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breast, ovarian, lung or pancreatic cancer. British Journal of Cancer 108 (10):
2045–2055.
92 Matsushita, T., Takada, W., Igarashi, K. etal. (2014). A straightforward protocol for
the preparation of high performance microarray displaying synthetic MUC1
glycopeptides. Biochimica et Biophysica Acta (BBA), General Subjects 1840 (3):
1105–1116.
93 Peng, W., Nycholat, C.M., and Razi, N. (2013). Glycan microarray screening assay
for glycosyltransferase specificities. Methods in Molecular Biology 1022: 1–14.
94 Ban, L., Pettit, N., Li, L. etal. (2012). Discovery of glycosyltransferases using
carbohydrate arrays and mass spectrometry. Nature Chemical Biology 8 (9):
769–773.
95 Muthana, S.M. (2020). Glycan microarray: toward drug discovery and
development. In: Carbohydrates in Drug Discovery and Development (ed.
V.K. Tiwari), 267–282. Elsevier.
96 Narimatsu, Y., Büll, C., Chen, Y.‐H. etal. (2021). Genetic glycoengineering in
mammalian cells. Journal of Biological Chemistry 296: 100448.
97 Chen, Y.‐H., Narimatsu, Y., Clausen, T.M. etal. (2018). The GAGOme: a cell‐based
library of displayed glycosaminoglycans. Nature Methods 15 (11): 881–888.
98 Narimatsu, Y., Joshi, H.J., Yang, Z. etal. (2018). A validated gRNA library for
CRISPR/Cas9 targeting of the human glycosyltransferase genome. Glycobiology 28
(5): 295–305.
99 Narimatsu, Y., Joshi, H.J., Nason, R. etal. (2019). An atlas of human glycosylation
pathways enables display of the human glycome by gene engineered cells.
Molecular Cell 75 (2): 394–407.e5.
100 Lonowski, L.A., Narimatsu, Y., Riaz, A. etal. (2017). Genome editing using FACS
enrichment of nuclease‐expressing cells and indel detection by amplicon analysis.
Nature Protocols 12 (3): 581–603.
101 Yang, Z., Wang, S., Halim, A. etal. (2015). Engineered CHO cells for production of
diverse, homogeneous glycoproteins. Nature Biotechnology 33 (8): 842–844.
102 Schulz, M.A., Tian, W., Mao, Y. etal. (2018). Glycoengineering design options for
IgG1in CHO cells using precise gene editing. Glycobiology 28 (7): 542–549.
103 Tian, W., Ye, Z., Wang, S. etal. (2019). The glycosylation design space for
recombinant lysosomal replacement enzymes produced in CHO cells. Nature
Communications 10 (1): 1785.
104 Čaval, T., Tian, W., Yang, Z. etal. (2018). Direct quality control of glycoengineered
erythropoietin variants. Nature Communications 9 (1): 3342.
105 Stanley, P. (2016). What have we learned from glycosyltransferase knockouts in
mice? Journal of Molecular Biology 428 (16): 3166–3182.
106 Orr, S.L., Le, D., Long, J.M. etal. (2012). A phenotype survey of 36mutant mouse
strains with gene‐targeted defects in glycosyltransferases or glycan‐binding
proteins. Glycobiology 23 (3): 363–380.
107 Takahashi, M., Yokoe, S., Asahi, M. etal. (2008). N‐glycan of ErbB family plays a
crucial role in dimer formation and tumor promotion. Biochimica et Biophysica
Acta (BBA), General Subjects 1780 (3): 520–524.
191
192
108 Miller, J.C., Holmes, M.C., Wang, J. etal. (2007). An improved zinc‐finger
nuclease architecture for highly specific genome editing. Nature Biotechnology 25
(7): 778–785.
109 Miller, J.C., Tan, S., Qiao, G. etal. (2011). A TALE nuclease architecture for
efficient genome editing. Nature Biotechnology 29 (2): 143–148.
110 Cong, L., Ran, F.A., Cox, D. etal. (2013). Multiplex genome engineering using
CRISPR/Cas systems. Science 339 (6121): 819–823.
111 Adli, M. (2018). The CRISPR tool kit for genome editing and beyond. Nature
Communications 9 (1): 1911.
112 Zhu, Y., Groth, T., Kelkar, A. etal. (2020). A GlycoGene CRISPR‐Cas9lentiviral
library to study lectin binding and human glycan biosynthesis pathways.
Glycobiology 31 (3): 173–180.
113 KJlC, K., Hefzi, H., Xiong, K. etal. (2020). Awakening dormant
glycosyltransferases in CHO cells with CRISPRa. Biotechnology and Bioengineering
117 (2): 593–598.
114 Schjoldager, K.T.‐B.G., Vakhrushev, S.Y., Kong, Y. etal. (2012). Probing isoform‐
specific functions of polypeptide GalNAc‐transferases using zinc finger nuclease
glycoengineered SimpleCells. Proceedings of the National Academy of Sciences of
the United States of America 109 (25): 9893–9898.
115 Hintze, J., Ye, Z., Narimatsu, Y. etal. (2018). Probing the contribution of
individual polypeptide GalNAc‐transferase isoforms to the O‐glycoproteome by
inducible expression in isogenic cell lines. Journal of Biological Chemistry 293
(49): 19064–19077.
116 Lavrsen, K., Dabelsteen, S., Vakhrushev, S.Y. etal. (2018). De novo expression of
human polypeptide N‐acetylgalactosaminyltransferase 6 (GalNAc‐T6) in colon
adenocarcinoma inhibits the differentiation of colonic epithelium. Journal of
Biological Chemistry 293 (4): 1298–1314.
117 Steentoft, C., Vakhrushev, S.Y., Joshi, H.J. etal. (2013). Precision mapping of the
human O‐GalNAc glycoproteome through SimpleCell technology. The EMBO
Journal 32 (10): 1478–1488.
118 Steentoft, C., Vakhrushev, S.Y., Vester‐Christensen, M.B. etal. (2011). Mining the
O‐glycoproteome using zinc‐finger nuclease–glycoengineered SimpleCell lines.
Nature Methods 8 (11): 977–982.
119 Vester‐Christensen, M.B., Halim, A., Joshi, H.J. etal. (2013). Mining the
O‐mannose glycoproteome reveals cadherins as major O‐mannosylated
glycoproteins. Proceedings of the National Academy of Sciences of the United States
of America 110 (52): 21018–21023.
120 Büll, C., Joshi, H.J., Clausen, H., and Narimatsu, Y. (2020). Cell‐based glycan
arrays–a practical guide to dissect the human glycome. STAR Protocols 1
(1): 100017.
121 Joeh, E., O’Leary, T., Li, W. etal. (2020). Mapping glycan‐mediated
galectin‐3interactions by live cell proximity labeling. Proceedings of the National
Academy of Sciences of the United States of America 117 (44): 27329–27338.
122 Wang, H. and Mooney, D.J. (2020). Metabolic glycan labelling for cancer‐targeted
therapy. Nature Chemistry 12 (12): 1102–1114.
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
123 Schumann, B., Malaker, S.A., Wisnovsky, S.P. etal. (2020). Bump‐and‐hole
engineering identifies specific substrates of glycosyltransferases in living cells.
Molecular Cell 78 (5): 824–34.e15.
124 Agatemor, C., Buettner, M.J., Ariss, R. etal. (2019). Exploiting metabolic
glycoengineering to advance healthcare. Nature Reviews Chemistry 3 (10):
605–620.
125 Debets, M.F., Tastan, O.Y., Wisnovsky, S.P. etal. (2020). Metabolic precision
labeling enables selective probing of O‐linked N‐acetylgalactosamine
glycosylation. Proceedings of the National Academy of Sciences of the United States
of America 117 (41): 25293–25301.
126 Cioce, A., Malaker, S.A., and Schumann, B. (2021). Generating orthogonal
glycosyltransferase and nucleotide sugar pairs as next‐generation glycobiology
tools. Current Opinion in Chemical Biology 60: 66–78.
127 Prescher, J.A. and Bertozzi, C.R. (2006). Chemical technologies for probing
glycans. Cell 126 (5): 851–854.
128 Thirumurugan, P., Matosiuk, D., and Jozwiak, K. (2013). Click chemistry for drug
development and diverse chemical–biology applications. Chemical Reviews 113
(7): 4905–4979.
129 Laughlin, S.T., Baskin, J.M., Amacher, S.L., and Bertozzi, C.R. (2008). In vivo
imaging of membrane‐associated glycans in developing zebrafish. Science 320
(5876): 664–667.
130 Xie, R., Dong, L., Huang, R. etal. (2014). Targeted imaging and proteomic analysis
of tumor‐associated glycans in living animals. Angewandte Chemie International
Edition 53 (51): 14082–14086.
131 Hong, S., Yu, C., Wang, P. etal. (2021). Glycoengineering of NK Cells with glycan
ligands of CD22 and selectins for B‐cell lymphoma therapy. Angewandte Chemie
International Edition 60 (7): 3603–3610.
132 Ge, C. and Stanley, P. (2008). The O‐fucose glycan in the ligand‐binding domain of
Notch1 regulates embryogenesis and T cell development. Proceedings of the
National Academy of Sciences of the United States of America 105 (5): 1539–1544.
133 Sung, Y.H., Baek, I.‐J., Seong, J.K. etal. (2012). Mouse genetics: catalogue and
scissors. BMB Reports 45 (12): 686–692.
134 Ioffe, E. and Stanley, P. (1994). Mice lacking N‐acetylglucosaminyltransferase I
activity die at mid‐gestation, revealing an essential role for complex or hybrid
N‐linked carbohydrates. Proceedings of the National Academy of Sciences of the
United States of America 91 (2): 728–732.
135 Metzler, M., Gertz, A., Sarkar, M. etal. (1994). Complex asparagine‐linked
oligosaccharides are required for morphogenic events during post‐implantation
development. The EMBO Journal 13 (9): 2056–2065.
136 Ye, Z. and Marth, J.D. (2004). N‐glycan branching requirement in neuronal and
postnatal viability. Glycobiology 14 (6): 547–558.
137 Shi, S., Williams, S.A., Seppo, A. etal. (2004). Inactivation of the Mgat1 gene in
oocytes impairs oogenesis, but embryos lacking complex and hybrid N‐glycans
develop and implant. Molecular and Cellular Biology 24 (22): 9920–9929.
193
194
138 Batista, F., Lu, L., Williams, S.A., and Stanley, P. (2012). Complex N‐glycans are
essential, but core 1 and 2mucin O‐glycans, O‐fucose glycans, and NOTCH1 are
dispensable, for mammalian spermatogenesis. Biology of Reproduction 86 (6): 179.
139 Zhou, R.W., Mkhikian, H., Grigorian, A. etal. (2014). N‐glycosylation
bidirectionally extends the boundaries of thymocyte positive selection by
2+
decoupling Lck from Ca
signaling. Nature Immunology 15 (11): 1038–1045.
140 Fonseca, K.L., Maceiras, A.R., Matos, R. etal. (2020). Deficiency in the
glycosyltransferase Gcnt1increases susceptibility to tuberculosis through a
mechanism involving neutrophils. Mucosal Immunology 13 (5): 836–848.
141 Engle, D.D., Tiriac, H., Rivera, K.D. etal. (2019). The glycan CA19‐9 promotes
pancreatitis and pancreatic cancer in mice. Science 364 (6446): 1156–1162.
142 Zavareh, R.B., Sukhai, M.A., Hurren, R. etal. (2012). Suppression of cancer
progression by MGAT1 shRNA knockdown. PLoS One 7 (9): e43721.
143 Song, Y., Aglipay, J.A., Bernstein, J.D. etal. (2010). The bisecting GlcNAc on
N‐glycans inhibits growth factor signaling and retards mammary tumor
progression. Cancer Research 70 (8): 3361–3371.
144 Silva, M.C., Fernandes, Â., Oliveira, M. etal. (2020). Glycans as immune
checkpoints: removal of branched N‐glycans enhances immune recognition
preventing cancer progression. Cancer Immunology Research 8 (11): 1407–1425.
145 Liu, F., Fu, J., Bergstrom, K. etal. (2020). Core 1–derived mucin‐type
O‐glycosylation protects against spontaneous gastritis and gastric cancer.
The Journal of Experimental Medicine 217 (1): e20182325.
146 Granovsky, M., Fata, J., Pawling, J. etal. (2000). Suppression of tumor growth and
metastasis in Mgat5‐deficient mice. Nature Medicine 6 (3): 306–312.
147 Hedlund, M., Ng, E., Varki, A., and Varki, N.M. (2008). α2‐6–linked sialic acids on
N‐glycans modulate carcinoma differentiation invivo. Cancer Research 68 (2):
388–394.
148 Magalhães, A., Gomes, J., Ismail, M.N. etal. (2009). Fut2‐null mice display an
altered glycosylation profile and impaired BabA‐mediated Helicobacter pylori
adhesion to gastric mucosa. Glycobiology 19 (12): 1525–1536.
149 Yoshida, G.J. (2020). Applications of patient‐derived tumor xenograft models and
tumor organoids. Journal of Hematology & Oncology 13 (1): 4.
150 Byrne, A.T., Alférez, D.G., Amant, F. etal. (2017). Interrogating open issues in
cancer precision medicine with patient‐derived xenografts. Nature Reviews Cancer
17 (4): 254.
151 Huang, L., Bockorny, B., Paul, I. etal. (2020). PDX‐derived organoids model
invivo drug response and secrete biomarkers. JCI Insight 5 (21): e135544.
152 Sinha, A., Hussain, A., Ignatchenko, V. etal. (2019). N‐Glycoproteomics of
patient‐derived xenografts: a strategy to discover tumor‐associated proteins in
high‐grade serous ovarian cancer. Cell Systems 8 (4): 345–51.e4.
153 Selman, M.H., Hoffmann, M., Zauner, G. etal. (2012). MALDI‐TOF‐MS analysis
of sialylated glycans and glycopeptides using 4‐chloro‐α‐cyanocinnamic acid
matrix. Proteomics 12 (9): 1337–1348.
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
154 Pralow, A., Cajic, S., Alagesan, K. etal. (2020). State‐of‐the‐Art Glycomics
Technologies in Glycobiotechnology, 1–33. Berlin, Heidelberg: Springer Berlin
Heidelberg.
155 Wuhrer, M. (2013). Glycomics using mass spectrometry. Glycoconjugate Journal 30
(1): 11–22.
156 Kotsias, M., Kozak, R.P., Gardner, R.A. etal. (2019). Improved and semi‐
automated reductive β‐elimination workflow for higher throughput protein
O‐glycosylation analysis. PLoS One 14 (1): e0210759.
157 Ruhaak, L., Zauner, G., Huhn, C. etal. (2010). Glycan labeling strategies and their
use in identification and quantification. Analytical and Bioanalytical Chemistry
397 (8): 3457–3481.
158 Wuhrer, M., Koeleman, C.A., Hokke, C.H., and Deelder, A.M. (2006). Mass
spectrometry of proton adducts of fucosylated N‐glycans: fucose transfer between
antennae gives rise to misleading fragments. Rapid Communications in Mass
Spectrometry: An International Journal Devoted to the Rapid Dissemination of
Up‐to‐the‐Minute Research in Mass Spectrometry 20 (11): 1747–1754.
159 de Haan, N., Reiding, K.R., Haberger, M. etal. (2015). Linkage‐specific sialic acid
derivatization for MALDI‐TOF‐MS profiling of IgG glycopeptides. Analytical
Chemistry 87 (16): 8284–8291.
160 Lageveen‐Kammeijer, G.S., de Haan, N., Mohaupt, P. etal. (2019). Highly sensitive
CE‐ESI‐MS analysis of N‐glycans from complex biological samples. Nature
Communications 10 (1): 1–8.
161 Kalay, H., Ambrosini, M., van Berkel, P.H. etal. (2012). Online nanoliquid
chromatography–mass spectrometry and nanofluorescence detection for high‐
resolution quantitative N‐glycan analysis. Analytical Biochemistry 423 (1):
153–162.
162 Hua, S., Nwosu, C.C., Strum, J.S. etal. (2012). Site‐specific protein glycosylation
analysis with glycan isomer differentiation. Analytical and Bioanalytical
Chemistry 403 (5): 1291–1302.
163 Jensen, P.H., Karlsson, N.G., Kolarich, D., and Packer, N.H. (2012). Structural
analysis of N‐ and O‐glycans released from glycoproteins. Nature Protocols 7 (7):
1299–1310.
164 Lu, G., Crihfield, C.L., Gattu, S. etal. (2018). Capillary electrophoresis separations
of glycans. Chemical Reviews 118 (17): 7867–7885.
165 Selman, M.H.J., Hemayatkar, M., Deelder, A.M., and Wuhrer, M. (2011). Cotton
HILIC SPE microtips for microscale purification and enrichment of glycans and
glycopeptides. Analytical Chemistry 83 (7): 2492–2499.
166 Jensen, P.H., Mysling, S., Højrup, P., and Jensen, O.N. (2013). Glycopeptide
Enrichment for MALDI‐TOF Mass Spectrometry Analysis by Hydrophilic Interaction
Liquid Chromatography Solid Phase Extraction (HILIC SPE). Mass Spectrometry of
Glycoproteins, 131–144. Springer.
167 Jin, C., Harvey, D.J., Struwe, W.B., and Karlsson, N.G. (2019). Separation of
isomeric O‐glycans by ion mobility and liquid chromatography–mass
spectrometry. Analytical Chemistry 91 (16): 10604–10613.
195
196
168 Pallister, E.G., Choo, M.S.F., Walsh, I. etal. (2020). Utility of ion‐mobility
spectrometry for deducing branching of multiply charged glycans and
glycopeptides in a high‐throughput positive ion LC‐FLR‐IMS‐MS workflow.
Analytical Chemistry 92 (23): 15323–15335.
169 Singhal, N., Kumar, M., Kanaujia, P.K., and Virdi, J.S. (2015). MALDI‐TOF mass
spectrometry: an emerging technology for microbial identification and diagnosis.
Frontiers in Microbiology 6: 791.
170 Nie, H., Li, Y., and Sun, X.‐L. (2012). Recent advances in sialic acid‐focused
glycomics. Journal of Proteomics 75 (11): 3098–3112.
171 Konermann, L., Ahadi, E., Rodriguez, A.D., and Vahidi, S. (2013). Unraveling the
mechanism of electrospray ionization. Analytical Chemistry 85 (1): 2–9.
172 Kolarich, D., Jensen, P.H., Altmann, F., and Packer, N.H. (2012). Determination of
site‐specific glycan heterogeneity on glycoproteins. Nature Protocols 7 (7):
1285–1298.
173 Zaia, J. (2010). Mass spectrometry and glycomics. Omics: A Journal of Integrative
Biology 14 (4): 401–418.
174 Kim, M.S., Zhong, J., and Pandey, A. (2016). Common errors in mass
spectrometry‐based analysis of post‐translational modifications. Proteomics 16 (5):
700–714.
175 An, H.J., Peavy, T.R., Hedrick, J.L., and Lebrilla, C.B. (2003). Determination of
N‐glycosylation sites and site heterogeneity in glycoproteins. Analytical Chemistry
75 (20): 5628–5637.
176 Swaney, D.L., Wenger, C.D., and Coon, J.J. (2010). Value of using multiple
proteases for large‐scale mass spectrometry‐based proteomics. Journal of Proteome
Research 9 (3): 1323–1329.
177 Giansanti, P., Tsiatsiani, L., Low, T.Y., and Heck, A.J. (2016). Six alternative
proteases for mass spectrometry–based proteomics beyond trypsin. Nature
Protocols 11 (5): 993–1006.
178 Sutton, C.W., Oneill, J.A., and Cottrell, J.S. (1994). Site‐specific characterization of
glycoprotein carbohydrates by exoglycosidase digestion and laser‐desorption mass
spectrometry. Analytical Biochemistry 218 (1): 34–46.
179 Zhu, R., Zacharias, L., Wooding, K.M. etal. (2017). Glycoprotein enrichment
analytical techniques: advantages and disadvantages. Methods in Enzymology 585:
397–429.
180 Matsuda, A., Kuno, A., Matsuzaki, H. etal. (2013). Glycoproteomics‐based cancer
marker discovery adopting dual enrichment with Wisteria floribunda agglutinin
for high specific glyco‐diagnosis of cholangiocarcinoma. Journal of Proteomics
85: 1–11.
181 Totten, S.M., Kullolli, M., and Pitteri, S.J. (2017). Multi‐lectin affinity
chromatography for separation, identification, and quantitation of intact protein
glycoforms in complex biological mixtures. In: Proteomics (ed. L. Comai, J.E. Katz,
and P. Mallick), 99–113. Springer.
182 Totten, S.M., Adusumilli, R., Kullolli, M. etal. (2018). Multi‐lectin affinity
chromatography and quantitative proteomic analysis reveal differential glycoform
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
levels between prostate cancer and benign prostatic hyperplasia sera. Scientific
Reports 8 (1): 6509.
183 Zeng, Z., Hincapie, M., Pitteri, S.J. etal. (2011). A proteomics platform combining
depletion, multi‐lectin affinity chromatography (M‐LAC), and isoelectric focusing
to study the breast cancer proteome. Analytical Chemistry 83 (12): 4845–4854.
184 Yang, Z., Harris, L.E., Palmer‐Toy, D.E., and Hancock, W.S. (2006). Multilectin
affinity chromatography for characterization of multiple glycoprotein biomarker
candidates in serum from breast cancer patients. Clinical Chemistry 52 (10):
1897–1905.
185 Na, K., Lee, E.Y., Lee, H.J. etal. (2009). Human plasma carboxylesterase 1, a novel
serologic biomarker candidate for hepatocellular carcinoma. Proteomics 9 (16):
3989–3999.
186 Palmisano, G., Lendal, S.E., and Larsen, M.R. (2011). Titanium dioxide
enrichment of sialic acid‐containing glycopeptides. Methods in Molecular Biology
753: 309–322.
187 Larsen, M.R., Jensen, S.S., Jakobsen, L.A., and Heegaard, N.H. (2007). Exploring
the sialiome using titanium dioxide chromatography and mass spectrometry.
Molecular and Cellular Proteomics 6 (10): 1778–1787.
188 Thaysen‐Andersen, M., Larsen, M.R., Packer, N.H., and Palmisano, G. (2013).
Structural analysis of glycoprotein sialylation–part I: pre‐LC‐MS analytical
strategies. RSC Advances 3 (45): 22683–22705.
189 Zhang, H., Li, X.‐j., Martin, D.B., and Aebersold, R. (2003). Identification and
quantification of N‐linked glycoproteins using hydrazide chemistry, stable isotope
labeling and mass spectrometry. Nature Biotechnology 21 (6): 660–666.
190 Wang, L., Aryal, U.K., Dai, Z. etal. (2012). Mapping N‐linked glycosylation sites in
the secretome and whole cells of Aspergillus niger using hydrazide chemistry and
mass spectrometry. Journal of Proteome Research 11 (1): 143–156.
191 Chen, R., Jiang, X., Sun, D. etal. (2009). Glycoproteomics analysis of human liver
tissue by combination of multiple enzyme digestion and hydrazide chemistry.
Journal of Proteome Research 8 (2): 651–661.
192 Yang, S., Chen, L., Chan, D.W. etal. (2017). Protein signatures of molecular
pathways in non‐small cell lung carcinoma (NSCLC): comparison of
glycoproteomics and global proteomics. Clinical Proteomics 14 (1): 1–15.
193 Chen, J., Xi, J., Tian, Y. etal. (2013). Identification, prioritization, and evaluation
of glycoproteins for aggressive prostate cancer using quantitative glycoproteomics
and antibody‐based assays on tissue specimens. Proteomics 13 (15): 2268–2277.
194 Tian, Y., Esteva, F.J., Song, J., and Zhang, H. (2012). Altered expression of
sialylated glycoproteins in breast cancer using hydrazide chemistry and mass
spectrometry. Molecular & Cellular Proteomics 11 (6): M111.011403.
195 Bones, J., Mittermayr, S., O’Donoghue, N. etal. (2010). Ultra performance liquid
chromatographic profiling of serum N‐glycans for fast and efficient identification
of cancer associated alterations in glycosylation. Analytical Chemistry 82 (24):
10208–10215.
197
198
196 Balmaña, M., Giménez, E., Puerta, A. etal. (2016). Increased α1‐3 fucosylation of
α‐1‐acid glycoprotein (AGP) in pancreatic cancer. Journal of Proteomics 132:
144–154.
197 Balog, C.I., Stavenhagen, K., Fung, W.L. etal. (2012). N‐glycosylation of colorectal
cancer tissues: a liquid chromatography and mass spectrometry‐based
investigation. Molecular and Cellular Proteomics 11 (9): 571–585.
198 Reiding, K.R., Bondt, A., Franc, V., and Heck, A.J.R. (2018). The benefits of hybrid
fragmentation methods for glycoproteomics. TrAC, Trends in Analytical Chemistry
108: 260–268.
199 Riley, N.M., Malaker, S.A., Driessen, M.D., and Bertozzi, C.R. (2020). Optimal
dissociation methods differ for N‐ and O‐glycopeptides. Journal of Proteome
Research 19 (8): 3286–3301.
200 Wuhrer, M., Catalina, M.I., Deelder, A.M., and Hokke, C.H. (2007).
Glycoproteomics based on tandem mass spectrometry of glycopeptides. Journal of
Chromatography B 849 (1, 2): 115–128.
201 Cao, L., Tolić, N., Qu, Y. etal. (2014). Characterization of intact N‐and O‐linked
glycopeptides using higher energy collisional dissociation. Analytical Biochemistry
452: 96–102.
202 Stavenhagen, K., Hinneburg, H., Kolarich, D., and Wuhrer, M. (2017). Site‐specific
N‐ and O‐glycopeptide analysis using an integrated C18‐PGC‐LC‐ESI‐QTOF‐MS/
MS approach. In: High‐Throughput Glycomics and Glycoproteomics: Methods and
Protocols (ed. G. Lauc and M. Wuhrer), 109–119. NewYork, NY, Springer
NewYork.
203 Syka, J.E., Coon, J.J., Schroeder, M.J. etal. (2004). Peptide and protein sequence
analysis by electron transfer dissociation mass spectrometry. Proceedings of the
National Academy of Sciences of the United States of America 101 (26): 9528–9533.
204 Riley, N.M. and Coon, J.J. (2018). The role of electron transfer dissociation in
modern proteomics. Analytical Chemistry 90 (1): 40–64.
205 Wu, S.‐W., Pu, T.‐H., Viner, R., and Khoo, K.‐H. (2014). Novel LC‐MS2 product
dependent parallel data acquisition function and data analysis workflow for
sequencing and identification of intact glycopeptides. Analytical Chemistry 86
(11): 5478–5486.
206 Rodrigues, J.G., Duarte, H.O., Gomes, C. etal. (2021). Terminal α2, 6‐sialylation of
epidermal growth factor receptor modulates antibody therapy response of
colorectal cancer cells. Cellular Oncology 1–16.
207 Pirro, M., Rombouts, Y., Stella, A. etal. (2020). Characterization of macrophage
galactose‐type lectin (MGL) ligands in colorectal cancer cell lines. Biochimica et
Biophysica Acta (BBA), General Subjects 44 (4): 835–850.
208 Pirro, M., Schoof, E., van Vliet, S.J. etal. (2018). Glycoproteomic analysis of
MGL‐binding proteins on acute T‐cell leukemia cells. Journal of Proteome
Research 18 (3): 1125–1132.
209 Rojas‐Macias, M.A., Mariethoz, J., Andersson, P. etal. (2019). Towards a
standardized bioinformatics infrastructure for N‐ and O‐glycomics. Nature
Communications 10 (1): 3275.
Данная книга находится в списке для перевода на русский язык сайта https://meduniver.com/
210 Apte, A. and Meitei, N.S. (2010). Bioinformatics in glycomics: glycan
characterization with mass spectrometric data using SimGlycan™. In: Functional
Glycomics (ed. J. Li), 269–281. Springer.
211 Ye, Z., Mao, Y., Clausen, H., and Vakhrushev, S.Y. (2019). Glyco‐DIA: a method for
quantitative O‐glycoproteomics with in silico‐boosted glycopeptide libraries.
Nature Methods 16 (9): 902–910.
212 Mayampurath, A.M., Wu, Y., Segu, Z.M. etal. (2011). Improving confidence in
detection and characterization of protein N‐glycosylation sites and
microheterogeneity. Rapid Communications in Mass Spectrometry 25 (14):
2007–2019.
213 Mayampurath, A., Yu, C.‐Y., Song, E. etal. (2014). Computational framework for
identification of intact glycopeptides in complex samples. Analytical Chemistry 86
(1): 453–463.
214 Bern, M., Kil, Y.J., and Becker, C. (2012). Byonic: advanced peptide and protein
identification software. Current Protocols in Bioinformatics 40 (1):
13.20.1–13.20.14.
215 Jansen, B.C., Reiding, K.R., Bondt, A. etal. (2015). MassyTools: a high‐throughput
targeted data processing tool for relative quantitation and quality control
developed for glycomic and glycoproteomic MALDI‐MS. Journal of Proteome
Research 14 (12): 5088–5098.
216 Woodin, C.L., Hua, D., Maxon, M. etal. (2012). GlycoPep grader: a web‐based
utility for assigning the composition of N‐linked glycopeptides. Analytical
Chemistry 84 (11): 4821–4829.
217 Serang, O., Froehlich, J.W., Muntel, J. etal. (2013). SweetSEQer, simple de Novo
filtering and annotation of glycoconjugate mass spectra. Molecular and Cellular
Proteomics 12 (6): 1735–1740.
218 Cheng, K., Chen, R., Seebun, D. etal. (2014). Large‐scale characterization of intact
N‐glycopeptides using an automated glycoproteomic method. Journal of
Proteomics 110: 145–154.
219 Zhu, Z., Hua, D., Clark, D.F. etal. (2013). GlycoPep detector: a tool for assigning
mass spectrometry data of N‐linked glycopeptides on the basis of their electron
transfer dissociation spectra. Analytical Chemistry 85 (10): 5023–5032.
220 Liu, M., Zhang, Y., Chen, Y. etal. (2014). Efficient and accurate glycopeptide
identification pipeline for high‐throughput site‐specific N‐glycosylation analysis.
Journal of Proteome Research 13 (6): 3121–3129.
221 Lynn, K.‐S., Chen, C.‐C., Lih, T.M. etal. (2015). MAGIC: an automated N‐linked
glycoprotein identification tool using a Y1‐ion pattern matching algorithm and in
silico MS2 approach. Analytical Chemistry 87 (4): 2466–2473.
222 Strum, J.S., Nwosu, C.C., Hua, S. etal. (2013). Automated assignments of N‐ and
O‐site specific glycosylation with extensive glycan heterogeneity of glycoprotein
mixtures. Analytical Chemistry 85 (12): 5666–5675.
223 Wu, S.‐W., Liang, S.‐Y., Pu, T.‐H. etal. (2013). Sweet‐heart–an integrated suite of
enabling computational tools for automated MS2/MS3 sequencing and
identification of glycopeptides. Journal of Proteomics 84: 1–16.
199
200
224 Toghi Eshghi, S., Shah, P., Yang, W. etal. (2015). GPQuest: a spectral library
matching algorithm for site‐specific assignment of tandem mass spectra to intact
N‐glycopeptides. Analytical Chemistry 87 (10): 5181–5188.
225 Chandler, K.B., Pompach, P., Goldman, R., and Edwards, N. (2013). Exploring
site‐specific N‐glycosylation microheterogeneity of haptoglobin using
glycopeptide CID tandem mass spectra and glycan database search. Journal of
Proteome Research 12 (8): 3652–3666.
226 Liu, M.‐Q., Zeng, W.‐F., Fang, P. etal. (2017). pGlyco 2.0 enables precision
N‐glycoproteomics with comprehensive quality control and one‐step mass
spectrometry for intact glycopeptide identification. Nature Communications 8
(1): 438.
227 Lu, L., Riley, N.M., Shortreed, M.R. etal. (2020). O‐pair search with
metamorpheus for O‐glycopeptide characterization. Nature Methods 17 (11):
1133–1138.
228 Xiao, K. and Tian, Z. (2019). GPSeeker enables quantitative structural
N‐glycoproteomics for site‐ and structure‐specific characterization of differentially
expressed N‐glycosylation in hepatocellular carcinoma. Journal of Proteome
Research 18 (7): 2885–2895.
229 An, Z., Shu, Q., Lv, H. etal. (2018). N‐linked glycopeptide identification based on
open mass spectral library search. BioMed Research International 2018: 1564136.
230 Pioch, M., Hoffmann, M., Pralow, A. etal. (2018). glyXtoolMS: an open‐source
pipeline for semiautomated analysis of glycopeptide mass spectrometry data.
Analytical Chemistry 90 (20): 11908–11916.
231 Stadlmann, J., Taubenschmid, J., Wenzel, D. etal. (2017). Comparative
glycoproteomics of stem cells identifies new players in ricin toxicity. Nature 549
(7673): 538–542.
232 Liu, G., Cheng, K., Lo, C.Y. etal. (2017). A comprehensive, open‐source platform
for mass spectrometry‐based glycoproteomics data analysis. Molecular and
Cellular Proteomics 16 (11): 2032–2047.
233 Park, G.W., Kim, J.Y., Hwang, H. etal. (2016). Integrated glycoproteome analyzer
(I‐GPA) for automated identification and quantitation of site‐specific
N‐glycosylation. Scientific Reports 6 (1): 21175.
234 He, L., Xin, L., Shan, B. etal. (2014). GlycoMaster DB: software to assist the
automated identification of N‐linked glycopeptides by tandem mass spectrometry.
Journal of Proteome Research 13 (9): 3881–3895.
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