Engineered systems of inducible anti-repressors for the next generation of biological programming

Groseclose, Thomas M; Rondon, Ronald E.; Herde, Zachary D.; Aldrete, Carlos A.; Wilson, Clive

doi:10.1038/s41467-020-18302-1

Cited by 33 publications

(70 citation statements)

References 60 publications

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“…As an additional example, we have established a system of multiple toggle switches with a master OFF signal 9 . Other studies also demonstrated the use of hybrid repressors for generating Boolean logic operations 13 , 14 . In addition to circuit development, module swapping of repressors has been used for other applications.…”

Section: Introductionmentioning

confidence: 99%

Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions

et al. 2021

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Genetic sensors with unique combinations of DNA recognition and allosteric response can be created by hybridizing DNA-binding modules (DBMs) and ligand-binding modules (LBMs) from distinct transcriptional repressors. This module swapping approach is limited by incompatibility between DBMs and LBMs from different proteins, due to the loss of critical module-module interactions after hybridization. We determine a design strategy for restoring key interactions between DBMs and LBMs by using a computational model informed by coevolutionary traits in the LacI family. This model predicts the influence of proposed mutations on protein structure and function, quantifying the feasibility of each mutation for rescuing hybrid repressors. We accurately predict which hybrid repressors can be rescued by mutating residues to reinstall relevant module-module interactions. Experimental results confirm that dynamic ranges of gene expression induction were improved significantly in these mutants. This approach enhances the molecular and mechanistic understanding of LacI family proteins, and advances the ability to design modular genetic parts.

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Section: Introductionmentioning

confidence: 99%

Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions

et al. 2021

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“…53 As such, it might be interesting to explore the possibility that temporally controlled fluctuations in Nanog transcription factors 54,55 could selectively direct specific neighboring cells to differentiate while maintaining others in the stem state. Overall, we envision that advancing synthetic biology motifs, especially an increasing diversity of orthogonal transcription factors and promoters, 12,56 improved live cell reporters, 13,57 and faster and more specific optogenetically controlled transcription factors inputs, 30 will integrate synergistically with new probabilistic model predictive control analyses to improve future efforts to understand how noise, non-linearity, and feedback combine to drive cell fate decisions in applications ranging from synthetic biofuel and biomaterial production to developmental dynamics or regenerative medicine. Under the assumption of a well-mixed spatial environment within each cell, one can define the dynamics of such a process by specifying the reaction stoichiometry vector and reaction rate for each µ th reaction.…”

Section: Discussionmentioning

confidence: 99%

“…could selectively direct specific neighboring cells to differentiate while maintaining others in the stem state. Overall, we envision that advancing synthetic biology motifs, especially an increasing diversity of orthogonal transcription factors and promoters [12,44], improved live cell reporters [13], and faster and more specific optogenetically controlled transcription factors inputs [27], will integrate synergistically with new probabilistic model predictive control analyses to improve future efforts to understand how noise, non-linearity and feedback combine to drive cell fate decisions in applications ranging from synthetic biofuel and biomaterial production to developmental dynamics or regenerative medicine.…”

Section: /28mentioning

confidence: 99%

“…In turn, these simple switches have led to more complex engineered biological systems and biotechnologies capable of performing tasks like controlling cells to behave as digital displays [9]. Much of the design process for synthetic biology has focused directly on the design of building better biological components, such as creating more sophisticated gene regulatory structures [10][11][12], introducing new response elements or reporters [13], or introducing more orthogonal cellular signals [14]. Development work on gene regulatory structure has led to substantial advances in plant biology and therapeutics [15,16].…”

Section: Introductionmentioning

confidence: 99%

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Exploiting noise, non-linearity, and feedback for differential control of multiple synthetic cells with a single optogenetic input

May

Munsky

2021

Preprint

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Synthetic biology seeks to develop modular bio-circuits that combine to produce complex, controllable behaviors. These designs are often subject to noisy fluctuations and uncertainties, and most modern synthetic biology design processes have focused to create robust components to mitigate the noise of gene expression and reduce the heterogeneity of single-cell responses. However, deeper understanding of noise can achieve control goals that would otherwise be impossible. We explore how an `Optogenetic Maxwell Demon' could selectively amplify noise to control multiple cells using single-input-multiple-output (SIMO) feedback. Using data-constrained stochastic model simulations and theory, we show how an appropriately selected stochastic SIMO controller can drive multiple different cells to different user-specified configurations irrespective of initial condition. We explore how controllability depends on cells' regulatory structures, the amount of information available to the controller, and the accuracy of the model used. Our results suggest that gene regulation noise, when combined with optogenetic feedback and non-linear biochemical auto-regulation, can achieve synergy to enable precise control of complex stochastic processes.

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“…synthetic biology j protein engineering j transcription factors j BANDPASS j BANDSTOP E ngineered gene circuits have become a hallmark of synthetic biology, a discipline which itself has come into fruition in recent years in pursuit of building robust and predictable parts and systems for biotechnological and biomedical applications (1)(2)(3)(4). Synthetic genetic circuits have enabled the development of biological sensors (5) and switches (6), diagnostics and therapeutics (7,8), and biological analogs to electrical and control devices and programs (9)(10)(11)(12)(13)(14)(15)(16)(17). Further advances in gene circuit design promise to facilitate increasingly complex methods to regulate biological processes (4,18).…”

mentioning

confidence: 99%

Biological signal processing filters via engineering allosteric transcription factors

Groseclose

Hersey

Huang

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Signal processing is critical to a myriad of biological phenomena (natural and engineered) that involve gene regulation. Biological signal processing can be achieved by way of allosteric transcription factors. In canonical regulatory systems (e.g., the lactose repressor), an INPUT signal results in the induction of a given transcription factor and objectively switches gene expression from an OFF state to an ON state. In such biological systems, to revert the gene expression back to the OFF state requires the aggressive dilution of the input signal, which can take 1 or more d to achieve in a typical biotic system. In this study, we present a class of engineered allosteric transcription factors capable of processing two-signal INPUTS, such that a sequence of INPUTS can rapidly transition gene expression between alternating OFF and ON states. Here, we present two fundamental biological signal processing filters, BANDPASS and BANDSTOP, that are regulated by D-fucose and isopropyl-β-D-1-thiogalactopyranoside. BANDPASS signal processing filters facilitate OFF–ON–OFF gene regulation. Whereas, BANDSTOP filters facilitate the antithetical gene regulation, ON–OFF–ON. Engineered signal processing filters can be directed to seven orthogonal promoters via adaptive modular DNA binding design. This collection of signal processing filters can be used in collaboration with our established transcriptional programming structure. Kinetic studies show that our collection of signal processing filters can switch between states of gene expression within a few minutes with minimal metabolic burden—representing a paradigm shift in general gene regulation.

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Engineered systems of inducible anti-repressors for the next generation of biological programming

Cited by 33 publications

References 60 publications

Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions

Coevolutionary methods enable robust design of modular repressors by reestablishing intra-protein interactions

Exploiting noise, non-linearity, and feedback for differential control of multiple synthetic cells with a single optogenetic input

Biological signal processing filters via engineering allosteric transcription factors

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