Author:
Sridharan Sriram,Layek Ritwik,Datta Aniruddha,Venkatraj Jijayanagaram
Abstract
Abstract
Background
Oxidative stress is a consequence of normal and abnormal cellular metabolism and is linked to the development of human diseases. The effective functioning of the pathway responding to oxidative stress protects the cellular DNA against oxidative damage; conversely the failure of the oxidative stress response mechanism can induce aberrant cellular behavior leading to diseases such as neurodegenerative disorders and cancer. Thus, understanding the normal signaling present in oxidative stress response pathways and determining possible signaling alterations leading to disease could provide us with useful pointers for therapeutic purposes. Using knowledge of oxidative stress response pathways from the literature, we developed a Boolean network model whose simulated behavior is consistent with earlier experimental observations from the literature. Concatenating the oxidative stress response pathways with the PI 3-Kinase-Akt pathway, the oxidative stress is linked to the phenotype of apoptosis, once again through a Boolean network model. Furthermore, we present an approach for pinpointing possible fault locations by using temporal variations in the oxidative stress input and observing the resulting deviations in the apoptotic signature from the normally predicted pathway. Such an approach could potentially form the basis for designing more effective combination therapies against complex diseases such as cancer.
Results
In this paper, we have developed a Boolean network model for the oxidative stress response. This model was developed based on pathway information from the current literature pertaining to oxidative stress. Where applicable, the behaviour predicted by the model is in agreement with experimental observations from the published literature. We have also linked the oxidative stress response to the phenomenon of apoptosis via the PI 3k/Akt pathway.
Conclusions
It is our hope that some of the additional predictions here, such as those pertaining to the oscillatory behaviour of certain genes in the presence of oxidative stress, will be experimentally validated in the near future. Of course, it should be pointed out that the theoretical procedure presented here for pinpointing fault locations in a biological network with feedback will need to be further simplified before it can be even considered for practical biological validation.
Publisher
Springer Science and Business Media LLC
Reference39 articles.
1. Weinberg RA: The Biology of Cancer. 2006, Garland Science, Princeton, 1
2. Datta A, Dougherty E: Introduction to Genomic Signal Processing with Control. 2007, Boca Raton: CRC Press
3. Viswanathan GA, Seto J, Patil S, Nudelman G, Sealfon SC: Getting Started in Biological Pathway Construction and Analysis. PLoS Comput Biol. 2008, 4: e16-10.1371/journal.pcbi.0040016.
4. Saraiya P, North C, Duca K: Visualizing biological pathways: requirements analysis, systems evaluation and research agenda. Information Visualization. 2005, 1-15.
5. Layek R, Datta A, Dougherty ER: From Biological Pathways to Regulatory Networks. Mol BioSyst. 2011, 7: 843-851. 10.1039/c0mb00263a.
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