Enzymatic depolymerization of polysaccharides

Impact and Control of Sugar Size in Glycoconjugate Vaccines

Glycoconjugate vaccines have contributed enormously to reducing and controlling encapsulated bacterial infections for over thirty years. Glycoconjugate vaccines are based on a carbohydrate antigen that is covalently linked to a carrier protein; this is necessary to cause T cell responses for optimal immunogenicity, and to protect young children. Many interdependent parameters affect the immunogenicity of glycoconjugate vaccines, including the size of the saccharide antigen. Here, we examine and discuss the impact of glycan chain length on the efficacy of glycoconjugate vaccines and report the methods employed to size polysaccharide antigens, while highlighting the underlying reaction mechanisms. A better understanding of the impact of key parameters on the immunogenicity of glycoconjugates is critical to developing a new generation of highly effective vaccines.

Understanding Starch Structure: Recent Progress

Starch is a major food supply for humanity. It is produced in seeds, rhizomes, roots and tubers in the form of semi-crystalline granules with unique properties for each plant. Though the size and morphology of the granules is specific for each plant species, their internal structures have remarkably similar architecture, consisting of growth rings, blocklets, and crystalline and amorphous lamellae. The basic components of starch granules are two polyglucans, namely amylose and amylopectin. The molecular structure of amylose is comparatively simple as it consists of glucose residues connected through α-(1,4)-linkages to long chains with a few α-(1,6)-branches. Amylopectin, which is the major component, has the same basic structure, but it has considerably shorter chains and a lot of α-(1,6)-branches. This results in a very complex, three-dimensional structure, the nature of which remains uncertain. Several models of the amylopectin structure have been suggested through the years, and in this review two models are described, namely the “cluster model” and the “building block backbone model”. The structure of the starch granules is discussed in light of both models.

Design starch: stochastic modeling of starch granule biogenesis

Starch is the most widespread and abundant storage carbohydrate in plants and the main source of carbohydrate in the human diet. Owing to its remarkable properties and commercial applications, starch is still of growing interest. Its unique granular structure made of intercalated layers of amylopectin and amylose has been unraveled thanks to recent progress in microscopic imaging, but the origin of such periodicity is still under debate. Both amylose and amylopectin are made of linear chains of α-1,4-bound glucose residues, with branch points formed by α-1,6 linkages. The net difference in the distribution of chain lengths and the branching pattern of amylose (mainly linear), compared with amylopectin (racemose structure), leads to different physico-chemical properties. Amylose is an amorphous and soluble polysaccharide, whereas amylopectin is insoluble and exhibits a highly organized structure of densely packed double helices formed between neighboring linear chains. Contrarily to starch degradation that has been investigated since the early 20th century, starch production is still poorly understood. Most enzymes involved in starch growth (elongation, branching, debranching, and partial hydrolysis) are now identified. However, their specific action, their interplay (cooperative or competitive), and their kinetic properties are still largely unknown. After reviewing recent results on starch structure and starch growth and degradation enzymatic activity, we discuss recent results and current challenges for growing polysaccharides on granular surface. Finally, we highlight the importance of novel stochastic models to support the analysis of recent and complex experimental results, and to address how macroscopic properties emerge from enzymatic activity and structural rearrangements.

Preparation and characterization of molecular weight fractions of guar galactomannans using acid and enzymatic hydrolysis

A procedure is described for the preparation of large amounts of guar galactomannan by acid hydrolysis that yields samples of various molecular weights (MW) with uniform polydispersity. This contrasts with preparation by enzymatic degradation that yields samples with a marked increase in polydispersity and a much broader molecular weight distribution (MWD). Acid hydrolyzed guar samples had a Mark-Houwink-Sakurada (MHS) relationship of [eta]=3.04x10(-4) M(w)(0.747) dl/g and a characteristic ratio of 11.87 as determined by gel permeation chromatography (GPC) and dilute solution viscometry. The Huggins coefficient for degraded guars is much smaller (approximately 0.4) than that of the native guar (approximately 0.79), suggesting a weakening of intermolecular association in guar prepared by acid hydrolysis.

Hydrolysis of wheat starch and its effect on the falling number procedure: mathematical model

A population balance model was developed for wheat starch hydrolysis to simulate the performance parameters of a viscosity-based device, known as the Falling Number instrument. The instrument is widely used as an indirect means to gauge the level of preharvest sprout activity in cereal grains such as wheat and barley. The model consists of three competing kinetics: starch gelatinization, enzymatic hydrolysis, and enzyme thermal deactivation. Using established principles of starch rheology and fluid mechanics, the model simulates the velocity profiles of the falling stirrer, starch gel viscosity, and the Falling Number readings at various levels of alpha-amylase. Model predictions for the velocity of the stirrer at any time during the downward fall, as well as the prediction of the total time needed for the fall, defined as the Falling Number, were in fair agreement with experimental measurements. There was better agreement between the modeled viscosity and the final viscosity of the starch gel as measured by a precision rheometer than there was with the measured Falling Number.

Enzymatic degradation of guar and substituted guar galactomannans

Enzymatic degradation of guar galactomannan is studied using gel permeation chromatography (GPC) and steady shear viscometry. In very dilute polymer solutions, reaction rate increases with first-order kinetics with substrate concentration. In the intermediate concentration regime, the enzyme/polymer binding saturates, and the degradation kinetics is zero-order. The observations are in accord with a Michaelis-Menton kinetics model. The Michaelis-Menton parameter, Km and Vmax, were determined to be 0.6 mM and 7.8 x 10(-10) mol/(mL s) for guar at pH = 7, where the maximal velocity of the reaction, Vmax, was measured in terms of the molar concentration of glycosidic bonds broken per unit time. However, as the solution increases in concentration, the reaction rate decreases and the enzyme diffusion through the concentrated polymer gel becomes a limiting factor. A reaction-diffusion model is presented to express the competition between enzyme reaction and diffusion. The scaling theory and kinetic data are used to define the boundaries of the polymer concentration regimes between substrate (i.e., polymer strand) limited reactions, enzyme limited reactions, and hindered diffusion limited reactions. The influence of polymer derivatization on the degradation kinetics was also explored. The degradation rate was shown to be greatly affected by the type of substituent groups as well as the degree of substitution. The triggering mechanism and controlled degradation were found for the enzymatic hydrolysis of cationically derivatized guar solutions.

Iteration model of starch hydrolysis by amylolytic enzymes

An elaborate computer program to simulate the process of starch hydrolysis by amylolytic enzymes was been developed. It is based on the Monte Carlo method and iteration kinetic model, which predict productive and non-productive amylase complexes with substrates. It describes both multienzymatic and multisubstrate reactions simulating the "real" concentrations of all components versus the time of the depolymerization reaction the number of substrates, intermediate products, and final products are limited only by computer memory. In this work, it is assumed that the "proper" substrate for amylases is the glucoside linkages in starch molecules. Dynamic changes of substrate during the simulation adequately influence the increase or decrease of reaction velocity, as well as the kinetics of depolymerization. The presented kinetic model, can be adapted to describe most enzymatic degradations of a polymer. This computer program has been tested on experimental data obtained for alpha- and beta-amylases.