Dataset Information

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

ABSTRACT: 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 transcriptome dynamics and genome sequence, a support vector machines (SVM)-based classification algorithm can accurately classify >90% of gene pairs in a set of known operons. Based on model predictions for the entire genome, we verified the co-transcription of more than 250 gene pairs by RT-PCR. These results vastly increase the database of known operons in S. coelicolor and provide valuable information for exploring gene function and regulation to harness the potential of this differentiating microorganism for synthesis of natural products.

SUBMITTER: Charaniya S

PROVIDER: S-EPMC2175336 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

ACCESS DATA

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

Similar Datasets

Project description:Nucleoid-associated proteins (NAPs) are small, highly abundant transcriptional regulators with low sequence specificity which are involved in multiple DNA-related processes including gene expression, DNA protection, recombination/repair and nucleoid structuring. Through these functions they are able to regulate important phenotypic properties including virulence, secondary metabolism and stress resistance. However the set of NAPs known within the Actinobacteria is small and incomplete. The missing proteins are likely to be key regulators of virulence in pathogens such as Mycobacterium tuberculosis and also of development and secondary metabolism in industrially-important species such as Streptomyces. Here, we use label-free LC-MS/MS to systematically search for novel NAPs in isolated nucleoids of the model actinomycete Streptomyces coelicolor. Based on the criteria of high abundance (emPAI score) and predicted DNA-binding ability (DNAbinder score) we identified a set of 24 proteins with a high predicted likelihood of being NAPs. The approach was deemed successful as the set included known major NAPs HupA, HupS, sIHF and Lsr2 as well as the global transcriptional regulators BldD and CRP and the pleiotropic response regulator AfsQ1. It also included a number of proteins whose functions are not yet known from recognisable classes of transcription factor (SCO2140, SCO4493, SCO1839, SCO1210, SCO5405, SCO4229, SCO3198) or from uncharacterised protein families (SCO5783, SCO5592, SCO3793, SCO6482) which comprise a valuable set of candidates for further study.In this paper we establish a robust protocol for preparing S. coelicolor nucleoids for mass spectrometric analysis and develop a workflow for identifying novel nucleoid-associated proteins (NAPs) by combining LC-MS/MS with a bioinformatical analysis. The nucleoid-associated proteins of many species are known to be key regulators of virulence, stress tolerance and global patterns of gene expression. Identifying the "missing" nucleoid proteins of S. coelicolor is likely to have important implications for manipulating the production of secondary metabolites such as antibiotics. Candidate NAPs were identified. Several of these are highly conserved in clinically important species such as Mycobacterium and in many commercially important species such as Salinispora and Micromonospora which represent a vital source of novel drugs such as antibiotics, antifungals and anticancer agents.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets