Analyzing mitochondrion metabolism using constraint-based modeling approaches and comparative proteomics

Title: Analyzing mitochondrion metabolism using constraint-based modeling approaches and comparative proteomics

Description

Supervisors: Richard Notebaart, Bas Teusink, Martijn Huynen

Mitochondria are well known to play a key role in the production of free-energy (ATP) by the oxidative phosphorylation process. However, many more metabolic functions of the mitochondria exist, depending on the specific needs of cell types. To model and to analyze the metabolic capacity (e.g. energy production) of mitochondria using classical modeling techniques it is required to know the mitochondrial objectives. As multiple objectives are likely to exist, it is not known and not trivial to determine the objectives for modeling. In this project we will investigate how proteomics data (i.e. protein content) can be used in the prediction of the objective (or distribution of objectives) at certain experimental conditions.
Recently, a proteomics data set has become available for mitochondria within three different rat tissues (i.e. skeletal muscle, heart and liver) revealing previous undiscovered proteins being part of the organelle and which are specific for the different tissues. Moreover, a metabolic network/model has also been published, which allows us to update the model and to analyse the metabolic capacity of the three different tissues. As the model includes the objectives we should be able to analyze whether or not there is a tendency towards different objectives for skeletal muscle, heart and liver given the specific protein contents. In other words, will there be a different distribution of known objectives for the tissues and can this be related to specific properties of the tissues (in this case protein data).

Student tasks:

    • Examine the possibility to update the previously published metabolic network of mitochondrion using proteomics for each tissue (i.e. construction of three tissue-specific models).
    • Implement the metabolic models within a modeling environment and analyze/compare metabolic properties of the three tissues. For example, relate protein expression in each tissue to its metabolic flux.