publication . Other literature type . Preprint . Article . 2020

Self-adaptive Biosystems Through Tunable Genetic Parts and Circuits

Vittorio Bartoli; Mario di Bernardo; Thomas E. Gorochowski;
Open Access
  • Published: 06 Oct 2020
  • Publisher: MDPI AG
Biological systems often need to operate in complex environments where conditions can rapidly change. This is possible due to their inherent ability to sense changes and adapt by adjusting their behavior in response. Here, we detail recent advances in the creation of synthetic genetic parts and circuits whose behaviors can be dynamically tuned through a variety of intra- and extra-cellular signals. We show how this capability lays the foundation for implementing control engineering schemes in living cells and allows for the creation of biological systems that are able to self-adapt, ensuring their functionality is maintained in the face of varying environmental ...
free text keywords: biotechnology, biochemistry, Synthetic biology, Systems biology, Electronic circuit, Computer science, Self adaptive, Electronic engineering, Distributed computing, Software deployment
Funded by
UKRI| BrisSynBio: Bristol Centre for Synthetic Biology
  • Funder: UK Research and Innovation (UKRI)
  • Project Code: BB/L01386X/1
  • Funding stream: BBSRC
Control Engineering of Biological Systems for Reliable Synthetic Biology Applications
  • Funder: European Commission (EC)
  • Project Code: 766840
  • Funding stream: H2020 | RIA
Validated by funder
UKRI| EPSRC and BBSRC Centre for Doctoral Training in Synthetic Biology
  • Funder: UK Research and Innovation (UKRI)
  • Project Code: EP/L016494/1
  • Funding stream: EPSRC
FET H2020FET OPEN: FET-Open research and innovation actions
FET H2020FET OPEN: Control Engineering of Biological Systems for Reliable Synthetic Biology Applications
66 references, page 1 of 5

Fernandez-Rodriguez J, Yang L, Gorochowski TE, Gordon DB, Voigt CA: Memory and Combinatorial Logic Based on DNA Inversions: Dynamics and Evolutionary Stability. ACS Synth Biol 2015, 4:1361-1372.

Sleight SC, Bartley BA, Lieviant JA, Sauro HM: Designing and engineering evolutionary robust genetic circuits. J Biol Eng 2010, 4:12. [OpenAIRE]

Gorochowski TE, Espah Borujeni A, Park Y, Nielsen AA, Zhang J, Der BS, Gordon DB, Voigt CA: Genetic circuit characterization and debugging using RNA-seq. Mol Syst Biol 2017, 13:952.

11. Chappell J, Westbrook A, Verosloff M, Lucks JB: Computational design of small transcription activating RNAs for versatile and dynamic gene regulation. Nat Commun 2017, 8:1051. [OpenAIRE]

12. Chappell J, Takahashi MK, Lucks JB: Creating small transcription activating RNAs. Nat Chem Biol 2015, 11:214-220.

13. Kim H, Bojar D, Fussenegger M: A CRISPR/Cas9-based central processing unit to program complex logic computation in human cells. Proc Natl Acad Sci 2019, 116:7214.

14. Gilbert LA, Horlbeck MA, Adamson B, Villalta JE, Chen Y, Whitehead EH, Guimaraes C, Panning B, Ploegh HL, Bassik MC, et al.: Genome-Scale CRISPR-Mediated Control of Gene Repression and Activation. Cell 2014, 159:647-661. [OpenAIRE]

15. Green AA, Silver PA, Collins JJ, Yin P: Toehold Switches: De-Novo-Designed Regulators of Gene Expression. Cell 2014, 159:925-939. [OpenAIRE]

16. Green AA, Kim J, Ma D, Silver PA, Collins JJ, Yin P: Complex cellular logic computation using ribocomputing devices. Nature 2017, 548:117.

17. Gorochowski TE, Chelysheva I, Eriksen M, Nair P, Pedersen S, Ignatova Z: Absolute quantification of translational regulation and burden using combined sequencing approaches. Mol Syst Biol 2019, 15:e8719.

18. Kelly CL, Harris AWK, Steel H, Hancock EJ, Heap JT, Papachristodoulou A: Synthetic negative feedback circuits using engineered small RNAs. Nucleic Acids Res 2018, 46:9875-9889. [OpenAIRE]

19. Soper T, Mandin P, Majdalani N, Gottesman S, Woodson SA: Positive regulation by small RNAs and the role of Hfq. Proc Natl Acad Sci 2010, 107:9602.

20. Greco FV, Tarnowski MJ, Gorochowski TE: Living computers powered by biochemistry. The Biochemist 2019, 41:14-18.

21. Briat C, Gupta A, Khammash M: Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks. Cell Syst 2016, 2:15-26.

22. M. Khammash, M. Di Bernardo, D. Di Bernardo: Cybergenetics: Theory and Methods for Genetic Control System. In 2019 IEEE 58th Conference on Decision and Control (CDC). . 2019:916-926. • A clear introduction to the emerging field of cybernetics covering the key theory and experimental methods that make these types of system possible.

66 references, page 1 of 5
Any information missing or wrong?Report an Issue