Accurate Predictions of Genetic Circuit Behavior from Part Characterization and Modular Composition

Abstract

A long-standing goal of synthetic biology is to rapidly engineer new regulatory circuits from simpler devices. As circuit complexity grows, it becomes increasingly important to guide design with quantitative models, but previous efforts have been hindered by lack of predictive accuracy. To address this, we developed Empirical Quantitative Incremental Prediction (EQuIP), a new method for accurate prediction of genetic regulatory network behavior from detailed characterizations of their components. In EQuIP, precisely calibrated time-series and dosage-response assays are used to construct hybrid phenotypic/mechanistic models of regulatory processes. This hybrid method ensures that model parameters match observable phenomena, using phenotypic formulation where current hypotheses about biological mechanisms do not agree closely with experimental observations. We demonstrate EQuIP's precision at predicting distributions of cell behaviors for six transcriptional cascades and three feed-forward circuits in mammalian cells. Our cascade predictions have only 1.6-fold mean error over a 261-fold mean range of fluorescence variation, owing primarily to calibrated measurements and piecewise-linear models. Predictions for three feed-forward circuits had a 2.0-fold mean error on a 333-fold mean range, further demonstrating that EQuIP can scale to more complex systems. Such accurate predictions will foster reliable forward engineering of complex biological circuits from libraries of standardized devices.

Absolute quantification of translational regulation and burden using combined sequencing approaches

“…To date, the accuracy of models in synthetic biology has been hampered by a lack of reliable, quantitative, and high‐throughput measurements of genetic parts and devices, as well as their effects on the host cell. Attempts have been made to improve this situation by using standard calibrants to increase reproducibility across laboratories and equipment (Davidsohn et al , ; Beal et al , ; Castillo‐Hair et al , ) and by including synthetic RNA spike‐ins to enable absolute quantification of transcription (Owens et al , ). Our methodology complements these efforts by combining RNA‐seq and Ribo‐seq with RNA spike‐in standards to quantify the regulation of transcription and translation.…”

FlowCal: A User-Friendly, Open Source Software Tool for Automatically Converting Flow Cytometry Data from Arbitrary to Calibrated Units

“…FlowCal histogram plots of a single sample of E. coli BW29655 expressing sfGFP from the IPTG-inducible promoter P tac (16) when fully induced, measured at 10 different detector gain settings in (A) a.u., and (B) MEFL. Histograms of fluorescence values (geometric mean of each population) of E. coli expressing the CcaS-CcaR v2.0 system (17) in the dark, taken from 54 experimental replicates carried out over eight months in (C) uncalibrated arbitrary units (left) and (D) FlowCal calibrated molecules of equivalent fluorescein (MEFL) values.…”

Cas9 gRNA engineering for genome editing, activation and repression

“…To this end, we used one of our previously characterized transcription activator–like effector repressors (TALERs) 11,12 and first tested whether Cas9-VPR could cleave within the TALER coding sequence and decrease the amount of available TALER, thereby negating its repression of EYFP (Supplementary Fig. 13).…”