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Related Concept Videos

Subcellular Fractionation01:32

Subcellular Fractionation

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The homogenate obtained after cell lysis contains various membrane-bound organelles that can be further separated into pure fractions by subcellular fractionation. These isolates are used to study specific cellular components, analyze localized protein activity, and are even employed in diagnostics. Fractionation is typically achieved using centrifugation methods, the most common being density-gradient and differential centrifugation.
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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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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Mining Spatial Transcriptomics Datasets using DeepSpaceDB
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CellSP enables module discovery and visualization for subcellular spatial transcriptomics data.

Bhavay Aggarwal1, Saurabh Sinha2,3

  • 1The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

Communications Biology
|November 5, 2025
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Summary
This summary is machine-generated.

CellSP is a new computational framework that identifies and visualizes subcellular mRNA patterns. This tool reveals gene-cell modules, offering functional insights into diverse biological processes like brain development and disease.

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Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Spatial transcriptomics allows studying mRNA distribution within cells, crucial for cellular function.
  • Existing tools lack the ability to identify and interpret functionally relevant subcellular transcript patterns.

Purpose of the Study:

  • To present CellSP, a computational framework for identifying, visualizing, and characterizing consistent subcellular spatial mRNA patterns.
  • To introduce "gene-cell modules" representing gene sets with coordinated subcellular transcript distributions.

Main Methods:

  • Development of CellSP, a computational framework.
  • Utilizing "gene-cell modules" to analyze coordinated transcript distributions.
  • Functional enrichment analysis of discovered modules.

Main Results:

  • CellSP reliably identifies functionally significant modules across diverse tissues and technologies.
  • Discovery of subcellular spatial phenomena related to myelination, axonogenesis, and synapse formation in the mouse brain.
  • Identification of immune response modules in kidney cancer and myelination modules in Alzheimer's Disease models.

Conclusions:

  • CellSP provides a powerful approach for dissecting subcellular transcript localization.
  • The framework offers functional insights into biological processes and disease states.
  • CellSP facilitates the discovery of novel spatial transcriptomic phenomena.