Amdoun Ryad, Khelifi Lakhdar, Khelifi-Slaoui Majda, Amroune Samia, Asch Mark, Assaf-Ducrocq Corinne, Gontier Eric
Laboratoire des Ressources Génétiques et Biotechnologie, École Nationale Supérieure Agronomique (ES1603), 16200 El-Harrach, Algiers - Algeria.
Laboratoire des cultures in vitro, Institut National de la Recherche Forestière (INRF), 37 Bp chéraga Bainem, Algiers - Algeria.
Iran J Biotechnol. 2018 Apr 18;16(1):e1339. doi: 10.21859/ijb.1339. eCollection 2018 Apr.
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.
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.
In this article, DOM is used to study the response of hairy roots (HRs), obtained by genetic transformation with A strain, subjected to the jasmonate treatments.
Antagonist effects on the growth and tropane alkaloid biosynthesis are 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.
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.
将期望函数法与响应面法(RSM)相结合,即所谓的期望优化法(DOM),已成功应用于解决医学、化学和技术方面的问题。它在确定涉及不同因素导致拮抗反应的自然或工业过程中的最佳条件时特别有效。
令人惊讶的是,DOM从未应用于致力于研究植物对复杂环境变化的反应以及生物技术问题的研究项目。
在本文中,DOM用于研究用A菌株进行遗传转化获得的毛状根(HRs)对茉莉酸处理的反应。
证实了对生长和托烷生物碱生物合成的拮抗作用。在有限数量的实验条件下,结果表明,施加0.06 mM茉莉酸(JA)24小时可实现最佳折衷。24小时后,莨菪碱水平最多可提高290%,且该处理不会显著抑制生物量生长。
因此证明,使用DOM可以通过最少数量的重复实验有效地实现生物技术过程的优化。