Transient growth arrest in Escherichia coli induced by chromosome condensation.

MukB is a bacterial SMC (structural maintenance of chromosome) protein that regulates the global folding of the Escherichia coli chromosome by bringing distant DNA segments together. We report that moderate overproduction of MukB may lead, depending on strain and growth conditions, to transient growth arrest. In DH5α cells, overproduction of MukB or MukBEF using pBAD expression system triggered growth arrest 2.5 h after induction. The exit from growth arrest was accompanied by the loss of the overproducing plasmid and a decline in the abundance of MukBEF. The arrested cells showed a compound gene expression profile which can be characterized by the following features: (i) a broad and deep downregulation of ribosomal proteins (up to 80-fold); (ii) downregulation of groups of genes encoding enzymes involved in nucleotide metabolism, respiration, and central metabolism; (iii) upregulation of some of the genes responsive to general stress; and (iv) degradation of the patterns of spatial correlations in the transcriptional activity of the chromosome. The transcriptional state of the MukB induced arrest is most similar to stationary cells and cells recovered from stationary phase into a nutrient deprived medium, to amino acid starved cells and to the cells shifting from glucose to acetate. The mukB++ state is dissimilar from all examined transcriptional states generated by protein overexpression with the possible exception of RpoE and RpoH overexpression. Thus, the transcription profile of MukB-arrested cells can be described as a combination of responses typical for other growth-arrested cells and those for overproducers of DNA binding proteins with a particularly deep down-regulation of ribosomal genes.

The association of DNA damage response and nucleotide level modulation with the antibacterial mechanism of the anti-folate drug trimethoprim.

BACKGROUND: Trimethoprim is a widely prescribed antibiotic for a variety of bacterial infections. It belongs to a class of anti-metabolites - antifolates - which includes drugs used against malarial parasites and in cancer therapy. However, spread of bacterial resistance to the drug has severely hampered its clinical use and has necessitated further investigations into its mechanism of action and treatment regimen. Trimethoprim selectively starves bacterial cells for tetrahydrofolate, a vital cofactor necessary for the synthesis of several metabolites. The outcome (bacteriostatic or bactericidal) of such starvation, however, depends on the availability of folate-dependent metabolites in the growth medium. To characterize this dependency, we investigated in detail the regulatory and structural components of Escherichia coli cellular response to trimethoprim in controlled growth and supplementation conditions. RESULTS: We surveyed transcriptional responses to trimethoprim treatment during bacteriostatic and bactericidal conditions and analyzed associated gene sets/pathways. Concurrent starvation of all folate dependent metabolites caused growth arrest, and this was accompanied by induction of general stress and stringent responses. Three gene sets were significantly associated with the bactericidal effect of TMP in different media including LB: genes of the SOS regulon, genes of the pyrimidine nucleotide biosynthetic pathway and members of the multiple antibiotic resistance (mar) regulon controlled by the MarR repressor. However, the SOS response was identified as the only universal transcriptional signature associated with the loss of viability by direct thymine starvation or by folate stress. We also used genome-wide gene knock-out screen to uncover means of sensitization of bacteria to the drug. We observed that among a number of candidate genes and pathways, the effect of knock-outs in the deoxyribose nucleotide salvage pathway, encoded by the deoCABD operon and under the control of the DeoR repressor, was most informative. CONCLUSION: Transcriptional induction of DNA damage response is an essential feature of the bactericidal effect of trimethoprim. Either the observation of the transcriptional response or DNA damage itself, or both, is made possible by thymine starvation when other folate-dependent metabolites are not limited. The effect of DNA damage by the drug takes place prior to its bactericidal effect, at the beginning of the lag stage of the treatment. Mutations in the deoxyribose nucleotide salvage pathway can affect duration of the lag as well as the rate of killing. This information can be used to postulate certain mechanistic differences between direct thymine starvation in thymidylate synthase deficient mutants and thymine starvation by anti-folate inhibitors.

Modeling Three-Dimensional Chromosome Structures Using Gene Expression Data.

Recent genomic studies have shown that significant chromosomal spatial correlation exists in gene expression of many organisms. Interestingly, coexpression has been observed among genes separated by a fixed interval in specific regions of a chromosome chain, which is likely caused by three-dimensional (3D) chromosome folding structures. Modeling such spatial correlation explicitly may lead to essential understandings of 3D chromosome structures and their roles in transcriptional regulation. In this paper, we explore chromosomal spatial correlation induced by 3D chromosome structures, and propose a hierarchical Bayesian method based on helical structures to formally model and incorporate the correlation into the analysis of gene expression microarray data. It is the first study to quantify and infer 3D chromosome structures in vivo using expression microarrays. Simulation studies show computing feasibility of the proposed method and that, under the assumption of helical chromosome structures, it can lead to precise estimation of structural parameters and gene expression levels. Real data applications demonstrate an intriguing biological phenomenon that functionally associated genes, which are far apart along the chromosome chain, are brought into physical proximity by chromosomal folding in 3D space to facilitate their coexpression. It leads to important biological insight into relationship between chromosome structure and function.

Thymineless death is associated with loss of essential genetic information from the replication origin.

Thymine starvation results in a terminal cellular condition known as thymineless death (TLD), which is the basis of action for several common antibiotics and anticancer drugs. We characterized the onset and progression of TLD in Escherichia coli and found that DNA damage is the only salient property that distinguishes cells irreversibly senesced under thymine starvation from cells reversibly arrested by the nucleotide limitation. The damage is manifested as the relative loss of genetic material spreading outward from the replication origin: the extent of TLD correlates with the progression of damage. The reduced lethality in mutants deficient in the RecFOR/JQ repair pathway also correlates with the extent of damage, which explains most of the observed variance in cell killing. We propose that such spatially localized and persistent DNA damage is the consequence of transcription-dependent initiation of replication in the thymine-starved cells and may be the underlying cause of TLD.

A Bayesian approach to joint modeling of protein-DNA binding, gene expression and sequence data.

The genome-wide DNA-protein-binding data, DNA sequence data and gene expression data represent complementary means to deciphering global and local transcriptional regulatory circuits. Combining these different types of data can not only improve the statistical power, but also provide a more comprehensive picture of gene regulation. In this paper, we propose a novel statistical model to augment protein-DNA-binding data with gene expression and DNA sequence data when available. We specify a hierarchical Bayes model and use Markov chain Monte Carlo simulations to draw inferences. Both simulation studies and an analysis of an experimental data set show that the proposed joint modeling method can significantly improve the specificity and sensitivity of identifying target genes as compared with conventional approaches relying on a single data source.

In vivo and in vitro patterns of the activity of simocyclinone D8, an angucyclinone antibiotic from Streptomyces antibioticus.

Simocyclinone D8 (SD8) exhibits antibiotic activity against gram-positive bacteria but not against gram-negative bacteria. The molecular basis of the cytotoxicity of SD8 is not fully understood, although SD8 has been shown to inhibit the supercoiling activity of Escherichia coli gyrase. To understand the mechanism of SD8, we have employed biochemical assays to directly measure the sensitivities of E. coli and Staphylococcus aureus type II topoisomerases to SD8 and microarray analysis to monitor the cellular responses to SD8 treatment. SD8 is a potent inhibitor of either E. coli or S. aureus gyrase. In contrast, SD8 exhibits only a moderate inhibitory effect on S. aureus topoisomerase IV, and E. coli topoisomerase IV is virtually insensitive to SD8. The antimicrobial effect of SD8 against E. coli has become evident in the absence of the AcrB multidrug efflux pump. As expected, SD8 treatment exhibits the signature responses to the loss of supercoiling activity in E. coli: upregulation of gyrase genes and downregulation of the topoisomerase I gene. Unlike quinolone treatment, however, SD8 treatment does not induce the SOS response. These results suggest that DNA gyrase is the target of SD8 in both gram-positive and gram-negative bacteria and that the lack of the antibacterial effect against gram-negative bacteria is due, in part, to the activity of the AcrB efflux pump.

Improved detection of differentially expressed genes through incorporation of gene locations.

In determining differential expression in cDNA microarray experiments, the expression level of an individual gene is usually assumed to be independent of the expression levels of other genes, but many recent studies have shown that a gene's expression level tends to be similar to that of its neighbors on a chromosome, and differentially expressed (DE) genes are likely to form clusters of similar transcriptional activity along the chromosome. When modeled as a one-dimensional spatial series, the expression level of genes on the same chromosome frequently exhibit significant spatial correlation, reflecting spatial patterns in transcription. By modeling these spatial correlations, we can obtain improved estimates of transcript levels. Here, we demonstrate the existence of spatial correlations in transcriptional activity in the Escherichia coli (E. coli) chromosome across more than 50 experimental conditions. Based on this finding, we propose a hierarchical Bayesian model that borrows information from neighboring genes to improve the estimation of the expression level of a given gene and hence the detection of DE genes. Furthermore, we extend the model to account for the circular structure of E. coli chromosome and the intergenetic distance between gene neighbors. The simulation studies and analysis of real data examples in E. coli and yeast Saccharomyces cerevisiae show that the proposed method outperforms the commonly used significant analysis of microarray (SAM) t-statistic in detecting DE genes.

Limited functional conservation of a global regulator among related bacterial genera: Lrp in Escherichia, Proteus and Vibrio.

BACKGROUND: Bacterial genome sequences are being determined rapidly, but few species are physiologically well characterized. Predicting regulation from genome sequences usually involves extrapolation from better-studied bacteria, using the hypothesis that a conserved regulator, conserved target gene, and predicted regulator-binding site in the target promoter imply conserved regulation between the two species. However many compared organisms are ecologically and physiologically diverse, and the limits of extrapolation have not been well tested. In E. coli K-12 the leucine-responsive regulatory protein (Lrp) affects expression of approximately 400 genes. Proteus mirabilis and Vibrio cholerae have highly-conserved lrp orthologs (98% and 92% identity to E. coli lrp). The functional equivalence of Lrp from these related species was assessed. RESULTS: Heterologous Lrp regulated gltB, livK and lrp transcriptional fusions in an E. coli background in the same general way as the native Lrp, though with significant differences in extent. Microarray analysis of these strains revealed that the heterologous Lrp proteins significantly influence only about half of the genes affected by native Lrp. In P. mirabilis, heterologous Lrp restored swarming, though with some pattern differences. P. mirabilis produced substantially more Lrp than E. coli or V. cholerae under some conditions. Lrp regulation of target gene orthologs differed among the three native hosts. Strikingly, while Lrp negatively regulates its own gene in E. coli, and was shown to do so even more strongly in P. mirabilis, Lrp appears to activate its own gene in V. cholerae. CONCLUSION: The overall similarity of regulatory effects of the Lrp orthologs supports the use of extrapolation between related strains for general purposes. However this study also revealed intrinsic differences even between orthologous regulators sharing >90% overall identity, and 100% identity for the DNA-binding helix-turn-helix motif, as well as differences in the amounts of those regulators. These results suggest that predicting regulation of specific target genes based on genome sequence comparisons alone should be done on a conservative basis.

RecA can stimulate the relaxation activity of topoisomerase I: Molecular basis of topoisomerase-mediated genome-wide transcriptional responses in Escherichia coli.

The superhelicity of the chromosome, which is controlled by DNA topoisomerases, modulates global gene expression. Investigations of transcriptional responses to the modulation of gyrase function have identified two types of topoisomerase-mediated transcriptional responses: (i) steady-state changes elicited by a mutation in gyrase, such as the D82G mutation in GyrA, and (ii) dynamic changes elicited by the inhibition of gyrase. We hypothesize that the steady-state effects are due to the changes in biochemical properties of gyrase, whereas the dynamic effects are due to an imbalance between supercoiling and relaxation activities, which appears to be influenced by the RecA activity. Herein, we present biochemical evidence for hypothesized mechanisms. GyrA D82G gyrase exhibits a reduced supercoiling activity. The RecA protein can influence the balance between supercoiling and relaxation activities either by interfering with the activity of DNA gyrase or by facilitating the relaxation reaction. RecA has no effect on the supercoiling activity of gyrase but stimulates the relaxation activity of topoisomerase I. This stimulation is specific and requires formation of an active RecA filament. These results suggest that the functional interaction between RecA and topoisomerase I is responsible for RecA-mediated modulation of the relaxation-dependent transcriptional activity of the Escherichia coli chromosome.

Analysis of pleiotropic transcriptional profiles: a case study of DNA gyrase inhibition.

Genetic and environmental perturbations often result in complex transcriptional responses involving multiple genes and regulons. In order to understand the nature of a response, one has to account for the contribution of the downstream effects to the formation of a response. Such analysis can be carried out within a statistical framework in which the individual effects are independently collected and then combined within a linear model. Here, we modeled the contribution of DNA replication, supercoiling, and repair to the transcriptional response of inhibition of the Escherichia coli gyrase. By representing the gyrase inhibition as a true pleiotropic phenomenon, we were able to demonstrate that: (1) DNA replication is required for the formation of spatial transcriptional domains; (2) the transcriptional response to the gyrase inhibition is coordinated between at least two modules involved in DNA maintenance, relaxation and damage response; (3) the genes whose transcriptional response to the gyrase inhibition does not depend on the main relaxation activity of the cell can be classified on the basis of a GC excess in their upstream and coding sequences; and (4) relaxation by topoisomerase I dominates the transcriptional response, followed by the effects of replication and RecA. We functionally tested the effect of the interaction between relaxation and repair activities, and found support for the model derived from the microarray data. We conclude that modeling compound transcriptional profiles as a combination of downstream transcriptional effects allows for a more realistic, accurate, and meaningful representation of the transcriptional activity of a genome.

Operon information improves gene expression estimation for cDNA microarrays.

BACKGROUND: In prokaryotic genomes, genes are organized in operons, and the genes within an operon tend to have similar levels of expression. Because of co-transcription of genes within an operon, borrowing information from other genes within the same operon can improve the estimation of relative transcript levels; the estimation of relative levels of transcript abundances is one of the most challenging tasks in experimental genomics due to the high noise level in microarray data. Therefore, techniques that can improve such estimations, and moreover are based on sound biological premises, are expected to benefit the field of microarray data analysis RESULTS: In this paper, we propose a hierarchical Bayesian model, which relies on borrowing information from other genes within the same operon, to improve the estimation of gene expression levels and, hence, the detection of differentially expressed genes. The simulation studies and the analysis of experiential data demonstrated that the proposed method outperformed other techniques that are routinely used to estimate transcript levels and detect differentially expressed genes, including the sample mean and SAM t statistics. The improvement became more significant as the noise level in microarray data increases. CONCLUSION: By borrowing information about transcriptional activity of genes within classified operons, we improved the estimation of gene expression levels and the detection of differentially expressed genes.

A classification based framework for quantitative description of large-scale microarray data.

Genome-wide surveys of transcription depend on gene classifications for the purpose of data interpretation. We propose a new information-theoretical-based method to: assess significance of co-expression within any gene group; quantitatively describe condition-specific gene-class activity; and systematically evaluate conditions in terms of gene-class activity. We applied this technique to describe microarray data tracking Escherichia coli transcriptional responses to more than 30 chemical and physiological perturbations. We correlated the nature and breadth of the responses with the nature of perturbation, identified gene group proxies for the perturbation classes and quantitatively compared closely related physiological conditions.

A note on using permutation-based false discovery rate estimates to compare different analysis methods for microarray data.

MOTIVATION: False discovery rate (FDR) is defined as the expected percentage of false positives among all the claimed positives. In practice, with the true FDR unknown, an estimated FDR can serve as a criterion to evaluate the performance of various statistical methods under the condition that the estimated FDR approximates the true FDR well, or at least, it does not improperly favor or disfavor any particular method. Permutation methods have become popular to estimate FDR in genomic studies. The purpose of this paper is 2-fold. First, we investigate theoretically and empirically whether the standard permutation-based FDR estimator is biased, and if so, whether the bias inappropriately favors or disfavors any method. Second, we propose a simple modification of the standard permutation to yield a better FDR estimator, which can in turn serve as a more fair criterion to evaluate various statistical methods. RESULTS: Both simulated and real data examples are used for illustration and comparison. Three commonly used test statistics, the sample mean, SAM statistic and Student's t-statistic, are considered. The results show that the standard permutation method overestimates FDR. The overestimation is the most severe for the sample mean statistic while the least for the t-statistic with the SAM-statistic lying between the two extremes, suggesting that one has to be cautious when using the standard permutation-based FDR estimates to evaluate various statistical methods. In addition, our proposed FDR estimation method is simple and outperforms the standard method.

Genome-wide localization of mobile elements: experimental, statistical and biological considerations.

BACKGROUND: The distribution and location of insertion elements in a genome is an excellent tool to track the evolution of bacterial strains and a useful molecular marker to distinguish between closely related bacterial isolates. The information about the genomic locations of IS elements is available in public sequence databases. However, the locations of mobile elements may vary from strain to strain and within the population of an individual strain. Tools that allow de novo localization of IS elements and are independent of existing sequence information are essential to map insertion elements and advance our knowledge of the role that such elements play in gene regulation and genome plasticity in bacteria. RESULTS: In this study, we present an efficient and reliable method for linear mapping of mobile elements using whole-genome DNA microarrays. In addition, we describe an algorithm for analysis of microarray data that can be applied to find DNA sequences physically juxtaposed with a target sequence of interest. This approach was used to map the locations of the IS5 elements in the genome of Escherichia coli K12. All IS5 elements present in the E. coli genome known from GenBank sequence data were identified. Furthermore, previously unknown insertion sites were predicted with high sensitivity and specificity. Two variants of E. coli K-12 MG1655 within a population of this strain were predicted by our analysis. The only significant difference between these two isolates was the presence of an IS5 element upstream of the main flagella regulator, flhDC. Additional experiments confirmed this prediction and showed that these isolates were phenotypically distinct. The effect of IS5 on the transcriptional activity of motility and chemotaxis genes in the genome of E. coli strain MG1655 was examined. Comparative analysis of expression profiles revealed that the presence of IS5 results in a mild enhancement of transcription of the flagellar genes that translates into a slight increase in motility. CONCLUSION: In summary, this work presents a case study of an experimental and analytical application of DNA microarrays to map insertion elements in bacteria and gains an insight into biological processes that might otherwise be overlooked by relying solely on the available genome sequence data.

Spatial patterns of transcriptional activity in the chromosome of Escherichia coli.

BACKGROUND: Although genes on the chromosome are organized in a fixed order, the spatial correlations in transcription have not been systematically evaluated. We used a combination of genomic and signal processing techniques to investigate the properties of transcription in the genome of Escherichia coli K12 as a function of the position of genes on the chromosome. RESULTS: Spectral analysis of transcriptional series revealed the existence of statistically significant patterns in the spatial series of transcriptional activity. These patterns could be classified into three categories: short-range, of up to 16 kilobases (kb); medium-range, over 100-125 kb; and long-range, over 600-800 kb. We show that the significant similarities in gene activities extend beyond the length of an operon and that local patterns of coexpression are dependent on DNA supercoiling. Unlike short-range patterns, the formation of medium and long-range transcriptional patterns does not strictly depend on the level of DNA supercoiling. The long-range patterns appear to correlate with the patterns of distribution of DNA gyrase on the bacterial chromosome. CONCLUSIONS: Localization of structural components in the transcriptional signal revealed an asymmetry in the distribution of transcriptional patterns along the bacterial chromosome. The demonstration that spatial patterns of transcription could be modulated pharmacologically and genetically, along with the identification of molecular correlates of transcriptional patterns, offer for the first time strong evidence of physiologically determined higher-order organization of transcription in the bacterial chromosome.

Genomic transcriptional response to loss of chromosomal supercoiling in Escherichia coli.

BACKGROUND: The chromosome of Escherichia coli is maintained in a negatively supercoiled state, and supercoiling levels are affected by growth phase and a variety of environmental stimuli. In turn, supercoiling influences local DNA structure and can affect gene expression. We used microarrays representing nearly the entire genome of Escherichia coli MG1655 to examine the dynamics of chromosome structure. RESULTS: We measured the transcriptional response to a loss of supercoiling caused either by genetic impairment of a topoisomerase or addition of specific topoisomerase inhibitors during log-phase growth and identified genes whose changes are statistically significant. Transcription of 7% of the genome (306 genes) was rapidly and reproducibly affected by changes in the level of supercoiling; the expression of 106 genes increased upon chromosome relaxation and the expression of 200 decreased. These changes are most likely to be direct effects, as the kinetics of their induction or repression closely follow the kinetics of DNA relaxation in the cells. Unexpectedly, the genes induced by relaxation have a significantly enriched AT content in both upstream and coding regions. CONCLUSIONS: The 306 supercoiling-sensitive genes are functionally diverse and widely dispersed throughout the chromosome. We propose that supercoiling acts as a second messenger that transmits information about the environment to many regulatory networks in the cell.

Life after transcription--revisiting the fate of messenger RNA.

Recently, several groups have used high-density DNA microarrays to study mRNA turnover. These new data suggest that decay contributes significantly to determining mRNA levels, and they should prompt us to refocus our attention on the regulatory potential of mRNA decay.

Global analysis of mRNA decay and abundance in Escherichia coli at single-gene resolution using two-color fluorescent DNA microarrays.

Much of the information available about factors that affect mRNA decay in Escherichia coli, and by inference in other bacteria, has been gleaned from study of less than 25 of the approximately 4,300 predicted E. coli messages. To investigate these factors more broadly, we examined the half-lives and steady-state abundance of known and predicted E. coli mRNAs at single-gene resolution by using two-color fluorescent DNA microarrays. An rRNA-based strategy for normalization of microarray data was developed to permit quantitation of mRNA decay after transcriptional arrest by rifampicin. We found that globally, mRNA half-lives were similar in nutrient-rich media and defined media in which the generation time was approximately tripled. A wide range of stabilities was observed for individual mRNAs of E. coli, although approximately 80% of all mRNAs had half-lives between 3 and 8 min. Genes having biologically related metabolic functions were commonly observed to have similar stabilities. Whereas the half-lives of a limited number of mRNAs correlated positively with their abundance, we found that overall, increased mRNA stability is not predictive of increased abundance. Neither the density of putative sites of cleavage by RNase E, which is believed to initiate mRNA decay in E. coli, nor the free energy of folding of 5' or 3' untranslated region sequences was predictive of mRNA half-life. Our results identify previously unsuspected features of mRNA decay at a global level and also indicate that generalizations about decay derived from the study of individual gene transcripts may have limited applicability.