Recent advancements in tissue clearing technologies have offered unparalleled opportunities for researchers to explore the whole mouse brain at cellular resolution. With the expansion of this experimental technique, however, a scalable and easy-to-use computational tool is in demand to effectively analyze and integrate whole-brain mapping datasets. To that end, here we present CUBIC-Cloud, a cloud-based framework to quantify, visualize, and integrate mouse brain data. CUBIC-Cloud is a fully automated system where users can upload their whole-brain data, run analyses, and publish the results. We demonstrate the generality of CUBIC-Cloud by a variety of applications. First, we investigated the brain-wide distribution of five cell types. Second, we quantified Aβ plaque deposition in Alzheimer's disease model mouse brains. Third, we reconstructed a neuronal activity profile under LPS-induced inflammation by c-Fos immunostaining. Last, we show brain-wide connectivity mapping by pseudotyped rabies virus. Together, CUBIC-Cloud provides an integrative platform to advance scalable and collaborative whole-brain mapping.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9017177 | PMC |
http://dx.doi.org/10.1016/j.crmeth.2021.100038 | DOI Listing |
Nat Commun
July 2024
Department of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan.
Cell Rep Methods
June 2021
Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.
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