Macrophage migration inhibitory factor activates the inflammatory response in joint capsule fibroblasts following post-traumatic joint contracture

Zhang, Yuxin; Lu, Shenji; Fan, Shuai; Jiang, Xin; Wang, Kexin; Cai, Bin

doi:10.18632/aging.202505

“…This is perhaps not surprising given the importance of MIF as a pro-inflammatory cytokine, inhibitor of p53, and positive regulator of NF-κB 72 . MIF appears to be pivotal for cellular senescence, aging, and joint inflammation; however, its presence has been associated with a beneficial effect on the healthy lung and in MSCs [73][74][75][76][77][78] . Of note, recent evidence indicates an important role for MIF signaling in immune Fig.…”

Section: Discussionmentioning

confidence: 99%

A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues

Saul

¹

,

Kosinsky

²

,

Atkinson

³

et al. 2022

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Although cellular senescence drives multiple age-related co-morbidities through the senescence-associated secretory phenotype, in vivo senescent cell identification remains challenging. Here, we generate a gene set (SenMayo) and validate its enrichment in bone biopsies from two aged human cohorts. We further demonstrate reductions in SenMayo in bone following genetic clearance of senescent cells in mice and in adipose tissue from humans following pharmacological senescent cell clearance. We next use SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from human and murine bone marrow/bone scRNA-seq data. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Using this senescence panel, we are able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways. SenMayo also represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

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“…71 MIF appears to be pivotal for cellular senescence, aging, and joint inflammation; however, its presence been associated with a beneficial effect on the healthy lung and in MSCs. [72][73][74][75][76][77] Of note, recent evidence indicates an important role for MIF signaling in immune evasion by tumors 78 and parasites, 79 raising the possibility that increased MIF expression by multiple senescent cell types may play a role in the ability of senescent cells to resist immune clearance, particularly with aging, 53 and this possibility warrants further study. Importantly, we also used Mif expression to validate our in silico predictions based on the scRNA-seq analyses, and confirmed both an increase in Mif expression with aging in murine bone as well as a reduction in Mif mRNA levels following genetic clearance of senescent cells.…”

Section: Discussionmentioning

confidence: 99%

A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

Saul

¹

,

Kosinsky

²

,

Atkinson

³

et al. 2021

Preprint

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Although cellular senescence is increasingly recognized as driving multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification, particularly in bulk or single cell RNA-sequencing (scRNA-seq) data remains challenging. Here, we generated a novel gene set (SenMayo) and first validated its enrichment in bone biopsies from two aged human cohorts. SenMayo also identified senescent cells in aged murine brain tissue, demonstrating applicability across tissues and species. For direct validation, we demonstrated significant reductions in SenMayo in bone following genetic clearance of senescent cells in mice, with similar findings in adipose tissue from humans in a pilot study of pharmacological senescent cell clearance. In direct comparisons, SenMayo outperformed all six existing senescence/SASP gene sets in identifying senescent cells across tissues and in demonstrating responses to senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from publicly available human and murine bone marrow/bone scRNA-seq data and identified monocytic and osteolineage cells, respectively, as showing the highest levels of senescence/SASP genes. Using pseudotime and cellular communication patterns, we found senescent hematopoietic and mesenchymal cells communicated with other cells through common pathways, including the Macrophage Migration Inhibitory Factor (MIF) pathway, which has been implicated not only in inflammation but also in immune evasion, an important property of senescent cells. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Moreover, using this senescence panel, we were able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways associated with these cells, which may be particularly useful for evolving efforts to map senescent cells (e.g., SenNet). In addition, SenMayo represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

show abstract

“…71 MIF appears to be pivotal for cellular senescence, aging, and joint inflammation; however, its presence has been associated with a beneficial effect on the healthy lung and in MSCs. [72][73][74][75][76][77] Of note, recent evidence indicates an important role for MIF signaling in immune evasion by tumors 78 and parasites, 79 raising the possibility that increased MIF expression by multiple senescent cell types may play a role in the ability of senescent cells to resist immune clearance, particularly with aging, 53 and this possibility warrants further study. Importantly, we also used Mif expression to validate our in silico predictions based on the scRNA-seq analyses, and confirmed both an increase in Mif expression with aging in murine bone as well as a reduction in Mif mRNA levels following genetic clearance of senescent cells.…”

Section: Discussionmentioning

confidence: 99%

A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

Khosla

¹

,

Saul

²

,

Kosinsky

³

et al. 2021

Preprint

0

View full text Add to dashboard Cite

Although cellular senescence is increasingly recognized as driving multiple age-related co-morbidities through the senescence-associated secretory phenotype (SASP), in vivo senescent cell identification, particularly in bulk or single cell RNA-sequencing (scRNA-seq) data remains challenging. Here, we generated a novel gene set (SenMayo) and first validated its enrichment in bone biopsies from two aged human cohorts. SenMayo also identified senescent cells in aged murine brain tissue, demonstrating applicability across tissues and species. For direct validation, we demonstrated significant reductions in SenMayo in bone following genetic clearance of senescent cells in mice, with similar findings in adipose tissue from humans in a pilot study of pharmacological senescent cell clearance. In direct comparisons, SenMayo outperformed all six existing senescence/SASP gene sets in identifying senescent cells across tissues and in demonstrating responses to senescent cell clearance. We next used SenMayo to identify senescent hematopoietic or mesenchymal cells at the single cell level from publicly available human and murine bone marrow/bone scRNA-seq data and identified monocytic and osteolineage cells, respectively, as showing the highest levels of senescence/SASP genes. Using pseudotime and cellular communication patterns, we found senescent hematopoietic and mesenchymal cells communicated with other cells through common pathways, including the Macrophage Migration Inhibitory Factor (MIF) pathway, which has been implicated not only in inflammation but also in immune evasion, an important property of senescent cells. Thus, SenMayo identifies senescent cells across tissues and species with high fidelity. Moreover, using this senescence panel, we were able to characterize senescent cells at the single cell level and identify key intercellular signaling pathways associated with these cells, which may be particularly useful for evolving efforts to map senescent cells (e.g., SenNet). In addition, SenMayo represents a potentially clinically applicable panel for monitoring senescent cell burden with aging and other conditions as well as in studies of senolytic drugs.

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Macrophage migration inhibitory factor activates the inflammatory response in joint capsule fibroblasts following post-traumatic joint contracture

Cited by 17 publications

References 59 publications

A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues

A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues

A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

A New Gene Set Identifies Senescent Cells and Predicts Senescence-Associated Pathways Across Tissues

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