Monday, 22 March 2010

Predicting Novel Metabolic Pathways in Genome-Scale Networks.

Stefan Schuster

Need systematic methods.

Decompose network into pathways. Need stoichiometries and reversibility.
Elementary modes are minimum sets of enzymes that can operate at steady state. Enzymes are weigted by their flux. Clipping of complete space for irreversibility to create a pyramid in high dimensions.

A connected route is not enough to infer a process occurs at steady state you need to do elementary mode analysis. Bioinformatics Schuster paper and discussion with other group. Other group defending graph theoretical models.

All metabolites that are involved in more than 4 reactions are specified as external metabolites.

Genome Research 19 2009 1872-1883 can work on sub-systems of the complete genome model so long as you perform a consistency check.

Modularity reduces the combinatorial problem of checking networks for all elementary modes. Not consistent if in the complete model the reagants used in the synthesis of a product are generated by the subsequent reactions of the product.

Cell Signalling in Space and Time


Src gradients are the same as Belousov Zhabotinsky. Bistable switches - hysteresis - different paths for the up and down cycles.

Problems with kinase cascades in large cells as these signals are opposed by phosphatases in the cytoplasm. Munoz-Garcia PLoS Comp Biol 5 e1000330

Solution to the French Flag problem for size does the signal propagate to the nucleus? If it does not then the cell is too large.

Moonlighting signalling the same as moonlighting enzymes. Wave front propagation as this makes fast signalling - reaction diffusion much faster than diffusion.

Different signals are obtained from different temporal profiles even if they use the same kinase pathway Marshall C.J. Cell 80 179-185. 1995.

Modelling does not always help understanding why is there different transient activity and not persistent vs transient actvity? Nakakuki et al Cell in Press

Analysing Genome Scale Metabolic Models

David Fell

Create the soichiometry matrix for the complete metablism from the reaction lists from the annotated genomes. Then you can work out the null space matrix for the steady states (actually superset of steady states) which corresponds to the matrix which when multiplied by the stoichiometric matrix will give you the vertical matrix of the velocities (all zero at the steady states).
Calculate complete picture of fluxes at steady state by measuring some fluxes, and using these as multiplier of the  Flux analysis. Can simplify the matrix for those rows that are the same in the null space. Can also remove rows where they are all zero as these are dead enzymes in the steady state. Then you can add extra constraints - Pallson's Flux Balance Analysis.

When using a cost function it is called linear programming.

[Mathematically you could use Lagrangian Multipliers to test cost function and where it intersects with model space.]

  • Transport - need to find which molecules can be exchanged with the environment - genome analysis should reveal this.
  • Need to check for mass balance
  • Remove dead reactions
  • ScrumPy tests the stoichiometry matrix
  • Use PRIAM to improve annotation
  • Use simulated annealing to sample EC classification when it is ambiguous