Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning
Kleindienst D, Costanzo T, Shigemoto R. 2024.Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In: New Aspects in Analyzing the Synaptic Organization of the Brain. Neuromethods, , 123–137.
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Book Chapter
| Published
| English
Scopus indexed
Book Editor
Lübke, Joachim H.R. ;
Rollenhagen, Astrid
Corresponding author has ISTA affiliation
Department
Series Title
Neuromethods
Abstract
Sodium dodecyl sulfate-digested freeze-fracture replica labeling (SDS-FRL) is an electron microscope (EM) sample preparation technique which allows for high-resolution visualization of membrane proteins with high sensitivity. However, image acquisition of specific replica profiles such as synapses in a large field of EM view needs a valid experience and a long time for manual searching. Here, we describe how to utilize deep learning for automatizing image acquisition of specific profiles of interest in replica samples. This protocol facilitates the labor-intensive collection of EM images, in particular for rare profiles. We provide instructions for using SerialEM image acquisition software in conjunction with object detection by our newly developed deep learning software DarEM, to automatically acquire tilt series of all synapses in a selected region. We then show how to perform a mostly automated analysis of gold particle labeling in the acquired images by utilizing Darea software.
Publishing Year
Date Published
2024-08-27
Book Title
New Aspects in Analyzing the Synaptic Organization of the Brain
Publisher
Springer Nature
Acknowledgement
This research was supported by the European Research Council Advanced Grant 694539 to RS and by the Scientific Service Units of IST Austria through resources provided by the Electron Microscopy Facility.
Acknowledged SSUs
Page
123-137
ISBN
ISSN
eISSN
IST-REx-ID
Cite this
Kleindienst D, Costanzo T, Shigemoto R. Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In: Lübke JHR, Rollenhagen A, eds. New Aspects in Analyzing the Synaptic Organization of the Brain. 1st ed. New York: Springer Nature; 2024:123-137. doi:10.1007/978-1-0716-4019-7_8
Kleindienst, D., Costanzo, T., & Shigemoto, R. (2024). Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In J. H. R. Lübke & A. Rollenhagen (Eds.), New Aspects in Analyzing the Synaptic Organization of the Brain (1st ed., pp. 123–137). New York: Springer Nature. https://doi.org/10.1007/978-1-0716-4019-7_8
Kleindienst, David, Tommaso Costanzo, and Ryuichi Shigemoto. “Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning.” In New Aspects in Analyzing the Synaptic Organization of the Brain, edited by Joachim H.R. Lübke and Astrid Rollenhagen, 1st ed., 123–37. New York: Springer Nature, 2024. https://doi.org/10.1007/978-1-0716-4019-7_8.
D. Kleindienst, T. Costanzo, and R. Shigemoto, “Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning,” in New Aspects in Analyzing the Synaptic Organization of the Brain, 1st ed., J. H. R. Lübke and A. Rollenhagen, Eds. New York: Springer Nature, 2024, pp. 123–137.
Kleindienst D, Costanzo T, Shigemoto R. 2024.Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In: New Aspects in Analyzing the Synaptic Organization of the Brain. Neuromethods, , 123–137.
Kleindienst, David, et al. “Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning.” New Aspects in Analyzing the Synaptic Organization of the Brain, edited by Joachim H.R. Lübke and Astrid Rollenhagen, 1st ed., Springer Nature, 2024, pp. 123–37, doi:10.1007/978-1-0716-4019-7_8.
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