Comprehensive optical and data management infrastructure for high-throughput light-sheet microscopy of whole mouse brains
Year: 2015
Authors: Muellenbroich M.C., Silvestri L., Onofri L., Costantini I., Van’t Hoff M., Sacconi L., Iannello G., Pavone F.S.
Autors Affiliation: Univ Florence, European Lab Nonlinear Spect, Via Nello Carrara 1, I-50019 Sesto Fiorentino, Italy; Univ Florence, Dept Phys & Astron, I-50019 Sesto Fiorentino, Italy; CNR, Natl Inst Opt, I-50019 Sesto Fiorentino, Italy; Univ Campus Biomed Rome, I-00128 Rome, Italy; Int Ctr Computat Neurophoton, I-50019 Sesto Fiorentino, Italy.
Abstract: Comprehensive mapping and quantification of neuronal projections in the central nervous system requires high-throughput imaging of large volumes with microscopic resolution. To this end, we have developed a confocal light-sheet microscope that has been optimized for three-dimensional (3-D) imaging of structurally intact clarified whole-mount mouse brains. We describe the optical and electromechanical arrangement of the microscope and give details on the organization of the microscope management software. The software orchestrates all components of the microscope, coordinates critical timing and synchronization, and has been written in a versatile and modular structure using the LabVIEW language. It can easily be adapted and integrated to other microscope systems and has been made freely available to the light-sheet community. The tremendous amount of data routinely generated by light-sheet microscopy further requires novel strategies for data handling and storage. To complete the full imaging pipeline of our high-throughput microscope, we further elaborate on big data management from streaming of raw images up to stitching of 3-D datasets. The mesoscale neuroanatomy imaged at micron-scale resolution in those datasets allows characterization and quantification of neuronal projections in unsectioned mouse brains. (C) The Authors.
Journal/Review: NEUROPHOTONICS
Volume: 2 (4) Pages from: 041404-1 to: 041404-13
More Information: The authors are grateful to Riccardo Ballerini and Ahmed Hajeb from the mechanics workshop at LENS for fabrication of the sample chamber. We further thank Marco De Pas from the electronic workshop for his expertize in the fabrication of the custom-made amplification electronics. We thank GARR for the 10-GB optical fibre connection to CINECA and CINECA for hosting our data. The research leading to these results has received funding from the European Union Seventh Framework Program (FP7/2007-2013) under grant agreements No. 604102 (Human Brain Project) and No. 284464 (LASERLAB-EUROPE). The research has also been supported by the Italian Ministry for Education, University, and Research in the framework of the Flagship Project NanoMAX, by “Ente Cassa di Risparmio di Firenze” (private foundation). Research activities were also supported by Regione Toscana in the program POR-CreO 2007-2013 (Linea di interventi 1.5.a-1.6-Bando Unico R&S 2012) under grant agreement (CUP) No. 6408.30122011.026000201. M.v. H has a financial interest in Murmex by Distrio, Amsterdam, the Netherlands.KeyWords: Brain mapping; Computer programming languages; Data handling; Digital storage; Information management; Mammals; Microscopes; Throughput, High-Throughput Imaging; Light-sheet microscopies; Selective plane illuminations; Software management; Whole brains, Big data, adult; animal experiment; Animal tissue; Article; Brain tissue; Computer analysis; Controlled study; Data analysis software; Fluorescence analysis; High throughput light sheet microscopy; Illumination; Information processing; Managed care; Mathematical analysis; Microscopy; Mouse; Neuroanatomy; Neuroimaging; Nonhuman; Optics; Pipeline; Structure analysis; Three dimensional imaging; Transgenic mouseDOI: 10.1117/1.NPh.2.4.041404Citations: 17data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-09-29References taken from IsiWeb of Knowledge: (subscribers only)Connecting to view paper tab on IsiWeb: Click hereConnecting to view citations from IsiWeb: Click here