Comparative Analysis of SPLICS and MCS-DETECT for Detecting Mitochondria-ER Contact Sites (MERCs)

Area of Science:

• Cell Biology
• Microscopy
• Organelle Interactions

Background:

• Mitochondria-ER contacts (MERCs) are vital for cellular function but challenging to detect due to their small size.
• Conventional confocal microscopy and split fluorescent probes (SPLICS) have limitations in resolving MERCs at nanometer scales.
• Super-resolution microscopy improves resolution but still struggles to precisely delineate MERCs.

Purpose of the Study:

• To evaluate the efficacy of the MCS-DETECT algorithm for identifying MERCs using 3D STED super-resolution microscopy.
• To compare MCS-DETECT findings with traditional colocalization analysis and SPLICS probe data.
• To validate MCS-DETECT's performance against 3D electron microscopy (EM) standards.

Main Methods:

• Utilized 3D STED super-resolution microscopy in HeLa cells expressing SPLICS and ER/mitochondria reporters.
• Applied the MCS-DETECT algorithm to analyze 3D STED image volumes.
• Compared MCS-DETECT results with co-occurrence colocalization analysis and SPLICS probe localization.
• Validated findings against 3D electron microscopy data for contact site metrics.

Main Results:

• MCS-DETECT successfully detected elongated riboMERCs in 3D STED volumes.
• The percentage of mitochondria covered by MCS-DETECT identified contacts was significantly smaller than colocalization or SPLICS methods.
• MCS-DETECT contact site metrics closely aligned with those obtained from 3D electron microscopy.
• STED analysis revealed SPLICS localization on mitochondria, with some puncta fully enveloped by mitochondria.

Conclusions:

• MCS-DETECT provides a more accurate and refined detection of MERCs compared to conventional methods.
• The algorithm's findings correlate better with ultrastructural data from electron microscopy.
• MCS-DETECT is a valuable tool for studying specific subsets of MERCs, particularly those with distinct structural features.