Biolog Phenotype MicroArray
     Serious Technology for Serious Microbiology September 2007
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Useful Links

Bacillus subtilis Metabolism and Gene Regulation Studied in Two Recent Applications of Phenotype MicroArray Technology

Phenotype MicroArray
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  Genome-scale reconstruction of metabolic network in bacillus subtilis based on high-throughput phenotyping and gene essentiality data.
Oh YK, Palsson BO, Park SM, Schilling CH, Mahadevan R. Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, ON M5S3E5. This landmark paper is the first example of a careful and thorough use of Phenotype MicroArray data to challenge and improve a whole-cell bioinformatics model of Bacilllus subtilis. Network gap analysis was used to identify 48 essential reactions missing from the genome annotation. Detailed growth rate analysis revealed incorrect modeling outcomes which were subsequently improved by adding 75 reactions. Simulation of growth phenotypes of knock-out strains were verified in 720 of 766 cases. Overall, the integrated analysis of substrate utilization and gene essentiality data led to identification of 80 required enzymes and improved the genome annotation for Bacillus subtilis.
 
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  Regulatory Overlap and Functional Redundancy Among Bacillus subtilis Extracytoplasmic Function (ECF) (sigma)-Factors.
Mascher T, Hachmann AB, Helmann JD. Department of Microbiology, Cornell University, Ithaca, NY 14853-8101, USA. The biological role of extracytoplasmic function sigma factors in Bacillus subtilis was examined in this paper. Seven genes encode these sigma factors, so the authors constructed strains with multiple gene knockouts and then used Phenotype MicroArray technology to test the phenotypes of their strains. A triple mutant in sigM, sigW, and sigX exhibited greatly increased sensitivity to detergents, polymyxin B, B-lactams, and D-cycloserine.
 
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Phenotype MicroArray Technology
Biolog's Phentoype MicroArray technology enables researchers to evaluate nearly 2000 phenotypes of a microbial cell in a single experiment. This integrated system of cellular assays, instrumentation and bioinformatics software provides cellular knowledge that complements molecular information, helping you interpret and find the relevant aspects in massive amounts of gene expression or proteomics data. Through comprehensive and precise quantitation of phenotypes, researchers are able to obtain an unbiased perspective of the effect on cells of genetic differences, environmental change, exposure to chemicals or drugs, and more.
 
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