University of Oulu

Benedetti, E., Pučić-Baković, M., Keser, T., Wahl, A., Hassinen, A., Yang, J., Liu, L., Trbojević-Akmačić, I., Razdorov, G., Štambuk, J., Klarić, L., Ugrina, I., Selman, M., Wuhrer, M., Rudan, I., Polasek, O., Hayward, C., Grallert, H., Strauch, K., Peters, A., Meitinger, T., Gieger, C., Vilaj, M., Boons, G., Moremen, K., Ovchinnikova, T., Bovin, N., Kellokumpu, S., Theis, F., Lauc, G., Krumsiek, J. (2017) Network inference from glycoproteomics data reveals new reactions in the IgG glycosylation pathway. Nature Communications, 8 (1). doi:10.1038/s41467-017-01525-0

Network inference from glycoproteomics data reveals new reactions in the IgG glycosylation pathway

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Author: Benedetti, Elisa1; Pučić-Baković, Maja2; Keser, Toma3;
Organizations: 1Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health
2Genos Glycoscience Research Laboratory
3Faculty of Pharmacy and Biochemistry, University of Zagreb
4Institute of Epidemiology 2, Research Unit Molecular Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health
5Institute of Epidemiology 2, Helmholtz Zentrum München—German Research Center for Environmental Health
6Faculty of Biochemistry and Molecular Medicine, University of Oulu
7Complex Carbohydrate Research Center, University of Georgia
8Usher Institute of Population Health Sciences and Informatics, University of Edinburgh
9Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh
10Faculty of Science, University of Split
11Intellomics Ltd.
12Leiden University Medical Center
13University of Split School of Medicine
14Gen-info Ltd.
15German Center for Diabetes Research (DZD)
16Institute of Genetic Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health
17Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians Universität
18Institute of Human Genetics, Helmholtz Zentrum München—German Research Center for Environmental Health
19Department of Chemical Biology and Drug Discovery, Utrecht Institute for Pharmaceutical Sciences, and Bijvoet Center for Biomolecular Research, Utrecht University
20Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences
21Department of Mathematics, Technical University Munich
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.3 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe201801111226
Language: English
Published: Springer Nature, 2017
Publish Date: 2018-01-11
Description:

Abstract

Immunoglobulin G (IgG) is a major effector molecule of the human immune response, and aberrations in IgG glycosylation are linked to various diseases. However, the molecular mechanisms underlying protein glycosylation are still poorly understood. We present a data-driven approach to infer reactions in the IgG glycosylation pathway using large-scale mass-spectrometry measurements. Gaussian graphical models are used to construct association networks from four cohorts. We find that glycan pairs with high partial correlations represent enzymatic reactions in the known glycosylation pathway, and then predict new biochemical reactions using a rule-based approach. Validation is performed using data from a GWAS and results from three in vitro experiments. We show that one predicted reaction is enzymatically feasible and that one rejected reaction does not occur in vitro. Moreover, in contrast to previous knowledge, enzymes involved in our predictions colocalize in the Golgi of two cell lines, further confirming the in silico predictions.

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Series: Nature communications
ISSN: 2041-1723
ISSN-E: 2041-1723
ISSN-L: 2041-1723
Volume: 8
Issue: 1
Article number: 1483
DOI: 10.1038/s41467-017-01525-0
OADOI: https://oadoi.org/10.1038/s41467-017-01525-0
Type of Publication: A1 Journal article – refereed
Field of Science: 1182 Biochemistry, cell and molecular biology
Subjects:
Funding: The CROATIA_Vis, CROATIA_Korčula, and CROATIA_Split studies were funded by grants from the Medical Research Council (UK), European Commission Framework 6 project EUROSPAN (Contract No. LSHG-CT-2006-018947), FP7 contract BBMRI-LPC (grant No. 313010), Croatian Science Foundation (grant 8875), and the Republic of Croatia Ministry of Science, Education and Sports (216-1080315-0302). This work was funded in part by grants from the German Federal Ministry of Education and Research (BMBF), by BMBF Grant No. 01ZX1313C (project e:Athero-MED), by the European Commission HighGlycan (contract #278535), MIMOmics (contract #305280), HTP-GlycoMet (contract #324400), IntegraLife (contract #315997), and CarTarDis (contract #602936) grants. N.B. was supported by the Russian Science Foundation (grant #14-50-00131). Additional support was from NIH grants P41GM103390 (to K.W.M.), P01GM107012 (G.J.B., PI). The KORA study was initiated and financed by the Helmholtz Zentrum München—German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the Free State of Bavaria.
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