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Related Concept Videos

Intracellular Signaling Cascades01:24

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Once a ligand binds to a receptor, the signal is transmitted through the membrane and into the cytoplasm. The continuation of a signal in this manner is called signal transduction. Signal transduction only occurs with cell-surface receptors, which cannot interact with most components of the cell, such as DNA. Only internal receptors can interact directly with DNA in the nucleus to initiate protein synthesis. When a ligand binds to its receptor, conformational changes occur that affect the...
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The physiological function of a cell and cellular communication are outcomes of a range of extrinsic signals, intracellular signaling pathways, and cellular responses. No two cell types express the same repertoire of signaling components. Receptors are highly selective for their cognate ligands, but once activated, they can alter multiple cellular processes such as DNA transcription, protein synthesis, and metabolic activity. 
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When a ligand binds to a cell-surface receptor, the receptor's intracellular domain changes shape, which may either activate its enzyme function or allow its binding to other molecules. The initial signal is amplified by most signal transduction pathways. This means that a single ligand molecule can activate multiple molecules of a downstream target. Proteins that relay a signal are most commonly phosphorylated at one or more sites, activating or inactivating the protein. Kinases catalyze...
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Integrins act both as extracellular input receivers and as intracellular processing activators. As their name suggests, integrins are entirely integrated into the membrane structure. Their hydrophobic membrane-spanning regions interact with the phospholipid bilayer's hydrophobic region. These membrane receptors provide extracellular attachment sites for effectors like hormones and growth factors. They activate intracellular response cascades when their effectors are bound and active.
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Related Experiment Video

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Real-time Live Imaging of T-cell Signaling Complex Formation
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Temporal protein expression pattern in intracellular signalling cascade during T-cell activation: a computational

Piyali Ganguli1, Saikat Chowdhury, Rupa Bhowmick

  • 1Chemical Engineering and Process Development Division, CSIR-National Chemical Laboratory, Pune 411 008, India.

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|November 14, 2015
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Summary

Defects in T-cell co-receptor and CRAC channel signaling alter effector molecule production. Computational modeling reveals how these defects impact protein expression and predict changes in T-cell behavior over time.

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Area of Science:

  • Immunology
  • Computational Biology
  • Systems Biology

Background:

  • T-cell co-receptor molecules and calcium channel CRAC are crucial for immune responses, regulating effector molecule production like cytokines.
  • Dysfunctional signaling pathways in T-cells can lead to altered effector molecule expression, impacting immune clearance and cell activity.

Purpose of the Study:

  • To computationally model the T-cell activation network and investigate the temporal propagation of defects in co-receptor signaling.
  • To analyze the effects of simulated co-receptor molecule knockdown on intracellular protein expression and predict T-cell phenotypic changes.

Main Methods:

  • Reconstruction of a comprehensive T-cell activation pathway map.
  • Translation of pathway reactions into logical equations for simulation.
  • Integration of time-series microarray expression data for model input and validation.
  • In silico knockdown experiments to assess downstream protein expression and cellular behavior.

Main Results:

  • Significant variations in protein expression patterns were observed following simulated co-receptor molecule knockdown.
  • Distinct signaling routes for response propagation within the T-cell cytoplasm were identified.
  • The model successfully predicted changes in T-cell phenotypic behaviors.

Conclusions:

  • An integrative computational approach provides a valuable method for studying alterations in protein expression patterns.
  • This approach can predict variations in cellular behavior resulting from defects in T-cell signaling pathways.
  • The developed model offers insights into the dynamics of T-cell activation and response to signaling perturbations.