Enzyme kinetic approach for mechanistic insight and predictions of in vivo starch digestibility and the glycaemic index of foods

Peter J. Butterworth, Balazs H. Bajka, Cathrina H. Edwards, Frederick J. Warren, Peter R. Ellis

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)
165 Downloads (Pure)

Abstract

Background: Starch is a principal dietary source of digestible carbohydrate and energy. Glycaemic and insulinaemic responses to foods containing starch vary considerably and glucose responses to starchy foods are often described by the glycaemic index (GI) and/or glycaemic load (GL). Low GI/GL foods are beneficial in the management of cardiometabolic disorders (e.g., type 2 diabetes, cardiovascular disease). Differences in rates and extents of digestion of starch-containing foods will affect postprandial glycaemia. Scope and approach: Amylolysis kinetics are influenced by structural properties of the food matrix and of starch itself. Native (raw) semi-crystalline starch is digested slowly but hydrothermal processing (cooking) gelatinises the starch and greatly increases its digestibility. In plants, starch granules are contained within cells and intact cell walls can limit accessibility of water and digestive enzymes hindering gelatinisation and digestibility. In vitro studies of starch digestion by α-amylase model early stages in digestion and can suggest likely rates of digestion in vivo and expected glycaemic responses. Reports that metabolic responses to dietary starch are influenced by α-amylase gene copy number, heightens interest in amylolysis. Key findings and conclusions: This review shows how enzyme kinetic strategies can provide explanations for differences in digestion rate of different starchy foods. Michaelis-Menten and Log of Slope analyses provide kinetic parameters (e.g., K m and k cat/K m) for evaluating catalytic efficiency and ease of digestibility of starch by α-amylase. Suitable kinetic methods maximise the information that can be obtained from in vitro work for predictions of starch digestion and glycaemic responses in vivo.

Original languageEnglish
Pages (from-to)254-264
Number of pages11
JournalTrends In Food Science & Technology
Volume120
Early online date23 Dec 2021
DOIs
Publication statusPublished - Feb 2022

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