Design, synthesis, and evaluation of a modular enzyme cascade for biomass conversion

Thesis Abstract

In the pursuit of sustainable bioprocessing, this study addresses the challenge of efficiently converting lignocellulosic biomass into fermentable sugars by engineering a modular enzyme cascade that combines complementary hydrolases and oxidoreductases to overcome recalcitrance and reduce process steps. The aim is to design, synthesize, and evaluate a modular enzyme cascade capable of sequential, one-pot hydrolysis and selective oxidation of biomass-derived polymers with high catalytic efficiency, stability, and reusability under industrially relevant conditions. Specific objectives include (1) constructing a library of modular enzyme modules with defined carrier fusion strategies and linkers to enable rapid assembly and tunable cascade length; (2) optimizing inter-enzyme proximities and cofactor cycling to maximize turnover numbers (TON) and space-time yields (STY) on pretreated corn stover and softwood substrates; (3) evaluating cascade performance under varying temperatures (40–60°C) and pH (5.0–7.0) to determine robustness; (4) assessing stability and recyclability through repeated batch runs (?10 cycles) and immobilization approaches; and (5) developing a kinetic and mechanistic model to predict cascade efficiency and identify rate-limiting steps. The methodology integrates design, synthesis, and evaluation within a systems-engineering framework. A modular enzyme library comprising cellulases, xylanases, lignin-degrading auxiliary enzymes, and redox-active partners will be assembled using genetic fusion and click-chemistry conjugation, with enzyme modules characterized by SDS-PAGE, mass spectrometry, and differential scanning calorimetry (DSC) to confirm integrity and thermostability. The population consists of purified enzyme variants expressed in Pichia pastoris and Escherichia coli, with substrate sets including finely milled pretreated corn stover, birchwood xylan, and model oligomers. A two-stage optimization will be conducted (i) a screening phase using Design of Experiments (DoE) to identify optimal module combinations and stoichiometries, and (ii) a refinement phase employing response surface methodology (RSM) to optimize reaction conditions and module spacings. Data collection employs high-performance liquid chromatography (HPLC) for monosaccharide and oligomer quantification, coupled with high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD) for detailed sugar profiling, and isotopic labeling to trace carbon flux through the cascade. Catalytic performance will be measured in terms of kinetic parameters (Km, Vmax, catalytic efficiency), TON, turnover frequency (TOF), STY, and overall saccharification yield. Analytical techniques will be complemented by mass spectrometry-based proteomics to monitor enzyme integrity over time, and Fourier-transform infrared spectroscopy (FTIR) for substrate-structure changes. Data analysis will integrate kinetic modeling and mechanistic interpretation. Regression analysis and ANOVA will identify significant factors affecting cascade performance, while non-linear mixed-effects modeling will address batch-to-batch variability. A multivariate optimization will be performed to determine the most effective cascade assembly. A theoretical framework drawing on the principles of enzyme channeling and the theory of proximity-induced catalysis will guide interpretation of module interactions, with a conceptual model mapping substrate flow and cofactor recycling across modules. The study anticipates demonstrating a modular cascade that achieves ?60% saccharification yield on complex biomass within 24 hours at 50°C and pH 6.0, with STY surpassing existing consolidated bioprocessing benchmarks by at least 20%. Expected contributions include a tunable modular design strategy for biomass-degrading cascades, empirical insights into enzyme proximity effects and cofactor economy, and a validated kinetic model for predicting cascade performance. The practical implications include potential reductions in enzyme loading and processing time, enabling more cost-effective biomass conversion processes. The study concludes with recommendations for scale-up strategies, integration with downstream fermentation, and guidance for modular library expansion to accommodate diverse biomass types and pretreatment methods.