Stochastic modelling of fatty acid biosynthesis Elahe Radmaneshfar 17th July 2015 Rothamsted.

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Stochastic modelling of fatty acid biosynthesis Elahe Radmaneshfar 17th July 2015 Rothamsted

Transcript of Stochastic modelling of fatty acid biosynthesis Elahe Radmaneshfar 17th July 2015 Rothamsted.

Stochastic modelling of fatty acid biosynthesis

Elahe Radmaneshfar17th July 2015

Rothamsted

De novo synthesis and biosynthesis of FA

Plastid

Acyl-CoA pool

16:0-CoA18:0-CoA18:1-CoA

FA Synthesis

Endoplasmic Reticulum

LC-PUFA biosynthesis pathway

Kennedy pathway

TAG

Aims of the model

• Developing a predictive mathematical model which: – can help us understand the mechanism of fatty

acid biosynthesis.– Suggest possibility to improve the production of

fatty acid of our interest (Omega-3)

Challenges for building the model

1. Representation of fatty acids

1 1 1 1 1 1 1 1 1 1 1 1 1 1111111111111

0

1111110111111

Elongation and desaturation in this representation

1111111111111 111111111111111 Elongase

1111111111111 1110111111111 Desaturase

Challenges for building the model

2. LC-PUFA (Long Chain Fatty Acid) biosynthesis pathway is not completely understood.

Tomohito Arao T. and Yamada M., Phaeodactylum Tricornutum, Phytochem 1994;35:1177–1181.

Challenges for building the model

2. LC-PUFA (Long Chain Fatty Acid) biosynthesis pathway is not completely understood.

Hamilton M.L., et alMetab Eng. 2014 Mar; 22(100): 3–9.

Stochastic model

18:0 pool

Elongation

20:0 pool

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool

Desaturation

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool18:1 pool

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool18:1 pool

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool18:1 pool

Model Schematic

Acyl-CoA pool

16:0-CoA18:0-CoA18:1-CoA

Endoplasmic Reticulum

Stochastic modification of

LC-PUFA

18:0 20:0

18:1 20:1

18:2 20:2

18:3 20:3

K influx

K TAG

K e

K d

TAG

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool18:1 pool

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool18:1 pool

Stochastic model

18:0 pool

Elongation

20:0 pool

20:1 pool18:1 pool

TAG

Assumptions of the model• There is just one type of elongase and one type

of desaturase in the model. • There is a minimum of 3 carbon distance

between each double bonds.• Desaturation can continue until a molecule is

fully desaturated.• Elongation can happen until the chain length of

an FA reaches maximum chain length, which is set to 20 for now.

• Every three FA molecules can form a TAG molecule.

Time course of FA production

Time evolutionof intermediate fatty acids

Time evolution of TAG fatty acids

Intermediate fatty acid distribution

TAG fatty acid distribution

Most probable pathways>20%<20%

Parameters effect on

FAs’distribution

Ke /Kd =1, KTAG /Kinflux =0.01 Ke /Kd =0.01, KTAG /Kinflux =1

Influence of parameters on most probable pathways

Ke /Kd =1, KTAG /Kinflux =0.01 Ke /Kd =0.01, KTAG /Kinflux =1

>20%<20%

Parameter influence on the EPA productionIntermediate

EPA

EPA in TAG

(Ke /Kd , KTAG /Kinflux )

Summary

• A stochastic model for biosynthesis of FA has been developed.

• The model demonstrates the influence of different rates (for elongation, desaturation, influx and out flux of a molecule) on the abundance of FA.

• The model can suggest the most probable reactions.

Feature works

• Add 3 (?) different type of desaturase to the model.

• Implement the feedback from TAG/ER(?) to FA pool outside ER.

• A more systematic parameter search.• Search for enzyme parameters via literature

and implement them to the model, maybe adapt the model to prokaryote first?

Intermediate fatty acid distribution

TAG fatty acid distribution

Parameters effect on

FAs’distribution

Ke /Kd =1, KTAG /Kinflux =0.01 Ke /Kd =0.01, KTAG /Kinflux =1

Parameters effect on FA biosynthesis