Correlating NanoSIMS images with ultra-high resolution EM images in Look@NanoSIMS
Contributors
- 1. Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Station 19, CH-1015 Lausanne, Switzerland
- 2. Laboratory for Biological Geochemistry, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- 3. Bioelectron Microscopy Core Facility, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- 4. Center for Advanced Surface Analysis, Institute of Earth Sciences, University of Lausanne, CH-1015 Lausanne, Switzerland
- 5. Bertarelli Platform for Gene Therapy, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
Description
Supplement of the study by Spataro et al. (2022) describes how to perform correlative image analysis in Look@NanoSIMS. This repository contains files used as an example in that analysis.
* Rat7SNR_21.tif = ultra-high resolution EM image (4096 x 3072 pixels)
* Spataro-Sept-2018_3.im.zip = zipped raw data produced by NanoSIMS 50L (256 x 256 pixels)
* Spataro-Sept-2018_3.zip = zipped folder containing data generated by Look@NanoSIMS
To start the analysis, download all files to a folder on your computer (preferably in the same folder) and unzip the file Spataro-Sept-2018_3.zip. The latter step will create a folder Spataro-Sept-2018_3 containing files generated by Look@NanoSIMS when analysing data in Spataro-Sept-2018_3.im.zip and Rat7SNR_21.tif. The files include information about the alignment of individual planes (xyalign.mat), coordinates of the pairs of reference points in the EM and NanoSIMS images (points_10x.mat), regions of interest defined for the resampled (cells_10x.mat) and original NanoSIMS data (cells_1x.mat), and Look@NanoSIMS preferences saved for the resampled (prefs_10x.mat) and original (prefs_1x.mat and prefs.mat) NanoSIMS data. You can use these files to reproduce the analysis described in the Supplement of Spataro et al. (2022).
Reference:
S. Spataro, B. Maco, S. Escrig, L. Jensen, L. Polerecky, G. Knott, A. Meibom, and B. L. Schneider (2022). Alpha-synuclein-induced changes to neuronal metabolism revealed by stable isotope labeling and ultra-high-resolution imaging.