Simulation of a Petri net-based model of the terpenoid biosynthesis pathway

Abstract

Background: The development and simulation of dynamic models of terpenoid biosynthesis has yielded a systems perspective that provides new insights into how the structure of this biochemical pathway affects compound synthesis. These insights may eventually help identify reactions that could be experimentally manipulated to amplify terpenoid production. In this study, a dynamic model of the terpenoid biosynthesis pathway was constructed based on the Hybrid Functional Petri Net (HFPN) technique. This technique is a fusion of three other extended Petri net techniques, namely Hybrid Petri Net (HPN), Dynamic Petri Net (HDN) and Functional Petri Net (FPN).

Results: The biological data needed to construct the terpenoid metabolic model were gathered from the literature and from biological databases. These data were used as building blocks to create an HFPNe model and to generate parameters that govern the global behaviour of the model. The dynamic model was simulated and validated against known experimental data obtained from extensive literature searches. The model successfully simulated metabolite concentration changes over time (pt) and the observations correlated with known data. Interactions between the intermediates that affect the production of terpenes could be observed through the introduction of inhibitors that established feedback loops within and crosstalk between the pathways.

Conclusions: Although this metabolic model is only preliminary, it will provide a platform for analysing various high-throughput data, and it should lead to a more holistic understanding of terpenoid biosynthesis.

Figure 1

HFPNe entities. Places, transitions and arcs are basic entities in the HFPNe architecture. Places and transitions can be subdivided into continuous, discrete and generic.

Figure 2

Overall sketch of the terpenoid biosynthetic pathways. The entire network is subdivided into MEV and MEP subnetworks, which are placed in different compartments. A rough sketch of the network is shown in A, with the MEV subnetwork on the left and the MEP subnetwork isolated in another compartment on the right. A clearer sketch of the MEV subnetwork is shown in B, and the MEP subnetwork is shown in C. The identified enzymatic and crosstalk mechanisms are shown in the sketches.

Figure 3

The overall layout of the terpenoid biosynthetic pathway model. All metabolites are represented using continous places whereas the regulatory components such as the on/off switches and parameter modulators are represented using generic places. Each transition entity represents a process such as phosphorylation, synthesis and degradation. Each substrate or intermediate is connected to the transition entity by a normal arc whereas an enzyme is connected to its transition entity using a test arc. The MEV subnetwork is on the left and the MEP subnetwork is secluded in a different compartment to depict that the pathway is operative in plastids of eubacterias or chloroplasts or plants.

Figure 4

The MEV and MEP pathway constructed using Cell Illustrator. The pathways are numbered according to sequence, as shown in Tables 1 and 2.

Figure 5

Concentration (unit) changes in metabolites involved in the feedback loop mechanism over time (pt). Oscillations between the concentrations describe how MEVPP production halts when high concentrations of ATP are present and resumes when the concentration of MEVP increases.

Figure 6

Concentration (unit) changes in metabolites involved in the feedback loop mechanism caused by overproduction of FPP over time (pt). The simulation successfully describes how high concentrations of FPP affect the production of MEVP. The oscillatory behaviour also affects the production of sesquiterpenes.

Figure 7

Concentration (unit) changes in metabolites affected by the crosstalk mechanism over time (pt). When the concentration of fosmidomycin increases over time, monoterpene production decelerates at 100 pt; however, a slight increase in sesquiterpene concentration is observed.

Figure 8

Concentration (unit) changes in levels of the main precursors involved in the crosstalk mechanism between both pathways over time (pt). IPP_2 and DMAPP_2 are precursors from the MEP subnetworks, whereas GPP and FPP serve as precursors in the MEV subnetwork. The transfer of fluxes from IPP_2 and DMAPP_2 to the MEV subnetwork enables GPP and FPP to be synthesised and thus produce sesquiterpenes.