Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

S. coelicolor M145 Time-course Study in R5- medium (Culture# 3)

ABSTRACT: Antibiotic biosynthesis in Streptomyces species is controlled by a complex genetic and biochemical network of global and pathway specific regulators. Details of their precise interactions in mediating temporal and spatial expression of secondary metabolite genes remain poorly defined. In this study, we employed whole-genome microarrays to investigate the temporal transcriptome profiles of S. coelicolor A3(2) M145 wild type and disruption mutants of regulatory genes (afsS and absA1) known to affect antibiotic biosynthesis. Keywords: Time course The time-course study involved analysis of 13 samples (10h, 13h, 14h, 16h, 18h, 20h, 22h, 24h, 27h, 29h, 32h, 34h, 37h). Of these, 13h, 14h, 16h, 18h, 20h, 22h, 24h, 32h, and 37h sample were analyzed on duplicate arrays (2 technical replicates). Genomic DNA of S. coelicolor wild type (M145) was used as a reference for all the arrays. cDNA was labeled with Alexa647 and genomic DNA was labeled with Cy3.

ORGANISM(S): Streptomyces coelicolor

SUBMITTER: Karthik Jayapal

PROVIDER: E-GEOD-8107 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Transcriptome dynamics-based operon prediction and verification in Streptomyces coelicolor.

Charaniya Salim S Mehra Sarika S Lian Wei W Jayapal Karthik P KP Karypis George G Hu Wei-Shou WS

Nucleic acids research 20071024 21

Streptomyces spp. produce a variety of valuable secondary metabolites, which are regulated in a spatio-temporal manner by a complex network of inter-connected gene products. Using a compilation of genome-scale temporal transcriptome data for the model organism, Streptomyces coelicolor, under different environmental and genetic perturbations, we have developed a supervised machine-learning method for operon prediction in this microorganism. We demonstrate that, using features dependent on transcr ...[more]

PMID: 17959654

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Project description:Many biological processes are intrinsically dynamic, incurring profound changes at both molecular and physiological levels. Systems analyses of such processes incorporating large-scale transcriptome or proteome profiling can be quite revealing. Although consistency between mRNA and proteins is often implicitly assumed in such studies, instances of divergent trends are frequently observed indicating the existence of post-transcriptional regulation. Here, we present a comparative transcriptome and proteome analysis of growth and stationary phase adaptation in Streptomyces coelicolor, taking the time-dynamics of process into consideration. These processes are of immense interest in streptomycetes as they encompass the physiological transformations eliciting biosynthesis of many naturally occurring therapeutic agents. A shotgun proteomics approach based on mass spectrometric analysis of isobaric stable isotope labeled peptides iTRAQ(TM) enabled identification and rapid quantification of approximately 14% of the theoretical proteome of S. coelicolor. Independent principal component analyses of this and DNA microarray-derived transcriptome data revealed that the prominent patterns in both protein and mRNA domains are surprisingly well correlated. Despite this general consensus, by employing a systematic concordance analysis we estimated that over 30% of the analyzed genes likely exhibited significantly divergent patterns, of which nearly one-third displayed even opposing trends. Integrating this data with biological information, we discovered that certain groups of functionally related genes were co-regulated independently as mRNA and/or proteins despite observations of apparent mRNA-protein discordance. This clearly suggests that post-transcriptional regulatory mechanisms are prominent even amongst prokaryotes while reaffirming the plausibility of such mechanisms acting in a concerted fashion at a protein complex or sub-pathway level. Keywords: Time course Time-course study involved analysis of 8 samples (7h, 11h, 14h, 16h, 22h, 26h, 34h, 38h). Of these, 14h, 22h, 26h and 38h were analyzed in duplicate arrays. All arrays used cDNA labeled with Alexa647 and gDNA labeled with Cy3.

Dataset Information

S. coelicolor M145 Time-course Study in R5- medium (Culture# 3)

Publications

Transcriptome dynamics-based operon prediction and verification in Streptomyces coelicolor.

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