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

BER Research Highlights

Mass Spectrometry Deduces Selectivity of Glycoside Hydrolases for Degrading Biomass Polysaccharides
Published: October 27, 2015
Posted: April 27, 2016

Improving the annotation of glycoside hydrolases and their phylogenetic trees.

The Science
Multiple classes of polysaccharide-degrading enzymes are used to hydrolyze plant biomass into fermentable sugars for conversion to biofuels. However, there are large numbers of suspected polysaccharide-degrading enzymes whose activities have not been determined biochemically. Researchers have now determined the reaction specificity and other parameters for several of these uncharacterized enzymes using a special mass spectroscopy system along with artificial substrates.

The Impact
Improving the annotation of glycoside hydrolase (GH) phylogenetic trees will improve understanding of the function, synergy, and stability of these enzymes and thereby the creation of biomass-degrading enzymatic cocktails.  

Researchers at the Department of Energy’s (DOE) Great Lakes Bioenergy Research Center (GLBRC) have used chemically synthesized nanostructure-initiator mass spectrometry (NIMS) probes derivatized with tetrasaccharides to study the reactivity of several enzymes representative of GH function. Patterns of reactivity identified with these NIMS probes provide a diagnostic approach to assess reaction selectivity as well as comparative apparent rate information. Their results show diagnostic patterns for reactions of a β-glucosidase, relaxed but varied specificity of several endoglucanases, and high specificity of a cellobiohydrolase with the model substrate. The researchers also modeled time-dependent reactions of these enzymes by numerical integration, providing a quantitative basis to make functional distinctions among reactive properties, thus providing a new approach to enhance the annotation of GH phylogenetic trees with functional measurements. This research was carried out in collaboration with researchers at DOE’s Joint BioEnergy Institute (JBEI).

Contacts (BER PM)
N. Kent Peters, SC-23.2, kent.peters@science.doe.gov, 301-903-5549

(PI Contact)
Brian Fox
University of Wisconsin-Madison

GLBRC and JBEI are supported by DOE’s Office of Science, Office of Biological and Environmental Research through contracts DE-FC02-07ER64494 and DE-AC02-05CH11231, respectively.

Deng, K., T. E. Takasuka, C. M. Bianchetti, L. F. Bergeman, P. D. Adams, T. R. Northen, and B. G. Fox. 2015. “Use of Nanostructure-Initiator Mass Spectrometry to Deduce Selectivity of Reaction in Glycoside Hydrolases,” Frontiers in Bioengineering and Biotechnology 3(165), DOI: 10.3389/fbioe.2015.00165. (Reference link)

Topic Areas:

  • Research Area: Genomic Analysis and Systems Biology
  • Research Area: Sustainable Biofuels and Bioproducts
  • Research Area: DOE Bioenergy Research Centers (BRC)
  • Research Area: Research Technologies and Methodologies

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)