Adaptability of non-genetic diversity in bacterial chemotaxis
- Yale University, United States
Figures
Figure 1
From proteins to fitness.
(A) The cell receives extracellular ligand signals through transmembrane receptors. Changes in signal are rapidly communicated to the flagellar motors through the kinase CheA and response regulator …
Figure 2 with 8 supplements
Performance of chemotactic phenotypes depends on environmental conditions.
(A) Cartoon diagram (not to scale) of the foraging challenge: cells navigating a 3-D time-varying gradient created by diffusion of a small spherical drop of nutrient 100 µm in diameter with …
Figure 2—figure supplement 1
Comparing the model to single cell and population averaged measurements.
The same set of model parameter values is used for all the plots. (A) Adaptation time and motor clockwise (CW) bias. Bottom: normalized histogram of motor clockwise bias in the population. Top: The …
Figure 2—figure supplement 2
Agreement between protein model and parametric dynamics model.
(A) Cartoon of step function of ligand delivered to immobilized cells in simulation to test response dynamics. (B) Direct comparison of response of molecular model (blue) and phenotypic model …
Figure 2—figure supplement 3
Performance as a function of distance to source.
(A) Cells with various phenotypes were challenged to forage a source presented at varying distances, r0 from 75 μm to 3 mm. Between 6000 and 30,000 replicates were simulated for each phenotype. : …
Figure 2—figure supplement 4
Optimal phenotypes as a function of source distance.
For each source distance and each task, the phenotype with highest performance was identified as shown in Figure 2—figure supplement 3. The clockwise bias and adaptation time of these phenotypes are …
Figure 2—figure supplement 5
Effect of time restrictions on foraging performance.
Cells were challenged to forage sources that appeared at distances of 200, 5000, or 1000 μm away (columns from left to right). Different amounts of time were allotted to cells to accumulate ligand: …
Figure 2—figure supplement 6
Effect of time limits on near/far foraging trade-offs.
Trade-offs in performance between foraging near and far sources are shown. From left to right (cyan to magenta), the far case is progressively more distant compared to the near case: 1 mm, 1.5 mm, 2 …
Figure 2—figure supplement 7
Effect of source concentration on performance.
Performance calculate and plotted as described in Figure 2—figure supplement 3, but for different concentrations at the source. Left block (‘Foraging’): foraging performance for increasing source …
Figure 2—figure supplement 8
Effect of CheY-P dynamic range on performance.
Left block (‘Foraging‘): foraging performance for near (200 µm) and far (1000 µm) sources and increasing CheY-P dynamic range, which was changed through the total number of CheY molecules, Ytot, as …
Figure 3
Relationship between Pareto front shape and population strategy.
Left: Two environments, A and B, select for different optimal phenotypes, specialist A and specialist B (blue and red circles). The generalist phenotype (gray circle) performs well, but not …
Figure 4
Performance trade-offs in E. coli chemotaxis.
Ecological chemotaxis tasks pose trade-off problems for E. coli that become strong when environmental variation is high. (A–C). Trade-off plot between nutrient accumulation when starting near and …
Figure 5 with 1 supplement
Selection can reshape trade-offs.
(A) Simple metabolic model of survival applied to the chemotactic foraging challenge. Each individual replicate is given a survival probability based on a Hill function of the nutrition they achieve …
Figure 5—figure supplement 1
Fitness trade-offs under alternate models of selection.
(A) Model of discrete physiological transitions applied to the chemotactic foraging challenge. Each individual replicate is given a number of progeny (0, 1, or 2) based on a two-step function of the …
Figure 6
Genetic control of phenotypic diversity.
(A) Clustering genes on multicistronic operons constrains the ratios in protein abundance. (B) Protein expression of core chemotaxis proteins CheRBYZ are shown relative to the mean level in wildtype …
Figure 7
Optimization of gene expression noise reshapes population distributions to the Pareto front.
Protein expression of populations were optimized for either weak or strong foraging fitness trade-offs (same trade-offs as in Figure 5B,C). For each population, 2000 individuals are plotted, protein …
Additional files
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Supplementary file 1
Parameter values.
- https://doi.org/10.7554/eLife.03526.019
