PMeS: Prediction of Methylation Sites Based on Enhanced Feature Encoding Scheme

Protein methylation is predominantly found on lysine and arginine residues, and carries many important biological functions, including gene regulation and signal transduction. Given their important involvement in gene expression, protein methylation and their regulatory enzymes are implicated in a variety of human disease states such as cancer, coronary heart disease and neurodegenerative disorders. Thus, identification of methylation sites can be very helpful for the drug designs of various related diseases. In this study, we developed a method called PMeS to improve the prediction of protein methylation sites based on an enhanced feature encoding scheme and support vector machine. The enhanced feature encoding scheme was composed of the sparse property coding, normalized van der Waals volume, position weight amino acid composition and accessible surface area. The PMeS achieved a promising performance with a sensitivity of 92.45%, a specificity of 93.18%, an accuracy of 92.82% and a Matthew’s correlation coefficient of 85.69% for arginine as well as a sensitivity of 84.38%, a specificity of 93.94%, an accuracy of 89.16% and a Matthew’s correlation coefficient of 78.68% for lysine in 10-fold cross validation. Compared with other existing methods, the PMeS provides better predictive performance and greater robustness. It can be anticipated that the PMeS might be useful to guide future experiments needed to identify potential methylation sites in proteins of interest. The online service is available at http://bioinfo.ncu.edu.cn/inquiries_PMeS.aspx

Clostridium difficile infection.

Infection of the colon with the Gram-positive bacterium Clostridium difficile is potentially life threatening, especially in elderly people and in patients who have dysbiosis of the gut microbiota following antimicrobial drug exposure. C. difficile is the leading cause of health-care-associated infective diarrhoea. The life cycle of C. difficile is influenced by antimicrobial agents, the host immune system, and the host microbiota and its associated metabolites. The primary mediators of inflammation in C. difficile infection (CDI) are large clostridial toxins, toxin A (TcdA) and toxin B (TcdB), and, in some bacterial strains, the binary toxin CDT. The toxins trigger a complex cascade of host cellular responses to cause diarrhoea, inflammation and tissue necrosis - the major symptoms of CDI. The factors responsible for the epidemic of some C. difficile strains are poorly understood. Recurrent infections are common and can be debilitating. Toxin detection for diagnosis is important for accurate epidemiological study, and for optimal management and prevention strategies. Infections are commonly treated with specific antimicrobial agents, but faecal microbiota transplants have shown promise for recurrent infections. Future biotherapies for C. difficile infections are likely to involve defined combinations of key gut microbiota