Natsuko Yamamoto

eSGA: E. coli Synthetic Genetic Array analysis

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.NOTE: In the version of this article initially published online two author names (Gabriel Moreno-Hagelseib and Constantine Christopolous) were spelled incorrectly. The correct author names are Gabriel Moreno-Hagelsieb and Constantine Christopoulos. The error has been corrected for the print, PDF and HTML versions of this article.

High-throughput, quantitative analyses of genetic interactions in E. coli.

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.

Update on the Keio collection of Escherichia coli single-gene deletion mutants

Mol Syst Biol. 5: 335 The Keio collection (Baba et al , 2006) has been established as a set of single‐gene deletion mutants of Escherichia coli K‐12. These mutants have a precisely designed deletion from the second codon from the seventh to the last codon of each predicted ORF. Further information is available at http://sal.cs.purdue.edu:8097/GB7/index.jsp or http://ecoli.naist.jp/. The distribution is now being handled by the National Institute of Genetics of Japan (http://www.shigen.nig.ac.jp/ecoli/pec/index.jsp). To date more than 4 million samples have been distributed worldwide. As we described earlier (Baba et al , 2006), gene amplification during construction is likely to have led to a small number of mutants with genetic duplications. The design of the Keio deletions was based on annotations that are now outdated. Of 4288 ORFs targeted, mutants were obtained for 3985 (Baba et al , 2006). Re‐annotation based on highly accurate sequencing of E. coli K‐12 (Hayashi et al , 2006) led to changing many coding regions and the total number of ORFs to 4296, including pseudogenes (Riley et al , 2006) (Supplementary Table I). The recent E. coli K‐12 MG1655 GenBank record (U0096, released in December 2008) has an additional 97 ORFs (exclusive of the ORFs in IS elements, Supplementary Table II) that were not targeted. Of these 4214 annotated ORFs, 4186 were targeted for deletion and 28 were not (Supplementary Table III), which resulted in the isolation of two independent mutants for 3864 targeted ORFs. No deletion was found for 299 ORFs, which are candidates for essential genes. Deletions were also isolated for 23 other ORFs; however, re‐annotation led to re‐classification of these ORFs as ‘split ORFs’, because their coding …

The Escherichia coli K-12 ORFeome: a resource for comparative molecular microbiology

BackgroundSystems 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.ResultsWe 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.ConclusionsThe 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.

GenoBase: comprehensive resource database of Escherichia coli K-12

Comprehensive experimental resources, such as ORFeome clone libraries and deletion mutant collections, are fundamental tools for elucidation of gene function. Data sets by omics analysis using these resources provide key information for functional analysis, modeling and simulation both in individual and systematic approaches. With the long-term goal of complete understanding of a cell, we have over the past decade created a variety of clone and mutant sets for functional genomics studies of Escherichia coli K-12. We have made these experimental resources freely available to the academic community worldwide. Accordingly, these resources have now been used in numerous investigations of a multitude of cell processes. Quality control is extremely important for evaluating results generated by these resources. Because the annotation has been changed since 2005, which we originally used for the construction, we have updated these genomic resources accordingly. Here, we describe GenoBase (http://ecoli.naist.jp/GB/), which contains key information about comprehensive experimental resources of E. coli K-12, their quality control and several omics data sets generated using these resources.

Combinatorial selection for replicable RNA by Qβ replicase while maintaining encoded gene function

Construction of a complex artificial self-replication system is challenging in the field of in vitro synthetic biology. Recently, we developed a translation-coupled RNA replication system, wherein an artificial genomic RNA replicates with the Qβ RNA replicase gene encoded on itself. The challenge is to introduce additional genes into the RNA to develop a complex system that mimics natural living systems. However, most RNA sequence encoding genes are not replicable by the Qβ replicase owing to its requirement for strong secondary structures throughout the RNA sequence that are absent in most genes. In this study, we establish a new combinatorial selection method to find an RNA sequence with secondary structures and functional amino acid sequences of the encoded gene. We selected RNA sequences based on their in vitro replication and in vivo gene functions. First, we used the α-domain gene of β-galactosidase as a model-encoding gene, with functional selection based on blue-white screening. Through the combinatorial selection, we developed more replicable RNAs while maintaining the function of the encoded α-domain. The selected sequence improved the affinity between the minus strand RNA and Qβ replicase. Second, we established an in vivo selection method applicable to a broader range of genes by using an Escherichia coli strain with one of the essential genes complemented with a plasmid. We performed the combinatorial selection using an RNA encoding serS and obtained more replicable RNA encoding functional serS gene. These results suggest that combinatorial selection methods are useful for the development of RNA sequences replicable by Qβ replicase while maintaining the encoded gene function.

Resources for Escherichia coli Systems Biology

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.

Towards Elucidation of the Escherichia coli K-12 Unknowneome

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.