Multicellular Computing Using Conjugation for Wiring

Abstract

Recent efforts in synthetic biology have focussed on the implementation of logical functions within living cells. One aim is to facilitate both internal “re-programming” and external control of cells, with potential applications in a wide range of domains. However, fundamental limitations on the degree to which single cells may be re-engineered have led to a growth of interest in multicellular systems, in which a “computation” is distributed over a number of different cell types, in a manner analogous to modern computer networks. Within this model, individual cell type perform specific sub-tasks, the results of which are then communicated to other cell types for further processing. The manner in which outputs are communicated is therefore of great significance to the overall success of such a scheme. Previous experiments in distributed cellular computation have used global communication schemes, such as quorum sensing (QS), to implement the “wiring” between cell types. While useful, this method lacks specificity, and limits the amount of information that may be transferred at any one time. We propose an alternative scheme, based on specific cell-cell conjugation. This mechanism allows for the direct transfer of genetic information between bacteria, via circular DNA strands known as plasmids. We design a multi-cellular population that is able to compute, in a distributed fashion, a Boolean XOR function. Through this, we describe a general scheme for distributed logic that works by mixing different strains in a single population; this constitutes an important advantage of our novel approach. Importantly, the amount of genetic information exchanged through conjugation is significantly higher than the amount possible through QS-based communication. We provide full computational modelling and simulation results, using deterministic, stochastic and spatially-explicit methods. These simulations explore the behaviour of one possible conjugation-wired cellular computing system under different conditions, and provide baseline information for future laboratory implementations.

Agent-based modelling in synthetic biology

“…These limitations make such a method unsuitable for systems requiring a short response time. To alleviate this problem, engineered bacteria have also been designed using agent-based models to perform similar functions exploiting conjugation as a quicker means of direct cell-to-cell communication [40]. …”

Bacterial computing with engineered populations

“…In figure 2 (top), we see the results of another simulation, this time for the NAND case, in which we can clearly see that the only quadrant in which the cells are not 'on' is (correctly) the one in which both inputs are equal to 1. Figure 4 (adapted from [53]) shows a similar multicellular simulation of a distributed XOR gate (comparator). This implementation does use conjugation, which facilitates direct cell-cell transfer of genetic information.…”

Mining Environmental Plasmids for Synthetic Biology Parts and Devices

“…However, conjugation has been exploited in synthetic biology not only for the sake of using its functional parts, but also as a phenomenon that can be utilized for biological computing and digital cell-to-cell communication (94). One can see DNA transfer as a scenario where individual bacterial types perform specific subtasks, the results of which are then communicated to other cell types for further processing.…”

“…Models predict this approach to be more powerful than other biological computation approaches using, e.g., quorum sensing. A conjugation-wired computing system could thus become a realistic methodology to implement newto-nature properties in biological systems (94).…”