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Quantitative analysis of intracellular communication and signaling errors in signaling networks.

Habibi I, Emamian ES, Abdi A - BMC Syst Biol (2014)

Bottom Line: 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: 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. ali.abdi@njit.edu.

ABSTRACT

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.

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The caspase3 network and its input-output characteristics and transition probability diagrams. (a) The caspase3 communication channel. The channel input molecules are EGF, insulin and TNF, and the channel output molecule is caspase3. The molecule ComplexI within the channel includes TNFR and TRADD-RIP-TRAF2 [20], whereas the molecule ComplexII stands for TRADD-RIP-TRAF2 and FADD [20]. (b) The input–output relationships for the caspase3 normal channel. (c) Transition probability diagram for the normal caspase3 channel. Numbers above the arrows are transition probabilities. (d) Transition probability diagram for the pathological caspase3 channel where all the molecules in the channel are equally likely to be dysfunctional. Numbers above the arrows are transition probabilities.
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Figure 1: The caspase3 network and its input-output characteristics and transition probability diagrams. (a) The caspase3 communication channel. The channel input molecules are EGF, insulin and TNF, and the channel output molecule is caspase3. The molecule ComplexI within the channel includes TNFR and TRADD-RIP-TRAF2 [20], whereas the molecule ComplexII stands for TRADD-RIP-TRAF2 and FADD [20]. (b) The input–output relationships for the caspase3 normal channel. (c) Transition probability diagram for the normal caspase3 channel. Numbers above the arrows are transition probabilities. (d) Transition probability diagram for the pathological caspase3 channel where all the molecules in the channel are equally likely to be dysfunctional. Numbers above the arrows are transition probabilities.

Mentions: Caspase3 is one of the most important molecules in the regulation of cell death (apoptosis) and cell survival. Caspase3 is a suitable molecule for the purpose of developing this approach for several reasons. This molecule has been extensively studied by several independent groups of scientists and the intracellular signaling molecules that regulate its activity are well characterized. Moreover, it is either in an active or inactive form. Caspases exist as inactive enzymes that undergo a proteolytic cleavage at conserved aspartic residues, to produce two subunits, large and small, that dimerize to form the active enzyme [1]. Dysfunction of the caspase network causes the failure of automated process of cell death and eventually results in a malignant transformation [1]. Signaling pathways from the input ligands EGF, insulin and TNF to the output caspase3 (Figure 1a) are extensively characterized and experimentally verified [20],[21]. Having the biological data and information from an independent group will validate the outcomes of this study, as discussed later. There are seventeen intermediate molecules between the inputs and the output, which constitute the communication channel of this network. The input–output relationships for the normal channel, i.e., when all the molecules in the channel are functional, are summarized in a table (Figure 1b), supported by the experimental findings of Janes et al. [20]. A value of 0 or 1 for a molecule means that it is either inactive or active, respectively [22]. Using the input–output relationships (Figure 1b), the channel transition probability diagram for the normal channel is obtained (Figure 1c).


Quantitative analysis of intracellular communication and signaling errors in signaling networks.

Habibi I, Emamian ES, Abdi A - BMC Syst Biol (2014)

The caspase3 network and its input-output characteristics and transition probability diagrams. (a) The caspase3 communication channel. The channel input molecules are EGF, insulin and TNF, and the channel output molecule is caspase3. The molecule ComplexI within the channel includes TNFR and TRADD-RIP-TRAF2 [20], whereas the molecule ComplexII stands for TRADD-RIP-TRAF2 and FADD [20]. (b) The input–output relationships for the caspase3 normal channel. (c) Transition probability diagram for the normal caspase3 channel. Numbers above the arrows are transition probabilities. (d) Transition probability diagram for the pathological caspase3 channel where all the molecules in the channel are equally likely to be dysfunctional. Numbers above the arrows are transition probabilities.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
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getmorefigures.php?uid=PMC4255782&req=5

Figure 1: The caspase3 network and its input-output characteristics and transition probability diagrams. (a) The caspase3 communication channel. The channel input molecules are EGF, insulin and TNF, and the channel output molecule is caspase3. The molecule ComplexI within the channel includes TNFR and TRADD-RIP-TRAF2 [20], whereas the molecule ComplexII stands for TRADD-RIP-TRAF2 and FADD [20]. (b) The input–output relationships for the caspase3 normal channel. (c) Transition probability diagram for the normal caspase3 channel. Numbers above the arrows are transition probabilities. (d) Transition probability diagram for the pathological caspase3 channel where all the molecules in the channel are equally likely to be dysfunctional. Numbers above the arrows are transition probabilities.
Mentions: Caspase3 is one of the most important molecules in the regulation of cell death (apoptosis) and cell survival. Caspase3 is a suitable molecule for the purpose of developing this approach for several reasons. This molecule has been extensively studied by several independent groups of scientists and the intracellular signaling molecules that regulate its activity are well characterized. Moreover, it is either in an active or inactive form. Caspases exist as inactive enzymes that undergo a proteolytic cleavage at conserved aspartic residues, to produce two subunits, large and small, that dimerize to form the active enzyme [1]. Dysfunction of the caspase network causes the failure of automated process of cell death and eventually results in a malignant transformation [1]. Signaling pathways from the input ligands EGF, insulin and TNF to the output caspase3 (Figure 1a) are extensively characterized and experimentally verified [20],[21]. Having the biological data and information from an independent group will validate the outcomes of this study, as discussed later. There are seventeen intermediate molecules between the inputs and the output, which constitute the communication channel of this network. The input–output relationships for the normal channel, i.e., when all the molecules in the channel are functional, are summarized in a table (Figure 1b), supported by the experimental findings of Janes et al. [20]. A value of 0 or 1 for a molecule means that it is either inactive or active, respectively [22]. Using the input–output relationships (Figure 1b), the channel transition probability diagram for the normal channel is obtained (Figure 1c).

Bottom Line: 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.

View Article: PubMed Central - HTML - PubMed

Affiliation: 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. ali.abdi@njit.edu.

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus