Citations

348 Citations Found

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4196738/

Lahiri, S., Chao, J. T., Tavassoli, S., Wong, A. K., Choudhary, V., Young, B. P., Loewen, C. J., … Prinz, W. A. PLoS Biol. 2014 Oct; 12(10): e1001969. Mitochondrial membrane biogenesis and lipid metabolism require phospholipid transfer from the endoplasmic reticulum (ER) to mitochondria. Transfer is thought to occur at regions of close contact of these organelles and to be nonvesicular, but the mechanism is not known. Here we used a novel genetic screen in S. cerevisiae to identify mutants with defects in lipid exchange between the ER and mitochondria. We show that a strain missing multiple components of the conserved ER membrane protein complex (EMC) has decreased phosphatidylserine (PS) transfer from the ER to mitochondria. Mitochondria from this strain have significantly reduced levels of PS and its derivative phosphatidylethanolamine (PE). Cells lacking EMC proteins and the ER–mitochondria tethering complex called ERMES (the ER–mitochondria encounter structure) are inviable, suggesting that the EMC also functions as a tether. These defects are corrected by expression of an engineered ER–mitochondrial tethering protein that artificially tethers the ER to mitochondria. EMC mutants have a significant reduction in the amount of ER tethered to mitochondria even though ERMES remained intact in these mutants, suggesting that the EMC performs an additional tethering function to ERMES. We find that all Emc proteins interact with the mitochondrial translocase of the outer membrane (TOM) complex protein Tom5 and this interaction is important for PS transfer and cell growth, suggesting that the EMC forms a tether by associating with the TOM complex. Together, our findings support that the EMC tethers ER to mitochondria, which is required for phospholipid synthesis and cell growth.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478535/

Zhu, J., Heinecke, D., Mulla, W. A., Bradford, W. D., Rubinstein, B., Box, A., Haug, J. S., … Li, R. Mol Biol Cell. 2016 Mar 15; 27(6): 1015–1025. Errors in mitosis are a primary cause of chromosome instability (CIN), generating aneuploid progeny cells. Whereas a variety of factors can influence CIN, under most conditions mitotic errors are rare events that have been difficult to measure accurately. Here we report a green fluorescent protein−based quantitative chromosome transmission fidelity (qCTF) assay in budding yeast that allows sensitive and quantitative detection of CIN and can be easily adapted to high-throughput analysis. Using the qCTF assay, we performed genome-wide quantitative profiling of genes that affect CIN in a dosage-dependent manner and identified genes that elevate CIN when either increased (icCIN) or decreased in copy number (dcCIN). Unexpectedly, qCTF screening also revealed genes whose change in copy number quantitatively suppress CIN, suggesting that the basal error rate of the wild-type genome is not minimized, but rather, may have evolved toward an optimal level that balances both stability and low-level karyotype variation for evolutionary adaptation.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4791123/

French, S., Mangat, C., Bharat, A., Côté, J. P., Mori, H., & Brown, E. D. (2016). Mol Biol Cell. 2016 Mar 15; 27(6): 1015–1025. While genetic perturbation has been the conventional route to probing bacterial systems, small molecules are showing great promise as probes for cellular complexity. Indeed, systematic investigations of chemical-genetic interactions can provide new insights into cell networks and are often starting points for understanding the mechanism of action of novel chemical probes. We have developed a robust and sensitive platform for chemical-genomic investigations in bacteria. The approach monitors colony volume kinetically using transmissive scanning measurements, enabling acquisition of growth rates and conventional endpoint measurements. We found that chemical-genomic profiles were highly sensitive to concentration, necessitating careful selection of compound concentrations. Roughly 20,000,000 data points were collected for 15 different antibiotics. While 1052 chemical-genetic interactions were identified using the conventional endpoint biomass approach, adding interactions in growth rate resulted in 1564 interactions, a 50–200% increase depending on the drug, with many genes uncharacterized or poorly annotated. The chemical-genetic interaction maps generated from these data reveal common genes likely involved in multidrug resistance. Additionally, the maps identified deletion backgrounds exhibiting class-specific potentiation, revealing conceivable targets for combination approaches to drug discovery. This open platform is highly amenable to kinetic screening of any arrayable strain collection, be it prokaryotic or eukaryotic.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5120140/

Côté, J. P., French, S., Gehrke, S. S., MacNair, C. R., Mangat, C. S., Bharat, A., & Brown, E. D. mBio. 2016 Nov-Dec; 7(6): e01714-16. Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo. To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio) to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli. Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358765/

Liu, G., Lanham, C., Buchan, J. R., & Kaplan, M. E. PLoS One. 2017; 12(3): e0174128. Saccharomyces cerevisiae (budding yeast) is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc) transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids) or genome mutation (e.g., gene mutation, deletion, epitope tagging) is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5400513/

Koo, B. M., Kritikos, G., Farelli, J. D., Todor, H., Tong, K., Kimsey, H., Wapinski, I., Galardini, M., Cabal, A., Peters, J. M., Hachmann, A. B., Rudner, D. Z., Allen, K. N., Typas, A., … Gross, C. A. Cell Syst. 2017 Mar 22; 4(3): 291–305.e7. A systems level understanding of Gram-positive bacteria is important from both an environmental and health perspective, and is most easily obtained when high-quality, validated genomic resources are available. To this end, we constructed two ordered, barcoded, erythromycin-resistance- and kanamycin-resistance-marked single-gene deletion libraries of the Gram-positive model organism, Bacillus subtilis. The libraries comprise 3968 and 3970 genes, respectively, and overlap in all but four genes. Using these libraries, we update the set of essential genes known for this organism, provide a comprehensive compendium of B. subtilis auxotrophic genes, and identify genes required for utilizing specific carbon and nitrogen sources, as well as those required for growth at low temperature. We report the identification of enzymes catalyzing several missing steps in amino acid biosynthesis. Finally, we describe a suite of high-throughput phenotyping methodologies and apply them to provide a genome-wide analysis of competence and sporulation. Altogether, we provide versatile resources for studying gene function and pathway and network architecture in Gram-positive bacteria.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3235803/

Reece-Hoyes, J. S., Diallo, A., Lajoie, B., Kent, A., Shrestha, S., Kadreppa, S., Pesyna, C., Dekker, J., Myers, C. L., … Walhout, A. J. Mol Syst Biol. 2016 Dec; 12(12): 893. A major challenge in systems biology is to understand the gene regulatory networks that drive development, physiology and pathology. Interactions between transcription factors and regulatory genomic regions provide the first level of gene control. Gateway-compatible yeast one-hybrid (Y1H) assays present a convenient method to identify and characterize the repertoire of transcription factors that can bind a DNA sequence of interest. To delineate genome-scale regulatory networks, however, large sets of DNA fragments need to be processed at high throughput and high coverage. Here, we present “enhanced” Y1H (eY1H) assays that utilize a robotic mating platform with a set of improved Y1H reagents and automated readout quantification. We demonstrate that eY1H assays provide excellent coverage and identify interacting transcription factors for multiple DNA fragments in a short amount of time. eY1H assays will be an important tool for gene regulatory network mapping in Caenorhabditis elegans and other model organisms, as well as humans.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5199130/

Urbanus, M. L., Quaile, A. T., Stogios, P. J., Morar, M., Rao, C., Di Leo, R., Evdokimova, E., Lam, M., Oatway, C., Cuff, M. E., Osipiuk, J., Michalska, K., Nocek, B. P., Taipale, M., Savchenko, A., … Ensminger, A. W. Mol Syst Biol. 2017 Feb; 13(2): 913. Pathogens deliver complex arsenals of translocated effector proteins to host cells during infection, but the extent to which these proteins are regulated once inside the eukaryotic cell remains poorly defined. Among all bacterial pathogens, Legionella pneumophila maintains the largest known set of translocated substrates, delivering over 300 proteins to the host cell via its Type IVB, Icm/Dot translocation system. Backed by a few notable examples of effector–effector regulation in L. pneumophila, we sought to define the extent of this phenomenon through a systematic analysis of effector–effector functional interaction. We used Saccharomyces cerevisiae, an established proxy for the eukaryotic host, to query > 108,000 pairwise genetic interactions between two compatible expression libraries of ~330 L. pneumophila‐translocated substrates. While capturing all known examples of effector–effector suppression, we identify fourteen novel translocated substrates that suppress the activity of other bacterial effectors and one pair with synergistic activities. In at least nine instances, this regulation is direct—a hallmark of an emerging class of proteins called metaeffectors, or “effectors of effectors”. Through detailed structural and functional analysis, we show that metaeffector activity derives from a diverse range of mechanisms, shapes evolution, and can be used to reveal important aspects of each cognate effector's function. Metaeffectors, along with other, indirect, forms of effector–effector modulation, may be a common feature of many intracellular pathogens—with unrealized potential to inform our understanding of how pathogens regulate their interactions with the host cell.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5327727/

Smith, J. D., Schlecht, U., Xu, W., Suresh, S., Horecka, J., Proctor, M. J., Aiyar, R. S., Bennett, R. A., Chu, A., Li, Y. F., Roy, K., Davis, R. W., Steinmetz, L. M., Hyman, R. W., Levy, S. F., … St Onge, R. P. Mol Syst Biol. 2017 Feb; 13(2): 913. The low costs of array‐synthesized oligonucleotide libraries are empowering rapid advances in quantitative and synthetic biology. However, high synthesis error rates, uneven representation, and lack of access to individual oligonucleotides limit the true potential of these libraries. We have developed a cost‐effective method called Recombinase Directed Indexing (REDI), which involves integration of a complex library into yeast, site‐specific recombination to index library DNA, and next‐generation sequencing to identify desired clones. We used REDI to generate a library of ~3,300 DNA probes that exhibited > 96% purity and remarkable uniformity (> 95% of probes within twofold of the median abundance). Additionally, we created a collection of ~9,000 individually accessible CRISPR interference yeast strains for > 99% of genes required for either fermentative or respiratory growth, demonstrating the utility of REDI for rapid and cost‐effective creation of strain collections from oligonucleotide pools. Our approach is adaptable to any complex DNA library, and fundamentally changes how these libraries can be parsed, maintained, propagated, and characterized.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4096534/

Takeuchi, R., Tamura, T., Nakayashiki, T., Tanaka, Y., Muto, A., Wanner, B. L., & Mori, H. BMC Microbiol. 2014; 14: 171. 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.