Unknown,Transcriptomics,Genomics,Proteomics

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Streptomyces griseus transcriptome analysis in delta sigD, encoding an ECF-sigma factor

ABSTRACT: To identify genes regulated by SigD, transcriptome profiles between wild type strain and sigD mutant with pI486-sigD, in which sigD level is low compared to wild type strain, were analyzed. Analysis used wild type strain steady state RNA as control samples for comparison to the sigD mutant.

ORGANISM(S): Streptomyces griseus

SUBMITTER: Akiyoshi Higo

PROVIDER: E-GEOD-27426 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Methicillin resistance in Staphylococcus aureus depends on the production of mecA, which encodes penicillin-binding protein 2A (PBP2A), an acquired peptidoglycan transpeptidase with reduced susceptibility to beta-lactam antibiotics. Here, we show that preventing the expression of wall teichoic acids (WTAs) genetically or with a TarO inhibitor sensitizes MRSA strains to beta-lactams although PBP2A is still expressed. Using S. aureus microarrays and array data analysis protocols (NIAID's Pathogen Functional Genomics Resource Center) we have characterized the transcriptomes of S. aureus COL. in order to further understand the sensitization of strain COL to methicillin by tunicamycin we determined the tunicamycin and methicillin transcriptomes alone and in combination. Methicillin treatment of COL at 500 Âµg/mL had almost no effect on cell growth rate and, remarkably, the only gene in the transcriptome that showed a more than two-fold change in expression was lytM, which was downregulated. The tunicamycin transcriptome of COL, acquired at 0.4 Âµg/mL, shows modest changes compared to the untreated control both in terms of the total numbers of affected genes and in the degree of up- or downregulation. Several of the genes upregulated upon tunicamycin treatment are part of the cell wall stress stimulon.COL was grown with methicillin to an OD600 ~0.4, and challenged with tunicamycin for 2 hrs whereas the control culture contained methicillin alone. transcriptome for COL growing in the presence of both agents showed extensive changes in gene expression. , the cell wall stress stimulon, which was not induced by methicillin when tunicamycin was absent, was clearly induced in its presence and the changes were far more dramatic than observed with tunicamycin alone. ). vraS and vraR, which encode a two component signaling system dedicated to the cell wall regulon, were upregulated 3.8 and 3.7 fold, respectively. Other upregulated cell wall stress stimulon genes include pbp2, fmtA, mvaD (mevalonate diphosphate decarboxylase), crtN (dehydrosqualene desaturase) mvak1 (mevalonate kinase), recU, SAV1424 (methionine sulfoxide reductase A), prsA (peptidyl-prolyl cis/trans isomerase), tcaA (Tca protein) and cwrA. A considerable number of genes were also downregulated upon challenge of COL with the combination of tunicamycin and methicillin. These included sspB, lrgA, dltA, capL, SAS0988, sspA, pflB, and spa. Several of these genes have been found to be downregulated in previous studies of cell wall-active antibiotic challenge of S. aureus. Growth conditions for microarray analysis- For transcriptional profiling, an overnight-grown COL culture was diluted (2% vol/vol) to 20 ml TSB medium in a 50-ml Erlenmeyer flask and grown at 30Â°C with shaking at 200 rpm. For the sensitization experiment, COL was grown with methicillin to an OD600 ~0.4, and challenged with tunicamycin for 2 hrs whereas the control culture contained methicillin alone. Total bacterial RNA was isolated as previously described from S. aureus COL (30Â°C, 200 rpm). The RNA samples were then converted to fluorescently-labeled cDNA and hybridized to S. aureus microarrays version 7 (NIAID's Pathogen Functional Genomics Resource Center). Hybridization signals were scanned using an Axon4000B scanner (Molecular Devices, Sunnyvale, CA ) with Acuity 4.0 software and scans were saved as TIFF image. Scans were analyzed using TIGR-Spotfinder (www.tigr.org/software/) software and the local background was subsequently subtracted. The data set was normalized by applying the LOWESS algorithm using TIGR-MIDAS (www.tigr.org/software/) software. The normalized log2 ratio of test/reference signal for each spot was recorded. Genes with less than three data points were considered unreliable, and their data points were discarded. The averaged log2 ratio for each remaining gene on the four replicate slides was ultimately calculated. Significant changes of gene expression were identified with SAM (significance analysis of microarrays; www.tat.stanford.edu/~tibs/SAM/index.html. Genes analyzed using these programs were further sorted and grouped based on their function using our in-house software Staphylococcus aureus Gene Sorter (SAGS). Several controls were employed to minimize the technical and biological variations and to ensure that the data obtained were of good quality. First, each ORF was present in triplicate on the array. Second, each RNA preparation was used to make probes for at least two separate arrays for which the incorporated dye was reversed. Contents of raw data files: Channel A = Cy3 dye Channel B = Cy5 dye File names ending with S1,S3 = Cy3 untreated, Cy5 treated File names ending with S2,S4 = Cy5 untreated, Cy3 treated

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Streptomyces griseus transcriptome analysis in delta sigD, encoding an ECF-sigma factor

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