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Related Concept Videos

Overview of Cell Signaling01:23

Overview of Cell Signaling

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Despite the protective membrane that separates a cell from the environment, cells need the ability to detect and respond to environmental changes. Additionally, cells often need to communicate with one another. Unicellular and multicellular organisms use a variety of cell signaling mechanisms to communicate with the environment.
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Diversity in Cell Signaling Responses01:22

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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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Interactions Between Signaling Pathways01:19

Interactions Between Signaling Pathways

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Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
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Contact-dependent Signaling01:19

Contact-dependent Signaling

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Contact-dependent signaling, as the name suggests, requires that communicating cells be in direct contact with each other. This is achieved either through receptor-ligand interactions or by specialized cytoplasmic channels that allow the flow of small molecules between cells. In animal cells, channels called gap junctions facilitate contact-dependent signaling in certain tissues, whereas, plasmodesmata perform a similar function in plants.
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Cell Specific Gene Expression01:58

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Positive and negative feedback loops are crucial for regulating biological signaling systems. These feedback loops are processes that connect output signals to their inputs.
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Related Experiment Video

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An Optogenetic Method to Control and Analyze Gene Expression Patterns in Cell-to-cell Interactions
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Revealing cell-cell communication pathways with their spatially coupled gene programs.

Junchao Zhu1, Hao Dai1, Luonan Chen1,2

  • 1Key Laboratory of Systems Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Cell building, No. 320 Yueyang Road, Xuhui District, Shanghai 200031, China.

Briefings in Bioinformatics
|May 6, 2024
PubMed
Summary

Intercellular Gene Association Network (IGAN) infers cell-cell communication (CCC) and its pathways using spatial transcriptomics. This novel method reveals complex regulatory mechanisms and spatial heterogeneity in cellular interactions.

Keywords:
cell–cell communicationintercellular gene associationligand–receptor pathwayspatial microenvironmentspatial transcriptome

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Area of Science:

  • Computational biology
  • Systems biology
  • Genomics

Background:

  • Cell-cell communication (CCC) is crucial for understanding biological processes.
  • Spatial transcriptomics enables prediction of CCCs using cellular spatial information.
  • Existing methods often lack exploration of upstream/downstream pathways for ligand-receptor interactions.

Purpose of the Study:

  • To propose a novel method, Intercellular Gene Association Network (IGAN), for inferring CCCs.
  • To enable estimation of gene associations between adjacent single cells.
  • To explore upstream/downstream pathways of ligands/receptors from a network perspective.

Main Methods:

  • Development of the Intercellular Gene Association Network (IGAN) method.
  • Estimation of gene associations between spatially adjacent single cells.
  • Construction of a cell-interaction-pathway graph.

Main Results:

  • IGAN accurately infers CCCs and explores associated pathways.
  • The method provides a panoramic view of cell interactions and regulatory mechanisms.
  • IGAN measures CCC activity at single-cell resolution, revealing spatial heterogeneity.
  • IGAN-derived CCC patterns align with spatial microenvironment patterns, confirming accuracy.

Conclusions:

  • IGAN offers a powerful new approach for inferring CCCs and their regulatory pathways.
  • The method enhances understanding of CCC spatial heterogeneity and biological mechanisms.
  • IGAN's accuracy is validated across multiple public datasets.