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In silico evolution of diauxic growth.

Chu DF - BMC Evol. Biol. (2015)

Bottom Line: The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth.Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency.Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves.

View Article: PubMed Central - PubMed

Affiliation: School of Computing, University of Kent, Canterbury, CT2 7NF, UK. D.F.Chu@kent.ac.uk.

ABSTRACT

Background: The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth. Diauxic growth is usually thought of as a an adaptation to maximise biomass production in an environment offering two or more carbon sources. While diauxic growth has been studied widely both experimentally and theoretically, the hypothesis that diauxic growth is a strategy to increase overall growth has remained an unconfirmed conjecture.

Methods: Here, we present a minimal mathematical model of a bacterial nutrient uptake system and metabolism. We subject this model to artificial evolution to test under which conditions diauxic growth evolves.

Results: As a result, we find that, indeed, sequential uptake of nutrients emerges if there is competition for nutrients and the metabolism/uptake system is capacity limited.

Discussion: However, we also find that diauxic growth is a secondary effect of this system and that the speed-up of nutrient uptake is a much larger effect. Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency.

Conclusions: Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves. This suggests that the lag-phase is a consequence of stochastic gene expression.

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The fitness as a function of the growth rate constant g. To generate this graph we took a solution that evolved in the first iteration. Then we removed N2 and varied the parameter g leaving all other parameters at their evolved value. The model suggest that there is a phase transition between high growth and no growth
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Fig2: The fitness as a function of the growth rate constant g. To generate this graph we took a solution that evolved in the first iteration. Then we removed N2 and varied the parameter g leaving all other parameters at their evolved value. The model suggest that there is a phase transition between high growth and no growth

Mentions: Insight into the nature of the parameter space is provided by varying the growth rate constant g that controls the amount of resource that is used for growth (R.VIII). Figure 2 shows the fitness of an evolved solution as a function of the growth rate for a particular solution we obtained. In this case, the fitness is high and minimally varying when g is within a certain intermediate range. When g is outside this range, either lower or higher, then the fitness is very low and again varying weakly only with the parameter. The transition between these two ranges is sudden. For other solutions we found this behaviour repeated qualitatively even though the numerical details are somewhat different.Fig. 2


In silico evolution of diauxic growth.

Chu DF - BMC Evol. Biol. (2015)

The fitness as a function of the growth rate constant g. To generate this graph we took a solution that evolved in the first iteration. Then we removed N2 and varied the parameter g leaving all other parameters at their evolved value. The model suggest that there is a phase transition between high growth and no growth
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4587919&req=5

Fig2: The fitness as a function of the growth rate constant g. To generate this graph we took a solution that evolved in the first iteration. Then we removed N2 and varied the parameter g leaving all other parameters at their evolved value. The model suggest that there is a phase transition between high growth and no growth
Mentions: Insight into the nature of the parameter space is provided by varying the growth rate constant g that controls the amount of resource that is used for growth (R.VIII). Figure 2 shows the fitness of an evolved solution as a function of the growth rate for a particular solution we obtained. In this case, the fitness is high and minimally varying when g is within a certain intermediate range. When g is outside this range, either lower or higher, then the fitness is very low and again varying weakly only with the parameter. The transition between these two ranges is sudden. For other solutions we found this behaviour repeated qualitatively even though the numerical details are somewhat different.Fig. 2

Bottom Line: The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth.Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency.Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves.

View Article: PubMed Central - PubMed

Affiliation: School of Computing, University of Kent, Canterbury, CT2 7NF, UK. D.F.Chu@kent.ac.uk.

ABSTRACT

Background: The glucose effect is a well known phenomenon whereby cells, when presented with two different nutrients, show a diauxic growth pattern, i.e. an episode of exponential growth followed by a lag phase of reduced growth followed by a second phase of exponential growth. Diauxic growth is usually thought of as a an adaptation to maximise biomass production in an environment offering two or more carbon sources. While diauxic growth has been studied widely both experimentally and theoretically, the hypothesis that diauxic growth is a strategy to increase overall growth has remained an unconfirmed conjecture.

Methods: Here, we present a minimal mathematical model of a bacterial nutrient uptake system and metabolism. We subject this model to artificial evolution to test under which conditions diauxic growth evolves.

Results: As a result, we find that, indeed, sequential uptake of nutrients emerges if there is competition for nutrients and the metabolism/uptake system is capacity limited.

Discussion: However, we also find that diauxic growth is a secondary effect of this system and that the speed-up of nutrient uptake is a much larger effect. Notably, this speed-up of nutrient uptake coincides with an overall reduction of efficiency.

Conclusions: Our two main conclusions are: (i) Cells competing for the same nutrients evolve rapid but inefficient growth dynamics. (ii) In the deterministic models we use here no substantial lag-phase evolves. This suggests that the lag-phase is a consequence of stochastic gene expression.

Show MeSH
Related in: MedlinePlus