Virgil A. Rhodius

Convergence of Molecular, Modeling, and Systems Approaches for an Understanding of the Escherichia coli Heat Shock Response

SUMMARY The heat shock response (HSR) is a homeostatic response that maintains the proper protein-folding environment in the cell. This response is universal, and many of its components are well conserved from bacteria to humans. In this review, we focus on the regulation of one of the most well-characterized HSRs, that of Escherichia coli. We show that even for this simple model organism, we still do not fully understand the central component of heat shock regulation, a chaperone-mediated negative feedback loop. In addition, we review other components that contribute to the regulation of the HSR in E. coli and discuss how these additional components contribute to regulation. Finally, we discuss recent genomic experiments that reveal additional functional aspects of the HSR.

Hfq Modulates the σE-Mediated Envelope Stress Response and the σ32-Mediated Cytoplasmic Stress Response in Escherichia coli

Hfq, a chaperone for small noncoding RNAs, regulates many processes in Escherichia coli, including the σS-mediated general stress response. Here we used microarray analysis to identify the changes in gene expression resulting from lack of Hfq. We identify several potential new targets for Hfq regulation, including genes encoding outer membrane proteins, enzymes, factors, and transporters. Many of these genes are involved in amino acid uptake and biosynthesis, sugar uptake and metabolism, and cell energetics. In addition, we find altered regulation of the σE- and σ32-mediated stress responses, which we analyze further. We show that cells lacking Hfq induce the σE-mediated envelope stress response and are defective in σE-mediated repression of outer membrane proteins. We also show that the σ32-mediated cytoplasmic stress response is repressed in cells lacking Hfq due to increased expression of DnaK. Furthermore, we show that cells lacking Hfq are defective in the “long-term adaptation” of σ32 to chronic chaperone overexpression. Together, our results indicate that Hfq may play a general role in stress response regulation in E. coli.

Positive activation of gene expression

Most bacterial transcription activators function by making direct contact with RNA polymerase at target promoters. Some activators contact the carboxy-terminal domain of the RNA polymerase alpha subunit, some contact region 4 of the sigma70 subunit, whilst others interact with other contact sites. A number of activators are ambidextrous and can, apparently simultaneously, contact more than one target site on RNA polymerase. Expression from many promoters is co-dependent on two or more activators. There are several different mechanisms for coupling promoter activity to more than one activator: in one such mechanism, the different activators make independent contacts with different target sites on RNA polymerase.

σE Regulates and Is Regulated by a Small RNA in Escherichia coli

RybB is a small, Hfq-binding noncoding RNA originally identified in a screen of conserved intergenic regions in Escherichia coli. Fusions of the rybB promoter to lacZ were used to screen plasmid genomic libraries and genomic transposon mutants for regulators of rybB expression. A number of plasmids, including some carrying rybB, negatively regulated the fusion. An insertion in the rep helicase and one upstream of dnaK decreased expression of the fusion. Multicopy suppressors of these insertions led to identification of two plasmids that stimulated the fusion. One contained the gene for the response regulator OmpR; the second contained mipA, encoding a murein hydrolase. The involvement of MipA and OmpR in cell surface synthesis suggested that the rybB promoter might be dependent on σE. The sequence upstream of the +1 of rybB contains a consensus σE promoter. The activity of rybB-lacZ was increased in cells lacking the RseA anti-sigma factor and when σE was overproduced from a heterologous promoter. The activity of rybB-lacZ and the detection of RybB were totally abolished in an rpoE-null strain. In vitro, σE efficiently transcribes from this promoter. Both a rybB mutation and an hfq mutation significantly increased expression of both rybB-lacZ and rpoE-lacZ fusions, consistent with negative regulation of the σE response by RybB and other small RNAs. Based on the plasmid screens, NsrR, a repressor sensitive to nitric oxide, was also found to negatively regulate σE-dependent promoters in an RseA-independent fashion.

Small RNAs endow a transcriptional activator with essential repressor functions for single-tier control of a global stress regulon

The Escherichia coli σE envelope stress response monitors and repairs the outer membrane, a function central to the life of Gram-negative bacteria. The σE stress response was characterized as a single-tier activation network comprised of ∼100 genes, including the MicA and RybB noncoding sRNAs. These highly expressed sRNAs were thought to carry out the specialized function of halting de novo synthesis of several abundant porins when envelope homeostasis was perturbed. Using a systematic target profiling and validation approach we discovered that MicA and RybB are each global mRNA repressors of both distinct and shared targets, and that the two sRNAs constitute a posttranscriptional repression arm whose regulatory scope rivals that of the protein-based σE activation arm. Intriguingly, porin mRNAs constitute only ∼1/3 of all targets and new nonporin targets predict roles for MicA and RybB in crosstalk with other regulatory responses. This work also provides an example of evolutionarily unrelated sRNAs that are coinduced and bind the same targets, but at different sites. Our finding that expression of either MicA or RybB sRNA protects the cell from the loss of viability experienced when σE activity is inadequate illustrates the importance of the posttranscriptional repression arm of the response. σE is a paradigm of a single-tier stress response with a clear division of labor in which highly expressed noncoding RNAs (MicA, RybB) endow a transcriptional factor intrinsically restricted to gene activation (σE) with the opposite repressor function.

Identification of the binding sites of regulatory proteins in bacterial genomes

We present an algorithm that extracts the binding sites (represented by position-specific weight matrices) for many different transcription factors from the regulatory regions of a genome, without the need for delineating groups of coregulated genes. The algorithm uses the fact that many DNA-binding proteins in bacteria bind to a bipartite motif with two short segments more conserved than the intervening region. It identifies all statistically significant patterns of the form W1NxW2, where W1 and W2 are two short oligonucleotides separated by x arbitrary bases, and groups them into clusters of similar patterns. These clusters are then used to derive quantitative recognition profiles of putative regulatory proteins. For a given cluster, the algorithm finds the matching sequences plus the flanking regions in the genome and performs a multiple sequence alignment to derive position-specific weight matrices. We have analyzed the Escherichia coli genome with this algorithm and found ≈1,500 significant patterns, which give rise to ≈160 distinct position-specific weight matrices. A fraction of these matrices match the binding sites of one-third of the ≈60 characterized transcription factors with high statistical significance. Many of the remaining matrices are likely to describe binding sites and regulons of uncharacterized transcription factors. The significance of these matrices was evaluated by their specificity, the location of the predicted sites, and the biological functions of the corresponding regulons, allowing us to suggest putative regulatory functions. The algorithm is efficient for analyzing newly sequenced bacterial genomes for which little is known about transcriptional regulation.

Design of orthogonal genetic switches based on a crosstalk map of σs, anti‐σs, and promoters

Cells react to their environment through gene regulatory networks. Network integrity requires minimization of undesired crosstalk between their biomolecules. Similar constraints also limit the use of regulators when building synthetic circuits for engineering applications. Here, we mapped the promoter specificities of extracytoplasmic function (ECF) σs as well as the specificity of their interaction with anti‐σs. DNA synthesis was used to build 86 ECF σs (two from every subgroup), their promoters, and 62 anti‐σs identified from the genomes of diverse bacteria. A subset of 20 σs and promoters were found to be highly orthogonal to each other. This set can be increased by combining the −35 and −10 binding domains from different subgroups to build chimeras that target sequences unrepresented in any subgroup. The orthogonal σs, anti‐σs, and promoters were used to build synthetic genetic switches in Escherichia coli. This represents a genome‐scale resource of the properties of ECF σs and a resource for synthetic biology, where this set of well‐characterized regulatory parts will enable the construction of sophisticated gene expression programs.

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

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 σE, as a representative of group 4 σs, the largest σ 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 σs. 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.

Interactions between the Escherichia coli cyclic AMP receptor protein and RNA polymerase at class II promoters.

The effects of a number of mutations in crp have been measured at different cyclic AMP receptor protein (CRP)‐dependent Class II promoters, where the CRP‐binding site is centred around 411/2 base pairs upstream from the transcription start point. The amino acid substitutions HL159 and TA158 result in reduced CRP‐dependent activation, but the reduction varies from one Class II promoter to another. Deletions in the C‐terminus of the RNA polymerase alpha subunit suppress the effects of HL159 and TA158. The role of the C‐terminus of alpha at these promoters is assessed. Other changes at E58, K52 and E96 affect CRP activity specifically at Class II promoters and their role is discussed.

Promoter Strength Properties of the Complete Sigma E Regulon of Escherichia coli and Salmonella enterica

The sigma(E)-directed envelope stress response maintains outer membrane homeostasis and is an important virulence determinant upon host infection in Escherichia coli and related bacteria. sigma(E) is activated by at least two distinct mechanisms: accumulation of outer membrane porin precursors and an increase in the alarmone ppGpp upon transition to stationary phase. Expression of the sigma(E) regulon is driven from a suite of approximately 60 sigma(E)-dependent promoters. Using green fluorescent protein fusions to each of these promoters, we dissected promoter contributions to the output of the regulon under a variety of in vivo conditions. We found that the sigma(E) promoters exhibit a large dynamic range, with a few strong and many weak promoters. Interestingly, the strongest promoters control either transcriptional regulators or functions related to porin homeostasis, the very functions conserved among E. coli and its close relatives. We found that (i) the strength of most promoters is significantly affected by the presence of the upstream (-35 to -65) region of the promoter, which encompasses the UP element, a binding site for the C-terminal domain of the alpha-subunit of RNA polymerase; (ii) ppGpp generally activates sigma(E) promoters, and (iii) sigma(E) promoters are responsive to changing sigma(E) holoenzyme levels under physiological conditions, reinforcing the idea that the sigma(E) regulon is extremely dynamic, enabling cellular adaptation to a constantly changing environment.