Background CHARGE syndrome is a complex of birth defects including coloboma, choanal atresia, ear malformations and deafness, cardiac defects, and growth delay. We have previously hypothesized that CHARGE syndrome could be caused by unidentified genomic microdeletion, but no such deletion was detected using short tandem repeat (STR) markers spaced an average of 5 cM apart. Recently, microdeletion at 8q12 locus was reported in two patients with CHARGE, although point mutation in  CHD7  on chromosome 8 was the underlying etiology in most of the affected patients.
Background
CHARGE syndrome is a complex of birth defects including coloboma, choanal atresia, ear malformations and deafness, cardiac defects, and growth delay. We have previously hypothesized that CHARGE syndrome could be caused by unidentified genomic microdeletion, but no such deletion was detected using short tandem repeat (STR) markers spaced an average of 5 cM apart. Recently, microdeletion at 8q12 locus was reported in two patients with CHARGE, although point mutation in  CHD7  on chromosome 8 was the underlying etiology in most of the affected patients.CHD7Methods We have extended our previous study by employing a much higher density of SNP markers (3258) with an average spacing of approximately 800 kb. These SNP markers are diallelic and, therefore, have much different properties for detection of deletions than STRs.
Methods
We have extended our previous study by employing a much higher density of SNP markers (3258) with an average spacing of approximately 800 kb. These SNP markers are diallelic and, therefore, have much different properties for detection of deletions than STRs.Results A global error rate estimate was produced based on Mendelian inconsistency. One marker, rs431722 exceeded the expected frequency of inconsistencies, but no deletion could be demonstrated after retesting the 4 inconsistent pedigrees with local flanking markers or by FISH with the corresponding BAC clone. Expected deletion detection (EDD) was used to assess the coverage of specific intervals over the genome by deriving the probability of detecting a common loss of heterozygosity event over each genomic interval. This analysis estimated the fraction of unobserved deletions, taking into account the allele frequencies at the SNPs, the known marker spacing and sample size.
Results
A global error rate estimate was produced based on Mendelian inconsistency. One marker, rs431722 exceeded the expected frequency of inconsistencies, but no deletion could be demonstrated after retesting the 4 inconsistent pedigrees with local flanking markers or by FISH with the corresponding BAC clone. Expected deletion detection (EDD) was used to assess the coverage of specific intervals over the genome by deriving the probability of detecting a common loss of heterozygosity event over each genomic interval. This analysis estimated the fraction of unobserved deletions, taking into account the allele frequencies at the SNPs, the known marker spacing and sample size.Conclusions The results of our genotyping indicate that more than 35% of the genome is included in regions with very low probability of a deletion of at least 2 Mb.
Conclusions
The results of our genotyping indicate that more than 35% of the genome is included in regions with very low probability of a deletion of at least 2 Mb.

Background CHARGE Association is characterized by ocular coloboma, cranial nerve abnormalities, common outflow tract heart defects, choanal atresia, cupped-shaped pinnae, Mondini dysplasia of the inner ear [ 1 , 2 ] and growth delay. The embryology and mechanisms of maldevelopment in CHARGE are not well understood. CHARGE Association may be genetically heterogeneous, a possibility supported by the rare and variable chromosomal aberrations observed in a few affected individuals. We have identified a  de novo  mutation in a semaphorin gene,  SEMA3E , in an affected patient, identified upon mapping the translocation breakpoints in an unrelated individual with a  de novo  balanced translocation involving chromosomes 2 and 7: karyotype 46, XY, t(2;7)(p14;q21.11) [ 3 ]. Recently, Vissers  et al . have reported mutations in  CHD7  gene, a member of the chromodomain family in a substantial number of patients [ 4 ]. In a large number of children, however, the genetic mechanism of this complex birth defect remains unidentified. Graham has suggested that a subgroup of children with CHARGE Association have a recognizable syndrome [ 5 ] and may have a common pathologic and molecular basis. We have focused our study in this subset of patients and hypothesized that within this group, there is a common chromosomal region where recombination events lead to frequent microdeletion. In a previous study we used short tandem repeat (STR) markers spaced at an average of 5 cM to examine ten CHARGE case-parent trios for a large common deletion [ 6 ]. STR markers, because they are multi-allelic, generally are highly informative in each trio and there is little ambiguity regarding Mendelian transmission of parental alleles. The study did not identify any common deletion, but it was limited because of the relatively broad marker spacing. We have now extended the analysis by genotyping 3258 diallelic SNP markers with an average spacing of approximately 800 kb, in the same nuclear families. If microdeletion is the underlying basis of this disorder, then genotyping using this dense set of SNPs would be expected to uncover loci with loss of expected heterozygosity in the probands. We have taken into account the major and minor allele frequencies of each of the 3258 SNP markers and used a metric called the expected deletion detection, EDD [Belmont  et al. , personal communication] to evaluate specific chromosomal intervals for the probability of detecting a deletion in the sample set. Although no deletion was detected in the CHARGE study sample, we conclude that this method could be generally useful in other studies in which small deletions occur as part of the allelic spectrum of disease.
Background
CHARGE Association is characterized by ocular coloboma, cranial nerve abnormalities, common outflow tract heart defects, choanal atresia, cupped-shaped pinnae, Mondini dysplasia of the inner ear [ 1 , 2 ] and growth delay. The embryology and mechanisms of maldevelopment in CHARGE are not well understood. CHARGE Association may be genetically heterogeneous, a possibility supported by the rare and variable chromosomal aberrations observed in a few affected individuals. We have identified a  de novo  mutation in a semaphorin gene,  SEMA3E , in an affected patient, identified upon mapping the translocation breakpoints in an unrelated individual with a  de novo  balanced translocation involving chromosomes 2 and 7: karyotype 46, XY, t(2;7)(p14;q21.11) [ 3 ]. Recently, Vissers  et al . have reported mutations in  CHD7  gene, a member of the chromodomain family in a substantial number of patients [ 4 ]. In a large number of children, however, the genetic mechanism of this complex birth defect remains unidentified. Graham has suggested that a subgroup of children with CHARGE Association have a recognizable syndrome [ 5 ] and may have a common pathologic and molecular basis. We have focused our study in this subset of patients and hypothesized that within this group, there is a common chromosomal region where recombination events lead to frequent microdeletion. In a previous study we used short tandem repeat (STR) markers spaced at an average of 5 cM to examine ten CHARGE case-parent trios for a large common deletion [ 6 ]. STR markers, because they are multi-allelic, generally are highly informative in each trio and there is little ambiguity regarding Mendelian transmission of parental alleles. The study did not identify any common deletion, but it was limited because of the relatively broad marker spacing. We have now extended the analysis by genotyping 3258 diallelic SNP markers with an average spacing of approximately 800 kb, in the same nuclear families. If microdeletion is the underlying basis of this disorder, then genotyping using this dense set of SNPs would be expected to uncover loci with loss of expected heterozygosity in the probands. We have taken into account the major and minor allele frequencies of each of the 3258 SNP markers and used a metric called the expected deletion detection, EDD [Belmont  et al. , personal communication] to evaluate specific chromosomal intervals for the probability of detecting a deletion in the sample set. Although no deletion was detected in the CHARGE study sample, we conclude that this method could be generally useful in other studies in which small deletions occur as part of the allelic spectrum of disease.de novoSEMA3Ede novoet alCHD7et al.Methods Patients The diagnosis of CHARGE syndrome was established by examination by a participating clinical genetics specialist (CB, JWB, SRL). A medical history questionnaire was completed by the parents or by direct interview. For the core genotyping, 8 Caucasian and 1 Hispanic case/parent trios were selected based on the presence of 4 major criteria or three major and three minor criteria for the syndrome [ 7 ]. There were five affected males and four affected females, with ages ranging from five to twenty years. Blood was collected and transformed cell lines were established for these families. This research protocol was reviewed and approved by the Baylor College of Medicine Institutional Review Board. Genotyping Genotyping for this study was carried out on an Orchid BioSciences SNPstream UHT platform (Princeton, NJ) as previously described [ 8 ]. For this study, an initial set of ~4,200 T/C SNPs were identified and selected from the public databases for incorporation into a genome wide SNP panel. After selection, the complete set of SNPs was arranged into ~350 unique 12-plex reactions for the purpose of performing the assays on the UHT platform. The complete set of markers was then validated on a set of 5 CEPH pedigrees (40 individuals) and in 3 independent populations. A final set of 3258 markers was chosen from these combined datasets for analysis after eliminating SNPs that performed poorly through all populations, SNPs that failed both Hardy-Weinberg and Mendelian error calculations and any SNPs that were not polymorphic in the evaluated populations. An average genome wide spacing of ~800 kb between markers was achieved for this panel. This genotyping method utilized Orchid's single base primer extension chemistry (SBE) to identify which bases were present at the site of interrogation. Multiplexed reactions (12-plex) were performed in a single tube that incorporated labeled chain terminating nucleotides onto the ends of the SBE oligonucleotides. These reactions were then hybridized onto a microarray format, that facilitates the solid-phase sorting of the labeled extension-primers to a set of universal tagged primers arrayed on the surface of the plate. The universal tags were arranged on the surface of the microarray plate in a 384-well microwell layout. This microarray format created a generic design consisting of 384 4 × 4 arrays that contained 12 oligonucleotides that corresponded to 12 unique universal capture tags. The four additional oligonucleotides, plotted in each array, were used for positive and negative controls. Genotyping calls were determined by the presence or absence of incorporated dyes that appeared at each spot on the printed arrays. TaqMan polymerase chain reaction Two Assays-on-demand SNPs, rs422951 and ss1309424, flanking rs431722 were obtained from Applied Biosystems and genotyping was performed in 384 well-plates, using the TaqMan polymerase chain reaction-based method. The final volume reaction was 5 μl using 12 ng of genomic DNA, 2.5 μl of Taqman Master mix and 0.25 μl of 20X Assays-on-Demand SNP Genotyping Assay Mix. The plate was heated at 95° for 10 minutes, followed by forty cycles of denaturation at 92° for 15 seconds and annealing/extension at 60° for 1 minute. PCR plates were read on ABI PRISM 7900HT instrument with SDS v2.0 software. Individual genotypes that were ambiguous were excluded. Fish Bacterial Artificial chromosomes (BACs) were selected from the public database [ 9 ] and obtained from Children's Hospital Oakland Research Institute. DNA extraction was performed according to the standard protocol. Fluorescence  in situ  hybridization was performed as described elsewhere [ 6 ]. Detection of the digoxigenin labeled probe was performed with anti-digoxigenin conjugated to rhodamine, giving a red signal. Biotin labeled control probe was detected with FITC (fluorescein isothiocyanate), giving a green signal. The chromosomes were counterstained with DAPI and analyzed with a Zeiss Axioskop fluorescence microscope equipped with appropriate filter combinations. Approximately 10 metaphase preparations were scored for each hybridization. Data analysis The genotype error rate was estimated using the method of Gordon  et al.  [ 10 ] and as implemented in CUE [ 11 ]. Expected deletion detection (EDD) is a new method designed for this study, which uses the allele frequency, the marker spacing and the number of pedigrees sampled to estimate the probability that a common deletion would be missed because of ambiguous genotype outcomes. Qualitatively, the information available in a single SNP marker for the purposes of detecting a deletion by lack of expected heterozygosity in a case-parent trio is limited by the many genotype configurations that could appear consistent with Mendelian inheritance, but actually harbor a deletion. Inclusion of 2 or more SNP markers in a deletion interval decreases the likelihood that a common deletion goes undetected.
Methods
Patients The diagnosis of CHARGE syndrome was established by examination by a participating clinical genetics specialist (CB, JWB, SRL). A medical history questionnaire was completed by the parents or by direct interview. For the core genotyping, 8 Caucasian and 1 Hispanic case/parent trios were selected based on the presence of 4 major criteria or three major and three minor criteria for the syndrome [ 7 ]. There were five affected males and four affected females, with ages ranging from five to twenty years. Blood was collected and transformed cell lines were established for these families. This research protocol was reviewed and approved by the Baylor College of Medicine Institutional Review Board.
Patients
The diagnosis of CHARGE syndrome was established by examination by a participating clinical genetics specialist (CB, JWB, SRL). A medical history questionnaire was completed by the parents or by direct interview. For the core genotyping, 8 Caucasian and 1 Hispanic case/parent trios were selected based on the presence of 4 major criteria or three major and three minor criteria for the syndrome [ 7 ]. There were five affected males and four affected females, with ages ranging from five to twenty years. Blood was collected and transformed cell lines were established for these families. This research protocol was reviewed and approved by the Baylor College of Medicine Institutional Review Board.Genotyping Genotyping for this study was carried out on an Orchid BioSciences SNPstream UHT platform (Princeton, NJ) as previously described [ 8 ]. For this study, an initial set of ~4,200 T/C SNPs were identified and selected from the public databases for incorporation into a genome wide SNP panel. After selection, the complete set of SNPs was arranged into ~350 unique 12-plex reactions for the purpose of performing the assays on the UHT platform. The complete set of markers was then validated on a set of 5 CEPH pedigrees (40 individuals) and in 3 independent populations. A final set of 3258 markers was chosen from these combined datasets for analysis after eliminating SNPs that performed poorly through all populations, SNPs that failed both Hardy-Weinberg and Mendelian error calculations and any SNPs that were not polymorphic in the evaluated populations. An average genome wide spacing of ~800 kb between markers was achieved for this panel. This genotyping method utilized Orchid's single base primer extension chemistry (SBE) to identify which bases were present at the site of interrogation. Multiplexed reactions (12-plex) were performed in a single tube that incorporated labeled chain terminating nucleotides onto the ends of the SBE oligonucleotides. These reactions were then hybridized onto a microarray format, that facilitates the solid-phase sorting of the labeled extension-primers to a set of universal tagged primers arrayed on the surface of the plate. The universal tags were arranged on the surface of the microarray plate in a 384-well microwell layout. This microarray format created a generic design consisting of 384 4 × 4 arrays that contained 12 oligonucleotides that corresponded to 12 unique universal capture tags. The four additional oligonucleotides, plotted in each array, were used for positive and negative controls. Genotyping calls were determined by the presence or absence of incorporated dyes that appeared at each spot on the printed arrays.
Genotyping
Genotyping for this study was carried out on an Orchid BioSciences SNPstream UHT platform (Princeton, NJ) as previously described [ 8 ]. For this study, an initial set of ~4,200 T/C SNPs were identified and selected from the public databases for incorporation into a genome wide SNP panel. After selection, the complete set of SNPs was arranged into ~350 unique 12-plex reactions for the purpose of performing the assays on the UHT platform. The complete set of markers was then validated on a set of 5 CEPH pedigrees (40 individuals) and in 3 independent populations. A final set of 3258 markers was chosen from these combined datasets for analysis after eliminating SNPs that performed poorly through all populations, SNPs that failed both Hardy-Weinberg and Mendelian error calculations and any SNPs that were not polymorphic in the evaluated populations. An average genome wide spacing of ~800 kb between markers was achieved for this panel.This genotyping method utilized Orchid's single base primer extension chemistry (SBE) to identify which bases were present at the site of interrogation. Multiplexed reactions (12-plex) were performed in a single tube that incorporated labeled chain terminating nucleotides onto the ends of the SBE oligonucleotides. These reactions were then hybridized onto a microarray format, that facilitates the solid-phase sorting of the labeled extension-primers to a set of universal tagged primers arrayed on the surface of the plate. The universal tags were arranged on the surface of the microarray plate in a 384-well microwell layout. This microarray format created a generic design consisting of 384 4 × 4 arrays that contained 12 oligonucleotides that corresponded to 12 unique universal capture tags. The four additional oligonucleotides, plotted in each array, were used for positive and negative controls. Genotyping calls were determined by the presence or absence of incorporated dyes that appeared at each spot on the printed arrays.TaqMan polymerase chain reaction Two Assays-on-demand SNPs, rs422951 and ss1309424, flanking rs431722 were obtained from Applied Biosystems and genotyping was performed in 384 well-plates, using the TaqMan polymerase chain reaction-based method. The final volume reaction was 5 μl using 12 ng of genomic DNA, 2.5 μl of Taqman Master mix and 0.25 μl of 20X Assays-on-Demand SNP Genotyping Assay Mix. The plate was heated at 95° for 10 minutes, followed by forty cycles of denaturation at 92° for 15 seconds and annealing/extension at 60° for 1 minute. PCR plates were read on ABI PRISM 7900HT instrument with SDS v2.0 software. Individual genotypes that were ambiguous were excluded.
TaqMan polymerase chain reaction
Two Assays-on-demand SNPs, rs422951 and ss1309424, flanking rs431722 were obtained from Applied Biosystems and genotyping was performed in 384 well-plates, using the TaqMan polymerase chain reaction-based method. The final volume reaction was 5 μl using 12 ng of genomic DNA, 2.5 μl of Taqman Master mix and 0.25 μl of 20X Assays-on-Demand SNP Genotyping Assay Mix. The plate was heated at 95° for 10 minutes, followed by forty cycles of denaturation at 92° for 15 seconds and annealing/extension at 60° for 1 minute. PCR plates were read on ABI PRISM 7900HT instrument with SDS v2.0 software. Individual genotypes that were ambiguous were excluded.Fish Bacterial Artificial chromosomes (BACs) were selected from the public database [ 9 ] and obtained from Children's Hospital Oakland Research Institute. DNA extraction was performed according to the standard protocol. Fluorescence  in situ  hybridization was performed as described elsewhere [ 6 ]. Detection of the digoxigenin labeled probe was performed with anti-digoxigenin conjugated to rhodamine, giving a red signal. Biotin labeled control probe was detected with FITC (fluorescein isothiocyanate), giving a green signal. The chromosomes were counterstained with DAPI and analyzed with a Zeiss Axioskop fluorescence microscope equipped with appropriate filter combinations. Approximately 10 metaphase preparations were scored for each hybridization.
Fish
Bacterial Artificial chromosomes (BACs) were selected from the public database [ 9 ] and obtained from Children's Hospital Oakland Research Institute. DNA extraction was performed according to the standard protocol. Fluorescence  in situ  hybridization was performed as described elsewhere [ 6 ]. Detection of the digoxigenin labeled probe was performed with anti-digoxigenin conjugated to rhodamine, giving a red signal. Biotin labeled control probe was detected with FITC (fluorescein isothiocyanate), giving a green signal. The chromosomes were counterstained with DAPI and analyzed with a Zeiss Axioskop fluorescence microscope equipped with appropriate filter combinations. Approximately 10 metaphase preparations were scored for each hybridization.in situData analysis The genotype error rate was estimated using the method of Gordon  et al.  [ 10 ] and as implemented in CUE [ 11 ]. Expected deletion detection (EDD) is a new method designed for this study, which uses the allele frequency, the marker spacing and the number of pedigrees sampled to estimate the probability that a common deletion would be missed because of ambiguous genotype outcomes. Qualitatively, the information available in a single SNP marker for the purposes of detecting a deletion by lack of expected heterozygosity in a case-parent trio is limited by the many genotype configurations that could appear consistent with Mendelian inheritance, but actually harbor a deletion. Inclusion of 2 or more SNP markers in a deletion interval decreases the likelihood that a common deletion goes undetected.
Data analysis
The genotype error rate was estimated using the method of Gordon  et al.  [ 10 ] and as implemented in CUE [ 11 ]. Expected deletion detection (EDD) is a new method designed for this study, which uses the allele frequency, the marker spacing and the number of pedigrees sampled to estimate the probability that a common deletion would be missed because of ambiguous genotype outcomes. Qualitatively, the information available in a single SNP marker for the purposes of detecting a deletion by lack of expected heterozygosity in a case-parent trio is limited by the many genotype configurations that could appear consistent with Mendelian inheritance, but actually harbor a deletion. Inclusion of 2 or more SNP markers in a deletion interval decreases the likelihood that a common deletion goes undetected.et al.Results SNP genotyping data were subjected to analysis for Hardy-Weinberg equilibrium. As an additional test of marker integrity, a transmission disequilibrium test was also performed for each of the SNP markers to examine for distortions in allele transmission in the trios. Unequal transmission of alleles from the heterozygote parents to the affected offspring was not determined by this analysis. Non-paternity was excluded in core pedigrees. Using the method of Gordon [ 12 ], we used the genotyping data to estimate the genotyping error rate at 0.02%. Analysis of the data showed transmission inconsistent with Mendelian inheritance for 22 markers on different chromosomes (20 with 1 inconsistency, 1 with 2 inconsistencies, and 1 with 4 inconsistencies). Given the underlying genotyping error rate, we could predict that markers with >2 inconsistencies would be highly unlikely to occur. One marker, rs431722 with overall call rate of 95%, showed Mendelian inconsistency in 4 trios. This SNP was found to lie within the intron 2 of the  NOTCH4  gene on chromosome 6p21.32. Human DNA sequence from clone XXbac-300A18 (GenBank accession number AL662884) on chromosome 6p21 was used for FISH. This BAC clone encompasses the  NOTCH4  gene, and was confirmed by PCR amplification of the clone sequence using  NOTCH4  specific primers (data not shown). The analysis of the metaphase chromosomes after staining with DAPI showed two bright hybridization signals, indicating the presence of both alleles (Figure  1 ). Two additional SNPs, rs422951 and ss1309424, flanking rs431722 within 780 bp, were genotyped using TaqMan chemistry. The results showed inheritance of biparental alleles in all four pedigrees. The  CHD7  locus on 8q12 was investigated additionally with FISH using RP11-33I11 (GenBank accession number AC113143) and RP11-414L17 (GenBank accession number AC023102). Using these BAC clones, microdeletion of this region was excluded in all the affected patients in this study sample. Because none of the pedigrees were consanguineous, we used parental data to estimate the allele frequencies for each of the 3258 SNP markers [ 13 ]. The EDD was then calculated for each chromosome. The percent coverage ranged from 51% on chromosome 20 to 20% on chromosome 15, with a mean of 36% for an autosomal deletion of 2 Mb (Figure  2 ).
Results
SNP genotyping data were subjected to analysis for Hardy-Weinberg equilibrium. As an additional test of marker integrity, a transmission disequilibrium test was also performed for each of the SNP markers to examine for distortions in allele transmission in the trios. Unequal transmission of alleles from the heterozygote parents to the affected offspring was not determined by this analysis. Non-paternity was excluded in core pedigrees. Using the method of Gordon [ 12 ], we used the genotyping data to estimate the genotyping error rate at 0.02%. Analysis of the data showed transmission inconsistent with Mendelian inheritance for 22 markers on different chromosomes (20 with 1 inconsistency, 1 with 2 inconsistencies, and 1 with 4 inconsistencies). Given the underlying genotyping error rate, we could predict that markers with >2 inconsistencies would be highly unlikely to occur. One marker, rs431722 with overall call rate of 95%, showed Mendelian inconsistency in 4 trios. This SNP was found to lie within the intron 2 of the  NOTCH4  gene on chromosome 6p21.32. Human DNA sequence from clone XXbac-300A18 (GenBank accession number AL662884) on chromosome 6p21 was used for FISH. This BAC clone encompasses the  NOTCH4  gene, and was confirmed by PCR amplification of the clone sequence using  NOTCH4  specific primers (data not shown). The analysis of the metaphase chromosomes after staining with DAPI showed two bright hybridization signals, indicating the presence of both alleles (Figure  1 ). Two additional SNPs, rs422951 and ss1309424, flanking rs431722 within 780 bp, were genotyped using TaqMan chemistry. The results showed inheritance of biparental alleles in all four pedigrees. The  CHD7  locus on 8q12 was investigated additionally with FISH using RP11-33I11 (GenBank accession number AC113143) and RP11-414L17 (GenBank accession number AC023102). Using these BAC clones, microdeletion of this region was excluded in all the affected patients in this study sample.NOTCH4NOTCH4NOTCH4CHD7Because none of the pedigrees were consanguineous, we used parental data to estimate the allele frequencies for each of the 3258 SNP markers [ 13 ]. The EDD was then calculated for each chromosome. The percent coverage ranged from 51% on chromosome 20 to 20% on chromosome 15, with a mean of 36% for an autosomal deletion of 2 Mb (Figure  2 ).Discussion Despite various efforts to understand the molecular basis of CHARGE syndrome, with candidate genes sequencing [ 14 , 15 ], comparative genomic hybridization [ 16 ], and genome-wide scan for microdeletion(s) using microsatellite markers [ 6 ], the underlying molecular mechanism in many patients remained unknown until recently [ 4 ]. Based on the complex phenotype and clinical overlap with Velocardiofacial syndrome, it is a plausible hypothesis that in a subset of CHARGE patients with a homogenous phenotype, the underlying genetic mechanism is a cryptic submicroscopic deletion involving highly pleiotropic gene(s). To address this hypothesis, we had previously used microsatellite markers to ascertain loci with loss of expected heterozygosity in case-parent trios. SNPs are far more abundant than microsatellite markers but have not yet been used extensively in linkage and loss of heterozygosity (LOH) studies. The present study represents the application of SNPs to scan for potential submicroscopic deletions across the autosomes. Amos  et al.  have previously shown that SNP genotyping of child-parent trios provides valuable information about the presence of  de novo  microdeletion when sufficient families are studied [ 17 ]. However, this method is most appropriate when linkage disequilibrium is accounted for because of high SNP marker density. They have provided a general analytical framework and point out the effects of non-paternity, sample mix-up, and genotyping error in the interpretation of Mendelian inconsistency in case-parent trio data with biallelic markers. As expected, increases in rates of such phenomenon in the data decrease power to detect a microdeletion. In addition, they point out that heterogeneity in the position of a putative deletion also has a large impact on power. Their analysis is particularly apt given the probable future availability of extremely high density SNP marker maps and the technical capability to genotype hundreds of thousands of markers per research subject. However, they do not explore the effect of intermarker distance in the ability to detect deletions of various sizes. Assuming the genotyping error rate of 0.5%, the probability of observing >2 inconsistencies per marker is very low. The SNP marker rs431722 showed Mendelian inconsistency in four of nine pedigrees, with apparent loss of a parental allele in each case i.e. a frequency much higher than expected for the genotyping error rate. Interestingly, this SNP is located within the  NOTCH4  gene on chromosome 6p21.32. The Notch gene family encodes highly conserved transmembrane receptors that are involved in intercellular signaling. The Notch signaling pathway plays an essential role in regulating embryonic vascular morphogenesis and remodeling [ 18 ]. Moreover, disruption of Notch signaling via mutation in the Notch ligand  JAG1  is known to result in Alagille syndrome [ 19 ], nonsyndromic Tetralogy of Fallot (TOF) [ 20 ] and possibly nonsyndromic biliary extrahepatic atresia [ 21 ]. Since TOF is a heart defect commonly seen in CHARGE Syndrome,  NOTCH4  was further studied with FISH as well as flanking SNP markers for microdeletion. The results, however conclusively excluded a discernible microdeletion at this locus. This screen is expected to detect deletions of about 1–2 Mb depending on the overlap of the SNP markers with the deletion interval. Variable coverage for each chromosome was determined for approximately 2 Mb microdeletion in this study. Almost 50% of chromosomes 7, 19 and 20 were excluded for any microdeletion greater than 2 Mb. The least coverage was observed for chromosome 15 and 18, with exclusion of 20% of the chromosome for the presence of a similar genetic aberration. Overall, we can estimate that approximately 36% of the genome had >80% chance for detecting a common 2 Mb deletion in at least 2 patients with CHARGE Syndrome. There are several limitations to this approach in studying the genetics of CHARGE syndrome. Although the marker density is high, the reduced amount of information per marker means that only some of the trios give the possibility of a conclusive result. Denser marker sets would be predicted to fill most of the gaps, but the regions around the centromeres are likely to be difficult with any currently available technique. The strategy out lined in this paper would work equally well for conventional Mendelian traits in which the mutant alleles included at least some deletions. Using a much denser SNP map of 1 marker every 5–10 kb, as is anticipated for whole genome association analyses, it would be possible to detect most deletions given a sufficient representation of deletions within the spectrum of gene mutations.
Discussion
Despite various efforts to understand the molecular basis of CHARGE syndrome, with candidate genes sequencing [ 14 , 15 ], comparative genomic hybridization [ 16 ], and genome-wide scan for microdeletion(s) using microsatellite markers [ 6 ], the underlying molecular mechanism in many patients remained unknown until recently [ 4 ]. Based on the complex phenotype and clinical overlap with Velocardiofacial syndrome, it is a plausible hypothesis that in a subset of CHARGE patients with a homogenous phenotype, the underlying genetic mechanism is a cryptic submicroscopic deletion involving highly pleiotropic gene(s). To address this hypothesis, we had previously used microsatellite markers to ascertain loci with loss of expected heterozygosity in case-parent trios. SNPs are far more abundant than microsatellite markers but have not yet been used extensively in linkage and loss of heterozygosity (LOH) studies. The present study represents the application of SNPs to scan for potential submicroscopic deletions across the autosomes. Amos  et al.  have previously shown that SNP genotyping of child-parent trios provides valuable information about the presence of  de novo  microdeletion when sufficient families are studied [ 17 ]. However, this method is most appropriate when linkage disequilibrium is accounted for because of high SNP marker density. They have provided a general analytical framework and point out the effects of non-paternity, sample mix-up, and genotyping error in the interpretation of Mendelian inconsistency in case-parent trio data with biallelic markers. As expected, increases in rates of such phenomenon in the data decrease power to detect a microdeletion. In addition, they point out that heterogeneity in the position of a putative deletion also has a large impact on power. Their analysis is particularly apt given the probable future availability of extremely high density SNP marker maps and the technical capability to genotype hundreds of thousands of markers per research subject. However, they do not explore the effect of intermarker distance in the ability to detect deletions of various sizes.et al.de novoAssuming the genotyping error rate of 0.5%, the probability of observing >2 inconsistencies per marker is very low. The SNP marker rs431722 showed Mendelian inconsistency in four of nine pedigrees, with apparent loss of a parental allele in each case i.e. a frequency much higher than expected for the genotyping error rate. Interestingly, this SNP is located within the  NOTCH4  gene on chromosome 6p21.32. The Notch gene family encodes highly conserved transmembrane receptors that are involved in intercellular signaling. The Notch signaling pathway plays an essential role in regulating embryonic vascular morphogenesis and remodeling [ 18 ]. Moreover, disruption of Notch signaling via mutation in the Notch ligand  JAG1  is known to result in Alagille syndrome [ 19 ], nonsyndromic Tetralogy of Fallot (TOF) [ 20 ] and possibly nonsyndromic biliary extrahepatic atresia [ 21 ]. Since TOF is a heart defect commonly seen in CHARGE Syndrome,  NOTCH4  was further studied with FISH as well as flanking SNP markers for microdeletion. The results, however conclusively excluded a discernible microdeletion at this locus.NOTCH4JAG1NOTCH4This screen is expected to detect deletions of about 1–2 Mb depending on the overlap of the SNP markers with the deletion interval. Variable coverage for each chromosome was determined for approximately 2 Mb microdeletion in this study. Almost 50% of chromosomes 7, 19 and 20 were excluded for any microdeletion greater than 2 Mb. The least coverage was observed for chromosome 15 and 18, with exclusion of 20% of the chromosome for the presence of a similar genetic aberration. Overall, we can estimate that approximately 36% of the genome had >80% chance for detecting a common 2 Mb deletion in at least 2 patients with CHARGE Syndrome.There are several limitations to this approach in studying the genetics of CHARGE syndrome. Although the marker density is high, the reduced amount of information per marker means that only some of the trios give the possibility of a conclusive result. Denser marker sets would be predicted to fill most of the gaps, but the regions around the centromeres are likely to be difficult with any currently available technique.The strategy out lined in this paper would work equally well for conventional Mendelian traits in which the mutant alleles included at least some deletions. Using a much denser SNP map of 1 marker every 5–10 kb, as is anticipated for whole genome association analyses, it would be possible to detect most deletions given a sufficient representation of deletions within the spectrum of gene mutations.Conclusions In this report we show that a SNP genotyping screen has excluded moderate length submicroscopic deletions in a subset of patients with CHARGE syndrome. Further analysis by microarray comparative genome hybridization methods or denser SNPs will allow a comprehensive assessment of the role, if any, of microdeletions in CHARGE syndrome.
Conclusions
In this report we show that a SNP genotyping screen has excluded moderate length submicroscopic deletions in a subset of patients with CHARGE syndrome. Further analysis by microarray comparative genome hybridization methods or denser SNPs will allow a comprehensive assessment of the role, if any, of microdeletions in CHARGE syndrome.Competing interests The author(s) declare that they have no competing interests.
Competing interests
The author(s) declare that they have no competing interests.Authors' contributions SRL carried out the data analysis, FISH and TaqMan assays and drafted the manuscript. AMS assisted in the data analysis. MP carried out the SNP genotyping, JWB conceived of the study, and participated in its design and coordination. He performed the statistical analysis and drafted the manuscript. SDF, CAB, and NLG participated in patient enrollment and LMM assisted in DNA extraction. WJC and JAT assisted in manuscript preparation. All authors read and approved the final manuscript.
Authors' contributions
SRL carried out the data analysis, FISH and TaqMan assays and drafted the manuscript. AMS assisted in the data analysis. MP carried out the SNP genotyping, JWB conceived of the study, and participated in its design and coordination. He performed the statistical analysis and drafted the manuscript. SDF, CAB, and NLG participated in patient enrollment and LMM assisted in DNA extraction. WJC and JAT assisted in manuscript preparation. All authors read and approved the final manuscript.Pre-publication history The pre-publication history for this paper can be accessed here:
Pre-publication history
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Background The diphtheria toxin repressor, DtxR, of  Corynebacterium diphtheriae  has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of  Corynebacterium diphtheriae .
Background
The diphtheria toxin repressor, DtxR, of  Corynebacterium diphtheriae  has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of  Corynebacterium diphtheriae .Corynebacterium diphtheriaeCorynebacterium diphtheriaeResult Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within  C. diphtheriae  genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG), an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps) which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin.
Result
Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within  C. diphtheriae  genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG), an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps) which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin.C. diphtheriaeConclusions We have used an  in silico  approach to identify the putative binding sites and genes controlled by DtxR in  Corynebacterium diphtheriae . Our analysis shows that DtxR could provide a molecular link between Fe +2 -induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe +2  and H 2 O 2  and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase, a potential vaccine candidate and proteins of secretory system.
Conclusions
We have used an  in silico  approach to identify the putative binding sites and genes controlled by DtxR in  Corynebacterium diphtheriae . Our analysis shows that DtxR could provide a molecular link between Fe +2 -induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe +2  and H 2 O 2  and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase, a potential vaccine candidate and proteins of secretory system.in silicoCorynebacterium diphtheriae

Background Iron is an important inorganic component of a cell. Iron is required as co-factor for various essential enzymes and proteins some of which are involved in electron transport (Cytochromes), redox reactions (oxidoreductases) and regulation of gene expression (fumarate-nitrate reduction regulatory protein, iron-binding protein) [ 1 ]. However a higher level of intracellular iron can catalyze formation of hydroxyl radicals and reactive oxygen species through Fenton's reaction which could be lethal to the cell [ 2 ]. Hence, a careful regulation of iron-requiring enzymes/proteins and iron uptake proteins/enzymes is required for the survival of bacteria. Inorganic iron is also known to influence virulence in many pathogenic bacteria such as  Corynebacterium diphtheriae ,  Escherichia coli , and  Bordetella bronchiseptica  [ 3 - 5 ]. The diphtheria toxin repressor DtxR is known as an iron-activated global transcription regulator that represses the transcription of various iron-dependent genes in  C. diphtheriae  [ 6 , 7 ]. Eight DtxR-binding sites in upstream sequences of operons/genes named as  tox, hmuO, irp1, irp2, irp3, irp4, irp5 and irp6  have been identified by DNA footprinting methods [ 6 ]. The product of  tox  gene is diphtheria toxin which catalyzes the NAD-dependent ADP ribosylation of eukaryotic aminoacyl-transferase-II, thereby causing inhibition of protein synthesis and subsequent death of the host. The  hmuO  gene, which encodes a haem oxygenase, oxidizes the haem to release free iron. The operons  irp1  and  irp6  encode the products with homology to ABC-type ferric-siderophore transport systems. The gene  irp3  encodes a homologue of AraC-type transcriptional activators. The products of  irp2, irp4 and irp5  do not show any homology to the other known proteins. In addition,  C. diphtheriae  with inactive DtxR has been shown to be sensitive to killing by exposure to high iron conditions or hydrogen peroxide than the wild type [ 8 ]. This work uses an  in silico  method to identify additional DtxR-binding sites and target genes to understand the role of DtxR in virulence and patho-physiology of  C. diphtheriae .
Background
Iron is an important inorganic component of a cell. Iron is required as co-factor for various essential enzymes and proteins some of which are involved in electron transport (Cytochromes), redox reactions (oxidoreductases) and regulation of gene expression (fumarate-nitrate reduction regulatory protein, iron-binding protein) [ 1 ]. However a higher level of intracellular iron can catalyze formation of hydroxyl radicals and reactive oxygen species through Fenton's reaction which could be lethal to the cell [ 2 ]. Hence, a careful regulation of iron-requiring enzymes/proteins and iron uptake proteins/enzymes is required for the survival of bacteria.Inorganic iron is also known to influence virulence in many pathogenic bacteria such as  Corynebacterium diphtheriae ,  Escherichia coli , and  Bordetella bronchiseptica  [ 3 - 5 ]. The diphtheria toxin repressor DtxR is known as an iron-activated global transcription regulator that represses the transcription of various iron-dependent genes in  C. diphtheriae  [ 6 , 7 ]. Eight DtxR-binding sites in upstream sequences of operons/genes named as  tox, hmuO, irp1, irp2, irp3, irp4, irp5 and irp6  have been identified by DNA footprinting methods [ 6 ]. The product of  tox  gene is diphtheria toxin which catalyzes the NAD-dependent ADP ribosylation of eukaryotic aminoacyl-transferase-II, thereby causing inhibition of protein synthesis and subsequent death of the host. The  hmuO  gene, which encodes a haem oxygenase, oxidizes the haem to release free iron. The operons  irp1  and  irp6  encode the products with homology to ABC-type ferric-siderophore transport systems. The gene  irp3  encodes a homologue of AraC-type transcriptional activators. The products of  irp2, irp4 and irp5  do not show any homology to the other known proteins. In addition,  C. diphtheriae  with inactive DtxR has been shown to be sensitive to killing by exposure to high iron conditions or hydrogen peroxide than the wild type [ 8 ].Corynebacterium diphtheriaeEscherichia coliBordetella bronchisepticaC. diphtheriaetox, hmuO, irp1, irp2, irp3, irp4, irp5 and irp6toxhmuOirp1irp6irp3irp2, irp4 and irp5C. diphtheriaeThis work uses an  in silico  method to identify additional DtxR-binding sites and target genes to understand the role of DtxR in virulence and patho-physiology of  C. diphtheriae .in silicoC. diphtheriaeResults In silico  identification of putative DtxR-binding sites Experimentally characterized DtxR-binding motifs were collected from the literature (Table  1 ). These binding sites were used to identify additional putative DtxR-binding sites along with associated operons in C.  diphtheriae  NCTC13129 genome (see materials and methods). Table  2  shows the predicted DtxR-binding sites with score 3.7438 or more. We could identify five (tox, irp4, irp5, irp6 and hmuO) of the eight known DtxR-binding sites, in sequenced  C. diphtheriae  NCTC13129 genome. We could not find irp1 and irp2 motifs as the corresponding genes ( irp1, irp2 ) are not present in the sequenced strain NCTC13129 [ 9 ]. The regulator binding sites of  irp3 ,  irp4  and  irp6  genes in the strain NCTC13129 shows one base change from the binding sites reported in strain C7 [ 6 ]. Binding site of  irp3  gene (TTAGGTGAGACGCACCCAT) although exists in strain NCTC13129, but not there in the predicted sites, because it is located within the coding region of  irp3  ORF. The predicted ORF of  irp3  in the sequenced strain NCTC13129 has different start position and is larger than what was previously reported in strain C7 [ 9 , 10 ]. In addition, we have identified binding sites in upstream sequences of eight genes recently reported to be regulated by DtxR [ 7 ]. However, our prediction differs from the previous report for five (secY, deoR, chtA, frgA, sidA) of the seven sites which were identified by BLAST search (Table  2 ). Our prediction agreed with the previous report that the genes such as  recA  (DIP1450) and  ywjA  (DIP1735) are not under a direct DtxR regulation as we could not detect any motif upstream to these gene with scores above the cutoff value [ 7 ]. Experimental validation of predicted binding sites Since our approach to identify DtxR-regulated genes is purely computational in nature, we decided to test the validity of our predictions. A sample of predicted regulator binding motifs (Table  2 ) (upstream to ORFs: DIP2161, DIP0699, DIP0586, DIP2304, DIP2272) were experimentally verified by EMSA using IdeR, an orthologue of DtxR from  M. tuberculosis . DtxR and IdeR are iron-dependent regulators. A pair wise sequence comparison of the two proteins shows a high (58%) overall sequence identity (similarity 72%) which increases further to 92% identity and 100% similarity in DNA recognition domain. In addition, the structural comparison of two regulators also shows a very similar 3D organization, suggesting that the IdeR regulator would be able to recognize the DtxR motif [ 11 ]. Synthetic double stranded oligonucleotides corresponding to DNA-binding sites were labeled with  32 P and mixed with purified IdeR in presence of manganese ions and was assayed for the formation of DNA-protein complex using EMSA. Manganese was used as the divalent metal in the binding reactions on account of its redox stability compared with ferrous ion. Electrophoretic mobility of all five double stranded oligonucleotides tested was retarded by IdeR (Figure  1 ). However a synthetic motif (TTTTCATGACGTCTTCTAA) used as a negative control did not show any complex formation. These results indicate that the predicted DtxR-binding sites can indeed bind to DtxR. Identification and annotation of DtxR-regulated genes  C. diphtheriae genome In addition to the binding site prediction, we have also identified co-regulated genes (operons) downstream to the predicted DtxR-binding site (Table  3 ). Function of the proteins encoded by the putative genes in Table  2  and Table  3  was predicted by RPS-BLAST search against conserved domain database [ 12 ].
Results
In silico  identification of putative DtxR-binding sites Experimentally characterized DtxR-binding motifs were collected from the literature (Table  1 ). These binding sites were used to identify additional putative DtxR-binding sites along with associated operons in C.  diphtheriae  NCTC13129 genome (see materials and methods). Table  2  shows the predicted DtxR-binding sites with score 3.7438 or more. We could identify five (tox, irp4, irp5, irp6 and hmuO) of the eight known DtxR-binding sites, in sequenced  C. diphtheriae  NCTC13129 genome. We could not find irp1 and irp2 motifs as the corresponding genes ( irp1, irp2 ) are not present in the sequenced strain NCTC13129 [ 9 ]. The regulator binding sites of  irp3 ,  irp4  and  irp6  genes in the strain NCTC13129 shows one base change from the binding sites reported in strain C7 [ 6 ]. Binding site of  irp3  gene (TTAGGTGAGACGCACCCAT) although exists in strain NCTC13129, but not there in the predicted sites, because it is located within the coding region of  irp3  ORF. The predicted ORF of  irp3  in the sequenced strain NCTC13129 has different start position and is larger than what was previously reported in strain C7 [ 9 , 10 ]. In addition, we have identified binding sites in upstream sequences of eight genes recently reported to be regulated by DtxR [ 7 ]. However, our prediction differs from the previous report for five (secY, deoR, chtA, frgA, sidA) of the seven sites which were identified by BLAST search (Table  2 ). Our prediction agreed with the previous report that the genes such as  recA  (DIP1450) and  ywjA  (DIP1735) are not under a direct DtxR regulation as we could not detect any motif upstream to these gene with scores above the cutoff value [ 7 ].
In silico  identification of putative DtxR-binding sites
In silicoExperimentally characterized DtxR-binding motifs were collected from the literature (Table  1 ). These binding sites were used to identify additional putative DtxR-binding sites along with associated operons in C.  diphtheriae  NCTC13129 genome (see materials and methods). Table  2  shows the predicted DtxR-binding sites with score 3.7438 or more. We could identify five (tox, irp4, irp5, irp6 and hmuO) of the eight known DtxR-binding sites, in sequenced  C. diphtheriae  NCTC13129 genome. We could not find irp1 and irp2 motifs as the corresponding genes ( irp1, irp2 ) are not present in the sequenced strain NCTC13129 [ 9 ]. The regulator binding sites of  irp3 ,  irp4  and  irp6  genes in the strain NCTC13129 shows one base change from the binding sites reported in strain C7 [ 6 ]. Binding site of  irp3  gene (TTAGGTGAGACGCACCCAT) although exists in strain NCTC13129, but not there in the predicted sites, because it is located within the coding region of  irp3  ORF. The predicted ORF of  irp3  in the sequenced strain NCTC13129 has different start position and is larger than what was previously reported in strain C7 [ 9 , 10 ].diphtheriaeC. diphtheriaeirp1, irp2irp3irp4irp6irp3irp3irp3In addition, we have identified binding sites in upstream sequences of eight genes recently reported to be regulated by DtxR [ 7 ]. However, our prediction differs from the previous report for five (secY, deoR, chtA, frgA, sidA) of the seven sites which were identified by BLAST search (Table  2 ). Our prediction agreed with the previous report that the genes such as  recA  (DIP1450) and  ywjA  (DIP1735) are not under a direct DtxR regulation as we could not detect any motif upstream to these gene with scores above the cutoff value [ 7 ].recAywjAExperimental validation of predicted binding sites Since our approach to identify DtxR-regulated genes is purely computational in nature, we decided to test the validity of our predictions. A sample of predicted regulator binding motifs (Table  2 ) (upstream to ORFs: DIP2161, DIP0699, DIP0586, DIP2304, DIP2272) were experimentally verified by EMSA using IdeR, an orthologue of DtxR from  M. tuberculosis . DtxR and IdeR are iron-dependent regulators. A pair wise sequence comparison of the two proteins shows a high (58%) overall sequence identity (similarity 72%) which increases further to 92% identity and 100% similarity in DNA recognition domain. In addition, the structural comparison of two regulators also shows a very similar 3D organization, suggesting that the IdeR regulator would be able to recognize the DtxR motif [ 11 ]. Synthetic double stranded oligonucleotides corresponding to DNA-binding sites were labeled with  32 P and mixed with purified IdeR in presence of manganese ions and was assayed for the formation of DNA-protein complex using EMSA. Manganese was used as the divalent metal in the binding reactions on account of its redox stability compared with ferrous ion. Electrophoretic mobility of all five double stranded oligonucleotides tested was retarded by IdeR (Figure  1 ). However a synthetic motif (TTTTCATGACGTCTTCTAA) used as a negative control did not show any complex formation. These results indicate that the predicted DtxR-binding sites can indeed bind to DtxR.
Experimental validation of predicted binding sites
Since our approach to identify DtxR-regulated genes is purely computational in nature, we decided to test the validity of our predictions. A sample of predicted regulator binding motifs (Table  2 ) (upstream to ORFs: DIP2161, DIP0699, DIP0586, DIP2304, DIP2272) were experimentally verified by EMSA using IdeR, an orthologue of DtxR from  M. tuberculosis . DtxR and IdeR are iron-dependent regulators. A pair wise sequence comparison of the two proteins shows a high (58%) overall sequence identity (similarity 72%) which increases further to 92% identity and 100% similarity in DNA recognition domain. In addition, the structural comparison of two regulators also shows a very similar 3D organization, suggesting that the IdeR regulator would be able to recognize the DtxR motif [ 11 ].M. tuberculosisSynthetic double stranded oligonucleotides corresponding to DNA-binding sites were labeled with  32 P and mixed with purified IdeR in presence of manganese ions and was assayed for the formation of DNA-protein complex using EMSA. Manganese was used as the divalent metal in the binding reactions on account of its redox stability compared with ferrous ion. Electrophoretic mobility of all five double stranded oligonucleotides tested was retarded by IdeR (Figure  1 ). However a synthetic motif (TTTTCATGACGTCTTCTAA) used as a negative control did not show any complex formation. These results indicate that the predicted DtxR-binding sites can indeed bind to DtxR.Identification and annotation of DtxR-regulated genes  C. diphtheriae genome In addition to the binding site prediction, we have also identified co-regulated genes (operons) downstream to the predicted DtxR-binding site (Table  3 ). Function of the proteins encoded by the putative genes in Table  2  and Table  3  was predicted by RPS-BLAST search against conserved domain database [ 12 ].
Identification and annotation of DtxR-regulated genes  C. diphtheriae genome
C. diphtheriae genomeIn addition to the binding site prediction, we have also identified co-regulated genes (operons) downstream to the predicted DtxR-binding site (Table  3 ). Function of the proteins encoded by the putative genes in Table  2  and Table  3  was predicted by RPS-BLAST search against conserved domain database [ 12 ].Discussion Our analysis identified putative DtxR motifs upstream to various operons/genes which could be involved in siderophore biosynthesis, ABC-type transport systems, iron storage, oxidative stress defense and iron-sulfur cluster biosynthesis. In addition, we have also identified the motifs upstream of operons that could be involved in anchoring of host-interacting proteins to the cell wall and secretion of various virulence factors. Important functions of some of these DtxR-regulated genes and their role in  C. diphtheriae  physiology are discussed here. Regulation of siderophore biosynthesis and ABC-type transport systems Predicted member of the DtxR regulon, the gene DIP0586, codes for the IucA/IucC family of enzymes that catalyze discrete step in the biosynthesis of the aerobactin [ 13 ]. In addition to known DtxR-regulated siderophore transport genes (irp1, irp6), DtxR could also regulate other ABC-type transport systems similar to Manganese/Zinc, peptide/Nickel and multidrug subfamilies of ABC transporters. The peptide/nickel transport system (DIP2162-DIP2165) has been suggested to be recently acquired by pathogenic  C. diphtheriae  [ 9 ]. Regulation of iron storage and oxidative stress defense We predict that DtxR could regulate divergently transcribed genes DIP2303 and DIP2304 whose products are similar to starvation inducible DNA-binding protein (Dps) and Formamidopyrimidine-DNA glycosylase (Fpg), respectively. Dps in  Escherichia coli  is induced in response to oxidative or nutritional stress and protects DNA from oxidative stress damage by nonspecific binding [ 14 ]. Dps also catalyzes oxidation of ferrous iron to ferric iron by hydrogen peroxide (2Fe 2+  + H 2 O 2  + 2H 2 O → 2Fe +3 OOH (core)  + 4H + ) which in turn prevents hydroxyl radical formation by Fenton's reaction (Fe 2+  + H 2 O 2  → Fe +3  + HO -  + HO . ) and thereby prevents subsequent DNA damage [ 15 ]. The enzyme, formamidopyrimidine-DNA glycosylase is a primary participant in the repair of 8-oxoguanine, an abundant oxidative DNA lesion [ 16 ]. The gene DIP1510 which codes for the site-specific recombinase XerD could also be regulated by DtxR. The  xerD  gene in  E. coli  belongs to the oxidative stress regulon [ 17 ]. Regulation of proteins involved in iron-sulfur cluster biosynthesis and iron-sulfur cluster containing proteins We predict that the operon DIP1288-DIP1296, which is similar to the  suf  operon of  E. coli , could be regulated by DtxR. The  suf  operon in bacteria encodes the genes for Fe-S cluster assembly machinery [ 18 ]. In addition, genes encoding the iron-sulfur containing proteins such as succinate dehydrogenase (Sdh), cytochrome oxidase (CtaD) and Ribonucleotide reductase (NrdF1) in  C. diphtheriae  also show DtxR motif in their upstream sequences. Regulation of sortases We predict that DtxR could regulate the recently acquired pathogenic island DIP2271-DIP2272, encoding the sortase srtA and hypothetical protein, respectively [ 9 ]. Sortases are membrane-bound trans-peptidases that catalyze the anchoring of surface proteins to the cell wall peptidoglycan [ 9 ]. Such systems are often used by gram-positive pathogens to anchor host-interacting proteins to the bacterial surface [ 19 ]. Regulation of protein translation and translocation system DtxR could regulate two operons that contain genes DIP0699 ( secA ) and DIP0540 ( secY ) that code for the protein translocation system. The  sec Y-containing operon, which is similar to the streptomycine operon spc from  B. subtilis  and other bacteria, involves the genes required for protein translation and translocation [ 20 ]. The operon contains additional sialidase gene (DIP0543) in comparison to non pathogenic Corynebacterium species. Activity of sialidase has been linked to virulence in several other microbial pathogens and may enhance fimbriae mediated adhesion in  Corynebacterium diphtheriae  by unmasking receptors on mammalian cells [ 9 ]. The Sec system can both translocate proteins across the cytoplasmic membrane and insert integral membrane proteins into it. The former proteins but not the latter possess N-terminal, cleavable, targeting signal sequences that are required to direct the proteins to the Sec system. Some of the DtxR-regulated genes including diphtheria toxin (Table  4 ) show predicted signal sequences by SignalP 3.0 [ 21 ] and hence they may play an important role in host interaction and virulence of  Corynebacterium diphtheriae  [ 9 ].
Discussion
Our analysis identified putative DtxR motifs upstream to various operons/genes which could be involved in siderophore biosynthesis, ABC-type transport systems, iron storage, oxidative stress defense and iron-sulfur cluster biosynthesis. In addition, we have also identified the motifs upstream of operons that could be involved in anchoring of host-interacting proteins to the cell wall and secretion of various virulence factors. Important functions of some of these DtxR-regulated genes and their role in  C. diphtheriae  physiology are discussed here.C. diphtheriaeRegulation of siderophore biosynthesis and ABC-type transport systems Predicted member of the DtxR regulon, the gene DIP0586, codes for the IucA/IucC family of enzymes that catalyze discrete step in the biosynthesis of the aerobactin [ 13 ]. In addition to known DtxR-regulated siderophore transport genes (irp1, irp6), DtxR could also regulate other ABC-type transport systems similar to Manganese/Zinc, peptide/Nickel and multidrug subfamilies of ABC transporters. The peptide/nickel transport system (DIP2162-DIP2165) has been suggested to be recently acquired by pathogenic  C. diphtheriae  [ 9 ].
Regulation of siderophore biosynthesis and ABC-type transport systems
Predicted member of the DtxR regulon, the gene DIP0586, codes for the IucA/IucC family of enzymes that catalyze discrete step in the biosynthesis of the aerobactin [ 13 ]. In addition to known DtxR-regulated siderophore transport genes (irp1, irp6), DtxR could also regulate other ABC-type transport systems similar to Manganese/Zinc, peptide/Nickel and multidrug subfamilies of ABC transporters. The peptide/nickel transport system (DIP2162-DIP2165) has been suggested to be recently acquired by pathogenic  C. diphtheriae  [ 9 ].C. diphtheriaeRegulation of iron storage and oxidative stress defense We predict that DtxR could regulate divergently transcribed genes DIP2303 and DIP2304 whose products are similar to starvation inducible DNA-binding protein (Dps) and Formamidopyrimidine-DNA glycosylase (Fpg), respectively. Dps in  Escherichia coli  is induced in response to oxidative or nutritional stress and protects DNA from oxidative stress damage by nonspecific binding [ 14 ]. Dps also catalyzes oxidation of ferrous iron to ferric iron by hydrogen peroxide (2Fe 2+  + H 2 O 2  + 2H 2 O → 2Fe +3 OOH (core)  + 4H + ) which in turn prevents hydroxyl radical formation by Fenton's reaction (Fe 2+  + H 2 O 2  → Fe +3  + HO -  + HO . ) and thereby prevents subsequent DNA damage [ 15 ]. The enzyme, formamidopyrimidine-DNA glycosylase is a primary participant in the repair of 8-oxoguanine, an abundant oxidative DNA lesion [ 16 ]. The gene DIP1510 which codes for the site-specific recombinase XerD could also be regulated by DtxR. The  xerD  gene in  E. coli  belongs to the oxidative stress regulon [ 17 ].
Regulation of iron storage and oxidative stress defense
We predict that DtxR could regulate divergently transcribed genes DIP2303 and DIP2304 whose products are similar to starvation inducible DNA-binding protein (Dps) and Formamidopyrimidine-DNA glycosylase (Fpg), respectively. Dps in  Escherichia coli  is induced in response to oxidative or nutritional stress and protects DNA from oxidative stress damage by nonspecific binding [ 14 ]. Dps also catalyzes oxidation of ferrous iron to ferric iron by hydrogen peroxide (2Fe 2+  + H 2 O 2  + 2H 2 O → 2Fe +3 OOH (core)  + 4H + ) which in turn prevents hydroxyl radical formation by Fenton's reaction (Fe 2+  + H 2 O 2  → Fe +3  + HO -  + HO . ) and thereby prevents subsequent DNA damage [ 15 ]. The enzyme, formamidopyrimidine-DNA glycosylase is a primary participant in the repair of 8-oxoguanine, an abundant oxidative DNA lesion [ 16 ]. The gene DIP1510 which codes for the site-specific recombinase XerD could also be regulated by DtxR. The  xerD  gene in  E. coli  belongs to the oxidative stress regulon [ 17 ].Escherichia colixerDE. coliRegulation of proteins involved in iron-sulfur cluster biosynthesis and iron-sulfur cluster containing proteins We predict that the operon DIP1288-DIP1296, which is similar to the  suf  operon of  E. coli , could be regulated by DtxR. The  suf  operon in bacteria encodes the genes for Fe-S cluster assembly machinery [ 18 ]. In addition, genes encoding the iron-sulfur containing proteins such as succinate dehydrogenase (Sdh), cytochrome oxidase (CtaD) and Ribonucleotide reductase (NrdF1) in  C. diphtheriae  also show DtxR motif in their upstream sequences.
Regulation of proteins involved in iron-sulfur cluster biosynthesis and iron-sulfur cluster containing proteins
We predict that the operon DIP1288-DIP1296, which is similar to the  suf  operon of  E. coli , could be regulated by DtxR. The  suf  operon in bacteria encodes the genes for Fe-S cluster assembly machinery [ 18 ]. In addition, genes encoding the iron-sulfur containing proteins such as succinate dehydrogenase (Sdh), cytochrome oxidase (CtaD) and Ribonucleotide reductase (NrdF1) in  C. diphtheriae  also show DtxR motif in their upstream sequences.sufE. colisufC. diphtheriaeRegulation of sortases We predict that DtxR could regulate the recently acquired pathogenic island DIP2271-DIP2272, encoding the sortase srtA and hypothetical protein, respectively [ 9 ]. Sortases are membrane-bound trans-peptidases that catalyze the anchoring of surface proteins to the cell wall peptidoglycan [ 9 ]. Such systems are often used by gram-positive pathogens to anchor host-interacting proteins to the bacterial surface [ 19 ].
Regulation of sortases
We predict that DtxR could regulate the recently acquired pathogenic island DIP2271-DIP2272, encoding the sortase srtA and hypothetical protein, respectively [ 9 ]. Sortases are membrane-bound trans-peptidases that catalyze the anchoring of surface proteins to the cell wall peptidoglycan [ 9 ]. Such systems are often used by gram-positive pathogens to anchor host-interacting proteins to the bacterial surface [ 19 ].Regulation of protein translation and translocation system DtxR could regulate two operons that contain genes DIP0699 ( secA ) and DIP0540 ( secY ) that code for the protein translocation system. The  sec Y-containing operon, which is similar to the streptomycine operon spc from  B. subtilis  and other bacteria, involves the genes required for protein translation and translocation [ 20 ]. The operon contains additional sialidase gene (DIP0543) in comparison to non pathogenic Corynebacterium species. Activity of sialidase has been linked to virulence in several other microbial pathogens and may enhance fimbriae mediated adhesion in  Corynebacterium diphtheriae  by unmasking receptors on mammalian cells [ 9 ]. The Sec system can both translocate proteins across the cytoplasmic membrane and insert integral membrane proteins into it. The former proteins but not the latter possess N-terminal, cleavable, targeting signal sequences that are required to direct the proteins to the Sec system. Some of the DtxR-regulated genes including diphtheria toxin (Table  4 ) show predicted signal sequences by SignalP 3.0 [ 21 ] and hence they may play an important role in host interaction and virulence of  Corynebacterium diphtheriae  [ 9 ].
Regulation of protein translation and translocation system
DtxR could regulate two operons that contain genes DIP0699 ( secA ) and DIP0540 ( secY ) that code for the protein translocation system. The  sec Y-containing operon, which is similar to the streptomycine operon spc from  B. subtilis  and other bacteria, involves the genes required for protein translation and translocation [ 20 ]. The operon contains additional sialidase gene (DIP0543) in comparison to non pathogenic Corynebacterium species. Activity of sialidase has been linked to virulence in several other microbial pathogens and may enhance fimbriae mediated adhesion in  Corynebacterium diphtheriae  by unmasking receptors on mammalian cells [ 9 ].secAsecYsecB. subtilisCorynebacterium diphtheriaeThe Sec system can both translocate proteins across the cytoplasmic membrane and insert integral membrane proteins into it. The former proteins but not the latter possess N-terminal, cleavable, targeting signal sequences that are required to direct the proteins to the Sec system. Some of the DtxR-regulated genes including diphtheria toxin (Table  4 ) show predicted signal sequences by SignalP 3.0 [ 21 ] and hence they may play an important role in host interaction and virulence of  Corynebacterium diphtheriae  [ 9 ].Corynebacterium diphtheriaeConclusions The bioinformatics method used to predict the targets of DtxR in  C. diphtheriae  NCTC13129 genome is promising, as some of the predicted targets were experimentally verified. The approach identified novel DtxR-regulated genes, which could play an important role in physiology of  C. diphtheriae  NCTC13129. DtxR, generally known as a repressor of diphtheriae toxin and iron siderophore/transport genes, can also regulate other metal ion transport genes, iron storage, oxidative stress, DNA-repair, biosynthesis of iron-sulfur cluster, Fe-S-cluster containing proteins, and even protein sortase and translocation systems.
Conclusions
The bioinformatics method used to predict the targets of DtxR in  C. diphtheriae  NCTC13129 genome is promising, as some of the predicted targets were experimentally verified. The approach identified novel DtxR-regulated genes, which could play an important role in physiology of  C. diphtheriae  NCTC13129. DtxR, generally known as a repressor of diphtheriae toxin and iron siderophore/transport genes, can also regulate other metal ion transport genes, iron storage, oxidative stress, DNA-repair, biosynthesis of iron-sulfur cluster, Fe-S-cluster containing proteins, and even protein sortase and translocation systems.C. diphtheriaeC. diphtheriaeMethods Source of genome sequence The complete genome sequence of  C. diphtheriae  was downloaded from NCBI ftp site [ 22 ], and the DtxR-binding sites identified by experimental methods were collected from literature [ 6 , 10 , 25 - 27 ]. Prediction of DtxR-binding sites DtxR-binding site recognition profile was calculated by positional Shannon relative entropy method [ 23 , 24 ]. The positional relative entropy  Q i  at position  i  in a binding site is defined as where  b  refers to each of the possible base (A, T, G, C),  f b,i  is observed frequency of each base at position  i  and  q b  is the frequency of base  b  in the genome sequence. The contribution of each base to the positional Shannon's relative entropy is calculated by multiplying positional frequency of each base with positional relative entropy. The binding site profile thus generated was used to scan upstream sequences of all the genes of the  Corynebacterium diphtheriae  genome. The score of each site is calculated as the sum of the respective positional Shannon relative entropy of each of the four possible bases. A maximally scoring site is selected from the upstream sequence of each gene. The lowest score among the input binding sites is considered as cut-off score. The sites scoring higher than the cut-off value are reported as potential binding sites conforming to the consensus sequence. Prediction of operons Co-directionally transcribed genes, downstream to the predicted binding site were selected as potential co-regulated genes (operons) according to one of the following criteria (a) Co-directionally transcribed orthologous gene pairs, conserved in at least 4 genomes; (b) genes belong to the same cluster of orthologous gene function category and the intergenic distance is less than 200 base pairs; (c) the first three letters in gene names are identical (gene names for putative genes were assigned from COG database); (d) intergenic distance is less than 90 base pairs [ 24 ]. Functional assignment of genes The function of predicted genes was inferred using the RPS-BLAST search against conserved domain database [ 12 ]. These genes were further classified according to their function. Expression and purification of IdeR The iron-dependent regulator IdeR from M.  tuberculosis  was expressed from a recombinant pRSET vector containing the IdeR gene fused to a six His affinity tag (P. Chakhiyar unpublished). The expressed protein was first purified using Ni-NTA Metal Chelate Affinity chromatography; later it was desalted and concentrated using Centricon Ultra filtration device. The concentration of the recombinant protein was estimated using Bradford method. Electrophoretic mobility shift assay Double-stranded oligonucleotides containing the predicted binding motif (19 bp long) were end labeled with T4 polynucleotide kinase and [γ 32 P]-ATP and were incubated with the recombinant purified IdeR protein in a binding reaction mixture. The binding reaction mixture (20-μl total volume) contain the DNA-binding buffer (20 mM Tris-HCl [pH 8.0], 2 mM DTT, 50 mM NaCl, 5 mM MgCl 2 , 50% glycerol, 5 μg of bovine serum albumin per ml), 10 μg of poly(dI-dC) per ml (for nonspecific binding) and 200 μM MnCl 2 . The reaction mixture was incubated at room temperature for 30 min. Approximately 2 μl of the tracking dye (50% sucrose, 0.6% bromophenol blue) was added to the reaction mixture at the end of incubation and was loaded onto 7% polyacrylamide gel containing 150 μM MnCl 2  in 1 × Tris-borate-EDTA buffer. The gel was electrophoresed at 200 V for 2 hours. Subsequently the gel was dried and exposed to Fuji Storage Phosphor Image Plates for 16 hours. The image plates were subsequently scanned in Fuji Storage Phosphor Imaging workstation.
Methods
Source of genome sequence The complete genome sequence of  C. diphtheriae  was downloaded from NCBI ftp site [ 22 ], and the DtxR-binding sites identified by experimental methods were collected from literature [ 6 , 10 , 25 - 27 ].
Source of genome sequence
The complete genome sequence of  C. diphtheriae  was downloaded from NCBI ftp site [ 22 ], and the DtxR-binding sites identified by experimental methods were collected from literature [ 6 , 10 , 25 - 27 ].C. diphtheriaePrediction of DtxR-binding sites DtxR-binding site recognition profile was calculated by positional Shannon relative entropy method [ 23 , 24 ]. The positional relative entropy  Q i  at position  i  in a binding site is defined as where  b  refers to each of the possible base (A, T, G, C),  f b,i  is observed frequency of each base at position  i  and  q b  is the frequency of base  b  in the genome sequence. The contribution of each base to the positional Shannon's relative entropy is calculated by multiplying positional frequency of each base with positional relative entropy. The binding site profile thus generated was used to scan upstream sequences of all the genes of the  Corynebacterium diphtheriae  genome. The score of each site is calculated as the sum of the respective positional Shannon relative entropy of each of the four possible bases. A maximally scoring site is selected from the upstream sequence of each gene. The lowest score among the input binding sites is considered as cut-off score. The sites scoring higher than the cut-off value are reported as potential binding sites conforming to the consensus sequence.
Prediction of DtxR-binding sites
DtxR-binding site recognition profile was calculated by positional Shannon relative entropy method [ 23 , 24 ]. The positional relative entropy  Q i  at position  i  in a binding site is defined asQiiwhere  b  refers to each of the possible base (A, T, G, C),  f b,i  is observed frequency of each base at position  i  and  q b  is the frequency of base  b  in the genome sequence. The contribution of each base to the positional Shannon's relative entropy is calculated by multiplying positional frequency of each base with positional relative entropy. The binding site profile thus generated was used to scan upstream sequences of all the genes of the  Corynebacterium diphtheriae  genome. The score of each site is calculated as the sum of the respective positional Shannon relative entropy of each of the four possible bases. A maximally scoring site is selected from the upstream sequence of each gene. The lowest score among the input binding sites is considered as cut-off score. The sites scoring higher than the cut-off value are reported as potential binding sites conforming to the consensus sequence.bfb,iiqbbCorynebacterium diphtheriaePrediction of operons Co-directionally transcribed genes, downstream to the predicted binding site were selected as potential co-regulated genes (operons) according to one of the following criteria (a) Co-directionally transcribed orthologous gene pairs, conserved in at least 4 genomes; (b) genes belong to the same cluster of orthologous gene function category and the intergenic distance is less than 200 base pairs; (c) the first three letters in gene names are identical (gene names for putative genes were assigned from COG database); (d) intergenic distance is less than 90 base pairs [ 24 ].
Prediction of operons
Co-directionally transcribed genes, downstream to the predicted binding site were selected as potential co-regulated genes (operons) according to one of the following criteria (a) Co-directionally transcribed orthologous gene pairs, conserved in at least 4 genomes; (b) genes belong to the same cluster of orthologous gene function category and the intergenic distance is less than 200 base pairs; (c) the first three letters in gene names are identical (gene names for putative genes were assigned from COG database); (d) intergenic distance is less than 90 base pairs [ 24 ].Functional assignment of genes The function of predicted genes was inferred using the RPS-BLAST search against conserved domain database [ 12 ]. These genes were further classified according to their function.
Functional assignment of genes
The function of predicted genes was inferred using the RPS-BLAST search against conserved domain database [ 12 ]. These genes were further classified according to their function.Expression and purification of IdeR The iron-dependent regulator IdeR from M.  tuberculosis  was expressed from a recombinant pRSET vector containing the IdeR gene fused to a six His affinity tag (P. Chakhiyar unpublished). The expressed protein was first purified using Ni-NTA Metal Chelate Affinity chromatography; later it was desalted and concentrated using Centricon Ultra filtration device. The concentration of the recombinant protein was estimated using Bradford method.
Expression and purification of IdeR
The iron-dependent regulator IdeR from M.  tuberculosis  was expressed from a recombinant pRSET vector containing the IdeR gene fused to a six His affinity tag (P. Chakhiyar unpublished). The expressed protein was first purified using Ni-NTA Metal Chelate Affinity chromatography; later it was desalted and concentrated using Centricon Ultra filtration device. The concentration of the recombinant protein was estimated using Bradford method.tuberculosisElectrophoretic mobility shift assay Double-stranded oligonucleotides containing the predicted binding motif (19 bp long) were end labeled with T4 polynucleotide kinase and [γ 32 P]-ATP and were incubated with the recombinant purified IdeR protein in a binding reaction mixture. The binding reaction mixture (20-μl total volume) contain the DNA-binding buffer (20 mM Tris-HCl [pH 8.0], 2 mM DTT, 50 mM NaCl, 5 mM MgCl 2 , 50% glycerol, 5 μg of bovine serum albumin per ml), 10 μg of poly(dI-dC) per ml (for nonspecific binding) and 200 μM MnCl 2 . The reaction mixture was incubated at room temperature for 30 min. Approximately 2 μl of the tracking dye (50% sucrose, 0.6% bromophenol blue) was added to the reaction mixture at the end of incubation and was loaded onto 7% polyacrylamide gel containing 150 μM MnCl 2  in 1 × Tris-borate-EDTA buffer. The gel was electrophoresed at 200 V for 2 hours. Subsequently the gel was dried and exposed to Fuji Storage Phosphor Image Plates for 16 hours. The image plates were subsequently scanned in Fuji Storage Phosphor Imaging workstation.
Electrophoretic mobility shift assay
Double-stranded oligonucleotides containing the predicted binding motif (19 bp long) were end labeled with T4 polynucleotide kinase and [γ 32 P]-ATP and were incubated with the recombinant purified IdeR protein in a binding reaction mixture. The binding reaction mixture (20-μl total volume) contain the DNA-binding buffer (20 mM Tris-HCl [pH 8.0], 2 mM DTT, 50 mM NaCl, 5 mM MgCl 2 , 50% glycerol, 5 μg of bovine serum albumin per ml), 10 μg of poly(dI-dC) per ml (for nonspecific binding) and 200 μM MnCl 2 . The reaction mixture was incubated at room temperature for 30 min. Approximately 2 μl of the tracking dye (50% sucrose, 0.6% bromophenol blue) was added to the reaction mixture at the end of incubation and was loaded onto 7% polyacrylamide gel containing 150 μM MnCl 2  in 1 × Tris-borate-EDTA buffer. The gel was electrophoresed at 200 V for 2 hours. Subsequently the gel was dried and exposed to Fuji Storage Phosphor Image Plates for 16 hours. The image plates were subsequently scanned in Fuji Storage Phosphor Imaging workstation.List of abbreviations DtxR – Diphtheria toxin repressor; IdeR – Iron-dependent regulator; Dps – DNA-binding protein from starved cells; RPS-BLAST – Reversed Position Specific – Basic Local Alignment Search Tool; EMSA – Electrophoretic Mobility Shift Assay
List of abbreviations
DtxR – Diphtheria toxin repressor; IdeR – Iron-dependent regulator; Dps – DNA-binding protein from starved cells; RPS-BLAST – Reversed Position Specific – Basic Local Alignment Search Tool; EMSA – Electrophoretic Mobility Shift AssayAuthors' contributions SY: carried out the computation, data analysis, and manuscript preparation. SR: Carried out the EMSA and drafted the manuscript. PC: provided the cloned IdeR construct, drafted the manuscript. SH: Manuscript preparation and coordination. AR: Design of the study and coordination. All authors read and approved the final manuscript.
Authors' contributions
SY: carried out the computation, data analysis, and manuscript preparation. SR: Carried out the EMSA and drafted the manuscript. PC: provided the cloned IdeR construct, drafted the manuscript. SH: Manuscript preparation and coordination. AR: Design of the study and coordination. All authors read and approved the final manuscript.