Activity-based protein profiling of secreted cellulolytic enzyme activity dynamics in Trichoderma reesei QM6a, NG14, and RUT-C30

Lignocellulosic biomass has great promise as a highly abundant and renewable source for the production of biofuels. However, the recalcitrant nature of lignocellulose toward hydrolysis into soluble sugars remains a significant challenge to harnessing the potential of this source of bioenergy. A primary method for deconstructing lignocellulose is via chemical treatments, high temperatures, and hydrolytic enzyme cocktails, many of which are derived from the fungus Trichoderma reesei. Herein, we use an activity-based probe for glycoside hydrolases to rapidly identify optimal conditions for maximum enzymatic lignocellulose deconstruction. We also demonstrate that subtle changes to enzyme composition and activity in various strains of T. reesei can be readily characterized by our probe approach. The approach also permits multimodal measurements, including fluorescent gel-based analysis of activity in response to varied conditions and treatments, and mass spectrometry-based quantitative identification of labelled proteins. We demonstrate the promise this probe approach holds to facilitate rapid production of enzyme cocktails for high-efficiency lignocellulose deconstruction to accommodate high-yield biofuel production.