Multi-objective optimization for gene expression noise reduction in a synthetic gene circuit

TitleMulti-objective optimization for gene expression noise reduction in a synthetic gene circuit
Publication TypeJournal Article
Year of Publication2017
AuthorsBoada Y., Vignoni A., Picó J.
JournalIFAC PapersOnLine
Date Published2017

Stochasticity in biological systems often referred to as gene expression noise is ubiquitous.The main sources of this noise come about in two ways. The implicit randomness of the biochemicalreactions generates intrinsic noise inside the cell. Other cellular processes are themselves products thatvary over time and from each cell to another, producing the so-called extrinsic noise. Controlling themean expression level of a gene while reducing its noise is a challenge in many applications of SyntheticBiology. In previous works, we proposed a gene synthetic circuit to reduce gene expression noise whileachieving a desired mean expression level. The circuit combines a negative feedback loop and a cell-to-cell communication mechanism based on quorum sensing. In this work, we use a multi-objectiveoptimization design approach to find the best values for the tunable-in-the-lab parameters that, for agiven desired mean expression value, achieve minimization of gene expression noise caused by intrinsicand extrinsic fluctuations. Our approach allows tuning the circuit parameters required to minimize noiseeffects, providing results which prove in accordance with genome-wide experimental data reported inthe literature. Exploring different scenarios, either considering only intrinsic noise or considering bothextrinsic and intrinsic ones, we find that the design strategies obtained for both cases are not transferable.Thus, designing the circuit parameters taking into account only intrinsic noise yields a sub-optimaldesign with decreased performance when evaluated in a scenario where both extrinsic and intrinsic noiseare present.