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Author Spotlight: High-Throughput Image-Based Quantification of Mitochondrial DNA Synthesis and Distribution
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RoundMi: A quantitative method to analyze mitochondrial morphology in mitotic cells
Elmira Parvindokht Bararpour1, Christine Volmert1, Valentina Piano1,2
1Institute of Human Genetics, University of Cologne, Faculty of Medicine and University Hospital Cologne, Germany.
FEBS Open Bio
|May 2, 2026
Summary
Analyzing mitochondrial morphology in dividing cells is challenging. RoundMi offers a rapid, quantitative method using single-plane imaging, simplifying complex analyses for broader accessibility.
Area of Science:
- Cell Biology
- Biophysics
- Computational Biology
Background:
- Mitochondrial morphology reflects cellular health and disease.
- Quantitative analysis in mitotic cells is difficult due to their 3D structure.
- Current volumetric methods are resource-intensive and slow.
Purpose of the Study:
- To develop a streamlined workflow for analyzing mitochondrial morphology in mitotic cells.
- To enable rapid, quantitative assessment using single focal plane imaging.
- To overcome limitations of existing high-throughput methods.
Main Methods:
- Developed RoundMi, a workflow integrating Nellie plugin (Napari) and MitoSkel.
- Utilized single focal plane imaging guided by DNA and mitochondrial staining.
- Validated in mouse embryonic fibroblasts (MEFs) and HeLa cells.
Main Results:
- RoundMi accurately detects mitochondrial morphology differences between wild-type and DRP1-deficient cells.
- Single-plane analysis reliably approximates volumetric data without artifacts.
- Significantly reduced computational demand and acquisition time compared to volumetric methods.
Conclusions:
- RoundMi provides a versatile, high-throughput solution for mitochondrial morphology analysis in dividing cells.
- The method is compatible with live-cell imaging and applicable across cell types.
- Simplifies complex analyses, enhancing accessibility for researchers.

