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.
Highlights
Applied assumptions consider microbial populations in bioreactors as uniform, leveling individual properties of subpopulations to averages
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 and the division phase (D-Phase) (Cooper 1991; Müller and Babel 2003)
Subpopulation dynamics of P. putida KT2440 were analyzed in a wide range from slow growth rates starting at μ = 0.1 h−1 to high growth rates of up to μ = 0.7 h−1
Summary
Applied assumptions consider microbial populations in bioreactors as uniform, leveling individual properties of subpopulations to averages. It is increasingly accepted that clonal microbial cultures comprise individuals that are not identical, differing in terms of DNA content and cell physiology (Brehm-Stecher and Johnson 2004; Delvigne and Goffin 2013). Heterogeneity of clonal microbial cultures may result from several distinct sources, either from internal biological origins, such as mutations, cell cycle decisions and age distribution, or from ‘external’ technical factors (Avery 2006; Müller et al 2010). External factors interact with biological properties, yielding the superimposition of both impacts in the population. We shed light on the impact of Traditionally, the cell cycle is suggested to play a role in the development of population heterogeneity within clonal populations (Müller et al 2010). Under optimal growth conditions accelerated proliferation ( 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)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.