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In this study, we extend imaging and modeling work that was done in Part I of this report for a pure cellulose substrate (filter paper) to more industrially relevant substrates (untreated and pretreated hardwood and switchgrass). Using confocal fluorescence microscopy, we are able to track both the structure of the biomass particle via its autofluorescence, and bound enzyme from a commercial cellulase cocktail supplemented with a small fraction of fluorescently labeled Trichoderma reseii Cel7A. Imaging was performed throughout hydrolysis at temperatures relevant to industrial processing (50°C). Enzyme bound predominantly to areas with low autofluorescence, where structure loss and lignin removal had occurred during pretreatment; this confirms the importance of these processes for successful hydrolysis. The overall shape of both untreated and pretreated hardwood and switchgrass particles showed little change during enzymatic hydrolysis beyond a drop in autofluorescence intensity. The permanence of shape along with a relatively constant bound enzyme signal throughout hydrolysis was similar to observations previously made for filter paper, and was consistent with a modeling geometry of a hollowing out cylinder with widening pores represented as infinite slits. Modeling estimates of available surface areas for pretreated biomass were consistent with previously reported experimental results., (© 2014 Wiley Periodicals, Inc.)

Enzymatic hydrolysis is one of the critical steps in depolymerizing lignocellulosic biomass into fermentable sugars for further upgrading into fuels and/or chemicals. However, many studies still rely on empirical trends to optimize enzymatic reactions. An improved understanding of enzymatic hydrolysis could allow research efforts to follow a rational design guided by an appropriate theoretical framework. In this study, we present a method to image cellulosic substrates with complex three-dimensional structure, such as filter paper, undergoing hydrolysis under conditions relevant to industrial saccharification processes (i.e., temperature of 50°C, using commercial cellulolytic cocktails). Fluorescence intensities resulting from confocal images were used to estimate parameters for a diffusion and reaction model. Furthermore, the observation of a relatively constant bound enzyme fluorescence signal throughout hydrolysis supported our modeling assumption regarding the structure of biomass during hydrolysis. The observed behavior suggests that pore evolution can be modeled as widening of infinitely long slits. The resulting model accurately predicts the concentrations of soluble carbohydrates obtained from independent saccharification experiments conducted in bulk, demonstrating its relevance to biomass conversion work., (© 2014 Wiley Periodicals, Inc.)

Until now, most efforts to improve monosaccharide production from biomass through pretreatment and enzymatic hydrolysis have used empirical optimization rather than employing a rational design process guided by a theory-based modeling framework. For such an approach to be successful a modeling framework that captures the key mechanisms governing the relationship between pretreatment and enzymatic hydrolysis must be developed. In this study, we propose a pore-hindered diffusion and kinetic model for enzymatic hydrolysis of biomass. When compared to data available in the literature, this model accurately predicts the well-known dependence of initial cellulose hydrolysis rates on surface area available to a cellulase-size molecule. Modeling results suggest that, for particles smaller than 5 × 10(-3) cm, a key rate-limiting step is the exposure of previously unexposed cellulose occurring after cellulose on the surface has hydrolyzed, rather than binding or diffusion. However, for larger particles, according to the model, diffusion plays a more significant role. Therefore, the proposed model can be used to design experiments that produce results that are either affected or unaffected by diffusion. Finally, by using pore size distribution data to predict the biomass fraction that is accessible to degradation, this model can be used to predict cellulose hydrolysis with time using only pore size distribution and initial composition data., (Copyright © 2012 Wiley Periodicals, Inc.)

Understanding the depolymerization mechanisms of cellulosic substrates by cellulase cocktails is a critical step towards optimizing the production of monosaccharides from biomass. The Spezyme CP cellulase cocktail combined with the Novo 188 β-glucosidase blend was used to depolymerize bacterial microcrystalline cellulose (BMCC), which was immobilized on a glass surface. The enzyme mixture was supplemented with a small fraction of fluorescently labeled Trichoderma reseii Cel7A, which served as a reporter to track cellulase binding onto the physical structure of the cellulosic substrate. Both micro-scale imaging and bulk experiments were conducted. All reported experiments were conducted at 50 °C, the optimal temperature for maximum hydrolytic activity of the enzyme cocktail. BMCC structure was observed throughout degradation by labeling it with a fluorescent dye. This method allowed us to measure the binding of cellulases in situ and follow the temporal morphological changes of cellulose during its depolymerization by a commercial cellulase mixture. Three kinetic models were developed and fitted to fluorescence intensity data obtained through confocal microscopy: irreversible and reversible binding models, and an instantaneous binding model. The models were successfully used to predict the soluble sugar concentrations that were liberated from BMCC in bulk experiments. Comparing binding and kinetic parameters from models with different assumptions to previously reported constants in the literature led us to conclude that exposing new binding sites is an important rate-limiting step in the hydrolysis of crystalline cellulose., (Copyright © 2012 Wiley Periodicals, Inc.)