Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states

Background: At the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a sigma-factor to recognize the genomic location at which the process initiates. Although the crucial role of sigma-factors has long been appreciated and characterized for many individual promoters, we do not yet have a genome-scale assessment of their function. Results: Using multiple genome-scale measurements, we elucidated the network of s-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 sigma-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 sigma-factors (the sigma(70) and sigma(38) regulons), confirming the competition model of sigma substitution and negative regulation by alternative s-factors. Comparison with sigma-factor binding in Klebsiella pneumoniae showed that transcriptional regulation of conserved genes in closely related species is unexpectedly divergent. Conclusions: The 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

The PurR regulon in Escherichia coli K-12 MG1655

The PurR transcription factor plays a critical role in transcriptional regulation of purine metabolism in enterobacteria. Here, we elucidate the role of PurR under exogenous adenine stimulation at the genome-scale using high-resolution chromatin immunoprecipitation (ChIP)–chip and gene expression data obtained under in vivo conditions. Analysis of microarray data revealed that adenine stimulation led to changes in transcript level of about 10% of Escherichia coli genes, including the purine biosynthesis pathway. The E. coli strain lacking the purR gene showed that a total of 56 genes are affected by the deletion. From the ChIP–chip analysis, we determined that over 73% of genes directly regulated by PurR were enriched in the biosynthesis, utilization and transport of purine and pyrimidine nucleotides, and 20% of them were functionally unknown. Compared to the functional diversity of the regulon of the other general transcription factors in E. coli, the functions and size of the PurR regulon are limited

Characterization of an Entner???Doudoroff pathway-activated Escherichia coli

Background Escherichia coli have both the Embden-Meyerhof-Parnas pathway (EMPP) and Entner-Doudoroff pathway (EDP) for glucose breakdown, while the EDP primarily remains inactive for glucose metabolism. However, EDP is a more favorable route than EMPP for the production of certain products. Results EDP was activated by deleting the pfkAB genes in conjunction with subsequent adaptive laboratory evolution (ALE). The evolved strains acquired mutations in transcriptional regulatory genes for glycolytic process (crp, galR, and gntR) and in glycolysis-related genes (gnd, ptsG, and talB). The genotypic, transcriptomic and phenotypic analyses of those mutations deepen our understanding of their beneficial effects on cellulosic biomass bio-conversion. On top of these scientific understandings, we further engineered the strain to produce higher level of lycopene and 3-hydroxypropionic acid. Conclusions These results indicate that the E. coli strain has innate capability to use EDP in lieu of EMPP for glucose metabolism, and this versatility can be harnessed to further engineer E. coli for specific biotechnological applications

Development of spalling estimation model for ball-type constant velocity joints

In this study, the spalling issue in ball-type Constant Velocity Joints (CVJ) was investigated. As one of the most common types of outboard CVJ, a ball-type CVJ has spalling problems caused by fatigue at the internal contact points. It causes noise and vibration in vehicles, which results in CVJ failures. This study provides a spalling-estimation model for a ball-type CVJ, which was developed by the following five steps. First, the relative coordinates of the internal contact points between each component were established by forward kinematics. Second, the acting forces were calculated according to the results of the relative coordinate analyses and the vehicle driving conditions, and then normal pressure at the contact points was derived by Hertz contact theory. Third, the maximum sliding speeds at the contact points were also calculated using slip motion analyses. These normal pressure and maximum sliding speeds were used to estimate the shear stresses at the contact points. Fourth, experiment to evaluate spalling occurrence was carried out under several contact conditions. Lastly, a spalling estimation model was developed based on the reliability analysis with experiment data. The developed model was verified by testing a ball-type CVJ under actual driving condition. The verified spalling estimation model accurately predicts the spalling occurrences in various driving conditions.N

Process Condition Diagram Predicting Onset of Microdefects and Fracture in Cold Bar Drawing

This paper presents a process condition diagram (PCD) that not only identifies conditions under which materials fracture during bar drawing, but also infers the presence or absence of microdefects such as microvoids and microcracks in the drawn material as accumulative damage changes owing to the die semi-angle and reduction ratio. The accumulative damage values were calculated by finite element (FE) analysis. The critical damage values were determined by performing a tensile test using a smooth round bar tensile specimen and performing FE analysis simulating the tensile test. High alloy steel with a 13 mm diameter was used for the draw bench testing in a wide range of drawing conditions. Scanning electron microscopy (SEM) analysis was performed to verify the usefulness of the PCD. SEM images showed that the accumulative damage roughly matched the size of microvoids around the non-metallic inclusions and the creation of microcracks, which eventually led to fractures of material being drawn. Hence, utilizing the proposed PCD, a process designer can design drawing conditions that minimize the occurrence of microdefects in the material being drawn while maximizing the reduction ratio

Revealing Causes for False-Positive and False-Negative Calling of Gene Essentiality in Escherichia coli Using Transposon Insertion Sequencing

Transposon mutagenesis is an efficient way to explore gene essentiality of a bacterial genome. However, there was a discrepancy between the essential gene set determined by transposon mutagenesis and that determined using single-gene knockout strains. The massive sequencing of transposon insertion mutant libraries (Tn-Seq) represents a commonly used method to determine essential genes in bacteria. Using a hypersaturated transposon mutant library consisting of 400,096 unique Tn insertions, 523 genes were classified as essential in Escherichia coli K-12 MG1655. This provided a useful genome-wide gene essentiality landscape for rapidly identifying 233 of 301 essential genes previously validated by a knockout study. However, there was a discrepancy in essential gene sets determined by conventional gene deletion methods and Tn-Seq, although different Tn-Seq studies reported different extents of discrepancy. We have elucidated two causes of this discrepancy. First, 68 essential genes not detected by Tn-Seq contain nonessential subgenic domains that are tolerant to transposon insertion, which leads to the false assignment of an essential gene as a nonessential or dispensable gene. These genes exhibited a high level of transposon insertion in their subgenic nonessential domains. In contrast, 290 genes were additionally categorized as essential by Tn-Seq, although their knockout mutants were available. The comparative analysis of Tn-Seq and high-resolution footprinting of nucleoid-associated proteins (NAPs) revealed that a protein-DNA interaction hinders transposon insertion. We identified 213 false-positive genes caused by NAP-genome interactions. These two limitations have to be considered when addressing essential bacterial genes using Tn-Seq. Furthermore, a comparative analysis of high-resolution Tn-Seq with other data sets is required for a more accurate determination of essential genes in bacteria.IMPORTANCE Transposon mutagenesis is an efficient way to explore gene essentiality of a bacterial genome. However, there was a discrepancy between the essential gene set determined by transposon mutagenesis and that determined using single-gene knockout strains. In this study, we generated a hypersaturated Escherichia coli transposon mutant library comprising approximately 400,000 different mutants. Determination of transposon insertion sites using next-generation sequencing provided a high-resolution essentiality landscape of the E. coli genome. We identified false negatives of essential gene discovery due to the permissive insertion of transposons in the C-terminal region. Comparisons between the transposon insertion landscape with binding profiles of DNA-binding proteins revealed interference of nucleoid-associated proteins to transposon insertion, generating false positives of essential gene discovery. Consideration of these findings is required to avoid the misinterpretation of transposon mutagenesis results

Determining the control circuitry of redox metabolism at the genome-scale.

Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs), ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2) (p<1e-6) correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network