Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals

Katherine A Kiwimagi; Justin H Letendre; Benjamin H Weinberg; Junmin Wang; Mingzhe Chen; Leandro Watanabe; Chris J Myers; Jacob Beal; Wilson W Wong; Ron Weiss

doi:10.1038/s42003-021-02325-5

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Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals

Journal article

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Peer reviewed

Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals

Katherine A Kiwimagi, Justin H Letendre, Benjamin H Weinberg, Junmin Wang, Mingzhe Chen, Leandro Watanabe, Chris J Myers, Jacob Beal, Wilson W Wong and Ron Weiss

Communications biology, Vol.4(1), pp.875-875

07/15/2021

DOI: 10.1038/s42003-021-02325-5

PMCID: PMC8282836

PMID: 34267310

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Abstract

Many synthetic gene circuits are restricted to single-use applications or require iterative refinement for incorporation into complex systems. One example is the recombinase-based digitizer circuit, which has been used to improve weak or leaky biological signals. Here we present a workflow to quantitatively define digitizer performance and predict responses to different input signals. Using a combination of signal-to-noise ratio (SNR), area under a receiver operating characteristic curve (AUC), and fold change (FC), we evaluate three small-molecule inducible digitizer designs demonstrating FC up to 508x and SNR up to 3.77 dB. To study their behavior further and improve modularity, we develop a mixed phenotypic/mechanistic model capable of predicting digitizer configurations that amplify a synNotch cell-to-cell communication signal (Δ SNR up to 2.8 dB). We hope the metrics and modeling approaches here will facilitate incorporation of these digitizers into other systems while providing an improved workflow for gene circuit characterization.

Genetic Engineering - methods

Recombinases - genetics

ROC Curve

Signal Transduction

Synthetic Biology - methods

Details

Title: Subtitle: Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals
Creators: Katherine A Kiwimagi - Massachusetts Institute of Technology
Justin H Letendre - Boston University
Benjamin H Weinberg - Boston University
Junmin Wang - Boston University
Mingzhe Chen - Massachusetts Institute of Technology
Leandro Watanabe - University of Utah
Chris J Myers - University of Utah
Jacob Beal - RTX
Wilson W Wong - Boston University
Ron Weiss - Massachusetts Institute of Technology
Resource Type: Journal article
Publication Details: Communications biology, Vol.4(1), pp.875-875
DOI: 10.1038/s42003-021-02325-5
PMID: 34267310
PMCID: PMC8282836
ISSN: 2399-3642
eISSN: 2399-3642
Grant note: DP2 CA186574 / NCI NIH HHS R01 GM129011 / NIGMS NIH HHS F31 HL149334 / NHLBI NIH HHS
Language: English
Date published: 07/15/2021
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984627239102771

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