Evidence map›Paper›PMID 34732797›Full record

ArticleScientific reports2021

Profiling of ob/ob mice skeletal muscle exosome-like vesicles demonstrates combined action of miRNAs, proteins and lipids to modulate lipid homeostasis in recipient cells.

Audrey Jalabert, Laura Reininger, Emmanuelle Berger, Yohann Coute, Emmanuelle Meugnier, Alexis Forterre, Elizabeth Errazuriz-Cerda, Alain Geloen, Myriam Aouadi, Karim Bouzakri and 2 more

Open access · goldAbstract 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 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 17% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

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  19. Muscle and Adipose Tissue Communicate with Extracellular Vesicles.International journal of molecular sciences · 2022
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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

12 authors at 8 institutions in 2 countries.

Audrey JalabertCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France.
Laura ReiningerUMR DIATHEC, EA 7294, Centre Européen d'Etude du Diabète, Université de Strasbourg, Strasbourg, France.
Emmanuelle BergerCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France.
Yohann CouteUniv. Grenoble-Alpes, Inserm, CEA, UMR BioSanté U1292, CNRS CEA FR2048, Grenoble, France.
Emmanuelle MeugnierCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France.
Alexis ForterreCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France.
Elizabeth Errazuriz-CerdaCIQLE, Claude Bernard Lyon 1 University, Lyon, France.
Alain GeloenCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France.
Myriam AouadiCentre for Infectious Medicine, Department of Medicine, Karolinska Institutet, Huddinge, Sweden.
Karim BouzakriUMR DIATHEC, EA 7294, Centre Européen d'Etude du Diabète, Université de Strasbourg, Strasbourg, France.
Jennifer RieussetCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France.
Sophie RomeCarMeN Laboratory (INSERM 1060, INRAE 1397, INSA), Lyon-Sud Faculty of Medicine, University of Lyon, Oullins, France. srome@univ-lyon1.fr.
Université Claude Bernard Lyon 1 · FRInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FRUniversité de Strasbourg · FRCentre National de la Recherche Scientifique · FRInserm · FRKarolinska Institutet · SELaboratoire CarMeN · FRUniversité Grenoble Alpes · FR

Funding

Agence Nationale de la Recherche ANR-10-INBS-08Agence Nationale de la Recherche ANR ZENITH n°45000260ANR ANR-17-EURE-0003
6 · The paper itself

Abstract

We have determined the lipid, protein and miRNA composition of skeletal muscle (SkM)-released extracellular vesicles (ELVs) from Ob/ob (OB) vs wild-type (WT) mice. The results showed that atrophic insulin-resistant OB-SkM released less ELVs than WT-SkM, highlighted by a RAB35 decrease and an increase in intramuscular cholesterol content. Proteomic analyses of OB-ELVs revealed a group of 37 proteins functionally connected, involved in lipid oxidation and with catalytic activities. OB-ELVs had modified contents for phosphatidylcholine (PC 34-4, PC 40-3 and PC 34-0), sphingomyelin (Sm d18:1/18:1) and ceramides (Cer d18:1/18:0) and were enriched in cholesterol, likely to alleviated intracellular accumulation. Surprisingly many ELV miRNAs had a nuclear addressing sequence, and targeted genes encoding proteins with nuclear activities. Interestingly, SkM-ELV miRNA did not target mitochondria. The most significant function targeted by the 7 miRNAs altered in OB-ELVs was lipid metabolism. In agreement, OB-ELVs induced lipid storage in recipient adipocytes and increased lipid up-take and fatty acid oxidation in recipient muscle cells. In addition, OB-ELVs altered insulin-sensitivity and induced atrophy in muscle cells, reproducing the phenotype of the releasing OB muscles. These data suggest for the first time, a cross-talk between muscle cells and adipocytes, through the SkM-ELV route, in favor of adipose tissue expansion.

Indexed as

HomeostasisInsulin ResistanceAdipose TissueAnimalsExosomesLipidsMaleMiceMice, Inbred C57BLMice, ObeseMicroRNAsMuscle ProteinsMuscle, SkeletalMuscular AtrophyProteomeLipidsMicroRNAsMuscle ProteinsProteome

Identifiers

PMID34732797
PMCPMC8566600
OpenAlexW3211075164

What OpenQuestion holds

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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.