eEF2 improves dense connective tissue repair and healing outcome by regulating cellular death, autophagy, apoptosis, proliferation and migration

Chen, Junyu; Wang, Jin; Wu, Xianguo; Simon, Nils; Svensson, Camilla I.; Yuan, Juan; Hart, David A.; Ahmed, Aisha Siddiqah; Ackermann, Paul W.

doi:10.1007/s00018-023-04776-x

Cited by 8 publications

(8 citation statements)

References 54 publications

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“…CircEEF2 also contributes to autophagy by inhibiting the mTOR pathway and upregulating the expression of autophagy-related gene 5 (ATG5) and ATG7 ( Yong et al, 2020 ). Regarding tissue repair, activation of EEF2 was observed to reduce apoptosis and enhance the recovery of dense connective tissue ( Chen et al, 2023 ) by promoting autophagic flux ( Pires Da Silva et al, 2020 ). Fibroblasts are the critical effector cells in RA ( Bartok and Firestein, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis

Dong,

Gao,

Chen

et al. 2023

Front. Genet.

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Background: Although rheumatoid arthritis (RA) is a common autoimmune disease, the precise pathogenesis of the disease remains unclear. Recent research has unraveled the role of autophagy in the development of RA. This research aims to explore autophagy-related diagnostic biomarkers in the peripheral blood of RA patients.Methods: The gene expression profiles of GSE17755 were retrieved from the gene expression ontology (GEO) database. Differentially expressed autophagy-related genes (DE-ARGs) were identified for the subsequent research by inserting autophagy-related genes and differentially expressed genes (DEGs). Three machine learning algorithms, including random forest, support vector machine recursive feature elimination (SVM-RFE), and least absolute shrinkage and selection operator (LASSO), were employed to identify diagnostic biomarkers. A nomogram model was constructed to assess the diagnostic value of the biomarkers. The CIBERSORT algorithm was performed to investigate the correlation of the diagnostic biomarkers with immune cells and immune factors. Finally, the diagnostic efficacy and differential expression trend of diagnostic biomarkers were validated in multiple cohorts containing different tissues and diseases.Results: In this study, 25 DE-ARGs were identified between RA and healthy individuals. In addition to “macroautophagy” and “autophagy-animal,” DE-ARGs were also associated with several types of programmed cell death and immune-related pathways according to GO and KEGG analysis. Three diagnostic biomarkers, EEF2, HSP90AB1 and TNFSF10, were identified by the random forest, SVM-RFE, and LASSO. The nomogram model demonstrated excellent diagnostic value in GSE17755 (AUC = 0.995, 95% CI: 0.988–0.999). Furthermore, immune infiltration analysis showed a remarkable association between EEF2, HSP90AB1, and TNFSF10 expression with various immune cells and immune factors. The three diagnostic biomarkers also exhibited good diagnostic efficacy and demonstrated the same trend of differential expression in multiple validation cohorts.Conclusion: This study identified autophagy-related diagnostic biomarkers based on three machine learning algorithms, providing promising targets for the diagnosis and treatment of RA.

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Section: Discussionmentioning

confidence: 99%

Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis

Dong,

Gao,

Chen

et al. 2023

Front. Genet.

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“…There is a close relationship between autophagy and tissue repair. 41 Briefly, autophagy participates in the clearance of intracellular waste and the recycling of metabolic products, which can provide necessary nutrients for damaged tissues and promote tissue repair. 42 Ma and colleagues have found that inducing autophagy leads to more labeled MSCs migrating to the site of injury.…”

Section: Discussionmentioning

confidence: 99%

Sodium hyaluronate promotes proliferation, autophagy, and migration of corneal epithelial cells by downregulating miR-18a in the course of corneal epithelial injury

Guo

Wang

2023

Eur J Histochem

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Corneal epithelium can resist the invasion of external pathogenic factors to protect the eye from external pathogens. Sodium hyaluronate (SH) has been confirmed to promote corneal epithelial wound healing. However, the mechanism by which SH protects against corneal epithelial injury (CEI) is not fully understood. CEI model mice were made by scratching the mouse corneal epithelium, and in vitro model of CEI were constructed via curettage of corneal epithelium or ultraviolet radiation. The pathologic structure and level of connective tissue growth factor (CTGF) expression were confirmed by Hematoxylin and Eosin staining and immunohistochemistry. CTGF expression was detected by an IHC assay. The levels of CTGF, TGF-β, COLA1A, FN, LC3B, Beclin1, and P62 expression were monitored by RT-qPCR, ELISA, Western blotting or immunofluorescence staining. Cell proliferation was detected by the CCK-8 assay and EdU staining. Our results showed that SH could markedly upregulate CTGF expression and downregulate miR-18a expression in the CEI model mice. Additionally, SH could attenuate corneal epithelial tissue injury, and enhance the cell proliferation and autophagy pathways in the CEI model mice. Meanwhile, overexpression of miR-18a reversed the effect of SHs on cell proliferation and autophagy in CEI model mice. Moreover, our data showed that SH could induce the proliferation, autophagy, and migration of CEI model cells by downregulating miR-18a. Down-regulation of miR-18a plays a significant role in the ability of SH to promote corneal epithelial wound healing. Our results provide a theoretical basis for targeting miR-18a to promote corneal wound healing.

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“…Rosavin thus influences the inhibition of the deacetylation process of EEF2 [44]. EEF2, in turn, under physiological conditions, is responsible for bone formation processes and is postulated to have an anti-osteoporotic effect [46,48]. In a dedicated study on the HDAC1/EEF2 axis, it was observed that rosavin reduced the levels of RANKL, M-CSF, and TRAP in the blood serum of OVX mice [44].…”

Section: Impact Of Rosavin On Bone Tissue Metabolismmentioning

confidence: 99%

The Role of Rosavin in the Pathophysiology of Bone Metabolism

Wojdasiewicz,

Turczyn,

Lach-Gruba

et al. 2024

IJMS

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Rosavin, a phenylpropanoid in Rhodiola rosea’s rhizome, and an adaptogen, is known for enhancing the body’s response to environmental stress. It significantly affects cellular metabolism in health and many diseases, particularly influencing bone tissue metabolism. In vitro, rosavin inhibits osteoclastogenesis, disrupts F-actin ring formation, and reduces the expression of osteoclastogenesis-related genes such as cathepsin K, calcitonin receptor (CTR), tumor necrosis factor receptor-associated factor 6 (TRAF6), tartrate-resistant acid phosphatase (TRAP), and matrix metallopeptidase 9 (MMP-9). It also impedes the nuclear factor of activated T-cell cytoplasmic 1 (NFATc1), c-Fos, the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), and mitogen-activated protein kinase (MAPK) signaling pathways and blocks phosphorylation processes crucial for bone resorption. Moreover, rosavin promotes osteogenesis and osteoblast differentiation and increases mouse runt-related transcription factor 2 (Runx2) and osteocalcin (OCN) expression. In vivo studies show its effectiveness in enhancing bone mineral density (BMD) in postmenopausal osteoporosis (PMOP) mice, restraining osteoclast maturation, and increasing the active osteoblast percentage in bone tissue. It modulates mRNA expressions by increasing eukaryotic translation elongation factor 2 (EEF2) and decreasing histone deacetylase 1 (HDAC1), thereby activating osteoprotective epigenetic mechanisms, and alters many serum markers, including decreasing cross-linked C-telopeptide of type I collagen (CTX-1), tartrate-resistant acid phosphatase 5b (TRACP5b), receptor activator for nuclear factor κ B ligand (RANKL), macrophage-colony-stimulating factor (M-CSF), and TRAP, while increasing alkaline phosphatase (ALP) and OCN. Additionally, when combined with zinc and probiotics, it reduces pro-osteoporotic matrix metallopeptidase 3 (MMP-3), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α), and enhances anti-osteoporotic interleukin 10 (IL-10) and tissue inhibitor of metalloproteinase 3 (TIMP3) expressions. This paper aims to systematically review rosavin’s impact on bone tissue metabolism, exploring its potential in osteoporosis prevention and treatment, and suggesting future research directions.

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eEF2 improves dense connective tissue repair and healing outcome by regulating cellular death, autophagy, apoptosis, proliferation and migration

Cited by 8 publications

References 54 publications

Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis

Machine learning and bioinformatics analysis to identify autophagy-related biomarkers in peripheral blood for rheumatoid arthritis

Sodium hyaluronate promotes proliferation, autophagy, and migration of corneal epithelial cells by downregulating miR-18a in the course of corneal epithelial injury

The Role of Rosavin in the Pathophysiology of Bone Metabolism

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