Evidence map›Paper›PMID 26757959›Full record

ArticleScientific reports2016

α-Synuclein and huntingtin exon 1 amyloid fibrils bind laterally to the cellular membrane.

Elodie Monsellier, Luc Bousset, Ronald Melki

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  16. Huntington disease: Advances in the understanding of its mechanisms.Clinical parkinsonism & related disorders · 2020
    Review
  17. Review
  18. 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

3 authors.

Elodie MonsellierParis-Saclay Institute of Neuroscience, Centre National de la Recherche Scientifique, Université Paris-Saclay, Gif-sur-Yvette, France.
Luc BoussetParis-Saclay Institute of Neuroscience, Centre National de la Recherche Scientifique, Université Paris-Saclay, Gif-sur-Yvette, France.
Ronald MelkiParis-Saclay Institute of Neuroscience, Centre National de la Recherche Scientifique, Université Paris-Saclay, Gif-sur-Yvette, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fibrillar aggregates involved in neurodegenerative diseases have the ability to spread from one cell to another in a prion-like manner. The underlying molecular mechanisms, in particular the binding mode of the fibrils to cell membranes, are poorly understood. In this work we decipher the modality by which aggregates bind to the cellular membrane, one of the obligatory steps of the propagation cycle. By characterizing the binding properties of aggregates made of α-synuclein or huntingtin exon 1 protein displaying similar composition and structure but different lengths to mammalian cells we demonstrate that in both cases aggregates bind laterally to the cellular membrane, with aggregates extremities displaying little or no role in membrane binding. Lateral binding to artificial liposomes was also observed by transmission electron microscopy. In addition we show that although α-synuclein and huntingtin exon 1 fibrils bind both laterally to the cellular membrane, their mechanisms of interaction differ. Our findings have important implications for the development of future therapeutic tools that aim to block protein aggregates propagation in the brain.

Indexed as

alpha-SynucleinAmyloidAnimalsBrainCell LineCell MembraneExonsHumansHuntingtin ProteinLipid MetabolismMicePermeabilityProtein AggregatesProtein BindingProtein ConformationProteolysisalpha-SynucleinAmyloidHTT protein, humanHuntingtin ProteinProtein AggregatesRecombinant ProteinsUnilamellar Liposomes

Identifiers

PMID26757959
PMCPMC4725933

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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.