Isocost Lines Describe the Cellular Economy of Genetic Circuits

Abstract

Genetic circuits in living cells share transcriptional and translational resources that are available in limited amounts. This leads to unexpected couplings among seemingly unconnected modules, which result in poorly predictable circuit behavior. In this study, we determine these interdependencies between products of different genes by characterizing the economy of how transcriptional and translational resources are allocated to the production of proteins in genetic circuits. We discover that, when expressed from the same plasmid, the combinations of attainable protein concentrations are constrained by a linear relationship, which can be interpreted as an isocost line, a concept used in microeconomics. We created a library of circuits with two reporter genes, one constitutive and the other inducible in the same plasmid, without a regulatory path between them. In agreement with the model predictions, experiments reveal that the isocost line rotates when changing the ribosome binding site strength of the inducible gene and shifts when modifying the plasmid copy number. These results demonstrate that isocost lines can be employed to predict how genetic circuits become coupled when sharing resources and provide design guidelines for minimizing the effects of such couplings.

Dynamic allocation of orthogonal ribosomes facilitates uncoupling of co-expressed genes

“…GFP transcription was constitutively driven from the P tet promoter and the host or oribosome pool utilised for translation, controlled by selection of RBS as described above. We determined the level of coupling between the two circuit genes by observing the slope of the isocost line of circuit gene expression during exponential growth; this quantifies the change in GFP as RFP is induced 3 (Fig. 2).…”

“…However, many initial designs fail upon implementation in vivo due to unforeseen interactions between the host and synthetic circuit 2 . These often arise due to competition for shared cellular resources, such as RNA polymerases and ribosomes 3,4 . Previous experimental studies have shown that translational capacity, in the form of free ribosomes, limits microbial gene expression 3,[5][6][7][8] and so is a key cause of these hidden interactions 4 .…”

“…These often arise due to competition for shared cellular resources, such as RNA polymerases and ribosomes 3,4 . Previous experimental studies have shown that translational capacity, in the form of free ribosomes, limits microbial gene expression 3,[5][6][7][8] and so is a key cause of these hidden interactions 4 . Previous work has shown that the nonregulatory coupling that emerges due to these hidden interactions can be reduced by careful design and selection of ribosome binding sites and plasmid copy numbers 3,4,6 .…”

“…Previous experimental studies have shown that translational capacity, in the form of free ribosomes, limits microbial gene expression 3,[5][6][7][8] and so is a key cause of these hidden interactions 4 . Previous work has shown that the nonregulatory coupling that emerges due to these hidden interactions can be reduced by careful design and selection of ribosome binding sites and plasmid copy numbers 3,4,6 . Additionally, incorporating negative feedback loops into the circuit can insulate genes [9][10][11] .…”

A resource dependent protein synthesis model for evaluating synthetic circuits

“…Some of these couplings originate from the usage of shared resources of the transcriptional and translational machinery. The influence of such limited pools of resources has been addressed just recently by Gyorgy et al (2015); Weiße et al (2015); Gorochowski et al (2016), where both experimental and computational approaches are being discussed. For the purpose of describing interactions of several genes and their products, the stated works mainly use Hill-kinetics to phenomenologically describe protein production depending on the concentration of certain transcription factors.…”