C. Released glycans were pipetted
from the wells and purified.
[0284] E) Alternatively, after the proteins were denatured, EndoH
or Endo F(instead of PNGASE F) was used to release the glycans.
[0285] F) Chemical methods, such as hydrazinolysis and reductive
.beta.-elimination were also used.
[0286] G) The denaturing, reduction, alkylation and glycan cleavage
steps were also performed in a semi-high-throughput fashion either
in solution or by binding the proteins to solid supports in plates
with hydrophobic membranes [Papac, 1998].
Purification of Released N-Glycans
[0287] Several methods were used to isolate and purify the released
carbohydrates. These methods were used either individually and some
were used in combination.
[0288] A) Proteins were precipitated with a 3.times. volume of cold
ethanol. After centrifugation to remove the proteins, the
supernatant containing the N-glycans was evaporated by vacuum
(SpeedVac, TeleChem International, Inc., Sunnyvale, Calif.). Dried
glycans were resuspended in water.
[0289] B) Concomitant protein and salt removal was achieved using
cation exchange column of AG50W X-8 beads (Bio-Rad, Hercules,
Calif.). The resin was charged with 150 mM acetic acid and washed
with water. Glycan samples were loaded onto the column in water,
and washed through with 3 ml H.sub.2O. The flow through was
collected and lyophilized to obtain the desalted sugars.
[0290] C) GlycoClean R cartridges (Prozyme, San Leandro, Calif.;
formerly Glyko) were primed with 3 ml of 5% acetic acid, and the
samples were loaded in water. Sugars were eluted with 3 ml of water
passed through the column.
[0291] D) GlycoClean S cartridges (Prozyme, San Leandro, Calif.;
formerly Glyko), were primed with 1 ml water and 1 ml 30% acetic
acid, followed by 1 ml acetonitrile. The glycan sample was loaded
(in a maximum volume of 10 .mu.l) onto the disc, and the glycans
were allowed to adsorb for 15 minutes. After washing the disc with
1 ml of 100% acetonitrile and 5.times.1 ml of 96% acetonitrile,
glycans were eluted with 3.times.0.5 ml water.
[0292] E) GlycoClean H cartridges (Prozyme; 200 mg bed) were washed
with 3 ml of 1M NaOH, 3 ml H.sub.2O, 3 ml 30% acetic acid, and 3 ml
H.sub.2O to remove impurities. The matrix was primed with 3 ml 50%
acetonitrile with 0.1% TFA (Solvent A) followed by 3 ml 5%
acetonitrile with 0.1% TFA (Solvent B). After loading the sample in
water, the column was washed with 3 ml H.sub.2O and 3 ml Solvent B.
Finally, the sugars were eluted using 4.times.0.5 ml of Solvent A.
GlycoClean H cartridges can be reused after washing with 100%
acetonitrile and re-priming with 3 ml of Solvent A followed by 3 ml
of Solvent B. For the 25 mg cartridge, wash volumes were reduced to
0.5 ml. Eluted fractions were lyophilized and the isolated glycans
were resuspended in 10-40 .mu.l H.sub.2O.
[0293] F) Hypercarb SPE cartridges (Thermo) were washed with 3 ml
of 1M NaOH, 3 ml H.sub.2O, 3 ml 30% acetic acid, and 3 ml H.sub.2O
to remove impurities. The matrix was primed with 3 ml 5%
acetonitrile with 0.05% TFA (Solvent B). After loading the sample
in water, the column was washed with 3 ml H.sub.2O and 3 ml Solvent
B. Finally, the neutral sugars were eluted using 15% acetonitrile
0.05% TFA and acidic glycans were eluted using 50% acetonitrile
0.05% TFA.
[0294] G) Non-porous graphitic carbon SPE cartridges (SUPELCO) were
primed with 3 ml 5% acetonitrile and 0.05% TFA (Solvent B). After
loading the sample in water, the column was washed with 3 ml
H.sub.2O and 3 ml Solvent B. Finally, the neutral sugars were
eluted using 15% acetonitrile 0.05% TFA and acidic glycans were
eluted using 50% acetonitrile 0.05% TFA.
[0295] H) The glycan purification step was also performed in a
high-throughput format by using columns in 96-well plates. This
process was facilitated by the use of a TECAN robot. This protocol
allowed the processing of more than 90 samples at the same
time.
Chemical Modification of N-Glycans
[0296] Several derivatization methods are currently used to
increase the sensitivity and ionization efficiency of mass
spectrometry data in the analysis of glycans. With these methods,
it is often possible to analyze glycan pools as a mixture of
neutral and acidic glycans, as the chemical properties of the
glycans are modified to allow for more uniform ionization. N-glycan
samples are commonly permethylated to protect each OH and NH.sub.2
or amide group in the carbohydrate. This is particularly useful for
MS techniques such as fast atom bombardment (FAB-MS), since
permethylated glycans fragment in a more predictable manner than
underivatized glycans. Permethylation can also increase sensitivity
in electrospray (ES-MS) and MALDI-MS.
[0297] For permethylation, glycans in water were placed in a
round-bottomed flask and lyophilized overnight. A slurry of NaOH in
DMSO (0.5 ml) was added to the glycan sample, along with 0.5 ml
methyl iodide and incubated for 15 minutes. The sample was then
diluted with water and extracted 2.times. with CHCl.sub.3,
collecting the organic phase. After drying the organic phase with
MgSO.sub.4, it was filtered through glass wool and dried under
vacuum. Samples were then redissolved in methanol for MALDI-MS
analysis. Some drawbacks to permethylation are that the sample has
to be extremely clean for the reaction to go to completion and
requires additional purification after the reaction. Although this
method slightly improved the ionization of N-glycan standards in
MALDI-MS over unmodified glycans, many species corresponding to
incomplete modification were detected.
[0298] To conjugate N-glycans to the synthetic aminooxyacetyl
peptide, glycans were dried and resuspended in aqueous peptide
solution (240 .mu.M). After adding 1 .mu.l of 500 mM NaOAc pH 5.5
and 20 .mu.l of acetonitrile, the sample was incubated overnight at
40.degree. C. Before MALDI-MS analysis, glycopeptides were purified
by C18, 0.6 .mu.l bed ZipTip (Millipore, Billerica, Mass.).
Specifically, the tip was washed with 5 .mu.l of 100% acetonitrile,
followed by water and 5% acetonitrile, 0.1% TFA. To load the
sample, 2 .mu.l of sample was drawn into the tip, and discarded
after 5 seconds. After washing 3.times. with 5 .mu.l H.sub.2O,
glycopeptides were eluted with 10% acetonitrile. Before MALDI-MS,
it was necessary to clean up the reaction mixture using a C18
ZipTip in order to eliminate the buffer (NaOAc) used in the
reaction. The ZipTip flowthrough, water wash and 10% acetonitrile
elution were all spotted on the plate. The glycopeptide conjugates
(in the 10% elution fraction) were readily observed in the
MALDI-MS, and neutral and acidic sugars ionized more evenly in the
positive mode as compared to unmodified glycans.
[0299] While the glycan-peptide conjugation reaction is simple, the
free peptide is particularly unstable. Specifically, the peptide's
hydroxylamine group readily reacts with any aldehydes or ketones
present, thus preventing it from conjugating to the glycans. Other
labeling reagents (i.e. APTS, ANTS, AMAC, etc.) have been used but
the analysis of unmodified glycans, separated into neutral and
acidic fractions, was the method of choice for these studies.
MALDI-MS Analysis Optimization of Unmodified Glycans
[0300] Neutral and acidic sugars require different treatment when
being analyzed by MALDI-MS. In particular, neutral sugars ionize
well in the positive ion mode, while the ionization of acidic
sugars is optimal using the negative ion mode. To be able to
analyze the low abundance glycans present in a mixture glycoforms
or different glycoproteins, a matrix of matrices containing more
than 96 possible recipe combinations was generated. This study was
designed to optimize the MALDI-MS analysis for the highest
sensitivity, spot morphology, reduced peak splitting, reduced
fragmentation and linear response as a function of
concentration.
[0301] As a starting point, the matrix for glycans (DHB) was
utilized in combination with spermine (20 mg/ml DHB in acetonitrile
and 25 mM spermine in water in a 1:1 ratio.). This recipe resulted
in detection limits of 1 pmol and 10 pmol for neutrals and acidic
glycan respectively. Significant peak splitting with multiple
sodium and potassium ions were observed. Also, this matrix
crystallized as long needle-shaped crystals, which makes it
difficult to achieve reproducible quantification of glycans present
in a sample and eliminates the possibility for the automation of
data acquisition.
[0302] Some of the matrices and reagents used in this study were:
cafeic acid, dihydroxybenzoic acid (DHB), spermine,
1-hydroxyisoquinoline (HIQ), 6-aza-2-thiothymine (ATT),
2,4,6-trihydroxyacetophenone (THAP), Nafion, 6-hydroxypicolinic
acid, 3-hydroxypicolinic, 5-methoxysalicylic acid (5-MSA), ammonium
citrate, ammonium tartrate, sodium chloride, ammonium resins, etc.
These reagents were used in combination with different solvents
such as methanol, ethanol, acetonitrile and water. The matrix of
matrices study resulted in new recipes of 2,5-dihydroxybenzoic acid
(5 mg/ml) and 5-methoxysalicylic acid (0.25 mg/ml) in acetonitrile
afor neutrals and 6-aza-thiothymine (10 mg/ml in Ethanol) spotted
on Nafion coating for acidic glycans. These matrices displayed the
best detection limits for a mixture of carbohydrates to our
knowledge: 25 fmol and 5 fmol for neutrals and acidic glycans
respectively (FIG. 20). The new matrices also showed minimum peak
splitting, highly uniform signal intensity, spot morphology and no
detectable fragmentation.
[0303] A detailed study to correlate between signal intensity,
concentration and molecular weight was also performed. The analysis
covered the entire range of possible molecular weights for
N-glycans (900-4200 Da). Linear response as a function of
concentration was observed for different glycans. Taken together,
MALDI analysis of glycans using these matrices can be used to
quantify the amount of glycans present in a mixture (FIG. 21). In
particular these data enable the quantification of glycans at the
low fmol concentration range. Other methods known to those of
ordinary skill in the relevant art can also be used to quantify
glycans at a higher range of concentrations [Harvey, 1993]. For
FIGS. 1 and 2, the assigned peaks and the labels correspond to
glycan standards from Dextra Laboratories Ltd. (Reading, United
Kingdom).
[0304] A potential concern in MALDI is that the ion yield of
specific analyte in a mixture drops as the number of constituents
increase. To evaluate this, the effect of the signal strength on
the number of glycans present in a mixture was also evaluated for
both matrices. Interestingly, there was very little change in the
intensity of individual glycan signals even in the presence of
other glycans, thus indicating that the ion yield of a specific
constituent is not affected by the number of analytes present in
the glycan mixture (FIG. 21B). This ensures that even in a complex
mixture of glycans accurate amounts can be calculated using the
signal intensity. Finally, the dynamic range of these matrices were
in the low fmol range ensuring that changes in low abundant glycans
can be accurately monitored by using these matrices.
[0305] To prepare the sample spots, three methods were used. For
the crushed spot method, 1 .mu.l of matrix was spotted on the
stainless steel MALDI-MS sample plate and allowed to dry. After
crushing the spot with a glass slide, 1 .mu.l of matrix mixed 1:1
with sample was spotted on the seed crystals and allowed to dry.
Alternatively, 1 .mu.l of matrix was applied followed by 1 .mu.l of
sample, or vice versa. When resins were used in combination with
the matrices, 1 .mu.l of the resin was applied to the probe and
allowed to dry before applying the sample in a 1:1 mixture with the
matrix. All spectra were taken with the following instrument
parameters: accelerating voltage 22000V, grid voltage 93%, guide
wire 0.15% and extraction delay time of 150 nsec (unless otherwise
noted). All N-glycans were detected in linear mode with delayed
extraction and positive polarity for neutrals and negative polarity
for acidics.
LC-MS, LC-MS/MS and Capillary Electrophoresis
[0306] Due to the limitations in isomass characterization using
MALDI-MS, in some instances other techniques such as LC-MS (or
MS/MS) and CE-LIF can be applied to further characterize the
glycans released from the glycoprotein of interest. For LC-MS (or
MS/MS), the reducing end of the carbohydrates is reduced using
sodium borohydrate and the carbohydrates are separated in the using
graphitized carbon column. The column is directly attached to an
electrospray ionization mass spectrometer (ESI-MS) which allows the
detection and characterization of the carbohydrates as they elute
from the column. Although the use of exoglycosidases is often added
to this LC-MS analysis, MS/MS fragmentation is also used for
further linkage characterization of the carbohydrates based on the
fragmentation pattern.
[0307] Similarly, capillary electrophoresis-laser induced
fluorescence (CE-LIF) can also used for the further separation and
characterization of the glycans. In this case, the carbohydrates,
are first derivatized, in some preferred embodiments, by a
reductive amination, at their reducing end with a fluorescent
molecule such as APTS, ANTS, AMAC, etc. The fluorescently-modified
(or "labeled") carbohydrates are then separated by capillary
electrophoresis and detected with high sensitivity via laser
induced fluorescence. Similar to LC-MS, glycosidases can also used
in combination with CE-LIF in order to get further structural
linkage information on the carbohydrates.
Identifying Glycans Composition from MALDI-MS Data
[0308] In a MALDI-MS spectrum, the main information obtained is
mass of the parent ion. With just this data, it was indeed possible
to deduce the monosaccharide composition of each peak (number of
hexNAc, hexose, fucose and sialic acid residues). Using available
information of biosynthetic rules, as well as whether each glycan
is charged or uncharged, the number of possible structures for each
mass peak observed can be significantly limited. A spreadsheet to
use as a lookup table for unknown peaks was created. In addition to
unmodified masses, entries for permethylated masses were included
as well as peptide-conjugated glycans, according to the following
equations: TABLE-US-00009 n = HexNAc h = hexose f = fucose s =
sialic acid MW-H.sub.2O = 203.1 162.1 146.1 291.3 Unmodified
glycans mass = 203.1n + 162.1h + 146.1f + 291.3s + 18 Permethylated
glycans perm = mass + 51 + 14[3(n + h) + 2f + 5s]
Peptide-conjugated glycans peptide = mass + 1527.1
[0309] Using this table, regardless of the analytical methods, mass
spectrometry peaks can be associated with specific monosaccharide
compositions. A table of sample entries was shown above in Table 6.
Other methods known to the art can be used to determine the glycan
identity from MS data (See, for example U.S. Pat. No. 5,607,859;
U.S. Ser. No. 09/558,137; and WO 00/65521).
Computational Tools to Characterize Glycoprotein Mixture
[0310] The diverse information gathered from the different
experimental techniques are incorporated as constraints and used in
combination with a panel of proteomics and glycomics based
bioinformatics tools and databases for the efficient
characterization (glycosylation site occupancy, quantification,
glycan structure, etc.) of the glycoprotein mixture of interest
(FIGS. 22 and 23). The following six steps provides one example of
how, a known or unknown glycopeptide mixture can be characterized
using the techniques described herein.
Step 1:
[0311] Separate the glycans from the glycopeptide mixture. Isolate
and sequence the resultant peptide(s). In this example, there was
only one peptide chain and that was determined to
be--YCNISQKMMSRNLTKDR. This peptide has two possible N
glycosylation sites: CNIS and RNLT.
Step 2:
[0312] Digest the glycopeptide using trypsin followed by the
cleavage of the glycans: one sample with .sup.18O labeling and
another without labeling (.sup.16O). Generate LC-MS spectra on both
of the resultant samples. In this example, the following mass peaks
were seen for the sample without labeling (289, 475, 476, 523, 855
and 856). With labeling the following mass peaks were seen (289,
475, 478, 523, 855, and 858).
[0313] By comparing the two spectra, the peptide fragments with
mass 475 and 855 contain the glycoslylation sites--both
glycoslyation sites are glycosylated. Based on a trypsin digest
simulation of the peptide (YCNISQKMMSRNLTKDR) (See, for example,
http://us.expasy.org/tools/peptidecutter/) the different masses
were assigned as the following: 289--DR; 475--NLTK; 523--MMSR;
855--YCNISQK.
[0314] During the deglycosylation step, the Asn residue is
converted into an Asp residue which results in a total increase in
molecular weight of 1 Da, thus explaining the appearance of the 476
and 856 peaks. The deglycosylation with concomitant
.sup.18O-labeling, results in an increase of 2 Da in the peptides
that originally had a glycosylation site. This explains the
appearance of the 478 and 858 peaks.
[0315] The quantitative measurement of the peaks via the methods
described above reveals that the glycosylation site at NLTK is 75%
glycosylated. Similarly, the data for YCNISQK reveals that it is
50% glycosylated. Similarly the undigested glycopeptide mixture is
also cleaved of the glycans and label processed as described above.
The resultant analysis shows that the entire mixture is 75%
glycosylated.
Step 3:
[0316] The glycans are separated and the resultant glycans analyzed
through MALDI-MS. In this example the resultant masses with
Relative Abundance (Table 8) were: TABLE-US-00010 TABLE 8 Masses
and Relative Abundance Mass Relative Abundance 1235 40 1397 44 1559
16
[0317] Thus, there are three different glycans in this glycopeptide
mixture.
Step 4:
[0318] Digest the glycopeptide mixture with trypsin and analyze the
resultant mixture through MALDI-MS. In this example the resultant
masses are 289, 475, 523, 854, 1871, 2033 and 2089.
[0319] Based on comparing the MS results with the trypsin digest
simulation of the peptide, the following observations are made.
Fragment NLTK is glycosylated with glycans with mass 1397 and 1559.
Fragment YCNISQK is glycosylated with glycan with mass 1235.
[0320] Thus there are six possible glycopeptide chains in the
mixture. [0321] Chain A that is not glycosylated. [0322] Chain B in
which the second Asn is glycosylated with Glycan--1397. [0323]
Chain C in which the second Asn is glycosylated with Glycan--1559.
[0324] Chain D in which the first Asn is glycosylated with Glycan
1235. [0325] Chain E in which the first Asn is glycosylated with
1235 and the second with 1397. [0326] Chain F in which the first
Asn is glycosylated with 1235 and the second with 1559. Step 5:
[0327] Generate equations based on the experimental results and/or
other data.
[0328] a,b,c,d,e and f are the relative abundances of the chains A,
B, C, D, E and F respectively, and the following set of equations
were generated based on the experimental results from steps 1
through 4. TABLE-US-00011 a + b + c + d + e + f = 1 6 possible
chains a + b + c = d + e + f 50% occupancy in first glycosylation
site (a + d) * 3 = (b + c + e + f) 75% occupancy in second
glycosylation site d + e + f = 2.5 * (c + f) Glycan 1235 to Glycan
1559 b + e = 2.75 * (c + f) Glycan 1397 to Glycan 1559 3 * a = b +
c + d + e + f 75% of glycopeptide chains are glycosylated
[0329] Solving the equations, the results are: a=0.25, b=0.25,
c=d=0, e=0.3, f=0.2 Step 6:
[0330] The masses from step 3 can be resolved into potential glycan
structures by using a glycan database lookup
(http://www.functionalglycomics.org/glycomics/molecule/jsp/carbohydrate/s-
earchByMw.jsp), and the exact structure of the carbohydrates were
corroborated from the glycosidase digest analysis. By putting
together the results in steps 1 to 6, the unknown glycoprotein
mixture was determined to be (Tables 9 and 10): TABLE-US-00012
TABLE 9 Glycan Identification Peptide Glycan Site 1 Glycan Site 2
Relative Abundance YCN.sub.1ISQKMMSRN.sub.2LTKDR None None .25
YCN.sub.1ISQKMMSRN.sub.2LTKDR None HEX.sub.6HEXNAC.sub.2 .25
YCN.sub.1ISQKMMSRN.sub.2LTKDR HEX.sub.5HEXNAC.sub.2
HEX.sub.6HEXNAC.sub.2 .3 YCN.sub.1ISQKMMSRN.sub.2LTKDR
HEX.sub.5HEXNAC.sub.2 HEX.sub.7HEXNAC.sub.2 .2
[0331] TABLE-US-00013 TABLE 10 Glycan Structure Glycan Structure
HEX.sub.5HEXNAC.sub.2 ##STR29## HEX.sub.6HEXNAC.sub.2 ##STR30##
HEX.sub.7HEXNAC.sub.2 ##STR31##
Analysis of Glycosylation of Glycoprotein Standards
[0332] As an example, the optimized procedures were performed using
two known N-glycosylated protein standards with different
properties, ribonuclease B (RNaseB), a glycoprotein that only
contains high mannose structures, and ovalbumin, which contains
both hybrid and complex glycan structures at one glycosylation
site. The procedures described above were applied to samples
(obtained from the Hamel laboratory, MIT Bioprocess Engineering
Center, Cambridge, Mass.) produced under various conditions.
Determination and Quantification of Glycosylation Site
Occupancy
[0333] Before protease cleavage, the glycoproteins are first
denatured in the presence of urea, reduced with DTT and
carboxymethylated with iodoacetamide. To remove the denaturing
reagents, the samples are concentrated using a centrifugal
concentrator (3,000 MWCO) followed by buffer exchanged into
protease compatible buffer (50 mM ammonium bicarbonate, pH 8.5, for
trypsin digest). The proteins are then cleaved by proteases
followed by denaturation of proteases by boiling the sample in
water and liophilization. Glycosylation site specific labeling is
achieved by reacting the samples with PNGase F in the presence of
.sup.18O-water (FIG. 24). After desalting the glycosylated,
unglycosylated, and .sup.18O-labeled unglycosylated peptides
through a C-18 solid phase extraction cartridge, these are used for
LC-MS, LC-MS/MS, MALDI or MALDI-FTMS. For this study the .sup.16O
and .sup.18O labeled samples were mixed in a 1:1 ratio before
injection in order to facilitate the analysis. Other techniques for
peptide sequencing can also be used at this point. The peptides
were analyzed using a capillary LC-MS using a Vydac C-18 MS 5 .mu.m
(250.times.0.3mm) column coupled to a Mariner Biospectrometry
Workstation. The peptides generated from the protease cleavage were
corroborated using the Swiss-Prot database (ribonuclease B, P00656
and ovalbumin, P01012).
[0334] By studying the data obtained from the differentially
labeled peptides after glycan cleavage, the specific glycosylation
site can be easily determined. The introduction of the .sup.18O at
the glycosylation site is detected as a 2 Da increase for a
specific peptide. This data facilitate the determination of the
glycosylation site and its occupancy. As determined using the
peptide mass calculator from the protein data bank
(http://us.expasy.org/tools/peptidemass.html), the tryptic digest
of ribonuclease B should yield a peptide fragment with a
[M+H].sup.+ of 475.29 Da containing the glycosylation site (NLTK).
Since the enzyme-mediated glycan cleavage generates an aspartic
acid at the asparagine site, a peptide ion of [M+H].sup.+ of 476.29
Da for the unlabeled peptide and a 478.29 Da for the
.sup.18O-labeled peptide containing the glycosylation site was
expected. As shown in FIG. 25, it was easy to identify the peptide
fragment containing the glycosylation site in ribonuclease B by
comparing the LC-MS data from the 1:1 mixture of .sup.16O/.sup.18O
labeled peptides against the unlabeled sample. The presence of the
+2 Da species in a 1:1 ratio in the .sup.16O/.sup.18O labeled
mixture and the absence of species with [M+H].sup.+ of 475.29 Da
indicates that this peptide contains a glycosylation site and that
it is 100% occupied in both samples of the mixture. By analyzing
the differences between the peptide masses in this batch to the
peptide masses from the samples not exposed to glycan cleavage, a
preliminary identification of the glycans was obtained. This was
further validated and quantified by analyzing the glycans
separately as described below.
Release and Purification of N-Glycans from Glycoprotein
Standards
[0335] Several enzymatic and chemical methods were used to separate
glycans from their protein cores. Of the chemical methods,
hydrazinolysis provides the most efficient release of glycans [31].
However, this approach requires the sample to be very clean, with
no residual salts, and the reaction does not proceed efficiently in
air or water, making hydrazinolysis somewhat undesirable as a quick
measure of quality control. N-glycanase F (PNGaseF) was chosen
among enzymatic methods for the cleavage of N-linked glycans since
the use of other enzymes results in loss of information such as
fucosylation at the proximal GlcNAc.
[0336] For optimal enzyme activity proteins were unfolded, reduced
and carboxymethylated prior to enzymatic digestion. Typically, the
samples were denatured by heating in the presence of
.beta.-mercaptoethanol and/or SDS or by incubating at room
temperature with urea, followed by reduction with DTT and
carboxymethylation with iodoactic acid or iodoacetamide. To isolate
the carbohydrates from the sample, the proteins were first
precipitated with ethanol and the supernatant containing the
glycans was then dried under vacuum and resuspended in water.
Subsequent purification steps were required when detergents were
used. Optimal results were obtained by using porous graphitic
carbon columns. Neutral and charged carbohydrates were separated
using these columns and eluted in mass spectrometry-compatible
buffers. At this point, the most difficult component to get rid of
was the detergent, which interferes with the types of analytical
techniques that were used in this study.
Glycan Analysis
[0337] Different analytical techniques known in the art can be used
for the glycan analysis methods. In this study MALDI-MS was used
due to its simplicity and sensitivity (low femtomol after
optimizations described above). The MALDI-MS protocol was optimized
for the detection and quantification of low abundance carbohydrates
(FIGS. 26 and 27). In particular, FIG. 27 shows the MALDI-MS
spectrum of ovalbumin glycans. The observed peaks and their
structures were found. The results are as shown above in Table
3.
RNAse B Computational Analysis
[0338] The information obtained from the previous analysis was
analyzed using the computational platform that contains the
proteomics and glycomics based bioinformatics tools and databases
described herein.
[0339] The sequence of the protein backbone was determined from the
proteomics database as follows: TABLE-US-00014 MALKSLVLLS
LLVLVLLLVR VQPSLGKETA AAKFERQHMD SSTSAASSSN YCNQMMKSRN.sub.1
LTKDRCKPVN TFVHESLADV QAVCSQKNVA CKNGQTNCYQ SYSTMSITDC RETGSSKYPN
CAYKTTQANK HIIVACEGNP YVPVHFDASV
[0340] The glycosylation site is at SNLT. It is 100% glycosylated
and five different glycans were observed on analysis of the glycans
via MALDI-MS. The results of the computational analysis showed that
there were 5 different chains in the glycoprotein mixture as shown
in Table 11 below: TABLE-US-00015 TABLE 11 Results from the
Computational Analysis Relative Protein Sequence Glycan Abundance
MALKSLVLLS LLVLVLLLVR VQPSLGKETA HEX.sub.5HEXNAC.sub.2 .41
AAKFERQHMD SSTSAASSSN YCNQMMKSRN.sub.1 LTKDRCKPVN TFVHESLADV
QAVCSQKNVA CKNGQTNCYQ SYSTMSITDC RETGSSKYPN CAYKTTQANK HIIVACEGNP
YVPVHFDASV MALKSLVLLS LLVLVLLLVR VQPSLGKETA HEX.sub.6HEXNAC.sub.2
.29 AAKFERQHMD SSTSAASSSN YCNQMMKSRN.sub.1 LTKDRCKPVN TFVHESLADV
QAVCSQKNVA CKNGQTNCYQ SYSTMSITDC RETGSSKYPN CAYKTTQANK HIIVACEGNP
YVPVHFDASV MALKSLVLLS LLVLVLLLVR VQPSLGKETA HEX.sub.7HEXNAC.sub.2
.1 AAKFERQHMD SSTSAASSSN YCNQMMKSRN.sub.1 LTKDRCKPVN TFVHESLADV
QAVCSQKNVA CKNGQTNCYQ SYSTMSITDC RETGSSKYPN CAYKTTQANK HIIVACEGNP
YVPVHFDASV MALKSLVLLS LLVLVLLLVR VQPSLGKETA HEX.sub.8HEXNAC.sub.2
.14 AAKFERQHMD SSTSAASSSN YCNQMMKSRN.sub.1 LTKDRCKPVN TFVHESLADV
QAVCSQKNVA CKNGQTNCYQ SYSTMSITDC RETGSSKYPN CAYKTTQANK HIIVACEGNP
YVPVHFDASV MALKSLVLLS LLVLVLLLVR VQPSLGKETA HEX.sub.9HEXNAC.sub.2
.06 AAKFERQHMD SSTSAASSSN YCNQMMKSRN.sub.1 LTKDRCKPVN TFVHESLADV
QAVCSQKNVA CKNGQTNCYQ SYSTMSITDC RETGSSKYPN CAYKTTQANK HIIVACEGNP
YVPVHFDASV
MALDI-MS Analysis Of N-Glycans from Antibodies Produced in Applikon
and Wave Reactors
[0341] Two antibody samples produced by mouse-mouse hybridoma cells
(Biokit SA, Barcelona, Spain) grown in an Applikon stirred tank
reactor (STR) were analyzed, along with three samples produced in
Wave reactors. The reactor conditions used are shown in Table 12.
TABLE-US-00016 TABLE 12 Reactor conditions used to produce antibody
samples. Sample Reactor Type DO pH Other 1 Applikon STR 50% 7 2
Applikon STR 90% Not controlled 3 Wave Controlled Not controlled 4
Wave Controlled 7 NaHCO.sub.3 for pH control 5 Wave Not 7 Fresh
media controlled for pH control
[0342] In the Applikon STR reactor, pH can be controlled
automatically by the instrument, which dispenses CO.sub.2,
NaHCO.sub.3 and O.sub.2 as needed. In the Wave reactor, however,
measurements must be taken manually and pH adjusted by hand. The pH
in this reactor can be controlled by either adding fresh media as
the cells grow, or adding NaHCO.sub.3 for increased buffering
capacity, and CO.sub.2 as needed. The main difference between the
reactor types is the mode of agitation. In the Applikon STR, a
blade stirrer keeps the cell suspension in motion, while a sparger
introduces oxygen to the system in a controlled manner. In the Wave
reactor, a rocking motion generates waves that mix the components
of the system and aids the transfer of oxygen and other gases into
the system.
[0343] The purified antibodies were processed according to the
optimized method described above. For each sample, 100 .mu.g of
protein was used as the starting material. Both positive and
negative ion modes were used in the MALDI-MS to determine whether
there were charged sugars present. No acidic glycans were observed
from the analysis; which indicated neutral sugars were obtained
from the antibodies. The MALDI-MS data of the five antibody samples
produced using different conditions contained the same six glycans
with molecular weights of 1317 Da, 1463 Da, 1478 Da, 1625 Da, 1641
Da and 1787 Da. The corresponding structures to these glycanswere
determined using the methods described above and are shown in FIG.
28 with their theoretical masses.
[0344] These results indicate that the production method did not
alter the nature of the glycans present in the samples, rather, the
quantities of some glycans were affected. Notably, samples prepared
in the Wave reactor displayed a 40% decrease in 1625.4 Da glycan as
well as 20% reductions in the 1787.7 Da glycan with respect to
samples prepared in the Applikon reactor while the other glycans
remained equal.
[0345] While the exact mechanisms for these changes are not known,
it is interesting that the largest changes occurred due to reactor
type, not reactor conditions such as pH, DO or media composition.
Because the Applikon STR and the Wave reactors differ most in their
method of agitation, reactor configuration is therefore the most
likely source of glycan variation.
[0346] Differences in protein glycosylation have been linked to
shear stress, such as by the stirring blade or the gas sparger in
an STR reactor. However, the turbulence created in the Wave reactor
also generates shear stress. One hypothesis for the shear stress
effect is that cells must increase their overall protein production
in response to membrane and/or cytoskeletal damage. As a
consequence, the biosynthetic enzymes for glycosylation are
diverted away from the protein of interest [27].
[0347] Although most observed parameters, including total antibody
production, were similar in Applikon STR and Wave cultures, cells
from the Wave reactor had slight increases in metabolic rates.
Changes in cell metabolism may yield effects similar to those
caused by shear stress, as all glycoproteins synthesized in the
cell must compete for the same machinery in the ER and golgi.
Example 3 References
[0348] 1. Hirschberg, C. B., Snider, M. D. (1987) Topography of
glycosylation in the rough endoplasmic reticulum and Golgi
apparatus. Annu Rev Biochem 56, 63-87. [0349] 2. Bause, E. (1983)
Structural requirements of N-glycosylation of proteins. Studies
with proline peptides as conformational probes. Biochem J 209,
331-6. [0350] 3. Marshall, R. D. (1972) Glycoproteins. Annu Rev
Biochem 41, 673-702. [0351] 4. Dwek, R. A. (1996) Glycobiology:
Toward Understanding the Function of Sugars. Chem Rev 96, 683-720.
[0352] 5. O'Connor, S. E., Imperiali, B. (1996) Modulation of
protein structure and function by asparagine-linked glycosylation.
Chem Biol 3, 803-12. [0353] 6. Crocker, P. R., Varki, A. (2001)
Siglecs in the immune system. Immunology 103, 137-45. [0354] 7.
Helenius, A., Aebi, M. (2001) Intracellular functions of N-linked
glycans. Science 291, 2364-9. [0355] 8. Imperiali, B., O'Connor, S.
E. (1999) Effect of N-linked glycosylation on glycopeptide and
glycoprotein structure. Curr Opin Chem Biol 3, 643-9. [0356] 9.
Furukawa, K., Takamiya, K., Okada, M., Inoue, M., Fukumoto, S.
(2001) Novel functions of complex carbohydrates elucidated by the
mutant mice of glycosyltransferase genes. Biochim Biophys Acta
1525, 1-12. [0357] 10. Jaeken, J., Matthijs, G. (2001) Congenital
disorders of glycosylation. Annu Rev Genomics Hum Genet 2, 129-51.
[0358] 11. Freeze, H. H., Aebi, M. (1999) Molecular basis of
carbohydrate-deficient glycoprotein syndromes type I with normal
phosphomannomutase activity. Biochim Biophys Acta 1455, 167-78.
[0359] 12. Carchon, H., Van Schaftingen, E., Matthijs, G., Jaeken,
J. (1999) Carbohydrate-deficient glycoprotein syndrome type IA
(phosphomannomutase-deficiency). Biochim Biophys Acta 1455, 155-65.
[0360] 13. Powell, L. D., Sgroi, D., Sjoberg, E. R., Stamenkovic,
I., Varki, A. (1993) Natural ligands of the B cell adhesion
molecule CD22 beta carry N-linked oligosaccharides with
alpha-2,6-linked sialic acids that are required for recognition. J
Biol Chem 268, 7019-27. [0361] 14. Sgroi, D., Varki, A.,
Braesch-Andersen, S., Stamenkovic, I. (1993) CD22, a B
cell-specific immunoglobulin superfamily member, is a sialic
acid-binding lectin. J Biol Chem 268, 7011-8. [0362] 15. Karlsson,
K. A. (1998) Meaning and therapeutic potential of microbial
recognition of host glycoconjugates. Mol Microbiol 29, 1-11. [0363]
16. Pritchett, T. J., Brossmer, R., Rose, U., Paulson, J. C. (1987)
Recognition of monovalent sialosides by influenza virus H3
hemagglutinin. Virology 160, 502-6. [0364] 17. Sears, P., Wong, C.
H. (1998) Enzyme action in glycoprotein synthesis. Cell Mol Life
Sci 54, 223-52. [0365] 18. Varki, A. (1999) Essentials of
glycobiology. Cold Spring Harbor Laboratory Press, Cold Spring
Harbor, N.Y. [0366] 19. Parodi, A. J. (2000) Protein glucosylation
and its role in protein folding. Annu Rev Biochem 69, 69-93. [0367]
20. Chang, G. D., Chen, C. J., Lin, C. Y., Chen, H. C., Chen, H.
(2003) Improvement of glycosylation in insect cells with mammalian
glycosyltransferases. J Biotechnol 102, 61-71. [0368] 21. Perlman,
S., van den Hazel, B., Christiansen, J., Gram-Nielsen, S.,
Jeppesen, C. B., Andersen, K. V., Halkier, T., Okkels, S.,
Schambye, H. T. (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, 3227-35.
[0369] 22. Darling, R. J., Kuchibhotla, U., Glaesner, W.,
Micanovic, R., Witcher, D. R., Beals, J. M. (2002) Glycosylation of
erythropoietin affects receptor binding kinetics: role of
electrostatic interactions. Biochemistry 41, 14524-31. [0370] 23.
Krapp, S., Mimura, Y., Jefferis, R., Huber, R., Sondermann, P.
(2003) Structural analysis of human IgG-Fc glycoforms reveals a
correlation between glycosylation and structural integrity. J Mol
Biol 325, 979-89. [0371] 24. Raju, T. S., Briggs, J. B., Borge, S.
M., Jones, A. J. (2000) Species-specific variation in glycosylation
of IgG: evidence for the species-specific sialylation and
branch-specific galactosylation and importance for engineering
recombinant glycoprotein therapeutics. Glycobiology 10, 477-86.
[0372] 25. Kunkel, J. P., Jan, D. C., Butler, M., Jamieson, J. C.
(2000) Comparisons of the glycosylation of a monoclonal antibody
produced under nominally identical cell culture conditions in two
different bioreactors. Biotechnol Prog 16, 462-70. [0373] 26.
Zhang, F., Saarinen, M. A., Itle, L. J., Lang, S. C., Murhammer, D.
W., Linhardt, R. J. (2002) The effect of dissolved oxygen (DO)
concentration on the glycosylation of recombinant protein produced
by the insect cell-baculovirus expression system. Biotechnol Bioeng
77, 219-24. [0374] 27. Senger, R. S., Karim, M. N. (2003) Effect of
Shear Stress on Intrinsic CHO Culture State and Glycosylation of
Recombinant Tissue-Type Plasminogen Activator Protein. Biotechnol
Prog 19, 1199-209. [0375] 28. Muthing, J., Kemminer, S. E.,
Conradt, H. S., Sagi, D., Nimtz, M., Karst, U., Peter-Katalinic, J.
(2003) Effects of buffering conditions and culture pH on production
rates and glycosylation of clinical phase I anti-melanoma mouse
IgG3 monoclonal antibody R24. Biotechnol Bioeng 83, 321-34. [0376]
29. Joao, H. C., Dwek, R. A. (1993) Effects of glycosylation on
protein structure and dynamics in ribonuclease B and some of its
individual glycoforms. Eur J Biochem 218, 239-44. [0377] 30.
Harvey, D. J., Wing, D. R., Kuster, B., Wilson, I. B. (2000)
Composition of N-linked carbohydrates from ovalbumin and
co-purified glycoproteins. J Am Soc Mass Spectrom 11, 564-71.
[0378] 31. Patel, T., Bruce, J., Merry, A., Bigge, C., Wormald, M.,
Jaques, A., Parekh, R. (1993) Use of hydrazine to release in intact
and unreduced form both N- and O-linked oligosaccharides from
glycoproteins. Biochemistry 32, 679-93. [0379] 32. Tarentino, A.
L., Plummer, T. H., Jr., Maley, F. (1974) The release of intact
oligosaccharides from specific glycoproteins by
endo-beta-N-acetylglucosaminidase H. J Biol Chem 249, 818-24.
[0380] 33. Tarentino, A. L., Maley, F. (1974) Purification and
properties of an endo-beta-N-acetylglucosaminidase from
Streptomyces griseus. J Biol Chem 249, 811-7. [0381] 34. Tarentino,
A. L., Gomez, C. M., Plummer, T. H., Jr. (1985) Deglycosylation of
asparagine-linked glycans by peptide:N-glycosidase F. Biochemistry
24, 4665-71. [0382] 35. Hu, G. F. (1995) Fluorophore-assisted
carbohydrate electrophoresis technology and applications. J
Chromatogr A 705, 89-103. [0383] 36. Rhomberg, A. J., Ernst, S.,
Sasisekharan, R., Biemann, K. (1998) Mass spectrometric and
capillary electrophoretic investigation of the enzymatic
degradation of heparin-like glycosaminoglycans. Proc Natl Acad Sci
USA 95, 4176-81.
Example 4
Glycome Profiling
[0383] Sample Preparation and Carbohydrate Purification
[0384] Samples (usually 60 .mu.l) from the different body fluids
(serum, saliva, urine, tears, etc.) were processed in a similar
manner as described below. Although in most cases the entire
glycoproteome from the sample was analyzed, in some cases, the
samples were further fractionated in order to analyze a
"sub-glycome" from a specific body fluid. For example, a specific
subset of proteins (such as antibodies, serum albumins, and other
high abundance proteins) were removed from the original serum
sample in order to analyze a more specific subset of glycoproteins
in more detail. For fractionation, the sample proteome was divided
into "high abundance" and "low abundance" using solid supports
containing antibodies, proteins and synthetic molecules specific
for the desired proteins to be removed or concentrated. For
example, IgGs were removed using protein A agarose (Biorad), beads
and serum albumin was removed using Affi-blue gel (Biorad). Other
fractionations included the separation into acidic and basic
proteome using cation and anion exchange chromatography or the
separation between glycosylated and unglycosylated proteins using
Con-A columns. The removal of specific proteins was quantified by
western blots.
[0385] Proteins in the samples (either fractionated or
unfractionated) were then denatured using a buffer containing 8M
urea, 3.2 mM EDTA and 360 mM Tris, pH 8.6.[Papac, 1998]. Reduction
and carboxymethylation of the sample proteome was then achieved
using DTT and iodoacetamide respectively. Although iodoacetic acid
is often used as the alkylating agent for the carboxymethylation,
this one is not optimal when analyzing body fluids containing a
wide range of glycoproteins since it generally causes precipitation
of most proteins. After removal of denaturing, reducing and
alkylating reagents, N-glycans were selectively released from the
glycoproteins by incubation with PNGase F. The steps for protein
denaturing, protein alkylation and glycan release were also
performed with the proteins bound to a solid support as described
below. The released carbohydrates were then purified from the
proteins and separated into neutrals and acidic glycans in one step
using a graphitized carbon columns. The glycan purification step
was also performed in a high-throughput format by using columns in
96-well plates. This process was facilitated by the use of a TECAN
robot. This protocol allowed the processing of more than 90 samples
at the same time.
Fractionation of Serum Proteins
[0386] As an example, to remove serum albumin and IgGs, Affi-Blue
Gel (Biorad, 200 .mu.L) and Prot A (Biorad, 200 .mu.L) were mixed
in a 1:1 ratio and placed in a serum protein column. The column was
washed with 1 mL of compatible serum protein binding buffer (20 mM
phosphate, 100 mM NaCl, pH 7.2) using gravity flow. The column was
placed in an empty 2 mL collection tube and centrifuged at 10,000 G
for 20 seconds at 4.degree. C. The flow was stopped during the
sample preparation. Serum (60 .mu.L) was mixed with compatible
serum protein binding buffer (180 .mu.L), and 200 .mu.L of diluted
serum was added to the top of the resin bed and allowed to mix with
the column for 15 minutes. The column was then centrifuged at
10,000 G for 20 seconds at 4 C. Using the same collection tube, the
column was washed with 200 .mu.L of compatible serum protein
binding buffer and centrifuged again at 10,000 G for 20 seconds at
4.degree. C. For the removal of IgGs alone, only protein A agarose
beads were used and the binding buffer was modified to 10 mM
phosphate, 150 mM NaCl, pH 8.2.
[0387] To separate glycosylated (mainly high-mannose) from
unglycosylated proteins, Concanavalin A-agarose beads (Vector
Laboratories, Burlingame, Calif.) were used. To prepare the column,
3 ml ConA-agarose slurry was washed with ConA buffer (20 mM Tris, 1
mM MgCl.sub.2, 1 mM CaCl.sub.2, 500 mM NaCl, pH 7.4). Before
loading, 500 .mu.l of serum was mixed with 150 .mu.l of 5.times.
ConA buffer. After washing with 3 ml ConA buffer, glycoproteins
were eluted with 2 ml of 500 mM .alpha.-methyl-mannoside and
dialyzed against 10 mM phosphate pH 7.2 overnight at 4.degree.
C.
Analysis of IgG and Serum Albumin Depletion
[0388] Samples were prepared for SDS-Page electrophoresis by
diluting 1:1 with 2.times. sample buffer (120 mM Tris base, 280 mM
SDS, 20% Glycerol, 10% BME, 20 ng/ml BPB), boiled for 5 minutes,
and 10 ul was loaded per lane in a 4-12% Bis-Tris precast gel
(Invitrogen: NPO323BOX). Lane one contained 5 ul of a standard
(BioRad: Precision All Blue Standard, 161-0373). The gel was run
for 70 minutes at 200V. The gel was stained with SimplyBlue
(Invtrogen:LC6060) according to the manufacturer. Imaging was
performed on a Kodak Image Station 2000R. Another set of duplicate
depleted samples were run as before and one gel was for SimplyBlue
and the other was transferred to a 0.20 um nitrocellulose membrane
(Invitrogen:LC2000) employing an X Cell Blot Module
(Invitrogen:E19051) for 70 minutes at 30V. The membrane was then
blocked overnight at 4.degree. C. in 5% Blotto (Santa Cruz:sc-2325)
and then probed with 1:1000 Protein A-hrp (Zymed:10-1023) for 1
hour at 4.degree. C. and washed 4 times with washing buffer (1
.times.TBS:200 mMTris base, 1.5M NaCl, pH7.5). The blot was
developed with 4 ml of substrate (ECL plus Western Blotting
Detection System:RPN2132) for 2 minutes and then exposed. The bands
corresponding to the treatments were manually captured as ROI
(region of interest) employing the Kodak 1D Image Analysis Software
and the Mean Intensity was normalized to the controls. The same
blot was then washed again and re-probed with 1:1000 Sheep
Anti-human Albumin-hrp (Serotec:AHP102P) for 1 hour at 4.degree. C.
The blot was washed again, developed and imaged as before (FIG.
29).
Glycoblotting of Serum Samples
[0389] Protein samples were prepared for SDS-PAGE by diluting 1:1
with 2.times. denaturing buffer (40 .mu.g/ml SDS, 20% glycerol, 30
.mu.g/ml DTT and 10 .mu.g/ml bromophenol blue in 125 mM Tris, pH
6.8) and boiling for 2 min. Pre-cast Nu-PAGE 10% Bis-Tris protein
gels were obtained from Invitrogen (Carlsbad, Calif.). Each lane
was loaded with a maximum of 10 .mu.l of sample and run for 50 min
at 200V. After electrophoresis was complete, the gel was stained
with Invitrogen SafeStain (1 hour in staining solution, then washed
overnight with water).
[0390] The GlycoTrack glycoprotein detection kit was obtained from
Prozyme (formerly Glyko). All reagents except buffers were supplied
with the kit. Two methods were attempted--either biotinylating
glycoproteins after blotting (a) or before blotting (b). For both
methods, samples were first diluted 1:1 with 200 mM sodium acetate
buffer, pH 5.5. The membrane was blocked by incubating overnight at
4.degree. C. with blocking reagent, then washed 3.times.10 minutes
with TBS.
[0391] For method (a), samples were denatured with SDS sample
buffer, and subjected to SDS-PAGE and blotting to nitrocellulose.
After washing the membrane with PBS, the proteins were oxidized
with 10 ml of 10 mM sodium periodate in the dark at room
temperature for 20 minutes. The membrane was washed 3 times with
PBS, and 2 .mu.l of biotin-hydrazide reagent was added in 10 ml of
100 mM sodium acetate, 2 mg/ml EDTA for 60 minutes at room
temperature. After 3 washes with TBS, the membrane was blocked
overnight at 4.degree. C. with blocking reagent. Before adding 5
.mu.l of streptavidin-alkaline phosphatase (S-AP) conjugate, the
membrane was washed again with TBS. The S-AP was allowed to
incubate for 60 minutes at room temperature, and excess was washed
off with TBS. To develop the blot, 50 .mu.l of nitro blue
tetrazolium (50 mg/ml) and 37.5 .mu.l of 5-bromo-4-chloro-3-indolyl
phosphate p-toluidine (50 mg/ml) were added in 10 ml TBS, 10 mg/ml
MgCl.sub.2. After 60 minutes, the blot was washed with distilled
water and allowed to air dry.
[0392] In method (b), 20 .mu.l of sample was mixed with 10 .mu.l of
10 mM periodate in 100 mM sodium acetate, 2 mg/ml EDTA and
incubated in the dark at room temperature for 20 minutes. To
destroy excess periodate 10 .mu.l of a 12.5 mg/ml sodium bisulfite
solution in 200 mM NaOAc, pH 5.5 was added for 5 minutes at room
temperature. Biotinylation was performed by adding 5 .mu.l of
biotin amidocaproyl hydrazide solution in DMF. After incubating at
room temperature for 60 minutes, the sample was mixed with SDS
denaturing buffer and boiled for 2 minutes. Samples were run on
SDS-PAGE gels and transferred to a nitrocellulose membrane (2 hrs,
30V). At this point, blocking and developing steps were identical
to method (a) (FIG. 30).
Glycan Release Using Solid Supports: PNGaseF Digestion on PVDF
Membrane
[0393] Glycans were also released using PVDF membranes as described
by Papac, et.al. [Papac, 1998]. However, high abundance proteins
were first removed before using this method since it resulted in
low recoveries when processing entire body fluids. PVDF-coated
wells in a 96-well plate were washed with 200 .mu.l MeOH,
3.times.200 .mu.l H.sub.2O and 200 .mu.l RCM buffer (8M urea, 360
mM Tris, 3.2 mM EDTA, pH 8.3). The protein samples (50 .mu.l) were
then loaded in the wells along with 300 .mu.l RCM buffer. After
washing with wells two times with fresh RCM buffer, 500 .mu.l of
0.1M DTT in RCM buffer was added for 1 hr at 37.degree. C. To
remove the excess DTT, the wells were washed three times with
H.sub.2O. For the carboxymethylation, 500 .mu.l of 0.1M iodoacetic
acid in RCM buffer was added for 30 minutes at 37.degree. C. in the
dark. The wells were washed again with water, then the membrane was
blocked with 1 ml polyvinylpyrrolidone (360,000 AMW, 1% solution in
H.sub.2O) for 1 hr at room temperature. Before adding the PNGaseF,
the wells were washed again with water. To release the glycans, 4
.mu.l of PNGaseF was added in 300 .mu.l of 50 mM Tris, pH 7.5 and
incubated overnight at 37.degree. C. Released glycans were pipetted
from the wells and purified through a graphitized carbon column.
Similar to protocols used for the purification of glycans after
performing the cleavage in solution, the purification of glycans
after their release using PVDF membranes was also performed in a
high-throughput format using using columns in 96-well plates. This
process was facilitated by the use of a TECAN robot.
Glycome Analysis Using Mass Spectrometry
[0394] Glycan analysis using methods known to the art were used and
applied to the total body fluid glycome analysis. Using the methods
provided above were also able to analyze more than 90 samples.
Optimized MALDI-MS methods which did not required additional
labeling and purification steps and also displayed great
reproducibility and sensitivity for the carbohydrate analysis was
used. As shown in FIG. 31, total serum glycome profiles typically
displayed between 25-30 neutral glycans as well as 25-30 acidic
glycans.
[0395] Using the look-up table described previously, almost all the
peaks in MALDI-MS serum profiles could be identified as glycans of
known composition. Many of the unidentified peaks are sodium
adducts. The composition and mass of each labeled peak are as
listed above in Table 18. However, a few peaks in the acidic glycan
spectrum correspond to more than one composition. This is more
common in the higher mass range since there are a larger number of
possible monosaccharide compositions.
Validation of Biomarker Structures
[0396] MALDI-MS analysis allows us to analyze the entire glycome
profile in a sample and compare the changes in the glycome
composition between samples in a rapid and efficient manner. Due to
the limitations in isomass characterization, in some instances,
other techniques known to the art can be used to further
characterize and validate the biomarkers determined from the total
profile found using MALDI-MS techniques. For example, liquid
chromatography-mass spectrometry (LC-MS) and capillary
electrophoresis-laser induced fluorescence (CE-LIF), are used in
combination with a panel of exoglycosidases in order to obtain
further linkage characterization of the carbohydrates (FIG. 32).
After a specific pattern is established based on MALDI-MS results
and the possible species are determined, matched samples displaying
the differences in patterns are analyzed by these techniques in
order to come up with defined structures of the biomarkers of
interest. LC-MS/MS is also used to obtain linkage information based
on the fragmentation patterns.
Other Body Fluids
[0397] Similar to the serum glycome analysis, the entire glycome
from other body fluids such as saliva and urine have been studied
(FIG. 33). For these cases, similar protocols employed for serum
were used. In some instances, additional fractionations were also
employed if a fraction of the glycome or glycoproteome was to be
studied. The method showed to be equally, reproducible and
sensitive for these other body fluids.
Glycome Analysis of Cell Surface Glycoproteins
[0398] The methods are also applied to the glycoprofiling of cell
surfaces. All cell surface glycoproteins are cleaved using methods
know to the art. Briefly, to harvest glycans using protease
extraction, cells are washed 3.times. with PBS and incubated for
20-45 minutes with trypsin/EDTA (GibcoBRL) at 37.degree. C. for
protease extraction. The samples are centrifuged for 10 minutes at
3000.times.g to pellet the cells, and the supernatant containing
glycopeptides is collected and processed using methods described
herein.
Glycomic Pattern Analysis
[0399] The emerging field of clinical proteomics has set new
avenues for the identification of potential cancer-related
biomarkers. In particular, the recent introduction of proteomic
pattern diagnostics[Petricoin III, 2002;Wulfkuhle, 2003; Conrads,
2003] provides a promising platform for the high-throughput
discovery of new and important biomarkers. Since the alterations to
the normal function of the glycosylation machinery have been
increasingly recognized as a consistent indication of malignant
transformations and tumorigenesis [Orntoft, 1999; Burchell, 2001;
Brockhausen, 1999;Dennis, 1999] the final glycoproteins
(specifically their carbohydrate moieties) can serve as sensitive
and reliable biochemical markers to numerous diseases including
cancer.
[0400] Some of the basic concepts from proteomic pattern
diagnostics have been adapted and applied to total glycomic pattern
analysis where the total profile of carbohydrates from body fluids
or tissues can be examined in a rapid format. This approach
provides an efficient overview of the total changes in carbohydrate
composition of a tissue or body fluid as a result of pathological
alterations and should be very reliable in sensing susceptible
physiological changes to the body's natural homeostasis. This
method not only serves as a fast diagnostic/prognostic tool but
should also help to understand the function of specific
carbohydrate modifications in some diseases. This method also
provides a reliable system to efficiently monitor the effects of
therapeutics.
[0401] The optimization of the MALDI-MS analysis allows reliable
reproducibility that enables the fast evaluation of alterations to
the glycomic patterns and their subsequent association to
pathological/physiological changes to a sample donor. The optimized
detection limits for this method (low femtomol) allows the
detection of low abundance species associated to diseases. Every
signal in the pattern is rapidly correlated to the glycan identity
and can be further validated using a panel of glycosydases and
other techniques. This prevents the erroneous identification as it
has sometimes been the case in the field of proteomic pattern
diagnostics. The pattern alterations can be easily determined
manually or more efficiently with the aid of bioinformatics tools
(described below). In some cases the decreasing levels of
circulating glycoproteins in serum are easily matched to the
analyzed glycans. As shown in FIG. 34, the glycome profile from
serum with low IgG levels, reflects the specific decrease in the
respective IgG glycans with molecular weights of 1463, 1626, 1666,
1788, 1829, 2102, and 1844. These glycans have been previously
shown to be attached to IgG molecules in serum [Butler, 2003].
[0402] By applying the "glycomic pattern diagnostics" platform to
different body fluids from patients with well-defined demographics,
specific alterations in the glycomic pattern that can be correlated
to the pathological state of the donor can be determined. For
example, glycomic patterns have been associated to prostate cancer
by studying the serum from prostate cancer patients (FIG. 35).
Glycomic patterns from the saliva of patients with viral infections
have also been established. Since every signal inside the pattern
corresponds to specific glycans, the alteration of these patterns
are easily determined and correlated with the expression levels of
the carbohydrates, such as with the methods provided herein. The
specific alterations in these glycan patterns are associated with a
disease state. Therefore, the methods provided serve as a reliable
platform for diagnosis, prognosis and monitoring the effects of
therapeutics.
Computational Pattern Analysis of Glycoprofile
[0403] The following is an example of a computational approach for
identifying glycan-based biomarkers for specific diseases using
data from glycoprofiling. The different steps of the process are
illustrated in the FIG. 36.
[0404] Using prostate cancer as an example, the goal is to identify
glycan-based markers for individuals with prostate cancer. In this
example, there are three possible categories of
individuals--individuals with prostate cancer, benign prostatic
hyperplasia (BPH) and individuals that are normal (healthy,
non-diseased prostate).
[0405] Glycoprofiling data such as mass spectras are generated from
samples from patients belonging to the different categories.
Features are extracted from the glycoprofiling spectras. These
features can be the presence or absence of one or more glycans in
the profile, the relative amount of different glycans in the
profile, combinations of different glycans found in the profile and
other glycan-related properties. These glycans are identified in
the glycoprofile spectra and can be corroborated with other
methods, for instance, by using a Glycan database
(http://www.functionalglycomics.org/glycomics/molecule/jsp/carbohydrate/c-
arbMoleculeHo me.jsp) and/or associated glycomics-based
bioinformatics tools.
[0406] The appropriate patient population is selected for the study
(based on their history in a patient database), such that the
subjects chosen in the different categories of prostate cancer, BPH
and normal have the same distribution when it comes to other
properties such as age, ethnicity, behavioral factors etc. This
ensures that the variation in the glycan profiles can be attributed
to the disease condition rather than other factors. The glycan
related features extracted for this population via the previous
step is run through a dataset generator to create the datasets
needed for pattern analysis [see Weiss, S. & Indurkhya, N.
Predictive data mining--A practical guide, (Morgan Kaufmann, San
Francisco, 1998)].
[0407] Different types of pattern analysis are performed to
identify the patterns in this dataset [Weiss and Indurkhya, 1998].
Three examples of patterns, rules or relationships that can be
identified are as follows: [0408] Linear Discriminant The pattern
identified is in the form of weights (w.sub.11, w.sub.12, etc.) for
the different glycan related features (G.sub.1, G.sub.2, etc.) as
they are related to property or class of interest (ProstateCancer,
BPH or Normal). w.sub.11G.sub.1+w.sub.12G.sub.12+ . . .
+w.sub.1mG.sub.m+w.sub.1=ProstateCancer
w.sub.21G.sub.1+w.sub.22G.sub.2+ . . . +w.sub.2mG.sub.m+w.sub.2=BPH
[0409] Neural Network: The neural network identifies non linear
relationships or patterns between the different features and the
property or class of interest.
net.sub.j=.SIGMA.W.sub.ij*f.sub.i+C.sub.j d.sub.j=1/(1+e.sup.netj),
where d.sub.j can be Prostate Cancer, BPH or Normal [0410] Decision
Rules: The pattern identified is in the form of IF-THEN rules, for
example [0411] (IFG.sub.11 is present and G.sub.7 is not present)
or (IF G.sub.8 is present and G.sub.9 is present) THEN
Class=Prostate Cancer [0412] (IFG.sub.1 is present and G.sub.2 is
present and G.sub.3 is not present) THEN Class=BPH [0413] Otherwise
Class=Normal
[0414] Once a pattern is identified using the decision set rules
above, the patterns, rules or relationships are validated. The
validation can be made based on variety of statistical methods that
are used in biomarker validation as well as scientific methods to
verify that the glycans found in the patterns do accurately reflect
the disease state. If the patterns cannot be validated, the process
described above can be repeated to look for other glycan-based
patterns in the glycoprofiles.
Use of Human Glycome for the Profiling of Populations:
Population-Tailored Treatments
[0415] It is well documented that different people react
differently to certain drugs. In many instances this might be a
result of drug interference with other inherent molecular
components. Also, the down-regulation of enzymes may prevent the
metabolism of some drugs or their by-products. The recent emphasis
in the development of new carbohydrate-based therapeutics will face
major challenges (in comparison to protein-based drugs) due to less
currently available glycomic information as well as less
understanding of the field.
[0416] More information of all human molecular components will
significantly facilitate the design and prescription of medications
to specific populations. The efficient analysis of the entire
glycome from body fluids not only serves as a reliable
diagnosis/prognosis platform but should become very valuable for
the profiling of populations. The generation of a human glycome
databank from different ethnic groups, gender, ages, diseases, etc.
will become of enormous value for current and future development
and applications of drugs that might interfere with carbohydrate
functions. For example, the overexpression of specific
carbohydrates in a specific population will aid in the design or
prescription of therapeutic antibodies (lectins, or other
molecules) that might interfere with these molecules. This
information will also aid in prospective studies for the selection
of dosing, activity monitoring and efficacy endpoints.
References for Example 4
[0417] 1. Petricoin III, E. F. et al. Use of proteomic patterns in
serum to identify ovarian cancer. Lancet 359, 572-577 (2002).
[0418] 2. Wulfkuhle, J. D., Liotta, L. A. & Petricoin III, E.
F. Proteomic applications for the early detection of cancer. Nature
Rev. Cancer 3, 267-275 (2003). [0419] 3. Conrads, T. P., Zhou, M.,
Petricoin III, E. F., Liotta, L. A. & Veenstra, T. D. Cancer
diagnosis using proteomic patterns. Expert. Rev. Mol. Diagn. 3,
411-420 (2003). [0420] 4. Orntoft, T. F. & Vestergaard, E.M.
Clinical aspects of altered glycosylation of glycoproteins in
cancer. Electrophoresis 20, 362-371 (1999). [0421] 5. Burchell, J.
M., Mungul, A., & Taylor-Papadimitriou, J. O-linked
glycosylation in the mammary gland: changes that occur during
malignancy. J Mam. Gland Biol. Neoplasia 6, 355-364 (2001). [0422]
6. Brockhausen, I. Pathways of O-glycan biosynthesis in cancer
cells. Biochim. Byophis. Acta 1473, 67-95 (1999). [0423] 7. Dennis,
J. W., Granovsky, M. & Waren, C. E. Glycoprotein glycosylation
and cancer progression. Biochim. Byophis. Acta 1473, 21-34 (1999).
[0424] 8. Pierce, M., Buckhaults, P., Chen, L. & Fregien, N.
Regulation of N-acetylglucosaminyltransferase V and Asn-linked
oligosaccharide beta(1,6) branching by a growth factor signaling
pathway and effects on cell adhesion and metastatic potential.
Glycoconj. J. 14, 623-630 (1997). [0425] 9. Murata, K. et al.
Expression of N-acetylglucosaminyltransferase V in colorectal
cancer correlates with metastasis and poor prognosis. Clin. Cancer
Res. 5, 1772-1777 (2000). [0426] 10. Yanagi, M., Aoyagi, Y., Suda,
T., Mita, Y. & Asakura, H. N-Acetylglucosaminyltransferase V as
a possible aid for the evaluation of tumor invasiveness in patients
with hepatocellular carcinoma. J. Gastroenterol. Hepatol. 16,
1282-1289 (2001). [0427] 11. Ihara, S. et al. Prometastatic effect
of N-acetylglucosaminyltransferase V is due to modification and
stabilization of active matriptase by adding beta 1-6 GlcNAc
branching. J. Biol. Chem. 277, 16960-16967 (2002). [0428] 12.
Yousefi, S. et al. Increased UDP-GlcNAc:Gal beta 1-3GaLNAc-R
(GlcNAc to GaLNAc) beta-1,6-N-acetylglucosaminyltransferase
activity in metastatic murine tumor cell lines. Control of
polylactosamine synthesis. J. Biol. Chem. 266, 1772-17782 (1991).
[0429] 13. Shimodaira, K. et al. Carcinoma-associated expression of
core 2 beta-1,6-N-acetylglucosaminyltransferase gene in human
colorectal cancer: role of O-glycans in tumor progression. Cancer
Res. 57, 5201-5206 (1997). [0430] 14. Machida, E., Nakayama, J.,
Amano, J. & Fukuda, M. Clinicopathological significance of core
2 betal,6-N-acetylglucosaminyltransferase messenger RNA expressed
in the pulmonary adenocarcinoma determined by in situ
hybridization. Cancer Res. 61, 2226-2231 (2001). [0431] 15. Vander,
A. J., Sherman, J. H. & Luciano, D. S. Human physiology: the
mechanisms of body function, Edn. 8th. (McGraw-Hill, Boston, Mass.;
2001). [0432] 16. Rohovec, J., Maschmeyer, T., Aime, S. &
Peters, J. A. The structure of the sugar residue in glycated human
serum albumin and its molecular recognition by phenylboronate.
Chemistry 9, 2193-2199 (2003). [0433] 17. Bihoreau, N., Ramon, C.,
Lazard, M. & Schmitter, J. M. Combination of capillary
electrophoresis and matrix-assisted laser desorption ionization
mass spectrometry for glycosylation analysis of a human monoclonal
anti-Rhesus(D) antibody. J Chromatogr B Biomed Sci Appl 697,
123-133 (1997). [0434] 18. Watt, G. M. et al. Site-specific
glycosylation of an aglycosylated human IgG1-Fc antibody protein
generates neoglycoproteins with enhanced function. Chem Biol 10,
807-814 (2003). [0435] 19. Papac, D. I., Briggs, J. B., Chin, E. T.
& Jones, A. J. A high-throughput microscale method to release
N-linked oligosaccharides from glycoproteins for matrix-assisted
laser desorption/ionization time-of-flight mass spectrometric
analysis. Glycobiology 8, 445-454 (1998). [0436] 20. Butler, M. et
al. Detailed glycan analysis of serum glycoproteins of patients
with congenital disorders of glycosylation indicates the specific
defective glycan processing step and provides an insight into
pathogenesis. Glycobiology 13, 601-622 (2003).
[0437] Each of the foregoing patents, patent applications and
references that are recited in this application are herein
incorporated in their entirety by reference. Having described the
presently preferred embodiments, and in accordance with the present
invention, it is believed that other modifications, variations and
changes will be suggested to those skilled in the art in view of
the teachings set forth herein. It is, therefore, to be understood
that all such variations, modifications, and changes are believed
to fall within the scope of the present invention as defined by the
appended claims.
* * * * *
References