Limits...
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.

Show MeSH

Related in: MedlinePlus

The caspase3 network and its input-output characteristics and transition probability diagrams. (a) Transmission error probability Pe versus the dominance factor k in the caspase3 communication channel. We have calculated transmission error probabilities using the total probability theorem and by considering all the error events (see Methods). The caspase3 network shows completely different behavior depending on the dominant dysfunctional molecule. For example, when AKT is the dominant molecule, Pe rapidly increases as the dominance factor k increases. This shows the critical role of AKT in signal transmission over this molecular communication channel. In contrast, other molecules, such as EGFR or MEKK1ASK1, cause a small increase in Pe, which indicates that they have less impact on information transfer. The decrease of Pe for the rest of the molecules means that even if any of these molecules is dysfunctional with probability one, there will be no transmission error. (b) Caspase3 signaling capacity C versus the dominance factor k. Small values of C for AKT confirm the significant role of a dysfunctional AKT. Higher values of C for EGFR and MEKK1ASK1 mean that their dysfunction is less harmful to signal transmission than AKT. Large values of C for the rest of the molecules indicate their insignificance, when they are dysfunctional.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: The caspase3 network and its input-output characteristics and transition probability diagrams. (a) Transmission error probability Pe versus the dominance factor k in the caspase3 communication channel. We have calculated transmission error probabilities using the total probability theorem and by considering all the error events (see Methods). The caspase3 network shows completely different behavior depending on the dominant dysfunctional molecule. For example, when AKT is the dominant molecule, Pe rapidly increases as the dominance factor k increases. This shows the critical role of AKT in signal transmission over this molecular communication channel. In contrast, other molecules, such as EGFR or MEKK1ASK1, cause a small increase in Pe, which indicates that they have less impact on information transfer. The decrease of Pe for the rest of the molecules means that even if any of these molecules is dysfunctional with probability one, there will be no transmission error. (b) Caspase3 signaling capacity C versus the dominance factor k. Small values of C for AKT confirm the significant role of a dysfunctional AKT. Higher values of C for EGFR and MEKK1ASK1 mean that their dysfunction is less harmful to signal transmission than AKT. Large values of C for the rest of the molecules indicate their insignificance, when they are dysfunctional.

Mentions: To explore how much each molecule contributes to channel transmission errors and signal loss, caused by dysfunctional molecules, now we introduce a more general channel model. In this model the probability of each molecule to be dysfunctional is β. However, there is one dominant molecule such that its dysfunctionality probability is kβ, k ≥ 1, where k is the dominance factor. In the model introduced earlier in the paper k = 1 but in this model the dominant molecule is more probable to be dysfunctional. Depending on which molecule in the channel (Figure 1a) is dominant, we obtain different channel transition probability diagrams, which result in different transmission error probabilities Pe (Figure 2a) and signaling capacities C (Figure 2b) (see Methods).


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) Transmission error probability Pe versus the dominance factor k in the caspase3 communication channel. We have calculated transmission error probabilities using the total probability theorem and by considering all the error events (see Methods). The caspase3 network shows completely different behavior depending on the dominant dysfunctional molecule. For example, when AKT is the dominant molecule, Pe rapidly increases as the dominance factor k increases. This shows the critical role of AKT in signal transmission over this molecular communication channel. In contrast, other molecules, such as EGFR or MEKK1ASK1, cause a small increase in Pe, which indicates that they have less impact on information transfer. The decrease of Pe for the rest of the molecules means that even if any of these molecules is dysfunctional with probability one, there will be no transmission error. (b) Caspase3 signaling capacity C versus the dominance factor k. Small values of C for AKT confirm the significant role of a dysfunctional AKT. Higher values of C for EGFR and MEKK1ASK1 mean that their dysfunction is less harmful to signal transmission than AKT. Large values of C for the rest of the molecules indicate their insignificance, when they are dysfunctional.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: The caspase3 network and its input-output characteristics and transition probability diagrams. (a) Transmission error probability Pe versus the dominance factor k in the caspase3 communication channel. We have calculated transmission error probabilities using the total probability theorem and by considering all the error events (see Methods). The caspase3 network shows completely different behavior depending on the dominant dysfunctional molecule. For example, when AKT is the dominant molecule, Pe rapidly increases as the dominance factor k increases. This shows the critical role of AKT in signal transmission over this molecular communication channel. In contrast, other molecules, such as EGFR or MEKK1ASK1, cause a small increase in Pe, which indicates that they have less impact on information transfer. The decrease of Pe for the rest of the molecules means that even if any of these molecules is dysfunctional with probability one, there will be no transmission error. (b) Caspase3 signaling capacity C versus the dominance factor k. Small values of C for AKT confirm the significant role of a dysfunctional AKT. Higher values of C for EGFR and MEKK1ASK1 mean that their dysfunction is less harmful to signal transmission than AKT. Large values of C for the rest of the molecules indicate their insignificance, when they are dysfunctional.
Mentions: To explore how much each molecule contributes to channel transmission errors and signal loss, caused by dysfunctional molecules, now we introduce a more general channel model. In this model the probability of each molecule to be dysfunctional is β. However, there is one dominant molecule such that its dysfunctionality probability is kβ, k ≥ 1, where k is the dominance factor. In the model introduced earlier in the paper k = 1 but in this model the dominant molecule is more probable to be dysfunctional. Depending on which molecule in the channel (Figure 1a) is dominant, we obtain different channel transition probability diagrams, which result in different transmission error probabilities Pe (Figure 2a) and signaling capacities C (Figure 2b) (see Methods).

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