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

Otto A, Bernhardt J, Meyer H, Schaffer M, Herbst FA, Siebourg J, Mäder U, Lalk M, Hecker M, Becher D - Nat Commun (2010)

Bottom Line: In this study, we monitor temporal changes in the proteome, transcriptome and extracellular metabolome of B. subtilis caused by glucose starvation.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.

View Article: PubMed Central - PubMed

Affiliation: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology, Greifswald 17487, Germany.

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.

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Regulon treemap of growing B. subtilis.(a) Gene expression of growing B. subtilis compared with average expression during the time course in cells entering the stationary phase. (b) Relative protein amount determined in cytosolic fraction of growing B. subtilis compared with the average protein amount during the investigated time course. Each cell in the graph displays a single gene locus that belongs to other hierarchically/regulatory related elements in parent convex-shaped categories. These are again summarized in higher-level regulatory categories. Functionally related elements seem in close neighbourhood to each other. Treemap design is based on hierarchically structured regulatory data (black borders: regulon/thin black borders within the regulons: operon/smallest cells: gene). +/-; depict regulons being induced (+) or repressed (-;) depending on the regulator assigned to the area. To visualize differences in expression level/protein amount compared with the average level colour coding was applied as following: blue—decreased level (dec.), grey—same level as average (avg.), orange—increased level (inc.). These figures are part of the time course analysis (Supplementary Movies S2 and S4), monitoring the changes from exponential growth to late stationary phase.
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f3: Regulon treemap of growing B. subtilis.(a) Gene expression of growing B. subtilis compared with average expression during the time course in cells entering the stationary phase. (b) Relative protein amount determined in cytosolic fraction of growing B. subtilis compared with the average protein amount during the investigated time course. Each cell in the graph displays a single gene locus that belongs to other hierarchically/regulatory related elements in parent convex-shaped categories. These are again summarized in higher-level regulatory categories. Functionally related elements seem in close neighbourhood to each other. Treemap design is based on hierarchically structured regulatory data (black borders: regulon/thin black borders within the regulons: operon/smallest cells: gene). +/-; depict regulons being induced (+) or repressed (-;) depending on the regulator assigned to the area. To visualize differences in expression level/protein amount compared with the average level colour coding was applied as following: blue—decreased level (dec.), grey—same level as average (avg.), orange—increased level (inc.). These figures are part of the time course analysis (Supplementary Movies S2 and S4), monitoring the changes from exponential growth to late stationary phase.

Mentions: To support the analysis of our gene expression data from transcriptome and proteome levels, we used the functional gene categorization from KEGG orthology2324 and a structured representation of gene regulatory information derived from SubtiWiki2526. Both schemes classify genes/proteins in an acyclic multihierarchical tree graph according to their function or regulation, respectively. For a well-arranged visualization, we adapted treemaps for an intuitive display of large omics data sets with their relative expression data and functional/regulatory classification (Figs 2,3).


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

Otto A, Bernhardt J, Meyer H, Schaffer M, Herbst FA, Siebourg J, Mäder U, Lalk M, Hecker M, Becher D - Nat Commun (2010)

Regulon treemap of growing B. subtilis.(a) Gene expression of growing B. subtilis compared with average expression during the time course in cells entering the stationary phase. (b) Relative protein amount determined in cytosolic fraction of growing B. subtilis compared with the average protein amount during the investigated time course. Each cell in the graph displays a single gene locus that belongs to other hierarchically/regulatory related elements in parent convex-shaped categories. These are again summarized in higher-level regulatory categories. Functionally related elements seem in close neighbourhood to each other. Treemap design is based on hierarchically structured regulatory data (black borders: regulon/thin black borders within the regulons: operon/smallest cells: gene). +/-; depict regulons being induced (+) or repressed (-;) depending on the regulator assigned to the area. To visualize differences in expression level/protein amount compared with the average level colour coding was applied as following: blue—decreased level (dec.), grey—same level as average (avg.), orange—increased level (inc.). These figures are part of the time course analysis (Supplementary Movies S2 and S4), monitoring the changes from exponential growth to late stationary phase.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105300&req=5

f3: Regulon treemap of growing B. subtilis.(a) Gene expression of growing B. subtilis compared with average expression during the time course in cells entering the stationary phase. (b) Relative protein amount determined in cytosolic fraction of growing B. subtilis compared with the average protein amount during the investigated time course. Each cell in the graph displays a single gene locus that belongs to other hierarchically/regulatory related elements in parent convex-shaped categories. These are again summarized in higher-level regulatory categories. Functionally related elements seem in close neighbourhood to each other. Treemap design is based on hierarchically structured regulatory data (black borders: regulon/thin black borders within the regulons: operon/smallest cells: gene). +/-; depict regulons being induced (+) or repressed (-;) depending on the regulator assigned to the area. To visualize differences in expression level/protein amount compared with the average level colour coding was applied as following: blue—decreased level (dec.), grey—same level as average (avg.), orange—increased level (inc.). These figures are part of the time course analysis (Supplementary Movies S2 and S4), monitoring the changes from exponential growth to late stationary phase.
Mentions: To support the analysis of our gene expression data from transcriptome and proteome levels, we used the functional gene categorization from KEGG orthology2324 and a structured representation of gene regulatory information derived from SubtiWiki2526. Both schemes classify genes/proteins in an acyclic multihierarchical tree graph according to their function or regulation, respectively. For a well-arranged visualization, we adapted treemaps for an intuitive display of large omics data sets with their relative expression data and functional/regulatory classification (Figs 2,3).

Bottom Line: In this study, we monitor temporal changes in the proteome, transcriptome and extracellular metabolome of B. subtilis caused by glucose starvation.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.

View Article: PubMed Central - PubMed

Affiliation: Ernst-Moritz-Arndt-Universität Greifswald, Institute for Microbiology, Greifswald 17487, Germany.

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.

Show MeSH