Citations

348 Citations Found

http://www.ncbi.nlm.nih.gov/pubmed/24463526

Yong HT, Yamamoto N, Takeuchi R, Hsieh YJ Genes Genet Syst. 2013;88(4):233-40 Bacteria/SGA Genetic interaction networks are especially useful for functional assignment of genes and gaining new insights into the systems-level organization of the cell. While studying interactions of nonessential genes can be relatively straight-forward via use of deletion mutants, different approaches must be used to reveal interactions of essential genes due to their indispensability. One method shown to be useful for revealing interactions of essentialgenes requires tagging the query protein. However, this approach can be complicated by mutational effects of potential hypomorphic alleles. Here, we describe a pilot study for a new scheme of systematically studying the interactions of essential genes. Our method uses a low-copy, F-based, complementing plasmid, pFE604T, from which the essential gene is conditionally expressed. The essential gene is expressed at lower levels, producing a moderate growth defect in a query host. Secondary mutations are introduced into the query host by conjugation and the resultant exconjugants are scored for growth by imaging them over time. We report results from studying five essential query genes: dnaN, ftsW, trmD, yrfF and yjgP, showing (on average) interactions with nearly 80 nonessential genes. This system should prove useful for genome-wide analyses of otheressential genes in E. coli K-12.

http://www.ncbi.nlm.nih.gov/pubmed/23292777

Nakayashiki T, Mori H J Bacteriol. 2013 Mar;195(6):1226–35 We performed a screening of hydroxyurea (HU)-sensitive mutants using a single-gene-deletion mutant collection in Escherichia coli. HU inhibits ribonucleotide reductase (RNR), which leads to arrest of the replication fork. Surprisingly, the wild-type was less resistant to HU than the average for the Keio Collection. Respiration-defective mutants were significantly more resistant to HU, suggesting that the generation of reactive oxygen species(ROS) contributes to cell death. High-throughput screening revealed that 15 mutants were completely sensitive on plates containing 7.5 mM HU. Unexpectedly, translation-related mutants based on COG categorization were the most enriched, and three of them were deletion mutants ofnonessential ribosomal proteins (L1, L32, and L36). We found that, in these mutants, an increased membrane stress response was provoked, resulting in increased ROS generation. The addition of OH radical scavenger thiourea rescued the HU sensitivity of these mutants, suggesting that ROS generation is the direct cause of cell death. Conversely, both the deletion of rpsF and the deletion of rimK, which encode S6 and S6 modification enzymes, respectively, showed an HU-resistant phenotype. These mutants increased the copy number of the p15A-based plasmid and exhibited reduced basal levels of SOS response. The data suggest that nonessential proteins indirectly affect the DNA-damaging process.

http://www.ncbi.nlm.nih.gov/pubmed/23457245

Nakayashiki T, Saito N, Takeuchi R, Kadokura H, Nakahigashi K, Wanner BL, Mori H J Bacteriol. 2013 Apr 9;195(9):2039–49 We have performed a screening of hydroxyurea (HU)-sensitive mutants using a single-gene-deletion mutant collection in Escherichia coli K-12. HU inhibits ribonucleotide reductase (RNR), an enzyme that catalyzes the formation of deoxyribonucleotides. Unexpectedly, seven of the mutants lacked genes that are required for the incorporation of sulfur into a specific tRNA modification base, 5-methylaminomethyl-2-thiouridine (mnm(5)s(2)U), via persulfide relay. We found that the expression of RNR in the mutants was reduced to about one-third both in the absence and presence of HU, while sufficient deoxynucleoside triphosphate (dNTP) was maintained in the mutants in the absence of HU but a shortage occurred in the presence of HU. Trans-supply of an RNR R2 subunit rescued the HU sensitivity of these mutants. The mutants showed high intracellularATP/ADP ratios, and overexpression of Hda, which catalyzes the conversion of DnaA-ATP to DnaA-ADP, rescued the HU sensitivity of the mutants, suggesting that DnaA-ATP represses RNR expression. The high intracellular ATP/ADP ratios were due to high respiration activity in the mutants. Our data suggested that intracellular redox was inclined toward the reduced state in these mutants, which may explain a change in RNR activity by reduction of the catalytically formed disulfide bond and high respiration activity by the NADH reducing potential. The relation between persulfide relay and intracellular redox is discussed.

http://www.ncbi.nlm.nih.gov/pubmed/24964927

Takeuchi R, Tamura T, Nakayashiki T, Tanaka Y, Muto A, Wanner BL, Mori H BMC Microbiol. BioMed Central Ltd; 2014;14(1):171 BACKGROUND: Precise quantitative growth measurements and detection of small growth changes in high-throughput manner is essential for fundamental studies of bacterial cell. However, an inherent tradeoff for measurement quality in high-throughput methods sacrifices some measurement quality. A key challenge has been how to enhance measurement quality without sacrificing throughput. RESULTS: We developed a new high-throughput measurement system, termed Colony-live. Here we show that Colony-live provides accurate measurement of three growth values (lag time of growth (LTG), maximum growth rate (MGR), and saturation point growth (SPG)) by visualizing colony growth over time. By using a new normalization method for colony growth, Colony-live gives more precise and accurate growth values than the conventional method. We demonstrated the utility of Colony-live by measuring growth values for the entire Keio collection of Escherichia coli single-gene knockout mutants. By using Colony-live, we were able to identify subtle growth defects of single-gene knockout mutants that were undetectable by the conventional method quantified by fixed time-point camera imaging. Further, Colony-live can reveal genes that influence the length of the lag-phase and the saturation point of growth. CONCLUSION: Measurement quality is critical to achieving the resolution required to identify unique phenotypes among a diverse range of phenotypes. Sharing high-quality genome-wide datasets should benefit many researchers who are interested in specific gene functions or the architecture of cellular systems. Our Colony-live system provides a new powerful tool to accelerate accumulation of knowledge of microbial growth phenotypes.

http://www.ncbi.nlm.nih.gov/pubmed/19160513

Typas A, Nichols RJ, Siegele DA, Shales M, Collins SR, Lim B, Braberg H, Yamamoto N, Takeuchi R, Wanner BL, Mori H, Weissman JS, Krogan NJ, Gross CA Nat Methods. 2008 Sep;5(9):781–7 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 andquantitative 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.

http://www.ncbi.nlm.nih.gov/pubmed/18677321

Butland G, Babu M, Díaz-Mejía JJ, Bohdana F, Phanse S, Gold B, Yang W, Li J, Gagarinova AG, Pogoutse O, Mori H, Wanner BL, Lo H, Wasniewski J, Christopolous C, Ali M, Venn P, Safavi-Naini A, Sourour N, Caron S, Choi JY, Laigle L, Nazarians-Armavil A, Deshpande A, Joe S, Datsenko KA, Yamamoto N, Andrews BJ, Boone C, Ding H, Sheikh B, Moreno-Hagelseib G, Greenblatt JF, Emili A Nat Methods. 2008 Sep;5(9):789–95 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.

http://www.ncbi.nlm.nih.gov/pubmed/21877280

Babu M, Gagarinova A, Emili A Methods Mol Biol. 2011;781:99–126 Cellular processes are carried out through a series of molecular interactions. Various experimental approaches can be used to investigate thesefunctional relationships on a large-scale. Recently, the power of investigating biological systems from the perspective of genetic (gene-gene, or epistatic) interactions has been evidenced by the ability to elucidate novel functional relationships. Examples of functionally related genes include genes that buffer each other's function or impinge on the same biological process. Genetic interactions have traditionally been investigated in bacteria by combining pairs of mutations (for example, gene deletions) and assessing deviation of the phenotype of each double mutant from an expected neutral (or no interaction) phenotype. Fitness is a particularly convenient phenotype to measure: when the double mutant grows faster or slower than expected, the two mutated genes are said to show alleviating or aggravating interactions, respectively. The most commonly used neutral model assumes that the fitness of the double mutant is equal to the product of individual single mutant fitness. A striking genetic interaction is exemplified by the loss of two nonessential genes that buffer each other in performing an essential biological function: deleting only one of these genes produces no detectable fitness defect; however, loss of both genes simultaneously results in systems failure, leading to synthetic sickness or lethality. Systematic large-scale genetic interaction screens have been used to generate functional maps for model eukaryotic organisms, such as yeast, to describe the functional organization of gene products into pathways and protein complexes within a cell. They also reveal the modular arrangement and cross-talk of pathways and complexes within broader functional neighborhoods (Dixon et al. Annu Rev Genet 43:601-625, 2009). Here, we present a high-throughput quantitative Escherichia coli synthetic genetic array (eSGA) screening procedure, which we developed to systematically infer genetic interactions by scoring growth defects among large numbers of double mutants in a classic gram-negative bacterium. The eSGA method exploits the rapid colony growth, ease of genetic manipulation, and natural efficient genetic exchange via conjugation of laboratory E. coli strains. Replica pinning is used to grow and mate arrayed sets of single-gene mutant strains as well as to select double mutants en mass. Strain fitness, which is used as the eSGA readout, is quantified by the digital imaging of the plates and subsequent measuring and comparing single and double mutant colony sizes. While eSGA can be used to screen select mutants to probe the functions of individual genes; using eSGA more broadly to collect genetic interaction data for many combinations of genes can help reconstruct a functional interaction network to reveal novel links and components of biological pathways as well as unexpected connections between pathways. A variety of bacterial systems can be investigated, wherein the genes impinge on a essential biological process (e.g., cell wall assembly, ribosome biogenesis, chromosome replication) that are of interest from the perspective of drug development (Babu et al. Mol Biosyst 12:1439-1455, 2009). We also show how genetic interactions generated by high-throughput eSGA screens can be validated by manual small-scale genetic crosses and by genetic complementation and gene rescue experiments.

http://www.ncbi.nlm.nih.gov/pubmed/24706510

Zhang R, Patena W, Armbruster U, Gang SS, Blum SR, Jonikas MC Plant Cell. 2014 Apr 4;26(4):1398-1409 A high-throughput genetic screening platform in a single-celled photosynthetic eukaryote would be a transformative addition to the plant biology toolbox. Here, we present ChlaMmeSeq (Chlamydomonas MmeI-based insertion site Sequencing), a tool for simultaneous mapping of tens of thousands of mutagenic insertion sites in the eukaryotic unicellular green alga Chlamydomonas reinhardtii. We first validated ChlaMmeSeq by in-depth characterization of individual insertion sites. We then applied ChlaMmeSeq to a mutant pool and mapped 11,478 insertions, covering 39% of annotated protein coding genes. We observe that insertions are distributed in a manner largely indistinguishable from random, indicating that mutantsin nearly all genes can be obtained efficiently. The data reveal that sequence-specific endonucleolytic activities cleave the transforming DNA and allow us to propose a simple model to explain the origin of the poorly understood exogenous sequences that sometimes surround insertion sites. ChlaMmeSeq is quantitatively reproducible, enabling its use for pooled enrichment screens and for the generation of indexed mutant libraries. Additionally, ChlaMmeSeq allows genotyping of hits from Chlamydomonas screens on an unprecedented scale, opening the door to comprehensive identification of genes with roles in photosynthesis, algal lipid metabolism, the algal carbon-concentrating mechanism, phototaxis, the biogenesis and function of cilia, and other processes for which C. reinhardtii is a leading model system.