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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- Baadhe, R.R., Mekala, N.K., Palagiri, S.R. et al. Appl Biochem Biotechnol (2012) 167: 1172. doi:10.1007/s12010-012-9583-1
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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.
KeywordsAmorpha dieneArtemisininFarnesyl pyrophosphateHybrid functional Petri net with extensionsMethylerythritol phosphate pathwayMevalonate Pathway
Hybrid functional Petri net with extension
Over the last few years, usage of terpenoids has increased exponentially in medicine and aromatics. They offer a viable commercial alternative to chemically synthesized products of similar use. Terpenoids are typically extracted from plants  and microorganisms. Terpenoids, being secondary metabolites, produced in very small quantities and scale up with existing plant and microorganism strains  are not cost effective. With commercial and medicinal uses of plant terpenoids on the rise, there is a need to increase the yield of terpenoid biosynthesis. Development of simulated models will diminish the troubleshooting and points the bottlenecks during the experimentation by understanding the relation between the complex biological pathway structures and dynamics of the system . Various computational, mathematical, and Perti net models are developed in order to understand the relation between numerous pathways. This gives thorough observation of the troubleshoots, which solved easily or should find the alternatives [4–6]. In addition to this, flux analysis enables us to estimate and enumerate the flow of carbon and energy within a given system of bioprocesses. Flux analysis helps not only to build a better target model but also to eliminate unwanted side effects that might potentially be encountered in engineered organisms .
Biological pathways fall under three categories: gene regulatory networks, metabolic pathways, and signaling pathways  whose behavior widely described using methods like ordinary differential equations (ODEs), partial differential equations (PDEs) and non-ODE approaches [9, 10]. The present model deals with metabolic pathways and explains the improved production of farnesyl pyrophosphate (FPP), an intermediate for all major isoprenoids or terpenoids synthesis through two independent pathways (mevalonate (MEV) and non mevalonate (MEP)) in yeast. The MEV pathway is frequently found in the eukaryotic cytoplasm, while the MEP pathway is observed in the eubacteria such as Escherichia coli and Streptomyces cerevisiae [11, 12] as well as in plant plastids. The MEP pathway is not found in animals or fungi, but both pathways are operational in higher-level plants such as Arabidopsis thaliana and Helianthus annuus and Artemisia annua .
In this case study, we designed a 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. A Petri net is a graphical diagram consisting of circles and lines representing the current status of a rule-based state-dependent procedural system. For this reason, a Petri net is also called a place transition network. To support more complicated networks with varying degrees and kinds of control structures, HFPNe are used .These networks support concepts essential to pathway design like quantitative (equation or value based) induction, inhibition, and repression. Petri net offers a versatile graphical language to design, integrate, and simulate multiple pathway networks . Petri nets are suitable because of their intuitive graphical representation and their capabilities for mathematical analyses. Prospect to find out new option for amplifying the production of FPP was our major objective, which can be further utilized to synthesize variety of isoprenoids having medical as well as industrial importance.
Resources and Methods
The information and data desirable to build this model was obtained from biological databases: KEGG, BRENDA, ENZYME, IUBMB, MetaCyc, and PATHWAYDATABASE [17–21]. These databases include information on the substrates, products, enzyme consumption, and production rates involved in the MEV and MEP pathways. Along with the above data, stoichiometric and enzyme mechanisms are also taken into consideration in developing the dynamic model. This information was used to design the model layout and parameter assignments for each of the HFPNe elements.
Model Pattern Design
Developmental stages as well as the simulation and validation processes of the model were carried out using Cell Illustrator 5.0 www.cellillustrator.com (developed by Human genome center, Institute of medical science. The University of Tokyo, Japan).
Simulation and Validation
Conventional production of FPP through the MEV pathway.
Conventional production of GPP2 through the MEP pathway.
Combined production of FPP through integrated MEV and MEP pathways.
Production of amorphadiene through integrated MEV and MEP pathways.
Simulation results were calculated as concentration (unit) versus time (pt) graphs. Petri net time (pt) indicates virtual Petri net time that do not match to real time; concentration also is given in general concentration units (unit) that do not specifically correspond to standard concentration units such as mM and μM. The changes in metabolite concentrations (unit), over time predicted by each simulation were confirmed against known biological data to identify breaks and variations. Unmatched biological processes were re-examined and previous developmental steps (pattern design and parameter assignment) were repeated. The simulation process was then reexecuted and revalidated using cell illustrator. The entire process was carried out repetitively in order to rule out contradictions and obtain a best possible system.
Results and Discussion
Outlines of the Model
Conventional Production of FPP Through the MEV Pathway
Conventional Production of GPP2 Through the MEP Pathway
Combined Production of FPP Through Integrated MEV and MEP Pathways
Production of Amorphadiene Through Integrated MEV and MEP Pathways
HFPNe technique enables complicated modeling tasks to be viewed and solved in a graphical manner. The model serves as a tool to better understand the reactions involved in combinatorial FPP synthesis and how they interact to each other. This gives needful information for finding the alternatives for production of isoprenoids. Apart from this, most of the acetyl-CoA in the MEV pathway is either transported from the cytosol into the mitochondrion for oxidization by TCA cycle or utilized in fatty acid and ergosterol synthesis. Channeling more acetyl-CoA into the mevalonate pathway by limiting acetyl-CoA transport to the mitochondrion or inhibiting ethanol and fatty acid synthesis, it can be possible to further increase the FPP production which is having tremendous significance in chemical industry and medicine.