Systems-wide temporal proteomic profiling in glucose-starved Bacillus subtilis

Andreas Otto, Jörg Bernhardt, Hanna Meyer, Marc Schaffer, Florian-A. Herbst, Juliane Siebourg, Ulrike Mäder, Michael Lalk, Michael Hecker and Dörte Becher ()
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Andreas Otto: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology
Jörg Bernhardt: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology
Hanna Meyer: Ernst-Moritz-Arndt-Universität Greifswald, Institute of Pharmacy
Marc Schaffer: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology
Florian-A. Herbst: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology
Juliane Siebourg: ETH Zürich, Mattenstrasse 26
Ulrike Mäder: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology
Michael Lalk: Ernst-Moritz-Arndt-Universität Greifswald, Institute of Pharmacy
Michael Hecker: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology
Dörte Becher: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology

Nature Communications, 2010, vol. 1, issue 1, 1-9

Abstract: Abstract Functional genomics of the Gram-positive model organism Bacillus subtilis reveals valuable insights into basic concepts of cell physiology. In this study, we monitor temporal changes in the proteome, transcriptome and extracellular metabolome of B. subtilis caused by glucose starvation. For proteomic profiling, a combination of in vivo metabolic labelling and shotgun mass spectrometric analysis was carried out for five different proteomic subfractions (cytosolic, integral membrane, membrane, surface and extracellular proteome fraction), leading to the identification of ∼52% of the predicted proteome of B. subtilis. Quantitative proteomic and corresponding transcriptomic data were analysed with Voronoi treemaps linking functional classification and relative expression changes of gene products according to their fate in the stationary phase. The obtained data comprise the first comprehensive profiling of changes in the membrane subfraction and allow in-depth analysis of major physiological processes, including monitoring of protein degradation.

Date: 2010
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DOI: 10.1038/ncomms1137

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