U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Most Complete Functional Map of an Entire Enzyme Family
Published: March 09, 2015
Posted: February 13, 2019

Researchers develop a new process for annotating cellulose-degrading enzymes.

The Science
Plants and other forms of biomass contain significant quantities of cellulose, a structural component of cell walls. Cellulose is extremely difficult to break down; however, microbial communities that work inside biomass-harvesting insects could help improve the enzymatic deconstruction of biomass materials for biofuel production. Scientists built the most complete functional mapping of an entire family of cellulose-degrading enzymes, glycoside hydrolase (GH) family, to date. The map identifies locales involved with binding, driving the reaction, and ensuring that only the right feedstocks are acted on.

The Impact
Members of the cellulose-degrading enzyme family, the GH55 enzyme family, break down cellulose and thus are of interest to researchers working on advancing large-scale biofuels production. The team’s new annotation approach could speed up the process of studying cellulose-degrading enzymes by allowing researchers to study entire families at once. Additionally, combining of disparate technologies and collaboration among a Department of Energy (DOE) Bioenergy Research Center and two DOE user facilities will advance the understanding of cellulose structure and function to a depth beyond the capabilities of any one facility.

Summary
In this study, researchers at the DOE Great Lakes Bioenergy Research Center collaborated with the DOE Joint Genome Institute to characterize the structure and function of SacteLam55A, a GH55 protein. The gene SACTE_4363 encodes this protein and was recently isolated from the microbe SirexAA-E in the gut of the pinewood-boring wasp Sirex notilio. The gene was found when the microbe was grown on cellobiose, xylan, and pretreated switchgrass samples, suggesting it has cellulolytic properties. To determine the gene’s structure, the researchers relied on diffraction data collected at the DOE Advanced Photon Source user facility at Argonne National Laboratory to develop high-resolution crystal structures. Through assays and techniques such as gene synthesis and cell-free protein translation, the team also characterized the biochemistry and structure of the GH55 family. To the team’s knowledge, the study provides the most detailed map of an entire GH family to date.

Contact
Brian G. Fox
Great Lakes Bioenergy Research Center, University of Madison, Wisconsin
bgfox@biochem.wisc.edu

Funding
This work was supported in part by the Office of Biological and Environmental Research (Grant DE-FC02-07ER64494) and Office of Basic Energy Sciences (Contract W-31-109-ENG-38), both of which are within the U.S. Department of Energy’s (DOE’s) Office of Science. Other funding was provided by the College of Agricultural and Life Sciences, Department of Biochemistry, University of Wisconsin’s Graduate School, Michigan Economic Development Corporation, and Michigan Technology Tri-Corridor (Grant 085P1000817).

Publications
C. M. Bianchetti, T. E. Takasuka, S. Deutsch, H. S. Udell, E. J. Yik, L. F. Bergeman, and B. G. Fox, “Active site and laminarin binding in glycoside hydrolase family 55.” Journal of Biological Chemistry 290(19), 11819-32 (2015). [DOI: 10.1074/jbc.M114.623579].

Topic Areas:

  • Research Area: Genomic Analysis and Systems Biology
  • Research Area: Microbes and Communities
  • Research Area: Plant Systems and Feedstocks, Plant-Microbe Interactions
  • Research Area: DOE Joint Genome Institute (JGI)
  • Research Area: DOE Bioenergy Research Centers (BRC)
  • Research Area: Structural Biology, Biomolecular Characterization and Imaging
  • Research Area: Structural Biology Infrastructure

Division: SC-23.2 Biological Systems Science Division, BER

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

May 10, 2019
Quantifying Decision Uncertainty in Water Management via a Coupled Agent-Based Model
Considering risk perception can improve the representation of human decision-making processes in age [more...]

May 09, 2019
Projecting Global Urban Area Growth Through 2100 Based on Historical Time Series Data and Future Scenarios
Study provides country-specific urban area growth models and the first dataset on country-level urba [more...]

May 05, 2019
Calibrating Building Energy Demand Models to Refine Long-Term Energy Planning
A new, flexible calibration approach improved model accuracy in capturing year-to-year changes in bu [more...]

May 03, 2019
Calibration and Uncertainty Analysis of Demeter for Better Downscaling of Global Land Use and Land Cover Projections
Researchers improved the Demeter model’s performance by calibrating key parameters and establi [more...]

Apr 22, 2019
Representation of U.S. Warm Temperature Extremes in Global Climate Model Ensembles
Representation of warm temperature events varies considerably among global climate models, which has [more...]

List all highlights (possible long download time)