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Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

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Related Experiment Video

Updated: Sep 24, 2025

Using R, Seurat, and CellChat to Analyze a Single-Cell Transcriptomics Dataset of Mouse Skin Wound Healing

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Reconstructing physical cell interaction networks from single-cell data using Neighbor-seq.

Bassel Ghaddar¹, Subhajyoti De¹

¹Rutgers Cancer Institute of New Jersey, Rutgers the State University of New Jersey, New Brunswick, NJ 08901, USA.

Nucleic Acids Research

|May 10, 2022

Summary

This summary is machine-generated.

Neighbor-seq identifies cell-cell interactions and signaling in tissues using single-cell sequencing. This method maps cellular architecture and communication across diverse tissues and tumors, advancing organ-level interactome studies.

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Area of Science:

Cellular Biology
Genomics
Bioinformatics

Background:

Cell-cell interactions are crucial for tissue organization and multicellular life.
Understanding these interactions is key to comprehending tissue architecture and function in health and disease.

Purpose of the Study:

To develop a novel method, Neighbor-seq, for identifying and annotating direct cell-cell interactions and ligand-receptor signaling.
To enable the study of cellular interactome at the organ level using standard single-cell sequencing data.

Main Methods:

Neighbor-seq analyzes undissociated cell fractions in massively parallel single-cell sequencing data.
The method infers cell-cell communication architectures without prior knowledge of cell types or multiplets.

Main Results:

Neighbor-seq accurately identifies microanatomical features in diverse tissues like the small intestine, lung, and spleen.
It captures complex cancer-immune-stromal cell communication topologies in tumors, consistent with spatial transcriptomics.
The method is fast, scalable, and applicable to routine single-cell data.

Conclusions:

Neighbor-seq provides a powerful framework for studying the organ-level cellular interactome.
It bridges the gap between single-cell and spatial transcriptomics, offering new insights into tissue organization and disease.