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Li X, An T, Yang Y, Xu Z, Chen S, Yi Z, Deng C, Zhou F, Man Y, Hu C. TLR9 activation in large wound induces tissue repair and hair follicle regeneration via γδT cells. Cell Death Dis 2024; 15:598. [PMID: 39153998 PMCID: PMC11330466 DOI: 10.1038/s41419-024-06994-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 08/07/2024] [Accepted: 08/12/2024] [Indexed: 08/19/2024]
Abstract
The mechanisms underlying tissue repair in response to damage have been one of main subjects of investigation. Here we leverage the wound-induced hair neogenesis (WIHN) models in adult mice to explore the correlation between degree of damage and the healing process and outcome. The multimodal analysis, in combination with single-cell RNA sequencing help to explore the difference in wounds of gentle and heavy damage degrees, identifying the potential role of toll-like receptor 9 (TLR9) in sensing the injury and regulating the immune reaction by promoting the migration of γδT cells. The TLR9 deficient mice or wounds injected with TLR9 antagonist have greatly impaired healing and lower WIHN levels. Inhibiting the migration of γδT cells or knockout of γδT cells also suppress the wound healing and regeneration, which can't be rescued by TLR9agonist. Finally, the amphiregulin (AREG) is shown as one of most important effectors secreted by γδT cells and keratinocytes both in silicon or in the laboratory, whose expression influences WIHN levels and the expression of stem cell markers. In total, our findings reveal a previously unrecognized role for TLR9 in sensing skin injury and influencing the tissue repair and regeneration by modulation of the migration of γδT cells, and identify the TLR9-γδT cells-areg axis as new potential targets for enhancing tissue regeneration.
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Affiliation(s)
- Xinhui Li
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Tiantian An
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yang Yang
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Zhaoyu Xu
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Shuaidong Chen
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Zumu Yi
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Chen Deng
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Feng Zhou
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yi Man
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
| | - Chen Hu
- State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
- Department of Oral Implantology, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, Sichuan, China.
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Tu KY, Jung CJ, Shih YH, Chang ALS. Therapeutic strategies focusing on immune dysregulation and neuroinflammation in rosacea. Front Immunol 2024; 15:1403798. [PMID: 39136023 PMCID: PMC11317294 DOI: 10.3389/fimmu.2024.1403798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 07/09/2024] [Indexed: 08/15/2024] Open
Abstract
Rosacea is a complex inflammatory condition characterized by papulopustular lesions and erythema on the central face for which there is no cure. The development of rosacea is influenced by both external triggers and genetics, but the common pathophysiology is overactivation of the immune system. Here, we review the current data on proinflammatory cytokines and dysregulation of the neurovascular system as targetable components of rosacea. Amelioration of cutaneous and gastrointestinal dysbiosis and other external factors impacts the immune state and has been observed to improve rosacea. While multiple treatments exist, many patients do not achieve their goals for rosacea control and highlights an unmet need for dermatologic care. Current interventions encompass topical/oral drugs, light devices, and avoidance of triggers management. Additional understanding of the underlying pathogenesis may help us develop novel targeted therapeutic strategies to improve rosacea.
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Affiliation(s)
- Kuan-Yi Tu
- Division of General Medicine, Taipei Medical University Shuang Ho Hospital, New Taipei, Taiwan
| | - Chiau-Jing Jung
- Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Department of Microbiology and Immunology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Yi-Hsien Shih
- Department of Dermatology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
- Department of Dermatology, Taipei Medical University Shuang Ho Hospital, New Taipei, Taiwan
| | - Anne Lynn S. Chang
- Department of Dermatology, Stanford University School of Medicine, Redwood City, CA, United States
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Yan K, Liang Y. Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation. Eur J Med Res 2024; 29:116. [PMID: 38341589 PMCID: PMC10858610 DOI: 10.1186/s40001-023-01622-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 12/25/2023] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Asthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease. METHODS The gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma. RESULTS A total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631-0.904, p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = - 0.3268, p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = - 0.3472, p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960, p = 0.0071) and FEV1/forced vital capacity (r = 0.3213, p = 0.0314) in asthmatic patients. CONCLUSIONS Decreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.
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Affiliation(s)
- Kemin Yan
- Department of Geriatrics, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Yuxia Liang
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, Guangdong, China.
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