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PePPER: a webserver for prediction of prokaryote promoter elements and regulons.

de Jong A, Pietersma H, Cordes M, Kuipers OP, Kok J - BMC Genomics (2012)

Bottom Line: Improved prediction and comparison algorithms are currently available for identifying transcription factor binding sites (TFBSs) and their accompanying TFs and regulon members.Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons.On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, 9747 AG Groningen, The Netherlands.

ABSTRACT

Background: Accurate prediction of DNA motifs that are targets of RNA polymerases, sigma factors and transcription factors (TFs) in prokaryotes is a difficult mission mainly due to as yet undiscovered features in DNA sequences or structures in promoter regions. Improved prediction and comparison algorithms are currently available for identifying transcription factor binding sites (TFBSs) and their accompanying TFs and regulon members.

Results: We here extend the current databases of TFs, TFBSs and regulons with our knowledge on Lactococcus lactis and developed a webserver for prediction, mining and visualization of prokaryote promoter elements and regulons via a novel concept. This new approach includes an all-in-one method of data mining for TFs, TFBSs, promoters, and regulons for any bacterial genome via a user-friendly webserver. We demonstrate the power of this method by mining WalRK regulons in Lactococci and Streptococci and, vice versa, use L. lactis regulon data (CodY) to mine closely related species.

Conclusions: The PePPER webserver offers, besides the all-in-one analysis method, a toolbox for mining for regulons, promoters and TFBSs and accommodates a new L. lactis regulon database in addition to already existing regulon data. Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons. On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons. The PePPER webserver is freely accessible at http://pepper.molgenrug.nl.

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Flow diagram of PePPER all-in-one. The first step of PePPER all-in-one is to select a set of genes that putatively belong to a certain regulon in one organism (target; Box I represents all genes of the target organism) through comparison with the corresponding regulons in all other organisms (source) using protein Blast (genes in Box Ia). In parallel, the known TFBSs of these regulons are used to find genes in the target organism that carry this DNA motif in their upstream regions (genes in Box Ib). Subsequently, a MEME search is performed on the upstream regions of the genes in both independently obtained gene pools. This results in a set of genes that represents the putative regulon in the target organism with its predicted TFBS (genes in Box II). Finally, features such as RBSs, promoter and transcription terminators are added, after which the result is graphically represented. The information can be accessed and viewed separately per gene.
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Figure 1: Flow diagram of PePPER all-in-one. The first step of PePPER all-in-one is to select a set of genes that putatively belong to a certain regulon in one organism (target; Box I represents all genes of the target organism) through comparison with the corresponding regulons in all other organisms (source) using protein Blast (genes in Box Ia). In parallel, the known TFBSs of these regulons are used to find genes in the target organism that carry this DNA motif in their upstream regions (genes in Box Ib). Subsequently, a MEME search is performed on the upstream regions of the genes in both independently obtained gene pools. This results in a set of genes that represents the putative regulon in the target organism with its predicted TFBS (genes in Box II). Finally, features such as RBSs, promoter and transcription terminators are added, after which the result is graphically represented. The information can be accessed and viewed separately per gene.

Mentions: PePPER all-in-one is a parameter-free pipeline of the individual PePPER tools allowing fully automatic intergenic annotation combined with analysis of regulons. A schematic overview of the PePPER all-in-one process is shown in Figure 1. Two input formats are accepted for analysis: i) plain DNA sequences in FastA format, ii) a fully annotated file in the Genbank file format. DNA sequences lacking ORF information will be automatically annotated using Glimmer3 to discriminate between ORFs and intergenic regions. Input files in Genbank format, either uploaded or selected from the PePPER library of genomes, will produce the most extended results, including hyperlinks to NCBI resources such as protein annotation, protein domains and genomic context of the genes. The output is organized into three tables and one figure: i) Table 1, the “Summary of Results” contains links to detailed information on analysis of regulons, TFBS, promoters, transcription terminators, RNA folding and motif analysis using MEME, ii) Table 2 and Table 3, “Files available for download”, iii) Table 4, Combined results of the TFBS and regulon mining. Figure 1 gives a graphical presentation of the intergenic regions.


PePPER: a webserver for prediction of prokaryote promoter elements and regulons.

de Jong A, Pietersma H, Cordes M, Kuipers OP, Kok J - BMC Genomics (2012)

Flow diagram of PePPER all-in-one. The first step of PePPER all-in-one is to select a set of genes that putatively belong to a certain regulon in one organism (target; Box I represents all genes of the target organism) through comparison with the corresponding regulons in all other organisms (source) using protein Blast (genes in Box Ia). In parallel, the known TFBSs of these regulons are used to find genes in the target organism that carry this DNA motif in their upstream regions (genes in Box Ib). Subsequently, a MEME search is performed on the upstream regions of the genes in both independently obtained gene pools. This results in a set of genes that represents the putative regulon in the target organism with its predicted TFBS (genes in Box II). Finally, features such as RBSs, promoter and transcription terminators are added, after which the result is graphically represented. The information can be accessed and viewed separately per gene.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472324&req=5

Figure 1: Flow diagram of PePPER all-in-one. The first step of PePPER all-in-one is to select a set of genes that putatively belong to a certain regulon in one organism (target; Box I represents all genes of the target organism) through comparison with the corresponding regulons in all other organisms (source) using protein Blast (genes in Box Ia). In parallel, the known TFBSs of these regulons are used to find genes in the target organism that carry this DNA motif in their upstream regions (genes in Box Ib). Subsequently, a MEME search is performed on the upstream regions of the genes in both independently obtained gene pools. This results in a set of genes that represents the putative regulon in the target organism with its predicted TFBS (genes in Box II). Finally, features such as RBSs, promoter and transcription terminators are added, after which the result is graphically represented. The information can be accessed and viewed separately per gene.
Mentions: PePPER all-in-one is a parameter-free pipeline of the individual PePPER tools allowing fully automatic intergenic annotation combined with analysis of regulons. A schematic overview of the PePPER all-in-one process is shown in Figure 1. Two input formats are accepted for analysis: i) plain DNA sequences in FastA format, ii) a fully annotated file in the Genbank file format. DNA sequences lacking ORF information will be automatically annotated using Glimmer3 to discriminate between ORFs and intergenic regions. Input files in Genbank format, either uploaded or selected from the PePPER library of genomes, will produce the most extended results, including hyperlinks to NCBI resources such as protein annotation, protein domains and genomic context of the genes. The output is organized into three tables and one figure: i) Table 1, the “Summary of Results” contains links to detailed information on analysis of regulons, TFBS, promoters, transcription terminators, RNA folding and motif analysis using MEME, ii) Table 2 and Table 3, “Files available for download”, iii) Table 4, Combined results of the TFBS and regulon mining. Figure 1 gives a graphical presentation of the intergenic regions.

Bottom Line: Improved prediction and comparison algorithms are currently available for identifying transcription factor binding sites (TFBSs) and their accompanying TFs and regulon members.Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons.On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Molecular Genetics, University of Groningen, Groningen Biomolecular Sciences and Biotechnology Institute, 9747 AG Groningen, The Netherlands.

ABSTRACT

Background: Accurate prediction of DNA motifs that are targets of RNA polymerases, sigma factors and transcription factors (TFs) in prokaryotes is a difficult mission mainly due to as yet undiscovered features in DNA sequences or structures in promoter regions. Improved prediction and comparison algorithms are currently available for identifying transcription factor binding sites (TFBSs) and their accompanying TFs and regulon members.

Results: We here extend the current databases of TFs, TFBSs and regulons with our knowledge on Lactococcus lactis and developed a webserver for prediction, mining and visualization of prokaryote promoter elements and regulons via a novel concept. This new approach includes an all-in-one method of data mining for TFs, TFBSs, promoters, and regulons for any bacterial genome via a user-friendly webserver. We demonstrate the power of this method by mining WalRK regulons in Lactococci and Streptococci and, vice versa, use L. lactis regulon data (CodY) to mine closely related species.

Conclusions: The PePPER webserver offers, besides the all-in-one analysis method, a toolbox for mining for regulons, promoters and TFBSs and accommodates a new L. lactis regulon database in addition to already existing regulon data. Identification of putative regulons and full annotation of intergenic regions in any bacterial genome on the basis of existing knowledge on a related organism can now be performed by biologists and it can be done for a wide range of regulons. On the basis of the PePPER output, biologist can design experiments to further verify the existence and extent of the proposed regulons. The PePPER webserver is freely accessible at http://pepper.molgenrug.nl.

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