Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

2024 Abstracts

Structural Characterization of GT47 Glycosyltransferases in Duckweed to Facilitate Predictive Biology

Authors:

Pradeep K. Prabhakar3,4* ([email protected]), Vivek S. Bharadwaj1, Samantha J. Ziegler2, Samantha Hennen2, Charles J. Corulli3,4, Tasleem Javaid3,4, Digantkumar Chapla3,4, Alexander S. Graf3, Daniel H. Tehrani3,4, Kelley W. Moremen3,4, Maria J. Pena3,4, Yannick J. Bomble2, Breeanna R. Urbanowicz3,4

Institutions:

1Complex Carbohydrate Research Center, University of Georgia; 2Department of Biochemistry and Molecular Biology, University of Georgia; 3Biosciences Center, National Renewable Energy Laboratory; 4Renewable Resources and Enabling Sciences Center, National Renewable Energy Laboratory

Goals

The long-term objective is to develop optimized computational and experimental design schema to study plant processes at the systems level to enable precise and reliable prediction of plant gene function. Studies of substrate specificity across the GT47 family will be evaluated through modeling-based predictions and cryo-electron microscopy (Cryo-EM) to determine the molecular mechanisms that underlie duckweed cell wall synthesis.

Abstract

Complex carbohydrates are essential molecules of life that are responsible for energy supply and diverse cellular functions in all species. Glycosyltransferases (GTs) facilitate the creation of glycosidic bonds, which are essential for synthesizing intricate carbohydrates that are the building blocks of the carbon stored in plant biomass. One of the team’s main goals is to use high throughput methods to determine sugar nucleotide donor and acceptor substrate specificities for genes encoding GTs to functionally assign them into glycopolymer-specific pathways, with the aim of harnessing these pathways to reengineer duckweed cell walls for optimized biofuel and feedstock production. These data are being used in a combinatorial approach involving machine learning models to understand and predict substrate specificity: AlphaFold to predict structures of both monomeric and oligomeric GT47 Carbohydrate-Active enZYme family proteins (Zhang et al. 2023), and cryo-EM to validate the predictions experimentally. The Facilities Integrating Collaborations for User Science (FICUS) program through Environmental Molecular Sciences Laboratory (EMSL) and DOE Joint Genome Institute (JGI) will help researchers broaden the enzyme library construction to identify GT47 complexes through a combination of plant engineering, mass spectrometry, solid state nuclear magnetic resonance spectroscopy, and structural biology to analyze the protein interaction networks of all GT family members and the integral architecture of the cell wall structure of duckweed. Ultimately, the data generated from this proposal will be used to inform functional studies in a species-agnostic manner to create designer-specified cell wall structures for bioproduction.

References

Zhang, L., et al. 2023. “Glycosyltransferase Family 47 (GT47) Proteins in Plants and Animals,” Essays in Biochemistry 67(3), 639–52. DOI:10.1042/EBC20220152.

Funding Information

This research was supported by the U.S. DOE, Office of Science, BER program, GSP grant no. DE- SC0023223. A portion of this research is supported by the Facilities Integrating Collaborations for User Science (FICUS) program (DOI:10.46936/fics.proj.2023.60868/60008910) and used resources at the DOE Joint Genome Institute (https://ror.org/04xm1d337) and the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), which are DOE Office of Science User Facilities operated under Contract Nos. DE-AC02-05CH11231 (JGI) and DE-AC05- 76RL01830 (EMSL).