Light-Sheet Fluorescence Microscopy Hub

Light-Sheet Fluorescence Microscopy (LSFM) of cleared brain samples offers the unique opportunity of exploring brain complexity on large scales yet at cellular resolution. The European Laboratory for Non-Linear Spectroscopy (LENS) has gathered long-standing experience in the whole LSFM pipeline, comprising sample preparation (clearing and staining), the actual imaging using custom-designed optical setups, and image post-processing (volumetric stitching, compression, feature segmentation).

The LSFM LSP offers access to two microscopy setups capable of high-speed and high-resolution imaging with up to four-color acquisition. One system can accommodate large bulky samples such as a whole mouse brain, while the other microscope is designed for thin but large tissue slices (several cm in lateral size (max 10cm), 0.5mm to 1mm in thickness). Within the LSP, LENS can provide clearing and staining of the samples, imaging, and data processing (deskewing, stitching, cell localization or 3D fiber analysis) or can host external scientists that wish to use the microscopes or acquire technical skills in light-sheet microscopy. Specific projects need to be discussed beforehand to ensure optimal planning of resource usage and the organisation of specific training if needed.  

Data obtained with LSFM can be connected with that obtained from other physical facility in order to obtain multimodal analysis of the same tissue. In particular, samples can be acquired both with MRI and 3D-PLI before LSFM measurement, and can undergo SIB-SEM analysis after it. In addition, the 3D point clouds of the cells obtained from the analysis of the LSFM reconstruction can be used to perform modeling in the Cerebellar, Hippocampus or Basal Ganglia Modelling competence centers.  

Coordination role: Maintain, foster, and coordinate the network of LSPs across EBRAINS.  Coordination of the LSPs ecosystem and support for new LSPs that would like to be integrated. Identification of gaps in EBRAINS fundamental datasets. Identification and harmonization of fundamental datasets to be integrated in the EBRAINS infrastructure.