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Related Experiment Video

Updated: May 20, 2025

Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

Author Spotlight: An Optimized Automated Method for Investigating Retinoic Acid Receptors in Neuronal Mitochondria

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mitoXplorer 3.0, A Web Tool for Exploring Mitochondrial Dynamics in Single-cell RNA-seq Data.

Margaux Haering¹, Andrea Del Bondio², Helene Puccio²

¹Aix-Marseille University, CNRS, IBDM UMR7288, Turing Center for Living Systems (CENTURI), 13009 Marseille, France.

Journal of Molecular Biology

|March 26, 2025

Summary

MitoXplorer 3.0 analyzes mitochondrial gene expression at the single-cell level, revealing cell-to-cell variability and identifying disease-specific mitochondrial dysfunction in Spinocerebellar Ataxia Type 1. This tool enhances understanding of mitochondrial roles in cellular health and disease.

Keywords:

data integration mitoXplorer mitochondria single-nuclei sequencing visual data mining

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Published on: February 3, 2022

Area of Science:

Mitochondrial biology
Single-cell genomics
Bioinformatics tools

Background:

Mitochondria are vital organelles with diverse functions, yet their variability within a single cell type remains underexplored.
Understanding mitochondrial dynamics at single-cell resolution is crucial for comprehensive functional analysis.

Purpose of the Study:

Introduce mitoXplorer 3.0, an enhanced web tool for analyzing single-cell sequencing data focused on mitochondrial genes (mito-genes).
Provide a new formatting script, scXplorer, to prepare single-cell RNA sequencing data for mitoXplorer 3.0 analysis.
Enable identification of cell subpopulations and in-depth analysis of mitochondrial function and variability.

Main Methods:

Development of mitoXplorer 3.0 with new features for single-cell mitochondrial analysis.
Creation of scXplorer script for data formatting and generation of pseudo-bulk and single-cell mito-gene expression matrices.
Application of mitoXplorer 3.0 to analyze single-cell transcriptome data from a Spinocerebellar Ataxia Type 1 (SCA1) study.

Main Results:

MitoXplorer 3.0 successfully generates compatible files and enables novel single-cell based mitochondrial analyses.
Identification of cell subpopulations based solely on mito-gene expression.
Significant mitochondrial processes and genes affected in SCA1 Purkinje cells were identified, linking them to disease pathology.

Conclusions:

MitoXplorer 3.0 provides powerful, interactive interfaces for in-depth, single-cell mitochondrial research.
The tool aids in understanding mitochondrial dysfunction in neurodegenerative diseases like SCA1.
MitoXplorer 3.0 is freely accessible, promoting further research in mitochondrial biology and disease.