Muscle specific stress fibers give rise to sarcomeres in cardiomyocytes

  1. Aidan M Fenix
  2. Abigail C Neininger
  3. Nilay Taneja
  4. Karren Hyde
  5. Mike R Visetsouk
  6. Ryan J Garde
  7. Baohong Liu
  8. Benjamin R Nixon
  9. Annabelle E Manalo
  10. Jason R Becker
  11. Scott W Crawley
  12. David Mansfield bader
  13. Matthew J Tyska
  14. Qi Liu
  15. Jennifer H Gutzman
  16. Dylan Tyler Burnette  Is a corresponding author
  1. Vanderbilt University, United States
  2. University of Wisconsin, Milwaukee, United States
  3. Vanderbilt University Medical Center, United States
  4. University of Toledo, United States

Abstract

The sarcomere is the contractile unit within cardiomyocytes driving heart muscle contraction. We sought to test the mechanisms regulating actin and myosin filament assembly during sarcomere formation. Therefore, we developed an assay using human cardiomyocytes to monitor sarcomere assembly. We report a population of muscle stress fibers, similar to actin arcs in non-muscle cells, which are essential sarcomere precursors. We show sarcomeric actin filaments arise directly from muscle stress fibers. This requires formins (e.g., FHOD3), non-muscle myosin IIA and non-muscle myosin IIB. Furthermore, we show short cardiac myosin II filaments grow to form ~1.5 µm long filaments that then 'stitch' together to form the stack of filaments at the core of the sarcomere (i.e., the A-band). A-band assembly is dependent on the proper organization of actin filaments and, as such, is also dependent on FHOD3 and myosin IIB. We use this experimental paradigm to present evidence for a unifying model of sarcomere assembly.

Data availability

Sequencing data have been deposited in GEO under accession codes GSE119743. All other data generated or analysed during this study are included in the manuscript and supporting files.

The following data sets were generated

Article and author information

Author details

  1. Aidan M Fenix

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Abigail C Neininger

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Nilay Taneja

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Karren Hyde

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Mike R Visetsouk

    Department of Biological Sciences, University of Wisconsin, Milwaukee, Milwaukee, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Ryan J Garde

    Department of Biological Sciences, University of Wisconsin, Milwaukee, Milwaukee, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Baohong Liu

    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Benjamin R Nixon

    Department of Medicine, Vanderbilt University Medical Center, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1840-0179
  9. Annabelle E Manalo

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Jason R Becker

    Department of Medicine, Vanderbilt University Medical Center, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2107-8179
  11. Scott W Crawley

    Department of Biological Sciences, University of Toledo, Toledo, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. David Mansfield bader

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Matthew J Tyska

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Qi Liu

    Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Jennifer H Gutzman

    Department of Biological Sciences, University of Wisconsin, Milwaukee, Milwaukee, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7725-6923
  16. Dylan Tyler Burnette

    Department of Cell and Developmental Biology, Vanderbilt University, Nashville, United States
    For correspondence
    dylan.burnette@vanderbilt.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2571-7038

Funding

National Institute of General Medical Sciences (R35 GM125028)

  • Dylan Tyler Burnette

National Heart, Lung, and Blood Institute (F31 HL136081)

  • Aidan M Fenix

American Heart Association (16PRE29100014)

  • Aidan M Fenix

National Cancer Institute (P50 CA095103)

  • Dylan Tyler Burnette

American Heart Association (17SDG33460353)

  • Dylan Tyler Burnette

National Heart, Lung, and Blood Institute (RO1 HL037675)

  • David Mansfield bader

National Heart, Lung, and Blood Institute (K08 HL116803)

  • Jason R Becker

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2018, Fenix et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 7,629
    views
  • 796
    downloads
  • 85
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Aidan M Fenix
  2. Abigail C Neininger
  3. Nilay Taneja
  4. Karren Hyde
  5. Mike R Visetsouk
  6. Ryan J Garde
  7. Baohong Liu
  8. Benjamin R Nixon
  9. Annabelle E Manalo
  10. Jason R Becker
  11. Scott W Crawley
  12. David Mansfield bader
  13. Matthew J Tyska
  14. Qi Liu
  15. Jennifer H Gutzman
  16. Dylan Tyler Burnette
(2018)
Muscle specific stress fibers give rise to sarcomeres in cardiomyocytes
eLife 7:e42144.
https://doi.org/10.7554/eLife.42144

Share this article

https://doi.org/10.7554/eLife.42144

Further reading

    1. Cell Biology
    Dan Wu, Venkateswararao Eeda ... Weidong Wang
    Research Article

    Overnutrition engenders the expansion of adipose tissue and the accumulation of immune cells, in particular, macrophages, in the adipose tissue, leading to chronic low-grade inflammation and insulin resistance. In obesity, several proinflammatory subpopulations of adipose tissue macrophages (ATMs) identified hitherto include the conventional ‘M1-like’ CD11C-expressing ATM and the newly discovered metabolically activated CD9-expressing ATM; however, the relationship among ATM subpopulations is unclear. The ER stress sensor inositol-requiring enzyme 1α (IRE1α) is activated in the adipocytes and immune cells under obesity. It is unknown whether targeting IRE1α is capable of reversing insulin resistance and obesity and modulating the metabolically activated ATMs. We report that pharmacological inhibition of IRE1α RNase significantly ameliorates insulin resistance and glucose intolerance in male mice with diet-induced obesity. IRE1α inhibition also increases thermogenesis and energy expenditure, and hence protects against high fat diet-induced obesity. Our study shows that the ‘M1-like’ CD11c+ ATMs are largely overlapping with but yet non-identical to CD9+ ATMs in obese white adipose tissue. Notably, IRE1α inhibition diminishes the accumulation of obesity-induced metabolically activated ATMs and ‘M1-like’ ATMs, resulting in the curtailment of adipose inflammation and ensuing reactivation of thermogenesis, without augmentation of the alternatively activated M2 macrophage population. Our findings suggest the potential of targeting IRE1α for the therapeutic treatment of insulin resistance and obesity.

    1. Cell Biology
    2. Immunology and Inflammation
    Mykhailo Vladymyrov, Luca Marchetti ... Britta Engelhardt
    Tools and Resources

    The endothelial blood-brain barrier (BBB) strictly controls immune cell trafficking into the central nervous system (CNS). In neuroinflammatory diseases such as multiple sclerosis, this tight control is, however, disturbed, leading to immune cell infiltration into the CNS. The development of in vitro models of the BBB combined with microfluidic devices has advanced our understanding of the cellular and molecular mechanisms mediating the multistep T-cell extravasation across the BBB. A major bottleneck of these in vitro studies is the absence of a robust and automated pipeline suitable for analyzing and quantifying the sequential interaction steps of different immune cell subsets with the BBB under physiological flow in vitro. Here, we present the under-flow migration tracker (UFMTrack) framework for studying immune cell interactions with endothelial monolayers under physiological flow. We then showcase a pipeline built based on it to study the entire multistep extravasation cascade of immune cells across brain microvascular endothelial cells under physiological flow in vitro. UFMTrack achieves 90% track reconstruction efficiency and allows for scaling due to the reduction of the analysis cost and by eliminating experimenter bias. This allowed for an in-depth analysis of all behavioral regimes involved in the multistep immune cell extravasation cascade. The study summarizes how UFMTrack can be employed to delineate the interactions of CD4+ and CD8+ T cells with the BBB under physiological flow. We also demonstrate its applicability to the other BBB models, showcasing broader applicability of the developed framework to a range of immune cell-endothelial monolayer interaction studies. The UFMTrack framework along with the generated datasets is publicly available in the corresponding repositories.