Universitat de BarcelonaSystems Biology

Understanding Metabolic Pathways

[SystemModeler] MathModelica provides state-of-the-art tools for kinetic analysis, which accelerates progress in the experimental area of systems biology.

—Dr. Vitaly Selivanov, Universitat de Barcelona

The research of Professor Marta Cascante's team at Universitat de Barcelona involves the identification of metabolic pathways, which are necessary in order to understand the metabolic effects of chronic obstructive pulmonary disease (COPD).

COPD is a group of diseases characterized by the limitation of airflow in the airway that is not fully reversible. It is most often due to tobacco smoking but can be due to other airborne irritants such as coal dust or solvents. The primary effect of the target disease is mitochondrial respiration, resulting in increased reactive oxygen species (ROS) production, which affect cellular nitroso-redox balance, glucose metabolism, and related cellular energetics. Analyzing the respective experimental and clinical data requires the development of special informatics tools, such as a kinetic model of mitochondrial respiratory chain that describes dynamics of thousands of states of the respiratory complexes, or/and a model for isotope-tracer-based data analysis, which also requires automatic construction and the solving of a large number of differential equations. "The modern experimental technique," Dr. Selivanov says, "can provide the most complete information about in vivo cell operation, but the problem now is in the methods of analysis which match the advance in experimental methods." Therefore he has developed an algorithm for flux estimation from the metabolite isotopic isomers (isotopomer) distribution. The method is based on the fact that if substrates of cellular metabolism contain labeled atoms (as 13C isotopes), metabolic networks introduce them into the intermediates and products in accordance with the internal metabolic fluxes. Therefore, the resulting label distribution carries the information about the cellular metabolic fluxes. This information can then be used by Dr. Selivanov's algorithm to tune kinetic reaction parameters of the metabolic pathway.

To tune the kinetic reaction parameters, you need to begin from the usual kinetic model. Until now, Dr. Selivanov has implemented the model equations by hand, but after learning about [SystemModeler Model Center] MathModelica System Designer at a seminar and how he could use it to develop and simulate metabolic pathway models, he now uses a graphical interface to compose the models. "The biggest advantage," he says, "is that it provides a user-friendly interface making tracer-based metabolomic analysis available for common use."

He also mentions the free BioChem library, which allows the easy construction of the kinetic model corresponding to the above scheme. As the library is easy to modify and extend, it provides a possibility of implementing the algorithms for construction of the equations for isotopic isomers.

Once the model has been built, Dr. Selivanov exports the model equations to Mathematica where he uses his flux-estimation algorithm to estimate model parameters. "As soon as I have obtained the parameters, I can simulate and check the results," he explains.

This technique will be also applicable to different areas of modeling, where huge equation systems have to be solved, such as detailed models of respiratory chain or signaling pathways. "[SystemModeler] MathModelica provides state-of-the-art tools for kinetic analysis, which accelerates progress in the experimental area of systems biology," he concludes.