A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly-interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc finger-based TFs. We show that circuits ‘wired’ using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-termcontinuous culture. Our naturally-inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.

These data were generated to support the characterization of a toolkit used to construct cooperatively binding synthetic transcription factors (synTFs) in yeast to both build stable genetic circuits and better understand eukaryotic transcriptional regulation. Our inducible synthetic zinc finger-derived transcription factors harbor an activation domain and bind to 9 bp cis regulatory elements that we integrate into the yeast genome. We use these transcriptional activators to build insulated genetic circuits, characterizing their performance, and the fitness of yeast cells expressing the activators, in our published work. We demonstrate circuit stability in competition experiments as well as long-term evolution experiments and describe a circuit with memory that functions via positive feedback following a short induction period.

Our datasets, comprised of data gathered using flow cytometry from which we calculate activation, as well as cellular fitness measurements and growth rate measurements, support the seven major figures of our manuscript:

1. Introduction of a cellular fitness cost from nonspecific binding of transcription factors in endogenous and synthetic regulatory networks.
2. A thermodynamic model indicates that increased TF cooperativity improves binding fidelity. Characterization of synTF concentration, affinity, and multi-synTF complex size from a synthetic TF cooperativity toolkit in yeast. Determining a synTF activation expression tradeoff with cellular fitness for nine candidate library synTFs.
3. RNA-sequencing analysis of differential gene expression in yeast strains containing either cooperatively binding or non-cooperative synTFs.
4. Chromatin immunoprecipitation-sequencing analysis of differential gene expression in yeast strains containing either cooperatively binding or non-cooperative synTFs. Differential gene expression at ten endogenous loci indicated as likely synTF binding events.
5. Long-term culturing experiments determine the cellular fitness cost and stability of synthetic circuits expressing cooperatively binding or non-cooperative synTFs.
6. Long-term culturing experiments indicate stable activation memory via a positive feedback loop in cells expressing cooperatively binding synTFs following a short inducer pulse.
7. synTF-cooperativity mediated long-term circuit stability is a promising strategy for industrial applications. 

The arranged datasets for each figure are included in .xlsx files, named “Fig#_arranged,” and the processed data are presented in .pzfx files, named “Fig#_processed.” They are accompanied by the relevant raw dataset files.

Please refer to the README file for a more detailed description of the data and file structure.

The .fcs raw datasets require FlowJo to open, and the .pzfx processed data files require GraphPad Prism.