Automated high-throughput mouse transsynaptic viral tracing using iDISCO+ tissue clearing, light-sheet microscopy, and BrainPipe

Thomas J. Pisano*, Austin T. Hoag, Zahra M. Dhanerawala, Sara R. Guariglia, Caroline Jung, Henk Jan Boele, Kelly M. Seagraves, Jessica L. Verpeut, Samuel S.H. Wang*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
23 Downloads (Pure)

Abstract

Transsynaptic viral tracing requires tissue sectioning, manual cell counting, and anatomical assignment, all of which are time intensive. We describe a protocol for BrainPipe, a scalable software for automated anatomical alignment and object counting in light-sheet microscopy volumes. BrainPipe can be generalized to new counting tasks by using a new atlas and training a neural network for object detection. Combining viral tracing, iDISCO+ tissue clearing, and BrainPipe facilitates mapping of cerebellar connectivity to the rest of the murine brain. For complete details on the use and execution of this protocol, please refer to Pisano et al. (2021).

Original languageEnglish
Article number101289
JournalSTAR Protocols
Volume3
Issue number2
Early online date14 Apr 2022
DOIs
Publication statusPublished - 17 Jun 2022

Bibliographical note

Funding Information:
We thank Nicolas Renier for help with tissue-clearing optimization; Stephan Thiberge for microscopy help; Esteban Engel for viral use guidance; Shruthi Deivasigamani, Joseph Gotto, Joyce Lee, Laura Lynch, Caroline Jung, Sanjeev Janarthanan, Dafina Pacuku, Federico Uquillas, and Thaddeus Weigel for technical assistance; and Pavel Osten for project advice. This work was supported by NIH R01 NS045193, R01 MH115750, and U19 NS104648 (S.W.), F31 NS089303 (T.P.), Netherlands Organization for Scientific Research Veni ZonMW, 91618112 (H.-J.B), and Erasmus MC Fellowship 106958 (H.-J.B). T.P. and S.W. conceived and designed studies. T.P. performed virus injections and prepared tissue. T.P. J.V. S.G. and C.J. did tissue extraction and clearing. T.P. and K.S. optimized tissue clearing. Z.D. and T.P. imaged tissue and ran the computational data analysis pipeline for light-sheet data. T.P. and H.-J.B. performed data analysis and prepared figures. T.P. designed image analysis algorithms. A.H. built visualizations, created tutorials, and manages BrainPipe on Github. T.P. and S.W. wrote the initial draft of the manuscript, which was edited by all authors. The authors declare no competing interests.

Funding Information:
We thank Nicolas Renier for help with tissue-clearing optimization; Stephan Thiberge for microscopy help; Esteban Engel for viral use guidance; Shruthi Deivasigamani, Joseph Gotto, Joyce Lee, Laura Lynch, Caroline Jung, Sanjeev Janarthanan, Dafina Pacuku, Federico Uquillas, and Thaddeus Weigel for technical assistance; and Pavel Osten for project advice. This work was supported by NIH R01 NS045193 , R01 MH115750 , and U19 NS104648 (S.W.), F31 NS089303 (T.P.), Netherlands Organization for Scientific Research Veni ZonMW, 91618112 (H.-J.B), and Erasmus MC Fellowship 106958 (H.-J.B).

Publisher Copyright:
© 2022 The Author(s)

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