Figure 3. Simulation of variable cellular composition and efficient use of enzymes.
(a) With our ME-Model, the RnA/protein ratio increases linearly with growth rate and with a slope proportional to translational capacity in amino acids per second (circles: 5 AA/s, squares: 10 AA/s, triangles: 20 AA/s). (b) Ribosomal RNA (rRnA) synthesis increases, relative to total RNA synthesis, with growth rate (symbols as in a). (c) Ribosomal protein promoter activity increases, relative to total RNA synthesis, with growth rate (symbols as in a). (d) Random sampling of the M-Model solution space indicates that the M-Model solution space contains numerous internal solutions with a broad range of total network flux. The probability of finding an M-Model solution as efficient as an ME-Model simulation is 2.1 × 10−5; the probability was calculated from a normal distribution constructed from the M-Model sample space. The M-Model sample contains 5,000 flux vectors randomly sampled from the M-Model solution space. (e) smooth estimate of the density of the flux ranges for the metabolic enzymes that may be simulated while maintaining the objective for efficient growth with a 1% tolerance (M-Model: red line, ME-Model: blue line). The shaded area denotes biologically unrealistic flux values. All simulations were performed with an in silico minimal medium with maltose as the sole carbon source.