Limits...
Metabolic co-dependence gives rise to collective oscillations within biofilms.

Liu J, Prindle A, Humphries J, Gabalda-Sagarra M, Asally M, Lee DY, Ly S, Garcia-Ojalvo J, Süel GM - Nature (2015)

Bottom Line: It remains unclear how these opposing interactions are resolved at the population level.We discover that this conflict between protection and starvation is resolved through emergence of long-range metabolic co-dependence between peripheral and interior cells.As a result, biofilm growth halts periodically, increasing nutrient availability for the sheltered interior cells.

View Article: PubMed Central - PubMed

Affiliation: Division of Biological Sciences, University of California San Diego, California 92093, USA.

ABSTRACT
Cells that reside within a community can cooperate and also compete with each other for resources. It remains unclear how these opposing interactions are resolved at the population level. Here we investigate such an internal conflict within a microbial (Bacillus subtilis) biofilm community: cells in the biofilm periphery not only protect interior cells from external attack but also starve them through nutrient consumption. We discover that this conflict between protection and starvation is resolved through emergence of long-range metabolic co-dependence between peripheral and interior cells. As a result, biofilm growth halts periodically, increasing nutrient availability for the sheltered interior cells. We show that this collective oscillation in biofilm growth benefits the community in the event of a chemical attack. These findings indicate that oscillations support population-level conflict resolution by coordinating competing metabolic demands in space and time, suggesting new strategies to control biofilm growth.

Show MeSH

Related in: MedlinePlus

Mathematical model of biofilm growth. a, The model describes the dynamics of two cell populations in a biofilm, interior and peripheral. As the biofilm grows, there is a constant distance between the interior population and the biofilm edge. b–e, Bifurcation diagrams showing systematic analysis on the effects of external glutamine, external glutamate, ammonium uptake, and GDH overexpression respectively. The red lines correspond to the extrema of oscillations in peripheral glutamate (stable limit cycle). The solid black line denotes stable fixed point. The dashed black line corresponds to an unstable fixed point. The vertical gray lines highlight the state of the system for each nutrient addition experiment shown in Fig. 3 of the main text. f, Model prediction of oscillation period as function of interior cell fraction in the whole biofilm. g–h, Sensitivity analysis of oscillation period and modulation depth to changes in model parameters. Modulation depth is defined as the amplitude of the oscillations divided by the mean value. Gray color denotes parameter regions where the system does not oscillate.
© Copyright Policy - permissions-link
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4862617&req=5

Figure 10: Mathematical model of biofilm growth. a, The model describes the dynamics of two cell populations in a biofilm, interior and peripheral. As the biofilm grows, there is a constant distance between the interior population and the biofilm edge. b–e, Bifurcation diagrams showing systematic analysis on the effects of external glutamine, external glutamate, ammonium uptake, and GDH overexpression respectively. The red lines correspond to the extrema of oscillations in peripheral glutamate (stable limit cycle). The solid black line denotes stable fixed point. The dashed black line corresponds to an unstable fixed point. The vertical gray lines highlight the state of the system for each nutrient addition experiment shown in Fig. 3 of the main text. f, Model prediction of oscillation period as function of interior cell fraction in the whole biofilm. g–h, Sensitivity analysis of oscillation period and modulation depth to changes in model parameters. Modulation depth is defined as the amplitude of the oscillations divided by the mean value. Gray color denotes parameter regions where the system does not oscillate.

Mentions: The results described above evoke the intriguing possibility that ammonium limitation for peripheral cells may arise due to glutamate limitation for interior cells. Specifically, persistent consumption of glutamate by peripheral cells can deprive the interior cells of the necessary glutamate for ammonium production. In order to explore this nontrivial hypothesis, we turned to mathematical modeling to develop a conceptual framework and generate experimentally testable predictions. Our model describes separately the metabolic dynamics of interior and peripheral cells and the metabolite exchange between them, where the distinction of the two subpopulations depends on nutrient availability (see Supplementary Information: Mathematical Model). The model thus consists of two main assumptions (Fig. 3a): First, consumption of glutamate during growth of peripheral cells deprives interior cells of this nutrient and thus inhibits ammonium production in the biofilm interior. Second, the growth of peripheral cells depends predominantly on ammonium that is produced by metabolically stressed interior cells. A model based on these two simplifying assumptions (Fig. 3b) generates oscillations consistent with our experimental observations (Fig. 3c–e) and reproduces the effects of supplementing the media with glutamine, glutamate and ammonium (Fig. 3f–h, Extended Data Fig. 6 and Supplementary Information: Mathematical Model). The model also accounts for the observed slight increase of the oscillation period by considering an increase in the ratio of interior to peripheral cells over time (Extended Data Fig.1b and 6f). Therefore, this simple model shows that periodic halting in biofilm growth can result from metabolic codependence between cells in the biofilm periphery and interior that is driven by glutamate consumption and ammonium production, respectively.


Metabolic co-dependence gives rise to collective oscillations within biofilms.

Liu J, Prindle A, Humphries J, Gabalda-Sagarra M, Asally M, Lee DY, Ly S, Garcia-Ojalvo J, Süel GM - Nature (2015)

Mathematical model of biofilm growth. a, The model describes the dynamics of two cell populations in a biofilm, interior and peripheral. As the biofilm grows, there is a constant distance between the interior population and the biofilm edge. b–e, Bifurcation diagrams showing systematic analysis on the effects of external glutamine, external glutamate, ammonium uptake, and GDH overexpression respectively. The red lines correspond to the extrema of oscillations in peripheral glutamate (stable limit cycle). The solid black line denotes stable fixed point. The dashed black line corresponds to an unstable fixed point. The vertical gray lines highlight the state of the system for each nutrient addition experiment shown in Fig. 3 of the main text. f, Model prediction of oscillation period as function of interior cell fraction in the whole biofilm. g–h, Sensitivity analysis of oscillation period and modulation depth to changes in model parameters. Modulation depth is defined as the amplitude of the oscillations divided by the mean value. Gray color denotes parameter regions where the system does not oscillate.
© Copyright Policy - permissions-link
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4862617&req=5

Figure 10: Mathematical model of biofilm growth. a, The model describes the dynamics of two cell populations in a biofilm, interior and peripheral. As the biofilm grows, there is a constant distance between the interior population and the biofilm edge. b–e, Bifurcation diagrams showing systematic analysis on the effects of external glutamine, external glutamate, ammonium uptake, and GDH overexpression respectively. The red lines correspond to the extrema of oscillations in peripheral glutamate (stable limit cycle). The solid black line denotes stable fixed point. The dashed black line corresponds to an unstable fixed point. The vertical gray lines highlight the state of the system for each nutrient addition experiment shown in Fig. 3 of the main text. f, Model prediction of oscillation period as function of interior cell fraction in the whole biofilm. g–h, Sensitivity analysis of oscillation period and modulation depth to changes in model parameters. Modulation depth is defined as the amplitude of the oscillations divided by the mean value. Gray color denotes parameter regions where the system does not oscillate.
Mentions: The results described above evoke the intriguing possibility that ammonium limitation for peripheral cells may arise due to glutamate limitation for interior cells. Specifically, persistent consumption of glutamate by peripheral cells can deprive the interior cells of the necessary glutamate for ammonium production. In order to explore this nontrivial hypothesis, we turned to mathematical modeling to develop a conceptual framework and generate experimentally testable predictions. Our model describes separately the metabolic dynamics of interior and peripheral cells and the metabolite exchange between them, where the distinction of the two subpopulations depends on nutrient availability (see Supplementary Information: Mathematical Model). The model thus consists of two main assumptions (Fig. 3a): First, consumption of glutamate during growth of peripheral cells deprives interior cells of this nutrient and thus inhibits ammonium production in the biofilm interior. Second, the growth of peripheral cells depends predominantly on ammonium that is produced by metabolically stressed interior cells. A model based on these two simplifying assumptions (Fig. 3b) generates oscillations consistent with our experimental observations (Fig. 3c–e) and reproduces the effects of supplementing the media with glutamine, glutamate and ammonium (Fig. 3f–h, Extended Data Fig. 6 and Supplementary Information: Mathematical Model). The model also accounts for the observed slight increase of the oscillation period by considering an increase in the ratio of interior to peripheral cells over time (Extended Data Fig.1b and 6f). Therefore, this simple model shows that periodic halting in biofilm growth can result from metabolic codependence between cells in the biofilm periphery and interior that is driven by glutamate consumption and ammonium production, respectively.

Bottom Line: It remains unclear how these opposing interactions are resolved at the population level.We discover that this conflict between protection and starvation is resolved through emergence of long-range metabolic co-dependence between peripheral and interior cells.As a result, biofilm growth halts periodically, increasing nutrient availability for the sheltered interior cells.

View Article: PubMed Central - PubMed

Affiliation: Division of Biological Sciences, University of California San Diego, California 92093, USA.

ABSTRACT
Cells that reside within a community can cooperate and also compete with each other for resources. It remains unclear how these opposing interactions are resolved at the population level. Here we investigate such an internal conflict within a microbial (Bacillus subtilis) biofilm community: cells in the biofilm periphery not only protect interior cells from external attack but also starve them through nutrient consumption. We discover that this conflict between protection and starvation is resolved through emergence of long-range metabolic co-dependence between peripheral and interior cells. As a result, biofilm growth halts periodically, increasing nutrient availability for the sheltered interior cells. We show that this collective oscillation in biofilm growth benefits the community in the event of a chemical attack. These findings indicate that oscillations support population-level conflict resolution by coordinating competing metabolic demands in space and time, suggesting new strategies to control biofilm growth.

Show MeSH
Related in: MedlinePlus