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17. Extracellular Vesicles From Mycoplasma gallisepticum: Modulators of Macrophage Activation and Virulence.

Author

Wang, Yingjie, Li, Shiying, Wang, Tengfei, Zou, Mengyun, and Peng, Xiuli

Subjects
MYCOPLASMA gallisepticum, EXTRACELLULAR vesicles, MACROPHAGE activation, CARRIER proteins, CELL communication
Abstract

Extracellular vesicles (EVs) mediate intercellular communication by transporting proteins. To investigate the pathogenesis of Mycoplasma gallisepticum , a major threat to the poultry industry, we isolated and characterized M. gallisepticum –produced EVs. Our study highlights the significant impact of M. gallisepticum –derived EVs on immune function and macrophage apoptosis, setting them apart from other M. gallisepticum metabolites. These EVs dose-dependently enhance M. gallisepticum adhesion and proliferation, simultaneously modulating Toll-like receptor 2 and interferon γ pathways and thereby inhibiting macrophage activation. A comprehensive protein analysis revealed 117 proteins in M. gallisepticum –derived EVs, including established virulence factors, such as GapA, CrmA, VlhA, and CrmB. Crucially, these EV-associated proteins significantly contribute to M. gallisepticum infection. Our findings advance our comprehension of M. gallisepticum pathogenesis, offering insights for preventive strategies and emphasizing the pivotal role of M. gallisepticum –derived EVs and their associated proteins. This research sheds light on the composition and crucial role of M. gallisepticum– derived EVs in M. gallisepticum pathogenesis, aiding our fight against M. gallisepticum infections. [ABSTRACT FROM AUTHOR]

Published
2024
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18. STAT5-mediated transcription of miR-33-5p in Mycoplasma gallisepticum-infected DF-1 cells.

Author

Sun, Yingfei, Wang, Yingjie, Wang, Lulu, Zou, Mengyun, and Peng, Xiuli

Subjects
GENETIC regulation, MYCOPLASMA gallisepticum, GENE expression, STAT proteins, MYCOPLASMA
Abstract

Mycoplasma gallisepticum (MG) represents the primary causative agent of chronic respiratory disease (CRD) in chickens. CRD is a prevalent ailment in the global poultry industry, resulting in substantial economic losses. In our previous work, we reported that miR-33-5p inhibits MG-induced apoptosis, inflammatory factor production, and MG replication by specifically targeting JNK1 in chickens. Nevertheless, the regulatory mechanisms governing miR-33-5p expression during MG infection remain poorly understood. Therefore, the objective of this study was to explore the regulation of miR-33-5p gene expression during MG infection. In this study, we observed an upregulation in the expression of pri-miR-33-5p and pre-miR-33-5p following MG infection, suggesting that their regulation takes place at the transcriptional level. Moreover, we characterized the transcriptional regulatory region of miR-33-5p and discovered the presence of a binding motif for STAT5, a recognized transcription factor responsible for gene expression regulation. Luciferase reporter assays and mutational analyses unequivocally showed that STAT5 binds to the miR-33-5p promoter element, thereby modulating miR-33-5p transcription in response to MG infection. Ultimately, the overexpression of STAT5 led to an elevation in miR-33-5p expression while concurrently suppressing JNK1 expression. Our findings elucidate that STAT5 governs the upregulation of miR-33-5p during MG infection. This research offers a comprehensive understanding of MG pathogenesis and the exploration of therapeutic approaches for MG-induced CRD. MG-HS regulates the expression of transcription factor STAT5. Transcription factor STAT5 can target miR-33-5p promoter element. MG-influenced STAT5 regulates miR-33-5p and its target gene expression. [ABSTRACT FROM AUTHOR]

Published
2024
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24. High-precision blood glucose prediction and hypoglycemia warning based on the LSTM-GRU model

Author

Peng Xiuli, Li Quanzhong, Wang Yannian, and Yan Dengfeng

Subjects
General Medicine
Abstract

Objective: The performance of blood glucose prediction and hypoglycemia warning based on the LSTM-GRU (Long Short Term Memory - Gated Recurrent Unit) model was evaluated. Methods: The research objects were 100 patients with Diabetes Mellitus (DM) who were chosen from Henan Provincial People’s Hospital. Their continuous blood glucose curves of 72 hours were acquired by a Continuous Glucose Monitoring System (CGMS). The blood glucose levels were predicted based on the LSTM, GRU and LSTM-GRU models, respectively. Analyses of the best predictive model were performed using Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE) and correlation analysis between the prediction blood glucose level and the original blood glucose level acquired by CGMS and Clark Error Grid Analysis (EGA). Repeated-measures analysis of variance (ANOVA) was used to analyze whether the RMSE values of the three models were statistically significant. 60 patients who had experienced hypoglycemia among 100 cases were selected for hypoglycemia warning. The sensitivity, false-positive rate and false-negative rate were used to evaluate the hypoglycemia warning performance of the LSTM-GRU model. This paper explored the changing relationship of the hypoglycemia warning performance of the model over time. Results: The predicted blood glucose levels of the three models were strongly correlated with the blood glucose levels acquired by CGMS (p < 0.001). The correlation coefficient (R-value) of the LSTM-GRU model remained stable over time (R = 0.995), nevertheless, a reduction in the R-value of the LSTM and GRU models when the Prediction Horizon (PH) was 30 min or longer. When PH was 15min, 30min, 45min and 60min, the mean RMSE values of the LSTM-GRU model were 0.259, 0.272, 0.275 and 0.278 (mmol/l), respectively, which were lower than the LSTM and GRU models and the RMSE values were statistically significant (p < 0.001). The EGA results showed the LSTM-GRU model had the highest proportion in zones A and B, as the PH extended. When PH was 30min or longer, the sensitivity and false-negative rate of the hypoglycemia warning of the LSTM-GRU model had subtle changes and the false-positive rate remained stable over time. Conclusions: The LSTM-GRU model demonstrated good performance in blood glucose prediction and hypoglycemia warning.

Published
2022

47. Characterization of differential pore-forming activities of ESAT-6 proteins from M. tuberculosis and M. smegmatis

Author

Peng, Xiuli, Jiang, Guozhong, Liu, Wei, Zhang, Qi, Qian, Wei, and Sun, Jianjun

Subjects
Antigens, Bacterial, Bacterial Proteins, Molecular Sequence Data, Mutation, Mycobacterium smegmatis, Porins, Amino Acid Sequence, Mycobacterium tuberculosis, Hydrogen-Ion Concentration, Article
Abstract

Mycobacterium tuberculosis ESAT-6 (MtbESAT-6) plays essential roles in pathogenesis. MtbESAT-6 exhibits a unique pore-forming activity (PFA) that is not found in its ortholog from non-pathogenic Mycobacterium smegmatis (MsESAT-6). Here, we characterized the differential PFAs and found that exchange of I25-H26/T25-A26 between two proteins reciprocally affected their PFAs. MtbESAT-6(IH/TA) had ~ 40% reduction, while MsESAT-6(TA/IH) fully acquired its activity similar to MtbESAT-6. Mutations of A17E, K38T, N67L or R74Q on MtbESAT-6(IH/TA) further reduced the activity, with MtbESAT-6(IH/TA-17) being the lowest. This study suggests I25-H26 as the pH-sensor essential for MsESAT-6 to fully acquire the activity, while multiple residues contributed to MtbESAT-6 PFA.

Published
2016

49. Molecular Cloning, Characterization and Expression Analysis of Duck Tyrosinase-Related Protein-1

Author

Feng YanPing, Gong YanZhang, Li ShiJun, Liang ZhenHua, Yu HuaWen, Wang Cui, and Peng XiuLi

Subjects
Signal peptide, Messenger RNA, General Veterinary, Tyrosinase, Biology, Molecular cloning, Molecular biology, law.invention, chemistry.chemical_compound, Open reading frame, chemistry, law, Complementary DNA, Agronomy and Crop Science, DNA, Polymerase chain reaction
Published
2010

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