Abstract
Genetic circuits implement computational operations within a cell. Debugging them is difficult because their function is defined by multiple states (e.g., combinations of inputs) that vary in time. Here, we develop RNA‐seq methods that enable the simultaneous measurement of: (i) the states of internal gates, (ii) part performance (promoters, insulators, terminators), and (iii) impact on host gene expression. This is applied to a three‐input one‐output circuit consisting of three sensors, five NOR/NOT gates, and 46 genetic parts. Transcription profiles are obtained for all eight combinations of inputs, from which biophysical models can extract part activities and the response functions of sensors and gates. Various unexpected failure modes are identified, including cryptic antisense promoters, terminator failure, and a sensor malfunction due to media‐induced changes in host gene expression. This can guide the selection of new parts to fix these problems, which we demonstrate by using a bidirectional terminator to disrupt observed antisense transcription. This work introduces RNA‐seq as a powerful method for circuit characterization and debugging that overcomes the limitations of fluorescent reporters and scales to large systems composed of many parts.
Highlights
Natural regulatory networks control the timing and conditions for gene expression
The first step in characterizing a genetic circuit is to gather data covering the range of states (Fig 1A)
This differs depending on the type of circuit; for logic, this corresponds to steady-state measurements for each combination of inputs, whereas for a dynamic circuit, it would involve sampling time points
Summary
An ability to construct synthetic networks would enable the spatiotemporal control of biological processes (Basu et al, 2004). These could be used to react to environmental conditions (e.g., different phases of growth in a bioreactor; Anderson et al, 2006; Gupta et al, 2017) or implement a dynamic response (e.g., avoiding the accumulation of toxic intermediates; Zhang et al, 2012). Obtaining a desired response requires numerous interacting genes and precise control over their expression. This results in large systems that contain many genetic parts, all of which must function correctly in concert. Mapping the fluorescence data of the output back to the specific internal failure can be difficult or impossible
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