Browsing by Author "Huang, Qian"

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    Roles of the Site 2 Protease Eep in Staphylococcus aureus
    (American Society for Microbiology, 2020-07-09) Cheng, Danhong; Lv, Huiying; Yao, Yong; Cheng, Sen; Huang, Qian; Wang, Hua; Liu, Xiaoyun; Bae, Taeok; Li, Min; Liu, Qian; Microbiology and Immunology, School of Medicine
    In Enterococcus faecalis, the site 2 protease Eep generates sex pheromones, including cAM373. Intriguingly, in Staphylococcus aureus, a peptide similar to cAM373, named cAM373_SA, is produced from the camS gene. Here, we report that the staphylococcal Eep homolog is not only responsible for the production of cAM373_SA but also critical for staphylococcal virulence. As with other Eep proteins, the staphylococcal Eep protein has four transmembrane (TM) domains, with the predicted zinc metalloprotease active site (HEXXH) in the first TM domain. eep deletion reduced the cAM373_SA activity in the culture supernatant to the level of the camS deletion mutant. It also markedly decreased the cAM373 peptide peak in a high-performance liquid chromatography (HPLC) analysis. Proteomics analysis showed that Eep affects the production and/or the release of diverse proteins, including the signal peptidase subunit SpsB and the surface proteins SpA, SasG, and FnbA. eep deletion decreased the adherence of S. aureus to host epithelial cells; however, the adherence of the eep mutant was increased by overexpression of the surface proteins SpA, SasG, and FnbA. eep deletion reduced staphylococcal resistance to killing by human neutrophils as well as survival in a murine model of blood infection. The overexpression of the surface protein SpA in the eep mutant increased bacterial survival in the liver. Our study illustrates that in S. aureus, Eep not only generates cAM373_SA but also contributes to the survival of the bacterial pathogen in the host.IMPORTANCE The emergence of multidrug-resistant Staphylococcus aureus makes the treatment of staphylococcal infections much more difficult. S. aureus can acquire a drug resistance gene from other bacteria, such as Enterococcus faecalis Intriguingly, S. aureus produces a sex pheromone for the E. faecalis plasmid pAM373, raising the possibility that S. aureus actively promotes plasmid conjugation from E. faecalis In this study, we found that the staphylococcal Eep protein is responsible for sex pheromone processing and contributes to the survival of the bacteria in the host. These results will enhance future research on the drug resistance acquisition of S. aureus and can lead to the development of novel antivirulence drugs.
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    Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites
    (Hindawi, 2015-09-03) Wang, Guohua; Wang, Fang; Huang, Qian; Li, Yu; Liu, Yunlong; Wang, Yadong; Medical and Molecular Genetics, School of Medicine
    Transcription factors are proteins that bind to DNA sequences to regulate gene transcription. The transcription factor binding sites are short DNA sequences (5-20 bp long) specifically bound by one or more transcription factors. The identification of transcription factor binding sites and prediction of their function continue to be challenging problems in computational biology. In this study, by integrating the DNase I hypersensitive sites with known position weight matrices in the TRANSFAC database, the transcription factor binding sites in gene regulatory region are identified. Based on the global gene expression patterns in cervical cancer HeLaS3 cell and HelaS3-ifnα4h cell (interferon treatment on HeLaS3 cell for 4 hours), we present a model-based computational approach to predict a set of transcription factors that potentially cause such differential gene expression. Significantly, 6 out 10 predicted functional factors, including IRF, IRF-2, IRF-9, IRF-1 and IRF-3, ICSBP, belong to interferon regulatory factor family and upregulate the gene expression levels responding to the interferon treatment. Another factor, ISGF-3, is also a transcriptional activator induced by interferon alpha. Using the different transcription factor binding sites selected criteria, the prediction result of our model is consistent. Our model demonstrated the potential to computationally identify the functional transcription factors in gene regulation.