---
_id: '18052'
abstract:
- lang: eng
  text: 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.
acknowledged_ssus:
- _id: EM-Fac
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.
alternative_title:
- Neuromethods
article_processing_charge: No
author:
- first_name: David
  full_name: Kleindienst, David
  id: 42E121A4-F248-11E8-B48F-1D18A9856A87
  last_name: Kleindienst
- first_name: Tommaso
  full_name: Costanzo, Tommaso
  id: D93824F4-D9BA-11E9-BB12-F207E6697425
  last_name: Costanzo
  orcid: 0000-0001-9732-3815
- first_name: Ryuichi
  full_name: Shigemoto, Ryuichi
  id: 499F3ABC-F248-11E8-B48F-1D18A9856A87
  last_name: Shigemoto
  orcid: 0000-0001-8761-9444
citation:
  ama: '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. <i>New Aspects in Analyzing the Synaptic Organization of the
    Brain</i>. 1st ed. New York: Springer Nature; 2024:123-137. doi:<a href="https://doi.org/10.1007/978-1-0716-4019-7_8">10.1007/978-1-0716-4019-7_8</a>'
  apa: 'Kleindienst, D., Costanzo, T., &#38; Shigemoto, R. (2024). Automated Imaging
    and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning.
    In J. H. R. Lübke &#38; A. Rollenhagen (Eds.), <i>New Aspects in Analyzing the
    Synaptic Organization of the Brain</i> (1st ed., pp. 123–137). New York: Springer
    Nature. <a href="https://doi.org/10.1007/978-1-0716-4019-7_8">https://doi.org/10.1007/978-1-0716-4019-7_8</a>'
  chicago: 'Kleindienst, David, Tommaso Costanzo, and Ryuichi Shigemoto. “Automated
    Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep
    Learning.” In <i>New Aspects in Analyzing the Synaptic Organization of the Brain</i>,
    edited by Joachim H.R.  Lübke and Astrid Rollenhagen, 1st ed., 123–37. New York:
    Springer Nature, 2024. <a href="https://doi.org/10.1007/978-1-0716-4019-7_8">https://doi.org/10.1007/978-1-0716-4019-7_8</a>.'
  ieee: 'D. Kleindienst, T. Costanzo, and R. Shigemoto, “Automated Imaging and Analysis
    of Synapses in Freeze-Fracture Replica Samples with Deep Learning,” in <i>New
    Aspects in Analyzing the Synaptic Organization of the Brain</i>, 1st ed., J. H.
    R. Lübke and A. Rollenhagen, Eds. New York: Springer Nature, 2024, pp. 123–137.'
  ista: '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.'
  mla: Kleindienst, David, et al. “Automated Imaging and Analysis of Synapses in Freeze-Fracture
    Replica Samples with Deep Learning.” <i>New Aspects in Analyzing the Synaptic
    Organization of the Brain</i>, edited by Joachim H.R.  Lübke and Astrid Rollenhagen,
    1st ed., Springer Nature, 2024, pp. 123–37, doi:<a href="https://doi.org/10.1007/978-1-0716-4019-7_8">10.1007/978-1-0716-4019-7_8</a>.
  short: D. Kleindienst, T. Costanzo, R. Shigemoto, in:, J.H.R. Lübke, A. Rollenhagen
    (Eds.), New Aspects in Analyzing the Synaptic Organization of the Brain, 1st ed.,
    Springer Nature, New York, 2024, pp. 123–137.
corr_author: '1'
date_created: 2024-09-10T12:32:38Z
date_published: 2024-08-27T00:00:00Z
date_updated: 2025-04-14T07:27:15Z
day: '27'
department:
- _id: EM-Fac
- _id: RySh
doi: 10.1007/978-1-0716-4019-7_8
ec_funded: 1
edition: '1'
editor:
- first_name: 'Joachim H.R. '
  full_name: 'Lübke, Joachim H.R. '
  last_name: Lübke
- first_name: Astrid
  full_name: Rollenhagen, Astrid
  last_name: Rollenhagen
language:
- iso: eng
month: '08'
oa_version: None
page: 123-137
place: New York
project:
- _id: 25CA28EA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '694539'
  name: 'In situ analysis of single channel subunit composition in neurons: physiological
    implication in synaptic plasticity and behaviour'
publication: New Aspects in Analyzing the Synaptic Organization of the Brain
publication_identifier:
  eisbn:
  - '9781071640197'
  eissn:
  - 1940-6045
  isbn:
  - '9781071640180'
  issn:
  - 0893-2336
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples
  with Deep Learning
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2024'
...
---
_id: '11456'
abstract:
- lang: eng
  text: The proteomes of specialized structures, and the interactomes of proteins
    of interest, provide entry points to elucidate the functions of molecular machines.
    Here, we review a proximity-labeling strategy that uses the improved E. coli biotin
    ligase TurboID to characterize C. elegans protein complexes. Although the focus
    is on C. elegans neurons, the method is applicable regardless of cell type. We
    describe detailed extraction procedures that solubilize the bulk of C. elegans
    proteins and highlight the importance of tagging endogenous genes, to ensure physiological
    expression levels. We review issues associated with non-specific background noise
    and the importance of appropriate controls. As proof of principle, we review our
    analysis of the interactome of a presynaptic active zone protein, ELKS-1. Our
    aim is to provide a detailed protocol for TurboID-based proximity labeling in
    C. elegans and to highlight its potential and its limitations to characterize
    protein complexes and subcellular compartments in this animal.
acknowledgement: We thank de Bono lab members for the helpful comments on the manuscript.
  The biotin-auxotrophic E. coli strain MG1655bioB:kan was a generous gift from J.
  Cronan (University of Illinois) and was kindly sent to us by Jessica Feldman and
  Ariana Sanchez (Stanford University). dg398 pEntryslot2_mNeongreen::3XFLAG::stop
  and dg397 pEntryslot3_mNeongreen::3XFLAG::stop::unc-54 3’UTR entry vector were kindly
  sent by Dr. Dominique Glauser (University of Fribourg). This work was supported
  by an Advanced ERC Grant (269058 ACMO) and a Wellcome Investigator Award (209504/Z/17/Z)
  to MdB and an ISTplus Fellowship to MA (Marie Sklodowska-Curie agreement No 754411).
alternative_title:
- Neuromethods
article_processing_charge: No
author:
- first_name: Murat
  full_name: Artan, Murat
  id: C407B586-6052-11E9-B3AE-7006E6697425
  last_name: Artan
  orcid: 0000-0001-8945-6992
- first_name: Mario
  full_name: de Bono, Mario
  id: 4E3FF80E-F248-11E8-B48F-1D18A9856A87
  last_name: de Bono
  orcid: 0000-0001-8347-0443
citation:
  ama: 'Artan M, de Bono M. Proteomic Analysis of C. Elegans Neurons Using TurboID-Based
    Proximity Labeling. In: Yamamoto D, ed. <i>Behavioral Neurogenetics</i>. Vol 181.
    NM. New York: Springer Nature; 2022:277-294. doi:<a href="https://doi.org/10.1007/978-1-0716-2321-3_15">10.1007/978-1-0716-2321-3_15</a>'
  apa: 'Artan, M., &#38; de Bono, M. (2022). Proteomic Analysis of C. Elegans Neurons
    Using TurboID-Based Proximity Labeling. In D. Yamamoto (Ed.), <i>Behavioral Neurogenetics</i>
    (Vol. 181, pp. 277–294). New York: Springer Nature. <a href="https://doi.org/10.1007/978-1-0716-2321-3_15">https://doi.org/10.1007/978-1-0716-2321-3_15</a>'
  chicago: 'Artan, Murat, and Mario de Bono. “Proteomic Analysis of C. Elegans Neurons
    Using TurboID-Based Proximity Labeling.” In <i>Behavioral Neurogenetics</i>, edited
    by Daisuke Yamamoto, 181:277–94. NM. New York: Springer Nature, 2022. <a href="https://doi.org/10.1007/978-1-0716-2321-3_15">https://doi.org/10.1007/978-1-0716-2321-3_15</a>.'
  ieee: 'M. Artan and M. de Bono, “Proteomic Analysis of C. Elegans Neurons Using
    TurboID-Based Proximity Labeling,” in <i>Behavioral Neurogenetics</i>, vol. 181,
    D. Yamamoto, Ed. New York: Springer Nature, 2022, pp. 277–294.'
  ista: 'Artan M, de Bono M. 2022.Proteomic Analysis of C. Elegans Neurons Using TurboID-Based
    Proximity Labeling. In: Behavioral Neurogenetics. Neuromethods, vol. 181, 277–294.'
  mla: Artan, Murat, and Mario de Bono. “Proteomic Analysis of C. Elegans Neurons
    Using TurboID-Based Proximity Labeling.” <i>Behavioral Neurogenetics</i>, edited
    by Daisuke Yamamoto, vol. 181, Springer Nature, 2022, pp. 277–94, doi:<a href="https://doi.org/10.1007/978-1-0716-2321-3_15">10.1007/978-1-0716-2321-3_15</a>.
  short: M. Artan, M. de Bono, in:, D. Yamamoto (Ed.), Behavioral Neurogenetics, Springer
    Nature, New York, 2022, pp. 277–294.
corr_author: '1'
date_created: 2022-06-20T08:10:34Z
date_published: 2022-06-04T00:00:00Z
date_updated: 2025-04-14T07:43:58Z
day: '04'
department:
- _id: MaDe
doi: 10.1007/978-1-0716-2321-3_15
ec_funded: 1
editor:
- first_name: Daisuke
  full_name: Yamamoto, Daisuke
  last_name: Yamamoto
intvolume: '       181'
language:
- iso: eng
month: '06'
oa_version: None
page: 277-294
place: New York
project:
- _id: 23870BE8-32DE-11EA-91FC-C7463DDC885E
  grant_number: 209504/A/17/Z
  name: Molecular mechanisms of neural circuit function
- _id: 260C2330-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '754411'
  name: ISTplus - Postdoctoral Fellowships
publication: Behavioral Neurogenetics
publication_identifier:
  eisbn:
  - '9781071623213'
  eissn:
  - 1940-6045
  isbn:
  - '9781071623206'
  issn:
  - 0893-2336
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
series_title: NM
status: public
title: Proteomic Analysis of C. Elegans Neurons Using TurboID-Based Proximity Labeling
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 181
year: '2022'
...
---
OA_type: closed access
_id: '19990'
abstract:
- lang: eng
  text: Visualizing molecular localization at high resolution contributes to understanding
    of their functions and roles in physiological and pathological conditions. Sodium
    dodecyl sulfate-digested freeze-fracture replica labeling (SDS-FRL) is a powerful
    electron microscopy method to study high-resolution two-dimensional distribution
    of transmembrane proteins and their tightly associated proteins on platinum-carbon
    replica. During treatment with SDS, unfixed proteins and intracellular organelle
    are dissolved and integral membrane proteins captured and stabilized by carbon
    and platinum deposition are denatured, retaining most of their antigenicity, and
    exposed on exoplasmic and protoplasmic surfaces of lipid monolayers. The exposure
    of these antigens on the surface of replica facilitates the accessibility of antibodies
    and therefore provides higher labeling efficiency than those obtained with other
    immunoelectron microscopy techniques. In this chapter, we describe the protocols
    of SDS-FRL adapted for mammalian brain samples and an additional procedure for
    fluorescence-guided electron microscopy for replica immunolabeling.
acknowledgement: We thank Mitsuru Ikeda for preparing replica images used in Fig.
  2.
article_processing_charge: No
author:
- first_name: Harumi
  full_name: Harada, Harumi
  id: 2E55CDF2-F248-11E8-B48F-1D18A9856A87
  last_name: Harada
  orcid: 0000-0001-7429-7896
- first_name: Ryuichi
  full_name: Shigemoto, Ryuichi
  id: 499F3ABC-F248-11E8-B48F-1D18A9856A87
  last_name: Shigemoto
  orcid: 0000-0001-8761-9444
citation:
  ama: 'Harada H, Shigemoto R. High-Resolution Localization of Membrane Proteins by
    SDS-Digested Freeze-Fracture Replica Labeling (SDS-FRL). In: <i>Receptor and Ion
    Channel Detection in the Brain</i>. Neuromethods. Springer Nature; 2016:233-245.
    doi:<a href="https://doi.org/10.1007/978-1-4939-3064-7_17">10.1007/978-1-4939-3064-7_17</a>'
  apa: Harada, H., &#38; Shigemoto, R. (2016). High-Resolution Localization of Membrane
    Proteins by SDS-Digested Freeze-Fracture Replica Labeling (SDS-FRL). In <i>Receptor
    and Ion Channel Detection in the Brain</i> (pp. 233–245). Springer Nature. <a
    href="https://doi.org/10.1007/978-1-4939-3064-7_17">https://doi.org/10.1007/978-1-4939-3064-7_17</a>
  chicago: Harada, Harumi, and Ryuichi Shigemoto. “High-Resolution Localization of
    Membrane Proteins by SDS-Digested Freeze-Fracture Replica Labeling (SDS-FRL).”
    In <i>Receptor and Ion Channel Detection in the Brain</i>, 233–45. Neuromethods.
    Springer Nature, 2016. <a href="https://doi.org/10.1007/978-1-4939-3064-7_17">https://doi.org/10.1007/978-1-4939-3064-7_17</a>.
  ieee: H. Harada and R. Shigemoto, “High-Resolution Localization of Membrane Proteins
    by SDS-Digested Freeze-Fracture Replica Labeling (SDS-FRL),” in <i>Receptor and
    Ion Channel Detection in the Brain</i>, Springer Nature, 2016, pp. 233–245.
  ista: 'Harada H, Shigemoto R. 2016.High-Resolution Localization of Membrane Proteins
    by SDS-Digested Freeze-Fracture Replica Labeling (SDS-FRL). In: Receptor and Ion
    Channel Detection in the Brain. , 233–245.'
  mla: Harada, Harumi, and Ryuichi Shigemoto. “High-Resolution Localization of Membrane
    Proteins by SDS-Digested Freeze-Fracture Replica Labeling (SDS-FRL).” <i>Receptor
    and Ion Channel Detection in the Brain</i>, Springer Nature, 2016, pp. 233–45,
    doi:<a href="https://doi.org/10.1007/978-1-4939-3064-7_17">10.1007/978-1-4939-3064-7_17</a>.
  short: H. Harada, R. Shigemoto, in:, Receptor and Ion Channel Detection in the Brain,
    Springer Nature, 2016, pp. 233–245.
corr_author: '1'
date_created: 2025-07-10T13:56:06Z
date_published: 2016-02-02T00:00:00Z
date_updated: 2026-04-07T08:32:03Z
day: '02'
department:
- _id: RySh
doi: 10.1007/978-1-4939-3064-7_17
language:
- iso: eng
month: '02'
oa_version: None
page: 233-245
publication: Receptor and Ion Channel Detection in the Brain
publication_identifier:
  eisbn:
  - '9781493930647'
  eissn:
  - 1940-6045
  isbn:
  - '9781493930630'
  issn:
  - 0893-2336
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
series_title: Neuromethods
status: public
title: High-Resolution Localization of Membrane Proteins by SDS-Digested Freeze-Fracture
  Replica Labeling (SDS-FRL)
type: book_chapter
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2016'
...