Enzymatic hydrolysis of lime-pretreated corn stover and investigation of the HCH-1 Model: Inhibition pattern, degree of inhibition, validity of simplified HCH-1 Model
Introduction
Lignocellulosic biomass can be converted to ethanol, which is a renewable liquid fuel that offers simultaneous environmental benefits. One major step in the conversion of biomass to ethanol is sugar production, which may be done with either free enzymes or microorganisms. The sugars are then fermented into alcohol or fermented into organic acids with further chemical transformations into alcohol. Enzymatic hydrolysis offers major advantages over other chemical routes (e.g., acid hydrolysis) such as higher yields, minimal byproduct formation, low energy requirements, mild operating conditions, and low chemical disposal costs (Ghose and Ghosh, 1978, Kadam et al., 1999, Van Wyk, 2001). Even though current costs of the enzymatic route are higher than other routes, what drives research is its long-term potential for cost reduction through genetic and/or metabolic engineering and economic viability over more established routes (Lynd et al., 1991).
A major hindrance of current biomass processing schemes is the high costs associated with enzymes and pretreatments. Despite the high costs, pretreatment, classified as either chemical (e.g., acid and alkaline) or physical (e.g., milling and irradiation), is an essential prerequisite to alter biomass structural features, thereby improving the susceptibility of biomass to enzymatic hydrolysis (Chang, 1999, Chang and Holtzapple, 2000). Economic evaluations of processes that convert biomass to bioethanol indicate that pretreatment is the single most expensive step, accounting for roughly one-third of the overall processing cost (Lynd et al., 1996). Enzyme production, on the other hand, alone can account for as much as 30% of the total process cost (Lynd et al., 1996). A thorough understanding of what structural features hinder enzymatic hydrolysis has the potential to aid in the design of more effective and economically feasible conditions of these two major contributors to the high cost of current biomass technologies.
Various theoretical, empirical, and hybrid models have been developed to predict the enzymatic hydrolysis of biomass (Holtzapple et al., 1984, Medve et al., 1998, Movagarnejad et al., 2000, Tarantili et al., 1996). Because cellulose is a highly complex substrate, its hydrolysis involves two distinct stages: enzyme–substrate complex formation and cellulose hydrolysis. Enzyme–substrate complex formation consists of two major steps including mass transfer of enzyme from the bulk aqueous phase to the cellulose surface and formation of the enzyme–substrate complex following enzyme adsorption. Cellulose enzymatic hydrolysis consists of three major steps including transfer of reactant molecules to the active site of the enzyme–substrate complex, reaction promoted by the enzyme, and transfer of soluble products to the bulk aqueous phase. The complex-heterogeneous reaction mechanism involved in cellulose enzymatic hydrolysis and the intricate morphology of biomass make enzymatic hydrolysis difficult to model (Movagarnejad et al., 2000, Zhang et al., 1999).
The classic Michaelis–Menton parametric model is inadequate to explain the action of cellulases on insoluble cellulose. In contrast, the kinetic behavior of cellulases on well-defined soluble oligosaccharides, in particular β-glucosidase, does fit the Michaelis–Menton model (Schou et al., 1993). This is due to the homogeneous nature of the reaction mechanism involved in cellobiose hydrolysis to glucose. The nonlinearity observed when plotting sugar conversion versus hydrolysis time at a given enzyme loading indicates that the rate of cellulose hydrolysis decreases and often stops before all of the substrate is consumed (Zhang et al., 1999). There are several factors that lead to a decrease in hydrolysis rates as the reaction progresses including end-product inhibition, lower substrate reactivity (higher crystallinity, higher lignin content, substrate accessibility, and others), enzyme inactivation, and enzyme loss due to irreversible lignin adsorption. Without the complication of product inhibition or cellulase inactivation, Desai and Converse (1997) concluded that the loss of substrate reactivity is not the principal cause for the long residence time required for complete biomass conversion. Likewise, Eriksson et al. (2002) concluded that thermal instability of the enzymes and product inhibition were not the main cause of reduced hydrolysis rates, instead enzymes become inactive while adsorbed to the substrate and that unproductive binding is the main cause of hydrolysis rate reduction.
In studies with pure celluloses, amorphous regions were shown to degrade 5–10 times faster than highly crystalline celluloses by fungal enzymes (Gama et al., 1994, Klyosov, 1990, Lynd et al., 2002). This suggests that the high initial rates are due to preferential hydrolysis of the more easily degraded amorphous regions and the rate decreases as the enzymes encounter the more recalcitrant crystalline regions. Therefore, models have been developed that account for the bicomposition (amorphous and crystalline) of cellulose (Huang, 1975). However, validation of such models is extremely difficult if not impossible. Accurately determining the quantity of cellulose that is crystalline and amorphous as the reaction progresses is extremely tricky. In contrast, several researchers have observed no substantial change in crystallinity as enzymatic hydrolysis progresses beyond the initial stage (Lenz et al., 1990, Ohmine et al., 1983, Puls and Wood, 1991). The inconsistencies in the rate of hydrolysis of crystalline cellulose may be due to the crude/impure nature of the cellulase enzyme complex. The quantities of endoglucanases (EGs) relative to cellobiohydrolases (CBHs) can be inconsistent from batch to batch. Because CBHs have been shown to degrade crystalline cellulose whereas EGs are very ineffective, the differences in enzyme batches may lead to conflicting results when investigating the increase or decrease of crystallinity as the reaction progresses.
Product inhibition of cellulases is a central limitation to the practical use of cellulases in biomass conversion processes. This explains the interest in Simultaneous Saccharification and Fermentation (SSF) technology as an alternative to the two-step technique that allows for the accumulation of low-molecular-weight sugars. Even though product inhibition is accepted as a limitation to thoroughly hydrolyzing biomass, the type of inhibition is a subject of much debate. The discrepancies result from the difficulty in conducting experiments because of the high inhibitor concentrations required to elicit an inhibitory effect. Researchers have reported conflicting results; while some measure competitive inhibition (Beltrame et al., 1984, Dwivedi and Ghose, 1979, Gonzalez et al., 1989) and non-competitive inhibition (Holtzapple et al., 1984, Scheiding et al., 1984, Wald et al., 1984) others measure uncompetitive inhibition (Beltrame et al., 1984). This discrepancy could be a result of the substrate to enzyme ratio employed, source of cellulase enzyme complex, and/or the hydrolysis time over which the experiments were conducted.
Previously, Holtzapple et al. (1984) developed a generalized theoretical model of cellulose hydrolysis, termed the HCH-1 Model. It was shown that the HCH-1 Model could be simplified in such a way that a plot of conversion versus the logarithm of enzyme loading is linear (Holtzapple et al., 1994). The linearity of this plot has been observed over a tenfold range in enzyme loading and a threefold range in initial cellulose concentration (Mandels et al., 1981). The modified HCH-1 model was used in these studies to predict the enzymatic hydrolysis of lime-pretreated corn stover.
Section snippets
Mathematical background
The HCH-1 Model uses non-competitive inhibition and does not predict linear reaction rates in enzyme concentration as does the classic Michaelis–Menton model (Holtzapple et al., 1984). The HCH-1 Model may be written aswhere Gx is the cellulose concentration, E is the enzyme concentration, ϕ is the fraction of the cellulose surface that is free to be hydrolyzed, and κ, α, and ε are parameters that describe the degree of substrate reactivity and hence are related to biomass
Substrate preparation
The ground and sieved biomass (−40 mesh) was pretreated with 0.1 g lime (Ca(OH)2)/g dry biomass and 10 g water/g dry biomass for 2 h at 100 °C. After pretreating, an appropriate amount of acetic acid was added to neutralize (pH 5.5) any residual lime. After pH adjustment, the corn stover was repeatedly washed with distilled water and centrifuged to separate the wash water from the biomass until the supernatant was clear. The pretreated and washed corn stover was air dried at 45 °C for 3 days. The
Determination of inhibition pattern
Lime-treated corn stover subjected to cellulase enzymatic hydrolysis exhibited the classic nonlinear kinetic profile of a heterogeneous lignocellulosic reaction system as shown in Fig. 1. The nonlinear profile was expected due to the heterogeneous nature of lignocellulosic hydrolysis, which requires an adsorption step at the enzyme binding domain prior to cleavage of the glycosidic bond and release of the product from the enzyme catalytic domain.
The inhibition pattern of cellulases by glucose
Conclusions
Systematic studies on the effect of substrate concentration and enzyme loading indicated the inhibition pattern for the lime-pretreated corn stover–cellulase reaction system was non-competitive, which agrees with the inhibition pattern used to develop the HCH-1 Model. As a result, future work developing an empirical model to predict biomass enzymatic hydrolysis based solely on biomass structural features will take advantage of the simplified HCH-1 Model developed by Holtzapple et al. (1984) to
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