1
|
Zhang X, Ng YE, Chini LCS, Heeren AA, White TA, Li H, Huang H, Doolittle ML, Khosla S, LeBrasseur NK. Senescent skeletal muscle fibroadipogenic progenitors recruit and promote M2 polarization of macrophages. Aging Cell 2024; 23:e14069. [PMID: 38115574 DOI: 10.1111/acel.14069] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 12/21/2023] Open
Abstract
Senescent cells compromise tissue structure and function in older organisms. We recently identified senescent fibroadipogenic progenitors (FAPs) with activated chemokine signaling pathways in the skeletal muscle of old mice, and hypothesized these cells may contribute to the age-associated accumulation of immune cells in skeletal muscle. In this study, through cell-cell communication analysis of skeletal muscle single-cell RNA-sequencing data, we identified unique interactions between senescent FAPs and macrophages, including those mediated by Ccl2 and Spp1. Using mouse primary FAPs in vitro, we verified increased expression of Ccl2 and Spp1 and secretion of their respective proteins in the context of both irradiation- and etoposide-induced senescence. Compared to non-senescent FAPs, the medium of senescent FAPs markedly increased the recruitment of macrophages in an in vitro migration assay, an effect that was mitigated by preincubation with antibodies to either CCL2 or osteopontin (encoded by Spp1). Further studies demonstrated that the secretome of senescent FAPs promotes polarization of macrophages toward an M2 subtype. These data suggest the unique secretome of senescent FAPs may compromise skeletal muscle homeostasis by recruiting and directing the behavior of macrophages.
Collapse
Affiliation(s)
- Xu Zhang
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota, USA
- Paul F. Glenn Center for Biology of Aging Research at Mayo Clinic, Rochester, Minnesota, USA
| | - Yan Er Ng
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
| | - Lucas C S Chini
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
| | - Amanda A Heeren
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
| | - Thomas A White
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
| | - Hao Li
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota, USA
| | - Haojie Huang
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota, USA
| | - Madison L Doolittle
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
- Division of Endocrinology, Mayo Clinic, Rochester, Minnesota, USA
| | - Sundeep Khosla
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
- Division of Endocrinology, Mayo Clinic, Rochester, Minnesota, USA
| | - Nathan K LeBrasseur
- Robert and Arlene Kogod Center on Aging, Mayo Clinic, Rochester, Minnesota, USA
- Paul F. Glenn Center for Biology of Aging Research at Mayo Clinic, Rochester, Minnesota, USA
- Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|
2
|
Yang L, Ng YE, Sun H, Li Y, Chini LCS, LeBrasseur NK, Chen J, Zhang X. Single-cell Mayo Map (scMayoMap): an easy-to-use tool for cell type annotation in single-cell RNA-sequencing data analysis. BMC Biol 2023; 21:223. [PMID: 37858214 PMCID: PMC10588107 DOI: 10.1186/s12915-023-01728-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 10/06/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Single-cell RNA-sequencing (scRNA-seq) has become a widely used tool for both basic and translational biomedical research. In scRNA-seq data analysis, cell type annotation is an essential but challenging step. In the past few years, several annotation tools have been developed. These methods require either labeled training/reference datasets, which are not always available, or a list of predefined cell subset markers, which are subject to biases. Thus, a user-friendly and precise annotation tool is still critically needed. RESULTS We curated a comprehensive cell marker database named scMayoMapDatabase and developed a companion R package scMayoMap, an easy-to-use single-cell annotation tool, to provide fast and accurate cell type annotation. The effectiveness of scMayoMap was demonstrated in 48 independent scRNA-seq datasets across different platforms and tissues. Additionally, the scMayoMapDatabase can be integrated with other tools and further improve their performance. CONCLUSIONS scMayoMap and scMayoMapDatabase will help investigators to define the cell types in their scRNA-seq data in a streamlined and user-friendly way.
Collapse
Affiliation(s)
- Lu Yang
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Yan Er Ng
- Robert and Arlene Kogod Center On Aging, Mayo Clinic, Rochester, MN, 55905, USA
| | - Haipeng Sun
- Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Ying Li
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, 32224, USA
| | - Lucas C S Chini
- Robert and Arlene Kogod Center On Aging, Mayo Clinic, Rochester, MN, 55905, USA
| | - Nathan K LeBrasseur
- Robert and Arlene Kogod Center On Aging, Mayo Clinic, Rochester, MN, 55905, USA.
- Department of Physical Medicine and Rehabilitation, Mayo Clinic, Rochester, MN, 55905, USA.
| | - Jun Chen
- Division of Computational Biology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, 55905, USA.
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, 55905, USA.
| | - Xu Zhang
- Robert and Arlene Kogod Center On Aging, Mayo Clinic, Rochester, MN, 55905, USA.
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN, 55905, USA.
| |
Collapse
|
3
|
Yang L, Ng YE, Sun H, Li Y, Chini LCS, LeBrasseur NK, Chen J, Zhang X. Single-cell Mayo Map ( scMayoMap ): an easy-to-use tool for cell type annotation in single-cell RNA-sequencing data analysis. bioRxiv 2023:2023.05.03.538463. [PMID: 37205463 PMCID: PMC10187171 DOI: 10.1101/2023.05.03.538463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Single-cell RNA-sequencing (scRNA-seq) has become a widely used tool for both basic and translational biomedical research. In scRNA-seq data analysis, cell type annotation is an essential but challenging step. In the past few years, several annotation tools have been developed. These methods require either labeled training/reference datasets, which are not always available, or a list of predefined cell subset markers, which are subject to biases. Thus, a user-friendly and precise annotation tool is still critically needed. We curated a comprehensive cell marker database named scMayoMapDatabase and developed a companion R package scMayoMap , an easy-to-use single cell annotation tool, to provide fast and accurate cell type annotation. The effectiveness of scMayoMap was demonstrated in 48 independent scRNA-seq datasets across different platforms and tissues. scMayoMap performs better than the currently available annotation tools on all the datasets tested. Additionally, the scMayoMapDatabase can be integrated with other tools and further improve their performance. scMayoMap and scMayoMapDatabase will help investigators to define the cell types in their scRNA-seq data in a streamlined and user-friendly way.
Collapse
|