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Biochem Soc Trans. 2017 Aug 15;45(4):885-893. doi: 10.1042/BST20160407. Epub 2017 Jul 3.

Design starch: stochastic modeling of starch granule biogenesis.

Author information

1
Institute of Quantitative and Theoretical Biology, Heinrich-Heine University, Düsseldorf 40225, Germany adelaide.raguin@uni-duesseldorf.de.
2
Institute of Quantitative and Theoretical Biology, Heinrich-Heine University, Düsseldorf 40225, Germany.
3
Cluster of Excellence on Plant Sciences, Institute of Quantitative and Theoretical Biology, Heinrich-Heine University, Düsseldorf 40225, Germany.

Abstract

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.

KEYWORDS:

mathematical models; starch; starch degradation; starch synthesis; stochastic simulations

PMID:
28673938
PMCID:
PMC5652221
DOI:
10.1042/BST20160407
[Indexed for MEDLINE]
Free PMC Article

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