Identification of ColR binding consensus and prediction of regulon of ColRS two-component system.;Kivistik PA, Kivi R, Kivisaar M, Hõrak R;BMC molecular biology 2009 May 16;
10():46
[19445690]
Promoter-lacZ fusion assays showed that ColR regulates the expression of PP0903. DNase I footprinting was used to identify ColR binding sites in oprQ and PP0903. ColR binding motif was then used to identify additional ColR targets. LacZ reporter assays, DNase I footprinting, EMSA were used to verify the functionality of the predicted ColR binding sites.
Regulated genes for each binding site are displayed below. Gene regulation diagrams
show binding sites, positively-regulated genes,
negatively-regulated genes,
both positively and negatively regulated
genes, genes with unspecified type of regulation.
For each indvidual site, experimental techniques used to determine the site are also given.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.
Reporter assay using the beta-galactosidase (lacZ) gene.
The lacZ gene is typically fused to the promoter of interest. Differential regulation of the promoter mediated by the TF is assessed by induction of the system and evaluation of lacZ expression. Bacteria expressing lacZ appear blue when grown on a X-gal medium.
The assay is often performed using a plasmid borne construction on a lacZ(def) strain.
The DNAse foot-printing method starts by focusing on a given region of interest (e.g. a promoter region) and amplifying it by PCR to obtain lots of sample. It then throws in the TF and then the DNAse. The mix is left to stir for a short time and then gel electrophoresis is run to compare the pattern of fragments in a control (no TF) and in the sample. If the TF has bound the sample, it will have protected a stretch of DNA (encompassing some fragments of the control) and thus those fragments will not appear in the sample gel. The fragments can then be cut-out from the gel, purified and sequenced to obtain the sequence of the protected region. This is often used to identify the binding motif of a TF for the first time. The foot-printing will typically resolve the protected region down to 50-100 bp, and the sequence can be then examined for possible TF-binding sites either by eye of using a computer search.
In motif discovery, we are given a set of sequences that we suspect harbor binding sites for a given transcription factor. A typical scenario is data coming from expression experiments, in which we wish to analyze the promoter region of a bunch of genes that are up- or down-regulated under some condition. The goal of motif discovery is to detect the transcription factor binding motif (i.e. the sequence “pattern” bound by the TF), by assuming that it will be overrepresented in our sample of sequences. There are different strategies to accomplish this, but the standard approach uses expectation maximization (EM) and in particular Gibbs sampling or greedy search. Popular algorithms for motif discovery are MEME, Gibbs Motif Sampler or CONSENSUS. More recently, motif discovery algorithms that make use of phylogenetic foot-printing (the idea that TF-binding site will be conserved in the promoter sequences for the same gene in different species) have become available. These are not usually applied to complement experimental work, but can be used to provide a starting point for it. Popular algorithms include FootPrinter and PhyloGibbs.
Once the binding motif for a TF is known, this motif (which essentially defines a pattern) can be used to scan sequences in order to search for putative TF-binding site. This is useful, for instance, when trying to identify TF-binding site in ChIP-chip data. Searching for TF-binding site can be done in numerous ways. The most basic method is consensus search, in sequences are scored according to how many mismatches they have with the consensus sequence for the motif. A more elaborate way of searching involves using regular expressions, which allow to search for more loosely defined motifs [e.g. C(C/G)AT]. Common algorithms for this type of search include Pattern Locator and the DNA Pattern Find method of the SMS2 suite, but also some word processors. Finally, the mainstream way of conducting TF-binding site search is through the use of position-specific scoring matrices, which basically count the occurrences of each base at each position of the motif and use the inferred frequencies to score candidate sites. Algorithms in this last category include TFSEARCH, FITOM, CONSITE, TESS and MatInspector.