Population Design for Synthetic Gene Circuits
OPEN ACCESS
Author / Producer
Date
2021
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
Altmetric
OPEN ACCESS
Data
Rights / License
Abstract
Synthetic biologists use and combine diverse biological parts to build systems such as genetic circuits that perform desirable functions in, for example, biomedical or industrial applications. Computer-aided design methods have been developed to help choose appropriate network structures and biological parts for a given design objective. However, they almost always model the behavior of the network in an average cell, despite pervasive cell-to-cell variability. Here, we present a computational framework to guide the design of synthetic biological circuits while accounting for cell-to-cell variability explicitly. Our design method integrates a NonLinear Mixed-Effect (NLME) framework into an existing algorithm for design based on ordinary differential equation (ODE) models. The analysis of a recently developed transcriptional controller demonstrates first insights into design guidelines when trying to achieve reliable performance under cell-to-cell variability. We anticipate that our method not only facilitates the rational design of synthetic networks under cell-to-cell variability, but also enables novel applications by supporting design objectives that specify the desired behavior of cell populations.
Permanent link
Publication status
published
External links
Book title
Computational Methods in Systems Biology. CMSB 2021
Journal / series
Volume
12881
Pages / Article No.
181 - 197
Publisher
Springer
Event
19th International Conference on Computational Methods in Systems Biology (CMSB 2021)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Cell-to-cell variability; Synthetic biology; Computer-aided design
Organisational unit
03699 - Stelling, Jörg / Stelling, Jörg
Notes
Funding
Related publications and datasets
Is cited by: