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In Silico Signature Prediction Modeling in Cytolethal Distending Toxin-Producing Escherichia coli Strains
Genomics & Informatics ; : 69-80, 2017.
Article in En | WPRIM | ID: wpr-93438
Responsible library: WPRO
ABSTRACT
In this study, cytolethal distending toxin (CDT) producer isolates genome were compared with genome of pathogenic and commensal Escherichia coli strains. Conserved genomic signatures among different types of CDT producer E. coli strains were assessed. It was shown that they could be used as biomarkers for research purposes and clinical diagnosis by polymerase chain reaction, or in vaccine development. cdt genes and several other genetic biomarkers were identified as signature sequences in CDT producer strains. The identified signatures include several individual phage proteins (holins, nucleases, and terminases, and transferases) and multiple members of different protein families (the lambda family, phage-integrase family, phage-tail tape protein family, putative membrane proteins, regulatory proteins, restriction-modification system proteins, tail fiber-assembly proteins, base plate-assembly proteins, and other prophage tail-related proteins). In this study, a sporadic phylogenic pattern was demonstrated in the CDT-producing strains. In conclusion, conserved signature proteins in a wide range of pathogenic bacterial strains can potentially be used in modern vaccine-design strategies.
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Full text: 1 Index: WPRIM Main subject: Tail / Bacteriophages / Computer Simulation / Biomarkers / Polymerase Chain Reaction / Genome / Prophages / Diagnosis / Escherichia / Escherichia coli Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Genomics & Informatics Year: 2017 Type: Article
Full text: 1 Index: WPRIM Main subject: Tail / Bacteriophages / Computer Simulation / Biomarkers / Polymerase Chain Reaction / Genome / Prophages / Diagnosis / Escherichia / Escherichia coli Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: En Journal: Genomics & Informatics Year: 2017 Type: Article