Modelling heterogeneity in cellulose properties predicts the slowdown phenomenon during enzymatic hydrolysis

Effect of Culture Conditions on Cellulose Production by a Komagataeibacter Xylinus Strain

Different fermentation conditions cause different shear forces, which have a great influence on BC synthesis. The shearing force activates the conversion of microbial cells to Cel^- mutants, and the accumulation of water-soluble exopolysaccharides is also observed. A substrate competitive relationship between these two polysaccharides is found, which is significant in terms of the optimization of cellulose production in commercial processes. This article is protected by copyright. All rights reserved.

Investigating the effects of substrate morphology and experimental conditions on the enzymatic hydrolysis of lignocellulosic biomass through modeling

BACKGROUND

Understanding how the digestibility of lignocellulosic biomass is affected by its morphology is essential to design efficient processes for biomass deconstruction. In this study, we used a model based on a set of partial differential equations describing the evolution of the substrate morphology to investigate the interplay between experimental conditions and the physical characteristics of biomass particles as the reaction proceeds. Our model carefully considers the overall quantity of cellulase present in the hydrolysis mixture and explores its interplay with the available accessible cellulose surface.

RESULTS

Exploring the effect of various experimental and structural parameters highlighted the significant role of internal mass transfer as the substrate size increases and/or the enzyme loading decreases. In such cases, diffusion of cellulases to the available cellulose surface limits the rate of glucose release. We notably see that increasing biomass loading, while keeping enzyme loading constant should be favored for both small- (R < 300 [Formula: see text]) and middle-ranged (300 < R < 1000 [Formula: see text]) substrates to enhance enzyme diffusion while minimizing the use of enzymes. In such cases, working at enzyme loadings exceeding the full coverage of the cellulose surface (i.e. eI>1) does not bring a significant benefit. For larger particles (R > 1000 [Formula: see text]), increases in biomass loading do not offset the significant internal mass transfer limitations, but high enzyme loadings improve enzyme penetration by maintaining a high concentration gradient within the particle. We also confirm the well-known importance of cellulose accessibility, which increases with pretreatment.

CONCLUSIONS

Based on the developed model, we are able to propose several design criteria for deconstruction process. Importantly, we highlight the crucial role of adjusting the enzyme and biomass loading to the wood particle size and accessible cellulose surface to maintain a strong concentration gradient, while avoiding unnecessary excess in cellulase loading. Theory-based approaches that explicitly consider the entire lignocellulose particle structure can be used to clearly identify the relative importance of bottlenecks during the biomass deconstruction process, and serve as a framework to build on more detailed cellulase mechanisms.

Modeling coordinated enzymatic control of saccharification and fermentation by Clostridium thermocellum during consolidated bioprocessing of cellulose

Consolidated bioprocessing (CBP) of cellulose is a cost-effective route to produce valuable biochemicals by integrating saccharification, fermentation and cellulase synthesis in a single step. However, the lack of understanding of governing factors of interdependent saccharification and fermentation in CBP eludes reliable process optimization. Here, we propose a new framework that synergistically couples population balances (to simulate cellulose depolymerization) and cybernetic models (to model enzymatic regulation of fermentation) to enable improved understanding of CBP. The resulting framework, named the unified cybernetic-population balance model (UC-PBM), enables simulation of CBP driven by coordinated control of enzyme synthesis through closed-loop interactions. UC-PBM considers two key aspects in controlling CBP: (1) heterogeneity in cellulose properties and (2) cellular regulation of competing cell growth and cellulase secretion. In a case study on Clostridium thermocellum, UC-PBM not only provides a decent fit with various exometabolomic data, but also reveals that: (i) growth-decoupled cellulase-secreting pathways are only activated during famine conditions to promote the production of growth substrates, and (ii) starting cellulose concentration has a strong influence on the overall flux distribution. Equipped with mechanisms of cellulose degradation and fermentative regulations, UC-PBM is practical to explore phenotypic functions for primary evaluation of microorganisms' potential for metabolic engineering and optimal design of bioprocess.

Preparation and catalytic performance of biomass-based solid acid catalyst from Pennisetum sinense for cellulose hydrolysis

As a kind of lignocellulosic biomass, Pennisetum sinense (P. sinense) is commonly used as animal feed, fertilizer or papermaking raw materials. Based on the high carbon content and renewability of P. sinense, we explored the possibility and feasibility of using it as catalyst matrix. The catalyst was produced by sulfonation of char obtained from the carbonization of P. sinense at 550 °C. The structure of the catalyst was characterized by SEM, BET, XRD, FT-IR, XPS and TGA, and its catalytic performance for the hydrolysis of cellulose was investigated in detail. The highest acidity of the catalyst was 3.79 mmol/g and the maximum glucose yield of 59.92% was achieved under optimized conditions. The catalyst also showed a promising reusability. The glucose yield was 53.01% after 5 cycles and as high as 55.92% when using the regenerated catalyst.

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

BACKGROUND

Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system.

RESULTS

A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed.

CONCLUSIONS

Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.