Articles of manufacture and methods for modeling
View Patent ↗The invention provides an in silico model for determining a S. cerevisiae physiological function. The model includes a data structure relating a plurality of S. cerevisiae reactants to a plurality of S. cerevisiae reactions, a constraint set for the plurality of S. cerevisiae reactions, and commands for determining a distribution of flux through the reactions that is predictive of a S. cerevisiae physiological function. A model of the invention can further include a gene database containing information characterizing the associated gene or genes. The invention further provides methods for making an in silico S. cerevisiae model and methods for determining a S. cerevisiae physiological function using a model of the invention.
1. A computer readable storage medium or media, comprising:
(a) a data structure contained on a computer readable storage medium or media that is read by a computer, said data structure comprising a stoichiometric matrix relating a plurality of Saccharomyces cerevisiae reactants to a plurality of Saccharomyces cerevisiae reactions, wherein each of said Saccharomyces cerevisiae reactions comprises a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product, wherein at least one of said Saccharomyces cerevisiae reactions is annotated to indicate an associated gene, and wherein a plurality of chemically and electrochemically balanced reactions are assigned to a plurality of different membranous compartments;
(b) a gene database comprising information characterizing said associated gene;
(c) a constraint set for said plurality of Saccharomyces cerevisiae reactions;
(d) a program contained on said computer readable storage medium or media comprising executable commands using said data structure for determining at least one flux distribution for said plurality of chemically and electrochemically balanced reactions across said plurality of different membranous compartments that minimizes or maximizes an objective function when said constraint set is applied to said data structure, wherein said at least one flux distribution is predictive of a Saccharomyces cerevisiae physiological function, and
(e) said program contained on said computer readable storage medium or media comprising executable commands for visually displaying said at least one resulting flux distribution to a user.
2. The computer readable storage medium or media of claim 1 , wherein said plurality of reactions comprises at least one reaction from a peripheral metabolic pathway.
3. The computer readable storage medium or media of claim 2 , wherein said peripheral metabolic pathway is selected from the group consisting of amino acid biosynthesis, amino acid degradation, purine biosynthesis, pyrimidine biosynthesis, lipid biosynthesis, fatty acid metabolism, cofactor biosynthesis, cell wall metabolism and transport processes.
4. The computer readable storage medium or media of claim 1 , wherein said Saccharomyces cerevisiae physiological function is selected from the group consisting of growth, energy production, redox equivalent production, biomass production, production of biomass precursors, production of a protein, production of an amino acid, production of a purine, production of a pyrimidine, production of a lipid, production of a fatty acid, production of a cofactor, production of a cell wall component, transport of a metabolite, and consumption of carbon, nitrogen, sulfur, phosphate, hydrogen or oxygen.
5. The computer readable medium or media of claim 1 , wherein said Saccharomyces cerevisiae physiological function is selected from the group consisting of degradation of a protein, degradation of an amino acid, degradation of a purine, degradation of a pyrimidine, degradation of a lipid, degradation of a fatty acid, degradation of a cofactor and degradation of a cell wall component.
6. The computer readable medium or media of claim 1 , wherein said data structure comprises a set of linear algebraic equations.
7. The computer readable storage medium or media of claim 1 , wherein said commands comprise an optimization problem.
8. The computer readable medium or media of claim 1 , wherein said commands comprise a linear program.
9. The computer readable storage medium or media of claim, wherein a first substrate or product in said plurality of Saccharomyces cerevisiae reactions is assigned to a first compartment and a second substrate or product in said plurality of Saccharomyces cerevisiae reactions is assigned to a second compartment.
10. The computer readable storage medium or media of claim 1 , wherein a plurality of said Saccharomyces cerevisiae reactions is annotated to indicate a plurality of associated genes and wherein said gene database comprises information characterizing said plurality of associated genes.
11. A computer readable medium or media, comprising:
(a) a data structure relating a plurality of Saccharomyces cerevisiae reactants to a plurality of Saccharomyces cerevisiae reactions, wherein each of said Saccharomyces cerevisiae reactions comprises a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product;
(b) a constraint set for said plurality of Saccharomyces cerevisiae reactions, and
(c) commands for determining at least one flux distribution that minimizes or maximizes an objective function when said constraint set is applied to said data representation, wherein said at least one flux distribution is predictive of Saccharomyces cerevisiae growth.
12. A method for predicting a Saccharomyces cerevisiae physiological function, comprising:
(a) storing in a computer a data structure relating a plurality of Saccharomyces cerevisiae reactants to a plurality of reactions, wherein each of said Saccharomyces cerevisiae reactions comprises a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product, wherein at least one of said Saccharomyces cerevisiae reactions is annotated to indicate an associated gene, and wherein a plurality of chemically and electrochemically balanced reactions are assigned to a plurality of different membranous compartments;
(b) providing a constraint set for said plurality of Saccharomyces cerevisiae reactions;
(c) providing an objective function;
(d) executing commands in a suitably programmed computer using said stored data structure for determining at least one flux distribution for said plurality of chemically and electrochemically balanced reactions across said plurality of different membranous compartments that minimizes or maximizes said objective function when said constraint set is applied to said data structure, wherein said at least one flux distribution is predictive of a Saccharomyces cerevisiae physiological function related to said gene, and
(e) visually displaying said at least one resulting flux distribution to a user.
13. The method of claim 12 , wherein said plurality of Saccharomyces cerevisiae reactions comprises at least one reaction from a peripheral metabolic pathway.
14. The method of claim 12 , wherein said peripheral metabolic pathway is selected from the group consisting of amino acid biosynthesis, amino acid degradation, purine biosynthesis, pyrimidine biosynthesis, lipid biosynthesis, fatty acid metabolism, cofactor biosynthesis, cell wall metabolism and transport processes.
15. The method of claim 12 , wherein said Saccharomyces cerevisiae physiological function is selected from the group consisting of growth, energy production, redox equivalent production, biomass production, production of biomass precursors, production of a protein, production of an amino acid, production of a purine, production of a pyrimidine, production of a lipid, production of a fatty acid, production of a cofactor, production of a cell wall component, transport of a metabolite, and consumption of carbon, nitrogen, sulfur, phosphate, hydrogen or oxygen.
16. The method of claim 12 , wherein said Saccharomyces cerevisiae physiological function is selected from the group consisting of glycolysis, the TCA cycle, pentose phosphate pathway, respiration, biosynthesis of an amino acid, degradation of an amino acid, biosynthesis of a purine, biosynthesis of a pyrimidine, biosynthesis of a lipid, metabolism of a fatty acid, biosynthesis of a cofactor, metabolism of a cell wall component, transport of a metabolite and metabolism of a carbon source, nitrogen source, oxygen source, phosphate source, hydrogen source or sulfur source.
17. The method of claim 12 , wherein said data structure comprises a set of linear algebraic equations.
18. The method of claim 12 , wherein said data structure comprises a matrix.
19. The method of claim 12 , wherein said flux distribution is determined by linear programming.
20. The method of claim 12 , further comprising:
(f) providing a modified data structure, wherein said modified data structure comprises at least one added reaction, compared to the data structure of part (a), and
(f) determining at least one flux distribution that minimizes or maximizes said objective function when said constraint set is applied to said modified data structure, thereby predicting a Saccharomyces cerevisiae physiological function.
21. The method of claim 20 , further comprising identifying at least one participant in said at least one added reaction.
22. The method of claim 21 , wherein said identifying at least one participant comprises associating a Saccharomyces cerevisiae protein with said at least one reaction.
23. The method of claim 22 , further comprising identifying at least one gene that encodes said protein.
24. The method of claim 21 , further comprising identifying at least one compound that alters the activity or amount of said at least one participant, thereby identifying a candidate drug or agent that alters a Saccharomyces cerevisiae physiological function.
25. The method of claim 12 , further comprising:
(f) providing a modified data structure, wherein said modified data structure lacks at least one reaction compared to the data structure of part (a), and
(g) determining at least one flux distribution that minimizes or maximizes said objective function when said constraint set is applied to said modified data structure, thereby predicting a Saccharomyces cerevisiae physiological function.
26. The method of claim 25 , further comprising identifying at least one participant in said at least one reaction.
27. The method of claim 26 , wherein said identifying at least one participant comprises associating a Saccharomyces cerevisiae protein with said at least one reaction.
28. The method of claim 27 , further comprising identifying at least one gene that encodes said protein that performs said at least one reaction.
29. The method of claim 26 , further comprising identifying at least one compound that alters the activity or amount of said at least one participant, thereby identifying a candidate drug or agent that alters a Saccharomyces cerevisiae physiological function.
30. The method of claim 12 , further comprising:
(f) providing a modified constraint set, wherein said modified constraint set comprises a changed constraint for at least one reaction compared to the constraint for said at least one reaction in the data structure of part (a), and
(g) determining at least one flux distribution that minimizes or maximizes said objective function when said modified constraint set is applied to said data structure, thereby predicting a Saccharomyces cerevisiae physiological function.
31. The method of claim 30 , further comprising identifying at least one participant in said at least one reaction.
32. The method of claim 31 , wherein said identifying at least one participant comprises associating a Saccharomyces cerevisiae protein with said at least one reaction.
33. The method of claim 32 , further comprising identifying at least one gene that encodes said protein.
34. The method of claim 31 , further comprising identifying at least one compound that alters the activity or amount of said at least one participant, thereby identifying a candidate drug or agent that alters a Saccharomyces cerevisiae physiological function.
35. The method of claim 12 , further comprising providing a gene database relating one or more reactions in said data structure with one or more genes or proteins in Saccharomyces cerevisiae.
36. A method for predicting Saccharomyces cerevisiae growth, comprising:
(a) storing in a computer a data structure relating a plurality of Saccharomyces cerevisiae reactants to a plurality of Saccharomyces cerevisiae reactions, wherein each of said Saccharomyces cerevisiae reactions comprises a reactant identified as a substrate of the reaction, a reactant identified as a product of the reaction and a stoichiometric coefficient relating said substrate and said product;
(b) providing a constraint set for said plurality of Saccharomyces cerevisiae reactions;
(c) providing an objective function, and
(d) executing commands in a suitably programmed computer using said stored data structure to determine at least one flux distribution that minimizes or maximizes said objective function when said constraint set is applied to said data structure, thereby predicting Saccharomyces cerevisiae growth.