Identification of Prophages in Bacterial Genomes by Dinucleotide Relative Abundance Difference
Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential protein...
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| Published in | PloS one Vol. 2; no. 11; p. e1193 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
21.11.2007
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0001193 |
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| Abstract | Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful.
Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method.
The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. |
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| AbstractList | BACKGROUND: Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful. METHODOLOGY: Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method. CONCLUSIONS: The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful. Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method. The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. Background Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful. Methodology Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at Conclusions The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. Background Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful. Methodology Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method. Conclusions The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful. Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method. The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful.BACKGROUNDProphages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated genes are reported to be prophage encoded. Present computational methods to detect prophages are either by identifying possible essential proteins such as integrases or by an extension of this technique, which involves identifying a region containing proteins similar to those occurring in prophages. These methods suffer due to the problem of low sequence similarity at the protein level, which suggests that a nucleotide based approach could be useful.Earlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method.METHODOLOGYEarlier dinucleotide relative abundance (DRA) have been used to identify regions, which deviate from the neighborhood areas, in genomes. We have used the difference in the dinucleotide relative abundance (DRAD) between the bacterial and prophage DNA to aid location of DNA stretches that could be of prophage origin in bacterial genomes. Prophage sequences which deviate from bacterial regions in their dinucleotide frequencies are detected by scanning bacterial genome sequences. The method was validated using a subset of genomes with prophage data from literature reports. A web interface for prophage scan based on this method is available at http://bicmku.in:8082/prophagedb/dra.html. Two hundred bacterial genomes which do not have annotated prophages have been scanned for prophage regions using this method.The relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences.CONCLUSIONSThe relative dinucleotide distribution difference helps detect prophage regions in genome sequences. The usefulness of this method is seen in the identification of 461 highly probable loci pertaining to prophages which have not been annotated so earlier. This work emphasizes the need to extend the efforts to detect and annotate prophage elements in genome sequences. |
| Audience | Academic |
| Author | Alaguraj, V. Krishnaswamy, S. Poornima, G. Raghavenderan, L. Singh, G. P. Kumar, Dinesh Katta, A. V. S. K. Mohan Mehta, Preeti Srividhya, K. V. |
| AuthorAffiliation | Weizmann Institute of Science, Israel Centre of Excellence in Bioinformatics, School of Biotechnology, Madurai Kamaraj University, Madurai, Tamilnadu, India |
| AuthorAffiliation_xml | – name: Weizmann Institute of Science, Israel – name: Centre of Excellence in Bioinformatics, School of Biotechnology, Madurai Kamaraj University, Madurai, Tamilnadu, India |
| Author_xml | – sequence: 1 givenname: K. V. surname: Srividhya fullname: Srividhya, K. V. – sequence: 2 givenname: V. surname: Alaguraj fullname: Alaguraj, V. – sequence: 3 givenname: G. surname: Poornima fullname: Poornima, G. – sequence: 4 givenname: Dinesh surname: Kumar fullname: Kumar, Dinesh – sequence: 5 givenname: G. P. surname: Singh fullname: Singh, G. P. – sequence: 6 givenname: L. surname: Raghavenderan fullname: Raghavenderan, L. – sequence: 7 givenname: A. V. S. K. Mohan surname: Katta fullname: Katta, A. V. S. K. Mohan – sequence: 8 givenname: Preeti surname: Mehta fullname: Mehta, Preeti – sequence: 9 givenname: S. surname: Krishnaswamy fullname: Krishnaswamy, S. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/18030328$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2007 Public Library of Science 2007 Srividhya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Srividhya et al. 2007 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: SK PM. Performed the experiments: KS VA GP LR. Analyzed the data: SK KS GP LR DK. Contributed reagents/materials/analysis tools: VA GS PM DK AM. Wrote the paper: SK KS. |
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| Snippet | Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many virulence-associated... Background Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many... BACKGROUND: Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many... Background Prophages are integrated viral forms in bacterial genomes that have been found to contribute to interstrain genetic variability. Many... |
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| SubjectTerms | Abundance Amino acid sequence Antigens Bacteria Bacterial genetics Bioinformatics Biotechnology Computational Biology Computational Biology/Comparative Sequence Analysis Computational Biology/Genomics Computer applications Deoxyribonucleic acid DNA E coli Escherichia coli Gene sequencing Genes Genetic Heterogeneity Genetic variability Genome, Bacterial Genomes Genomics Helicobacter pylori Identification methods Mycobacterium Mycobacterium - genetics Mycobacterium - virology Mycobacterium tuberculosis Nucleotides - metabolism Pathogenesis Pathogens Prophages Prophages - metabolism Proteins Relative abundance Salmonella Salmonella enterica - genetics Salmonella enterica - virology Salmonella Typhimurium Sensitivity and Specificity Shigella Toxins Trends Tuberculosis Typhoid Vibrio mimicus Virulence Virulence (Microbiology) Zoonoses |
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| Title | Identification of Prophages in Bacterial Genomes by Dinucleotide Relative Abundance Difference |
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