2018
DOI: 10.1007/s00449-018-1922-3
|View full text |Cite
|
Sign up to set email alerts
|

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

0
77
0
3

Year Published

2019
2019
2024
2024

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 65 publications
(80 citation statements)
references
References 277 publications
0
77
0
3
Order By: Relevance
“…Due to technical and economic constraints for bioreactor operation, the demand for high oxygen levels is hardly satisfied. Imperfect mixing in large‐scale bioreactor regions with low oxygen concentrations can also appear (Heins & Weuster‐Botz, ). Oxygen limitation is undesirable for E. coli because fermentation pathways are activated with the concomitant accumulation of metabolic byproducts.…”
Section: Introductionmentioning
confidence: 99%
“…Due to technical and economic constraints for bioreactor operation, the demand for high oxygen levels is hardly satisfied. Imperfect mixing in large‐scale bioreactor regions with low oxygen concentrations can also appear (Heins & Weuster‐Botz, ). Oxygen limitation is undesirable for E. coli because fermentation pathways are activated with the concomitant accumulation of metabolic byproducts.…”
Section: Introductionmentioning
confidence: 99%
“…Nowadays, it is known that microbial cell populations in industrial‐scale, biotechnological production processes, though originating from pure, isogenic cultures, are heterogeneous. Due to nonideal mixing, gradients of process parameters like substrate, dissolved oxygen, and pH arise, creating different local microenvironments that are experienced by cells traveling throughout the reactor . This induces dynamic cell responses on genetic, metabolic, and physiological level, and consequently causes development of population heterogeneity .…”
Section: Introductionmentioning
confidence: 99%
“…Hence, potentially less productive or less robust subpopulations can occur that reduce overall process efficiency. Even though these consequences of population heterogeneity and acetate formation are well known, the underlying cellular phenomena are poorly understood . One reason might be that studies of the role of acetate and diauxic shift have mostly been performed in shake flasks instead of bioreactors, or have focused on population level not taking into account single cell physiology .…”
Section: Introductionmentioning
confidence: 99%
“…Metabolic gradients were found as key regulators in zonation of cellular metabolic regimes, that is excess, limitation, and starvation status of the limiting nutrient, most likely leading to ensemble reduction of productivity and relevant yields (Haringa et al, ), and phenotypic heterogeneity has been evolved as bet‐hedging adaptation strategies to actively increase fitness of a subpopulation in an unpredictable scenario (Grimbergen, Siebring, Solopova, & Kuipers, ). A recent review article by Heins and Weuster‐Botz () has summarized several mechanisms, such as (a) bet‐hedging; (b) noise in gene expression; (c) persistence; (d) bistability, behind population heterogeneity in microbial bioprocesses. Also, recent findings have concluded that stochastic fluctuations in the molecular level can propagate by both regulatory proteins and metabolic reactions and the inherently stochastic cellular metabolism could be a generic source of phenotypic heterogeneity (Kiviet et al, ; Takhaveev & Heinemann, ).…”
Section: Introductionmentioning
confidence: 99%
“…Metabolic gradients were found as key regulators in zonation of cellular metabolic regimes, that is excess, limitation, and starvation status of the limiting nutrient, most likely leading to ensemble reduction of productivity and relevant yields , and phenotypic heterogeneity has been evolved as bet-hedging adaptation strategies to actively increase fitness of a subpopulation in an unpredictable scenario (Grimbergen, Siebring, Solopova, & Kuipers, 2015). A recent review article by Heins and Weuster-Botz (2018) has summarized several mechanisms, such as (a) bet-hedging;…”
Section: Introductionmentioning
confidence: 99%