Evidence map›Paper›PMID 32240622›Full record

ArticleMolecular metabolism2020

Genetic deletion of microRNA biogenesis in muscle cells reveals a hierarchical non-clustered network that controls focal adhesion signaling during muscle regeneration.

Edlira Luca, Katarina Turcekova, Angelika Hartung, Sebastian Mathes, Hubert Rehrauer, Jan Krützfeldt

Open access · goldAbstract read
In one paragraph

Article in Molecular metabolism, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.9field-weighted citation impact, top 32% 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

9 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Skeletal Muscle Regeneration in Cardiotoxin-Induced Muscle Injury Models.International journal of molecular sciences · 2022
    Review
  7. Review
  8. FGF-2-dependent signaling activated in aged human skeletal muscle promotes intramuscular adipogenesis.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  9. Article
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 at 3 institutions in 1 country.

Edlira LucaDivision of Endocrinology, Diabetes, and Clinical Nutrition, University Hospital Zurich, 8091, Switzerland.
Katarina TurcekovaDivision of Endocrinology, Diabetes, and Clinical Nutrition, University Hospital Zurich, 8091, Switzerland; Competence Center Personalized Medicine UZH/ETH, ETH Zurich and University of Zurich, 8091, Switzerland.
Angelika HartungDivision of Endocrinology, Diabetes, and Clinical Nutrition, University Hospital Zurich, 8091, Switzerland.
Sebastian MathesDivision of Endocrinology, Diabetes, and Clinical Nutrition, University Hospital Zurich, 8091, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, 8091, Switzerland.
Hubert RehrauerFunctional Genomics Center Zurich UZH/ETH, ETH Zurich and University of Zurich, 8091, Switzerland.
Jan KrützfeldtDivision of Endocrinology, Diabetes, and Clinical Nutrition, University Hospital Zurich, 8091, Switzerland; Competence Center Personalized Medicine UZH/ETH, ETH Zurich and University of Zurich, 8091, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, 8091, Switzerland. Electronic address: jan.kruetzfeldt@usz.ch.
University Hospital of Zurich · CHUniversity of Zurich · CHETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveDecreased muscle mass is a major contributor to age-related morbidity, and strategies to improve muscle regeneration during ageing are urgently needed. Our aim was to identify the subset of relevant microRNAs (miRNAs) that partake in critical aspects of muscle cell differentiation, irrespective of computational predictions, genomic clustering or differential expression of the miRNAs.

methodsmiRNA biogenesis was deleted in primary myoblasts using a tamoxifen-inducible CreLox system and combined with an add-back miRNA library screen. RNA-seq experiments, cellular signalling events, and glycogen synthesis, along with miRNA inhibitors, were performed in human primary myoblasts. Muscle regeneration in young and aged mice was assessed using the cardiotoxin (CTX) model.

resultsWe identified a hierarchical non-clustered miRNA network consisting of highly (miR-29a), moderately (let-7) and mildly active (miR-125b, miR-199a, miR-221) miRNAs that cooperate by directly targeting members of the focal adhesion complex. Through RNA-seq experiments comparing single versus combinatorial inhibition of the miRNAs, we uncovered a fundamental feature of this network, that miRNA activity inversely correlates to miRNA cooperativity. During myoblast differentiation, combinatorial inhibition of the five miRNAs increased activation of focal adhesion kinase (FAK), AKT, and p38 mitogen-activated protein kinase (MAPK), and improved myotube formation and insulin-dependent glycogen synthesis. Moreover, antagonizing the miRNA network in vivo following CTX-induced muscle regeneration enhanced muscle mass and myofiber formation in young and aged mice.

conclusionOur results provide novel insights into the dynamics of miRNA cooperativity and identify a miRNA network as therapeutic target for impaired focal adhesion signalling and muscle regeneration during ageing.

Indexed as

AnimalsCell DifferentiationCell LineFocal AdhesionsGene DeletionGene Regulatory NetworksHumansMiceMice, Inbred C57BLMicroRNAsMuscle DevelopmentMuscle Fibers, SkeletalMuscle, SkeletalMyoblastsRegenerationSignal TransductionMicroRNAsFocal adhesion signallingGlycogen synthesismicroRNA networkPrimary human muscle cellsSkeletal muscle regeneration

Identifiers

PMID32240622
PMCPMC7139120
OpenAlexW3010524494

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.