Parameter Determination and Validation for a Mechanistic Model of the Enzymatic Saccharification of Cellulose-I..beta..

Jonathan Stickel, James Lischeske, Ambarish Nag, Michael Sprague, Ashutosh Mittal, Wei Wang, David Johnson, Andrew Griggs

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10 Scopus Citations

Abstract

Cost-effective production of fuels and chemicals from lignocellulosic biomass often involves enzymatic saccharification, which has been the subject of intense research and development. Recently, a mechanistic model for the enzymatic saccharification of cellulose has been developed that accounts for distribution of cellulose chain lengths, the accessibility of insoluble cellulose to enzymes, and the distinct modes of action of the component cellulases [Griggs et al. (2012) Biotechnol. Bioeng., 109(3):665-675; Griggs et al. (2012) Biotechnol. Bioeng., 109(3):676-685]. However, determining appropriate values for the adsorption, inhibition, and rate parameters required further experimental investigation. In this work, we performed several sets of experiments to aid in parameter estimation and to quantitatively validate the model. Cellulosic materials differing in degrees of polymerization and crystallinity (α-cellulose-Iβ and highly crystalline cellulose-Iβ) were digested by component enzymes (EGI/CBHI/ βG) and by mixtures of these enzymes. Based on information from the literature and the results from these experiments, a single set of model parameters was determined, and the model simulation results using this set of parameters were compared with the experimental data of total glucan conversion, chain-length distribution, and crystallinity. Model simulations show significant agreement with the experimentally derived glucan conversion and chain-length distribution curves and provide interesting insights into multiple complex and interacting physico-chemical phenomena involved in enzymatic hydrolysis, including enzyme synergism, substrate accessibility, cellulose chain length distribution and crystallinity, and inhibition of cellulases by soluble sugars.

Original languageAmerican English
Pages (from-to)1237-1248
Number of pages12
JournalBiotechnology Progress
Volume31
Issue number5
DOIs
StatePublished - 2015

Bibliographical note

Publisher Copyright:
© 2015 American Institute of Chemical Engineers Biotechnol.

NREL Publication Number

  • NREL/JA-5100-62840

Keywords

  • Biomass
  • Enzymatic hydrolysis model
  • Highly crystalline cellulose
  • Kinetic parameter estimation
  • α-cellulose

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