IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v12y2021i1d10.1038_s41467-021-26095-0.html
   My bibliography  Save this article

Endurance exercise training-responsive miR-19b-3p improves skeletal muscle glucose metabolism

Author

Listed:
  • Julie Massart

    (Karolinska Institutet)

  • Rasmus J. O. Sjögren

    (Karolinska Institutet)

  • Brendan Egan

    (Karolinska Institutet
    Dublin City University)

  • Christian Garde

    (University of Copenhagen)

  • Magnus Lindgren

    (Karolinska Institutet)

  • Weifeng Gu

    (University of Massachusetts Medical School
    Department of Cell Biology and Neuroscience, University of California at Riverside)

  • Duarte M. S. Ferreira

    (Karolinska Institutet)

  • Mutsumi Katayama

    (Karolinska Institutet)

  • Jorge L. Ruas

    (Karolinska Institutet)

  • Romain Barrès

    (University of Copenhagen)

  • Donal J. O’Gorman

    (Dublin City University)

  • Juleen R. Zierath

    (Karolinska Institutet
    Karolinska Institutet
    University of Copenhagen)

  • Anna Krook

    (Karolinska Institutet)

Abstract

Skeletal muscle is a highly adaptable tissue and remodels in response to exercise training. Using short RNA sequencing, we determine the miRNA profile of skeletal muscle from healthy male volunteers before and after a 14-day aerobic exercise training regime. Among the exercise training-responsive miRNAs identified, miR-19b-3p was selected for further validation. Overexpression of miR-19b-3p in human skeletal muscle cells increases insulin signaling, glucose uptake, and maximal oxygen consumption, recapitulating the adaptive response to aerobic exercise training. Overexpression of miR-19b-3p in mouse flexor digitorum brevis muscle enhances contraction-induced glucose uptake, indicating that miR-19b-3p exerts control on exercise training-induced adaptations in skeletal muscle. Potential targets of miR-19b-3p that are reduced after aerobic exercise training include KIF13A, MAPK6, RNF11, and VPS37A. Amongst these, RNF11 silencing potentiates glucose uptake in human skeletal muscle cells. Collectively, we identify miR-19b-3p as an aerobic exercise training-induced miRNA that regulates skeletal muscle glucose metabolism.

Suggested Citation

  • Julie Massart & Rasmus J. O. Sjögren & Brendan Egan & Christian Garde & Magnus Lindgren & Weifeng Gu & Duarte M. S. Ferreira & Mutsumi Katayama & Jorge L. Ruas & Romain Barrès & Donal J. O’Gorman & Ju, 2021. "Endurance exercise training-responsive miR-19b-3p improves skeletal muscle glucose metabolism," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26095-0
    DOI: 10.1038/s41467-021-26095-0
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-021-26095-0
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-021-26095-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Victor Ambros, 2004. "The functions of animal microRNAs," Nature, Nature, vol. 431(7006), pages 350-355, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. José María Galván-Román & Ángel Lancho-Sánchez & Sergio Luquero-Bueno & Lorena Vega-Piris & Jose Curbelo & Marcos Manzaneque-Pradales & Manuel Gómez & Hortensia de la Fuente & Mara Ortega-Gómez & Javi, 2020. "Usefulness of circulating microRNAs miR-146a and miR-16-5p as prognostic biomarkers in community-acquired pneumonia," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-13, October.
    2. Kshitij Srivastava & Anvesha Srivastava, 2012. "Comprehensive Review of Genetic Association Studies and Meta-Analyses on miRNA Polymorphisms and Cancer Risk," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-1, November.
    3. Xing Chen & Jun Yin & Jia Qu & Li Huang, 2018. "MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-24, August.
    4. Yanyan Wang & Yujie Zhang & Chi Pan & Feixia Ma & Suzhan Zhang, 2015. "Prediction of Poor Prognosis in Breast Cancer Patients Based on MicroRNA-21 Expression: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-13, February.
    5. Thierry Chekouo & Francesco C. Stingo & James D. Doecke & Kim-Anh Do, 2015. "miRNA–target gene regulatory networks: A Bayesian integrative approach to biomarker selection with application to kidney cancer," Biometrics, The International Biometric Society, vol. 71(2), pages 428-438, June.
    6. Xing Chen & Li Huang, 2017. "LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction," PLOS Computational Biology, Public Library of Science, vol. 13(12), pages 1-28, December.
    7. Ang Li & Yingwei Deng & Yan Tan & Min Chen, 2021. "A novel miRNA-disease association prediction model using dual random walk with restart and space projection federated method," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-17, June.
    8. Charlotte Glinge & Sebastian Clauss & Kim Boddum & Reza Jabbari & Javad Jabbari & Bjarke Risgaard & Philipp Tomsits & Bianca Hildebrand & Stefan Kääb & Reza Wakili & Thomas Jespersen & Jacob Tfelt-Han, 2017. "Stability of Circulating Blood-Based MicroRNAs – Pre-Analytic Methodological Considerations," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-16, February.
    9. Alexander Link & Verena Becker & Ajay Goel & Thomas Wex & Peter Malfertheiner, 2012. "Feasibility of Fecal MicroRNAs as Novel Biomarkers for Pancreatic Cancer," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-9, August.
    10. Hossain Ahmed & Beyene Joseph, 2013. "Estimation of weighted log partial area under the ROC curve and its application to MicroRNA expression data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(6), pages 743-755, December.
    11. Hai Lian & Lei Wang & Jingmin Zhang, 2012. "Increased Risk of Breast Cancer Associated with CC Genotype of Has-miR-146a Rs2910164 Polymorphism in Europeans," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-7, February.
    12. Fabricio F Costa & Jared M Bischof & Elio F Vanin & Rishi R Lulla & Min Wang & Simone T Sredni & Veena Rajaram & Maria de Fátima Bonaldo & Deli Wang & Stewart Goldman & Tadanori Tomita & Marcelo B Soa, 2011. "Identification of MicroRNAs as Potential Prognostic Markers in Ependymoma," PLOS ONE, Public Library of Science, vol. 6(10), pages 1-10, October.
    13. Le Thi Truc Linh, 2018. "The Microrna 29 family and its regulation," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 8(1), pages 18-27.
    14. Seyedehsadaf Asfa & Halil Ibrahim Toy & Reza Arshinchi Bonab & George P. Chrousos & Athanasia Pavlopoulou & Styliani A. Geronikolou, 2023. "Soft Tissue Ewing Sarcoma Cell Drug Resistance Revisited: A Systems Biology Approach," IJERPH, MDPI, vol. 20(13), pages 1-17, July.
    15. Man-Tang Qiu & Jing-Wen Hu & Xiang-Xiang Ding & Xin Yang & Zhi Zhang & Rong Yin & Lin Xu, 2012. "Hsa-miR-499 rs3746444 Polymorphism Contributes to Cancer Risk: A Meta-Analysis of 12 Studies," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
    16. Li Li & Yunjian Sheng & Lin Lv & Jian Gao, 2013. "The Association between Two MicroRNA Variants (miR-499, miR-149) and Gastrointestinal Cancer Risk: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-1, November.
    17. Blanca Elena Castro-Magdonel & Manuela Orjuela & Diana E Alvarez-Suarez & Javier Camacho & Lourdes Cabrera-Muñoz & Stanislaw Sadowinski-Pine & Aurora Medina-Sanson & Citlali Lara-Molina & Daphne Garcí, 2020. "Circulating miRNome detection analysis reveals 537 miRNAS in plasma, 625 in extracellular vesicles and a discriminant plasma signature of 19 miRNAs in children with retinoblastoma from which 14 are al," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-19, April.
    18. Adam Emmer, 2019. "The careers behind and the impact of solo author articles in Nature and Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 825-840, August.
    19. Ahmed Hossain & Joseph Beyene, 2015. "Application of skew-normal distribution for detecting differential expression to microRNA data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 477-491, March.
    20. Lianjun Zhang & Le Xuan Truong Nguyen & Ying-Chieh Chen & Dijiong Wu & Guerry J. Cook & Dinh Hoa Hoang & Casey J. Brewer & Xin He & Haojie Dong & Shu Li & Man Li & Dandan Zhao & Jing Qi & Wei-Kai Hua , 2021. "Targeting miR-126 in inv(16) acute myeloid leukemia inhibits leukemia development and leukemia stem cell maintenance," Nature Communications, Nature, vol. 12(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26095-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.