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A Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics.
Momenzadeh, Amanda; Jiang, Yuming; Kreimer, Simion; Teigen, Laura E; Zepeda, Carlos S; Haghani, Ali; Mastali, Mitra; Song, Yang; Hutton, Alexandre; Parker, Sarah J; Van Eyk, Jennifer E; Sundberg, Christopher W; Meyer, Jesse G.
Afiliação
  • Momenzadeh A; Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, California 90069, United States.
  • Jiang Y; Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Kreimer S; Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Teigen LE; Department of Computational Biomedicine, Cedars Sinai Medical Center, Los Angeles, California 90069, United States.
  • Zepeda CS; Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Haghani A; Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Mastali M; Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Song Y; Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Hutton A; Department of Physical Therapy, Marquette University, Milwaukee, Wisconsin 53233, United States.
  • Parker SJ; Department of Physical Therapy, Marquette University, Milwaukee, Wisconsin 53233, United States.
  • Van Eyk JE; Advanced Clinical Biosystems Research Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Sundberg CW; Smidt Heart Institute, Cedars Sinai Medical Center, Los Angeles, California 90048, United States.
  • Meyer JG; Department of Physical Therapy, Marquette University, Milwaukee, Wisconsin 53233, United States.
J Am Soc Mass Spectrom ; 34(9): 1858-1867, 2023 Sep 06.
Article em En | MEDLINE | ID: mdl-37463334
ABSTRACT
Skeletal muscle is a major regulatory tissue of whole-body metabolism and is composed of a diverse mixture of cell (fiber) types. Aging and several diseases differentially affect the various fiber types, and therefore, investigating the changes in the proteome in a fiber-type specific manner is essential. Recent breakthroughs in isolated single muscle fiber proteomics have started to reveal heterogeneity among fibers. However, existing procedures are slow and laborious, requiring 2 h of mass spectrometry time per single muscle fiber; 50 fibers would take approximately 4 days to analyze. Thus, to capture the high variability in fibers both within and between individuals requires advancements in high throughput single muscle fiber proteomics. Here we use a single cell proteomics method to enable quantification of single muscle fiber proteomes in 15 min total instrument time. As proof of concept, we present data from 53 isolated skeletal muscle fibers obtained from two healthy individuals analyzed in 13.25 h. Adapting single cell data analysis techniques to integrate the data, we can reliably separate type 1 and 2A fibers. Ninety-four proteins were statistically different between clusters indicating alteration of proteins involved in fatty acid oxidation, oxidative phosphorylation, and muscle structure and contractile function. Our results indicate that this method is significantly faster than prior single fiber methods in both data collection and sample preparation while maintaining sufficient proteome depth. We anticipate this assay will enable future studies of single muscle fibers across hundreds of individuals, which has not been possible previously due to limitations in throughput.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Limite: Humans Idioma: En Revista: J Am Soc Mass Spectrom Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Limite: Humans Idioma: En Revista: J Am Soc Mass Spectrom Ano de publicação: 2023 Tipo de documento: Article