Rational identification of target enzymes for starch improvement through system-level analysis of a potato tuber model

Abstract

In this study, identification of target enzymes for starch improvement through system-level analysis of a potato tuber model is presented. A kinetic model representing the conversion of sucrose to starch in potato tubers was employed. This model was used to predict the percentage of amylose content (AC%) and starch content in potato tubers in response to perturbations of enzyme activities. The predicted AC% (23%) was found to be in the range of the actual AC% reported in literature. The model could satisfactorily predict the response trend to down-regulation of enzymes on the starch content and AC% (Pearson's correlation coefficients > 0.9). To identify the target enzymes, the sensitivity of starch content and AC% to changes in the activity of each enzyme within the model was assessed by sensitivity analysis. The enzymes identified as targets were those to which starch content and AC% were found to be highly sensitive. The analysis revealed that the targets for increasing the starch content in potato tubers were inorganic pyrophosphatase (iPPtase), starch synthase (SS), granule-bound starch synthase (GBSS), and ADP-glucose pyrophosphorylase. Also, SS and GBSS were found to be targets for altering AC%. By dual perturbation studies, the increase of activities of both iPPtase and SS simultaneously was found to further improve the starch content. In addition, the model was applied to predict relative changes in tuber metabolite profiles to infer physiological changes of metabolically-engineered tubers. The suggested target enzymes and inferred tuber physiology are useful guidelines for rational metabolic engineering towards starch improvement in potatoes.