Summary

Emergence of complex patterns in nature is a fascinating and widely spread phenomenon, which is not fully understood yet. Mosaicoli aims to investigate emergence of complex patterns from a simple rule by engineering a cellular automaton into E. coli bacteria. This automaton comprises a grid of colonies on a 3D-printed millifluidic chip. Each colony is either in an ON or OFF state and updates its state by integrating signals from its neighbors according to a genetically pre-programmed logic rule. Complex patterns such as Sierpinski triangles are visualized by fluorescence after several steps of row-wise propagation. Sequential logic computation based on quorum sensing is challenged by leakiness and crosstalk present in biological systems. Mosaicoli overcomes these issues by exploiting multichannel orthogonal communication, riboregulators and integrase-based XOR logic gates. Engineering such a reliable system not only enables a better understanding of emergent patterns, but also provides novel building blocks for biological computers.

Background

Our project : Mosaicoli

Principle and Goals

The aim of our project is to investigate the emergence of complexity and how we can deal with it. Our project adresses this goal in two ways.

First, we follow a biomimetic approach, and reproduce emergent complex patterns inspired by those that we can observe in nature. This approach corresponds to the moto "What I cannot build, I cannot understand." We are inspired by Sierpinski triangle patterns present on sea snail shells, and engineer the same kind of emergent patterns on grids of bacterial colonies. These patterns are emergent because they arise directly from one logic gate implemented in the bacteria.

Two types of bacterial colonies are placed on a grid on a millifluidic chip, in an alternating way, as shown on this picture:

Every colony is either on an ON or OFF state. When a colony of type A is ON, bacteria from this colony express GFP and produce a signaling molecule A. When a colony of type B is ON, it also expresses GFP, and produces a signaling molecule B. At the beginning of the experiment, all colonies are OFF. We induces some of the colonies of the first line, they become ON. Every colony in the second line will update its state by computing an XOR gate of the states of the two colonies above it, by sensing signals it receives from these two colonies. Once the second line has updated its state, it will send signals to the third line which will also update its state. A pattern will thus propagate line by line until the whole chip displays a pattern.

This project that combines modeling and wet-lab work will enable us to answer some questions such as how complexity can emerge from simple rules, whether it can be predicted from simple rules, how we can deal with crosstalk and leakiness of biological systems to enable a good predictability.

Second, we widen the scope of our investigation to other projects and disciplines, from scientific fields to philosophy, sociology or art. We adress once more the issue of how to deal with complexity, by interviewing experts in several fields and gathering more massive responses with a survey. We want to investigate how people deal with complexity today. Do they consider that parts are strictly ordered, and try to reduce complexity to simple parts strictly following a set of deterministic rules, or do they accept that complexity comprises a mix of order and disorder, that a part of uncertainty can't be neglected and that complex systems should be studied as a whole ? Both approaches have their advantages and their disadvantages, which one should we choose to deal with the increasing complexity of our world ?

Implementation in E. coli

Biological tools: quorum sensing and integrases

Applications

alginate-microencapsulated implants^[1]

Multichannel orthogonal communication^[2]