A transcriptomics resource reveals a transcriptional transition during ordered sarcomere morphogenesis in flight muscle

  1. Maria L Spletter  Is a corresponding author
  2. Christiane Barz
  3. Assa Yeroslaviz
  4. Xu Zhang
  5. Sandra B Lemke
  6. Adrien Bonnard
  7. Erich Brunner
  8. Giovanni Cardone
  9. Konrad Basler
  10. Bianca H Habermann
  11. Frank Schnorrer  Is a corresponding author
  1. Max Planck Institute of Biochemistry, Germany
  2. Aix Marseille University, France
  3. University of Zurich, Switzerland

Abstract

Muscles organise pseudo-crystalline arrays of actin, myosin and titin filaments to build force-producing sarcomeres. To study sarcomerogenesis, we have generated a transcriptomics resource of developing Drosophila flight muscles and identified 40 distinct expression profile clusters. Strikingly, most sarcomeric components group in two clusters, which are strongly induced after all myofibrils have been assembled, indicating a transcriptional transition during myofibrillogenesis. Following myofibril assembly, many short sarcomeres are added to each myofibril. Subsequently, all sarcomeres mature, reaching 1.5 µm diameter and 3.2 µm length and acquiring stretch-sensitivity. The efficient induction of the transcriptional transition during myofibrillogenesis, including the transcriptional boost of sarcomeric components, requires in part the transcriptional regulator Spalt major. As a consequence of Spalt knock-down, sarcomere maturation is defective and fibers fail to gain stretch-sensitivity. Together, this defines an ordered sarcomere morphogenesis process under precise transcriptional control - a concept that may also apply to vertebrate muscle or heart development.

Data availability

Processed data from DESeq2, Mfuzz and GO-Elite are available in Supplementary Files 1, 2, 4. mRNA-Seq data are publicly available from NCBI's Gene Expression Omnibus (GEO) under accession number GSE107247. Fiji scripts for analysis of sarcomere length, myofibril width and myofibril diameter are available from https://imagej.net/MyofibrilJ. Raw data used to generate all plots presented in figure panels are available in the source data files for Figures 1, 5, 6, 7 and 8. Data on statistical test results are presented in Supplementary File 5.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Maria L Spletter

    Muscle Dynamics Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    For correspondence
    maria.spletter@bmc.med.lmu.de
    Competing interests
    The authors declare that no competing interests exist.
  2. Christiane Barz

    Muscle Dynamics Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Assa Yeroslaviz

    Computational Biology Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Xu Zhang

    Muscle Dynamics Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1628-9895
  5. Sandra B Lemke

    Muscle Dynamics Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  6. Adrien Bonnard

    IBDM, Aix Marseille University, Marseille, France
    Competing interests
    The authors declare that no competing interests exist.
  7. Erich Brunner

    Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  8. Giovanni Cardone

    Imaging Facility, Max Planck Institute of Biochemistry, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4712-1451
  9. Konrad Basler

    Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  10. Bianca H Habermann

    Computational Biology Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    Competing interests
    The authors declare that no competing interests exist.
  11. Frank Schnorrer

    Muscle Dynamics Group, Max Planck Institute of Biochemistry, Martinsried, Germany
    For correspondence
    frank.schnorrer@univ-amu.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9518-7263

Funding

Max-Planck-Gesellschaft

  • Maria L Spletter
  • Christiane Barz
  • Assa Yeroslaviz
  • Xu Zhang
  • Sandra B Lemke
  • Bianca H Habermann
  • Frank Schnorrer

Agence Nationale de la Recherche (ANR-10-INBS-04- 01)

  • Frank Schnorrer

Agence Nationale de la Recherche (ANR ACHN)

  • Frank Schnorrer

Centre National de la Recherche Scientifique

  • Xu Zhang
  • Adrien Bonnard
  • Bianca H Habermann
  • Frank Schnorrer

European Molecular Biology Organization (EMBO-LTR 688-2011)

  • Maria L Spletter

Alexander von Humboldt-Stiftung

  • Maria L Spletter

National Institute for Health Research (5F32AR062477)

  • Maria L Spletter

H2020 European Research Council (ERC Grant 310939)

  • Frank Schnorrer

Aix-Marseille Université (ANR-11-IDEX-0001-02)

  • Bianca H Habermann
  • Frank Schnorrer

Agence Nationale de la Recherche (ANR-11- LABX-0054)

  • Frank Schnorrer

European Molecular Biology Organization (EMBO-YIP)

  • Frank Schnorrer

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

Copyright

© 2018, Spletter 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

  • 4,590
    views
  • 551
    downloads
  • 86
    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. Maria L Spletter
  2. Christiane Barz
  3. Assa Yeroslaviz
  4. Xu Zhang
  5. Sandra B Lemke
  6. Adrien Bonnard
  7. Erich Brunner
  8. Giovanni Cardone
  9. Konrad Basler
  10. Bianca H Habermann
  11. Frank Schnorrer
(2018)
A transcriptomics resource reveals a transcriptional transition during ordered sarcomere morphogenesis in flight muscle
eLife 7:e34058.
https://doi.org/10.7554/eLife.34058

Share this article

https://doi.org/10.7554/eLife.34058

Further reading

    1. Cell Biology
    Affiong Ika Oqua, Kin Chao ... Alejandra Tomas
    Research Article

    G protein-coupled receptors (GPCRs) are integral membrane proteins which closely interact with their plasma membrane lipid microenvironment. Cholesterol is a lipid enriched at the plasma membrane with pivotal roles in the control of membrane fluidity and maintenance of membrane microarchitecture, directly impacting on GPCR stability, dynamics, and function. Cholesterol extraction from pancreatic beta cells has previously been shown to disrupt the internalisation, clustering, and cAMP responses of the glucagon-like peptide-1 receptor (GLP-1R), a class B1 GPCR with key roles in the control of blood glucose levels via the potentiation of insulin secretion in beta cells and weight reduction via the modulation of brain appetite control centres. Here, we unveil the detrimental effect of a high cholesterol diet on GLP-1R-dependent glucoregulation in vivo, and the improvement in GLP-1R function that a reduction in cholesterol synthesis using simvastatin exerts in pancreatic islets. We next identify and map sites of cholesterol high occupancy and residence time on active vs inactive GLP-1Rs using coarse-grained molecular dynamics (cgMD) simulations, followed by a screen of key residues selected from these sites and detailed analyses of the effects of mutating one of these, Val229, to alanine on GLP-1R-cholesterol interactions, plasma membrane behaviours, clustering, trafficking and signalling in INS-1 832/3 rat pancreatic beta cells and primary mouse islets, unveiling an improved insulin secretion profile for the V229A mutant receptor. This study (1) highlights the role of cholesterol in regulating GLP-1R responses in vivo; (2) provides a detailed map of GLP-1R - cholesterol binding sites in model membranes; (3) validates their functional relevance in beta cells; and (4) highlights their potential as locations for the rational design of novel allosteric modulators with the capacity to fine-tune GLP-1R responses.

    1. Cell Biology
    2. Immunology and Inflammation
    Alejandro Rosell, Agata Adelajda Krygowska ... Esther Castellano Sanchez
    Research Article

    Macrophages are crucial in the body’s inflammatory response, with tightly regulated functions for optimal immune system performance. Our study reveals that the RAS–p110α signalling pathway, known for its involvement in various biological processes and tumourigenesis, regulates two vital aspects of the inflammatory response in macrophages: the initial monocyte movement and later-stage lysosomal function. Disrupting this pathway, either in a mouse model or through drug intervention, hampers the inflammatory response, leading to delayed resolution and the development of more severe acute inflammatory reactions in live models. This discovery uncovers a previously unknown role of the p110α isoform in immune regulation within macrophages, offering insight into the complex mechanisms governing their function during inflammation and opening new avenues for modulating inflammatory responses.