Fig. 2.

Noise in metabolite molecular number (η_s = σ_s/s) for different pathways. Monte Carlo simulations (bars) are compared with the analytic prediction (symbols) obtained by assuming decorrelation for different nodes of the pathways. The structure of each pathway is shown under each image. Parameter values were chosen randomly such that 10³ < K_i < 10⁴ and c < v_i < 10c. Similar decorrelation was obtained for 100 different random choices of parameters and for 100 different sets with K_i 10-fold smaller (data not shown). The effect on the different metabolites of a change in the velocity of the first reaction, v₁ = 1.1c (dark gray) → 5c (light gray), is demonstrated. Similar results are obtained for changes in K₁ (data not shown). (a) Directed pathway. Here the decorrelation property is exact. (b) Directed pathway with two reversible reactions. For these reactions, v_3,4⁺ = 8.4, 6.9c; v_3,4⁻ = 1.6, 3.7c; K_3,4⁺ = 2500, 8000; and K_3,4⁻ = 7700, 3700. (c) Linear dilution of metabolites. Here β/c = 1/100. (d) End-product inhibition, where the influx rate is given by α = c₀[1 + (m_L/K_I)]⁻¹ with K_I = 1,000. (e) Diverging pathways. Here metabolite 4 is being processed by two enzymes (with different affinities, K^I = 810, K^II = 370) into metabolites 5 and 7, respectively. (f) Converging pathways. Here two independent three-reaction pathways, with fluxes c and c′ = c/2, produce the same product, S₄.