With the rapid evolution in the automation of serial electron microscopy in life sciences, the acquisition of terabyte-sized datasets is becoming increasingly common. High resolution serial block-face imaging (SBEM) of biological tissues offers the opportunity to segment and reconstruct nanoscale structures to reveal spatial features previously inaccessible with simple, single section, two-dimensional images, with a particular focus on glial cells, whose reconstruction efforts in literature are still limited, compared to neurons. Here, we imaged a 750000 cubic micron volume of the somatosensory cortex from a juvenile P14 rat, with 20 nm accuracy. We recognized a total of 186 cells using their nuclei, and classified them as neuronal or glial based on features of the soma and the processes. We reconstructed for the first time 4 almost complete astrocytes and neurons, 4 complete microglia and 4 complete pericytes, including their intracellular mitochondria, 186 nuclei and 213 myelinated axons. We then performed quantitative analysis on the three-dimensional models. Out of the data that we generated, we observed that neurons have larger nuclei, which correlated with their lesser density, and that astrocytes and pericytes have a higher surface to volume ratio, compared to other cell types. All reconstructed morphologies represent an important resource for computational neuroscientists, as morphological quantitative information can be inferred, to tune simulations that take into account the spatial compartmentalization of the different cell types.
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We thank all the students and interns from the various KAUST programs, including VSRP, VS and KGSP, that participated to the segmentation of this dataset: Nicolas Gagnon, Fernanda Vargas, Jose Maria Martinez De Paz, Mohammed Jawhari, Dana Almedallah, Danielle Gaitor, Tajamul Hussain, Hajar AlReefi, Juamanh Alsawaf, Fatima Albazron, Bayan Khojah, Jumana Baghabra, Rana Alrabeh, and a very special thanks to Mohammed AlThunayan, a very talented student who passed away in his 20s. We also thank the KVL for the technical support, in particular Glendon Holst and Thomas Theussl. We thank Paola Bezzi (DNF, UNIL) for kindly providing brain sections for EM analysis, Graham Knott and Stephanie Rosset (BioEM, EPFL) for the technical support in the preparation of the sample for EM.