Deep muscle-proteomic analysis of freeze-dried human muscle biopsies reveals fiber type-specific adaptations to exercise training

A. S. Deshmukh (), D. E. Steenberg, M. Hostrup, J. B. Birk, J. K. Larsen, A. Santos, R. Kjøbsted, J. R. Hingst, C. C. Schéele, M. Murgia, B. Kiens, E. A. Richter, M. Mann and J. F. P. Wojtaszewski ()
Additional contact information
A. S. Deshmukh: University of Copenhagen
D. E. Steenberg: University of Copenhagen
M. Hostrup: University of Copenhagen
J. B. Birk: University of Copenhagen
J. K. Larsen: University of Copenhagen
A. Santos: University of Copenhagen
R. Kjøbsted: University of Copenhagen
J. R. Hingst: University of Copenhagen
C. C. Schéele: University of Copenhagen
M. Murgia: Max-Planck-Institute of Biochemistry
B. Kiens: University of Copenhagen
E. A. Richter: University of Copenhagen
M. Mann: University of Copenhagen
J. F. P. Wojtaszewski: University of Copenhagen

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: Abstract Skeletal muscle conveys several of the health-promoting effects of exercise; yet the underlying mechanisms are not fully elucidated. Studying skeletal muscle is challenging due to its different fiber types and the presence of non-muscle cells. This can be circumvented by isolation of single muscle fibers. Here, we develop a workflow enabling proteomics analysis of pools of isolated muscle fibers from freeze-dried human muscle biopsies. We identify more than 4000 proteins in slow- and fast-twitch muscle fibers. Exercise training alters expression of 237 and 172 proteins in slow- and fast-twitch muscle fibers, respectively. Interestingly, expression levels of secreted proteins and proteins involved in transcription, mitochondrial metabolism, Ca2+ signaling, and fat and glucose metabolism adapts to training in a fiber type-specific manner. Our data provide a resource to elucidate molecular mechanisms underlying muscle function and health, and our workflow allows fiber type-specific proteomic analyses of snap-frozen non-embedded human muscle biopsies.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-020-20556-8 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20556-8

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-20556-8

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().