A Fractal-Like Kinetic Equation to Investigate Temperature Effect on Cellulose Hydrolysis by Free and Immobilized Cellulase

Zhang, Yu; Xu, Jingliang; Qi, Wei; Yuan, Zhenhong; Zhuang, Xinshu; Liu, Yun; He, Meng

doi:10.1007/s12010-011-9362-4

Cited by 22 publications

(27 citation statements)

References 42 publications

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“…3. h values are of the same order of magnitude as values obtained by Väljamäe et al (2003) or Zhang et al (2012), for cellulose hydrolysis. To our knowledge, similar models have not been applied before to starch hydrolysis, and then we did not find numerical values of h for starch hydrolysis in the literature.…”

Section: Can Fractal-like Kinetics Describe Starch Granule Hydrolysissupporting

confidence: 74%

Amylolysis of maize mutant starches described with a fractal-like kinetics model

Kansou

Buléon

Gérard³

et al. 2015

Carbohydrate Polymers

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Section: Can Fractal-like Kinetics Describe Starch Granule Hydrolysissupporting

confidence: 74%

Amylolysis of maize mutant starches described with a fractal-like kinetics model

Kansou

Buléon

Gérard³

et al. 2015

Carbohydrate Polymers

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“…Manganese ions can enhance cell growth (Xue et al 2008;Pereira et al 2010) and increase the activity of cellulase (Guerfali et al 2011;El-Gindy et al 2015). Cellulase enzyme production is relatively costly, which requires the enzyme to be used as fully as possible (Zhang et al 2012). Therefore, further research on manganese supplementation is needed to optimize the process of manganese catalyzed ethanol production.…”

Section: Introductionmentioning

confidence: 99%

“…The study of fermentation kinetic parameters is important for understanding the impacts of process parameters on ethanol production (Wang and Feng 2010;Zhang et al 2012). Moreover, a mathematical model is both an important tool for understanding the mechanism of a complex reaction and the base for largescale process model development (Wang and Feng 2010).…”

Section: Introductionmentioning

confidence: 99%

“…The Langmuir equation has been utilized to describe the complex, fractal-like process of converting lignocellulosic materials to ethanol (Chen et al 2014). Moreover, kinetic parameters can be used with mathematical models to predict the dynamics of the ethanol production rate (Yao et al 2011;Zhang et al 2012). The current understanding of the kinetic model of ethanol production is underdeveloped.…”

Section: Introductionmentioning

confidence: 99%

“…The effects of enzyme loading, fermentation time, substrate concentration, fermentation temperature, and size distribution on cellulose hydrolysis have been examined in previously proposed kinetic models (Yao et al 2011;Zhang et al 2012;Chen et al 2013;Chen et al 2014), but few papers considered the effect of manganese catalyst on ethanol yield. Consequently, the kinetic models of ethanol production, the optimization of ethanol production from cornstalks, and productivity should be examined systemically.…”

Section: Introductionmentioning

confidence: 99%

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Kinetic Models and Effects of Mn(II) Ion on Ethanol Production from Cornstalks

Chen

Jing

2017

BioResources

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a This paper presents a kinetic study of ethanol production by simultaneous saccharification and fermentation (SSF) from Mn(II)-catalyzed cornstalks. The optimal conditions of ethanol production were as follows: 1:2 inoculation proportion (ratio of Pachysolen tannophilus to Saccharomyces cerevisiae), 30 °C fermentation temperature, 15% inoculation quantity, 4 mg/g addition amount of Mn 2+ , and 10 U/g cellulase dosage. An optimal ethanol yield of 0.359 g/g was obtained from cornstalks under optimum conditions. A 38.5% increase in the yield was observed compared with the control group without the addition of Mn 2+ . The relationship between ethanol yield and fermentation time followed a Langmuir isotherm model. The relationship between the rate constant and fermentation time in the conversion of cornstalks to ethanol was fractal like. The findings elucidate the complex characteristics of ethanol production from cornstalks with Mn 2+ catalysis and will be useful in improving production yield.

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Thermoactivation of a cellobiohydrolase

Westh¹,

Borch

Sørensen³

et al. 2018

Biotech & Bioengineering

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We have measured activity and substrate affinity of the thermostable cellobiohydrolase, Cel7A, from Rasamsonia emersonii over a broad range of temperatures. For the wild type enzyme, which does not have a Carbohydrate Binding Module (CBM), higher temperature only led to moderately increased activity against cellulose, and we ascribed this to a pronounced, temperature induced desorption of enzyme from the substrate surface. We also tested a "high affinity" variant of R. emersonii Cel7A with a linker and CBM from a related enzyme. At room temperature, the activity of the variant was similar to the wild type, but the variant was more accelerated by temperature and about two-fold faster around 70°C. This better thermoactivation of the high-affinity variant could not be linked to differences in stability or the catalytic process, but coincided with less desorption as temperature increased. Based on these observations and earlier reports on moderate thermoactivation of cellulases, we suggest that better cellulolytic activity at industrially relevant temperatures may be attained by engineering improved substrate affinity into enzymes that already possess good thermostability. K E Y W O R D SArrhenius equation, Cel7A, cellulase, enzyme inactivation, interfacial enzyme activity, optimal temperature 1 | INTRODUCTION One of the most important concepts in technical applications of enzymes is the bell-shaped relationship between temperature and activity, and in the simplest interpretation, this reflects a balance between two independent processes (Laidler & Peterman, 1979). At moderate temperatures, where the enzyme is stable, the rate increases with temperature in same way as other chemical reactions. We will call this thermoactivation of the enzyme process, and in many cases, it follows an exponential course in concurrence with the canonical Arrhenius equation. In practical terms, thermoactivation may be quantified by the so-called Q 10 -value, which is the fractional growth in reaction rate upon a 10°C increment in temperature. As long as the enzyme is stable, thermoactivation corresponding to Q 10 about two has been commonly reported for enzyme reactions (Elias, Wieczorek, Rosenne, & Tawfik, 2014) although widely differing values are also known (Wolfenden, Snider, Ridgway, & Miller, 1999). At higher temperatures, enzyme inactivation (reversible or irreversible) becomes significant. This diminishes thermoactivation, and ultimately leads to a rapid decline in activity as the enzyme denatures. The resulting maximum in activity defines the optimal temperature, T opt . Although poorly defined because it depends on experimental conditions (e.g., duration of the assay), this parameter has proven practical in comparative discussions of enzymes for technical applications.The bell-shaped course of temperature-activity curves has influenced engineering strategies for industrial enzymes. Thus, a feasible way to speed up a certain enzyme application is to engineer variants with increased stability. This will limit activity lo...

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A Fractal-Like Kinetic Equation to Investigate Temperature Effect on Cellulose Hydrolysis by Free and Immobilized Cellulase

Cited by 22 publications

References 42 publications

Amylolysis of maize mutant starches described with a fractal-like kinetics model

Amylolysis of maize mutant starches described with a fractal-like kinetics model

Kinetic Models and Effects of Mn(II) Ion on Ethanol Production from Cornstalks

Thermoactivation of a cellobiohydrolase

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