@article {37,
	title = {Genomic analysis of the Opi- phenotype.},
	journal = {Genetics},
	volume = {173},
	year = {2006},
	month = {2006 Jun},
	pages = {621-34},
	abstract = {Most of the phospholipid biosynthetic genes of Saccharomyces cerevisiae are coordinately regulated in response to inositol and choline. Inositol affects the intracellular levels of phosphatidic acid (PA). Opi1p is a repressor of the phospholipid biosynthetic genes and specifically binds PA in the endoplasmic reticulum. In the presence of inositol, PA levels decrease, releasing Opi1p into the nucleus where it represses transcription. The opi1 mutant overproduces and excretes inositol into the growth medium in the absence of inositol and choline (Opi(-) phenotype). To better understand the mechanism of Opi1p repression, the viable yeast deletion set was screened to identify Opi(-) mutants. In total, 89 Opi(-) mutants were identified, of which 7 were previously known to have the Opi(-) phenotype. The Opi(-) mutant collection included genes with roles in phospholipid biosynthesis, transcription, protein processing/synthesis, and protein trafficking. Included in this set were all nonessential components of the NuA4 HAT complex and six proteins in the Rpd3p-Sin3p HDAC complex. It has previously been shown that defects in phosphatidylcholine synthesis (cho2 and opi3) yield the Opi(-) phenotype because of a buildup of PA. However, in this case the Opi(-) phenotype is conditional because PA can be shuttled through a salvage pathway (Kennedy pathway) by adding choline to the growth medium. Seven new mutants present in the Opi(-) collection (fun26, kex1, nup84, tps1, mrpl38, mrpl49, and opi10/yol032w) were also suppressed by choline, suggesting that these affect PC synthesis. Regulation in response to inositol is also coordinated with the unfolded protein response (UPR). Consistent with this, several Opi(-) mutants were found to affect the UPR (yhi9, ede1, and vps74).},
	keywords = {Gene Expression Regulation, Fungal, Genes, Fungal, Genes, Reporter, Genome, Fungal, Genomics, Inositol, Lac Operon, Models, Biological, Mutation, Phenotype, Phospholipids, Protein Folding, Repressor Proteins, Saccharomyces cerevisiae, Saccharomyces cerevisiae Proteins},
	issn = {0016-6731},
	doi = {10.1534/genetics.106.057489},
	author = {Hancock, Leandria C and Behta, Ryan P and Lopes, John M}
}
@article {40,
	title = {Genomic analysis of PIS1 gene expression.},
	journal = {Eukaryot Cell},
	volume = {4},
	year = {2005},
	month = {2005 Mar},
	pages = {604-14},
	abstract = {The Saccharomyces cerevisiae PIS1 gene is essential and required for the final step in the de novo synthesis of phosphatidylinositol. Transcription of the PIS1 gene is uncoupled from the factors that regulate other yeast phospholipid biosynthetic genes. Most of the phospholipid biosynthetic genes are regulated in response to inositol and choline via a regulatory circuit that includes the Ino2p:Ino4p activator complex and the Opi1p repressor. PIS1 is regulated in response to carbon source and anaerobic growth conditions. Both of these regulatory responses are modest, which is not entirely surprising since PIS1 is essential. However, even modest regulation of PIS1 expression has been shown to affect phosphatidylinositol metabolism and to affect cell cycle progression. This prompted the present study, which employed a genomic screen, database mining, and more traditional promoter analysis to identify genes that affect PIS1 expression. A screen of the viable yeast deletion set identified 120 genes that affect expression of a PIS1-lacZ reporter. The gene set included several peroxisomal genes, silencing genes, and transcription factors. Factors suggested by database mining, such as Pho2 and Yfl044c, were also found to affect PIS1-lacZ expression. A PIS1 promoter deletion study identified an upstream regulatory sequence element that was required for carbon source regulation located downstream of three previously defined upstream activation sequence elements. Collectively, these studies demonstrate how a collection of genomic and traditional strategies can be implemented to identify a set of genes that affect the regulation of an essential gene.},
	keywords = {Gene Expression Profiling, Gene Expression Regulation, Fungal, Gene Silencing, Genome, Fungal, Glycerol, Oligonucleotide Array Sequence Analysis, Peroxisomes, Phospholipids, Promoter Regions, Genetic, Recombinant Fusion Proteins, Saccharomyces cerevisiae, Transferases (Other Substituted Phosphate Groups)},
	issn = {1535-9778},
	doi = {10.1128/EC.4.3.604-614.2005},
	author = {Gardocki, Mary E and Bakewell, Margaret and Kamath, Deepa and Robinson, Kelly and Borovicka, Kathy and Lopes, John M}
}
@article {558,
	title = {Cleaning up with genomics: applying molecular biology to bioremediation.},
	journal = {Nat Rev Microbiol},
	volume = {1},
	year = {2003},
	month = {2003 Oct},
	pages = {35-44},
	abstract = {Bioremediation has the potential to restore contaminated environments inexpensively yet effectively, but a lack of information about the factors controlling the growth and metabolism of microorganisms in polluted environments often limits its implementation. However, rapid advances in the understanding of bioremediation are on the horizon. Researchers now have the ability to culture microorganisms that are important in bioremediation and can evaluate their physiology using a combination of genome-enabled experimental and modelling techniques. In addition, new environmental genomic techniques offer the possibility for similar studies on as-yet-uncultured organisms. Combining models that can predict the activity of microorganisms that are involved in bioremediation with existing geochemical and hydrological models should transform bioremediation from a largely empirical practice into a science.},
	keywords = {Bacteria, Bacterial Physiological Phenomena, Biodegradation, Environmental, Ecology, Environmental Microbiology, Fungi, Genetic Vectors, Genome, Bacterial, Genome, Fungal, Genomics, Models, Biological, Molecular Biology},
	issn = {1740-1526},
	doi = {10.1038/nrmicro731},
	author = {Lovley, Derek R}
}
