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Visualization and Quantification of Endogenous Intra-Organelle Protein Interactions at ER-Mitochondria Contact Sites by Proximity Ligation Assays

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Organelle landscape analysis using a multiparametric particle-based method.

Yoshitaka Kurikawa¹, Ikuko Koyama-Honda¹, Norito Tamura¹

¹Department of Biochemistry and Molecular Biology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

|September 17, 2024

Summary

This study introduces a new multiparametric particle-based analysis method to visualize and analyze diverse organelle landscapes. The technique captures heterogeneous organelle populations and their transitional states, offering deeper insights into cellular organization.

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Published on: September 7, 2018

Area of Science:

Cell Biology
Molecular Biology
Biophysics

Background:

Organelles possess unique structures and molecular compositions crucial for cellular functions.
Organelles are often heterogeneous, undergoing maturation and differentiation.
Traditional methods lack the resolution to fully capture organelle heterogeneity.

Purpose of the Study:

To develop a novel method for multiparametric particle-based analysis of organelles.
To visualize and analyze the heterogeneous landscapes of organelles within cells.
To characterize transitional states of organelles and their functional pathways.

Main Methods:

Cells were disrupted, and organelle particles were labeled with 6-8 distinct organelle markers.
Fluorescence microscopy images were acquired for the labeled organelle particles.
Multidimensional data were processed and visualized using uniform manifold approximation and projection (UMAP) in 2D spaces.

Main Results:

The method enabled visualization of landscapes for 7 major organelles.
Transitional states of endocytic organelles, including those in recycling and degradation pathways, were identified.
Endoplasmic reticulum-mitochondria contact sites were successfully detected.

Conclusions:

The proposed method allows for simultaneous detection of a wide array of organelles.
This approach effectively analyzes heterogeneous organelle landscapes and transitional states.
The technique provides a powerful tool for understanding cellular organelle dynamics.