The Desirability Optimization Methodology; a Tool to Predict Two Antagonist Responses in Biotechnological Systems: Case of Biomass Growth and Hyoscyamine Content in Elicited Datura starmonium Hairy Roots

Authors

1 Laboratoire des Ressources Génétiques et Biotechnologie, École Nationale Supérieure Agronomique (ES1603), 16200 El-Harrach, Algiers - Algeria.

2 Laboratoire des Ressources Génétiques et Biotechnologie, École Nationale Supérieure Agronomique (ES1603), 16200

3 Université de Picardie Jules Verne, UFR des Sciences, Laboratoire Amiénois de Mathématique Fondamentale et Appliquée, CNRS-UMR 6140, 33 rue Saint Leu, 80039 Amiens Cedex 1 - France.

4 Unité de Recherche EA3900 BIOPI-UPJV Biologie des plantes et Innovation, Université de Picardie Jules Verne, UFR des Sciences, Ilot des poulies, 33 rue Saint Leu, 80039 Amiens Cedex 1 - France.

Abstract

Background: The use of the desirability function approach combined with the response surface methodology (RSM), also called Desirability Optimization Methodology (DOM), has been successfully applied to solve medical, chemical, and technological questions. It is particularly effi cient for the determination of the optimal conditions in natural or industrial processes involving diff erent factors leading to the antagonist responses.
Objectives: Surprisingly, DOM has never been applied to the research programs devoted to the study of plant responses to the complex environmental changes, and thus to biotechnological questions.
Materials and Methods: In this article, DOM is used to study the response of Datura stramonium hairy roots (HRs), obtained by genetic transformation with Agrobacterium rhizogenes A4 strain, subjected to the jasmonate treatments.
Results: Antagonist eff ects on the growth and tropane alkaloid biosynthesis are confi rmed. With a limited number of experimental conditions, it is shown that 0.06 mM jasmonic acid (JA) applied for 24 h leads to an optimal compromise. Hyoscyamine levels increase by up to 290% after 24 h and this treatment does not significantly inhibit biomass growth.
Conclusions: It is thus demonstrated that the use of DOM can efficiently - with a minimized number of replicates - leads to the optimization of the biotechnological processes.

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