Evidence map›Paper›PMID 38343799›Full record

ArticleResearch square2024

SUB-Immunogold-SEM reveals nanoscale distribution of submembranous epitopes.

Katharine K Miller, Pei Wang, Nicolas Grillet

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Katharine K MillerDepartment of Otolaryngology-Head & Neck Surgery, School of Medicine, 240 Pasteur Drive, Stanford University, Stanford, CA 94305, USA.
Pei WangDepartment of Otolaryngology-Head & Neck Surgery, School of Medicine, 240 Pasteur Drive, Stanford University, Stanford, CA 94305, USA.
Nicolas GrilletDepartment of Otolaryngology-Head & Neck Surgery, School of Medicine, 240 Pasteur Drive, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-8007-9246
Stanford University · US

Funding

Molecular Genetics of Human Age-Related Hearing LossR01AG081608 · NIA · UNIVERSITY OF KENTUCKY · PI Nicolas Grillet · 2023 to 2026
$2.3M
Function of LOXHD1 in mechanosensory hair cellsR01DC016409 · NIDCD · STANFORD UNIVERSITY · PI GRILLET, NICOLAS · 2018 to 2022
$2.1M
High-resolution localization of the hair cell mechanotransduction channel components by immunogold-scanning electronic microscopyR21DC019457 · NIDCD · STANFORD UNIVERSITY · PI GRILLET, NICOLAS · 2021 to 2022
$435k
NIA NIH HHS R01 AG081608NIDCD NIH HHS R01 DC016409NIDCD NIH HHS R21 DC019457
6 · The paper itself

Abstract

Electron microscopy paired with immunogold labeling is the most precise tool for protein localization. However, these methods are either cumbersome, resulting in small sample numbers and restricted quantification, or limited to identifying protein epitopes external to the membrane. Here, we introduce SUB-immunogold-SEM, a scanning electron microscopy technique that detects intracellular protein epitopes proximal to the membrane. We identified four critical sample preparation factors that contribute to the method's sensitivity and validate its efficacy through precise localization and high-powered quantification of cytoskeletal and transmembrane proteins. We evaluated the capabilities of SUB-immunogold-SEM on cells with highly differentiated apical surfaces: (i) auditory hair cells, revealing the presence of nanoscale Myosin rings at the tip of stereocilia; and (ii) respiratory multiciliate cells, mapping the distribution of the SARS-CoV-2 receptor ACE2 along the motile cilia. SUB-immunogold-SEM provides a novel solution for nanoscale protein localization at the exposed surface of any cell.

Identifiers

PMID38343799
PMCPMC10854333
OpenAlexW4391092406

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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.