Development of Petri Net-Based Dynamic Model for Improved Production of Farnesyl Pyrophosphate by Integrating Mevalonate and Methylerythritol Phosphate Pathways in Yeast
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  • 作者:Rama Raju Baadhe (1) ramarajub@nitw.ac.in
    Naveen Kumar Mekala (1)
    Satwik Reddy Palagiri (2)
    Sreenivasa Rao Parcha (1)
  • 关键词:Amorpha diene &#8211 ; Artemisinin &#8211 ; Farnesyl pyrophosphate &#8211 ; Hybrid functional Petri net with extensions &#8211 ; Methylerythritol phosphate pathway &#8211 ; Mevalonate Pathway
  • 刊名:Applied Biochemistry and Biotechnology
  • 出版年:2012
  • 出版时间:July 2012
  • 年:2012
  • 卷:167
  • 期:5
  • 页码:1172-1182
  • 全文大小:571.2 KB
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  • 作者单位:1. Department of Biotechnology, National Institute of Technology, Warangal, India2. Arkabio Research Technologies, Hyderabad, India
  • ISSN:1559-0291
文摘
In this case study, we designed a farnesyl pyrophosphate (FPP) biosynthetic network using hybrid functional Petri net with extension (HFPNe) which is derived from traditional Petri net theory and allows easy modeling with graphical approach of various types of entities in the networks together. Our main objective is to improve the production of FPP in yeast, which is further converted to amorphadiene (AD), a precursor of artemisinin (antimalarial drug). Natively, mevalonate (MEV) pathway is present in yeast. Methyl erythritol phosphate pathways (MEP) are present only in higher plant plastids and eubacteria, but not present in yeast. IPP and DAMP are common isomeric intermediate in these two pathways, which immediately yields FPP. By integrating these two pathways in yeast, we augmented the FPP synthesis approximately two folds higher (431.16 U/pt) than in MEV pathway alone (259.91 U/pt) by using HFPNe technique. Further enhanced FPP levels converted to AD by amorphadiene synthase gene yielding 436.5 U/pt of AD which approximately two folds higher compared to the AD (258.5 U/pt) synthesized by MEV pathway exclusively. Simulation and validation processes performed using these models are reliable with identified biological information and data.

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