論文 - 詳細
| RRC ID | 81011 |
|---|---|
| 著者 | Leiwe MN, Fujimoto S, Baba T, Moriyasu D, Saha B, Sakaguchi R, Inagaki S, Imai T. |
| タイトル | Automated neuronal reconstruction with super-multicolour Tetbow labelling and threshold-based clustering of colour hues. |
| ジャーナル | 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. |
| 巻・号 | 15(1) |
| ページ | 5279 |
| 公開日 | 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 |
| IF | 12.121 |
| オルトメトリクス指標 |
オルトメトリクス指標項目
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| 最多言及媒体 | X(Twitter) |
| 各媒体での言及数の合計 | 94 |
| 過去6か月間でのオルトメトリクス指標の変動値 | 0.5 |
| リソース情報 | |
| 実験動物マウス | RBRC02189 |