GSE202636
Spatial Transcriptomics correlated Electron Microscopy [scRNA-Seq]
Current spatial transcriptomics methods identify cell types and states in a spatial context but lack morphological information. Electron microscopy, in contrast, provides structural details at nanometer resolution without decoding the diverse cellular states and identity.  STEM address this limitation by correlating multiplexed error-robust FISH with electron microscopy from adjacent tissue sections. Using STEM to characterize demyelinated lesions in mice, we were able to bridge spatially resolved transcriptional data with morphological information on cell identities. This approach allowed us to link the morphology of foamy microglia and interferon-response microglia with their transcriptional signatures. Overall design: CD11b+ cells were isolated by flow-cytometry from brain white and grey matter of control mice and mice with white-matter demyelination injury induced by lysophosphatidylcholine injection and analyzed by scRNA-Seq