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Subpopulation-proteomics reveal growth rate, but not cell cycling, as a major impact on protein composition in Pseudomonas putida KT2440.

Lieder S, Jahn M, Seifert J, von Bergen M, Müller S, Takors R - AMB Express (2014)

Bottom Line: The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery.In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level.In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biochemical Engineering, University of Stuttgart, Allmandring 31, Stuttgart, Germany.

ABSTRACT
Population heterogeneity occurring in industrial microbial bioprocesses is regarded as a putative effector causing performance loss in large scale. While the existence of subpopulations is a commonly accepted fact, their appearance and impact on process performance still remains rather unclear. During cell cycling, distinct subpopulations differing in cell division state and DNA content appear which contribute individually to the efficiency of the bioprocess. To identify stressed or impaired subpopulations, we analyzed the interplay of growth rate, cell cycle and phenotypic profile of subpopulations by using flow cytometry and cell sorting in conjunction with mass spectrometry based global proteomics. Adjusting distinct growth rates in chemostats with the model strain Pseudomonas putida KT2440, cells were differentiated by DNA content reflecting different cell cycle stages. The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery. In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level. In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

No MeSH data available.


Related in: MedlinePlus

Heatmaps of metabolic pathways of special interest. The log2 fold changes of annotated proteins are visualized ranging from blue (low abundance) to red (high abundance). A detailed annotation of the protein names can be found in the Additional file 1. One line of the heatmap represents the different subpopulations (C1, C2 and Cx) at different growth rates (μ = 0.1 h−1, μ = 0.7 h−1). Proteins of the specific pathways are shown column-wise.
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Figure 5: Heatmaps of metabolic pathways of special interest. The log2 fold changes of annotated proteins are visualized ranging from blue (low abundance) to red (high abundance). A detailed annotation of the protein names can be found in the Additional file 1. One line of the heatmap represents the different subpopulations (C1, C2 and Cx) at different growth rates (μ = 0.1 h−1, μ = 0.7 h−1). Proteins of the specific pathways are shown column-wise.

Mentions: Comparing the subpopulations of different growth rates with RP, biologically significant differences were detectable as tested by gene set analysis (GAGE (Luo et al. [2009]) and Globaltest (Goeman et al. [2006])) (Figure 4b and 4c). At μ = 0.1 h−1, subpopulations C1 and C2 showed higher abundance of proteins related to ‘cell motility’, and proteins involved in ‘cell cycle control, cell division and chromosome partitioning’ (cell cycle) were additionally highly abundant in subpopulation C2. Apart from COG annotated pathways, several proteins connected to carbon storage were found to be significantly changed (Figure 5). Mirroring low qS at slow growth compared to moderate growth, four main signaling proteins in chemotaxis (CheA, CheB, CheW, CheV) as well as 6 methyl accepting chemotaxis transducers were significantly increased. Furthermore, the low abundance of glycogen synthesis proteins (GlgA, Pgm) and the high abundance of glycogen hydrolysis proteins (GlgX, GlgP) could be seen together with an increase of proteins involved in PHA production (PhaA, PhaC).


Subpopulation-proteomics reveal growth rate, but not cell cycling, as a major impact on protein composition in Pseudomonas putida KT2440.

Lieder S, Jahn M, Seifert J, von Bergen M, Müller S, Takors R - AMB Express (2014)

Heatmaps of metabolic pathways of special interest. The log2 fold changes of annotated proteins are visualized ranging from blue (low abundance) to red (high abundance). A detailed annotation of the protein names can be found in the Additional file 1. One line of the heatmap represents the different subpopulations (C1, C2 and Cx) at different growth rates (μ = 0.1 h−1, μ = 0.7 h−1). Proteins of the specific pathways are shown column-wise.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230896&req=5

Figure 5: Heatmaps of metabolic pathways of special interest. The log2 fold changes of annotated proteins are visualized ranging from blue (low abundance) to red (high abundance). A detailed annotation of the protein names can be found in the Additional file 1. One line of the heatmap represents the different subpopulations (C1, C2 and Cx) at different growth rates (μ = 0.1 h−1, μ = 0.7 h−1). Proteins of the specific pathways are shown column-wise.
Mentions: Comparing the subpopulations of different growth rates with RP, biologically significant differences were detectable as tested by gene set analysis (GAGE (Luo et al. [2009]) and Globaltest (Goeman et al. [2006])) (Figure 4b and 4c). At μ = 0.1 h−1, subpopulations C1 and C2 showed higher abundance of proteins related to ‘cell motility’, and proteins involved in ‘cell cycle control, cell division and chromosome partitioning’ (cell cycle) were additionally highly abundant in subpopulation C2. Apart from COG annotated pathways, several proteins connected to carbon storage were found to be significantly changed (Figure 5). Mirroring low qS at slow growth compared to moderate growth, four main signaling proteins in chemotaxis (CheA, CheB, CheW, CheV) as well as 6 methyl accepting chemotaxis transducers were significantly increased. Furthermore, the low abundance of glycogen synthesis proteins (GlgA, Pgm) and the high abundance of glycogen hydrolysis proteins (GlgX, GlgP) could be seen together with an increase of proteins involved in PHA production (PhaA, PhaC).

Bottom Line: The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery.In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level.In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institute for Biochemical Engineering, University of Stuttgart, Allmandring 31, Stuttgart, Germany.

ABSTRACT
Population heterogeneity occurring in industrial microbial bioprocesses is regarded as a putative effector causing performance loss in large scale. While the existence of subpopulations is a commonly accepted fact, their appearance and impact on process performance still remains rather unclear. During cell cycling, distinct subpopulations differing in cell division state and DNA content appear which contribute individually to the efficiency of the bioprocess. To identify stressed or impaired subpopulations, we analyzed the interplay of growth rate, cell cycle and phenotypic profile of subpopulations by using flow cytometry and cell sorting in conjunction with mass spectrometry based global proteomics. Adjusting distinct growth rates in chemostats with the model strain Pseudomonas putida KT2440, cells were differentiated by DNA content reflecting different cell cycle stages. The proteome of separated subpopulations at given growth rates was found to be highly similar, while different growth rates caused major changes of the protein inventory with respect to e.g. carbon storage, motility, lipid metabolism and the translational machinery. In conclusion, cells in various cell cycle stages at the same growth rate were found to have similar to identical proteome profiles showing no significant population heterogeneity on the proteome level. In contrast, the growth rate clearly determines the protein composition and therefore the metabolic strategy of the cells.

No MeSH data available.


Related in: MedlinePlus