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Related Concept Videos

Synaptic Signaling01:12

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Synaptic Signaling01:09

Synaptic Signaling

Neurons communicate at synapses, or junctions, to excite or inhibit the activity of other neurons or target cells, such as muscles. Synapses may be chemical or electrical.
Most synapses are chemical, meaning an electrical impulse or action potential spurs the release of chemical messengers called neurotransmitters. The neuron sending the signal is called the presynaptic neuron, and the neuron receiving the signal is the postsynaptic neuron.
The presynaptic neuron fires an action potential that...
Signal Sequences and Sorting Receptors01:41

Signal Sequences and Sorting Receptors

Signal sequences are short amino acid sequences that guide newly synthesized proteins to their proper location within the cell. Classical signal sequences are fifteen to sixty amino acids long and present at the N-terminus of a polypeptide chain. Each signal sequence has a conserved segment of basic residues towards their N terminus, a hydrophobic core, and a C-terminus rich in polar residues. The C-terminus also contains a signal cleavage site and features a -3 -1 sequence motif. The -3-1...
Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
Amplifying Signals via Second Messengers01:15

Amplifying Signals via Second Messengers

Many receptor binding ligands are hydrophilic; they do not cross the cell membrane but bind to cell-surface receptors. Thus, their message must be relayed by second messengers present in the cell cytoplasm. There are several second messenger pathways, each with its own way of relaying information. For example, the G protein-coupled receptors can activate both phosphoinositol and cyclic AMP (cAMP) second messenger pathways. The phosphoinositol pathway is active when the receptor induces...
Diversity in Cell Signaling Responses01:22

Diversity in Cell Signaling Responses

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. 
Graded and Abrupt Responses
Some signaling systems generate...

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An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
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Noise-processing by signaling networks.

Styliani Kontogeorgaki1, Rubén J Sánchez-García1,2, Rob M Ewing3,2

  • 1Mathematical Sciences, University of Southampton, SO17 1BJ, Southampton, UK.

Scientific Reports
|April 5, 2017
PubMed
Summary
This summary is machine-generated.

Signaling networks can distinguish important signals from environmental noise by adopting sparse and directional structures. Complex, dense networks are poor at noise processing, impacting cellular decision-making.

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Area of Science:

  • Cellular signaling
  • Systems biology
  • Network theory

Background:

  • Signaling networks transmit environmental information to the cell nucleus.
  • Effective signaling requires integrating multiple stimuli and filtering environmental noise.
  • Understanding how signaling networks process noise is crucial but not well understood.

Purpose of the Study:

  • To develop a mathematical framework linking signaling network structure to noise-processing capacity.
  • To analyze the noise-processing capabilities of different signaling network architectures.
  • To investigate the role of network structure in distinguishing signals from transient fluctuations.

Main Methods:

  • Development of a mathematical framework to quantify network noise processing.
  • Analysis of network density and directionality in relation to signal fidelity.
  • Application of the framework to the signaling network maintaining pluripotency in mouse embryonic stem cells.

Main Results:

  • Sparse and strongly directional signaling networks exhibit superior noise-processing capabilities.
  • Complex networks dense in directed paths are inefficient at filtering environmental noise.
  • An incoherent feedforward loop involving Stat3, Tfcp2l1, Esrrb, Klf2, and Klf4 is critical for noise processing in stem cell pluripotency.

Conclusions:

  • Signaling network structure is a key determinant of noise-processing efficiency.
  • Optimized network structures, like sparse and directional pathways, are essential for accurate cellular responses.
  • Noise processing is an integral function of signaling networks, influencing their architectural design.