4.0 Article

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

Journal

IRANIAN JOURNAL OF BIOTECHNOLOGY
Volume 16, Issue 1, Pages 11-19

Publisher

NATL INST GENETIC ENGINEERING & BIOTECHNOLOGY
DOI: 10.21859/ijb.1339

Keywords

Desirability Optimization Methodology (DOM); Hyoscyamine; Jasmonic Acid; Multiresponse Optimization; Response Surface Methodology (RSM)

Funding

  1. ENSA of Algiers
  2. Algerian Ministry of High Education and Research (MESRS)
  3. University of Picardie Jules Verne, Amiens, France

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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 efficient for the determination of the optimal conditions in natural or industrial processes involving different 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 A(4) strain, subjected to the jasmonate treatments. Results: Antagonist effects on the growth and tropane alkaloid biosynthesis arc confirmed. 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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