Differential ability of σs and σ70 of Escherichia coli to utilize promoters containing half or full UP-element sites

PromoterLCNN: A Light CNN-Based Promoter Prediction and Classification Model

Promoter identification is a fundamental step in understanding bacterial gene regulation mechanisms. However, accurate and fast classification of bacterial promoters continues to be challenging. New methods based on deep convolutional networks have been applied to identify and classify bacterial promoters recognized by sigma (σ) factors and RNA polymerase subunits which increase affinity to specific DNA sequences to modulate transcription and respond to nutritional or environmental changes. This work presents a new multiclass promoter prediction model by using convolutional neural networks (CNNs), denoted as PromoterLCNN, which classifies Escherichia coli promoters into subclasses σ70, σ24, σ32, σ38, σ28, and σ54. We present a light, fast, and simple two-stage multiclass CNN architecture for promoter identification and classification. Training and testing were performed on a benchmark dataset, part of RegulonDB. Comparative performance of PromoterLCNN against other CNN-based classifiers using four parameters (Acc, Sn, Sp, MCC) resulted in similar or better performance than those that commonly use cascade architecture, reducing time by approximately 30–90% for training, prediction, and hyperparameter optimization without compromising classification quality.

Benchmarking Bacterial Promoter Prediction Tools: Potentialities and Limitations

The correct mapping of promoter elements is a crucial step in microbial genomics. Also, when combining new DNA elements into synthetic sequences, predicting the potential generation of new promoter sequences is critical. Over the last years, many bioinformatics tools have been created to allow users to predict promoter elements in a sequence or genome of interest. Here, we assess the predictive power of some of the main prediction tools available using well-defined promoter data sets. Using Escherichia coli as a model organism, we demonstrated that while some tools are biased toward AT-rich sequences, others are very efficient in identifying real promoters with low false-negative rates. We hope the potentials and limitations presented here will help the microbiology community to choose promoter prediction tools among many available alternatives.

The promoter region is a key element required for the production of RNA in bacteria. While new high-throughput technology allows massively parallel mapping of promoter elements, we still mainly rely on bioinformatics tools to predict such elements in bacterial genomes. Additionally, despite many different prediction tools having become popular to identify bacterial promoters, no systematic comparison of such tools has been performed. Here, we performed a systematic comparison between several widely used promoter prediction tools (BPROM, bTSSfinder, BacPP, CNNProm, IBBP, Virtual Footprint, iPro70-FMWin, 70ProPred, iPromoter-2L, and MULTiPly) using well-defined sequence data sets and standardized metrics to determine how well those tools performed related to each other. For this, we used data sets of experimentally validated promoters from Escherichia coli and a control data set composed of randomly generated sequences with similar nucleotide distributions. We compared the performance of the tools using metrics such as specificity, sensitivity, accuracy, and Matthews correlation coefficient (MCC). We show that the widely used BPROM presented the worse performance among the compared tools, while four tools (CNNProm, iPro70-FMWin, 70ProPred, and iPromoter-2L) offered high predictive power. Of these tools, iPro70-FMWin exhibited the best results for most of the metrics used. We present here some potentials and limitations of available tools, and we hope that future work can build upon our effort to systematically characterize this useful class of bioinformatics tools.

IMPORTANCE The correct mapping of promoter elements is a crucial step in microbial genomics. Also, when combining new DNA elements into synthetic sequences, predicting the potential generation of new promoter sequences is critical. Over the last years, many bioinformatics tools have been created to allow users to predict promoter elements in a sequence or genome of interest. Here, we assess the predictive power of some of the main prediction tools available using well-defined promoter data sets. Using Escherichia coli as a model organism, we demonstrated that while some tools are biased toward AT-rich sequences, others are very efficient in identifying real promoters with low false-negative rates. We hope the potentials and limitations presented here will help the microbiology community to choose promoter prediction tools among many available alternatives.

Coherent Domains of Transcription Coordinate Gene Expression During Bacterial Growth and Adaptation

Recent studies strongly suggest that in bacteria, both the genomic pattern of DNA thermodynamic stability and the order of genes along the chromosomal origin-to-terminus axis are highly conserved and that this spatial organization plays a crucial role in coordinating genomic transcription. In this article, we explore the relationship between genomic sequence organization and transcription in the commensal bacterium Escherichia coli and the plant pathogen Dickeya. We argue that, while in E. coli the gradient of DNA thermodynamic stability and gene order along the origin-to-terminus axis represent major organizational features orchestrating temporal gene expression, the genomic sequence organization of Dickeya is more complex, demonstrating extended chromosomal domains of thermodynamically distinct DNA sequences eliciting specific transcriptional responses to various kinds of stress encountered during pathogenic growth. This feature of the Dickeya genome is likely an adaptation to the pathogenic lifestyle utilizing differences in genomic sequence organization for the selective expression of virulence traits. We propose that the coupling of DNA thermodynamic stability and genetic function provides a common organizational principle for the coordinated expression of genes during both normal and pathogenic bacterial growth.

The Escherichia coli MarA protein regulates the ycgZ-ymgABC operon to inhibit biofilm formation

The Escherichia coli marRAB operon is a paradigm for chromosomally encoded antibiotic resistance. The operon exerts its effect via an encoded transcription factor called MarA that modulates efflux pump and porin expression. In this work, we show that MarA is also a regulator of biofilm formation. Control is mediated by binding of MarA to the intergenic region upstream of the ycgZ-ymgABC operon. The operon, known to influence the formation of curli fibres and colanic acid, is usually expressed during periods of starvation. Hence, the ycgZ-ymgABC promoter is recognised by σ³⁸ (RpoS)-associated RNA polymerase (RNAP). Surprisingly, MarA does not influence σ³⁸ -dependent transcription. Instead, MarA drives transcription by the housekeeping σ⁷⁰ -associated RNAP. The effects of MarA on ycgZ-ymgABC expression are coupled with biofilm formation by the rcsCDB phosphorelay system, with YcgZ, YmgA and YmgB forming a complex that directly interacts with the histidine kinase domain of RcsC.

Analysis of the nucleotide content of Escherichia coli promoter sequences related to the alternative sigma factors

Promoters are DNA sequences located upstream of the transcription start site of genes. In bacteria, the RNA polymerase enzyme requires additional subunits, called sigma factors (σ) to begin specific gene transcription in distinct environmental conditions. Currently, promoter prediction still poses many challenges due to the characteristics of these sequences. In this paper, the nucleotide content of Escherichia coli promoter sequences, related to five alternative σ factors, was analyzed by a machine learning technique in order to provide profiles according to the σ factor which recognizes them. For this, the clustering technique was applied since it is a viable method for finding hidden patterns on a data set. As a result, 20 groups of sequences were formed, and, aided by the Weblogo tool, it was possible to determine sequence profiles. These found patterns should be considered for implementing computational prediction tools. In addition, evidence was found of an overlap between the functions of the genes regulated by different σ factors, suggesting that DNA structural properties are also essential parameters for further studies.

Transcription Initiation by Mix and Match Elements: Flexibility for Polymerase Binding to Bacterial Promoters

Bacterial RNA polymerase is composed of a core of subunits (β β′, α1, α2, ω), which have RNA synthesizing activity, and a specificity factor (σ), which identifies the start of transcription by recognizing and binding to sequence elements within promoter DNA. Four core promoter consensus sequences, the –10 element, the extended –10 (TGn) element, the –35 element, and the UP elements, have been known for many years; the importance of a nontemplate G at position -5 has been recognized more recently. However, the functions of these elements are not the same. The AT-rich UP elements, the –35 elements (–35TTGACA–30), and the extended –10 (15TGn–13) are recognized as double-stranded binding elements, whereas the –5 nontemplate G is recognized in the context of single-stranded DNA at the transcription bubble. Furthermore, the –10 element (–12TATAAT–7) is recognized as both double-stranded DNA for the T:A bp at position –12 and as nontemplate, single-stranded DNA from positions –11 to –7. The single-stranded sequences at positions –11 to –7 as well as the –5 contribute to later steps in transcription initiation that involve isomerization of polymerase and separation of the promoter DNA around the transcription start site. Recent work has demonstrated that the double-stranded elements may be used in various combinations to yield an effective promoter. Thus, while some minimal number of contacts is required for promoter function, polymerase allows the elements to be mixed and matched. Interestingly, which particular elements are used does not appear to fundamentally alter the transcription bubble generated in the stable complex. In this review, we discuss the multiple steps involved in forming a transcriptionally competent polymerase/promoter complex, and we examine what is known about polymerase recognition of core promoter elements. We suggest that considering promoter elements according to their involvement in early (polymerase binding) or later (polymerase isomerization) steps in transcription initiation rather than simply from their match to conventional promoter consensus sequences is a more instructive form of promoter classification.

Vertical stratification of matrix production is essential for physical integrity and architecture of macrocolony biofilms of Escherichia coli

Bacterial macrocolony biofilms grow into intricate three-dimensional structures that depend on self-produced extracellular polymers conferring protection, cohesion and elasticity to the biofilm. In Escherichia coli, synthesis of this matrix - consisting of amyloid curli fibres and cellulose - requires CsgD, a transcription factor regulated by the stationary phase sigma factor RpoS, and occurs in the nutrient-deprived cells of the upper layer of macrocolonies. Is this asymmetric matrix distribution functionally important or is it just a fortuitous by-product of an unavoidable nutrient gradient? In order to address this question, the RpoS-dependent csgD promoter was replaced by a vegetative promoter. This re-wiring of csgD led to CsgD and matrix production in both strata of macrocolonies, with the lower layer transforming into a rigid 'base plate' of growing yet curli-connected cells. As a result, the two strata broke apart followed by desiccation and exfoliation of the top layer. By contrast, matrix-free cells at the bottom of wild-type macrocolonies maintain colony contact with the humid agar support by flexibly filling the space that opens up under buckling areas of the macrocolony. Precisely regulated stratification in matrix-free and matrix-producing cell layers is thus essential for the physical integrity and architecture of E. coli macrocolony biofilms.

sigmaS, a major player in the response to environmental stresses in Escherichia coli: role, regulation and mechanisms of promoter recognition

Bacterial cells often face hostile environmental conditions, to which they adapt by activation of stress responses. In Escherichia coli, environmental stresses resulting in significant reduction in growth rate stimulate the expression of the rpoS gene, encoding the alternative σ factor σ(S). The σ(S) protein associates with RNA polymerase, and through transcription of genes belonging to the rpoS regulon allows the activation of a 'general stress response', which protects the bacterial cell from harmful environmental conditions. Each step of this process is finely tuned in order to cater to the needs of the bacterial cell: in particular, selective promoter recognition by σ(S) is achieved through small deviations from a common consensus DNA sequence for both σ(S) and the housekeeping σ(70). Recognition of specific DNA elements by σ(S) is integrated with the effects of environmental signals and the interaction with regulatory proteins, in what represents a fascinating example of multifactorial regulation of gene expression. In this report, we discuss the function of the rpoS gene in the general stress response, and review the current knowledge on regulation of rpoS expression and on promoter recognition by σ(S).

Predicting the strength of UP-elements and full-length E. coli σE promoters

Predicting the location and strength of promoters from genomic sequence requires accurate sequenced-based promoter models. We present the first model of a full-length bacterial promoter, encompassing both upstream sequences (UP-elements) and core promoter modules, based on a set of 60 promoters dependent on σ(E), an alternative ECF-type σ factor. UP-element contribution, best described by the length and frequency of A- and T-tracts, in combination with a PWM-based core promoter model, accurately predicted promoter strength both in vivo and in vitro. This model also distinguished active from weak/inactive promoters. Systematic examination of promoter strength as a function of RNA polymerase (RNAP) concentration revealed that UP-element contribution varied with RNAP availability and that the σ(E) regulon is comprised of two promoter types, one of which is active only at high concentrations of RNAP. Distinct promoter types may be a general mechanism for increasing the regulatory capacity of the ECF group of alternative σ's. Our findings provide important insights into the sequence requirements for the strength and function of full-length promoters and establish guidelines for promoter prediction and for forward engineering promoters of specific strengths.

Stationary-Phase Gene Regulation in Escherichia coli §

In their stressful natural environments, bacteria often are in stationary phase and use their limited resources for maintenance and stress survival. Underlying this activity is the general stress response, which in Escherichia coli depends on the σS (RpoS) subunit of RNA polymerase. σS is closely related to the vegetative sigma factor σ70 (RpoD), and these two sigmas recognize similar but not identical promoter sequences. During the postexponential phase and entry into stationary phase, σS is induced by a fine-tuned combination of transcriptional, translational, and proteolytic control. In addition, regulatory "short-cuts" to high cellular σS levels, which mainly rely on the rapid inhibition of σS proteolysis, are triggered by sudden starvation for various nutrients and other stressful shift conditons. σS directly or indirectly activates more than 500 genes. Additional signal input is integrated by σS cooperating with various transcription factors in complex cascades and feedforward loops. Target gene products have stress-protective functions, redirect metabolism, affect cell envelope and cell shape, are involved in biofilm formation or pathogenesis, or can increased stationary phase and stress-induced mutagenesis. This review summarizes these diverse functions and the amazingly complex regulation of σS. At the molecular level, these processes are integrated with the partitioning of global transcription space by sigma factor competition for RNA polymerase core enzyme and signaling by nucleotide second messengers that include cAMP, (p)ppGpp, and c-di-GMP. Physiologically, σS is the key player in choosing between a lifestyle associated with postexponential growth based on nutrient scavenging and motility and a lifestyle focused on maintenance, strong stress resistance, and increased adhesiveness. Finally, research with other proteobacteria is beginning to reveal how evolution has further adapted function and regulation of σS to specific environmental niches.

Structural coupling between RNA polymerase composition and DNA supercoiling in coordinating transcription: a global role for the omega subunit?

In growing bacterial cells, the global reorganization of transcription is associated with alterations of RNA polymerase composition and the superhelical density of the DNA. However, the existence of any regulatory device coordinating these changes remains elusive. Here we show that in an exponentially growing Escherichia coli rpoZ mutant lacking the polymerase ω subunit, the impact of the Eσ(38) holoenzyme on transcription is enhanced in parallel with overall DNA relaxation. Conversely, overproduction of σ(70) in an rpoZ mutant increases both overall DNA supercoiling and the transcription of genes utilizing high negative superhelicity. We further show that transcription driven by the Eσ(38) and Eσ(70) holoenzymes from cognate promoters induces distinct superhelical densities of plasmid DNA in vivo. We thus demonstrate a tight coupling between polymerase holoenzyme composition and the supercoiling regimen of genomic transcription. Accordingly, we identify functional clusters of genes with distinct σ factor and supercoiling preferences arranging alternative transcription programs sustaining bacterial exponential growth. We propose that structural coupling between DNA topology and holoenzyme composition provides a basic regulatory device for coordinating genome-wide transcription during bacterial growth and adaptation. IMPORTANCE Understanding the mechanisms of coordinated gene expression is pivotal for developing knowledge-based approaches to manipulating bacterial physiology, which is a problem of central importance for applications of biotechnology and medicine. This study explores the relationships between variations in the composition of the transcription machinery and chromosomal DNA topology and suggests a tight interdependence of these two variables as the major coordinating principle of gene regulation. The proposed structural coupling between the transcription machinery and DNA topology has evolutionary implications and suggests a new methodology for studying concerted alterations of gene expression during normal and pathogenic growth both in bacteria and in higher organisms.

In vitro transcription profiling of the σS subunit of bacterial RNA polymerase: re-definition of the σS regulon and identification of σS-specific promoter sequence elements

Specific promoter recognition by bacterial RNA polymerase is mediated by σ subunits, which assemble with RNA polymerase core enzyme (E) during transcription initiation. However, σ⁷⁰ (the housekeeping σ subunit) and σ^S (an alternative σ subunit mostly active during slow growth) recognize almost identical promoter sequences, thus raising the question of how promoter selectivity is achieved in the bacterial cell. To identify novel sequence determinants for selective promoter recognition, we performed run-off/microarray (ROMA) experiments with RNA polymerase saturated either with σ⁷⁰ (Eσ⁷⁰) or with σ^S (Eσ^S) using the whole Escherichia coli genome as DNA template. We found that Eσ⁷⁰, in the absence of any additional transcription factor, preferentially transcribes genes associated with fast growth (e.g. ribosomal operons). In contrast, Eσ^S efficiently transcribes genes involved in stress responses, secondary metabolism as well as RNAs from intergenic regions with yet-unknown function. Promoter sequence comparison suggests that, in addition to different conservation of the −35 sequence and of the UP element, selective promoter recognition by either form of RNA polymerase can be affected by the A/T content in the −10/+1 region. Indeed, site-directed mutagenesis experiments confirmed that an A/T bias in the −10/+1 region could improve promoter recognition by Eσ^S.

Characterization of the relationship between integrase, excisionase and antirepressor activities associated with a superinfecting Shiga toxin encoding bacteriophage

Shigatoxigenic Escherichia coli emerged as new food borne pathogens in the early 1980s, primarily driven by the dispersal of Shiga toxin-encoding lambdoid bacteriophages. At least some of these Stx phages display superinfection phenotypes, which differ significantly from lambda phage itself, driving through in situ recombination further phage evolution, increasing host range and potentially increasing the host's pathogenic profile. Here, increasing levels of Stx phage Φ24(B) integrase expression in multiple lysogen cultures are demonstrated along with apparently negligible repression of integrase expression by the cognate CI repressor. The Φ24(B) int transcription start site and promoter region were identified and found to differ from in silico predictions. The unidirectional activity of this integrase was determined in an in situ, inducible tri-partite reaction. This indicated that Φ24(B) must encode a novel directionality factor that is controlling excision events during prophage induction. This excisionase was subsequently identified and characterized through complementation experiments. In addition, the previous proposal that a putative antirepressor was responsible for the lack of immunity to superinfection through inactivation of CI has been revisited and a new hypothesis involving the role of this protein in promoting efficient induction of the Φ24(B) prophage is proposed.

A sequence that affects the copy number and stability of pSW200 and ColE1

Pantoea stewartii SW2 contains 13 plasmids. One of these plasmids, pSW200, has a replicon that resembles that of ColE1. This study demonstrates that pSW200 contains a 9-bp UP element, 5'-AAGATCTTC, which is located immediately upstream of the -35 box in the RNAII promoter. A transcriptional fusion study reveals that substituting this 9-bp sequence reduces the activity of the RNAII promoter by 78%. The same mutation also reduced the number of plasmid copies from 13 to 5, as well as the plasmid stability. When a similar sequence in a ColE1 derivative, pYCW301, is mutated, the copy number of the plasmid also declines from 34 to 16 per cell. Additionally, inserting this 9-bp sequence stabilizes an unstable pSW100 derivative, pSW142K, which also contains a replicon resembling that of ColE1, indicating the importance of this sequence in maintaining the stability of the plasmid. In conclusion, the 9-bp sequence upstream of the -35 box in the RNAII promoter is required for the efficient synthesis of RNAII and maintenance of the stability of the plasmids in the ColE1 family.

General organisational principles of the transcriptional regulation system: a tree or a circle?

Recent advances of systemic approaches to gene expression and cellular metabolism provide unforeseen opportunities for relating and integrating extensive datasets describing the transcriptional regulation system as a whole. However, due to the multifaceted nature of the phenomenon, these datasets often contain logically distinct types of information determined by underlying approach and adopted methodology of data analysis. Consequently, to integrate the datasets comprising information on the states of chromatin structure, transcriptional regulatory network and cellular metabolism, a novel methodology enabling interconversion of logically distinct types of information is required. Here we provide a holistic conceptual framework for analysis of global transcriptional regulation as a system coordinated by structural coupling between the transcription machinery and DNA topology, acting as interdependent sensors and determinants of metabolic functions. In this operationally closed system any transition in physiological state represents an emergent property determined by shifts in structural coupling, whereas genetic regulation acts as a genuine device converting one logical type of information into the other.

Predicting strength and function for promoters of the Escherichia coli alternative sigma factor, sigmaE

Sequenced bacterial genomes provide a wealth of information but little understanding of transcriptional regulatory circuits largely because accurate prediction of promoters is difficult. We examined two important issues for accurate promoter prediction: (1) the ability to predict promoter strength and (2) the sequence properties that distinguish between active and weak/inactive promoters. We addressed promoter prediction using natural core promoters recognized by the well-studied alternative sigma factor, Escherichia coli sigma(E), as a representative of group 4 sigmas, the largest sigma group. To evaluate the contribution of sequence to promoter strength and function, we used modular position weight matrix models comprised of each promoter motif and a penalty score for suboptimal motif location. We find that a combination of select modules is moderately predictive of promoter strength and that imposing minimal motif scores distinguished active from weak/inactive promoters. The combined -35/-10 score is the most important predictor of activity. Our models also identified key sequence features associated with active promoters. A conserved "AAC" motif in the -35 region is likely to be a general predictor of function for promoters recognized by group 4 sigmas. These results provide valuable insights into sequences that govern promoter strength, distinguish active and inactive promoters for the first time, and are applicable to both in vivo and in vitro measures of promoter strength.

Analysis of the RpoS regulon in Borrelia burgdorferi in response to mammalian host signals provides insight into RpoS function during the enzootic cycle

Borrelia burgdorferi (Bb) adapts to its arthropod and mammalian hosts by altering its transcriptional and antigenic profiles in response to environmental signals associated with each of these milieus. In studies presented here, we provide evidence to suggest that mammalian host signals are important for modulating and maintaining both the positive and negative aspects of mammalian host adaptation mediated by the alternative sigma factor RpoS in Bb. Although considerable overlap was observed between genes induced by RpoS during growth within the mammalian host and following temperature-shift, comparative microarray analyses demonstrated unequivocally that RpoS-mediated repression requires mammalian host-specific signals. A substantial portion of the in vivo RpoS regulon was uniquely upregulated within dialysis membrane chambers, further underscoring the importance of host-derived environmental stimuli for differential gene expression in Bb. Expression profiling of genes within the RpoS regulon by quantitative reverse transcription polymerase chain reaction (qRT-PCR) revealed a level of complexity to RpoS-dependent gene regulation beyond that observed by microarray, including a broad range of expression levels and the presence of genes whose expression is only partially dependent on RpoS. Analysis of Bb-infected ticks by qRT-PCR established that expression of rpoS is induced during the nymphal blood meal but not within unfed nymphs or engorged larvae. Together, these data have led us to postulate that RpoS acts as a gatekeeper for the reciprocal regulation of genes involved in the establishment of infection within the mammalian host and the maintenance of spirochetes within the arthropod vector.

SbcCD regulation and localization in Escherichia coli

The SbcCD complex and its homologues play important roles in DNA repair and in the maintenance of genome stability. In Escherichia coli, the in vitro functions of SbcCD have been well characterized, but its exact cellular role remains elusive. This work investigates the regulation of the sbcDC operon and the cellular localization of the SbcC and SbcD proteins. Transcription of the sbcDC operon is shown to be dependent on starvation and RpoS protein. Overexpressed SbcC protein forms foci that colocalize with the replication factory, while overexpressed SbcD protein is distributed through the cytoplasm.

Cellular levels and activity of the flagellar sigma factor FliA of Escherichia coli are controlled by FlgM-modulated proteolysis

In Escherichia coli the flagellar regulon consists of more than 60 genes organized in three hierarchically and temporally regulated transcriptional classes. The flagellar sigma factor FliA (sigma(28)) is responsible for class 3 expression and, in the early phase of flagellar assembly, is inhibited by its anti-sigma factor FlgM. The flagellar hook basal body forms a type III secretion system capable of secreting both flagellar subunits and FlgM. This results in release and therefore activation of FliA and class 3 expression. Here we demonstrate that FliA is also subject to proteolysis which mainly depends on Lon protease. FlgM not only acts as an anti-sigma factor but also protects FliA from being degraded. Based on quantitative measurements over time upon experimental induction of the flagellar cascade as well as during the growth cycle of a motile strain, we show that FliA proteolysis increases in parallel to class 3 expression, i.e. correlates with FlgM secretion and the phase of highest activity of FliA. Thus, when FlgM is not available due to secretion or mutation, and with RNA polymerase interaction being only transient during the transcription initiation cycle, the proteases can degrade FliA. Experiments with a lon mutant indicate that Lon protease and FliA degradation maintain appropriate FliA : FlgM stoichiometry upon induction of the flagellar system and thereby contribute to timely shut-off of this system.

The molecular basis of selective promoter activation by the ?Ssubunit of RNA polymerase

Different environmental stimuli cause bacteria to exchange the sigma subunit in the RNA polymerase (RNAP) and, thereby, tune their gene expression according to the newly emerging needs. Sigma factors are usually thought to recognize clearly distinguishable promoter DNA determinants, and thereby activate distinct gene sets, known as their regulons. In this review, we illustrate how the principle sigma factor in stationary phase and in stressful conditions in Escherichia coli, sigmaS (RpoS), can specifically target its large regulon in vivo, although it is known to recognize the same core promoter elements in vitro as the housekeeping sigma factor, sigma70 (RpoD). Variable combinations of cis-acting promoter features and trans-acting protein factors determine whether a promoter is recognized by RNAP containing sigmaS or sigma70, or by both holoenzymes. How these promoter features impose sigmaS selectivity is further discussed. Moreover, additional pathways allow sigmaS to compete more efficiently than sigma70 for limiting amounts of core RNAP (E) and thereby enhance EsigmaS formation and effectiveness. Finally, these topics are discussed in the context of sigma factor evolution and the benefits a cell gains from retaining competing and closely related sigma factors with overlapping sets of target genes.

The sigmaS subunit of RNA polymerase as a signal integrator and network master regulator in the general stress response in Escherichia coli

The sigmaS (RpoS) subunit of RNA polymerase in Escherichia coli is a key master regulator which allows this bacterial model organism and important pathogen to adapt to and survive environmentally rough times. While hardly present in rapidly growing cells, sigmaS strongly accumulates in response to many different stress conditions, partly replaces the vegetative sigma subunit in RNA polymerase and thereby reprograms this enzyme to transcribe sigmaS-dependent genes (up to 10% of the E. coli genes). In this review, we summarize the extremely complex regulation of sigmaS itself and multiple signal input at the level of this master regulator, we describe the way in which sigmaS specifically recognizes "stress" promoters despite their similarity to vegetative promoters, and, while being far from comprehensive, we give a short overview of the far-reaching physiological impact of sigmaS. With sigmaS being a central and multiple signal integrator and master regulator of hundreds of genes organized in regulatory cascades and sub-networks or regulatory modules, this system also represents a key model system for analyzing complex cellular information processing and a starting point for understanding the complete regulatory network of an entire cell.

Selective promoter recognition by chlamydial sigma28 holoenzyme

The sigma transcription factor confers the promoter recognition specificity of RNA polymerase (RNAP) in eubacteria. Chlamydia trachomatis has three known sigma factors, sigma(66), sigma(54), and sigma(28). We developed two methods to facilitate the characterization of promoter sequences recognized by C. trachomatis sigma(28) (sigma(28)(Ct)). One involved the arabinose-induced expression of plasmid-encoded sigma(28)(Ct) in a strain of Escherichia coli defective in the sigma(28) structural gene, fliA. The second was an analysis of transcription in vitro with a hybrid holoenzyme reconstituted with E. coli RNAP core and recombinant sigma(28)(Ct). These approaches were used to investigate the interactions of sigma(28)(Ct) with the sigma(28)(Ct)-dependent hctB promoter and selected E. coli sigma(28) (sigma(28)(Ec))-dependent promoters, in parallel, compared with the promoter recognition properties of sigma(28)(EC). Our results indicate that RNAP containing sigma(28)(Ct) has at least three characteristics: (i) it is capable of recognizing some but not all sigma(28)(EC)-dependent promoters; (ii) it can distinguish different promoter structures, preferentially activating promoters with upstream AT-rich sequences; and (iii) it possesses a greater flexibility than sigma(28)(EC) in recognizing variants with different spacing lengths separating the -35 and -10 elements of the core promoter.

Regulon and promoter analysis of the E. coli heat-shock factor, sigma32, reveals a multifaceted cellular response to heat stress

The heat-shock response (HSR), a universal cellular response to heat, is crucial for cellular adaptation. In Escherichia coli, the HSR is mediated by the alternative sigma factor, sigma32. To determine its role, we used genome-wide expression analysis and promoter validation to identify genes directly regulated by sigma32 and screened ORF overexpression libraries to identify sigma32 inducers. We triple the number of genes validated to be transcribed by sigma32 and provide new insights into the cellular role of this response. Our work indicates that the response is propagated as the regulon encodes numerous global transcriptional regulators, reveals that sigma70 holoenzyme initiates from 12% of sigma32 promoters, which has important implications for global transcriptional wiring, and identifies a new role for the response in protein homeostasis, that of protecting complex proteins. Finally, this study suggests that the response protects the cell membrane and responds to its status: Fully 25% of sigma32 regulon members reside in the membrane and alter its functionality; moreover, a disproportionate fraction of overexpressed proteins that induce the response are membrane localized. The intimate connection of the response to the membrane rationalizes why a major regulator of the response resides in that cellular compartment.

Computational prediction of RpoS and RpoD regulatory sites in Geobacter sulfurreducens using sequence and gene expression information

RpoS, the sigma S subunit of RNA polymerase, is vital during the growth and survival of Geobacter sulfurreducens under conditions typically encountered in its native subsurface environments. We investigated the conservation of sites that may be important for RpoS function in G. sulfurreducens. We also employed sequence information and expression microarray data to predict G. sulfurreducens genome sites that may be related to RpoS regulation. Hierarchical clustering identified three clusters of significantly downregulated genes in the rpoS deletion mutant. The search for conserved overrepresented motifs in co-regulated operons identified likely -35 and -10 promoter elements upstream of a number of functionally important G. sulfurreducens operons that were downregulated in the rpoS deletion mutant. Putative -35/-10 promoter elements were also identified in the G. sulfurreducens genome using sequence similarity searches to matrices of -35/-10 promoter elements found in G. sulfurreducens and in Escherichia coli. Due to a sufficient degree of sequence similarity between -35/-10 promoter elements for RpoS, RpoD, and other sigma factors, both the sequence similarity searches and the search for conserved overrepresented motifs using microarray data may identify promoter elements for both RpoS and other sigma factors.

Regulation of RraA, a protein inhibitor of RNase E-mediated RNA decay

The recently discovered RraA protein acts as an inhibitor of the essential endoribonuclease RNase E, and we demonstrated that ectopic expression of RraA affects the abundance of more than 700 transcripts in Escherichia coli (K. Lee, X. Zhan, J. Gao, J. Qiu, Y. Feng, R. Meganathan, S. N. Cohen, and G. Georgiou, Cell 114:623-634, 2003). We show that rraA is expressed from its own promoter, P(rraA), located in the menA-rraA intergenic region. Primer extension and lacZ fusion analysis revealed that transcription from P(rraA) is elevated upon entry into stationary phase in a sigma(s)-dependent manner. In addition, the stability of the rraA transcript is dependent on RNase E activity, suggesting the involvement of a feedback circuit in the regulation of the RraA level in E. coli.

Sigma factor selectivity in Borrelia burgdorferi: RpoS recognition of the ospE/ospF/elp promoters is dependent on the sequence of the -10 region

Members of the ospE/ospF/elp lipoprotein gene families of Borrelia burgdorferi, the Lyme disease agent, are transcriptionally upregulated in response to the influx of blood into the midgut of an infected tick. We recently have demonstrated that despite the high degree of similarity between the promoters of the ospF (P(ospF)) and ospE (P(ospE)) genes of B. burgdorferi strain 297, the differential expression of ospF is RpoS-dependent, while ospE is controlled by sigma(70). Herein we used wild-type and RpoS-deficient strains of B. burgdorferi and Escherichia coli to analyse transcriptional reporters consisting of a green fluorescent protein (gfp) gene fused to P(ospF), P(ospE), or two hybrid promoters in which the -10 regions of P(ospF) and P(ospE) were switched [P(ospF ) ((E - 10)) and P(ospE) ((F - 10)) respectively]. We found that the P(ospF)-10 region is both necessary and sufficient for RpoS-dependent recognition in B. burgdorferi, while sigma(70) specificity for P(ospE) is dependent on elements outside of the -10 region. In E. coli, sigma factor selectivity for these promoters was much more permissive, with expression of each being primarily due to sigma(70). Alignment of the sequences upstream of each of the ospE/ospF/elp genes from B. burgdorferi strains 297 and B31 revealed that two B31 ospF paralogues [erpK (BBM38) and erpL (BBO39)] have -10 regions virtually identical to that of P(ospF). Correspondingly, expression of gfp reporters based on the erpK and erpL promoters was RpoS-dependent. Thus, the sequence of the P(ospF)-10 region appears to serve as a motif for RpoS recognition, the first described for any B. burgdorferi promoter. Taken together, our data support the notion that B. burgdorferi utilizes sequence differences at the -10 region as one mechanism for maintaining the transcriptional integrity of RpoS-dependent and -independent genes activated at the onset of tick feeding.

Role of the spacer between the -35 and -10 regions in sigmas promoter selectivity in Escherichia coli

In vitro, the sigma(s) subunit of RNA polymerase (RNAP), RpoS, recognizes nearly identical -35 and -10 promoter consensus sequences as the vegetative sigma70. In vivo, promoter selectivity of RNAP holoenzyme containing either sigma(s) (Esigma(s)) or sigma70 (Esigma70) seems to be achieved by the differential ability of the two holoenzymes to tolerate deviations from the promoter consensus sequence. In this study, we suggest that many natural sigma(s)-dependent promoters possess a -35 element, a feature that has been considered as not conserved among sigma(s)-dependent promoters. These -35 hexamers are mostly non-optimally spaced from the -10 region, but nevertheless functional. A +/- 2 bp deviation from the optimal spacer length of 17 bp or the complete absence of a -35 consensus sequence decreases overall promoter activity, but at the same time favours Esigma(s) in its competition with Esigma70 for promoter recognition. On the other hand, the reduction of promoter activity due to shifting of the -35 element can be counterbalanced by an activity-stimulating feature such as A/T-richness of the spacer region without compromising Esigma(s) selectivity. Based on mutational analysis of sigma(s), we suggest a role of regions 2.5 and 4 of sigma(s) in sensing sub-optimally located -35 elements.

The maltodextrin system of Escherichia coli: glycogen-derived endogenous induction and osmoregulation

Strains of Escherichia coli lacking MalQ (maltodextrin glucanotransferase or amylomaltase) are endogenously induced for the maltose regulon by maltotriose that is derived from the degradation of glycogen (glycogen-dependent endogenous induction). A high level of induction was dependent on the presence of MalP, maltodextrin phosphorylase, while expression was counteracted by MalZ, maltodextrin glucosidase. Glycogen-derived endogenous induction was sensitive to high osmolarity. This osmodependence was caused by MalZ. malZ, the gene encoding this enzyme, was found to be induced by high osmolarity even in the absence of MalT, the central regulator of all mal genes. The osmodependent expression of malZ was neither RpoS nor OmpR dependent. In contrast, the malPQ operon, whose expression was also increased at a high osmolarity, was partially dependent on RpoS. In the absence of glycogen, residual endogenous induction of the mal genes that is sensitive to increasing osmolarity can still be observed. This glycogen-independent endogenous induction is not understood, and it is not affected by altering the expression of MalP, MalQ, and MalZ. In particular, its independence from MalZ suggests that the responsible inducer is not maltotriose.

RNA polymerase holoenzymes can share a single transcription start site for the Pm promoter. Critical nucleotides in the -7 to -18 region are needed to select between RNA polymerase with sigma38 or sigma32

The Pm promoter of the benzoate meta-cleavage pathway is transcribed with E sigma32 or E sigma38 according to the growth phase, with an identical transcriptional start site. To investigate sequence determinants in the interaction between either of the two RNA polymerases and Pm, all possible single mutants between positions -7 and -18 were generated, and the activity in the exponential and stationary phases of the resulting mutant promoters was compared. The results precisely delimited a -10 element between positions -7 and -12 (TAGGCT), which defined a promoter sharing nucleotides with both sigma38 and sigma32 consensus. The first two and the last positions of this hexamer were crucial for recognition by both polymerases. Position -10 was the only one specifically recognized by E sigma38, whereas positions -8, -9, and the C-track between positions -14 and -17 were important for specific E sigma32 recognition. Western blots showed that sigma32 was only detectable in the exponential phase, and sigma38 appeared in the early stationary phase. In the rpoH mutant KY1429, sigma38 was already present in the exponential growth phase both free and bound to the RNA polymerase core, in good correlation with the transcription levels found. Pm seems to be optimized for recognition by sigma32 as an initial response to the addition of effector to the medium and allows binding of the adaptable sigma38-dependent RNA polymerase in the stationary phase. XylS is always required for Pm transcription. Therefore, the mechanism that controls Pm expression involves specific nucleotide sequences, the abundance of free and core-bound sigma32 and sigma38 factors during growth, and the presence of the regulator activated by an effector.