دورية أكاديمية
Automated high-throughput mouse transsynaptic viral tracing using iDISCO+ tissue clearing, light-sheet microscopy, and BrainPipe.
العنوان: | Automated high-throughput mouse transsynaptic viral tracing using iDISCO+ tissue clearing, light-sheet microscopy, and BrainPipe. |
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المؤلفون: | Pisano TJ; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Hoag AT; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Dhanerawala ZM; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Guariglia SR; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Jung C; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Boele HJ; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA.; Department of Neuroscience, Erasmus University Medical Center, Rotterdam, the Netherlands., Seagraves KM; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Verpeut JL; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA., Wang SS; Neuroscience Institute, Princeton University, Washington Road, Princeton, NJ 08544, USA. |
المصدر: | STAR protocols [STAR Protoc] 2022 Apr 14; Vol. 3 (2), pp. 101289. Date of Electronic Publication: 2022 Apr 14 (Print Publication: 2022). |
نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't; Research Support, N.I.H., Extramural |
اللغة: | English |
بيانات الدورية: | Publisher: Cell Press Country of Publication: United States NLM ID: 101769501 Publication Model: eCollection Cited Medium: Internet ISSN: 2666-1667 (Electronic) Linking ISSN: 26661667 NLM ISO Abbreviation: STAR Protoc Subsets: MEDLINE |
أسماء مطبوعة: | Original Publication: [Cambridge, MA] : Cell Press, [2020]- |
مواضيع طبية MeSH: | Brain*/diagnostic imaging , Cerebellum*, Animals ; Mice ; Microscopy, Fluorescence/methods ; Software |
مستخلص: | 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). Competing Interests: The authors declare no competing interests. (© 2022 The Author(s).) |
References: | Cell. 2016 Jun 16;165(7):1789-1802. (PMID: 27238021) Nat Protoc. 2009;4(8):1157-66. (PMID: 19617887) PeerJ. 2014 Jun 19;2:e453. (PMID: 25024921) J Vis Exp. 2012 Jul 30;(65):. (PMID: 22871843) Nat Methods. 2020 Mar;17(3):261-272. (PMID: 32015543) Mol Ther. 2001 Feb;3(2):225-32. (PMID: 11237679) J Neurosci Methods. 2010 Dec 15;194(1):2-20. (PMID: 20004688) Mol Ther. 2005 Feb;11(2):327-31. (PMID: 15668145) Front Neuroinform. 2013 Dec 30;7:45. (PMID: 24416015) Front Neurosci. 2019 Aug 27;13:897. (PMID: 31507369) Cell Rep. 2021 Sep 21;36(12):109721. (PMID: 34551311) Development. 2009 Jun;136(12):1963-75. (PMID: 19465594) J Neurosci. 2017 Apr 12;37(15):4128-4144. (PMID: 28283558) BMC Bioinformatics. 2012 Nov 27;13:316. (PMID: 23181553) |
معلومات مُعتمدة: | F31 NS089303 United States NS NINDS NIH HHS; R01 MH115750 United States MH NIMH NIH HHS; R01 NS045193 United States NS NINDS NIH HHS; U19 NS104648 United States NS NINDS NIH HHS |
فهرسة مساهمة: | Keywords: Bioinformatics; Computer sciences; Microscopy; Neuroscience |
تواريخ الأحداث: | Date Created: 20220502 Date Completed: 20220503 Latest Revision: 20240515 |
رمز التحديث: | 20240515 |
مُعرف محوري في PubMed: | PMC9038781 |
DOI: | 10.1016/j.xpro.2022.101289 |
PMID: | 35496792 |
قاعدة البيانات: | MEDLINE |
تدمد: | 2666-1667 |
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DOI: | 10.1016/j.xpro.2022.101289 |