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A coarse-grained model for synergistic action of multiple enzymes on cellulose.

Asztalos A, Daniels M, Sethi A, Shen T, Langan P, Redondo A, Gnanakaran S - Biotechnol Biofuels (2012)

Bottom Line: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level.Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails.This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA. gnana@lanl.gov.

ABSTRACT

Background: Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates.

Results: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose.

Conclusions: Our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

No MeSH data available.


Related in: MedlinePlus

Endo-exo synergy. (a) Comparison of the time course of sugar production when cellulose is degraded only by endo-cellulases (red curve), only by exo-R cellulases (green curve), or when the two types of enzymes were acting together (orange curve). The sum of the red and green curves (blue curve) yields lower sugar production than in the case when the substrate is converted simultaneously by endo- and exo-cellulases. (b) Adsorbed enzyme percentages during hydrolysis when the cellulases are acting alone (red and green dots) or in a mixture (maroon and orange dots).
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Figure 12: Endo-exo synergy. (a) Comparison of the time course of sugar production when cellulose is degraded only by endo-cellulases (red curve), only by exo-R cellulases (green curve), or when the two types of enzymes were acting together (orange curve). The sum of the red and green curves (blue curve) yields lower sugar production than in the case when the substrate is converted simultaneously by endo- and exo-cellulases. (b) Adsorbed enzyme percentages during hydrolysis when the cellulases are acting alone (red and green dots) or in a mixture (maroon and orange dots).

Mentions: In order to test whether our model reproduces the experimentally observed endo-exo synergy, we used experimental data reported by Eriksson and colleagues (see Figure 1A[50]) and modified the kinetic rate constants for both types of cellulases by fitting the model single enzyme hydrolysis curves to the experimental data. The initial enzyme concentration was set to [E]0 = 1.5 μM and the cellulose concentration to 10 g/L[50]. Numerical results show the endo-exo synergy (Figure 12a) and the time scale is the same as observed experimentally [50]. It should be kept in mind that the substrate in that experimental work is steam-pretreated spruce (lignocellulose), not pure cellulose. However, it is encouraging that we do observe similar behavior. Sugar production is higher when exo-R cellulases hydrolyze the cellulose surface in the presence of endo-cellulases when compared to the sum of their conversions achieved alone.


A coarse-grained model for synergistic action of multiple enzymes on cellulose.

Asztalos A, Daniels M, Sethi A, Shen T, Langan P, Redondo A, Gnanakaran S - Biotechnol Biofuels (2012)

Endo-exo synergy. (a) Comparison of the time course of sugar production when cellulose is degraded only by endo-cellulases (red curve), only by exo-R cellulases (green curve), or when the two types of enzymes were acting together (orange curve). The sum of the red and green curves (blue curve) yields lower sugar production than in the case when the substrate is converted simultaneously by endo- and exo-cellulases. (b) Adsorbed enzyme percentages during hydrolysis when the cellulases are acting alone (red and green dots) or in a mixture (maroon and orange dots).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475064&req=5

Figure 12: Endo-exo synergy. (a) Comparison of the time course of sugar production when cellulose is degraded only by endo-cellulases (red curve), only by exo-R cellulases (green curve), or when the two types of enzymes were acting together (orange curve). The sum of the red and green curves (blue curve) yields lower sugar production than in the case when the substrate is converted simultaneously by endo- and exo-cellulases. (b) Adsorbed enzyme percentages during hydrolysis when the cellulases are acting alone (red and green dots) or in a mixture (maroon and orange dots).
Mentions: In order to test whether our model reproduces the experimentally observed endo-exo synergy, we used experimental data reported by Eriksson and colleagues (see Figure 1A[50]) and modified the kinetic rate constants for both types of cellulases by fitting the model single enzyme hydrolysis curves to the experimental data. The initial enzyme concentration was set to [E]0 = 1.5 μM and the cellulose concentration to 10 g/L[50]. Numerical results show the endo-exo synergy (Figure 12a) and the time scale is the same as observed experimentally [50]. It should be kept in mind that the substrate in that experimental work is steam-pretreated spruce (lignocellulose), not pure cellulose. However, it is encouraging that we do observe similar behavior. Sugar production is higher when exo-R cellulases hydrolyze the cellulose surface in the presence of endo-cellulases when compared to the sum of their conversions achieved alone.

Bottom Line: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level.Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails.This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

View Article: PubMed Central - HTML - PubMed

Affiliation: Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, 87545, USA. gnana@lanl.gov.

ABSTRACT

Background: Degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing β-1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, β-glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates.

Results: We present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose.

Conclusions: Our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

No MeSH data available.


Related in: MedlinePlus