Title Dynamical Analysis of Yeast Protein Interaction Network During the Sake Brewing Process
Author Mitra Mirzarezaee1*, Mehdi Sadeghi2,3*, and Babak N. Araabi4,5
Address 1Department of Computer Engineering, Islamic Azad University, Science and Research Branch, Tehran, Iran, 2National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran 14965‐161, Iran, 3School of Computer Sciences, Institute for Research in Fundamental Sciences, IPM, Tehran 19395‐5746, Iran, 4Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, University of Tehran, Tehran 11155‐4563, Iran, 5School of Cognitive Sciences, Institute for Research in Fundamental Sciences, IPM, Tehran 19395‐5746, Iran
Bibliography Journal of Microbiology, 49(6),965-973, 2011,
DOI
Key Words protein interaction network, dynamical analysis, sake brewing, hubs, Saccharomyces cerevisiae
Abstract Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.