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...
Prokaryotic genomes can be annotated based on their structural, operational, and functional properties. These annotations provide the pivotal scaffold for understanding cellular functions on a genome-scale, such as metabolism and transcriptional regulation. Here, we describe a systems approach to simultaneously determine the structural and operational annotation of the Geobacter sulfurreducens genome. Integration of proteomics, transcriptomics, RNA polymerase, and sigma factor-binding information with deep-sequencing-based analysis of primary 59-end transcripts allowed for a most precise annotation. The structural annotation is comprised of numerous previously undetected genes, noncoding RNAs, prevalent leaderless mRNA transcripts, and antisense transcripts. When compared with other prokaryotes, we found that the number of antisense transcripts reversely correlated with genome size. The operational annotation consists of 1453 operons, 22% of which have multiple transcription start sites that use different RNA polymerase holoenzymes. Several operons with multiple transcription start sites encoded genes with essential functions, giving insight into the regulatory complexity of the genome. The experimentally determined structural and operational annotations can be combined with functional annotation, yielding a new three-level annotation that greatly expands our understanding of prokaryotic genomes.
Even though mRNA quantification provides significant information for biological analysis, current methods such as Northern blot analysis and real-time PCR are known to be laborious and lacking in precision. In this study, we demonstrate a new precise mRNA quantification method using CE based on SSCP (CE-SSCP) coupled with reverse transcription. mRNA samples could be simply analyzed for the quantification directly with reverse transcript obtained from a single reaction. This helps to avoid considerable errors generated by a series of the tedious manual steps. Also, unlike real-time PCR, reverse transcripts can be directly quantified by CE-SSCP in this method without further data estimation. Reproducibility and accuracy of CE-SSCP for mRNA quantification was examined using enhanced green fluorescent protein (eGFP) mRNA transcribed in vitro. Specific reverse transcription primer was determined for the accurate quantification of eGFP mRNA from total RNA obtained from the recombinant Escherichia coli. Using elongation factor Tu mRNA as an internal standard, it was shown that sample-to-sample variation could be minimized. Expression kinetics at both mRNA level and protein level was studied and the potential of CE-SSCP in expression analysis was demonstrated by comparison with the eGFP activity assay.
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