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Abstract

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington’s disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes.

Jeremy Linsley, Atmiyata Tripathi et al. optimise culturing techniques and develop a microscopy platform and that can automatically image and track single neurons within organotypic slices for up to a three-week period. Using a model of polyQ neurodegeneration, they show that this method can assess longitudinal cell changes with high accuracy.

Details

1009240
Business indexing term
Identifier / keyword
Title
Automated four-dimensional long term imaging enables single cell tracking within organotypic brain slices to study neurodevelopment and degeneration
Author
Linsley, Jeremy W 1   VIAFID ORCID Logo  ; Tripathi Atmiyata 1 ; Epstein, Irina 1 ; Schmunk Galina 2 ; Mount, Elliot 3 ; Campioni, Matthew 3 ; Oza Viral 3 ; Barch Mariya 3 ; Javaherian Ashkan 3 ; Nowakowski, Tomasz J 2 ; Samsi Siddharth 4 ; Finkbeiner, Steven 5 

 Gladstone Center for Systems and Therapeutics, San Francisco, USA 
 University of California, Department of Anatomy, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811) 
 Gladstone Center for Systems and Therapeutics, San Francisco, USA (GRID:grid.266102.1) 
 University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Luxembourg, Luxembourg (GRID:grid.16008.3f) (ISNI:0000 0001 2295 9843); MIT Lincoln Laboratory, Lexington, USA (GRID:grid.116068.8) (ISNI:0000 0001 2341 2786) 
 Gladstone Center for Systems and Therapeutics, San Francisco, USA (GRID:grid.116068.8); University of California, Neuroscience Graduate Program, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of California, Biomedical Sciences and Neuroscience Graduate Program, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); Gladstone Institutes, Taube/Koret Center for Neurodegenerative Disease, San Francisco, USA (GRID:grid.249878.8) (ISNI:0000 0004 0572 7110); University of California, Department of Neurology, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811); University of California, Department of Physiology, San Francisco, USA (GRID:grid.266102.1) (ISNI:0000 0001 2297 6811) 
Publication title
Volume
2
Issue
1
Publication year
2019
Publication date
2019
Publisher
Nature Publishing Group
Place of publication
London
Country of publication
United States
Publication subject
e-ISSN
23993642
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2019-05-01
Milestone dates
2019-04-04 (Registration); 2018-08-28 (Received); 2019-03-18 (Accepted)
Publication history
 
 
   First posting date
01 May 2019
ProQuest document ID
2389675891
Document URL
https://www.proquest.com/scholarly-journals/automated-four-dimensional-long-term-imaging/docview/2389675891/se-2?accountid=208611
Copyright
© The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2023-11-28
Database
2 databases
  • ProQuest One Academic
  • ProQuest One Academic