Quantitative analysis of intracellular communication and signaling errors in signaling networks

BMC Systems Biology

Ali Abdi²  Effat S Emamian¹  Iman Habibi² 

[1] Advanced Technologies for Novel Therapeutics (ATNT), Enterprise Development Center, New Jersey Institute of Technology, 211 Warren St, Newark 07103, NJ, USA;Center for Wireless Communications and Signal Processing Research, Department of Electrical and Computer Engineering and Department of Biological Sciences, New Jersey Institute of Technology, 323 King Blvd, Newark 07102, NJ, USA

关键词: Signal transduction;    Molecular networks;    Intracellular communication;    Cell signaling;   

Others  :  1159577
DOI  :  10.1186/s12918-014-0089-z

 received in 2014-04-26, accepted in 2014-07-15,  发布年份 2014

【 摘 要 】

Background

Intracellular signaling networks transmit signals from the cell membrane to the nucleus, via biochemical interactions. The goal is to regulate some target molecules, to properly control the cell function. Regulation of the target molecules occurs through the communication of several intermediate molecules that convey specific signals originated from the cell membrane to the specific target outputs.

Results

In this study we propose to model intracellular signaling network as communication channels. We define the fundamental concepts of transmission error and signaling capacity for intracellular signaling networks, and devise proper methods for computing these parameters. The developed systematic methodology quantitatively shows how the signals that ligands provide upon binding can be lost in a pathological signaling network, due to the presence of some dysfunctional molecules. We show the lost signals result in message transmission error, i.e., incorrect regulation of target proteins at the network output. Furthermore, we show how dysfunctional molecules affect the signaling capacity of signaling networks and how the contributions of signaling molecules to the signaling capacity and signaling errors can be computed. The proposed approach can quantify the role of dysfunctional signaling molecules in the development of the pathology. We present experimental data on caspese3 and T cell signaling networks to demonstrate the biological relevance of the developed method and its predictions.

Conclusions

This study demonstrates how signal transmission and distortion in pathological signaling networks can be modeled and studied using the proposed methodology. The new methodology determines how much the functionality of molecules in a network can affect the signal transmission and regulation of the end molecules such as transcription factors. This can lead to the identification of novel critical molecules in signal transduction networks. Dysfunction of these critical molecules is likely to be associated with some complex human disorders. Such critical molecules have the potential to serve as proper targets for drug discovery.

【 授权许可】

   
2014 Habibi et al.; licensee BioMed Central Ltd.

【 图 表 】

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