Large-Scale Analysis of Fitness Cost of tet(X4)-Positive Plasmids in Escherichia coli.

Tigecycline is one of important antimicrobial agents for the treatment of infections caused by multidrug-resistant (MDR) Gram-negative bacteria. However, the emergence and prevalence of plasmid-mediated tigecycline resistance gene tet(X4) are threatening human and animal health. Fitness cost elicited by resistance plasmids is a key factor affecting the maintenance and transmission of antibiotic resistance genes (ARGs) in the host. A comparative analysis of the fitness cost of different types of tet(X4)-positive plasmids is helpful to understand and predict the prevalence of dominant plasmids. In this study, we performed a large-scale analysis of fitness cost of tet(X4)-positive plasmids origin from clinical isolates. These plasmids were successfully electroporated into a reference strain Escherichia coli TOP10, and a series of transformants carrying the tet(X) gene were obtained. The effects of tet(X4)-positive plasmids on the growth rate, plasmid stability, relative fitness, biofilm formation, and virulence in a Galleria mellonella model were evaluated. Consequently, we found that these plasmids resulted in varying degrees of fitness cost on TOP10, including delayed bacterial growth and attenuated virulence. Out of these plasmids, tet(X4)-harboring IncFII plasmids showed the lowest fitness cost on the host. Furthermore, by means of experimental evolution in the presence of commonly used drugs in clinic, the fitness cost of tet(X4)-positive plasmids was substantially alleviated, accompanied by increased plasmid stability. Collectively, our data reveal the differential fitness cost caused by different types of tet(X4)-positive plasmids and suggest that the wide use of tetracycline antibiotics may promote the evolution of plasmids.

Characterization of Fitness Cost Caused by Tigecycline-Resistance Gene tet(X6) in Different Host Bacteria.

The emergence and prevalence of the tet(X) gene and its variants in the environment and in clinical settings constitute a growing concern for public health worldwide. Accordingly, the tigecycline resistance gene variant tet(X6) is widely detected in Proteus spp. and Acinetobacter spp. rather than Enterobacteriaceae, while the underpinning behind this phenomenon is still unclear. To investigate the mechanisms underlying this distinct phenomenon, we assessed the fitness of the engineered plasmid pBAD-tet(X6) in different host bacteria by monitoring their growth curves, relative fitness and the ability of biofilm formation, as well as virulence in a Galleria mellonella model. MIC and qRT-PCR analysis indicated the successful expression of the tet(X6) gene in these strains in the presence of l-arabinose. Furthermore, we found that pBAD-tet(X6) displayed the lowest fitness cost in P. mirabilis compared with that in E. coli or S. Enteritidis, suggesting the fitness difference of tet(X6)-bearing plasmids in different host bacteria. Consistently, the carriage of pBAD-tet(X6) remarkably reduced the biofilm production and virulence of E. coli or S. Enteritidis. These findings not only indicate that the fitness cost difference elicited by the tet(X6) gene may be responsible for its selectivity in host bacteria but also sheds new insight into the dissemination of antibiotic resistance genes (ARGs) in clinical and environmental isolates.

Network pharmacology assessment of Qingkailing injection treatment of cholestatic hepatitis.

OBJECTIVE: To investigate the targets and mechanisms of action of Qingkailing injection (，QKL) in the treatment of cholestatic hepatitis. METHODS: A network pharmacology method was implemented using drug and disease databases to target QKL and cholestasis hepatitis, respectively. The functional protein association network STRING database was used to construct a protein-protein interaction network using R language and the Bioconductor toolkit. The org.Hs.eg.db and clusterProfiler packages were used for gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, which explored biological functions and pathways of potential targets. Targets were then visualized using Cytoscape 3.6.0 software. RESULTS: We screened 121 compounds in QKL and identified 112 targets for the treatment of cholestatic hepatitis. QKL played a role in the treatment of cholestatic hepatitis through 305 biology process terms, 15 cellular component and 29 molecular function terms. The mechanism of QKL action was mainly related to tumor necrosis factor, mitogen-activated protein kinase, and PI3K-Akt signaling pathways. CONCLUSION: The treatment of cholestatic hepatitis by QKL involved multiple targets, biological functions, and signaling pathways that are closely associated with the disease.