Sign in
BiochemistryPlant Biotechnology Journal
Peer-reviewed journal article

DNA-barcoded polysaccharide specific monoclonal antibodies facilitate sensitive and multiplexed detection of cell wall polymers

C. Frankie GriffithiD, Michael G. HahniD, Ian S. WallaceiD

Abstract

Plant cell walls are polysaccharide-rich extracellular matrices composed of multiple complex carbohydrate polymer networks, including cellulose, hemicelluloses, pectins, and glycosylated proteins. Polysaccharide deposition critically impacts cell wall structure, and structural microheterogeneity within cell wall glycans also influences polymer rigidity and polymer-polymer interactions. Collections of monoclonal antibodies (mAbs) have been developed to target unique carbohydrate epitopes within cell wall polysaccharides and to investigate how these structural changes impact cellular and plant development. Here, we implement generalizable methods to attach unique DNA barcodes to mAbs that recognize major cell wall polysaccharide classes. By applying these mAbs individually to polysaccharide standards, we demonstrate that bound DNA barcoded antibody abundance can be measured via quantitative PCR. Additionally, we demonstrate that DNA conjugated antibodies can be pooled to quantitatively analyze polysaccharide epitope composition of polysaccharide standards and fractionated cell wall material by amplifying their unique barcodes via qPCR. These results demonstrate that barcoded polysaccharide-directed mAbs offer sensitive, quantitative insights into cell wall polysaccharide composition and facilitate multiplexed profiling of cell wall polysaccharide abundance. This approach will also enable multiple future high-throughput applications, such as glycome profiling, spatial glycomics, and glycan interaction measurements, that will further our understanding of cell wall compositional impacts on plant physiology.

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISKang '25Besten '25Lyczakowski '19Jayachandra '23Wilson '21Notová '22
58% semantic matchPlant Biology
Hee Sung Kang, X. Tong, Alban Mariette+11 more·The Plant Journal·Aug 30, 2025· 3 citations