Stochastic model of lignocellulosic material saccharification.

The processing of agricultural wastes towards extraction of renewable resources is recently being considered as a promising alternative to conventional biofuel production. The degradation of agricultural residues is a complex chemical process that is currently time intensive and costly. Various pre-...

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Autores principales:	Eric Behle, Adélaïde Raguin
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/a3c960cc99bd421f832c35c98b927c39
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spelling	oai:doaj.org-article:a3c960cc99bd421f832c35c98b927c392021-12-02T19:57:48ZStochastic model of lignocellulosic material saccharification.1553-734X1553-735810.1371/journal.pcbi.1009262https://doaj.org/article/a3c960cc99bd421f832c35c98b927c392021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009262https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The processing of agricultural wastes towards extraction of renewable resources is recently being considered as a promising alternative to conventional biofuel production. The degradation of agricultural residues is a complex chemical process that is currently time intensive and costly. Various pre-treatment methods are being investigated to determine the subsequent modification of the material and the main obstacles in increasing the enzymatic saccharification. In this study, we present a computational model that complements the experimental approaches. We decipher how the three-dimensional structure of the substrate impacts the saccharification dynamics. We model a cell wall microfibril composed of cellulose and surrounded by hemicellulose and lignin, with various relative abundances and arrangements. This substrate is subjected to digestion by different cocktails of well characterized enzymes. The saccharification dynamics is simulated in silico using a stochastic procedure based on a Gillespie algorithm. As we additionally implement a fitting procedure that optimizes the parameters of the simulation runs, we are able to reproduce experimental saccharification time courses for corn stover. Our model highlights the synergistic action of enzymes, and confirms the linear decrease of sugar conversion when either lignin content or crystallinity of the substrate increases. Importantly, we show that considering the crystallinity of cellulose in addition to the substrate composition is essential to interpret experimental saccharification data. Finally, our findings support the hypothesis of xylan being partially crystalline.Eric BehleAdélaïde RaguinPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009262 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Eric Behle Adélaïde Raguin Stochastic model of lignocellulosic material saccharification.
description	The processing of agricultural wastes towards extraction of renewable resources is recently being considered as a promising alternative to conventional biofuel production. The degradation of agricultural residues is a complex chemical process that is currently time intensive and costly. Various pre-treatment methods are being investigated to determine the subsequent modification of the material and the main obstacles in increasing the enzymatic saccharification. In this study, we present a computational model that complements the experimental approaches. We decipher how the three-dimensional structure of the substrate impacts the saccharification dynamics. We model a cell wall microfibril composed of cellulose and surrounded by hemicellulose and lignin, with various relative abundances and arrangements. This substrate is subjected to digestion by different cocktails of well characterized enzymes. The saccharification dynamics is simulated in silico using a stochastic procedure based on a Gillespie algorithm. As we additionally implement a fitting procedure that optimizes the parameters of the simulation runs, we are able to reproduce experimental saccharification time courses for corn stover. Our model highlights the synergistic action of enzymes, and confirms the linear decrease of sugar conversion when either lignin content or crystallinity of the substrate increases. Importantly, we show that considering the crystallinity of cellulose in addition to the substrate composition is essential to interpret experimental saccharification data. Finally, our findings support the hypothesis of xylan being partially crystalline.
format	article
author	Eric Behle Adélaïde Raguin
author_facet	Eric Behle Adélaïde Raguin
author_sort	Eric Behle
title	Stochastic model of lignocellulosic material saccharification.
title_short	Stochastic model of lignocellulosic material saccharification.
title_full	Stochastic model of lignocellulosic material saccharification.
title_fullStr	Stochastic model of lignocellulosic material saccharification.
title_full_unstemmed	Stochastic model of lignocellulosic material saccharification.
title_sort	stochastic model of lignocellulosic material saccharification.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/a3c960cc99bd421f832c35c98b927c39
work_keys_str_mv	AT ericbehle stochasticmodeloflignocellulosicmaterialsaccharification AT adelaideraguin stochasticmodeloflignocellulosicmaterialsaccharification
_version_	1718375794000003072

Stochastic model of lignocellulosic material saccharification.

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