Correlative microscopies: Quantitatively fusing information from 3D+ to 6D+
Creators: name: Paul-Gilloteaux, Perrine
Publisher: name: F1000 Research Limited
Year: 2021

description: Correlative microscopies is a set of methods allowing to fuse the information from complementary imaging modalities, usually also at different scales, on the same sample (Walter et al. 2020).<br> In addition to the experimental elements helping to bridge different imaging modalities acquisitions, automated software solutions to correlate multiscale, multimodal and volumetric image data are an essential pillar of correlative microscopies workflows . They include in particular segmentation (identifying and spatially localizing objects in images), registration (aligning different images of the same or similar objects) and visualization (generating a comprehensive, potentially interactive, representation of the acquired imaging data), but also quantification of the accuracy and confidence in matching to create multidimensional measurements on the same biological object. Combining volume image together allow adding other information about the same object identified in both modalities, by fusing intensities with different meaning (different probes, or specific functional measurements) according to the modality used, or adding accurate shape information or neighborhood information only accessible from one of the modalities used.<br> <br> In this talk I will present the challenges of correlating 3D multimodal microscopies and of new methods to compute automatically the spatial relationship between sets of images or volumes of the same sample, but also to get the scientific information that is looked for. In particular, different ways of investigating and analyzing merged contents after fusion are relying on the way to quantitatively assess the accuracy of this fusion, and to take into account any artefact of registration , including interpolation, when merging the information itself at the object level.<br> I will present how we tackle some of these challenges in the new release of the software EC-Clem (Paul-Gilloteaux et al. 2017) by introducing the latest developments which makes it easier and faster to use, in particular for 3D registration, and how to use statistical tools provided to better understand and quantify the registration between two modalities (Potier et al. 2021; 2019). We will demonstrate the use of these tools on some recent applications in correlative workflows (Kounatidis et al. 2020; Scher et al. 2021).<br> <br> <b>Références:</b><br> Kounatidis, Ilias, Megan L. Stanifer, Michael A. Phillips, Perrine Paul-Gilloteaux, Xavier Heiligenstein, Hongchang Wang, Chidinma A. Okolo, et al. 2020. « 3D Correlative Cryo-Structured Illumination Fluorescence and Soft X-Ray Microscopy Elucidates Reovirus Intracellular Release Pathway ». <i>Cell</i> 182 (2): 515-530.e17. https://doi.org/10.1016/j.cell.2020.05.051.<br> Paul-Gilloteaux, Perrine, Xavier Heiligenstein, Martin Belle, Marie-Charlotte Domart, Banafshe Larijani, Lucy Collinson, Graca Raposo, et Jean Salamero. 2017. « eC-CLEM: flexible multidimensional registration software for correlative microscopies ». <i>Nature Methods</i> 14 (2): 102‑3. https://doi.org/10.1038/nmeth.4170.<br> Potier, Guillaume, Romain Capoulade, Jean Mérot, Frédéric Lavancier, Xavier Heiligenstein, Jean Salamero, et Perrine Paul-Gilloteaux. 2019. « Automatic Registration of Correlative Microscopies with Error Assessment and Applications for the Optimization of Multimodal Acquisitions. » <i>Microscopy and Microanalysis</i> 25 (S2): 1020‑21.<br> Potier, Guillaume, Frédéric Lavancier, Stephan Kunne, et Perrine Paul-Gilloteaux. 2021. « A registration error estimation framework for correlative imaging ». <i>arXiv:2103.06256 [cs, q-bio]</i>, mars. http://arxiv.org/abs/2103.06256.<br> Scher, Nadav, Katya Rechav, Perrine Paul-Gilloteaux, et Ori Avinoam. 2021. « In-Situ Fiducial Markers for 3D Correlative Cryo- Fluorescence and FIB-SEM Imaging ». Preprint. Cell Biology. https://doi.org/10.1101/2021.03.14.435311.<br> Walter, Andreas, Perrine Paul-Gilloteaux, Birgit Plochberger, Ludek Sefc, Paul Verkade, Julia G. Mannheim, Paul Slezak, et al. 2020. « Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon ». <i>Frontiers in Physics</i> 8 (avril): 47. https://doi.org/10.3389/fphy.2020.00047.