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. 2022 Aug;44(4):2139-2155.
doi: 10.1007/s11357-022-00578-4. Epub 2022 May 11.

Single-cell transcriptomics identifies premature aging features of TERC-deficient mouse brain and bone marrow

Affiliations

Single-cell transcriptomics identifies premature aging features of TERC-deficient mouse brain and bone marrow

Chunying Yang et al. Geroscience. 2022 Aug.

Abstract

Aging is a progressive loss of physiological function and increased susceptibility to major pathologies. Degenerative diseases in both brain and bone including Alzheimer disease (AD) and osteoporosis are common in aging groups. TERC is RNA component of telomerase, and its deficiency accelerates aging-related phenotypes including impaired life span, organ failure, bone loss, and brain dysfunction. In this study, we investigated the traits of bone marrow-brain cross-tissue communications in young mice, natural aging mice, and premature aging (TERC deficient, TERC-KO) mice by single-cell transcriptome sequencing. Differentially expressed gene analysis of brain as well as bone marrow between premature aging mouse and young mouse demonstrated aging-related inflammatory response and suppression of neuron development. Further analysis of senescence-associated secretory phenotype (SASP) landscape indicated that TERC-KO perturbation was enriched in oligodendrocyte progenitor cells (OPCs) and hematopoietic stem and progenitor cells (HSPC). Series of inflammatory associated myeloid cells was activated in premature aging mice brain and bone marrow. Cross-tissue comparison of TERC-KO mice brain and bone marrow illustrated obvious ligand-receptor communications between brain glia cells, macrophages, and bone marrow myeloid cells in premature aging-induced inflammation. Enrichment of co-regulation modules between brain and bone marrow identified premature aging response genes such as Dusp1 and Ifitm3. Our study provides a rich resource for understanding premature aging-associated perturbation in brain and bone marrow and supporting myeloid cells and endothelial cells as promising therapy targeting for age-related brain-bone diseases.

Keywords: Aging; Brain-bone axis; Single-cell RNA sequencing; TERC; Telomerase.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Single-cell transcriptome landscape of control and TERC-KO mouse brain and bone marrow. (a–c) UMAP plot of batch, number of unique molecular identifiers (UMIs), and sub-clusters in 6-month-old WT, TERC-KO, and 20-month-old WT brain, and (d) featureplot of selected marker genes. (e–g) UMAP plot of batch, UMIs, and sub-clusters in 6-month-old WT, TERC-KO, and 20-month-old WT bone marrow, and (h) featureplot of selected marker genes
Fig. 2
Fig. 2
Single-cell differentially expressed gene analysis of control and TERC-KO mouse brain and bone marrow. The fraction of cell types in different brain (a) and bone marrow (b) samples. Volcano plot shows differentially expressed genes in different cell types from brain (c–e) and bone marrow (f–g) samples (Upregulated: upregulated genes in TERC-KO samples, Downregulated: downregulated genes in TERC-KO samples, NS: no significant, Glial cells: astrocytes, microglial and oligodendrocytes, OPCs: oligodendrocyte precursor cells)
Fig. 3
Fig. 3
Senescence-associated secretory phenotype (SASP) evaluation in TERC-KO mouse brain and bone marrow. Ridge plot showing the shift of SASP gene set score with age in all cells from brain (a–b) and bone marrow (d–e) samples. Violin plots showing the cell types in which the SASP gene set score is significantly increased with age in brain (c) and bone marrow (f–h) samples
Fig. 4
Fig. 4
Cross-tissue differentially expressed genes analysis in TERC-KO mouse brain and bone marrow during aging. (a) Top 10 upregulated and top 10 downregulated differentially expressed genes in brain and bone marrow (Avg logFC: average fold-change level). (b) Vennplot of upregulated genes and downregulated genes between TERC-KO mouse brain samples and TERC-KO mouse bone marrow samples. (c) Network plot showing the differentially expressed genes between TERC-KO mouse brain and TERC-KO mouse bone marrow. (d) Gene ontology enrichment of upregulated genes and downregulated genes in TERC-KO mouse brain compared with 6-month WT mouse. (e) Gene ontology enrichment of upregulated genes and downregulated genes in TERC-KO mouse bone marrow compared with 6-month young mouse
Fig. 5
Fig. 5
Co-regulated expression pattern of Dusp1 and Ifitm3 in TERC-KO mouse brain and bone marrow during aging. Violin plot of brain-bone marrow co-regulated genes (Dusp1 and Ifitm3) in brain and bone marrow (a–b) cell types. Confocal images (c and e) and fluorescence intensities quantitation (d and f) show increased expressions of DUSP1 and IFIMT3 CD31-positive cells in brain, and Cd11b-positive cells in bone marrow (Data are representative of three independent experiments)
Fig. 6
Fig. 6
Ligand-receptor analysis between TERC-KO mouse brain glia cells and bone marrow myeloid cells. (a) Dot plot of ligand-receptor pairs between macrophages and glia cells in TERC-KO mouse brain. (b) Dot plot of ligand-receptor pairs between neutrophils and glia cells in TERC-KO mouse brain. (c) Dot plot of ligand-receptor pairs between other myeloid cells and glia cells in TERC-KO mouse brain
Fig. 7
Fig. 7
Systematic diagram illustrating the cell-cell interaction model between brain and bone marrow during TERC-KO premature aging. Predicted regulatory network between brain and bone marrow during TERC-KO premature aging

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