Data for Multiparametric Identification of Putative Senescent Cells in Skeletal Muscle via Mass Cytometry

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https://doi.org/10.13020/06hn-xq85
https://hdl.handle.net/11299/262956

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2019-08
2023-06

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Title

Data for Multiparametric Identification of Putative Senescent Cells in Skeletal Muscle via Mass Cytometry

Published Date

2024-05-02

Authors

Baig, Nameera

Li, Yijia

Roncancio, Daniel

Elbein, Kris

Lowe, Dawn

Kyba, Michael

Arriaga, Edgar A

Group

University of Minnesota, Arriaga Lab

Author Contact

Arriaga, Edgar A
arriaga@umn.edu

Type

Dataset
Experimental Data

Abstract

This study includes three sets of compressed files: the original data (35 FCS documents collected from the CyTOF2 instrument per mouse), the gating results (FCS files gated based on the diagram in Figure S1 of the article 'Multiparametric Identification of Putative Senescent Cells in Skeletal Muscle via Mass Cytometry', with 35 per mouse for each cell type) and the batch corrected gating results (CSV files for each cell type). Also included is an ipynb file for a Jupyter notebook used for data analysis. This notebook reproduces the analysis pipeline and generates some plots used in the manuscript. The batch corrected gating results serve as the input for this analysis.

Description

1. Senescence-related proteins: The study involves the characterization of senescence in skeletal muscle cells. Various senescence-related proteins such as p21, GAPDH and KI-67 are covered. 2. Cell Type: The cell type within skeletal muscle tissue is mentioned as a variable. Different types of cells, such as fibro/adipogenic progenitors (FAPs), satellite cells, and M1 and M2 macrophages, and erythro-myeloid progenitors (EMPs) are examined for the presence of putative senescent cells (SCs). 3. Age and Sex: Age and sex are specified as variables. The study investigates how age (young vs. old mice) and sex (male and female) affect the proportion of putative SCs and expression levels of senescence-related proteins in putative SCs. 4. Protein Expression Levels: The expression levels of senescence-related proteins, such as p21, GAPDH, and IL-6, are experimental variables. The study explores differences in the expression levels of these proteins in putative SCs from different age groups and cell types. 5. Autophagy-Related Proteins: Autophagy-related proteins like ATG4A, LRRK2, and GLB1 are also considered as experimental variables, as their presence and levels are examined in relation to senescence in skeletal muscle cells. 5. Clustering and Outlier Detection: The methodology involving clustering and outlier detection is a variable in the study. It describes the analytical approach used to identify putative SCs within the complex tissue. 6. Mass Cytometry (CyTOF): The use of mass cytometry as a technology for analyzing cells is another experimental variable. It allows for the monitoring of up to forty different cell markers at the single-cell level.

Referenced by

Li, Y., Baig, N., Roncancio, D., Elbein, K., Lowe, D., Kyba, M., & Arriaga, E. A. (2024). Multiparametric identification of putative senescent cells in skeletal muscle via mass cytometry. Cytometry. Part A, 105(8), 580–594. https://doi.org/10.1002/cyto.a.24853

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CC0 1.0 Universal
http://creativecommons.org/publicdomain/zero/1.0/

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Data Repository for U of M (DRUM)

Funding information

This work was supported by the National Institutes of Health/National Institute on Aging [R01-AG020866, R01-AG063543, R01 AG062899, R37-AG013925, T32-AG029796], and the University of Minnesota [GIA University of Minnesota].

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Suggested citation

Baig, Nameera; Li, Yijia; Roncancio, Daniel; Elbein, Kris; Lowe, Dawn; Kyba, Michael; Arriaga, Edgar A. (2024). Data for Multiparametric Identification of Putative Senescent Cells in Skeletal Muscle via Mass Cytometry. Retrieved from the Data Repository for the University of Minnesota (DRUM), https://doi.org/10.13020/06hn-xq85.

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