A data-driven methodology reveals novel myofiber clusters in older human muscles

Yotam Raz, Erik B. van den Akker*, Tijmen Roest, Muhammad Riaz, Ondine van de Rest, Eka D. Suchiman, Nico Lakenberg, Stefanie A. Stassen, Maaike van Putten, Edith J.M. Feskens, Marcel J.T. Reinders, Jelle Goeman, Marian Beekman, Vered Raz, Pieternella Eline Slagboom

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Skeletal muscles control posture, mobility and strength, and influence whole-body metabolism. Muscles are built of different types of myofibers, each having specific metabolic, molecular, and contractile properties. Fiber classification is, therefore, regarded the key for understanding muscle biology, (patho-) physiology. The expression of three myosin heavy chain (MyHC) isoforms, MyHC-1, MyHC-2A, and MyHC-2X, marks myofibers in humans. Typically, myofiber classification is performed by an eye-based histological analysis. This classical approach is insufficient to capture complex fiber classes, expressing more than one MyHC-isoform. We, therefore, developed a methodological procedure for high-throughput characterization of myofibers on the basis of multiple isoforms. The mean fluorescence intensity of the three most abundant MyHC isoforms was measured per myofiber in muscle biopsies of 56 healthy elderly adults, and myofiber classes were identified using computational biology tools. Unsupervised clustering revealed the existence of six distinct myofiber clusters. A comparison with the visual assessment of myofibers using the same images showed that some of these myofiber clusters could not be detected or were frequently misclassified. The presence of these six clusters was reinforced by RNA expressions levels of sarcomeric genes. In addition, one of the clusters, expressing all three MyHC isoforms, correlated with histological measures of muscle health. To conclude, this methodological procedure enables deep characterization of the complex muscle heterogeneity. This study opens opportunities to further investigate myofiber composition in comparative studies.

Original languageEnglish
Pages (from-to)5525-5537
Number of pages13
JournalFASEB Journal
Volume34
Issue number4
Early online date5 Mar 2020
DOIs
Publication statusPublished - Apr 2020

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Keywords

  • bioinformatics
  • clustering
  • fibertyping
  • human
  • muscle
  • muscle health
  • myofiber
  • myosin heavy chain
  • RNA-sequencing
  • sarcomere

Cite this

Raz, Y., van den Akker, E. B., Roest, T., Riaz, M., van de Rest, O., Suchiman, E. D., ... Slagboom, P. E. (2020). A data-driven methodology reveals novel myofiber clusters in older human muscles. FASEB Journal, 34(4), 5525-5537. https://doi.org/10.1096/fj.201902350R