Wenjing Yang, Jing Jie, Chunxiuli Li, Dong Chen, Shuang Zhao, Sanwei Gu, Jiancheng Xu, Lei Song
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引用次数: 0
Abstract
The Type VI Secretion System (T6SS) is a crucial mechanism mediating intercellular interactions in Gram-negative bacteria, particularly in pathogenic species such as Acinetobacter baumannii. Previous studies have shown that the large plasmid pAB3 in the A. baumannii ATCC 17978 strain encodes a TetR-like protein that inhibits the expression of core T6SS genes. In contrast, the WTR- strain, which lacks pAB3, can stably express and secrete the T6SS effector protein Hcp and exhibits the ability to kill E. coli. The tssM gene, one of the core genes of T6SS, is essential for its activity; its deletion directly leads to the inactivation of T6SS. However, traditional T6SS activity detection methods, such as killing assays, suffer from low throughput and insufficient sensitivity. To address these limitations, we have developed quantitative detection methods based on fluorescent labeling. To improve T6SS activity detection, we developed three fluorescent labeling methods: (1) A quantitative detection method based on Luciferase labeling, which is characterized by high specificity, sensitivity, and reproducibility, making it suitable for high-throughput analysis; (2) A detection method based on green fluorescent protein (GFP) labeling, which, despite being susceptible to environmental interference, offers the advantage of high throughput; (3) Flow cytometry detection, which can quantitatively assess bacterial viability but is operationally complex and costly. After a comprehensive comparison, the Luciferase-based labeling method proved to be the most accurate, sensitive, and user-friendly. When applied to 20 clinical isolates of A. baumannii, this method was confirmed to rapidly and accurately evaluate T6SS activity.
期刊介绍:
JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.