IP Library Granted Patent US 7,650,242
Granted Patent B2
US 7,650,242 · App. 10/043,440 · Granted Jan 19, 2010

Method and system for modeling cellular metabolism

Assignee: The Penn State Research Foundation
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Quick Facts
Patent No.
US 7,650,242
App. No.
10/043,440
Granted
Jan 19, 2010
Kind
B2
Abstract

This invention relates to methods and systems for in silico or bioinformatic modeling of cellular metabolism. The invention includes methods and systems for modeling cellular metabolism of an organism, comprising constructing a flux balance analysis model, and applying constraints to the flux balance analysis model, the constraints selected from the set consisting of: qualitative kinetic information constraints, qualitative regulatory information constraints, and differential DNA microarray experimental data constraints. In addition, the present invention provides for computational procedures for solving metabolic problems.

Claims (54)

1. A method for modeling cellular metabolism of an organism, comprising:

constructing on a computer a flux balance analysis model utilizing stoichiometric mass balances of metabolic and cellular composition information of the organism to identify stoichiometric boundaries for available flux distributions of a metabolic network;

applying logic constraints comprising a regulation matrix to the flux balance analysis model to produce an altered flux balance analysis model, wherein said logic constraints constrain one of said identified stoichiometric boundaries for one of said available flux distributions, wherein said altered flux balance analysis model has improved predictive capabilities of cellular metabolism of the organism over said flux balance analysis model and thereby provides a model of cellular metabolism of the organism; and

providing an output to a user of said available flux distribution having said constrained stoichiometric boundary.

2. The method of claim 1 wherein the logic constraints are capable of protecting against violation of a kinetic barrier.

3. The method of claim 1 wherein the logic constraints further include a set of connectivity restraints.

4. The method of claim 1 further comprising the step of applying mixed-integer linear programming to said altered flux balance analysis model having improved predictive capabilities to solve for a desired metabolic outcome.

5. The method of claim 1 further comprising the step of solving for a desired metabolic outcome.

6. The method of claim 1 wherein the logic constraints further include qualitative regulatory information constraints.

7. The method of claim 6 wherein the logic constraints protect against violation of a regulatory barrier.

8. The method of claim 1 wherein the logic constraints further include DNA microarray experimental data constraints.

9. A method for modeling cellular metabolism of an organism that improves upon a flux balance analysis model, comprising:

constructing on a computer the flux balance analysis model utilizing stoichiometric mass balances of metabolic and cellular composition information of the organism to identify stoichiometric boundaries for available flux distributions of a metabolic network;

applying a plurality of logic constraints comprising a regulation matrix to the flux balance analysis model to produce an altered flux balance analysis model, wherein said plurality of logic constraints constrain one of said identified stoichiometric boundaries for one of said available flux distributions, wherein said altered flux balance analysis model has improved predictive capabilities of cellular metabolism of the organism over said flux balance analysis model and thereby provides a model of cellular metabolism of the organism; and

providing an output to a user of said available flux distribution having said constrained stoichiometric boundary.

10. The method of claim 9 , further comprising selecting the set of logic constraints to protect against violation of a kinetic or regulatory barrier.

11. The method of claim 9 wherein the logic constraints are defined by a relationship between changes in reaction fluxes and metabolic concentrations.

12. The method of claim 9 wherein the logic constraints are represented by binary variables.

13. The method of claim 12 wherein a first binary variable represents the presence of a reaction and a second binary variable represents the absence of a reaction.

14. The method of claim 9 further comprising applying a computational procedure to identify a minimal set of metabolic reactions.

15. The method of claim 14 further comprising selecting a growth rate, and wherein the step of applying a computational procedure is applying a computational procedure to identify the minimal set of metabolic reactions capable of supporting the growth rate.

16. The method of claim 9 further comprising the step of applying mixed-integer linear programming to said altered flux balance analysis model having improved predictive capabilities to solve for a desired metabolic outcome.

17. The method of claim 9 further comprising the step of solving for a desired metabolic outcome.

18. The method of claim 17 further comprising engineering a change in an organism to produce the desired metabolic outcome.

19. A system for modeling cellular metabolism of an organism, comprising:

a flux balance analysis model utilizing stoichiometric mass balances of metabolic and cellular composition information of the organism to identify stoichiometric boundaries for available flux distributions of a metabolic network;

a plurality of logic constraints comprising a regulation matrix applied to the flux balance analysis model, the logic constraints selected from the set consisting of qualitative kinetic information constraints, qualitative regulatory information constraints, and differential DNA microarray experimental data constraints; and

commands for execution on a computer for producing an altered flux balance analysis model wherein said plurality of logic constraints constrain one of said identified stoichiometric boundaries for one of said available flux distributions, wherein said altered flux balance analysis model has improved predictive capabilities of cellular metabolism of the organism over said flux balance analysis model and thereby provides a model of cellular metabolism of the organism.

20. The system of claim 19 , wherein said constraints comprise qualitative kinetic information constraints.

21. The system of claim 19 , wherein said constraints comprise qualitative regulatory information constraints.

22. The system of claim 19 , wherein said constraints comprise differential DNA microarray experimental data constraints.

23. A method for modeling cellular metabolism of an organism, comprising:

constructing on a computer a flux balance analysis model of a metabolic network of the organism;

applying constraints to the flux balance analysis model, wherein the constraints include qualitative kinetic information constraints, qualitative regulatory information constraints, differential DNA microarray experimental data constraints, or a combination thereof;

producing an altered flux balance analysis model wherein said constraints constrain a stoichiometric boundary for an available flux distribution, wherein said altered flux balance analysis model has improved predictive capabilities of cellular metabolism of the organism over said flux balance analysis model and thereby provides a model of cellular metabolism of the organism; and

providing an output to a user of said available flux distribution having said constrained stoichiometric boundary.

24. The method of claim 23 wherein the constraints include logic constraints to protect against violation of a regulatory barrier.

25. The method of claim 23 wherein the constraints further include connectivity restraints.

26. The method of claim 23 further comprising applying mixed-integer linear programming to said altered flux balance analysis model having improved predictive capabilities to solve for a desired metabolic outcome.

27. The method of claim 23 further comprising solving for a desired metabolic outcome.

28. The method of claim 23 , wherein said constraints include qualitative kinetic information constraints.

29. The method of claim 23 , wherein said constraints include qualitative regulatory information constraints.

30. The method of claim 23 , wherein said constraints include differential DNA microarray experimental data constraints.

31. A method for modeling cellular metabolism of an organism that improves upon a flux balance analysis model, comprising:

constructing on a computer the flux balance analysis model utilizing stoichiometric mass balances of metabolic and cellular composition information of the organism to identify stoichiometric boundaries for available flux distributions of a metabolic network;

applying a plurality of logic constraints comprising a regulation matrix to the flux balance analysis model to produce an altered flux balance analysis model, wherein said plurality of logic constraints constrain one of said identified stoichiometric boundaries for one of said available flux distributions, wherein said altered flux balance analysis model has improved predictive capabilities of cellular metabolism of the organism over said flux balance analysis model; applying mixed-integer linear programming to said altered flux balance analysis model having improved predictive capabilities to solve for a desired metabolic outcome of the altered flux balance analysis model, thereby modeling cellular metabolism of the organism; and

providing an output to a user of the application of mixed-integer linear programming to solve for a desired metabolic outcome.

32. The method of claim 31 further comprising the step of solving for the desired metabolic outcome.

33. The method of claim 32 further comprising engineering a change in the organism to produce the desired metabolic outcome.

34. A method for modeling cellular metabolism of an organism, comprising:

constructing on a computer a flux balance analysis model using stoichiometric mass balances of metabolic and cellular composition information of the organism to identify stoichiometric boundaries for available flux distributions of a metabolic network;

determining logic constraints comprising a regulation matrix to apply to the flux balance analysis model, the logic constraints based on qualitative relationships between changes in reaction fluxes and changes in metabolite concentrations;

applying the logic constraints to the flux balance analysis model to produce an altered flux balance analysis model, wherein said logic constraints constrain one of said identified stoichiometric boundaries for one of said available flux distributions, wherein said altered flux balance analysis model has improved predictive capabilities of cellular metabolism of the organism over said flux balance analysis model and thereby provides a model of cellular metabolism of the organism; and

providing an output to a user of said available flux distribution having said constrained stoichiometric boundary.

Assignments (2)
CONFIRMATORY LICENSE Recorded May 20, 2010
From: THE PENNSYLVANIA STATE UNIVERSITY
To: NATIONAL SCIENCE FOUNDATION
Reel/Frame 024414/0050 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 29, 2002
From: MARANAS, COSTAS D.; BURGARD, ANTHONY P.
To: PENN STATE RESEARCH FOUNDATION, THE
Reel/Frame 012848/0554 →
Continuity (3)
Provisional Application 6026071300 · Jan 10, 2001
Provisional Application 6027853500 · Mar 23, 2001
Related Publication 20020168654A1 · Nov 14, 2002