Nag Ambarish, Sprague Michael A, Griggs Andrew J, Lischeske James J, Stickel Jonathan J, Mittal Ashutosh, Wang Wei, Johnson David K
Computational Science Center, National Renewable Energy Laboratory, 15013, Denver West Parkway, Golden, CO, 80401.
National Bioenergy Center, National Renewable Energy Laboratory, 15013, Denver West Parkway, Golden, CO, 80401.
Biotechnol Prog. 2015 Sep-Oct;31(5):1237-48. doi: 10.1002/btpr.2122. Epub 2015 Jul 3.
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.
从木质纤维素生物质中经济高效地生产燃料和化学品通常涉及酶促糖化，这一直是深入研发的主题。最近，已开发出一种纤维素酶促糖化的机理模型，该模型考虑了纤维素链长的分布、不溶性纤维素对酶的可及性以及组分纤维素酶的不同作用模式[Griggs等人（2012年），《生物技术与生物工程》，109(3):665 - 675；Griggs等人（2012年），《生物技术与生物工程》，109(3):676 - 685]。然而，确定吸附、抑制和速率参数的合适值需要进一步的实验研究。在这项工作中，我们进行了几组实验以辅助参数估计并定量验证该模型。通过组分酶（EGI/CBHI/βG）以及这些酶的混合物对聚合度和结晶度不同的纤维素材料（α - 纤维素 - Iβ和高度结晶的纤维素 - Iβ）进行消化。基于文献信息和这些实验结果，确定了一组单一的模型参数，并将使用这组参数的模型模拟结果与总葡聚糖转化率、链长分布和结晶度的实验数据进行比较。模型模拟结果与实验得出的葡聚糖转化率和链长分布曲线显示出显著的一致性，并为酶促水解中涉及的多种复杂且相互作用的物理化学现象提供了有趣的见解，包括酶的协同作用、底物可及性、纤维素链长分布和结晶度以及可溶性糖对纤维素酶的抑制作用。
