Evidence map›Paper›PMID 34162977›Full record

ArticleScientific reports2021

Reactive oxygen FIB spin milling enables correlative workflow for 3D super-resolution light microscopy and serial FIB/SEM of cultured cells.

Jing Wang, Steven Randolph, Qian Wu, Aurélien Botman, Jenna Schardt, Cedric Bouchet-Marquis, Xiaolin Nan, Chad Rue, Marcus Straw

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Volume electron microscopy.Nature reviews. Methods primers · 2022
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jing WangThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA. jing.wang5@thermofisher.com.
Steven RandolphThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.
Qian WuThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.
Aurélien BotmanThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.
Jenna SchardtThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.
Cedric Bouchet-MarquisThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.
Xiaolin NanKnight Cancer Early Detection Advanced Research Center, Oregon Health and Science University, 2720 S. Moody Ave., Portland, OR, 97201, USA.
Chad RueThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.
Marcus StrawThermo Fisher Scientific, 5350 NE Dawson Creek Drive, Hillsboro, OR, 97124, USA.

Funding

Defining mechanisms of Ras clustering and signaling in membrane nanodomains with multiplexed superresolution and correlative microscopiesR01GM132322 · NIGMS · OREGON HEALTH & SCIENCE UNIVERSITY · PI NAN, XIAOLIN · 2020 to 2023
$1.4M
NIGMS NIH HHS R01 GM132322
6 · The paper itself

Abstract

Correlative light and electron microscopy (CLEM) is a powerful tool for defining the ultrastructural context of molecularly-labeled biological specimens, particularly when superresolution fluorescence microscopy (SRM) is used for CLEM. Current CLEM, however, is limited by the stark differences in sample preparation requirements between the two modalities. For CLEM using SRM, the small region of interest (ROI) of either or both modalities also leads to low success rate and imaging throughput. To overcome these limitations, here we present a CLEM workflow based on a novel focused ion beam/scanning electron microscope (FIB/SEM) compatible with common SRM for imaging biological specimen with ultrahigh 3D resolution and improved imaging throughput. By using a reactive oxygen source in a plasma FIB (PFIB) and a rotating sample stage, the novel FIB/SEM was able to achieve several hundreds of micrometer large area 3D analysis of resin embedded cells through a process named oxygen serial spin mill (OSSM). Compared with current FIB mechanisms, OSSM offers gentle erosion, highly consistent slice thickness, reduced charging during SEM imaging, and improved SEM contrast without increasing the dose of post-staining and fixation. These characteristics of OSSM-SEM allowed us to pair it with interferometric photoactivated localization microscopy (iPALM), a recent SRM technique that affords 10-20 nm isotropic spatial resolution on hydrated samples, for 3D CLEM imaging. We demonstrate a CLEM workflow generalizable to using other SRM strategies using mitochondria in human osteosarcoma (U2OS) cells as a model system, where immunostained TOM20, a marker for the mitochondrial outer membrane, was used for iPALM. Owing to the large scan area of OSSM-SEM, it is now possible to select as many FOVs as needed for iPALM and conveniently re-locate them in EM, this improving the imaging throughput. The significantly reduced dose of post-fixation also helped to better preserve the sample ultrastructures as evidenced by the excellent 3D registration between OSSM-SEM and iPALM images and by the accurate localization of TOM20 (by iPALM) to the peripheries of mitochondria (by OSSM-SEM). These advantages make OSSM-SEM an ideal modality for CLEM applications. As OSSM-SEM is still in development, we also discuss some of the remaining issues and the implications to biological imaging with SEM alone or with CLEM.

Indexed as

Bone NeoplasmsCell Line, TumorCells, CulturedFiducial MarkersFluorescent DyesGoldHumansImage Processing, Computer-AssistedImaging, Three-DimensionalMicroscopyMicroscopy, Electron, ScanningMicroscopy, Scanning ProbeMitochondriaNanotubesOsteosarcomaWorkflowFluorescent DyesGold

Identifiers

PMID34162977
PMCPMC8222390

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.