C-STABILITY an innovative modeling framework to leverage the continuous representation of organic matter

The understanding of soil organic matter (SOM) dynamics has considerably advanced in recent years. It was previously assumed that most SOM consisted of recalcitrant compounds, whereas the emerging view considers SOM as a range of polymers continuously processed into smaller molecules by decomposer enzymes. Mainstreaming this new paradigm in current models is challenging because of their ill-adapted framework. We propose the C-STABILITY model to resolve this issue. Its innovative framework combines compartmental and continuous modeling approaches to accurately reproduce SOM cycling processes. C-STABILITY emphasizes the influence of substrate accessibility on SOM turnover and makes enzymatic and microbial biotransformations of substrate explicit. Theoretical simulations provide new insights on how depolymerization and decomposers ecology impact organic matter chemistry and amount during decomposition and at steady state. The flexible mathematical structure of C-STABILITY offers a promising foundation for exploring new mechanistic hypotheses and supporting the design of future experiments.

Hydrolysis and fermentation steps of a pretreated sawmill mixed feedstock for bioethanol production in a wood biorefinery

The aim of this work was to demonstrate the feasibility of second-generation bioethanol production using for the first time a sawmill mixed feedstock comprising four softwood species, representative of biomass resource in Auvergne-Rhône-Alpes region (France). The feedstock was subjected to a microwave-assisted water/ethanol Organosolv pretreatment. The investigation focused on enzymatic hydrolysis of this pretreated sawmill feedstock (PSF) using Cellic® Ctec2 as the enzyme, followed by fermentation of the resulting sugar solution using Saccharomyces cerevisiae strain. The cellulose-rich PSF with 71% w/w cellulose content presented high saccharification yields (up to 80%), which made it perfect for subsequent fermentation; this yield was predicted vs. time up to 5.2% w/v PSF loading using a mathematical model fitted only on data at 1.5%. Finally, high PSF loading (7.5%) and scaleup were shown to impair the saccharification yield, but alcoholic fermentation could still be carried out up to 80% of the theoretical glucose-to-ethanol conversion yield.

Mechanistic kinetic models of enzymatic cellulose hydrolysis-A review

Bioconversion of lignocellulose forms the basis for renewable, advanced biofuels, and bioproducts. Mechanisms of hydrolysis of cellulose by cellulases have been actively studied for nearly 70 years with significant gains in understanding of the cellulolytic enzymes. Yet, a full mechanistic understanding of the hydrolysis reaction has been elusive. We present a review to highlight new insights gained since the most recent comprehensive review of cellulose hydrolysis kinetic models by Bansal et al. (2009) Biotechnol Adv 27:833-848. Recent models have taken a two-pronged approach to tackle the challenge of modeling the complex heterogeneous reaction-an enzyme-centric modeling approach centered on the molecularity of the cellulase-cellulose interactions to examine rate limiting elementary steps and a substrate-centric modeling approach aimed at capturing the limiting property of the insoluble cellulose substrate. Collectively, modeling results suggest that at the molecular-scale, how rapidly cellulases can bind productively (complexation) and release from cellulose (decomplexation) is limiting, while the overall hydrolysis rate is largely insensitive to the catalytic rate constant. The surface area of the insoluble substrate and the degrees of polymerization of the cellulose molecules in the reaction both limit initial hydrolysis rates only. Neither enzyme-centric models nor substrate-centric models can consistently capture hydrolysis time course at extended reaction times. Thus, questions of the true reaction limiting factors at extended reaction times and the role of complexation and decomplexation in rate limitation remain unresolved. Biotechnol. Bioeng. 2017;114: 1369-1385. © 2017 Wiley Periodicals, Inc.

A discretized model for enzymatic hydrolysis of cellulose in a fed-batch process

In the enzymatic hydrolysis of cellulose, several phenomena have been proposed to cause a decrease in the reaction rate with increasing conversion. The importance of each phenomenon is difficult to distinguish from batch hydrolysis data. Thus, kinetic models for the enzymatic hydrolysis of cellulose often suffer from poor parameter identifiability. This work presents a model that is applicable to fed-batch hydrolysis by discretizing the substrate based on the feeding time. Different scenarios are tested to explain the observed decrease in reaction rate with increasing conversion, and comprehensive assessment of the parameter sensitivities is carried out. The proposed model performed well in the broad range of experimental conditions used in this study and when compared to literature data. Furthermore, the use of data from fed-batch experiments and discretization of the model substrate to populations was found to be very informative when assessing the importance of the rate-decreasing phenomena in the model.