Boolean model of yeast apoptosis as a tool to study yeast and human apoptotic regulations
Journal article, 2012

Programmed cell death (PCD) is an essential cellular mechanism that is evolutionary conserved, mediated through various pathways and acts by integrating different stimuli. Many diseases such as neurodegenerative diseases and cancers are found to be caused by, or associated with, regulations in the cell death pathways. Yeast Saccharomyces cerevisiae, is a unicellular eukaryotic organism that shares with human cells components and pathways of the PCD and is therefore used as a model organism. Boolean modeling is becoming promising approach to capture qualitative behavior and describe essential properties of such complex networks. Here we present large literature-based and to our knowledge first Boolean model that combines pathways leading to apoptosis (a type of PCD) in yeast. Analysis of the yeast model confirmed experimental findings of anti-apoptotic role of Bir1p and pro-apoptotic role of Stm1p and revealed activation of the stress protein kinase Hog proposing the maximal level of activation upon heat stress. In addition we extended the yeast model and created an in silico humanized yeast in which human pro- and anti-apoptotic regulators Bcl-2 family and Valosin-contain protein (VCP) are included in the model. We showed that accumulation of Bax in silico humanized yeast shows apoptotic markers and that VCP is essential target of Akt Signaling. The presented Boolean model provides comprehensive description of yeast apoptosis network behavior. Extended model of humanized yeast gives new insights of how complex human disease like neurodegeneration can initially be tested.


Boolean modeling



Bcl-2 family




Laleh Kazemzadeh

Chalmers, Chemical and Biological Engineering

Marija Cvijovic

University of Gothenburg

Chalmers, Chemical and Biological Engineering, Life Sciences

Chalmers, Mathematical Sciences, Mathematics

Dina Petranovic Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences

Frontiers in Physiology

1664042x (eISSN)

Vol. 3 Atrticle 446

Subject Categories

Bioinformatics and Systems Biology



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