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N-linked glycosite profiling and use of Skyline as a platform for characterization and relative quantification of glycans in differentiating xylem of Populus trichocarpa

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Abstract

Our greater understanding of the importance of N-linked glycosylation in biological systems has spawned the field of glycomics and development of analytical tools to address the many challenges regarding our ability to characterize and quantify this complex and important modification as it relates to biological function. One of the unmet needs of the field remains a systematic method for characterization of glycans in new biological systems. This study presents a novel workflow for identification of glycans using Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT™) strategy developed in our lab. This consists of monoisotopic mass extraction followed by peak pair identification of tagged glycans from a theoretical library using an in-house program. Identification and relative quantification could then be performed using the freely available bioinformatics tool Skyline. These studies were performed in the biological context of studying the N-linked glycome of differentiating xylem of the poplar tree, a widely studied model woody plant, particularly with respect to understanding lignin biosynthesis during wood formation. Through our workflow, we were able to identify 502 glycosylated proteins including 12 monolignol enzymes and 1 peroxidase (PO) through deamidation glycosite analysis. Finally, our novel semi-automated workflow allowed for rapid identification of 27 glycans by intact mass and by NAT/SIL peak pairing from a library containing 1573 potential glycans, eliminating the need for extensive manual analysis. Implementing Skyline for relative glycan quantification allowed for improved accuracy and precision of quantitative measurements over current processing tools which we attribute to superior algorithms correction for baseline variation and MS1 peak filtering.

Workflow for FANGS-INLIGHT glycosite profiling of plant xylem and monolignol proteins followed by INLIGHT tagging with semi-automated identification of glycans by light-heavy peak pairs. Finally, manual validation and relative quantification was performed in Skyline

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Acknowledgments

This material is based on work supported by North Carolina State University and the Chemistry Graduate Assistantship and the NIH/NCSU Molecular Biotechnology Training Program (Grant 5T32GM00-8776-08). We gratefully acknowledge Jack P. Wang and Vincent L. Chiang for providing the xylem used in this study. Finally, we would also like to thank Jon Ziefle for writing MIsearch.py.

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  1. W.M. Keck FTMS Laboratory for Human Health Research, Department of Chemistry, North Carolina State University, 116 Cox Hall, Campus Box 8201, Raleigh, NC, 27695, USA

    Philip L. Loziuk, Elizabeth S. Hecht & David C. Muddiman

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  1. Philip L. Loziuk
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Correspondence to David C. Muddiman.

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Published in the topical collection Glycomics, Glycoproteomics and Allied Topics with guest editors Yehia Mechref and David Muddiman.

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Loziuk, P.L., Hecht, E.S. & Muddiman, D.C. N-linked glycosite profiling and use of Skyline as a platform for characterization and relative quantification of glycans in differentiating xylem of Populus trichocarpa . Anal Bioanal Chem 409, 487–497 (2017). https://doi.org/10.1007/s00216-016-9776-5

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