Ultrastructural protein mapping through Correlation of Light and Electron Microscopy

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Project Description

The project developed a correlative light and electron microscopy (CLEM) workflow for ultrastructural mapping of protein distributions in cells. It aligns high-resolution TEM images with fluorescence microscopy channels using fiducial markers. LM provides multi-channel protein labeling through fluorescence microscopy, while EM offers nanoscale morphological details. Aligning these images enables comprehensive insights into cellular structures. Key aspects of the image analysis pipeline include:

• Fiducial particles detection in EM images using the template matching algorithm

• Fiducial particles detection in LM images using the Big-FISH Python package

• Finding correlation between EM and LM images using the Coherent Point Drift (CPD) registration