Customizable gene sensing and response without altering endogenous coding sequences

Fabio Caliendo^#^{1

2}, Elvira Vitu^#^{1

2}, Junmin Wang³, Shuo-Hsiu Kuo^{2

4}, Hayden Sandt^{1

2}, Casper Nørskov Enghuus^{1

2}, Jesse Tordoff^{1

2}, Neslly Estrada¹, James J Collins^{1

5

6

7}, Ron Weiss^{8

9

10}

Affiliations

¹ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
² Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
³ Bioinformatics Graduate Program, Boston University, Boston, MA, USA.
⁴ Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁵ Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
⁶ Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.
⁹ Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.
¹⁰ Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.

^# Contributed equally.

PMID: 39266721
DOI: 10.1038/s41589-024-01733-y

Customizable gene sensing and response without altering endogenous coding sequences

Fabio Caliendo et al. Nat Chem Biol. 2025 Mar.

. 2025 Mar;21(3):348-359.

doi: 10.1038/s41589-024-01733-y. Epub 2024 Sep 12.

Authors

Affiliations

¹ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
² Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
³ Bioinformatics Graduate Program, Boston University, Boston, MA, USA.
⁴ Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁵ Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
⁶ Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.
⁹ Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.
¹⁰ Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA. rweiss@mit.edu.

^# Contributed equally.

PMID: 39266721
DOI: 10.1038/s41589-024-01733-y

Abstract

Synthetic biology aims to modify cellular behaviors by implementing genetic circuits that respond to changes in cell state. Integrating genetic biosensors into endogenous gene coding sequences using clustered regularly interspaced short palindromic repeats and Cas9 enables interrogation of gene expression dynamics in the appropriate chromosomal context. However, embedding a biosensor into a gene coding sequence may unpredictably alter endogenous gene regulation. To address this challenge, we developed an approach to integrate genetic biosensors into endogenous genes without modifying their coding sequence by inserting into their terminator region single-guide RNAs that activate downstream circuits. Sensor dosage responses can be fine-tuned and predicted through a mathematical model. We engineered a cell stress sensor and actuator in CHO-K1 cells that conditionally activates antiapoptotic protein BCL-2 through a downstream circuit, thereby increasing cell survival under stress conditions. Our gene sensor and actuator platform has potential use for a wide range of applications that include biomanufacturing, cell fate control and cell-based therapeutics.

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Conflict of interest statement

Competing interests: The Massachusetts Institute of Technology has filed a patent application on behalf of the inventors (R.W., J.J.C., E.V., C.N.E. and J. Gam) of the gene sensor design described (US Patent App. 16/875,257, 2020). The remaining authors declare no competing interests.

References

1. Paddon, C. J. & Keasling, J. D. Semi-synthetic artemisinin: a model for the use of synthetic biology in pharmaceutical development. Nat. Rev. Microbiol. 12, 355–367 (2014). - PubMed - DOI
1. Chang, M. M. et al. Small-molecule control of antibody N-glycosylation in engineered mammalian cells. Nat. Chem. Biol. 15, 730–736 (2019). - PubMed - DOI
1. Charlton Hume, H. K. et al. Synthetic biology for bioengineering virus-like particle vaccines. Biotechnol. Bioeng. 116, 919–935 (2019). - PubMed - DOI
1. Collins, L. T. & Curiel, D. T. Synthetic biology approaches for engineering next-generation adenoviral gene therapies. ACS Nano 15, 13970–13979 (2021). - PubMed - DOI
1. Kitada, T., DiAndreth, B., Teague, B. & Weiss, R. Programming gene and engineered-cell therapies with synthetic biology. Science 359, eaad1067 (2018). - PubMed - PMC - DOI

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Customizable gene sensing and response without altering endogenous coding sequences

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Customizable gene sensing and response without altering endogenous coding sequences

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Conflict of interest statement

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