Abstract
Streptomyces coelicolor, the model species of the genus Streptomyces, presents a complex life cycle of successive morphological and biochemical changes involving the formation of substrate and aerial mycelium, sporulation and the production of antibiotics. The switch from primary to secondary metabolism can be triggered by nutrient starvation and is of particular interest as some of the secondary metabolites produced by related Streptomycetes are commercially relevant. To understand these events on a molecular basis, a reliable technical platform encompassing reproducible fermentation as well as generation of coherent transcriptomic data is required. Here, we investigate the technical basis of a previous study as reported by Nieselt et al. (BMC Genomics 11:10, 2010) in more detail, based on the same samples and focusing on the validation of the custom-designed microarray as well as on the reproducibility of the data generated from biological replicates. We show that the protocols developed result in highly coherent transcriptomic measurements. Furthermore, we use the data to predict chromosomal gene clusters, extending previously known clusters as well as predicting interesting new clusters with consistent functional annotations.
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Acknowledgements
We are grateful to Mervyn Bibb for helpful discussion concerning the Affymetrix custom microarray design. We acknowledge the excellent technical help of K. Klein, S. Poths and M. Walter at the Microarray Facility Tübingen, and Anders Øverby and Elin Hansen at SINTEF Materials and Chemistry, Department of Biotechnology. This project was supported by grants of the ERA-NET SySMO Project (GEN2006-27745-E/SYS) and the Research Council of Norway (project no. 181840/I30).
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Battke, F. et al. (2011). A Technical Platform for Generating Reproducible Expression Data from Streptomyces coelicolor Batch Cultivations. In: Arabnia, H., Tran, QN. (eds) Software Tools and Algorithms for Biological Systems. Advances in Experimental Medicine and Biology, vol 696. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7046-6_1
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DOI: https://doi.org/10.1007/978-1-4419-7046-6_1
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