Evidence map›Paper›PMID 31844138›Full record

ArticleScientific reports2019

AutoCLEM: An Automated Workflow for Correlative Live-Cell Fluorescence Microscopy and Cryo-Electron Tomography.

Xiaofeng Fu, Jiying Ning, Zhou Zhong, Zandrea Ambrose, Simon Charles Watkins, Peijun Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
  6. Recent advances in correlative cryo-light and electron microscopy.Current opinion in structural biology · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Recent advances and current trends in cryo-electron microscopy.Current opinion in structural biology · 2022
    Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. To the Surface and Back: Exo- and Endocytic Pathways inFrontiers in cell and developmental biology · 2021
    Review
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

6 authors.

Xiaofeng FuDepartment of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
Jiying NingDepartment of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
Zhou ZhongDepartment of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
Zandrea AmbroseDepartment of Microbiology and Molecular Genetics, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
Simon Charles WatkinsDepartment of Cell Biology and Physiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA.
Peijun ZhangDepartment of Structural Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15260, USA. peijun@strubi.ox.ac.uk.ORCID http://orcid.org/0000-0003-1803-691X

Funding

X-Ray Core P50GM082251 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CALERO, GUILLERMO ALBERTO · 2007 to 2018
$48.1M
Technology Development 2: MAS NMR and dynamic nuclear polarization for HIV-1 structural biologyP50AI150481 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI GRONENBORN, ANGELA M. · 2019 to 2021
$14.1M
NIAID NIH HHS P50 AI150481NIGMS NIH HHS P50 GM082251RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) BB/S003339/1Wellcome Trust 206422/Z/17/ZWellcome Trust (Wellcome) 206422/Z/17/Z
6 · The paper itself

Abstract

Correlative light and electron microscopy (CLEM) combines the strengths of both light and electron imaging modalities and enables linking of biological spatiotemporal information from live-cell fluorescence light microscopy (fLM) to high-resolution cellular ultra-structures from cryo-electron microscopy and tomography (cryoEM/ET). This has been previously achieved by using fLM signals to localize the regions of interest under cryogenic conditions. The correlation process, however, is often tedious and time-consuming with low throughput and limited accuracy, because multiple correlation steps at different length scales are largely carried out manually. Here, we present an experimental workflow, AutoCLEM, which overcomes the existing limitations and improves the performance and throughput of CLEM methods, and associated software. The AutoCLEM system encompasses a high-speed confocal live-cell imaging module to acquire an automated fLM grid atlas that is linked to the cryoEM grid atlas, followed by cryofLM imaging after freezing. The fLM coordinates of the targeted areas are automatically converted to cryoEM/ET and refined using fluorescent fiducial beads. This AutoCLEM workflow significantly accelerates the correlation efficiency between live-cell fluorescence imaging and cryoEM/ET structural analysis, as demonstrated by visualizing human immunodeficiency virus type 1 (HIV-1) interacting with host cells.

Indexed as

Cells, CulturedCryoelectron MicroscopyElectron Microscope TomographyHEK293 CellsHIV-1HIV InfectionsHumansHuman Umbilical Vein Endothelial CellsMicroscopy, FluorescenceSoftwareWorkflow

Identifiers

PMID31844138
PMCPMC6915765

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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.