Evidence of an Unusually Long Operator for the Fur Repressor in the Aerobactin Promoter of Escherichia coli

Escolar, L; Pérez-Martı́n, José; Lorenzo, Vı́ctor de

doi:10.1074/jbc.m002839200

Cited by 53 publications

(55 citation statements)

References 37 publications

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“…Thus, in each of these cases, the binding affinity of a TF for the auxiliary site is adapted in order to reach an optimal TF concentration dependence of the response. Experimental support for these results comes from E. coli cis-regulatory regions containing homocooperative LysR family activator binding sites and others containing homocooperative Fur repressor binding sites, which have both been studied in some detail and confirm the role of strong and weak binding sites proposed by the model (80,165,318). Therefore, in the case that multiple TFBSs for a single TF are present in a promoter, the secondary sites are expected to be more conserved than the primary TFBS in the case of activators and the other way around in the case of repressors.…”

Section: Cooperative and Competitive Dna Binding And Motif Stringencysupporting

confidence: 52%

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

Hijum

Medema

Kuipers

2009

Microbiol Mol Biol Rev

137

149

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SUMMARY A major part of organismal complexity and versatility of prokaryotes resides in their ability to fine-tune gene expression to adequately respond to internal and external stimuli. Evolution has been very innovative in creating intricate mechanisms by which different regulatory signals operate and interact at promoters to drive gene expression. The regulation of target gene expression by transcription factors (TFs) is governed by control logic brought about by the interaction of regulators with TF binding sites (TFBSs) in cis-regulatory regions. A factor that in large part determines the strength of the response of a target to a given TF is motif stringency, the extent to which the TFBS fits the optimal TFBS sequence for a given TF. Advances in high-throughput technologies and computational genomics allow reconstruction of transcriptional regulatory networks in silico. To optimize the prediction of transcriptional regulatory networks, i.e., to separate direct regulation from indirect regulation, a thorough understanding of the control logic underlying the regulation of gene expression is required. This review summarizes the state of the art of the elements that determine the functionality of TFBSs by focusing on the molecular biological mechanisms and evolutionary origins of cis-regulatory regions.

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Section: Cooperative and Competitive Dna Binding And Motif Stringencysupporting

confidence: 52%

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

Hijum

Medema

Kuipers

2009

Microbiol Mol Biol Rev

137

149

View full text Add to dashboard Cite

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“…This sequence is followed by the hexamer GATAAG that closely resembles the minimal interaction unit NAT(A\T)AT, which was recently reported as the nucleotide array that can explain the iron-regulated expression of AT-rich promoters that do not contain canonical Fur boxes (Escolar et al, 1999). Furthermore, at least 10 other units very similar to those found in the aerobactin promoter region (Escolar et al, 2000) can be identified upstream of the adhC1 initiation codon. This region also includes the sequence TAGCATTACAT-TATCTATTTTGCT that matches 19 of the 24 nucleotides found in the non-template strand of the Furbinding site I of the promoter region of the fatDCBA operon of the pJM1 plasmid (Chai et al, 1998).…”

Section: Regulation Of the Expression Of Adhcmentioning

confidence: 91%

Acinetobacter baumannii has two genes encoding glutathione-dependent formaldehyde dehydrogenase: evidence for differential regulation in response to iron This paper is dedicated to the memory of Dr M. A. Vides, Facultad de Ciencias Quı́micas, Universidad Nacional de Córdoba, Argentina, who was a great mentor and colleague. The GenBank accession number for the sequence reported in this paper is AF130307.

et al. 2001

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The adhC1 gene from Acinetobacter baumannii 8399, which encodes a glutathione-dependent formaldehyde dehydrogenase (GSH-FDH), was identified and cloned after mapping the insertion site of Tn3-HoHo1 in a recombinant cosmid isolated from a gene library. Sequence analysis showed that this gene encodes a protein exhibiting significant similarity to alcohol dehydrogenases in bacterial, yeast, plant and animal cells. The expression of the adhC1 gene was confirmed by the detection of GSH-FDH enzyme activity in A. baumannii and Escherichia coli cells that expressed the cloned gene. However, the construction and analysis of an A. baumannii 8399 adhC1 ::Tn3-HoHo1 isogenic derivative revealed the presence of adhC2, a second copy of the gene encoding GSH-FDH activity. Enzyme assays and immunoblot analysis showed that adhC2 encodes a 465 kDa protein that is produced in similar amounts under iron-rich and iron-limited conditions. In contrast, the expression of adhC1, which encodes a 45 kDa protein with GSH-FDH activity, is induced under iron limitation and repressed when the cells are cultured in the presence of free inorganic iron. The differential expression of adhC1 is controlled at the transcriptional level and mediated through the Fur ironrepressor protein, which has potential binding sites within the promoter region of this adhC copy. The expression of both adhC copies is significantly enhanced by the presence of sub-inhibitory concentrations of formaldehyde in the culture media. Examination of different A. baumannii isolates indicates that they can be divided into two groups based on the type of GSH-FDH they produce. One group contains only the constitutively expressed 465 kDa protein, whilst the other produces this GSH-FDH type in addition to the ironregulated isoenzyme. Further analysis showed that the presence and expression of the two adhC genes does not confer resistance to exogenous formaldehyde, nor does it enable it to utilize methylated compounds as a sole carbon source when cultured under iron-rich as well as iron-deficient conditions.

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“…For example, the two cooperative Fur-binding sites that overlap the core promoter on the pColV-K30 plasmid are supported by an array of low-affinity auxiliary sites [29]. A second example is the duo of dnaA promoters, 1P and 2P [40].…”

Section: Homo-cooperative Auxiliary Sites Provide Steep Responsesmentioning

confidence: 99%

Transcriptional Regulation by Competing Transcription Factor Modules

Hermsen¹,

Tans²,

Wolde³

2005

PLoS Comp Biol

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Gene regulatory networks lie at the heart of cellular computation. In these networks, intracellular and extracellular signals are integrated by transcription factors, which control the expression of transcription units by binding to cisregulatory regions on the DNA. The designs of both eukaryotic and prokaryotic cis-regulatory regions are usually highly complex. They frequently consist of both repetitive and overlapping transcription factor binding sites. To unravel the design principles of these promoter architectures, we have designed in silico prokaryotic transcriptional logic gates with predefined input-output relations using an evolutionary algorithm. The resulting cis-regulatory designs are often composed of modules that consist of tandem arrays of binding sites to which the transcription factors bind cooperatively. Moreover, these modules often overlap with each other, leading to competition between them. Our analysis thus identifies a new signal integration motif that is based upon the interplay between intramodular cooperativity and intermodular competition. We show that this signal integration mechanism drastically enhances the capacity of cis-regulatory domains to integrate signals. Our results provide a possible explanation for the complexity of promoter architectures and could be used for the rational design of synthetic gene circuits.

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Evidence of an Unusually Long Operator for the Fur Repressor in the Aerobactin Promoter of Escherichia coli

Cited by 53 publications

References 37 publications

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

Mechanisms and Evolution of Control Logic in Prokaryotic Transcriptional Regulation

Transcriptional Regulation by Competing Transcription Factor Modules

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