Non-canonical sequence elements in the promoter structure. Cluster analysis of promoters recognized by Escherichia coli RNA polymerase

Antimicrobial resistance and molecular characterization of gene cassettes from class 1 integrons in Salmonella strains

Introduction. The emergence of antibiotic-resistant Salmonella isolates is a global concern and has been attributed to the indiscriminate use of antibiotics in humans and animals. Integrons are mobile gene elements closely related to bacterial drug resistance. Among them, class 1 integrons containing various resistance gene cassettes could play an important role in disseminating and maintaining antibiotic resistance in Salmonella isolates.Hypothesis. Salmonella class 1 integrons have a relationship with Salmonella drug resistance.Aim. This study aims to investigate the distribution of class 1 integrons and their variable regional molecular characteristics, as well as the diversity of the promoters and drug sensitivity among Salmonella strains.Methodology. A total of 111 Salmonella strains, collected between 2018 and 2020, underwent fully automated bacterial identification using the VITEK 2 Compact system and an antibiotic sensitivity test. PCR was employed to screen class 1 integrase genes (IntI1) and integron variable regions, while promoter type and variable region gene cassette characteristics were determined using sequencing analysis.Results. A total of 24 IntI1-positive strains were detected in 111 Salmonella strains. Moreover, IntI1-positive strains exhibited statistically significant resistance to ceftazidime, ciprofloxacin, levofloxacin, ceftriaxone, trimethoprim/sulfamethoxazole and azithromycin compared to integron-negative strains (P<0.05). The multidrug resistance rate of IntI1-positive strains was significantly higher than that of negative strains. Variable regions were observed in 6 of the 24 IntI1-positive strains. Four gene cassettes were detected, namely dfrA17-aadA5, dfrA12-aadA2, aadA22 and aar-3-dfrA27. Finally, 3 types of class 1 integron variable region promoters were identified in 24 strains, including PcW, PcH1 and PcW_TGN-10; they are all relatively weak promoters.Conclusion. The integron and the drug resistance genes carried by integron have a certain relationship with drug resistance.

A functional promoter from the archaeon Halobacterium salinarum is also transcriptionally active in E. coli

Background

Archaea form a third domain of life that is distinct from Bacteria and Eukarya. So far, many scholars have elucidated considerable details about the typical promoter architectures of the three domains of life. However, a functional promoter from the archaeon Halobacterium salinarum has never been studied in Escherichia coli.

Results

This paper found that the promoter of Halobacterium salinarum showed a promoter function in Escherichia coli. This Escherichia coli promoter structure contains − 10 box, -10 box extension and − 29 elements, however, no -35 box. The − 29 element is exercised by the TATA box in archaea. And we isolated the RM10 fragment that possessed the fusion characteristics of bacteria and archaea, which was overlapped with functionality of TATA box and − 29 elements.

Conclusions

The − 29 element reflects the evolutionary relationship between the archaeal promoter and the bacterial promoter. The result possibly indicated that there may be a certain internal connection between archaea and bacteria. We hypothesized that it provided a new viewpoint of the evolutionary relationship of archaea and other organisms.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-022-02489-y.

Promoters of Escherichia coli versus promoter islands: function and structure comparison

Expression of bacterial genes takes place under the control of RNA polymerase with exchangeable σ-subunits and multiple transcription factors. A typical promoter region contains one or several overlapping promoters. In the latter case promoters have the same or different σ-specificity and are often subjected to different regulatory stimuli. Genes, transcribed from multiple promoters, have on average higher expression levels. However, recently in the genome of Escherichia coli we found 78 regions with an extremely large number of potential transcription start points (promoter islands, PIs). It was shown that all PIs interact with RNA polymerase in vivo and are able to form transcriptionally competent open complexes both in vitro and in vivo but their transcriptional activity measured by oligonucleotide microarrays was very low, if any. Here we confirmed transcriptional defectiveness of PIs by analyzing the 5'-end specific RNA-seq data, but showed their ability to produce short oligos (9-14 bases). This combination of functional properties indicated a deliberate suppression of transcriptional activity within PIs. According to our data this suppression may be due to a specific conformation of the DNA double helix, which provides an ideal platform for interaction with both RNA polymerase and the histone-like nucleoid protein H-NS. The genomic DNA of E.coli contains therefore several dozen sites optimized by evolution for staying in a heterochromatin-like state. Since almost all promoter islands are associated with horizontally acquired genes, we offer them as specific components of bacterial evolution involved in acquisition of foreign genetic material by turning off the expression of toxic or useless aliens or by providing optimal promoter for beneficial genes. The putative molecular mechanism underlying the appearance of promoter islands within recipient genomes is discussed.

Genome-wide prediction and validation of sigma70 promoters in Lactobacillus plantarum WCFS1

BACKGROUND

In prokaryotes, sigma factors are essential for directing the transcription machinery towards promoters. Various sigma factors have been described that recognize, and bind to specific DNA sequence motifs in promoter sequences. The canonical sigma factor σ(70) is commonly involved in transcription of the cell's housekeeping genes, which is mediated by the conserved σ(70) promoter sequence motifs. In this study the σ(70)-promoter sequences in Lactobacillus plantarum WCFS1 were predicted using a genome-wide analysis. The accuracy of the transcriptionally-active part of this promoter prediction was subsequently evaluated by correlating locations of predicted promoters with transcription start sites inferred from the 5'-ends of transcripts detected by high-resolution tiling array transcriptome datasets.

RESULTS

To identify σ(70)-related promoter sequences, we performed a genome-wide sequence motif scan of the L. plantarum WCFS1 genome focussing on the regions upstream of protein-encoding genes. We obtained several highly conserved motifs including those resembling the conserved σ(70)-promoter consensus. Position weight matrices-based models of the recovered σ(70)-promoter sequence motif were employed to identify 3874 motifs with significant similarity (p-value<10(-4)) to the model-motif in the L. plantarum genome. Genome-wide transcript information deduced from whole genome tiling-array transcriptome datasets, was used to infer transcription start sites (TSSs) from the 5'-end of transcripts. By this procedure, 1167 putative TSSs were identified that were used to corroborate the transcriptionally active fraction of these predicted promoters. In total, 568 predicted promoters were found in proximity (≤ 40 nucleotides) of the putative TSSs, showing a highly significant co-occurrence of predicted promoter and TSS (p-value<10(-263)).

CONCLUSIONS

High-resolution tiling arrays provide a suitable source to infer TSSs at a genome-wide level, and allow experimental verification of in silico predicted promoter sequence motifs.

Functional characterization of a Cassette-specific promoter in the class 1 integron-associated qnrVC1 gene

Integrons are natural expression vectors due to the presence of an intrinsic promoter (P(c)). Although rare, gene cassettes can harbor their own promoter. This study determined the functionality of an internal promoter in the qnrVC1 cassette whose presence was suggested by a level of transcription similar to that of the preceding cassette (aadA2) and confirmed by in silico analysis. Its functionality was determined by 5' rapid amplification of cDNA ends (RACE) and cloning into promoter-probe vectors. P(qnrVC) was found in the qnrVC cassette family, stressing its role in contributing to resistance manifestation.

BIOLOGICAL DATA MINING USING BAYESIAN NEURAL NETWORKS: A CASE STUDY

Biological data mining is the activity of finding significant information in biomolecular data. The significant information may refer to motifs, clusters, genes, and protein signatures. This paper presents an example of biological data mining: the recognition of promoters in DNA. We propose a two-level ensemble of classifiers to recognize E. Coli promoter sequences. The first-level classifiers include three Bayesian neural networks that learn from three different feature sets. The outputs of the first-level classifiers are combined in the second-level to give the final result. Empirical study shows that a precision rate of 92.2% is achieved, indicating an excellent performance of the proposed approach.

Pc promoter from class 2 integrons and the cassette transcription pattern it evokes

OBJECTIVES

Integrons are considered expression systems due to the presence of Pc promoters that drive gene cassette transcription. The role and configurations of Pc are well known in class 1 integrons; however, this region has not yet been identified in class 2 integrons. This study aimed to characterize the Pc promoter from class 2 integrons and to determine the effect of gene cassette position on transcription driven by this promoter.

METHODS

The class 2 cassette arrays from Klebsiella pneumoniae and Vibrio cholerae strains were determined by sequencing. Transcription analyses were performed by real-time RT-PCR and relative quantification was carried out by comparing the transcripts of each normalized gene inserted in the integron to each other. The resistance profile was determined by the disc diffusion method. The class 2 Pc promoter was characterized by 5' rapid amplification of cDNA ends and promoter prediction programs.

RESULTS

Sequence analysis revealed the presence of the dfrA1-sat2-aadA1-ybeA and sat2-aadA1-ybeA arrangements in K. pneumoniae and V. cholerae strains, respectively. Real-time RT-PCR showed that the transcription of the first cassettes was higher than that of distal ones in wild-type and recombinant strains. All strains were resistant, indicating cassette expression. The Pc promoter of class 2 integrons (-35 TTTAAT |16 bp| -10 TAAAAT) was determined based on in silico analyses and on the transcription start site sequence of the class 2 integron cassette array.

CONCLUSIONS

The Pc from class 2 integrons was characterized for the first time and the cassette position effect on transcription was demonstrated.

Fractal topology of gene promoter networks at phase transitions

Much is known regarding the structure and logic of genetic regulatory networks. Less understood is the contextual organization of promoter signals used during transcription initiation, the most pivotal stage during gene expression. Here we show that promoter networks organize spontaneously at a dimension between the 1-dimension of the DNA and 3-dimension of the cell. Network methods were used to visualize the global structure of E. coli sigma (σ) recognition footprints using published promoter sequences (RegulonDB). Footprints were rendered as networks with weighted edges representing bp-sharing between promoters (nodes). Serial thresholding revealed phase transitions at positions predicted by percolation theory, and nuclei denoting short steps through promoter space with geometrically constrained linkages. The network nuclei are fractals, a power-law organization not yet described for promoters. Genome-wide promoter abundance also scaled as a power-law. We propose a general model for the development of a fractal nucleus in a transcriptional grammar.

Genome-wide identification of transcription start sites, promoters and transcription factor binding sites in E. coli

Despite almost 40 years of molecular genetics research in Escherichia coli a major fraction of its Transcription Start Sites (TSSs) are still unknown, limiting therefore our understanding of the regulatory circuits that control gene expression in this model organism. RegulonDB (http://regulondb.ccg.unam.mx/) is aimed at integrating the genetic regulatory network of E. coli K12 as an entirely bioinformatic project up till now. In this work, we extended its aims by generating experimental data at a genome scale on TSSs, promoters and regulatory regions. We implemented a modified 5' RACE protocol and an unbiased High Throughput Pyrosequencing Strategy (HTPS) that allowed us to map more than 1700 TSSs with high precision. From this collection, about 230 corresponded to previously reported TSSs, which helped us to benchmark both our methodologies and the accuracy of the previous mapping experiments. The other ca 1500 TSSs mapped belong to about 1000 different genes, many of them with no assigned function. We identified promoter sequences and type of sigma factors that control the expression of about 80% of these genes. As expected, the housekeeping sigma(70) was the most common type of promoter, followed by sigma(38). The majority of the putative TSSs were located between 20 to 40 nucleotides from the translational start site. Putative regulatory binding sites for transcription factors were detected upstream of many TSSs. For a few transcripts, riboswitches and small RNAs were found. Several genes also had additional TSSs within the coding region. Unexpectedly, the HTPS experiments revealed extensive antisense transcription, probably for regulatory functions. The new information in RegulonDB, now with more than 2400 experimentally determined TSSs, strengthens the accuracy of promoter prediction, operon structure, and regulatory networks and provides valuable new information that will facilitate the understanding from a global perspective the complex and intricate regulatory network that operates in E. coli.

Gains and unexpected lessons from genome-scale promoter mapping

Potential promoters in the genome of Escherichia coli were searched by pattern recognition software PlatProm and classified on the basis of positions relative to gene borders. Beside the expected promoters located in front of the coding sequences we found a considerable amount of intragenic promoter-like signals with a putative ability to drive either antisense or alternative transcription and revealed unusual genomic regions with extremely high density of predicted transcription start points (promoter ‘islands’), some of which are located in coding sequences. PlatProm scores converted into probability of RNA polymerase binding demonstrated certain correlation with the enzyme retention registered by ChIP-on-chip technique; however, in ‘dense’ regions the value of correlation coefficient is lower than throughout the entire genome. Experimental verification confirmed the ability of RNA polymerase to interact and form multiple open complexes within promoter ‘island’ associated with appY, yet transcription efficiency was lower than might be expected. Analysis of expression data revealed the same tendency for other promoter ‘islands’, thus assuming functional relevance of non-productive RNA polymerase binding. Our data indicate that genomic DNA of E. coli is enriched by numerous unusual promoter-like sites with biological role yet to be understood.

ArgR-dependent repression of arginine and histidine transport genes in Escherichia coli K-12

In Escherichia coli L-arginine is taken up by three periplasmic binding protein-dependent transport systems that are encoded by two genetic loci: the artPIQM-artJ and argT-hisJQMP gene clusters. The transcription of the artJ, artPIQM and hisJQMP genes and operons is repressed by liganded ArgR, whereas argT, encoding the LAO (lysine, arginine, ornithine) periplasmic binding protein, is insensitive to the repressor. Here we characterize the repressible Esigma70 P artJ, P artP and P hisJ promoters and demonstrate that the cognate operators consist of two 18 bp ARG boxes separated by 3 bp. Determination of the energy landscape of the ArgR-operator contacts by missing contact probing and mutant studies indicated that each box of a pair contributes to complex formation in vitro and to the repressibility in vivo, but to a different extent. The organization of the ARG boxes and promoter elements in the control regions of the uptake genes is distinct from that of the arginine biosynthetic genes. The hisJQMP operon is the first member of the E. coli ArgR regulon, directly repressed by liganded ArgR, where none of the core promoter elements overlaps the ARG boxes. Single round in vitro transcription assays and DNase I footprinting experiments indicate that liganded ArgR inhibits P artJ and P artP promoter activity by steric exclusion of the RNA polymerase. In contrast, ArgR-mediated repression of P hisJ by inhibition of RNA polymerase binding appears to occur through topological changes of the promoter region.

Selection against spurious promoter motifs correlates with translational efficiency across bacteria

Because binding of RNAP to misplaced sites could compromise the efficiency of transcription, natural selection for the optimization of gene expression should regulate the distribution of DNA motifs capable of RNAP-binding across the genome. Here we analyze the distribution of the −10 promoter motifs that bind the σ⁷⁰ subunit of RNAP in 42 bacterial genomes. We show that selection on these motifs operates across the genome, maintaining an over-representation of −10 motifs in regulatory sequences while eliminating them from the nonfunctional and, in most cases, from the protein coding regions. In some genomes, however, −10 sites are over-represented in the coding sequences; these sites could induce pauses effecting regulatory roles throughout the length of a transcriptional unit. For nonfunctional sequences, the extent of motif under-representation varies across genomes in a manner that broadly correlates with the number of tRNA genes, a good indicator of translational speed and growth rate. This suggests that minimizing the time invested in gene transcription is an important selective pressure against spurious binding. However, selection against spurious binding is detectable in the reduced genomes of host-restricted bacteria that grow at slow rates, indicating that components of efficiency other than speed may also be important. Minimizing the number of RNAP molecules per cell required for transcription, and the corresponding energetic expense, may be most relevant in slow growers. These results indicate that genome-level properties affecting the efficiency of transcription and translation can respond in an integrated manner to optimize gene expression. The detection of selection against promoter motifs in nonfunctional regions also confirms previous results indicating that no sequence may evolve free of selective constraints, at least in the relatively small and unstructured genomes of bacteria.

Selection for unequal densities of sigma70 promoter-like signals in different regions of large bacterial genomes

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that could be recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to see the generality of this pattern, we have analyzed 43 additional genomes belonging to most established bacterial phyla. Differential densities between regulatory and nonregulatory regions are detectable in most of the analyzed genomes, with the exception of those that have evolved toward extreme genome reduction. Thus, presence of this pattern follows that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is an outcome of the process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential distribution of promoter-like signals between regulatory and nonregulatory regions detected in large bacterial genomes confers a significant, although small, fitness advantage. This study paves the way for further identification of the specific types of selective constraints that affect the organization of regulatory regions and the overall distribution of promoter-like signals through more detailed comparative analyses among closely related bacterial genomes.

The most important step in the regulation of genetic expression is the initiation of transcription. This process is accomplished by the association or specific binding of RNA polymerase to particular sequence segments present in the DNA, the promoters. Promoters are located in the upstream regions of the transcribed genes. The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. For a long time, the canonical picture of a σ⁷⁰ promoter has been a 60 base pair region defined by the transcription start-point (+1) and two conserved hexanucleotide sequences centered 10 and 35 base pairs upstream from the +1. The authors have shown that in Escherichia coli, promoters exist in clusters, as a series of overlapping potentially competing RNAP interaction sites. The E. coli regulatory regions contain high densities of these promoter-like signals, in contrast to coding regions and regions located between convergently transcribed genes. They report that the differential densities between regulatory and nonregulatory regions are detectable in most eubacterial genomes, with the exception of those that have experienced severe genome degradation and size reduction. This suggests that the presence of this pattern in large bacterial genomes confers a significant, although small, fitness advantage.

The Rhizobium etli sigma70 (SigA) factor recognizes a lax consensus promoter

A collection of Rhizobium etli promoters was isolated from a genomic DNA library constructed in the promoter-trap vector pBBMCS53, by their ability to drive the expression of a gusA reporter gene. Thirty-seven clones were selected, and their transcriptional start-sites were determined. The upstream sequence of these 37 start-sites, and the sequences of seven previously identified promoters were compared. On the basis of sequence conservation and mutational analysis, a consensus sequence CTTGACN_16–23TATNNT was obtained. In this consensus sequence, nine on of twelve bases are identical to the canonical Escherichia coli σ⁷⁰ promoter, however the R.etli promoters only contain 6.4 conserved bases on average. We show that the R.etli sigma factor SigA recognizes all R.etli promoters studied in this work, and that E.coli RpoD is incapable of recognizing them. The comparison of the predicted structure of SigA with the known structure of RpoD indicated that regions 2.4 and 4.2, responsible for promoter recognition, are different only by a single amino acid, whereas the region 1 of SigA contains 72 extra residues, suggesting that the differences contained in this region could be related to the lax promoter recognition of SigA.

Improving promoter prediction for the NNPP2.2 algorithm: a case study using Escherichia coli DNA sequences

MOTIVATION

Although a great deal of research has been undertaken in the area of promoter prediction, prediction techniques are still not fully developed. Many algorithms tend to exhibit poor specificity, generating many false positives, or poor sensitivity. The neural network prediction program NNPP2.2 is one such example.

RESULTS

To improve the NNPP2.2 prediction technique, the distance between the transcription start site (TSS) associated with the promoter and the translation start site (TLS) of the subsequent gene coding region has been studied for Escherichia coli K12 bacteria. An empirical probability distribution that is consistent for all E.coli promoters has been established. This information is combined with the results from NNPP2.2 to create a new technique called TLS-NNPP, which improves the specificity of promoter prediction. The technique is shown to be effective using E.coli DNA sequences, however, it is applicable to any organism for which a set of promoters has been experimentally defined.

AVAILABILITY

The data used in this project and the prediction results for the tested sequences can be obtained from http://www.uow.edu.au/~yanxia/E_Coli_paper/SBurden_Results.xls

CONTACT

alh98@uow.edu.au.

Genome-wide operon prediction in Staphylococcus aureus

Identification of operon structure is critical to understanding gene regulation and function, and pathogenesis, and for identifying targets towards the development of new antibiotics in bacteria. Recently, the complete genome sequences of a large number of important human bacterial pathogens have become available for computational analysis, including the major human Gram-positive pathogen Staphylococcus aureus. By annotating the predicted operon structure of the S.aureus genome, we hope to facilitate the exploration of the unique biology of this organism as well as the comparative genomics across a broad range of bacteria. We have integrated several operon prediction methods and developed a consensus approach to score the likelihood of each adjacent gene pair to be co-transcribed. Gene pairs were separated into distinct operons when scores were equal to or below an empirical threshold. Using this approach, we have generated a S.aureus genome map with scores annotated at the intersections of every adjacent gene pair. This approach predicted about 864 monocistronic transcripts and 533 polycistronic operons from the protein-encoding genes in the S.aureus strain Mu50 genome. When compared with a set of experimentally determined S.aureus operons from literature sources, this method successfully predicted at least 91% of gene pairs. At the transcription unit level, this approach correctly identified at least 92% of complete operons in this dataset. This consensus approach has enabled us to predict operons with high accuracy from a genome where limited experimental evidence for operon structure is available.

Occurrence probability of structured motifs in random sequences

The problem of extracting from a set of nucleic acid sequences motifs which may have biological function is more and more important. In this paper, we are interested in particular motifs that may be implicated in the transcription process. These motifs, called structured motifs, are composed of two ordered parts separated by a variable distance and allowing for substitutions. In order to assess their statistical significance, we propose approximations of the probability of occurrences of such a structured motif in a given sequence. An application of our method to evaluate candidate promoters in E. coli and B. subtilis is presented. Simulations show the goodness of the approximations.

Sigma70 promoters in Escherichia coli: specific transcription in dense regions of overlapping promoter-like signals

We present here a computational analysis showing that sigma70 house-keeping promoters are located within zones with high densities of promoter-like signals in Escherichia coli, and we introduce strategies that allow for the correct computer prediction of sigma70 promoters. Based on 599 experimentally verified promoters of E.coli K-12, we generated and evaluated more than 200 weight matrices optimizing different criteria to obtain the best recognition matrices. The alignments generating the best statistical models did not fully correspond with the canonical sigma70 model. However, matrices that correspond to such a canonical model performed better as tools for prediction. We tested the predictive capacity of these matrices on 250 bp long regions upstream of gene starts, where 90% of the known promoters occur. The computational matrix models generated an average of 38 promoter-like signals within each 250 bp region. In more than 50% of the cases, the true promoter does not have the best score within the region. We observed, in fact, that real promoters occur mostly within regions with high densities of overlapping putative promoters. We evaluated several strategies to identify promoters. The best one uses an intrinsic score of the -10 and -35 hexamers that form the promoter as well as an extrinsic score that uses the distribution of promoters from the start of the gene. We were able to identify 86% true promoters correctly, generating an average of 4.7 putative promoters per region as output, of which 3.7, on average, exist in clusters, as a series of overlapping potentially competing RNA polymerase-binding sites. As far as we know, this is the highest predictive capability reported so far. This high signal density is found mainly within regions upstream of genes, contrasting with coding regions and regions located between convergently transcribed genes. These results are consistent with experimental evidence that show the existence of multiple overlapping promoter sites that become functional under particular conditions. This density is probably the consequence of a rich number of vestiges of promoters in evolution. We suggest that transcriptional regulators as well as other functional promoters play an important role in keeping these latent signals suppressed.

Mechanism of transcriptional activation by FIS: role of core promoter structure and DNA topology

The Escherichia coli DNA architectural protein FIS activates transcription from stable RNA promoters on entry into exponential growth and also reduces the level of negative supercoiling. Here we show that such a reduction decreases the activity of the tyrT promoter but that activation by FIS rescues tyrT transcription at non-optimal superhelical densities. Additionally we show that three different "up" mutations in the tyrT core promoter either abolish or reduce the dependence of tyrT transcription on both high negative superhelicity and FIS in vivo and infer that the specific sequence organisation of the core promoter couples the control of transcription initiation by negative superhelicity and FIS. In vitro all the mutations potentiate FIS-independent untwisting of the -10 region while at the wild-type promoter FIS facilitates this step. We propose that this untwisting is a crucial limiting step in the initiation of tyrT RNA synthesis. The tyrT core promoter structure is thus optimised to combine high transcriptional activity with acute sensitivity to at least three major independent regulatory inputs: negative superhelicity, FIS and ppGpp.

Stationary phase gene regulation: what makes an Escherichia coli promoter sigmaS-selective?

The general stress sigma factor sigma(S) and the vegetative sigma(70) are highly related and recognise the same core promoter elements. Nevertheless, they clearly control different sets of genes in vivo. Recent studies have demonstrated that Esigma(S) selectivity is based on modular combinations of several sequence and structural features of a promoter, to which also trans-acting factors can strongly contribute. These results throw novel light on the details of transcription initiation, as well as on the co-evolution of sigma factors and their cognate promoter sequences.

Plant-specific promoter sequences carry elements that are recognised by the eubacterial transcription machinery

During evolution the promoter elements from prokaryotes and eukaryotes have developed differently with regard to their sequence and structure, implying that in general a transfer of eukaryotic promoter sequences into prokaryotes will not cause an efficient gene expression. However, there have been reports on the functionality of the 35S promoter from cauliflower mosaic virus (CaMV) in bacteria. We therefore decided to experimentally investigate the capability of plant promoter sequences to direct gene expression in various bacteria. Accordingly, we tested ten different plant-specific promoters from Solanum tuberosum, Nicotiana tabacum, CaMV, Agrobacterium tumefaciens, and A. rhizogenes for their ability to initiate transcription in five different eubacterial species (Escherichia coli, Yersinia enterocolitica, A. tumefaciens, Pseudomonas putida, and Acinetobacter sp. BD413). To monitor the strength of the plant-specific promoters in bacteria we created fusions between these promoters and the coding region of the luciferase genes from Vibrio harveyi and measured the luminescence in the bacteria. Heterologous gene expression was observed in 50% of the combinations analysed. We then mapped the transcription start site caused by one of the plant-specific promoters, the ST-LS1 promoter from S. tuberosum, in these bacterial species. The location of the mapped transcription start site indicated that the sequences of the plant promoter themselves were recognised by the bacterial transcription apparatus. The recognition of plant-specific promoter sequences by the bacterial RNA polymerase was further confirmed by site-directed mutagenesis of the ST-LS1 promoter and the analysis of the effects of the mutations on the strength of gene expression in E. coli. Using these mutants in our reporter assays we could localise the sequences of the ST-LS1 promoter serving as -10 region in E. coli. The results of our study show that promoter sequences are much less specific than is generally assumed. This is of great importance for our knowledge about the evolution of gene expression systems and for the construction of optimised expression vectors.

Mode of DNA-protein interaction between the C-terminal domain of Escherichia coli RNA polymerase alpha subunit and T7D promoter UP element

The C-terminal domain (CTD) downstream from residue 235 of Escherichia coli RNA polymerase alpha subunit is involved in recognition of the promoter UP element. Here we have demonstrated, by DNase I and hydroxyl radical mapping, the presence of two UP element subsites on the promoter D of phage T7, each located half and one-and-a-half helix turns, respectively, upstream from the promoter -35 element. This non-typical UP element retained its alphaCTD-binding capability when transferred into the genetic environment of the rrnBP1 basic promoter, leading to transcription stimulation as high as the typical rrnBP1 UP element. Chemical protease FeBABE conjugated to alphaCTD S309C efficiently attacked the T7D UP element but not the rrnBP1 UP element. After alanine scanning, most of the amino acid residues that were involved in rrnBP1 interaction were also found to be involved in T7D UP element recognition, but alanine substitution at three residues had the opposite effect on the transcription activation between rrnBP1 and T7D promoters. Mutation E286A stimulated T7D transcription but inhibited rrnBP1 RNA synthesis, while L290A and K304A stimulated transcription from rrnBP1 but not the T7D promoter. Taken together, we conclude that although the overall sets of amino acid residues responsible for interaction with the two UP elements overlap, the mode of alphaCTD interaction with T7D UP element is different from that with rrnBP1 UP element, involving different residues on helices III and IV.

Algorithms for extracting structured motifs using a suffix tree with an application to promoter and regulatory site consensus identification

This paper introduces two exact algorithms for extracting conserved structured motifs from a set of DNA sequences. Structured motifs may be described as an ordered collection of p > or = 1 "boxes" (each box corresponding to one part of the structured motif), p substitution rates (one for each box) and p - 1 intervals of distance (one for each pair of successive boxes in the collection). The contents of the boxes--that is, the motifs themselves--are unknown at the start of the algorithm. This is precisely what the algorithms are meant to find. A suffix tree is used for finding such motifs. The algorithms are efficient enough to be able to infer site consensi, such as, for instance, promoter sequences or regulatory sites, from a set of unaligned sequences corresponding to the noncoding regions upstream from all genes of a genome. In particular, both algorithms time complexity scales linearly with N2n where n is the average length of the sequences and N their number. An application to the identification of promoter and regulatory consensus sequences in bacterial genomes is shown.

What makes an Escherichia coli promoter sigma(S) dependent? Role of the -13/-14 nucleotide promoter positions and region 2.5 of sigma(S)

The sigmaS and sigma70 subunits of Escherichia coli RNA polymerase recognize very similar promoter sequences. Therefore, many promoters can be activated by both holoenzymes in vitro. The same promoters, however, often exhibit distinct sigma factor selectivity in vivo. It has been shown that high salt conditions, reduced negative supercoiling and the formation of complex nucleoprotein structures in a promoter region can contribute to or even generate sigmaS selectivity. Here, we characterize the first positively acting sigmaS-selective feature in the promoter sequence itself. Using the sigmaS-dependent csiD promoter as a model system, we demonstrate that C and T at the -13 and -14 positions, respectively, result in strongest expression. We provide allele-specific suppression data indicating that these nucleotides are contacted by K173 in region 2.5 of sigmaS. In contrast, sigma70, which features a glutamate at the corresponding position (E458), as well as the sigmaS(K173E) variant, exhibit a preference for a G(-13). C(-13) is highly conserved in sigmaS-dependent promoters, and additional data with the osmY promoter demonstrate that the K173/C(-13) interaction is of general importance. In conclusion, our data demonstrate an important role for region 2.5 in sigmaS in transcription initiation. Moreover, we propose a consensus sequence for a sigmaS-selective promoter and discuss its emergence and functional properties from an evolutionary point of view.

Interaction of the C-terminal domain of the E. coli RNA polymerase alpha subunit with the UP element: recognizing the backbone structure in the minor groove surface

The C-terminal domain of the alpha-subunit of Escherichia coli RNA polymerase (alphaCTD) is responsible for transcriptional activation through interaction with both activator proteins and UP element DNA. Previously, we determined the solution structure of alphaCTD. Here, we investigated the interaction between alphaCTD and UP element DNA by NMR. DNA titration curves and intermolecular NOE measurements indicate that alphaCTD can bind to multiple sites on the UP element DNA. Unlike many transcription factors, alphaCTD does not have a strict base sequence requirement for binding. There is a good correlation between the strength of the interaction and the extent of intrinsic bending of the DNA oligomer estimated from the gel retardation assay. We propose that alphaCTD recognizes the backbone structure of DNA oligomers responsible for the intrinsic bending. Moreover, NMR studies and drug competition experiments indicated that alphaCTD interacts with the UP element on the minor groove side of the DNA. The C-terminal end of helix-1, the N-terminal end of helix-4, and the loop between helices 3 and 4 are used for the interaction. Based on these observations, we propose a model for the UP element-alphaCTD complex.

Dissection of two hallmarks of the open promoter complex by mutation in an RNA polymerase core subunit

Deletion of 10 evolutionarily conserved amino acids from the beta subunit of Escherichia coli RNA polymerase leads to a mutant enzyme that is unable to efficiently hold onto DNA. Open promoter complexes formed by the mutant enzyme are in rapid equilibrium with closed complexes and, unlike the wild-type complexes, are highly sensitive to the DNA competitor heparin (Martin, E., Sagitov, V., Burova, E., Nikiforov, V., and Goldfarb, A. (1992) J. Biol. Chem. 267, 20175-20180). Here we show that despite this instability, the mutant enzyme forms partially open complexes at temperatures as low as 0 degrees C when the wild-type complex is fully closed. Thus, the two hallmarks of the open promoter complex, the stability toward a challenge with DNA competitors and the sensitivity toward low temperature, can be uncoupled by mutation and may be independent in the wild-type complex. We use the high resolution structure of Thermus aquaticus RNA polymerase core to build a functional model of promoter complex formation that accounts for the observed defects of the E. coli RNA polymerase mutants.

DNA sequence elements located immediately upstream of the -10 hexamer in Escherichia coli promoters: a systematic study

We have made a systematic study of how the activity of an Escherichia coli promoter is affected by the base sequence immediately upstream of the -10 hexamer. Starting with an activator-independent promoter, with a 17 bp spacing between the -10 and -35 hexamer elements, we constructed derivatives with all possible combinations of bases at positions -15 and -14. Promoter activity is greatest when the 'non-template' strand carries T and G at positions -15 and -14, respectively. Promoter activity can be further enhanced by a second T and G at positions -17 and -16, respectively, immediately upstream of the first 'TG motif'. Our results show that the base sequence of the DNA segment upstream of the -10 hexamer can make a significant contribution to promoter strength. Using published collections of characterised E.coli promoters, we have studied the frequency of occurrence of 'TG motifs' upstream of the promoters' -10 elements. We conclude that correctly placed 'TG motifs' are found at over 20% of E.coli promoters.

Inferring regulatory elements from a whole genome. An analysis of Helicobacter pylori sigma(80) family of promoter signals

Helicobacter pylori is adapted to life in a unique niche, the gastric epithelium of primates. Its promoters may therefore be different from those of other bacteria. Here, we determine motifs possibly involved in the recognition of such promoter sequences by the RNA polymerase using a new motif identification method. An important feature of this method is that the motifs are sought with the least possible assumptions about what they may look like. The method starts by considering the whole genome of H. pylori and attempts to infer directly from it a description for a family of promoters. Thus, this approach differs from searching for such promoters with a previously established description. The two algorithms are based on the idea of inferring motifs by flexibly comparing words in the sequences with an external object, instead of between themselves. The first algorithm infers single motifs, the second a combination of two motifs separated from one another by strictly defined, sterically constrained distances. Besides independently finding motifs known to be present in other bacteria, such as the Shine-Dalgarno sequence and the TATA-box, this approach suggests the existence in H. pylori of a new, combined motif, TTAAGC, followed optimally 21 bp downstream by TATAAT. Between these two motifs, there is in some cases another, TTTTAA or, less frequently, a repetition of TTAAGC separated optimally from the TATA-box by 12 bp. The combined motif TTAAGCx(21+/-2)TATAAT is present with no errors immediately upstream from the only two copies of the ribosomal 23 S-5 S RNA genes in H. pylori, and with one error upstream from the only two copies of the ribosomal 16 S RNA genes. The operons of both ribosomal RNA molecules are strongly expressed, representing an encouraging sign of the pertinence of the motifs found by the algorithms. In 25 cases out of a possible 30, the combined motif is found with no more than three substitutions immediately upstream from ribosomal proteins, or operons containing a ribosomal protein. This is roughly the same frequency of occurrence as for TTGACAx(15-19)TATAAT (with the same maximum number of substitutions allowed) described as being the sigma(70 )promoter sequence consensus in Bacillus subtilis and Escherichia coli. The frequency of occurrence of the new motif obtained, TTAAGCx(19-23)TATAAT, remains high when all protein genes in H. pylori are considered, as is the case for the TTGACAx(15-19)TATAAT motif in B. subtilis but not in E. coli.

Transcription activation mediated by the carboxyl-terminal domain of the RNA polymerase alpha-subunit. Multipoint monitoring using a fluorescent probe

Conformational changes within the carboxyl-terminal domain of the Escherichia coli RNA polymerase alpha-subunit (alpha-CTD) upon interaction with the DNA UP element or the transcription factor cAMP receptor protein (CRP) were studied by monitoring the spectral parameters of a fluorescent dye, fluorescein mercuric acetate, conjugated to various positions of alpha-CTD. When fluorescein mercuric acetate was conjugated to Cys located on helix I and the loop between helices III and IV, the spectral changes typical for DNA interaction were observed for the RNA polymerase-promoter binary complex with UP element-dependent rrnBP1 and the ternary complex with the CRP-dependent uxuAB promoter in the presence of cAMP/CRP. Likewise, the chemical nuclease iron-(p-bromoacetamidobenzyl)-EDTA conjugated to Cys-269 or Cys-272 introduced CRP-dependent cleavage of the uxuAB promoter, as in the case of rrnBP1 (Murakami, K., Owens, J. T., Belyaeva, T. A., Meares, C. F., Busby, S. J. W., and Ishihama, A. (1997) Proc. Natl. Acad. Sci. U. S. A. 94, 11274-11278), indicating that CRP rearranges the topology of the DNA contact surface in alpha-CTD. Conformational changes in alpha-CTD were also observed upon formation of a binary complex with the uxuAB (in the absence of CRP) and factor-independent T7D promoters. The spectral changes suggested that helix IV of alpha-CTD approaches the negatively charged phosphate moiety of DNA. In agreement with this prediction, iron-(p-bromoacetamidobenzyl)-EDTA conjugated to Cys-309 induced extensive DNA cleavage upstream from the uxuAB promoter -35 element. We propose that helix IV of alpha-CTD is involved in direct interaction with some promoters.

Promoter sequences and algorithmical methods for identifying them

This paper presents a survey of currently available mathematical models and algorithmical methods for trying to identify promoter sequences. The methods concern both searching in a genome for a previously defined consensus and extracting a consensus from a set of sequences. Such methods were often tailored for either eukaryotes or prokaryotes although this does not preclude use of the same method for both types of organisms. The survey therefore covers all methods; however, emphasis is placed on prokaryotic promoter sequence identification. Illustrative applications of the main extracting algorithms are given for three bacteria.

A plasmid vector for isolation of strong promoters in Escherichia coli

In order to isolate very strong promoters from bacteria and bacteriophage a plasmid named pProm was constructed. It possesses an origin (ORI) for replication in Gram-negative bacteria, an ORI for replication in Gram-positive bacteria, a promoterless ampicillin resistance gene with a multiple cloning site (MCS) in the position formerly occupied by the ampicillin promoter, a tetracycline resistance gene for selection in Gram-negative bacteria and a chloramphenicol resistance gene for selection in Gram-positive bacteria. Insertion in the MCS of DNA fragments of Staphylococcus aureus bacteriophages resulted in isolation of several clones very resistant to ampicillin. The DNA fragments inserted in these recombinant plasmids were sequenced and all of them contained putative promoter motifs. Direct measurement of the penicillinase activity indicated that one of the isolated promoters could be included within a group of the stronger known prokaryotic promoters. According to these results pProm is a powerful tool to perform studies on promoter strength and for industrial applications.

Effect of mutations in the "extended -10" motif of three Bacillus subtilis sigmaA-RNA polymerase-dependent promoters

The "extended -10" motif described originally in Escherichia coli promoters occurs frequently in other bacterial promoters. Most Bacillus subtilis bacteriophage o29 promoters contain this motif. To analyse the influence of the motif on sigmaA-RNA polymerase transcription, the 5'-TG-3' dinucleotide was changed to 5'-AC-3' in three o29 promoters. This change impaired RNA polymerase binding to the promoters; the yields of closed and open complexes were reduced independently of other differences inherent to each promoter. The mutation abolished transcription in vitro from a promoter lacking the consensus sequence at the -35 hexamer. In contrast, at other promoters with a -35 consensus sequence, the yield of run off transcription was not reduced by the mutation. Indeed an apparent interference phenomenon at high polymerase/DNA ratios was relieved. These results indicate that the extended -10 motif provides contact points for sigmaA-RNA polymerase with a role restricted to the first steps of transcription.

DNA bendability--a novel feature in E. coli promoter recognition

The distribution of deformable base-pair steps in the structure of bacterial promoters is analyzed with respect to their possible structural and functional role. A regular positioning of TA and TG stacks is detected with the best fit period 5.6 bp. This value is interpreted as a half of the sequence period 11.2 bp, somewhat higher than the structural helical repeat of B-DNA (10.55 bp). The difference, +0.65 bp, suggests a sequence-dependent helical writhe of the promoter DNA--a right-handed superhelix. Apparently, to favour rotational setting of DNA on the surface of RNA polymerase the flexible steps deformable largely towards the grooves, follow the half-period spacing. Such rotational setting is consistent with the DNase I footprinting data. Periodical distribution of deformable base-pair stacks shows negative correlation with the presence of -35 canonical hexamer, suggesting the functional significance of this novel element for promoter recognition. The RNA polymerase--DNA recognition is discussed as interaction of distributional type that involves many elements of different nature which are in partially compensatory relations.

Upstream A-tracts increase bacterial promoter activity through interactions with the RNA polymerase alpha subunit

Upstream A-tracts stimulate transcription from a variety of bacterial promoters, and this has been widely attributed to direct effects of the intrinsic curvature of A-tract-containing DNA. In this work we report experiments that suggest a different mechanism for the effects of upstream A-tracts on transcription. The similarity of A-tract-containing sequences to the adenine- and thymine-rich upstream recognition elements (UP elements) found in some bacterial promoters suggested that A-tracts might increase promoter activity by interacting with the alpha subunit of RNA polymerase (RNAP). We found that an A-tract-containing sequence placed upstream of the Escherichia coli lac or rrnB P1 promoters stimulated transcription both in vivo and in vitro, and that this stimulation required the C-terminal (DNA-binding) domain of the RNAP alpha subunit. The A-tract sequence was protected by wild-type RNAP but not by alpha-mutant RNAPs in footprints. The effect of the A-tracts on transcription was not as great as that of the most active UP elements, consistent with the degree of similarity of the A-tract sequence to the UP element consensus. A-tracts functioned best when positioned close to the -35 hexamer rather than one helical turn farther upstream, similar to the positioning optimal for UP element function. We conclude that A-tracts function as UP elements, stimulating transcription by providing binding site(s) for the RNAP alphaCTD, and we suggest that these interactions could contribute to the previously described wrapping of promoter DNA around RNAP.

Escherichia coli promoters with UP elements of different strengths: modular structure of bacterial promoters

The alpha subunit of Escherichia coli RNA polymerase (RNAP) participates in promoter recognition through specific interactions with UP element DNA, a region upstream of the recognition hexamers for the sigma subunit (the -10 and -35 hexamers). UP elements have been described in only a small number of promoters, including the rRNA promoter rrnB P1, where the sequence has a very large (30- to 70-fold) effect on promoter activity. Here, we analyzed the effects of upstream sequences from several additional E. coli promoters (rrnD P1, rrnB P2, lambda pR, lac, merT, and RNA II). The relative effects of different upstream sequences were compared in the context of their own core promoters or as hybrids to the lac core promoter. Different upstream sequences had different effects, increasing transcription from 1.5- to approximately 90-fold, and several had the properties of UP elements: they increased transcription in vitro in the absence of accessory protein factors, and transcription stimulation required the C-terminal domain of the RNAP alpha subunit. The effects of the upstream sequences correlated generally with their degree of similarity to an UP element consensus sequence derived previously. Protection of upstream sequences by RNAP in footprinting experiments occurred in all cases and was thus not a reliable indicator of UP element strength. These data support a modular view of bacterial promoters in which activity reflects the composite effects of RNAP interactions with appropriately spaced recognition elements (-10, -35, and UP elements), each of which contributes to activity depending on its similarity to the consensus.

Identification of an UP element consensus sequence for bacterial promoters

The UP element, a component of bacterial promoters located upstream of the -35 hexamer, increases transcription by interacting with the RNA polymerase alpha-subunit. By using a modification of the SELEX procedure for identification of protein-binding sites, we selected in vitro and subsequently screened in vivo for sequences that greatly increased promoter activity when situated upstream of the Escherichia coli rrnB P1 core promoter. A set of 31 of these upstream sequences increased transcription from 136- to 326-fold in vivo, considerably more than the natural rrnB P1 UP element, and was used to derive a consensus sequence: -59 nnAAA(A/T)(A/T)T(A/T)TTTTnnAAAAnnn -38. The most active selected sequence contained the derived consensus, displayed all of the properties of an UP element, and the interaction of this sequence with the alpha C-terminal domain was similar to that of previously characterized UP elements. The identification of the UP element consensus should facilitate a detailed understanding of the alpha-DNA interaction. Based on the evolutionary conservation of the residues in alpha responsible for interaction with UP elements, we suggest that the UP element consensus sequence should be applicable throughout eubacteria, should generally facilitate promoter prediction, and may be of use for biotechnological applications.