[show abstract][hide abstract] ABSTRACT: It has long been recognized that analyzing the behaviour of the complex intracellular biological networks is important for breeding industrially useful microorganisms. However, because of the complexity of these biological networks, it is currently not possible to obtain all the desired microorganisms. In this study, we constructed a system for analyzing the effect of gene expression perturbations on the behavior of biological networks in Escherichia coli. Specifically, we utilized 13 C metabolic flux analysis (13 C-MFA) to analyze the effect of perturbations to the expression levels of pgi and eno genes encoding phosphoglucose isomerase and enolase, respectively on metabolic fluxes.
We constructed gene expression-controllable E. coli strains using a single-copy mini F plasmid. Using the pgi expression-controllable strain, we found that the specific growth rate correlated with the pgi expression level. 13 C-MFA of this strain revealed that the fluxes for the pentose phosphate pathway and Entner-Doudoroff pathway decreased, as the pgi expression lelvel increased. In addition, the glyoxylate shunt became active when the pgi expression level was almost zero. Moreover, the flux for the glyoxylate shunt increased when the pgi expression level decreased, but was significantly reduced in the pgi-knockout cells. Comparatively, eno expression could not be decreased compared to the parent strain, but we found that increased eno expression resulted in a decreased specific growth rate. 13 C-MFA revealed that the metabolic flux distribution was not altered by an increased eno expression level, but the overall metabolic activity of the central metabolism decreased. Furthermore, to evaluate the impact of perturbed expression of pgi and eno genes on changes in metabolic fluxes in E. coli quantitatively, metabolic sensitivity analysis was performed. As a result, the perturbed expression of pgi gene had a great impact to the metabolic flux changes in the branch point between the glycolysis and pentose phosphate pathway, isocitrate dehydrogenase reaction, anaplerotic pathways and Entner-Doudoroff pathway. In contrast, the impact of perturbed eno expression to the flux changes in E. coli metabolic network was small.
Our results indicate that the response of metabolic fluxes to perturbation to pgi expression was different from that to eno expression; perturbations to pgi expression affect the reaction related to the Pgi protein function, the isocitrate dehydrogenase reaction, anaplerotic reactions and Entner-Doudoroff pathway. Meanwhile, eno expression seems to affect the overall metabolic activity, and the impact of perturbed eno expression on metabolic flux change is small. Using the gene expression control system reported here, it is expected that we can analyze the response and adaptation process of complex biological networks to gene expression perturbations.
[show abstract][hide abstract] ABSTRACT: Advances in genome sequencing have revolutionized biology by providing the molecular blueprints for thousands of living organisms.
Yet, the functions of a large fraction, as much as one-half, of the component parts remain unknown even for the best understood
organisms, including Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae. Here, we describe our development of comprehensive genomic resources (ORFeome clone sets and mutant libraries) for systematic
functional analysis of E. coli, summaries on our use of these resources, the GenoBase information resource for handling high-throughput experimental data
obtained with them, and our creation of user workspaces at our Protein Function Elucidation Team (http://www.PrFEcT.org) website.
[show abstract][hide abstract] ABSTRACT: Systems biology and functional genomics require genome-wide datasets and resources. Complete sets of cloned open reading frames (ORFs) have been made for about a dozen bacterial species and allow researchers to express and study complete proteomes in a high-throughput fashion.
We have constructed an open reading frame (ORFeome) collection of 3974 or 94% of the known Escherichia coli K-12 ORFs in Gateway entry vector pENTR/Zeo. The collection has been used for protein expression and protein interaction studies. For example, we have compared interactions among YgjD, YjeE and YeaZ proteins in E. coli, Streptococcus pneumoniae, and Staphylococcus aureus. We also compare this ORFeome with other Gateway-compatible bacterial ORFeomes and show its utility for comparative functional genomics.
The E. coli ORFeome provides a useful resource for functional genomics and other areas of protein research in a highly flexible format. Our comparison with other ORFeomes makes comparative analyses straighforward and facilitates direct comparisons of many proteins across many genomes.
[show abstract][hide abstract] ABSTRACT: Since genomic sequencing project launched, during in 1990s, biological research environments has been dramatically changed
by developments of inter-disciplinary fields between biology and others such as chemistry, physics, information science, mathematics
and engineering. Many high-throughput systems to obtain comprehensive analysis results have become available. As the result,
accumulation of experimental data is now growing exponentially like sequence data in public databases. Experimental resources,
such as plasmid clone and deletion mutant libraries, are the products of such high-throughput systems, and at the same time,
motive force to generate further comprehensive information from xperimental analyses. In this manuscript, we summarize the
situation about the experimental resources and how they have contributed in biology fields, especially in the 21st new generation
of biology, such as systems biology.
[show abstract][hide abstract] ABSTRACT: Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli.
[show abstract][hide abstract] ABSTRACT: Physical and functional interactions define the molecular organization of the cell. Genetic interactions, or epistasis, tend to occur between gene products involved in parallel pathways or interlinked biological processes. High-throughput experimental systems to examine genetic interactions on a genome-wide scale have been devised for Saccharomyces cerevisiae, Schizosaccharomyces pombe, Caenorhabditis elegans and Drosophila melanogaster, but have not been reported previously for prokaryotes. Here we describe the development of a quantitative screening procedure for monitoring bacterial genetic interactions based on conjugation of Escherichia coli deletion or hypomorphic strains to create double mutants on a genome-wide scale. The patterns of synthetic sickness and synthetic lethality (aggravating genetic interactions) we observed for certain double mutant combinations provided information about functional relationships and redundancy between pathways and enabled us to group bacterial gene products into functional modules.
[show abstract][hide abstract] ABSTRACT: Bacterial drug resistance is a serious concern for human health. Multidrug efflux pumps export a broad variety of substrates out of the cell and thereby convey resistance to the host. In Escherichia coli, the AcrB:AcrA:TolC efflux complex forms a principal transporter for which structures of the individual component proteins have been determined in isolation. Here, we present the X-ray structure of AcrB in complex with a single transmembrane protein, assigned by mass spectrometry as YajC. A specific rotation of the periplasmic porter domain of AcrB is also revealed, consistent with the hypothesized "twist-to-open" mechanism for TolC activation. Growth experiments with yajc-deleted E. coli reveal a modest increase in the organism's susceptibility to beta-lactam antibiotics, but this effect could not conclusively be attributed to the loss of interactions between YajC and AcrB.
[show abstract][hide abstract] ABSTRACT: Protein-protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni2+-NTA column were identified by MALDI-TOF MS (matrix-assisted laser desorption ionization time of flight mass spectrometry). An extended analysis of these interacting networks by bioinformatics and experimentation should provide new insights and novel strategies for E. coli systems biology.
Genome Research 06/2006; 16(5):686-91. · 14.40 Impact Factor