Modular, robust and extendible multicellular circuit design in yeast
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Curated by eLife
Evaluation Summary:
In this manuscript, the authors address important problems in the field of synthetic biology about scalability, robustness, and modularity. They used multiple strains to build gene circuits and demonstrate the modular composition of strain circuits with an automated design strategy to achieve a target behavior from a large space of possible functional circuit architectures. The major claims of the manuscript are well supported by solid quantitative data and systematic mathematical modeling analysis, and the approaches used are thoughtful and rigorous. This paper is of interest to synthetic biologists within the field of designing communitylevel behaviors, such as distributed computing, in multicellular consortia.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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 Evaluated articles (eLife)
 Synthetic Biology (eLife)
Abstract
Division of labor between cells is ubiquitous in biology but the use of multicellular consortia for engineering applications is only beginning to be explored. A significant advantage of multicellular circuits is their potential to be modular with respect to composition but this claim has not yet been extensively tested using experiments and quantitative modeling. Here, we construct a library of 24 yeast strains capable of sending, receiving or responding to three molecular signals, characterize them experimentally and build quantitative models of their inputoutput relationships. We then compose these strains into two and threestrain cascades as well a fourstrain bistable switch and show that experimentally measured consortia dynamics can be predicted from the models of the constituent parts. To further explore the achievable range of behaviors, we perform a fully automated computational search over all two, three and fourstrain consortia to identify combinations that realize target behaviors including logic gates, bandpass filters and time pulses. Strain combinations that are predicted to map onto a target behavior are further computationally optimized and then experimentally tested. Experiments closely track computational predictions. The high reliability of these model descriptions further strengthens the feasibility and highlights the potential for distributed computing in synthetic biology.
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Evaluation Summary:
In this manuscript, the authors address important problems in the field of synthetic biology about scalability, robustness, and modularity. They used multiple strains to build gene circuits and demonstrate the modular composition of strain circuits with an automated design strategy to achieve a target behavior from a large space of possible functional circuit architectures. The major claims of the manuscript are well supported by solid quantitative data and systematic mathematical modeling analysis, and the approaches used are thoughtful and rigorous. This paper is of interest to synthetic biologists within the field of designing communitylevel behaviors, such as distributed computing, in multicellular consortia.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the …
Evaluation Summary:
In this manuscript, the authors address important problems in the field of synthetic biology about scalability, robustness, and modularity. They used multiple strains to build gene circuits and demonstrate the modular composition of strain circuits with an automated design strategy to achieve a target behavior from a large space of possible functional circuit architectures. The major claims of the manuscript are well supported by solid quantitative data and systematic mathematical modeling analysis, and the approaches used are thoughtful and rigorous. This paper is of interest to synthetic biologists within the field of designing communitylevel behaviors, such as distributed computing, in multicellular consortia.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

Joint Public Review:
In this work, Carignano et al. built a library of 24 yeast strains for signal sensing, synthesis, and depletion as an attempt to implement modular composition of multicellular circuits to demonstrate defined consortia dynamics that can be predicted from the models of the constituent parts. They systematically characterized all the doseresponse curves for each strain experimentally and fitted model 1 and model 2 based on ordinary differential equations with eight parameters. Then they proved that these strains can be modularly combined to realize several functions, including two and threestrain cascades. They set a factor K as the output gain in the model and as the foldchange with respect to the standard initial cell concentration in the experiment to easily tune the response dynamics. In addition to monotonic, …
Joint Public Review:
In this work, Carignano et al. built a library of 24 yeast strains for signal sensing, synthesis, and depletion as an attempt to implement modular composition of multicellular circuits to demonstrate defined consortia dynamics that can be predicted from the models of the constituent parts. They systematically characterized all the doseresponse curves for each strain experimentally and fitted model 1 and model 2 based on ordinary differential equations with eight parameters. Then they proved that these strains can be modularly combined to realize several functions, including two and threestrain cascades. They set a factor K as the output gain in the model and as the foldchange with respect to the standard initial cell concentration in the experiment to easily tune the response dynamics. In addition to monotonic, quasilinear dynamic systems with a single equilibrium point, they used a positive feedback loop to generate nonlinear responses to the inputs to extend the range of observable behaviors. Furthermore, they constructed a bistable switch strain circuit that requires enhanced nonlinearity to accomplish through induced signal degradation. They used model 3 to capture this circuit and tuned the indicated gains of the circuit to maximize the distance between equilibria in the phase diagram. The switching behavior to the respective external signal was clearly demonstrated. To expand the target behaviors, the authors developed an automated approach to compose the 24 engineered yeast strains to generate logic gates such as AND, NOR, NAND, and OR gates and verified the predictions in the experiments. Finally, they exploited their automated design strategy to identify the circuit designs for time pulses and bandpass filters from a very large design and test space that are out of reach by using an experimental approach. The mutuality of both the strains and mathematical model was maintained amazingly well in the multistrain systems. Overall, this paper is very interesting and useful given that circuit modularity can be easily lost due to the resource competition in a single strain. The manuscript is generally easy to read, and the figures are easy to understand.
Strengths:
 Characterization of modular components for engineering multicellular signaling circuits in the experiments and data fitting in the models paves a solid foundation for later development in this work.
 Their automated design strategy that comprises topology search, optimal circuit identification, and stoichiometry optimization largely increases the success rate in experimental realization from a large design space of the intended behavior in consortia.Weakness:
 Small difference in strain growth rate could explain the stabletounstable shift in a bistable switch circuit (Figure 3F and SI Figure 9). This suggested that uniform or approximately the same growth rate of all strains in multicellular consortia imposes a constraint to ensure the intended consortia dynamics. 