AIM: To apply a new, integrated technique for visualizing bacterial genomes to identify novel pathogenicity islands in Helicobacter pylori (H. pylori). METHODS: A genomic barcode imaging method (converting frequency matrices to grey-scale levels) was designed to visually distinguish origin-specific genomic regions in H. pylori. The complete genome sequences of the six H. pylori strains published in the National Center for Biotechnological Information prokaryotic genome database were scanned, and compared to the genome barcodes of Escherichia coli (E. coli) O157:H7 strain EDL933 and a random nucleotide sequence. The following criteria were applied to identify potential pathogenicity islands (PAIs): (1) barcode distance distinct from that of the general background; (2) length greater than 10000 continuous base pairs; and (3) containing genes with known virulence-related functions (as determined by PfamScan and Blast2GO). RESULTS: Comparison of the barcode images generated for the 26695, HPAG1, J99, Shi470, G27 and P12 H. pylori genomes with those for the E. coli and random sequence controls revealed that H. pylori genomes contained fewer anomalous regions. Among the H. pylori-specific continuous anomalous regions (longer than 20 kbp in each strain's genome), two fit the criteria for identifying candidate PAIs. The bioinformatic-based functional analyses revealed that one of the two anomalous regions was the known pathogenicity island cag-PAI, this finding also served as proof-of-principle for the utility of the genomic barcoding approach for identifying PAIs, and characterized the other as a novel PAI, which was designated as tfs3-PAI. Furthermore, the cag-PAI and tfs3-PAI harbored genes encoding type IV secretion system proteins and were predicted to have potential for functional synergy. CONCLUSION: Genomic barcode imaging represents an effective bioinformatic-based approach for scanning bacterial genomes, such as H. pylori, to identify candidate PAIs.
AIM: To apply a new, integrated technique for visualizing bacterial genomes to identify novel pathogenicity islands in Helicobacter pylori (H. pylori). METHODS: A genomic barcode imaging method (converting frequency matrices to grey-scale levels) was designed to visually distinguish origin-specific genomic regions in H. pylori. The complete genome sequences of the six H. pylori strains published in the National Center for Biotechnological Information prokaryotic genome database were scanned, and compared to the genome barcodes of Escherichia coli (E. coli) O157:H7 strain EDL933 and a random nucleotide sequence. The following criteria were applied to identify potential pathogenicity islands (PAIs): (1) barcode distance distinct from that of the general background; (2) length greater than 10000 continuous base pairs; and (3) containing genes with known virulence-related functions (as determined by PfamScan and Blast2GO). RESULTS: Comparison of the barcode images generated for the 26695, HPAG1, J99, Shi470, G27 and P12 H. pylori genomes with those for the E. coli and random sequence controls revealed that H. pylori genomes contained fewer anomalous regions. Among the H. pylori-specific continuous anomalous regions (longer than 20 kbp in each strain's genome), two fit the criteria for identifying candidate PAIs. The bioinformatic-based functional analyses revealed that one of the two anomalous regions was the known pathogenicity island cag-PAI, this finding also served as proof-of-principle for the utility of the genomic barcoding approach for identifying PAIs, and characterized the other as a novel PAI, which was designated as tfs3-PAI. Furthermore, the cag-PAI and tfs3-PAI harbored genes encoding type IV secretion system proteins and were predicted to have potential for functional synergy. CONCLUSION: Genomic barcode imaging represents an effective bioinformatic-based approach for scanning bacterial genomes, such as H. pylori, to identify candidate PAIs.
Entities:
Keywords:
Genome analysis; Genomic bar coding; Helicobacter pylori; Pathogenicity islands
Authors: David A Baltrus; Manuel R Amieva; Antonello Covacci; Todd M Lowe; D Scott Merrell; Karen M Ottemann; Markus Stein; Nina R Salama; Karen Guillemin Journal: J Bacteriol Date: 2008-10-24 Impact factor: 3.490
Authors: Robert D Finn; John Tate; Jaina Mistry; Penny C Coggill; Stephen John Sammut; Hans-Rudolf Hotz; Goran Ceric; Kristoffer Forslund; Sean R Eddy; Erik L L Sonnhammer; Alex Bateman Journal: Nucleic Acids Res Date: 2007-11-26 Impact factor: 16.971
Authors: Stefan Götz; Juan Miguel García-Gómez; Javier Terol; Tim D Williams; Shivashankar H Nagaraj; María José Nueda; Montserrat Robles; Manuel Talón; Joaquín Dopazo; Ana Conesa Journal: Nucleic Acids Res Date: 2008-04-29 Impact factor: 16.971