RRC ID 81011
Author Leiwe MN, Fujimoto S, Baba T, Moriyasu D, Saha B, Sakaguchi R, Inagaki S, Imai T.
Title Automated neuronal reconstruction with super-multicolour Tetbow labelling and threshold-based clustering of colour hues.
Journal Nat Commun
Abstract Fluorescence imaging is widely used for the mesoscopic mapping of neuronal connectivity. However, neurite reconstruction is challenging, especially when neurons are densely labelled. Here, we report a strategy for the fully automated reconstruction of densely labelled neuronal circuits. Firstly, we establish stochastic super-multicolour labelling with up to seven different fluorescent proteins using the Tetbow method. With this method, each neuron is labelled with a unique combination of fluorescent proteins, which are then imaged and separated by linear unmixing. We also establish an automated neurite reconstruction pipeline based on the quantitative analysis of multiple dyes (QDyeFinder), which identifies neurite fragments with similar colour combinations. To classify colour combinations, we develop unsupervised clustering algorithm, dCrawler, in which data points in multi-dimensional space are clustered based on a given threshold distance. Our strategy allows the reconstruction of neurites for up to hundreds of neurons at the millimetre scale without using their physical continuity.
Volume 15(1)
Pages 5279
Published 2024-6-25
DOI 10.1038/s41467-024-49455-y
PII 10.1038/s41467-024-49455-y
PMID 38918382
MeSH Algorithms Animals Cluster Analysis Color* Image Processing, Computer-Assisted / methods Luminescent Proteins / genetics Luminescent Proteins / metabolism Mice Neurites* / metabolism Neurons* / metabolism Optical Imaging / methods Staining and Labeling / methods
Resource
Mice RBRC02189