Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars

To our knowledge, this is the first growth model of Clostridium beijerinckii NCIMB 8052 on glucose and xylose as representative lignocellulosic sugars, which considers the synergistic effects of sugars on the growth rate. We fitted models with different types of interactions between the substrates t...

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Main Authors: C. Birgen, S. Markussen, A. Wentzel, H.A. Preisig, B. Wittgens
Format: Article
Language:English
Published: AIDIC Servizi S.r.l. 2018-06-01
Series:Chemical Engineering Transactions
Online Access:https://www.cetjournal.it/index.php/cet/article/view/2957
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spelling doaj-cc23f06b6cd5410c90d4cab8ee8c61352021-02-17T21:06:33ZengAIDIC Servizi S.r.l.Chemical Engineering Transactions2283-92162018-06-016510.3303/CET1865049Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic SugarsC. BirgenS. MarkussenA. WentzelH.A. PreisigB. WittgensTo our knowledge, this is the first growth model of Clostridium beijerinckii NCIMB 8052 on glucose and xylose as representative lignocellulosic sugars, which considers the synergistic effects of sugars on the growth rate. We fitted models with different types of interactions between the substrates to the growth rate data obtained with varying sugar concentrations. Noncompetitive binary substrate growth model gave the best fit with the smallest mean standard errors (MSE), and sum of squares error (SSE), 0.0778 and 0.0071, respectively. Confidence intervals for the parameter estimates showed that the substrate affinity constant for xylose, KsX (g/l) had the largest uncertainty, while the maximum specific growth rate on xylose, µmaxX (h-1) had the smallest. The correlation matrix showed that the model parameters were highly correlated. Carbon cataboliterepression (CCR) effect on the growth rate was of the noncompetitive type. Validation with other sugar concentration values is necessary to evaluate the prediction capability of the proposed model. A transcriptional study will be beneficial to understand global gene regulation mechanisms as guidance for improving the efficiency of lignocellulosic fermentation processes.https://www.cetjournal.it/index.php/cet/article/view/2957
collection DOAJ
language English
format Article
sources DOAJ
author C. Birgen
S. Markussen
A. Wentzel
H.A. Preisig
B. Wittgens
spellingShingle C. Birgen
S. Markussen
A. Wentzel
H.A. Preisig
B. Wittgens
Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars
Chemical Engineering Transactions
author_facet C. Birgen
S. Markussen
A. Wentzel
H.A. Preisig
B. Wittgens
author_sort C. Birgen
title Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars
title_short Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars
title_full Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars
title_fullStr Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars
title_full_unstemmed Modeling the Growth of Clostridium beijerinckii NCIMB 8052 on Lignocellulosic Sugars
title_sort modeling the growth of clostridium beijerinckii ncimb 8052 on lignocellulosic sugars
publisher AIDIC Servizi S.r.l.
series Chemical Engineering Transactions
issn 2283-9216
publishDate 2018-06-01
description To our knowledge, this is the first growth model of Clostridium beijerinckii NCIMB 8052 on glucose and xylose as representative lignocellulosic sugars, which considers the synergistic effects of sugars on the growth rate. We fitted models with different types of interactions between the substrates to the growth rate data obtained with varying sugar concentrations. Noncompetitive binary substrate growth model gave the best fit with the smallest mean standard errors (MSE), and sum of squares error (SSE), 0.0778 and 0.0071, respectively. Confidence intervals for the parameter estimates showed that the substrate affinity constant for xylose, KsX (g/l) had the largest uncertainty, while the maximum specific growth rate on xylose, µmaxX (h-1) had the smallest. The correlation matrix showed that the model parameters were highly correlated. Carbon cataboliterepression (CCR) effect on the growth rate was of the noncompetitive type. Validation with other sugar concentration values is necessary to evaluate the prediction capability of the proposed model. A transcriptional study will be beneficial to understand global gene regulation mechanisms as guidance for improving the efficiency of lignocellulosic fermentation processes.
url https://www.cetjournal.it/index.php/cet/article/view/2957
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