Noise analysis of genome-scale protein synthesis using a discrete computational model of translation.

摘要: Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few these studies have considered noise properties using mechanistic models that account for discrete movement ribosomes RNA polymerases along their corresponding templates (messenger (mRNA) DNA). The large size systems, which scales with number genes, mRNA copies, codons per mRNA, ribosomes, is responsible some challenges. Additionally, one should be able to describe dynamics ribosome exchange between free pool those bound mRNAs, as well how species compete ribosomes. We developed an efficient algorithm stochastic simulations addresses issues used it study contribution trade-offs translation (rates, time delays, rate-limiting steps). linearly allowed us importance genome-scale competition mRNAs same determined minimized under conditions maximizing specific synthesis rate. Moreover, sensitivity analysis system revealed elongation rate resultant noise, whereas initiation constant was more closely related average protein observed significant differences our results most commonly models. Overall, demonstrate use full essential transcription.