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Contribution of dipeptidyl peptidase 4 to non-typeable Haemophilus influenzae-induced lung inflammation in COPD. Clin Sci (Lond) 2021; 135:2067-2083. [PMID: 34405230 DOI: 10.1042/cs20210099] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 08/17/2021] [Accepted: 08/17/2021] [Indexed: 12/13/2022]
Abstract
Dipeptidyl peptidase 4 (DPP4) expression is increased in the lungs of chronic obstructive pulmonary disease (COPD). DPP4 is known to be associated with inflammation in various organs, including LPS-induced acute lung inflammation. Since non-typeable Haemophilus influenzae (NTHi) causes acute exacerbations in COPD patients, we examined the contribution of DPP4 in NTHi-induced lung inflammation in COPD. Pulmonary macrophages isolated from COPD patients showed higher expression of DPP4 than the macrophages isolated from normal subjects. In response to NTHi infection, COPD, but not normal macrophages show a further increase in the expression of DPP4. COPD macrophages also showed higher expression of IL-1β, and CCL3 responses to NTHi than normal, and treatment with DPP4 inhibitor, diprotin A attenuated this response. To examine the contribution of DPP4 in NTHi-induced lung inflammation, COPD mice were infected with NTHi, treated with diprotin A or PBS intraperitoneally, and examined for DPP4 expression, lung inflammation, and cytokine expression. Mice with COPD phenotype showed increased expression of DPP4, which increased further following NTHi infection. DPP4 expression was primarily observed in the infiltrated inflammatory cells. NTHi-infected COPD mice also showed sustained neutrophilic lung inflammation and expression of CCL3, and this was inhibited by DPP4 inhibitor. These observations indicate that enhanced expression of DPP4 in pulmonary macrophages may contribute to sustained lung inflammation in COPD following NTHi infection. Therefore, inhibition of DPP4 may reduce the severity of NTHi-induced lung inflammation in COPD.
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Jia R, Cui K, Li Z, Gao Y, Zhang B, Wang Z, Cui J. NK cell-derived exosomes improved lung injury in mouse model of Pseudomonas aeruginosa lung infection. J Physiol Sci 2020; 70:50. [PMID: 33096976 PMCID: PMC10717361 DOI: 10.1186/s12576-020-00776-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Accepted: 09/28/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND Pseudomonas aeruginosa (PA) is one of the most common bacteria that causes lung infection in hospital. The aim of our study is to explore the role and action mechanism of NK cells in lung PA infection. METHODS In this present study, 2.5 × 108 CFU/mouse PA was injected into murine trachea to make lung PA infection mouse model. Anti-asialo GM1 was used to inhibit NK cell. The percentage of NK cells was ensured by flow cytometry, and the M1- and M2-polarized macrophages were determined by flow cytometry, qRT-PCR, and ELISA assay. Besides, H&E staining was performed to ensure the pathological changes in lung tissues. Transmission electron microscopy and western blot were carried out to identify the exosome. RESULTS Here, in the mouse model of PA lung infection, NK cell depletion caused M2 polarization of lung macrophage, and exacerbated PA-induced lung injury. Next, our data shown that M2 macrophage polarization was enhanced when the generation of NK cell-derived exosome was blocked in the co-culture system of NK cells and macrophages. Subsequently, we demonstrated that NK cells promoted M1 macrophage polarization both in PA-infected macrophage and the mouse model of PA lung infection, and attenuated lung injury through exosome. CONCLUSION Overall, our data proved that NK cell may improve PA-induced lung injury through promoting M1 lung macrophage polarization by secreting exosome. Our results provide a new idea for the treatment of PA lung infection.
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Affiliation(s)
- Ruiqi Jia
- Respiratory Intensive Care Unit, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China
| | - Kuili Cui
- Tuberculosis Medicine, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China
| | - Zhenkui Li
- Tuberculosis Medicine, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China
| | - Yuan Gao
- Tuberculosis Medicine, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China
| | - Bianfang Zhang
- Tuberculosis Medicine, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China
| | - Zhixia Wang
- Respiratory Medicine, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China
| | - Junwei Cui
- Tuberculosis Medicine, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Xinxiang, 453003, China.
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Chen HH, Chen CC, Ho CW, Hsieh MC, Hsu SP, Lin CL, Kao CH. Dipeptidyl peptidase-4 inhibitor treatment could decrease Klebsiella pneumoniae pneumonia in patients with type 2 diabetes. Postgrad Med 2020; 132:714-719. [PMID: 32633173 DOI: 10.1080/00325481.2020.1793520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
OBJECTIVES To investigate the effect of dipeptidyl peptidase-4 inhibitor (DPP4i) for Klebsiella pneumoniae (KP) pneumonia in patients with diabetes. PATIENTS AND METHODS Patients newly diagnosed with type 2 diabetes from 2009 to 2012 were recruited for this population-based and observational study. Diabetes complications severity index (DCSI) score and defined daily dose (DDD) were used for analysis. The multivariable Cox proportional hazards models were used to estimate the risk of KP pneumonia by DPP4i use, with adjustments for propensity score. The Kaplan-Meier method with the log-rank test was used to estimate the risk of KP pneumonia for DPP4i users. RESULTS 34774 patients were included. The incidence rate of KP pneumonia in DDP4i users was 1.51 per 1000 person-years and that for the comparison was 2.25 per 1000 person-years. DDP4i users also had a significantly lower cumulative incidence of KP pneumonia (log-rank test p-value = 0.03). DDP4i users had a significantly lower risk of developing KP pneumonia compared with nonusers (adjusted HR = 0.67, 95% CI = 0.48-0.95). CONCLUSIONS For public health issue with type2 diabetes and infection, DPP4i use decreased KP pneumonia. Male gender, patients with co-morbidities, patients with higher DSCI score and higher DDD of DPP4i were observed to decrease KP pneumonia infection in our analysis. The possible role of DPP4i causing immunological disturbances should be considered.
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Affiliation(s)
- Hsin-Hung Chen
- Intelligent Diabetes Metabolism and Exercise Center, China Medical University Hospital , Taichung, Taiwan.,School of Medicine, Institute of Medicine and Public Health, Chung Shan Medical University , Taichung, Taiwan
| | - Ching-Chu Chen
- Division of Endocrinology and Metabolism, Department of Internal Medicine, China Medical University Hospital , Taichung, Taiwan.,School of Chinese Medicine, China Medical University , Taichung, Taiwan
| | - Chun-Wei Ho
- Intelligent Diabetes Metabolism and Exercise Center, China Medical University Hospital , Taichung, Taiwan
| | - Ming-Chia Hsieh
- Intelligent Diabetes Metabolism and Exercise Center, China Medical University Hospital , Taichung, Taiwan.,Graduate Institute of Integrative Medicine, China Medical University , Taichung, Taiwan.,Division of Clinical Nutrition, China Medical University Hospital , Taichung, Taiwan
| | - Sheng-Pang Hsu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, China Medical University Hospital , Taichung, Taiwan
| | - Cheng-Li Lin
- Management Office for Health Data, China Medical University Hospital , Taichung, Taiwan.,College of Medicine, China Medical University , Taichung, Taiwan
| | - Chia-Hung Kao
- Graduate Institute of Biomedical Sciences, China Medical University , Taichung, Taiwan.,Department of Nuclear Medicine and PET Center, China Medical University Hospital , Taichung, Taiwan.,Department of Bioinformatics and Medical Engineering, Asia University , Taichung, Taiwan.,Center of Augmented Intelligence in Healthcare, China Medical University Hospital , Taichung, Taiwan
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