ABSTRACT
A murF conditional mutant was used to evaluate the effect of suboptimal transcription of this gene on the transcriptome of the methicillin-resistant Staphylococcus aureus strain COL. The mutant was grown in the presence of optimal and suboptimal concentrations of the inducer, and the relative levels of transcription of genes were evaluated genome wide with an Affymetrix DNA microarray that included all open reading frames (ORFs) as well as intergenic sequences derived from four sequenced S. aureus strains. Using a sensitivity threshold value of 1.5, suboptimal expression of murF altered the transcription of a surprisingly large number of genes, i.e., 668 out of the 2,740 ORFs (close to one-fourth of all ORFs), of the genome of S. aureus strain COL. The genes with altered transcription were distributed evenly around the S. aureus chromosome, and groups of genes involved with distinct metabolic functions responded in unique and operon-specific manners to modulation in murF transcription. For instance, all genes belonging to the isd operon and all but 2 of the 35 genes of prophage L54a were down-regulated, whereas all but one of the 21 members of the vraSR regulon and most of the 79 virulence-related genes (those for fibronectin binding proteins A and B, clumping factor A, gamma hemolysin, enterotoxin B, etc.) were up-regulated in cells with suboptimal expression of murF. Most importantly, the majority of these altered gene expression profiles were reversible by resupplying the optimal concentration of IPTG (isopropyl-beta-D-thiogalactopyranoside) to the culture. The observations suggest the coordinate regulation of a large sector of the S. aureus transcriptome in response to a disturbance in cell wall synthesis.
Subject(s)
Bacterial Proteins/metabolism , Gene Expression Profiling , Gene Expression Regulation, Bacterial , Methicillin Resistance , Oligonucleotide Array Sequence Analysis/methods , Peptide Synthases/metabolism , Staphylococcus aureus/metabolism , Bacterial Proteins/genetics , Cell Wall/metabolism , Genome, Bacterial , Humans , Isopropyl Thiogalactoside/pharmacology , Microbial Sensitivity Tests , Peptide Synthases/genetics , Proteome , Staphylococcus aureus/drug effects , Staphylococcus aureus/genetics , Staphylococcus aureus/growth & development , Transcription, GeneticABSTRACT
A high-resolution time series of transcript abundance was generated to describe global expression dynamics in response to nutrition in Drosophila. Nonparametric change-point statistics revealed that within 7 h of feeding upon yeast, transcript levels changed significantly for approximately 3,500 genes or 20% of the Drosophila genome. Differences as small as 15% were highly significant, and 80% of the changes were <1.5-fold. Notably, transcript changes reflected rapid downregulation of the nutrient-sensing insulin and target of rapamycin pathways, shifting of fuel metabolism from lipid to glucose oxidation, and increased purine synthesis, TCA-biosynthetic functions and mitochondria biogenesis. To investigate how nutrition coordinates these transcriptional changes, feeding-induced expression changes were compared with those induced by the insulin-regulated transcription factor dFOXO in Drosophila S2 cells. Remarkably, 28% (995) of the nutrient-responsive genes were regulated by activated dFOXO, including genes of mitochondrial biogenesis and a novel homolog of mammalian peroxisome proliferator-gamma coactivator-1 (PGC-1), a transcriptional coactivator implicated in controlling mitochondrial gene expression in mammals. These data implicate dFOXO as a major coordinator of the transcriptional response to nutrients downstream of insulin and suggest that mitochondria biogenesis is linked to insulin signaling via dFOXO-mediated repression of a PGC-1 homolog.
Subject(s)
Animal Nutritional Physiological Phenomena/physiology , Drosophila Proteins/metabolism , Drosophila melanogaster/physiology , Forkhead Transcription Factors/metabolism , Gene Expression Regulation/physiology , Animals , Cells, Cultured , Drosophila Proteins/pharmacology , Drosophila melanogaster/metabolism , Energy Metabolism/physiology , Female , Forkhead Transcription Factors/pharmacology , Gene Expression Profiling , Gene Expression Regulation/drug effects , Insulin/metabolism , Mitochondrial Proteins/metabolism , Time Factors , Transcription Factors/metabolism , YeastsABSTRACT
There are several different methodologies that can be used for designing a database schema; no one is the best for all occasions. This unit demonstrates two different techniques for designing relational tables and discusses when each should be used. These two techniques presented are (1) traditional Entity-Relationship (E-R) modeling and (2) a hybrid method that combines aspects of data warehousing and E-R modeling. The method of choice depends on (1) how well the information and all its inherent relationships are understood, (2) what types of questions will be asked, (3) how many different types of data will be included, and (4) how much data exists.
