Distributed Implementation of Boolean Functions by Transcriptional Synthetic Circuits

Abstract

Starting in the early 2000s, a sophisticated technology has been developed for the rational construction of synthetic genetic networks that implement specified logical functionalities. Despite impressive progress, however, the scaling necessary in order to achieve greater computational power has been hampered by many constraints, including repressor toxicity and the lack of large sets of mutually-orthogonal repressors. As a consequence, a typical circuit contains no more than roughly seven repressor-based gates per cell. A possible way around this scalability problem is to distribute the computation among multiple cell types, which communicate among themselves using diffusible small molecules (DSMs) and each of which implements a small sub-circuit. Examples of DSMs are those employed by quorum sensing systems in bacteria. This paper focuses on systematic ways to implement this distributed approach, in the context of the evaluation of arbitrary Boolean functions.The unique characteristics of genetic circuits and the properties of DSMs require the development of new Boolean synthesis methods, distinct from those classically used in electronic circuit design. In this work, we propose a fast algorithm to synthesize distributed realizations for any Boolean function, under constraints on the number of gates per cell and the number of orthogonal DSMs. The method is based on an exact synthesis algorithm to find the minimal circuit per cell, which in turn allows us to build an extensive database of Boolean functions up to a given number of inputs.

Context-Dependent Stability and Robustness of Genetic Toggle Switches with Leaky Promoters

“…Crucially, these results are directly translatable to experimental considerations due to the mechanistic model underpinning our results: e.g., α can be tuned via RBS engineering [51], β via the introduction of decoy sites [59], ν via promoter engineering [52], and β c via the expression of heterologous proteins [15,16]. Our findings complement recent efforts by mitigating the adverse effects of competition for shared cellular resources, for instance, by employing orthogonal resource pools [62,82,83], by relying on control theoretic strategies [84][85][86], and by splitting up multi-component genetic systems into smaller subcomponents distributed among multiple collaborative cell strains [87].…”

A synthetic distributed genetic multi-bit counter

“…However, it critically relies on high expression levels of Cas9 which is toxic to the host cells ( Zhang and Voigt, 2018 ). Hence, adopting new principles and new synthetic architectures like distributed computation have also been widely discussed ( Xiang et al., 2018 ; Karkaria et al., 2020 ; Al- Radhawi et al., 2020 ). Similarly, our approach for designing a multi-bit counter system tries to solve scalability issues via distributed computation using cell-cell communication.…”

“…To avoid this issue, we base our design on distributed computation, with specialized cell types allocated to specific tasks, such as the computation of carry bits. This is an approach that we have also proposed for designing large classes of Boolean functions ( Al-Radhawi et al., 2020 ). The communication between the different types of cells can be in principle implemented by diffusible small molecules such as quorum-sensing molecules.…”

From Microbial Communities to Distributed Computing Systems

“…The output was also distributed across multiple cell types, helping to reduce wiring requirements and enabling the construction of all the two input logic gates, multiplexer and 1-bit adder with carry ( Regot et al, 2011 ). Mathematical work into the optimal design of computational communities implementing distributed genetic logic gates given realistic constraints on the number of logic gates possible per cell and the number of orthogonal quorum molecules has been done ( Al-Radhawi et al, 2020 ). It was found that under the assumption that any cell is limited to a maximum of seven logic gates the use of a community composed of two cell types increased the number of logic gates by 7.58-fold over the capabilities of a monoculture.…”

“…Interestingly, when optimizing for the communication constraints within a microbial community using quorum sensing, a high number of non-standard logic gates (NIMPLIES, NOT, and AND) are selected, highlighting the differences between electrical and biological computing. The optimal design of computational communities will require new tools, such as an algorithm to distribute genetic NOR gates among cell populations communicating via diffusible molecules ( Al-Radhawi et al, 2020 ).…”