A quantitative method for analyzing glycome profiles of plant cell walls
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. In this paper 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.
- Authors:
-
- University of Georgia, Athens, GA (United States)
- University of Georgia, Athens, GA (United States); University of Georgia, Aiken, SC (United States). Savannah River Ecology Laboratory
- Publication Date:
- Research Org.:
- Univ. of Georgia, Athens, GA (United States)
- Sponsoring Org.:
- USDOE Office of Environmental Management (EM); National Science Foundation (NSF); Agriculture and Food Research Initiative; National Institute of Food and Agriculture
- OSTI Identifier:
- 1533601
- Alternate Identifier(s):
- OSTI ID: 1547088
- Grant/Contract Number:
- EM0004391; DBI-0421683; IOS-0923922; 2013-67009-21405
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Carbohydrate Research
- Additional Journal Information:
- Journal Volume: 448; Journal Issue: C; Journal ID: ISSN 0008-6215
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; cell walls; moisture stress; monoclonal antibodies; pinus taeda; xylan; pectin; xyloglucans
Citation Formats
Pattathil, Sivakumar, Ingwers, Miles W., Aubrey, Doug P., Li, Zenglu, and Dahlen, Joseph. A quantitative method for analyzing glycome profiles of plant cell walls. United States: N. p., 2017.
Web. doi:10.1016/j.carres.2017.06.009.
Pattathil, Sivakumar, Ingwers, Miles W., Aubrey, Doug P., Li, Zenglu, & Dahlen, Joseph. A quantitative method for analyzing glycome profiles of plant cell walls. United States. https://doi.org/10.1016/j.carres.2017.06.009
Pattathil, Sivakumar, Ingwers, Miles W., Aubrey, Doug P., Li, Zenglu, and Dahlen, Joseph. Mon .
"A quantitative method for analyzing glycome profiles of plant cell walls". United States. https://doi.org/10.1016/j.carres.2017.06.009. https://www.osti.gov/servlets/purl/1533601.
@article{osti_1533601,
title = {A quantitative method for analyzing glycome profiles of plant cell walls},
author = {Pattathil, Sivakumar and Ingwers, Miles W. and Aubrey, Doug P. and Li, Zenglu and Dahlen, Joseph},
abstractNote = {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. In this paper 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.},
doi = {10.1016/j.carres.2017.06.009},
journal = {Carbohydrate Research},
number = C,
volume = 448,
place = {United States},
year = {Mon Jun 19 00:00:00 EDT 2017},
month = {Mon Jun 19 00:00:00 EDT 2017}
}
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