N-linked glycosite profiling and use of Skyline as a platform for characterization and relative quantification of glycans in differentiating xylem of Populus trichocarpa.
Identifieur interne : 001299 ( Main/Exploration ); précédent : 001298; suivant : 001300N-linked glycosite profiling and use of Skyline as a platform for characterization and relative quantification of glycans in differentiating xylem of Populus trichocarpa.
Auteurs : Philip L. Loziuk [États-Unis] ; Elizabeth S. Hecht [États-Unis] ; David C. Muddiman [États-Unis]Source :
- Analytical and bioanalytical chemistry [ 1618-2650 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
- analyse : Polyosides.
- composition chimique : Populus, Xylème.
- normes : Biologie informatique.
- tendances : Biologie informatique.
English descriptors
- KwdEn :
- MESH :
- chemical , analysis : Polysaccharides.
- chemistry : Populus, Xylem.
- standards : Computational Biology.
- trends : Computational Biology.
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. Graphical abstract 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.
DOI: 10.1007/s00216-016-9776-5
PubMed: 27491298
PubMed Central: PMC5209793
Affiliations:
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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. Graphical abstract 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. 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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. Graphical abstract 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.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Loziuk</LastName><ForeName>Philip L</ForeName><Initials>PL</Initials><AffiliationInfo><Affiliation>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.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hecht</LastName><ForeName>Elizabeth S</ForeName><Initials>ES</Initials><AffiliationInfo><Affiliation>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.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Muddiman</LastName><ForeName>David C</ForeName><Initials>DC</Initials><AffiliationInfo><Affiliation>W.M. 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Loziuk</name></noRegion><name sortKey="Hecht, Elizabeth S" sort="Hecht, Elizabeth S" uniqKey="Hecht E" first="Elizabeth S" last="Hecht">Elizabeth S. Hecht</name><name sortKey="Muddiman, David C" sort="Muddiman, David C" uniqKey="Muddiman D" first="David C" last="Muddiman">David C. Muddiman</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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