Table 1.
Biomass composition used in the model iDsh827.
Figure 1.
Histogram of average swimming velocities of D. shibae.
The velocities are given in µm/s and the heights of the bars indicate the fraction of bacteria displaying this velocity.
Table 2.
Properties of the genome-scale metabolic model iDsh827.
Table 3.
Proton-translocating reactions in iDsh827.
Table 4.
Conditions whose combinations were covered in the simulations.
Figure 2.
High-level overview of all simulations.
A) Histogram showing the distribution of growth rates over all simulations. B) Number of simulations displaying a given flux distribution ranked by the number of simulations. For clarity, every 1000th flux distribution was chosen as representative.
Figure 3.
Overview of the wild type simulations.
In this figure the growth rate is charted against the flux through the citrate synthase. The carbon source is given by the color and shape of the inner marker. Moreover, the outer marker indicates motility (shape), aerobic/anaerobic conditions (line style), and illumination (background color). No growth was predicted in any high motility physiological state for dark and anaerobic conditions if DMSP was used as carbon source. Hence, this entry is missing in the figure. PHB: polyhydroxybutyrate; DMSP: dimethylsulfoniopropionate.
Figure 4.
Metabolic context of oxaloacetate during growth on glucose.
Reactions are shown in yellow (round boxes) while metabolites are shown in blue (angular boxes). The total flux through a metabolite is given in mmol/(gDW h). Outgoing and incoming fluxes are given in percentages of the total flux. The upper numbers correspond to a dark states and the lower numbers to light states. In both cases growth on glucose was simulated under aerobic conditions.
Figure 5.
Metabolic context of oxaloacetate during growth on DMSP.
Reactions are shown in yellow (round boxes) while metabolites are shown in blue (angular boxes). The total flux through a metabolite is given in mmol/(gDW h). Outgoing and incoming fluxes are given in percentages of the total flux. The upper numbers correspond to a dark states and the lower numbers to light states. In both cases growth on DMSP was simulated under aerobic conditions.
Figure 6.
Relative contribution of the DMSP demethylation pathway in dependence of varying simulation parameters.
The percentage and the background color indicate the maximal fraction of demethylated DMSP determined by flux variability analysis while the remainder represents the DMSP degraded by the cleavage pathway. The maximal difference to the minimal contribution is 1.2%.
Figure 7.
Histogram of the growth rate gain observed if phosphofructokinase is enabled in all simulations with glucose as carbon source.
The simulations representing oligotrophic states in light are shown in dark blue. Simulations in which both strains do not display growth are not considered.
Figure 8.
Distribution of the growth phenotype of all 348,300 single gene knock-out mutants.
Figure 9.
Knock-out matrix showing the growth phenotype of 43 single gene knock-out mutants in selected simulations.
Mutants are identified by the locus tag of the disabled gene and physiological states are given by their conditions (illumination, carbon source, and electron acceptor).