Evidence map›Paper›PMID 36094473›Full record

ArticleeLife2022

Unfolding and identification of membrane proteins in situ.

Nicola Galvanetto, Zhongjie Ye, Arin Marchesi, Simone Mortal, Sourav Maity, Alessandro Laio, Vincent Torre

Open access · goldAbstract read
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
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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

7 authors at 3 institutions in 4 countries.

Nicola Galvanetto *International School for Advanced Studies, Trieste, Italy.ORCID 0000-0002-0408-1747
Zhongjie Ye *International School for Advanced Studies, Trieste, Italy.ORCID 0000-0003-0306-5267
Arin MarchesiNano Life Science Institute, Kanazawa Medical University, Kanazawa, Japan.ORCID 0000-0002-8219-1642
Simone MortalInternational School for Advanced Studies, Trieste, Italy.ORCID 0000-0001-6534-9324
Sourav MaityInternational School for Advanced Studies, Trieste, Italy.
Alessandro LaioInternational School for Advanced Studies, Trieste, Italy.
Vincent TorreInternational School for Advanced Studies, Trieste, Italy.ORCID 0000-0001-8133-3584
Scuola Internazionale Superiore di Studi Avanzati · ITMarche Polytechnic University · ITThe Abdus Salam International Centre for Theoretical Physics (ICTP) · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-molecule force spectroscopy (SMFS) uses the cantilever tip of an atomic force microscopy (AFM) to apply a force able to unfold a single protein. The obtained force-distance curve encodes the unfolding pathway, and from its analysis it is possible to characterize the folded domains. SMFS has been mostly used to study the unfolding of purified proteins, in solution or reconstituted in a lipid bilayer. Here, we describe a pipeline for analyzing membrane proteins based on SMFS, which involves the isolation of the plasma membrane of single cells and the harvesting of force-distance curves directly from it. We characterized and identified the embedded membrane proteins combining, within a Bayesian framework, the information of the shape of the obtained curves, with the information from mass spectrometry and proteomic databases. The pipeline was tested with purified/reconstituted proteins and applied to five cell types where we classified the unfolding of their most abundant membrane proteins. We validated our pipeline by overexpressing four constructs, and this allowed us to gather structural insights of the identified proteins, revealing variable elements in the loop regions. Our results set the basis for the investigation of the unfolding of membrane proteins in situ, and for performing proteomics from a membrane fragment.

Indexed as

Lipid BilayersMembrane ProteinsBayes TheoremMicroscopy, Atomic ForceProtein UnfoldingProteomicsLipid BilayersMembrane Proteinsatomic force microscopymolecular biophysicsprotein identificationratsingle-molecule force spectroscopystructural biology

Identifiers

PMID36094473
PMCPMC9531951
OpenAlexW4295292864

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.