Literature DB >> 28662408

A quantitative method for analyzing glycome profiles of plant cell walls.

Sivakumar Pattathil1, Miles W Ingwers2, Doug P Aubrey3, Zenglu Li2, Joseph Dahlen4.   

Abstract

Glycome profiling allows for the characterization of plant cell wall ultrastructure via sequential extractions and subsequent detection of specific epitopes with a suite of glycan-specific monoclonal antibodies (mAbs). The data are often viewed as the amount of materials recovered and coinciding colored heatmaps of mAb binding are generated. Interpretation of these data can be considered qualitative in nature as it depends on detecting subtle visual differences in antibody binding strength. Here, we report a mixed model-based quantitative approach for glycome profile analyses, which accounts for the amount of materials recovered and displays the normalized values in revised heatmaps and statistical heatmaps depicting significant differences. The utility of this methodology was demonstrated on a previously published dataset investigating the effects of moisture stress on the roots and needles of Pinus taeda. An annotated R script for the quantitative methodology is included to allow future studies to utilize the same approach.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Cell walls; Moisture stress; Monoclonal antibodies; Pectin; Pinus taeda; Xylan; Xyloglucans

Mesh:

Year:  2017        PMID: 28662408     DOI: 10.1016/j.carres.2017.06.009

Source DB:  PubMed          Journal:  Carbohydr Res        ISSN: 0008-6215            Impact factor:   2.104


  1 in total

1.  Glycome Profiling and Bioprospecting Potential of the Himalayan Buddhist Handmade Paper of Tawang Region of Arunachal Pradesh.

Authors:  Muzamil Ahmad Rather; Anutee Dolley; Nabajit Hazarika; Vimha Ritse; Kuladip Sarma; Latonglila Jamir; Siddhartha Shankar Satapathy; Suvendra Kumar Ray; Ramesh Chandra Deka; Ajaya Kumar Biswal; Robin Doley; Manabendra Mandal; Nima D Namsa
Journal:  Front Plant Sci       Date:  2022-05-23       Impact factor: 6.627

  1 in total

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