- Deng, Kai;
- Guenther, Joel M;
- Gao, Jian;
- Bowen, Benjamin P;
- Tran, Huu;
- Reyes-Ortiz, Vimalier;
- Cheng, Xiaoliang;
- Sathitsuksanoh, Noppadon;
- Heins, Richard;
- Takasuka, Taichi E;
- Bergeman, Lai F;
- Geertz-Hansen, Henrik;
- Deutsch, Samuel;
- Loqué, Dominique;
- Sale, Kenneth L;
- Simmons, Blake A;
- Adams, Paul D;
- Singh, Anup K;
- Fox, Brian G;
- Northen, Trent R
Cost-effective hydrolysis of biomass into sugars for biofuel production requires high-performance low-cost glycoside hydrolase (GH) cocktails that are active under demanding process conditions. Improving the performance of GH cocktails depends on knowledge of many critical parameters, including individual enzyme stabilities, optimal reaction conditions, kinetics, and specificity of reaction. With this information, rate- and/or yield-limiting reactions can be potentially improved through substitution, synergistic complementation, or protein engineering. Given the wide range of substrates and methods used for GH characterization, it is difficult to compare results across a myriad of approaches to identify high performance and synergistic combinations of enzymes. Here, we describe a platform for systematic screening of GH activities using automatic biomass handling, bioconjugate chemistry, robotic liquid handling, and nanostructure-initiator mass spectrometry (NIMS). Twelve well-characterized substrates spanning the types of glycosidic linkages found in plant cell walls are included in the experimental workflow. To test the application of this platform and substrate panel, we studied the reactivity of three engineered cellulases and their synergy of combination across a range of reaction conditions and enzyme concentrations. We anticipate that large-scale screening using the standardized platform and substrates will generate critical datasets to enable direct comparison of enzyme activities for cocktail design.