Alex Chi Wu

Molecular weight distributions of starch branches reveal genetic constraints on biosynthesis

Modeling the chain-length distributions (CLDs, the molecular weight distributions of individual branches) in a polymer system can be exploited to obtain information on the underlying (bio)synthesis mechanisms. Such a model is developed for starch (a highly branched glucose polymer), taking into account multiple isoforms of the three types of enzymatic mechanisms contributing directly to the CLD: propagation, branching, and debranching. The resulting CLD is given by two parameters and can thus be represented by a point in a two-dimensional phase diagram. The model implies that all native-starch amylopectin CLDs are confined to a line in this phase diagram, an inference supported by fitting data for a wide range of plants. This gives new ways to classify mutants and suggests useful directions for plant engineering (e.g., which isoforms could be targeted to give long branches, which are nutritionally desirable).

A Parameterized Model of Amylopectin Synthesis Provides Key Insights into the Synthesis of Granular Starch

A core set of genes involved in starch synthesis has been defined by genetic studies, but the complexity of starch biosynthesis has frustrated attempts to elucidate the precise functional roles of the enzymes encoded. The chain-length distribution (CLD) of amylopectin in cereal endosperm is modeled here on the basis that the CLD is produced by concerted actions of three enzyme types: starch synthases, branching and debranching enzymes, including their respective isoforms. The model, together with fitting to experiment, provides four key insights. (1) To generate crystalline starch, defined restrictions on particular ratios of enzymatic activities apply. (2) An independent confirmation of the conclusion, previously reached solely from genetic studies, of the absolute requirement for debranching enzyme in crystalline amylopectin synthesis. (3) The model provides a mechanistic basis for understanding how successive arrays of crystalline lamellae are formed, based on the identification of two independent types of long amylopectin chains, one type remaining in the amorphous lamella, while the other propagates into, and is integral to the formation of, an adjacent crystalline lamella. (4) The model provides a means by which a small number of key parameters defining the core enzymatic activities can be derived from the amylopectin CLD, providing the basis for focusing studies on the enzymatic requirements for generating starches of a particular structure. The modeling approach provides both a new tool to accelerate efforts to understand granular starch biosynthesis and a basis for focusing efforts to manipulate starch structure and functionality using a series of testable predictions based on a robust mechanistic framework.

Exploring extraction/dissolution procedures for analysis of starch chain-length distributions

The analysis of starch chain-length distributions (CLDs) is important for understanding starch biosythesis-structure-property relations. It is obtained by analyzing the number distribution of the linear glucan chains released by enzymatic debranching of starch α-(1→6) glycosidic bonds for subsequent characterization by techniques such as fluorophore-assisted carbohydrate electrophoresis (FACE) or size-exclusion chromatography (SEC). Current literature pretreatments for debranching prior to CLD determination involve varying protocols, which might yield artifactual results. This paper examines the two widely used starch dissolution treatments with dimethyl sulfoxide (DMSO) containing 0.5% (w/w) lithium bromide (DMSO-LiBr) at 80°C and with aqueous alkaline (i.e. NaOH) solvents at 100 ˚C. Analyses by FACE with a very high range of degree of polymerization, and by SEC, of the CLD of barley starches with different structures show the following. (1) The NaOH treatment, even at a dilute concentration, causes significant degradation at higher degrees of polymerization, leading to quantitatively incorrect CLD results in longer amylopectin and in amylose chains. (2) Certain features in both amylopectin and amylose fractions of the CLD reduced to bumps or are missing with NaOH treatment. (3) Overestimation of amylose chains in starch CLD due to incomplete amylopectin dissolution with dilute NaOH concentration. These results indicate starch dissolution with DMSO-LiBr is the method of choice for minimizing artifacts. An improved pretreatment protocol is presented for starch CLD analysis by FACE and SEC.

The biosynthesis, structure and gelatinization properties of starches from wild and cultivated African rice species (Oryza barthii and Oryza glaberrima)

The molecular structure and gelatinization properties of starches from domesticated African rice (Oryza glaberrima) and its wild progenitor (Oryza barthii) are determined and comparison made with Asian domesticated rice (Oryza sativa), the commonest commercial rice. This suggests possible enzymatic processes contributing to the unique traits of the African varieties. These have similar starch structures, including smaller amylose molecules, but larger amounts of amylose chains across the whole amylose chain-length distribution, and higher amylose contents, than O. sativa. They also show a higher proportion of two- and three-lamellae spanning amylopectin branch chains (degree of polymerization 34-100) than O. sativa, which contributes to their higher gelatinization temperatures. Fitting amylopectin chain-length distribution with a biosynthesis-based mathematical model suggests that the reason for this difference might be because O. glaberrima and O. barthii have more active SSIIIa and/or less active SBEIIb enzymes.

Variation in Caffeine Concentration in Single Coffee Beans

Twenty-eight coffee samples from around the world were tested for caffeine levels to develop near-infrared reflectance spectroscopy (NIRS) calibrations for whole and ground coffee. Twenty-five individual beans from five of those coffees were used to develop a NIRS calibration for caffeine concentration in single beans. An international standard high-performance liquid chromatography method was used to analyze for caffeine content. Coffee is a legal stimulant and possesses a number of heath properties. However, there is variation in the level of caffeine in brewed coffee and other caffeinated beverages. Being able to sort beans on the basis of caffeine concentration will improve quality control in the level of caffeine in those beverages. The range in caffeine concentration was from 0.01 mg/g (decaffeinated coffee) to 19.9 mg/g (Italian coffee). The majority of coffees were around 10.0-12.0 mg/g. The NIRS results showed r(2) values for bulk unground and ground coffees were >0.90 with standard errors <2 mg/g. For the single-bean calibration the r(2) values were between 0.85 and 0.93 with standard errors of cross validation of 0.8-1.6 mg/g depending upon calibration. The results showed it was possible to develop NIRS calibrations to estimate the caffeine concentration of individual coffee beans. One application of this calibration could be sorting beans on caffeine concentration to provide greater quality control for high-end markets. Furthermore, bean sorting may open new markets for novel coffee products.

Improving human health through understanding the complex structure of glucose polymers

AbstractTwo highly branched glucose polymers with similar structures—starch and glycogen—have important relations to human health. Slowly digestible and resistant starches have desirable health benefits, including the prevention and alleviation of metabolic diseases and prevention of colon cancer. Glycogen is important in regulating the use of glucose in the body, and diabetic subjects have an anomaly in their glycogen structure compared with that in healthy subjects. This paper reviews the biosynthesis–structure–property relations of these polymers, showing that polymer characterization produces knowledge which can be useful in producing healthier foods and new drug targets aimed at improving glucose storage in diabetic patients. Examples include mathematical modeling to design starch with better nutritional values, the effects of amylose fine structures on starch digestibility, the structure of slowly digested starch collected from in vitro and in vivo digestion, and the mechanism of the formation of glycogen α particles from β particles in healthy subjects. A new method to overcome a current problem in the structural characterization of these polymers using field-flow fractionation is also given, through a technique to calibrate evaporative light scattering detection with starch. Figureᅟ

Characterization Methods for Starch-Based Materials: State of the Art and Perspectives

Improving starch-containing materials, whether food, animal feed, high-tech biomaterials, or engineering plastics, is best done by understanding how biosynthetic processes and any subsequent processing control starch structure, and how this structure controls functional properties. Starch structural characterization is central to this. This review examines how information on the three basic levels of the complex multi-scale structure of starch – individual chains, the branching structure of isolated molecules, and the way these molecules form various crystalline and amorphous arrangements – can be obtained from experiment. The techniques include fluorophore-assisted carbohydrate electrophoresis, multiple-detector size-exclusion chromatography, and various scattering techniques (light, X-ray, and neutron). Some examples are also given to show how these data provide mechanistic insight into how biosynthetic processes control the structure and how the various structural levels control functional properties.

The Characterization of Modified Starch Branching Enzymes: Toward the Control of Starch Chain-Length Distributions

Starch is a complex branched glucose polymer whose branch molecular weight distribution (the chain-length distribution, CLD) influences nutritionally important properties such as digestion rate. Chain-stopping in starch biosynthesis is by starch branching enzyme (SBE). Site-directed mutagenesis was used to modify SBEIIa from Zea mays (mSBEIIa) to produce mutants, each differing in a single conserved amino-acid residue. Products at different times from in vitro branching were debranched and the time evolution of the CLD measured by size-exclusion chromatography. The results confirm that Tyr352, Glu513, and Ser349 are important for mSBEIIa activity while Arg456 is important for determining the position at which the linear glucan is cut. The mutant mSBEIIa enzymes have different activities and suggest the length of the transferred chain can be varied by mutation. The work shows analysis of the molecular weight distribution can yield information regarding the enzyme branching sites useful for development of plants yielding starch with improved functionality.

New perspectives on the role of α- and β-amylases in transient starch synthesis.

Transient starch in leaves is synthesized by various biosynthetic enzymes in the chloroplasts during the light period. This paper presents the first mathematical model for the (bio)synthesis of the chain-length distribution (CLD) of transient starch to aid the understanding of this synthesis. The model expresses the rate of change of the CLD in terms of the actions of the enzymes involved. Using this to simulate the experimental CLD with different enzyme combinations is a new means to test for enzymes that are significant to the rate of change of the CLD during synthesis. Comparison between the simulated CLD from different enzyme combinations and the experimental CLD in the leaves of the model plant Arabidopsis thaliana indicate α-amylase, in addition to the core starch biosynthetic enzymes, is also involved in the modification of glucans for the synthesis of insoluble starch granules. The simulations suggest involvement of β-amylase, in the absence of α-amylase in mutants, slows the rate of attaining a crystalline-competent CLD for crystallization of glucans to form insoluble starch. This suggests a minor role of β-amylase in shaping normal starch synthesis. The model simulation predicts that debranching of glucans is an efficient mechanism for the attainment of crystalline-competent CLD; however, attaining this is still possible, albeit slower, through combinations of α- and β-amylase in the absence of isoamylase-type debranching enzyme. In Arabidopsis defective in one of the isoamylase-type debranching enzymes, the impact of α-amylase in starch synthesis is reduced, while β-amylase becomes significantly involved, slowing the rate of synthesis in this mutant. Modeling of transient starch CLD brings to light previously unrecognized but significant effects of α- and β-amylase on the rate of transient starch synthesis.

Connecting biochemical photosynthesis models with crop models to support crop improvement

The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward. There has been a long history of development of crop models capable of simulating dynamics of crop physiological attributes. Many crop models incorporate canopy photosynthesis (source) as a key driver for crop growth, while others derive crop growth from the balance between source- and sink-limitations. Modeling leaf photosynthesis has progressed from empirical modeling via light response curves to a more mechanistic basis, having clearer links to the underlying biochemical processes of photosynthesis. Cross-scale modeling that connects models at the biochemical and crop levels and utilizes developments in upscaling leaf-level models to canopy models has the potential to bridge the gap between photosynthetic manipulation at the biochemical level and its consequences on crop productivity. Here we review approaches to this emerging cross-scale modeling framework and reinforce the need for connections across levels of modeling. Further, we propose strategies for connecting biochemical models of photosynthesis into the cross-scale modeling framework to support crop improvement through photosynthetic manipulation.