Link to bioRxiv paper:
http://biorxiv.org/cgi/content/short/2020.10.15.340638v1?rss=1
Authors: Guan, Y., Hu, J., Cao, W., Cui, W., Yang, F., Krisp, C., Lin, L., Zhang, M., Voss, H., Schuster, R., Yan, G., Fuh, M. M., Thaysen-Andersen, M., H. Packer, N., Shen, H., Yang, P., Schlüter, H.
Abstract:
Global in-depth analysis of N-glycosylation, as the most complex post-translational modification of proteins, is requiring methods being as sensitive, selective and reliable as possible. Here, an enhanced strategy for N-glycomics is presented comprising optimized sample preparation yielding enhanced glycoprotein recovery and permethylation efficiency, isotopic labelling for data quality control and relative quantification, integration of new N-glycan libraries (human and mouse), newly developed R-scripts matching experimental MS1 data to theoretical N-glycan compositions and bundled sequencing algorithms for MS2-based structural identification to ultimately enhance the coverage and accuracy of N-glycans. With this strategy the numbers of identified N-glycans are more than doubled compared with previous studies, exemplified by etanercept (more than 3-fold) and chicken ovalbumin (more than 2-fold) at nanogram level. The power of this strategy and applicability to biological samples is further demonstrated by comparative N-glycomics of human acute promyelocytic leukemia cells before and after treatment with all-trans retinoic acid, showing that N-glycan biosynthesis is slowed down and 57 species are significantly altered in response to the treatment. This improved analytical platform enables deep and accurate N-glycomics for glycobiological research and biomarker discovery.
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