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Prediction of genomic islands in three bacterial pathogens of pneumonia.

ABSTRACT: Pneumonia is one kind of common infectious disease, which is usually caused by bacteria, viruses, or fungi. In this paper, we predicted genomic islands in three bacterial pathogens of pneumonia. They are Chlamydophila pneumoniae, Mycoplasma pneumoniae and Streptococcus pneumoniae, respectively. For each pathogen, one clinical strain is involved. After implementing the cumulative GC profile combined with h and BCN index, eight genomic islands are found in three pathogens. Among them, six genomic islands are found to have mobility elements, which constitute a kind of conserved character of genomic islands, and this introduces the possibility that they are genuine genomic islands. The present results show that the cumulative GC profile when combined with h and BCN indexes is a good method for predicting genomic islands in bacteria and it has lower false positive rate than the SIGI method. Specially, three genomic islands are found to contain clusters of genes coding for production of virulence factors and this is useful for research into the pathogenicity of these pathogens and helpful for the treatment of diseases caused by them.

SUBMITTER: Guo FB

PROVIDER: S-EPMC3317706 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Prediction of genomic islands in three bacterial pathogens of pneumonia.

Guo Feng-Biao FB Wei Wen W

International journal of molecular sciences 20120307 3

Pneumonia is one kind of common infectious disease, which is usually caused by bacteria, viruses, or fungi. In this paper, we predicted genomic islands in three bacterial pathogens of pneumonia. They are Chlamydophila pneumoniae, Mycoplasma pneumoniae and Streptococcus pneumoniae, respectively. For each pathogen, one clinical strain is involved. After implementing the cumulative GC profile combined with h and BCN index, eight genomic islands are found in three pathogens. Among them, six genomic ...[more]

PMID: 22489145

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Project description:Commensal organisms are frequent causes of pneumonia. However, the detection of these organisms in the airway does not mean that they are the causative pathogens; they may exist merely as colonizers. In up to 50% cases of pneumonia, the causative pathogens remain unidentified, thereby hampering targeting therapies. In speculating on the role of a commensal organism in pneumonia, we devised the battlefield hypothesis. In the "pneumonia battlefield," the organism-to-human cell number ratio may be an index for the pathogenic role of the organism. Using real-time PCR reactions for sputum samples, we tested whether the hypothesis predicts the results of bacteriological clinical tests for 4 representative commensal organisms: Streptococcus pneumoniae, Haemophilus influenzae, Pseudomonas spp., and Moraxella catarrhalis. The cutoff value for the organism-to-human cell number ratio, above which the pathogenic role of the organism was suspected, was set up for each organism using 224 sputum samples. The validity of the cutoff value was then tested in a prospective study that included 153 samples; the samples were classified into 3 groups, and each group contained 93%, 7%, and 0% of the samples from pneumonia, in which the pathogenic role of Streptococcus pneumoniae was suggested by the clinical tests. The results for Haemophilus influenzae, Pseudomonas spp., and Moraxella catarrhalis were 100%, 0%, and 0%, respectively. The battlefield hypothesis enabled legitimate interpretation of the PCR results and predicted pneumonia in which the pathogenic role of the organism was suggested by the clinical test. The PCR reactions based on the battlefield hypothesis may help to promote targeted therapies for pneumonia. The prospective observatory study described in the current report had been registered to the University Hospital Medical Information Network (UMIN) registry before its initiation, where the UMIN is a registry approved by the International Committee of Medical Journal Editors (ICMJE). The UMIN registry number was UMIN000001118: A prospective study for the investigation of the validity of cutoff values established for the HIRA-TAN system (April 9, 2008).

Dataset Information

Prediction of genomic islands in three bacterial pathogens of pneumonia.

Publications

Prediction of genomic islands in three bacterial pathogens of pneumonia.

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