Method for determining gene knockouts
A method for determining candidates for gene deletions and additions using a model of a metabolic network associated with an organism, the model includes a plurality of metabolic reactions defining metabolite relationships, the method includes selecting a bioengineering objective for the organism, selecting at least one cellular objective, forming an optimization problem that couples the at least one cellular objective with the bioengineering objective, and solving the optimization problem to yield at least one candidate.
1. A method for determining candidates for gene deletions and additions using a model of a metabolic network associated with an organism, the method comprising:
providing a model in a computer comprising an electronic representation of a plurality of metabolic reactions defining metabolite relationships;
selecting at least one bioengineering objective function for the organism;
selecting at least one cellular objective function for the organism;
forming a linear optimization problem that couples the at least one cellular objective function with the at least one bioengineering objective function;
executing commands in a suitably programmed computer for solving the linear optimization problem to provide an optimal solution for the bioengineering objective function that simultaneously requires optimality of the cellular objective function and yields at least one candidate gene deletion; and
providing a visual output of the at least one candidate gene deletion to a user.
2. The method of claim 1 further comprising using the at least one candidate to genetically modify the organism.
3. The method of claim 1 wherein the bioengineering objective function is overproduction of a chemical.
4. The method of claim 1 wherein the bioengineering objective function is underproduction of a chemical.
5. The method of claim 1 wherein the cellular objective function is growth.
6. The method of claim 1 wherein the cellular objective is minimization of metabolic adjustment.
7. The method of claim 1 wherein the candidate is a candidate for gene deletion, and the optimization problem includes a binary value for specifying if reaction flux is active or inactive.
8. The method of claim 1 wherein the optimization problem is a bilevel optimization problem.
9. The method of claim 1 wherein the optimization problem is a mixed-integer optimization problem.
10. The method of claim 1 wherein the optimization problem includes at least one stoichiometric constraint.
11. The method of claim 1 wherein the optimization problem includes at least one chemical uptake constraint.
12. The method of claim 1 wherein the step of forming an optimization problem includes quantifying the cellular objective function as an aggregate reaction flux.
13. The method of claim 1 further comprising evaluating performance limits of the metabolic network with the at least one candidate based on ability of the network to meet the at least one cellular objective function.
14. The method of claim 1 wherein the cellular objective function is selected from the group consisting of: maximizing a growth rate, maximizing ATP production, minimizing metabolic adjustment, minimizing nutrient uptake, minimizing redox production, minimizing a Euclidean norm, and combinations thereof.
15. The method of claim 1 wherein the bioengineering objective is overproduction of glycerol and at least one candidate is for gene deletion and comprising genes coding for the enzymes fructose-1,6-bisphosphatase, fructose-1,6-bisphosphatase aldolase, phosphoglycerate kinase, glyceraldehydes-3-phosphate dehydrogenase, phosphoenolpyruvate synthase, NADH dehydrogenase I, phosphogluconate dehydratase, 2-keto-3-deoxy-6-phosphofluconate aldolase, triosphosphate isomerase, glucose 6-phosphate-1-dehydrogenase, 6-phosphogluconolactonase-, deoxyribose-phosphate aldolase, aldehyde dehydrogenase, or combinations thereof.
16. The method of claim 1 wherein the bioengineering objective is overproduction of 1,3-propanediol and at least one candidate is for gene deletion and comprising genes coding for the enzymes fructose-1,6-bisphosphatase, fructose-1,6-bisphosphatase aldolase, phosphoglycerate kinase, glyceraldehyde-3-phosphate dehyrogenase, triosphosphate isomerase, glucose 6-phosphate-1-dehydrogenase, 6-phosphogluconolactonase, deoxyribose-phosphate aldolase, aldehyde dehydrogenase, or combinations thereof.
17. The method of claim 1 wherein the bioengineering objective is overproduction of succinate and at least ape candidate is for gene deletion and comprising genes coding for the enzymes pyruvate formate lyase, acetaldehyde dehydrogenase, pyruvate kinase, FOF1-ATPase, NADH dehydrogenase I, fumarase, D-Lactate dehydrogenase, pyridine nucleotide transhydrogenase, phosphotransacetylase, acetate kinase, phosphotransferase, or combinations thereof.
18. The method of claim 1 wherein the bioengineering objective function is overproduction of lactate and at least one candidate is for gene deletion and comprising genes coding for the enzymes phosphotransacetylase, acetate kinase, phosphofructokinase, fructose-4 1,6-bisphosphatase aldolase, triosphosphate isomerase, acetaldehyde dehyrogenase, glucokinase, or combinations thereof.
19. A computer-based method for determining candidates for gene deletions using a model of a metabolic network associated with an organism, the method comprising:
providing a model in a computer comprising an electronic representation of a plurality of metabolic reactions defining metabolite relationships;
inputting at least one bioengineering objective function;
receiving as input as least one cellular objective function;
forming a linear optimization problem that quantities the at least one cellular objective function as an aggregate reaction flux and couples the at least one cellular objective function with the at least one bioengineering objective function;
executing commands in a suitably programmed computer for solving the linear optimization problem to provide an optimal solution for the bioengineering objective function that simultaneously requires optimality of the cellular objective function and yields at least one candidate gene deletion; and
visually outputting the at least one candidate gene deletion to a user.
20. The method of claim 1 wherein the cellular objective function comprises maximizing a growth rate.
21. The method of claim 1 , further comprising solving the linear optimization problem to yield at least one candidate gene addition.
22. The computer-based method of claim 19 , further comprising solving the linear optimization problem to yield at least one candidate gene addition.