Dataset Information

Immunoproteasome remodeling in senescing human macrophages reveals the loss of PA28αβ capping as a hallmark of immunosenescence

ABSTRACT: We established an in vitro model of blood monocyte-derived human macrophages that acquire a senescent-like phenotype upon long-term culture. Using this model, we investigated how the proteome is remodeled during senescence by analyzing cell extracts at 7 days (mature macrophages), 14 days (onset of senescence), and 28 days (fully senescent.)

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture, Macrophage

SUBMITTER: Michele Menotta

LAB HEAD: Michele Menotta

PROVIDER: PXD066998 | Pride | 2025-10-06

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	macroF_senescenza.msf	Msf
	pz1961_14gg.raw	Raw
	pz1961_14gg_20230815113752.raw	Raw
	pz1961_14gg_20230816185732.raw	Raw
	pz1961_14gg_20230818104403.raw	Raw

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Immunoproteasome remodeling in senescing human macrophages reveals the loss of PA28αβ capping as a hallmark of immunosenescence.

Monittola Francesca F Masini Sofia S Montanari Mariele M Nasoni Maria Gemma MG Bianchi Marzia M De Matteis Rita R Ricci Anastasia A Ligi Daniela D Luchetti Francesca F Canonico Barbara B Magnani Mauro M Menotta Michele M Fraternale Alessandra A Crinelli Rita R

Communications biology 20250926 1

Aging negatively impacts proteasome activity and/or content, and this impairment contributes to disrupted protein homeostasis and cellular dysfunction. However, little is known about proteasome complex dynamics during aging, particularly in the context of immunosenescence. Indeed, only limited data are available on the immunoproteasome, a specialized variant expressed in immune cells. We establish an in vitro model of monocyte-derived human macrophages that develop a senescence-like phenotype up ...[more]

PMID: 41006761

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Project description:BACKGROUND: Periodontal ligament mesenchymal stem cells (PDLSCs) are a promising cell resource for cell-based regenerative medicine in dentistry. PDLSCs inevitably acquire a senescent phenotype after prolonged in vitro expansion, and the key regulators of cells during replicative senescence remain unclear.METHODS: We cultured periodontal ligament stem cells to passages 4, 10 and 20 (P4, P10, P20). The senescent phenotypes, proliferation and migration ability of PDLSCs (P4, P10, P20) were detected, and non-targeted metabonomic sequencing was performed. We treated PDLSCs with AICAR and detected the expression of FOXO1, FOXO3a, FOXO6 and AMPK phosphorylation (p-AMPK) levels of replicating senescent PDLSCs to explore the correlation between the metabolic changes and the AMPK pathway.RESULTS: Immunofluorescence staining of γ-H2AX, β-galactosidase staining, cell scratch test and qPCR were performed to confirm the occurrence of replicative senescence in PDLSCs during passaging. Three groups of cells at passage 4 (P4), passage 10 (P10) and passage 20 (P20) were collected for non-targeted metabolomics analysis. Metabonomic sequencing showed that the metabolism of replicative senescence in PDLSCs varied significantly. In particular, the content of fatty acid metabolites decreased with senescence, including capric acid, stearic acid, myristic acid and dodecanoic acid. KEGG pathway analysis showed that the AMPK signaling pathway was closely related to AMP levels. The AMP:ATP ratio increased in senescent PDLSCs; however, the levels of p-AMPK and the profile of FOXO1 and FOXO3a, which are downstream of the AMPK signaling pathway, decreased with senescence. We treated PDLSCs with AICAR, an activator of the AMPK pathway, and the phosphorylated AMPK level at P20 PDLSCs was partially restored. CONCLUSION: In summary, our study suggests that the metabolic process of PDLSCs is active in the early stage of senescence, prefers to consume fatty acids, and is attenuated in the later stages of senescence. AMP accumulates in replicative senescent PDLSCs; however, the sensitivity of AMPK phosphorylation sites is impaired, causing senescent PDLSCs to fail to respond to changes in energy metabolism. Our findings provide a new basis for the clinical application of periodontal ligament stem cells.

Project description:This is the model described in: Feedback between p21 and reactive oxygen production is necessary for cell senescence. Passos JF, Nelson G, Wang C, Richter T, Simillion C, Proctor CJ, Miwa S, Olijslagers S, Hallinan J, Wipat A, Saretzki G, Rudolph KL, Kirkwood TB, von Zglinicki T. ;Mol Sys Biol2010;6:347. Epub 2010 Feb 16. PMID:20160708 doi:10.1038/msb.2010.5; Abstract: Cellular senescence--the permanent arrest of cycling in normally proliferating cells such as fibroblasts--contributes both to age-related loss of mammalian tissue homeostasis and acts as a tumour suppressor mechanism. The pathways leading to establishment of senescence are proving to be more complex than was previously envisaged. Combining in-silico interactome analysis and functional target gene inhibition, stochastic modelling and live cell microscopy, we show here that there exists a dynamic feedback loop that is triggered by a DNA damage response (DDR) and, which after a delay of several days, locks the cell into an actively maintained state of 'deep' cellular senescence. The essential feature of the loop is that long-term activation of the checkpoint gene CDKN1A (p21) induces mitochondrial dysfunction and production of reactive oxygen species (ROS) through serial signalling through GADD45-MAPK14(p38MAPK)-GRB2-TGFBR2-TGFbeta. These ROS in turn replenish short-lived DNA damage foci and maintain an ongoing DDR. We show that this loop is both necessary and sufficient for the stability of growth arrest during the establishment of the senescent phenotype. This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team.For more information see the terms of use.To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.