Team:ETH Zurich/project/overview

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==Summary==
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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.
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== Background ==
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== Our project : Mosaicoli ==
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=== Principle and Goals ===
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== Implementation in ''E. coli'' ==
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Here you can see our circuit in action. More details on how it works are <html> <a class="circled scrolly" href="#implementation"> just below</a></html>. For a comprehensive inventory of all parts used, you can check our [https://2014.igem.org/Team:ETH_Zurich/data Data page].
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<div id="bloc1" style='margin-left:3em;'><h3 style='font-weight:800;'> Choose the cell type and the inputs:</h3></html>
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<h3 style='text-align:center; font-weight:800;'>See how the information is processed to get the right output : </h3>
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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.
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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.
 
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Two types of bacterial colonies are placed on a grid on a millifluidic chip, in an alternating way, as shown on this picture:
 
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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.
 
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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.
 
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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 ?
 
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=== Implementation in ''E. coli'' ===
 
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Mosai''coli'' involves three main constructs per cell, one for quorum sensing, one for production of integrases, and the last with the integrase based XOR logic gate to perform computation. Each cell can receive two orthogonal AHLs - the RhlI and LuxI products.  The rhl-AHL or the lux-AHL received by the cell bind to their corresponding repressors RhlR and LuxR, thus freeing the promoters PRhl and PLux on the second plasmid respectively. Upon activation the promoters express the two integrases phiC31 and Bxb1 respectively.
 
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The XOR gate present on the third plasmid comprises an asymmetric transcription terminator flanked by two pairs of opposing recombination sites recognised by phiC31 and Bxb1 respectively.  In the absence of both integrases, the terminator blocks transcription. Expression of either integrase alone inverts the DNA encoding the terminator and allows transcription of LuxI (or RhlI) and GFP. Presence of both integrases inverts the terminator twice bringing it back to original orientation of the terminator blocking transcription. {reference Bonnet} We intend to use riboswitches to reduce leakiness. {reference}
 
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Colonies of such cells are placed in a grid in a 3D-printed millifluidic chip. Each colony can exist in one of two states - ON and OFF. The cells are OFF if they do not produce any GFP and LuxI (or RhlI) and ON when they produce GFP and LuxI (or RhlI). The LuxI or RhlI expressed catalyse the production of the corresponding AHL molecules which are propagated to the colonies in the next row. Each colony updates its state by integrating signals from its neighbours (colonies in the previous rows). We expect to see complex fluorescent patterns, such as the Sierpinski triangles after several rows of colonies on the grid have updated their states.
 
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=== Biological tools: quorum sensing and integrases ===
 
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== Applications and Outlook ==
 
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Future development of synthetic biological systems will require the implementation of reliable synthetic circuits. These gene circuits will be designed to program new biological behaviour, dynamics and logic control.<sup>[[#refWeiss|[1]]]</sup> A crucial part to coordinate and control the biological computation needed to perform their tasks can be seen in multichannel orthogonal communication. In order to achieve the goals of our project we need to thoroughly characterize available components, improve their performance, and develop novel constructs that get closer to actual multichannel orthogonal communication and subsequent logic processing. With our findings we will try to make a contribution to the field of biological computation by enabling further development of complex systems that rely on the interaction between its subparts.
 
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These biological computers in turn also need to find a way to be implemented in patients, if they are developed to perform therapeutic tasks. A promising application of such synthetic biological systems is cell based therapy by alginate-microencapsulated implants.<sup>[[#refAuslander|[2]]]</sup> We will try to achieve communication and input integration in a grid of alginate beads and thus producing a more complex behavior than a single bead could show. This can be seen as a step towards the development of artificial organs composed of multiple alginate-microencapsulated implants that work together to tackle tasks a single implant, which is not communicating with its neighbors, could not solve.
 
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== ==
 
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<div id="refWeiss" align="left">[1] [http://dx.doi.org/10.1038/nrg3227 Adrian L. Slusarczyk, Allen Lin & Ron Weiss, Foundations for the design and implementation of synthetic genetic circuits, Nature Reviews Genetics, 13, 2012]</div>
 
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<div id="refAuslander" align="left">[2] [http://dx.doi.org/10.1016/j.molcel.2014.06.007 D. Ausländer ''et al''.,  A Synthetic Multifunctional Mammalian pH Sensor and CO<sub>2</sub> Transgene-Control Device, Molecular Cell, 55, 2014]</div>
 
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Latest revision as of 01:33, 18 October 2014

iGEM ETH Zurich 2014

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