A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

• MeSH
• genetická transkripce MeSH
• genové regulační sítě * MeSH
• kinetika MeSH
• modely genetické * MeSH
• počítačová simulace MeSH
• regulace genové exprese u bakterií * MeSH
• sekvenční analýza hybridizací s uspořádaným souborem oligonukleotidů MeSH
• sigma faktor metabolismus   MeSH
• spory bakteriální genetika   růst a vývoj   metabolismus   MeSH
• stanovení celkové genové exprese * MeSH
• Streptomyces coelicolor genetika   metabolismus   fyziologie   MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• sigma faktor MeSH

Streptomycetes have been studied mostly as producers of secondary metabolites, while the transition from dormant spores to an exponentially growing culture has largely been ignored. Here, we focus on a comparative analysis of fluorescently and radioactively labeled proteome and microarray acquired transcriptome expressed during the germination of Streptomyces coelicolor. The time-dynamics is considered, starting from dormant spores through 5.5 hours of growth with 13 time points. Time series of the gene expressions were analyzed using correlation, principal components analysis and an analysis of coding genes utilization. Principal component analysis was used to identify principal kinetic trends in gene expression and the corresponding genes driving S. coelicolor germination. In contrast with the correlation analysis, global trends in the gene/protein expression reflected by the first principal components showed that the prominent patterns in both the protein and the mRNA domains are surprisingly well correlated. Analysis of the number of expressed genes identified functional groups activated during different time intervals of the germination.

• MeSH
• analýza hlavních komponent MeSH
• energetický metabolismus genetika   MeSH
• fenotyp MeSH
• fyziologický stres genetika   MeSH
• genové regulační sítě MeSH
• metabolické sítě a dráhy MeSH
• proteom * MeSH
• regulace genové exprese u bakterií * MeSH
• spory bakteriální genetika   metabolismus   MeSH
• Streptomyces coelicolor genetika   metabolismus   ultrastruktura   MeSH
• transkriptom * MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• proteom * MeSH