Reconstruction of Biological Networks for Integrative Analysis
Doctoral thesis, 2014

Biological systems can be very complex and consist of several thousand components that interact with each other in the cell. One of the goals of systems biology is to study biological systems from a systemic viewpoint in order to get an increased understanding of the behavior of the cell. Biological network reconstructions are important tools in systems biology in order to model the behavior of different biological systems. The biological networks can also be used as a scaffold for integrative analysis where high-throughput data from different conditions or different strains are integrated into the biological network to reduce the dimension of the data and to group the response between conditions or strains into biological pathways or key metabolites etc. The biological interpretation and discovery using integrative analysis can be facilitated by constructing more comprehensive and diverse biological networks. In this thesis I expanded current biological network reconstructions for the yeast Saccharomyces cereveisae in three steps and used them as a scaffold for biological interpretation and discovery. First I constructed an up-to-date yeast genome-scale metabolic model. The model is a comprehensive description of yeast metabolism and contains more genes, reactions and metabolites than previous models. The model performs well in simulating the metabolism under different conditions. Second, I studied the transcriptional regulatory network of yeast in terms of topology and structure of the network and compared it to transcriptional regulation in E. coli, human and mouse. I also used high-throughput data from many different conditions to study the condition-dependent response of the yeast transcriptional regulatory network. Third, I was involved in reconstruction of models of the protein secretion machinery in S. cerevisiae and for the high protein producer Aspergillus oryzae, describing protein folding, post-translational modifications and protein transport etc. High-throughput data from several different strains producing α-amylase were integrated into the models in order to get an insight in the mechanisms and bottlenecks of protein secretion in these organisms. The biological networks presented here were also used for data integration and the results and interpretation of the cellular behavior under different conditions can give us a deeper understanding and insight in for example condition-specific transcriptional regulation and protein production.

transcriptional regulation

: Biological networks

integrative analysis

protein secretion

genome-scale metabolic model

Opponent: Kiran Patil, EMBL, Heidelberg, Germany


Tobias Österlund

Chalmers, Chemical and Biological Engineering, Life Sciences

Anaerobic alpha-Amylase Production and Secretion with Fumarate as the Final Electron Acceptor in Saccharomyces cerevisiae

Applied and Environmental Microbiology,; Vol. 79(2013)p. 2962-2967

Journal article

Fifteen years of large scale metabolic modeling of yeast: Developments and impacts

Biotechnology Advances,; Vol. 30(2012)p. 979-988

Review article

Biological systems are very complex and can involve thousands of components such as genes, proteins and small molecules. Systems biology uses mathematical approaches to model the system based on the involved components and their interactions in order to better understand how a cell respond to a change of environment or as a function of a disease. Biological network reconstructions can help to understand the complexity of the cell by studying the system as a whole rather than studying individual components. The yeast Saccharomyces cerevisiae can be used as a host to produce other products, e.g. biofuels and proteins such as amylase or insulin. Understanding the biology of yeast on the systems level can help to produce more products with higher yields. In order to get an increased understanding of the biological system we need more comprehensive network reconstructions that cover many processes and pathways in the cell. In my thesis work I have expanded previous biological network reconstructions and created a new, more comprehensive genome-scale model of the yeast metabolism, called iTO977. Further we have reconstructed a model of the protein secretion machinery for yeast and Aspergillus oryzae. I have also investigated the topology and organization of the yeast transcriptional regulatory network. The biological network reconstructions were also used as a scaffold for integrative analysis in order to understand how the cell behaves in different conditions.

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Bioinformatics and Systems Biology



Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 3641


Opponent: Kiran Patil, EMBL, Heidelberg, Germany

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