JOURNAL ARTICLE

Metabolic‐Engineering Approach to Enhance Vanillin and Phenolic Compounds in Ocimum Sanctum (CIM‐Angana) via VpVAN Overexpression.

  • Published In: Physiologia Plantarum, 2024, v. 176, n. 6. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Husain, Zakir; Khan, Sana; Sarfraz, Aqib; Iqbal, Zafar; Chandran, Ashish; Khatoon, Kahkashan; Parween, Gazala; Deeba, Farah; Afroz, Shama; Khan, Feroz; Ch, Ratnasekhar; Rahman, Laiq ur 3 of 3

Abstract

Transgenic Ocimum sanctum plants were engineered to produce vanillin by overexpressing the VpVAN gene using Agrobacterium‐mediated transformation. Positive transformants developed shoots within 4–5 weeks and were transferred to a root induction medium and four independent transformants with no observed adverse effects were kept for anlysis. Quantitative RT‐PCR indicated significantly higher VpVAN expression in transgenic lines AG_3 and AG_1, impacting the phenylpropanoid pathway and phenolic compound accumulation. Molecular docking studies indicated ferulic acid's higher binding affinity to vanillin synthase than eugenol. LC–MS/MS analysis revealed a marked increase in vanillin production in transgenic lines compared to wild type, with AG_3 exhibiting the highest vanillin content (1.98 ± 0.0047 mg/g extract) and AG_1 following (1.49 ± 0.0047 mg/g extract). AG_3 also showed elevated levels of benzoic acid, 4‐hydroxy benzyl alcohol, and ferulic acid. This study highlights the potential of metabolic engineering in O. sanctum for enhanced vanillin production, suggesting pathways for large‐scale production of natural vanillin and other valuable compounds in transgenic plants. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Physiologia Plantarum. 2024/11, Vol. 176, Issue 6, p1
  • Document Type:Article
  • Subject Area:Biology
  • Publication Date:2024
  • ISSN:0031-9317
  • DOI:10.1111/ppl.70005
  • Accession Number:181889276
  • Copyright Statement:Copyright of Physiologia Plantarum is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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