Bacterial genomes are organized in terms of structural and functional components. These components include promoters, transcription start and termination sites, open reading frames, regulatory non-coding regions, untranslated regions and transcription units, that together comprise the functional organization of a genome. Here, we use a systems approach that iteratively integrates multiple high-throughput measurements at a genome-scale to identify the organizational structure of the Escherichia coli K-12 MG1655 genome. Integration of the organizational components provides experimentally annotated transcription unit (TU) architecture, including alternative transcription start sites, promoter structures, boundaries and open reading frames. A total of 4,661 TUs were identified, representing an increase of > 530% over current knowledge. This comprehensive TU architecture allows for the elucidation of condition-specific uses of alternative sigma factors at the genome-scale. Furthermore, the TU architecture provides a foundation on which genome-scale transcriptional and translational regulatory networks are based.

Broad-acting transcription factors (TFs) in bacteria form regulons. Here, we present a 4-step method to fully reconstruct the leucineresponsive protein (Lrp) regulon in Escherichia coli K-12 MG 1655 that regulates nitrogen metabolism.Step 1 is composed of obtaining high-resolution ChIP-chip data for Lrp, the RNA polymerase and expression profiles under multiple environmental conditions. We identified 138 unique and reproducible Lrp-binding regions and classified their binding state under different conditions. In the second step, the analysis of these data revealed 6 distinct regulatory modes for individual ORFs. In the third step, we used the functional assignment of the regulated ORFs to reconstruct 4 types of regulatory network motifs around the metabolites that are affected by the corresponding gene products. In the fourth step, we determined how leucine, as a signaling molecule, shifts the regulatory motifs for particular metabolites. The physiological structure that emerges shows the regulatory motifs for different amino acid fall into the traditional classification of amino acid families, thus elucidating the structure and physiological functions of the Lrp-regulon. The same procedure can be applied to other broad-acting TFs, opening the way to full bottom-up reconstruction of the transcriptional regulatory network in bacterial cells. ChIP-chip ͉ transcription factorT ranscriptional regulatory systems often regulate the formation rates and the concentration of small molecules by 2 feedback loops that regulate the transporters and metabolic enzymes. In many cases, these 2 feedback loops are connected by a common transcription factor (TF) that senses the concentration of the small molecule (1). Little is known at present about the transition between the regulatory modes in the feedback loop motifs for global TFs in bacteria. One such transcription factor is the leucineresponsive protein (Lrp), which is a global transcription regulator widely distributed throughout the bacteria including Escherichia coli (2-4). The Lrp regulon includes genes involved in amino acid biosynthesis and degradation, small molecule transport, pili synthesis, and other cellular functions including 1-carbon metabolism (2, 4-6). The regulatory action of Lrp on target genes is often modulated by the binding of the small effector molecule leucine and in effect endows Lrp with the ability to affect transcriptional regulation in all possible ways. That is, upon addition of leucine to the environment, the activity of Lrp can be enhanced, reversed, or unaffected (2, 4, 7). Little is known about in vivo Lrp-binding events at the genome scale in the presence or absence of leucine and the extent to which the different modes of regulation are used for different metabolites. Such information is needed to reconstruct the Lrp regulon and the understanding of nitrogen metabolism.In this study, we applied a systems approach by integrating genome-scale data from chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) for Lrp and...

Individual Streptomyces species have the genetic potential to produce a diverse array of natural products of commercial, medical and veterinary interest. However, these products are often not detectable under laboratory culture conditions. To harness their full biosynthetic potential, it is important to develop a detailed understanding of the regulatory networks that orchestrate their metabolism. Here we integrate nucleotide resolution genome-scale measurements of the transcriptome and translatome of Streptomyces coelicolor, the model antibiotic-producing actinomycete. Our systematic study determines 3,570 transcription start sites and identifies 230 small RNAs and a considerable proportion (∼21%) of leaderless mRNAs; this enables deduction of genome-wide promoter architecture. Ribosome profiling reveals that the translation efficiency of secondary metabolic genes is negatively correlated with transcription and that several key antibiotic regulatory genes are translationally induced at transition growth phase. These findings might facilitate the design of new approaches to antibiotic discovery and development.

We determined the genome-wide distribution of the nucleoid-associated protein Fis in Escherichia coli using chromatin immunoprecipitation coupled with high-resolution whole genome-tiling microarrays. We identified 894 Fis-associated regions across the E. coli genome. A significant number of these binding sites were found within open reading frames (33%) and between divergently transcribed transcripts (5%). Analysis indicates that A-tracts and AT-tracts are an important signal for preferred Fis-binding sites, and that A6-tracts in particular constitute a high-affinity signal that dictates Fis phasing in stretches of DNA containing multiple and variably spaced A-tracts and AT-tracts. Furthermore, we find evidence for an average of two Fis-binding regions per supercoiling domain in the chromosome of exponentially growing cells. Transcriptome analysis shows that ∼21% of genes are affected by the deletion of fis; however, the changes in magnitude are small. To address the differential Fis bindings under growth environment perturbation, ChIP-chip analysis was performed using cells grown under aerobic and anaerobic growth conditions. Interestingly, the Fis-binding regions are almost identical in aerobic and anaerobic growth conditions—indicating that the E. coli genome topology mediated by Fis is superficially identical in the two conditions. These novel results provide new insight into how Fis modulates DNA topology at a genome scale and thus advance our understanding of the architectural bases of the E. coli nucleoid.

Specific small deletions within the rpoC gene encoding the β′-subunit of RNA polymerase (RNAP) are found repeatedly after adaptation of Escherichia coli K-12 MG1655 to growth in minimal media. Here we present a multiscale analysis of these mutations. At the physiological level, the mutants grow 60% faster than the parent strain and convert the carbon source 15-35% more efficiently to biomass, but grow about 30% slower than the parent strain in rich medium. At the molecular level, the kinetic parameters of the mutated RNAP were found to be altered, resulting in a 4-to 30-fold decrease in open complex longevity at an rRNA promoter and a ∼10-fold decrease in transcriptional pausing, with consequent increase in transcript elongation rate. At a genome-scale, systems biology level, gene expression changes between the parent strain and adapted RNAP mutants reveal large-scale systematic transcriptional changes that influence specific cellular processes, including strong down-regulation of motility, acid resistance, fimbria, and curlin genes. RNAP genome-binding maps reveal redistribution of RNAP that may facilitate relief of a metabolic bottleneck to growth. These findings suggest that reprogramming the kinetic parameters of RNAP through specific mutations allows regulatory adaptation for optimal growth in new environments.kinetics | stringent response | transcription

Demands for faster and more accurate methods to analyze microbial communities from natural and clinical samples have been increasing in the medical and healthcare industry. Recent advances in next-generation sequencing technologies have facilitated the elucidation of the microbial community composition with higher accuracy and greater throughput than was previously achievable; however, the short sequencing reads often limit the microbial composition analysis at the species level due to the high similarity of 16S rRNA amplicon sequences. To overcome this limitation, we used the nanopore sequencing platform to sequence full-length 16S rRNA amplicon libraries prepared from the mouse gut microbiota. A comparison of the nanopore and short-read sequencing data showed that there were no significant differences in major taxonomic units (89%) except one phylotype and three taxonomic units. Moreover, both sequencing data were highly similar at all taxonomic resolutions except the species level. At the species level, nanopore sequencing allowed identification of more species than short-read sequencing, facilitating the accurate classification of the bacterial community composition. Therefore, this method of full-length 16S rRNA amplicon sequencing will be useful for rapid, accurate and efficient detection of microbial diversity in various biological and clinical samples.

Genome-wide transcription start site (TSS) profiles of the enterobacteria Escherichia coli and Klebsiella pneumoniae were experimentally determined through modified 5′ RACE followed by deep sequencing of intact primary mRNA. This identified 3,746 and 3,143 TSSs for E. coli and K. pneumoniae, respectively. Experimentally determined TSSs were then used to define promoter regions and 5′ UTRs upstream of coding genes. Comparative analysis of these regulatory elements revealed the use of multiple TSSs, identical sequence motifs of promoter and Shine-Dalgarno sequence, reflecting conserved gene expression apparatuses between the two species. In both species, over 70% of primary transcripts were expressed from operons having orthologous genes during exponential growth. However, expressed orthologous genes in E. coli and K. pneumoniae showed a strikingly different organization of upstream regulatory regions with only 20% identical promoters with TSSs in both species. Over 40% of promoters had TSSs identified in only one species, despite conserved promoter sequences existing in the other species. 662 conserved promoters having TSSs in both species resulted in the same number of comparable 5′ UTR pairs, and that regulatory element was found to be the most variant region in sequence among promoter, 5′ UTR, and ORF. In K. pneumoniae, 48 sRNAs were predicted and 36 of them were expressed during exponential growth. Among them, 34 orthologous sRNAs between two species were analyzed in depth, and the analysis showed that many sRNAs of K. pneumoniae, including pleiotropic sRNAs such as rprA, arcZ, and sgrS, may work in the same way as in E. coli. These results reveal a new dimension of comparative genomics such that a comparison of two genomes needs to be comprehensive over all levels of genome organization.

BackgroundAt the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a σ-factor to recognize the genomic location at which the process initiates. Although the crucial role of σ-factors has long been appreciated and characterized for many individual promoters, we do not yet have a genome-scale assessment of their function.ResultsUsing multiple genome-scale measurements, we elucidated the network of σ-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 σ-factor-specific promoters corresponding to transcription units (TUs), representing an increase of more than 300% over what has been previously reported. The reconstructed network was used to investigate competition between alternative σ-factors (the σ70 and σ38 regulons), confirming the competition model of σ substitution and negative regulation by alternative σ-factors. Comparison with σ-factor binding in Klebsiella pneumoniae showed that transcriptional regulation of conserved genes in closely related species is unexpectedly divergent.ConclusionsThe reconstructed network reveals the regulatory complexity of the promoter architecture in prokaryotic genomes, and opens a path to the direct determination of the systems biology of their transcriptional regulatory networks.