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Related Concept Videos

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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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The extracellular matrix or ECM holds cells together to form a tissue and allows the cells within the tissue to communicate. ECM comprises proteins such as fibronectin, collagen, laminin, etc. The most abundant protein in this space is collagen. Collagen fibers are interwoven with carbohydrate-containing protein molecules called proteoglycans. ECM allows cell migration and provides a structural scaffold at cell adhesion that anchors the cell when the extracellular matrix proteins interact with...
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Hormones—or any molecule that binds to a receptor, known as a ligand—that are lipid-insoluble (water-soluble) are not able to diffuse across the cell membrane. In order to be able to affect a cell without entering it, these hormones bind to receptors on the cell membrane. When a first messenger, a hormone, binds to a receptor, a signal cascade is set off, causing second messengers, proteins inside the cell, to become activated, resulting in downstream effects.
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Related Experiment Video

Updated: Jul 30, 2025

Single-cell Microinjection for Cell Communication Analysis
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Comparative analysis of cell-cell communication at single-cell resolution.

Aaron J Wilk1,2,3, Alex K Shalek4,5,6,7,8, Susan Holmes9

  • 1Stanford Immunology Program, Stanford University School of Medicine, Stanford, CA, USA. awilk@stanford.edu.

Nature Biotechnology
|May 11, 2023
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Summary

Scriabin analyzes cell-cell communication at single-cell resolution, revealing hidden networks and spatial interactions without data aggregation. This framework enhances understanding of niche-phenotype relationships in health and disease.

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Area of Science:

  • Computational biology
  • Genomics
  • Systems biology

Background:

  • Single-cell RNA sequencing (scRNA-seq) enables inference of cell-cell communication.
  • Current methods aggregate cells, losing single-cell resolution and critical communication details.

Purpose of the Study:

  • Introduce Scriabin, a novel framework for analyzing cell-cell communication at single-cell resolution.
  • Overcome limitations of existing methods by avoiding cell aggregation and downsampling.

Main Methods:

  • Developed Scriabin, a flexible and scalable computational framework.
  • Applied Scriabin to atlas-scale scRNA-seq datasets, genetic perturbation screens, and spatial transcriptomic data.
  • Validated findings using experimental data and longitudinal studies.

Main Results:

  • Scriabin accurately identifies known cell-cell communication pathways.
  • Revealed communication networks previously obscured by cell aggregation methods.
  • Uncovered spatial interaction features from dissociated single-cell data.
  • Tracked communication pathways across different timepoints in longitudinal datasets.

Conclusions:

  • Scriabin provides a powerful tool for high-resolution cell-cell communication analysis.
  • The framework enhances the discovery of complex intercellular relationships.
  • Enables a deeper understanding of niche-phenotype interactions in biological systems and disease states.