THE CRISPRATOR: A FEEDBACK CONTROLLER IN MAMMALIAN CELLS FOR ROBUST PERFECT ADAPTATION

Synthetic Biology, merging genetic engineering with control theory, aims to achieve predictable behaviours in living systems, not relying on single components but rather on their interactions. Viewing DNA, RNA, and proteins as electronic circuit components, Synthetic Biology seeks to emulate circuit topologies to attain desired functionalities. Natural gene networks display robustness, the capacity of the cell to maintain its state despite perturbations, and more specifically Robust Perfect Adaptation (RPA), i.e. the ability to maintain a constant output level despite changes in the environment. In Control Engineering, RPA can be achieved by mechanisms like integral feedback control, a specific implementation of Negative Feedback loops. However, the engineering of synthetic biomolecular circuits implementing an integral controller able to confer RPA in living cells is still an open problem, which if solved could have a major impact in several applications. Gene networks implementing an Antithetic Integral Controller have only been presented very recently using mRNA pairs and inteins. In this thesis, I implemented the CRISPRaTOR, an Integral Controller based on the interaction between a CRISPR/Cas9-derived transcription factor and the recently discovered anti-CRISPR proteins, demonstrating its capability to achieve robust perfect adaptation in cell lines to various disturbances. I showcase precise, tunable, and robust control of a synthetic gene of interest and harness the programmable nature of the CRISPR/Cas9-derived transcription factor to apply this controller to an endogenous gene of interest. Additionally, I showcased an application of the CRISPRaTOR to enhance the linearity and robustness of a whole-cell biosensor of intracellular copper.

Grantor dc:publisher

Università degli Studi di Milano

Year dc:date

2023

Author dc:creator

• MALLOZZI, ALESSIO

Contributors dc:contributor

• internal advisor: M. A. de Matteis ; external advisor: R. Jerala ; supervisor: D. Di Bernardo
• A. Mallozzi

• Synthetic Biology
• Gene Circuit
• CRISPR/Cas9
• Anti-CRISPR
• Robustne
• Robust Perfect Adaptation
• RPA
• Doxycycline
• Linearity
• Feedback Controller
• Negative Feedback
• Antithetic Integral Controller
• AIC
• dCas9
• Settore ING-IND/34 - Bioingegneria Industriale

Statement dc:rights

• info:eu-repo/semantics/openAccess

Language dc:language

eng

Identifier

http://dx.doi.org/10.13130/mallozzi-alessio_phd2023-12-04
10.13130/mallozzi-alessio_phd2023-12-04

OAI identifier oai:identifier

oai:air.unimi.it:2434/1018415