Prediction of genomic islands in seven human pathogens using the Z-Island method

Abstract

We adopted the method of Zhang and Zhang (the Z-Island method) to identify genomic islands in seven human pathogens, analyzing their chromosomal DNA sequences. The Z-Island method is a theoretical method for predicting genomic islands in bacterial genomes; it consists of determination of the cumulative GC profile and computation of codon usage bias. Thirty-one genomic islands were found in seven pathogens using this method. Further analysis demonstrated that most have the known conserved features; this increases the probability that they are real genomic islands. Eleven genomic islands were found to code for products involved in causing disease (virulence factors) or in resistance to antibiotics (resistance factors). This finding could be useful for research on the pathogenicity of these bacteria and helpful in the treatment of the diseases that they cause. In a comparison of the distribution of mobility elements in genomic islands predicted by different methods, the Z-Island method gave lower false-positive rates. The Z-Island method was found to detect more known genomic islands than the two methods that we compared it with, SIGI-HMM and IslandPick. Furthermore, it maintained a better balance between specificity and sensitivity. The only inconvenience is that the steps for finding genomic islands by the Z-Island method are semi-automatic.