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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

Schematic overview of the bacterial cell cycle. The bacterial cell cycle can be divided into B, C, pre-D and D phases constituting a defined order within one generation time. Under unlimited growth conditions, some bacterial species are capable of accelerating proliferation by uncoupling DNA synthesis from division. As a result, a new round of DNA replication is initiated before the completion of the previous round (Cooper [1991]; Müller et al. [2010]).
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Figure 1: Schematic overview of the bacterial cell cycle. The bacterial cell cycle can be divided into B, C, pre-D and D phases constituting a defined order within one generation time. Under unlimited growth conditions, some bacterial species are capable of accelerating proliferation by uncoupling DNA synthesis from division. As a result, a new round of DNA replication is initiated before the completion of the previous round (Cooper [1991]; Müller et al. [2010]).

Mentions: Traditionally, the cell cycle is suggested to play a role in the development of population heterogeneity within clonal populations (Müller et al. [2010]). A short summary of the sequence of cell cycle phases can be found in Figure 1. The bacterial cell cycle was described for Escherichia coli comprising the B-Phase, which is defined as the time between division and start of replication, the replication phase (C-Phase), the pre-D-Phase (an interphase between the C- and D-Phase) and the division phase (D-Phase) (Cooper [1991]; Müller and Babel [2003]). Furthermore, under optimal growth conditions accelerated proliferation (also called ‘multifork DNA-replication’) can be monitored: new rounds of DNA replication may be initiated before a previous round is completed, putatively providing another source of heterogeneity (Bley [1990]; Müller [2007]).


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)

Schematic overview of the bacterial cell cycle. The bacterial cell cycle can be divided into B, C, pre-D and D phases constituting a defined order within one generation time. Under unlimited growth conditions, some bacterial species are capable of accelerating proliferation by uncoupling DNA synthesis from division. As a result, a new round of DNA replication is initiated before the completion of the previous round (Cooper [1991]; Müller et al. [2010]).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Schematic overview of the bacterial cell cycle. The bacterial cell cycle can be divided into B, C, pre-D and D phases constituting a defined order within one generation time. Under unlimited growth conditions, some bacterial species are capable of accelerating proliferation by uncoupling DNA synthesis from division. As a result, a new round of DNA replication is initiated before the completion of the previous round (Cooper [1991]; Müller et al. [2010]).
Mentions: Traditionally, the cell cycle is suggested to play a role in the development of population heterogeneity within clonal populations (Müller et al. [2010]). A short summary of the sequence of cell cycle phases can be found in Figure 1. The bacterial cell cycle was described for Escherichia coli comprising the B-Phase, which is defined as the time between division and start of replication, the replication phase (C-Phase), the pre-D-Phase (an interphase between the C- and D-Phase) and the division phase (D-Phase) (Cooper [1991]; Müller and Babel [2003]). Furthermore, under optimal growth conditions accelerated proliferation (also called ‘multifork DNA-replication’) can be monitored: new rounds of DNA replication may be initiated before a previous round is completed, putatively providing another source of heterogeneity (Bley [1990]; Müller [2007]).

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