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Computational Prediction of Synthetic Circuit Function Across Growth Conditions

View ORCID ProfileBreschine Cummins, Robert C. Moseley, Anastasia Deckard, Mark Weston, George Zheng, Daniel Bryce, Joshua Nowak, Marcio Gameiro, Tomas Gedeon, Konstantin Mischaikow, View ORCID ProfileJacob Beal, Tessa Johnson, Matthew Vaughn, Niall I. Gaffney, Shweta Gopaulakrishnan, Joshua Urrutia, Robert P. Goldman, Bryan Bartley, Tramy T. Nguyen, Nicholas Roehner, Tom Mitchell, Justin D. Vrana, Katie J. Clowers, Narendra Maheshri, Diveena Becker, Ekaterina Mikhalev, Vanessa Biggers, Trissha R. Higa, Lorraine A. Mosqueda, Steven B. Haase
doi: https://doi.org/10.1101/2022.06.13.495701
Breschine Cummins
1Montana State University, Bozeman, MT, U.S.A.
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  • ORCID record for Breschine Cummins
Robert C. Moseley
2Duke University, Durham, NC, U.S.A.
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Anastasia Deckard
3Geometric Data Analytics, Inc., Durham, NC, U.S.A.
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Mark Weston
4Netrias LLC, Annapolis, MD, U.S.A.
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George Zheng
4Netrias LLC, Annapolis, MD, U.S.A.
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Daniel Bryce
5SIFT, LLC, Minneapolis, MN, U.S.A.
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Joshua Nowak
6Strateos, Inc., Menlo Park, CA, U.S.A.
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Marcio Gameiro
7Rutgers University, New Brunswick, NJ, U.S.A.
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Tomas Gedeon
1Montana State University, Bozeman, MT, U.S.A.
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Konstantin Mischaikow
7Rutgers University, New Brunswick, NJ, U.S.A.
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Jacob Beal
8Raytheon BBN, Cambridge, MA, U.S.A.
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Tessa Johnson
3Geometric Data Analytics, Inc., Durham, NC, U.S.A.
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Matthew Vaughn
9Texas Advanced Computing Center, Austin, TX, U.S.A.
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Niall I. Gaffney
9Texas Advanced Computing Center, Austin, TX, U.S.A.
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Shweta Gopaulakrishnan
9Texas Advanced Computing Center, Austin, TX, U.S.A.
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Joshua Urrutia
9Texas Advanced Computing Center, Austin, TX, U.S.A.
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Robert P. Goldman
5SIFT, LLC, Minneapolis, MN, U.S.A.
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Bryan Bartley
8Raytheon BBN, Cambridge, MA, U.S.A.
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Tramy T. Nguyen
8Raytheon BBN, Cambridge, MA, U.S.A.
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Nicholas Roehner
8Raytheon BBN, Cambridge, MA, U.S.A.
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Tom Mitchell
8Raytheon BBN, Cambridge, MA, U.S.A.
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Justin D. Vrana
10UW Biofab, Seattle, WA, U.S.A.
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Katie J. Clowers
11Ginkgo Bioworks, Boston, MA, U.S.A.
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Narendra Maheshri
11Ginkgo Bioworks, Boston, MA, U.S.A.
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Diveena Becker
11Ginkgo Bioworks, Boston, MA, U.S.A.
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Ekaterina Mikhalev
11Ginkgo Bioworks, Boston, MA, U.S.A.
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Vanessa Biggers
6Strateos, Inc., Menlo Park, CA, U.S.A.
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Trissha R. Higa
6Strateos, Inc., Menlo Park, CA, U.S.A.
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Lorraine A. Mosqueda
6Strateos, Inc., Menlo Park, CA, U.S.A.
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Steven B. Haase
2Duke University, Durham, NC, U.S.A.
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  • For correspondence: steve.haase@duke.edu
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Abstract

A challenge in the design and construction of synthetic genetic circuits is that they will operate within biological systems that have noisy and changing parameter regimes that are largely unmeasurable. The outcome is that these circuits do not operate within design specifications or have a narrow operational envelope in which they can function. This behavior is often observed as a lack of reproducibility in function from day to day or lab to lab. Moreover, this narrow range of operating conditions does not promote reproducible circuit function in deployments where environmental conditions for the chassis are changing, as environmental changes can affect the parameter space in which the circuit is operating. Here we describe a computational method for assessing the robustness of circuit function across broad parameter regions. Previously designed circuits are assessed by this computational method and then circuit performance is measured across multiple growth conditions in budding yeast. The computational predictions are correlated with experimental findings, suggesting that the approach has predictive value for assessing the robustness of a circuit design.

Competing Interest Statement

Some of the authors are employed by companies that may benefit or be perceived to benefit from this publication.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted June 13, 2022.
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Computational Prediction of Synthetic Circuit Function Across Growth Conditions
Breschine Cummins, Robert C. Moseley, Anastasia Deckard, Mark Weston, George Zheng, Daniel Bryce, Joshua Nowak, Marcio Gameiro, Tomas Gedeon, Konstantin Mischaikow, Jacob Beal, Tessa Johnson, Matthew Vaughn, Niall I. Gaffney, Shweta Gopaulakrishnan, Joshua Urrutia, Robert P. Goldman, Bryan Bartley, Tramy T. Nguyen, Nicholas Roehner, Tom Mitchell, Justin D. Vrana, Katie J. Clowers, Narendra Maheshri, Diveena Becker, Ekaterina Mikhalev, Vanessa Biggers, Trissha R. Higa, Lorraine A. Mosqueda, Steven B. Haase
bioRxiv 2022.06.13.495701; doi: https://doi.org/10.1101/2022.06.13.495701
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Computational Prediction of Synthetic Circuit Function Across Growth Conditions
Breschine Cummins, Robert C. Moseley, Anastasia Deckard, Mark Weston, George Zheng, Daniel Bryce, Joshua Nowak, Marcio Gameiro, Tomas Gedeon, Konstantin Mischaikow, Jacob Beal, Tessa Johnson, Matthew Vaughn, Niall I. Gaffney, Shweta Gopaulakrishnan, Joshua Urrutia, Robert P. Goldman, Bryan Bartley, Tramy T. Nguyen, Nicholas Roehner, Tom Mitchell, Justin D. Vrana, Katie J. Clowers, Narendra Maheshri, Diveena Becker, Ekaterina Mikhalev, Vanessa Biggers, Trissha R. Higa, Lorraine A. Mosqueda, Steven B. Haase
bioRxiv 2022.06.13.495701; doi: https://doi.org/10.1101/2022.06.13.495701

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