Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

0

Growth dependent expression of s. aureus mssa476


ABSTRACT: Survival and pathogenesis of Staphylococcus aureus in the host requires the ability to respond to changes. Therefore, tight regulation of gene expression via various regulators is essential. Also, the organization of genes in operons is of influence on the regulation of gene expression. Knowledge of gene expression under different conditions and the ability to accurately predict operons are important steps towards understanding the transcriptional regulation, function and pathogenesis. A whole genome Agilent microarray was developed for the highly virulent, community-acquired MSSA476.During standard growth in a defined medium, we were able to determine four basic gene expression patterns of S. aureus for both virulence and non-virulence genes. In addition, we predicted operon structures by calculating Pearson correlation coefficients of the transcriptional profiles for all adjacent probes over all time points and replicas. In this study, we have set a basis for the knowledge on gene expression of MSSA476 during growth. Moreover, the correlation of time-dependent transcriptional profiles of adjacent probes seems to be a promising approach to predict operon structures. Five separate cultures of S. aureus mssa476 were grown. Of each replicate culture, samples were taken at 1, 2, 3, 4, 5, 6 and 9 h post inoculation (p.i.). In total, this amounts to 35 samples (7 time points in 5 replicates).

ORGANISM(S): Staphylococcus aureus subsp. aureus MSSA476

SUBMITTER: Timo Breit 

PROVIDER: E-GEOD-16488 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

altmetric image

Publications


In bacteria, gene regulation is one of the fundamental characteristics of survival, colonization and pathogenesis. Operons play a key role in regulating expression of diverse genes involved in metabolism and virulence. However, operon structures in pathogenic bacteria have been determined only by in silico approaches that are dependent on factors such as intergenic distances and terminator/promoter sequences. Knowledge of operon structures is crucial to fully understand the pathophysiology of in  ...[more]

Similar Datasets

2005-11-30 | E-GEOD-3176 | biostudies-arrayexpress
2010-05-18 | E-GEOD-13233 | biostudies-arrayexpress
2010-05-18 | E-GEOD-13236 | biostudies-arrayexpress
2010-05-18 | E-GEOD-13203 | biostudies-arrayexpress
2010-05-18 | E-GEOD-16553 | biostudies-arrayexpress
2008-12-14 | E-GEOD-9847 | biostudies-arrayexpress
2010-06-10 | E-GEOD-8135 | biostudies-arrayexpress
2010-05-25 | E-GEOD-8777 | biostudies-arrayexpress
2008-09-15 | E-GEOD-9102 | biostudies-arrayexpress
2016-02-10 | E-GEOD-77069 | biostudies-arrayexpress