Project 2 Flux Balance Analysis of Mitochondria Energy Metabolism Suresh Gudimetla Salil Pathare.

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Project 2 Flux Balance Analysis of Mitochondria Energy Metabolism Suresh Gudimetla Salil Pathare

Objective Objective To characterize the optimal flux distributions for maximal Adrenosine Triphosphate(ATP) production in the mitochondrion using flux balance analysis.

Introduction Mitochondrial metabolism is a critical component in the functioning and maintenance of cellular organs It has a significant role in the functions of aerobic organs and other organs such as liver and brain.

Mitochondrial metabolism results the genetic content can lead to change from the action of several biochemical reactions. Mutation can lead to changes in enzyme expression. This may alter the mitochondrial function by changing fluxes of important metabolic reactions

The biochemical reactions involved function as a coordinated network subject to stoichoimetry and regulatory constraints. The objective of this study was to develop a model for mitochondrial function

F undamentals of flux balance analysis The fundamental principle underlying FBA is the conservation of mass. A flux balance can be written for each metabolite (X i ) within a metabolic system to yield the mass equations. A steady state assumption is made which states that the formation fluxes are balanced by degradation fluxes.

Dynamic flux balances dx/dt = S*v – b v = fn(X,…..) Where X = metabolite concentrations S = stoichiometric matrix v = metabolism reaction fluxes b = net transport out of network

FBA postulates that the metabolic system exhibits a metabolic state that is optimal under some criteria. This objective is expressed as a linear combination of fluxes contained in v

MODEL The model is formulated as a linear programming problem as follows Minimize(maximize) Z = c i v i Such that S * v – b = 0 0 <= B i <= v i <= a i

Z is the objective function, representing a phenotype property, and c is a vector that are either costs of or benefits derived from the fluxes. The limits of a i and B i represent known constraints on the maximum or minimum values that the fluxes assume. When the maximization of ATP production is considered, the net flux of ATP hydrolysis is maximized Z is the objective function, representing a phenotype property, and c is a vector that are either costs of or benefits derived from the fluxes. The limits of a i and B i represent known constraints on the maximum or minimum values that the fluxes assume. When the maximization of ATP production is considered, the net flux of ATP hydrolysis is maximized

ATP ADP + P i MAXIMIZE Z= V ATP_PR As ATP breaks, a large amount of energy is released and it is broken down into ADP(Adinosine diphosphate) and an organic molecule. The shadow price and the reduced cost help optimize the solution. For the objective of maximization of ATP production, if the value of shadow price of NADH is 3 that means an additional molecule of NADH can generate three more molecules of ATP.

The diagram shows the role of malate aspartate shuttle in the mitochondria. Shuttles play a important role in transporting reducing equivalents produced in the cytosol into the mitochondrion. - the ubiquitous malate aspartate shuttle transports external NADH into the mitochondrion. The coordinated exchange exchange of malate and ketoglutarate with aspartate and glutamate by respective antiporters is a key feature of the shuttle.The diagram shows the role of malate aspartate shuttle in the mitochondria. Shuttles play a important role in transporting reducing equivalents produced in the cytosol into the mitochondrion. - the ubiquitous malate aspartate shuttle transports external NADH into the mitochondrion. The coordinated exchange exchange of malate and ketoglutarate with aspartate and glutamate by respective antiporters is a key feature of the shuttle.

RESULTS The model predicted the expected ATP yields for glucose, lactate and palmitate. Genetic defects that affect mitochondrial functions have been implicated in several human diseases

The simulations were carried out for the three substrates, glucose,lactate and palmitic acid. The complete utilzation of 1 mol of glucose results in the formation of 38 ATP with the concomitant utilization of 6 mol of oxygen. The utilization of 1 mol of lactate forms 17.5 ATP with the utilization of 3 mol of oxygen and palmitic acid produces 129 ATP but requires 23 mol of oxygen.The simulations were carried out for the three substrates, glucose,lactate and palmitic acid. The complete utilzation of 1 mol of glucose results in the formation of 38 ATP with the concomitant utilization of 6 mol of oxygen. The utilization of 1 mol of lactate forms 17.5 ATP with the utilization of 3 mol of oxygen and palmitic acid produces 129 ATP but requires 23 mol of oxygen.

In normal functioning hearts under aerobic conditions, free fatty acids(FFA) are primarily used for energy production. FBA predicts that under these circumstances, the ideal substrate to maximize ATP production is glucose. However it is known that FFA metabolism inhibits pyruvate dehydrogenase(PDH) activities and reduces the flux through of glucose catabolism.

This metabolic regulation can be modeled in the FBA model by constraining the the fluxes through these enzymes.

The FBA model can be used to evaluate the systemic consequences of reduced enzyme activity. Mathematically, this is equivalent to setting a constraint on a specific flux to be either zero or some specific value.

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