IGEM:IMPERIAL/2006/BioSysBio Abstract Comments

Comments about the abstract

--Vincent 09:58, 21 September 2006 (EDT): Glad to see that someone has kicked-off the abstract. However, we should keep in mind that the abstract is some sort of teaser. We want people to get straight the main ideas and achievements about our project. We have to avoid to be too wordy. As a start, we should list all the results we plan to describe + all the stuff that makes our approach original. Any ideas ???

• Johnsy 08:43, 22 September 2006 (EDT): Oh...ok...I'll cut down on some of the bit and bobs. But can someone else please fill in the results stuff? Thanks...

• JohnChattaway 06:51, 23 September 2006 (EDT) the abstract should draw people onto our openwetware wiki rather than try to explain the whole project by itself.

• JohnChattaway 06:51, 23 September 2006 (EDT) if we mention any past work done by other people we have to reference it and the history of synthetic biological oscilators is actually quite long and goes back much futher than just ETH Zurich and MIT

Outline of the BioSysBio Abstract

Main ideas of the project:

• Design of a synthetic biological oscillator based on predator-prey dynamics and the Lotka Volterra population dynamics model (This is our idea and it is original!)
• Two-cell system
• Population-wide oscillations of the concentrations of the quorum sensing molecule AHL
• Approach to building the oscillator by creating the different components of the oscillator first and corresponding test constructs

Results obtained:

• Successfully built the prey and predator cells and their corresponding test contructs (At the time of the conference, can we expect to have the predator cell finished?)
• Prey cell characterized in DH5a – What can we mention about the results and their interpretation?
• Predator cell (growth and killing) characterized in DH5a (Can we include this in the abstract assuming we have done it – or should we rather list only the results that we have at the current state of our project?)
• Modelling: Lotka-Volterra & modelling the test constructs; learned about the behaviour of the system from the models
• Synthetic biological oscillator – summarize what we have achieved & how far we got during our project to implement the oscillator

References: (do we need to include references in the abstract – some abstracts from BioSysBio 2005 listed some references ?)

• MIT Registry

BioSysBio Abstract

Abstract - Version 3 by Christin 17:04, 28 September 2006 (EDT):

- Minor modification by chuehloo 09:01, 29 September 2006 (EDT)

Background
Oscillators are a fundamental building block in many engineering fields, as they provide the basis for counting, timing and synchronisation. Oscillators are found in many everyday devices such as clocks, computers or radios. Similarly, oscillations are an essential part of biological systems - providing the basis for, for example, rhythmic patterns and regulatory networks. The ability to build a stable, controllable biological oscillator would be a major step towards reliable synthetic biology based circuits. Elowitz et. al. were part of the first ones to try to build an oscillator. Their oscillator was based on genetic network at the single cell level. However, due to the stochastic behaviour inherent at the gene expression level, the oscillations were not stable or persistent(refs.). In this paper, we present an original oscillator design produced during the iGEM-2006 competition at Imperial College. The project addressed stability and reliability issues by defining an oscillator at the population level and by applying strict engineering rules to the system development process.

Methods

Fig. 1: Illustration of the Methodology

This iGEM project combined genetic engineering methods with a clearly defined development cycle, copied from the traditional engineering approach - a cycle of specification, design, modelling, testing and implementation - with biological processes to produce a synthetic biological oscillator.

The overall specification aim was to build a biological oscillator in E.Coli based on the Lotka-Volterra population dynamics. This approach was used to design a synthetic quorum sensing & quenching mechanism, made of BioBricks (design page). In order to satisfy the requirements for the Lotka-Volterra predator-prey dynamics BioBricks were constructed to show properties such as exponential growth of a prey molecule (Acyl Homoserine Lactone) (parts page). In order to reduce the complexity of the overall assembly, test constructs were built to characterise the different system components. Because the design comprises BioBricks in a two population system, the parameters of the oscillations can be controlled to achieve synchronised oscillations. Furthermore, since the system uses population wide oscillations, it enables other devices to synchronise the oscillator.

It is important to determine the component properties and their impact on the overall system. Hence, the modelling of the pure and modified Lotka-Volterra dynamics, along with the test constructs, were carried out. Because BioBricks were used in the design, the implementation was carried out with standard assembly. At the testing stage, the test constructs were characterised (protocols page). Consequently, the properties and constraints on the full system could be extracted. (See a summary of the method below.)

Results
BioBricks composing the test constructs and the final oscillator were engineered and a number of important results were extracted from the modelling and testing stages: i) The test constructs/BioBricks representing the different parts of the oscillator were characterised from testing in E.Coli (DH5α) (testing page). ii) The model of the test constructs, which included experimental data, predicted stable oscillations as output of the full system (modelling pages). iii) The influence of specific system parameters on the frequency, amplitude and stability of the oscillations was investigated with the Lotka-Volterra model (LV model).

Conclusion
In the project, fundamental units of the system were fabricated and characterised. These have been added to the Registry of Standard Biological Parts (Contributions page). The modelling exercise was highly successful and we fully expect to complete a stable synthetic biology based oscillator to be completed in the near future.

For full details visit our openwetware project site (OWW).

A Summary of Our Methods

SPECIFICATIONS
Fig. 2: Biological oscillator	Deliver a stable biological oscillator. Measurable output. Frequency and amplitude tunable. Produce documentation at each step for quality control and traceability purposes.
DESIGN
Fig. 3: Design showing the two-population system and the BioBricks within each cell	Based on Lotka-Volterra dynamic. Use of Quorum sensing-quenching BioBricks from MIT Registry. Population wide oscillations of AHL. Two cell population system defined to be able to tune frequency and amplitude. Definition of test constructs to break down complexity and to allow fine characterization.
MODELLING
Fig. 4: Full system model in cell designer and its output, showing oscillations	Test construct modelling. Investigation of the Lotka-Volterra dynamic. Full system modelling.
IMPLEMENTATION
Fig. 5: Overview of the ligations	Based on BioBricks. Use of the Standard Assembly. Quality control procedure based on sequencing.
TESTING-VALIDATION
Fig. 6: Representative testing result for one of the testing constructs	Definition of testing protocols to satisfy specifications. Characterisation of the different test construts. Characterisation of the two-cell population oscillator

Abstract - Version 2 by Christin 12:47, 26 September 2006 (EDT):

Oscillators are a vital building block for electronic devices like clocks, which have applications in vast fields of e.g. computer technology or electronic circuits. Likewise, oscillations are an essential part of biological systems providing the basis for e.g. rhythmic patterns and regulatory networks. However, due to the stochastic behaviour, producing stable oscillations from a synthetic biological oscillator, which would be the first step towards synthetic biological circuits, still provides a challenge nowadays (link to reference?).

This iGEM project uniquely combines engineering concepts with biological processes to implement a synthetic biological oscillator in E.Coli based on the Lotka-Volterra population dynamics model. In order to establish predator-prey dynamics according to the properties of the Lotka-Volterra model, the oscillator is designed to execute a synthetic quorum sensing & quenching mechanism. Because the design comprises BioBricks in a two-populations system, the parameters of the oscillations can be controlled. Synchronised oscillations of the concentration of the molecule Acyl Homoserine Lactone are generated within the whole population (design page).

The implementation of the system was approached as in engineering – however, facing a biological system: The engineering and analysing of the system components allowed determining their properties and thus their impact on the overall system. For this, test constructs representing the different parts of the oscillator were made using BioBricks and characteristics were extracted from testing in E.Coli (DH5α) (parts created). The model of these test constructs included experimental data and predicted stable oscillations as output of the full system (modelling pages). In addition, the influence of specific system parameters on the frequency, amplitude and stability of the oscillations was investigated with the Lotka-Volterra model (LV model). With this project, fundamental units of the system were fabricated and characterised, which promises the successful outcome of a stable synthetic biological oscillator.

For full details visit our openwetware project site (OWW).

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Abstract - Version 1 by Christin 16:53, 24 September 2006 (EDT):

__HIDER__ <hide> Oscillators are a vital building block for synchronization in a vast field of electronic devices like clocks. Likewise, oscillations are an essential part of biological systems providing the basis for e.g. rhythmic behaviour, regulatory networks. However, producing stable oscillations from a synthetic biological oscillator, which would be the first step towards synthetic biological circuits, still provides a challenge nowadays.

This iGEM project uniquely combines engineering concepts with biological processes to implement a synthetic biological oscillator in E.Coli based on the Lotka-Volterra population dynamics model. Applying a synthetic quorum sensing & quenching mechanism in a two-cell system, using BioBricks, establishes the predator-prey dynamics. Synchronised oscillations of the concentration of the molecule Acyl Homoserine Lactone are generated within the whole population in this design (design page).

To implement the system, BioBricks were engineered to provide test constructs. These were used to characterise the different components of the oscillator in E.coli (DH5α) (parts created). Modelling the test constructs, which included experimental data, predicted stable oscillations as output of the full system (modelling pages). In addition, the influence of specific system parameters on the frequency, amplitude and stability of the oscillations was investigated with the Lotka-Volterra model (LV model). This project has achieved to create and characterise the fundamental units of the system, which promises the successful outcome of a stable synthetic biological oscillator.

For full details visit our openwetware project site (OWW). </hide> </showhide>

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Abstract - Version by John C. (22 Sept 2006)

__HIDER__ <hide> Oscillators or clocks are a vital part of all electronic devices from computers to televisions they allow synchronisation of a system which prevents an overflow of information. Stable biological oscillators are a vital first step towards synthetic biological computers which can harness the massive parallel computing power inherent to biological systems. We have designed a synthetic biological oscillator which can be used in synthetic biological circuits.

It is based on predator prey dynamics and creates population wide synchronised oscillations of the concentration of an Acyl Homoserine Lactone molecule. The oscillations are driven by a synthetic quorum sensing / quenching mechanism which has been designed to behave in such a way that it fits the lotka volterra population dynamics model. The machinery is housed in two separate populations of cells which do not kill each other. Instead the cell density of the cell populations is proportional to parameters of the model such as the AHL production rate. Thereby altering the relative cell densities of the cells in our system allows us to tune the frequency and amplitude of the oscillations. This system works in mathematical models and we are currently trying to build it.

[For full details visit our openwetware project site] I recomend visiting the design pages for a more complete overview </hide> </showhide>

Abstract - Version by John S. (20 Sept 2006)

<showhide> __HIDER__ <hide>

Background/Introduction

Oscillators and oscillatory systems are ubiquitous in everyday life, from the alternating current electricity that we use to the circadian rhythms that control our sleep and wake cycle. Already, synthetic biology has begun to take on the challenge of creating the first biological computer, starting with ETH Zurich’s 2005 iGEM competition entry for creating a biological NOR logic gate and a two bit counter as well as Harvard’s BioWire design concept to transmit a signal down a length of bacteria. In computers, clocks are used to synchronise the components in order to prevent overflow of information within the system. On a broader scale, these clocks synchronise time around the world and are also used to determine the winner of eBay bids accurate to seconds, perhaps a more recognisable example to our modern life.

Why would we want to create a biological computer? Consider first the human brain, a complex network of cells intercommunicating to create our thoughts and conduct the human body symphoniously. If we can mimic this type of system in other non-neural type cells, we might be able to harness the massive scale parallel computing power inherent to biological systems.

Once we are able to create a biological oscillator, we can then move to synchronise several biological computers paving the way for an internet-like system controlled by bacteria. Further developments in biological to electrical interfacing could mean that communication between electrical devices and biological devices would be seamless. This can potentially integrate the existing infrastructure and novel biological approaches so the current technology would not be drastically displaced, but gradually replaced by biological machines. Moreover, the quest for self-reproducing machines has finally succeeded. Wouldn't it be great if our computers upgraded themselves? Made themselves faster every 30 mintutes? Genetically engineered bacteria indeed have this potential and are only limited by their lifespan and the biological reaction rates. Unfortunately, biological reaction rates are relatively slow when compared to electrical signals, but consider 100 years ago when we knew very little about electricity and how to harness the power of electricity. Biological engineering is at that stage now, and we cannot expect to surpass in a few years the engineering foundations that have been perfected throughout the ages.

Stable biological oscillations are seen to be produced with accuracy in predator-prey relationships, where we assume an exponential growth of prey and insatiable predators. The Lotka-Voltarra model for predator-prey interaction can be implemented given certain assumptions and given that we are able to find biological equivalents to predator and prey. Of course, a molecular predator-prey system would have different assumptions and thus different equations, but the fundamental predator-prey relationship can still hold. The assumptions and adaptations to the Lotka-Volterra system will be discussed further in the modelling document. Once we find molecules that can act similarly to predator-prey interactions, the next step is to successfully implement the system into bacteria!

Design of Biological Oscillator

Our design focused on implementing predator-prey molecular interactions into E. coli cells. In order to have population wide control and not just single cell oscillations, the team decided to use N-acyl homoserine lactone (AHL) synthesis and degradation pathways. The team wanted to mimic Lotka-Volterra interactions as much as possible so certain assumptions had to be taken into consideration. First, the L-V model assumes that there is an exponential increase in prey and that prey do not die on their own accord. Second, the predator must "eat" the prey and it's "productivity" is determined by how many prey it eats. Finally, the predator have a fixed death rate.

The first assumption was considered and implemented as a positive feedback loop to produce AHL in the "prey cell". A Lux R and a LuxI protein coding region was attached to a pLuxR promoter. Inherent noise in the system would cause both LuxR and LuxI to be produced. The LuxI would then catalyse AHL production leading, which would feed back into the system leading to an exponential increase of AHL. However, as biological resources are limited, the exponential increase eventually stops giving way to a steady state level of AHL. This is where AiiA, an AHL-lactonase and our predator molecule, has a pivotal role. AiiA will limit the amount of AHL in the cell by continuously "eating" the prey molecules, keeping the concentration of AHL away from steady state. However, before we implement the prey cell into our oscillator, we would like to exert some control in order to prevent the AHL concentration from reaching steady state prematurely. Several methods were devised. First, a RNA sequence called a riboswitch was designed such that the addition of theophylline would trigger the exponential feedback mechanism. The sequence coding for the riboswitch was placed in between the pLux promoter and the LuxR protein coding region, such that any leaky expression would produce the riboswitch and prevent further transcription from occuring. In its native state, the riboswitch sequence has a sticky end that will bind to the DNA sequence preventing it from being transcribed. Theophylline acts as an aptamer to change the conformation of the riboswitch, enabling the DNA sequence to be exposed, thus leading to protein expression. The second method of control was the Cre/Lox system, whereby non-coding regions of DNA were inserted in between the promoter and the protein coding region. Similar to the riboswitch, this prevents the transcription of DNA and maintains the baseline level of AHL. A second plasmid is inserted which codes for a specific restriction enzyme that will remove the non-coding region of DNA. This other plasmid is controlled by a LacI promoter, such that IPTG induction will cause its expression. This will result in the DNA being cleaved and subsequent protein expression. Also taken into consideration was the monocystronic versus polycistronic efficiency. Two test constructs were designed to investigate into which construct would provide the most exponential surge of AHL (to match as closely as possible to the Lotka-Volterra model).

But how is our predator production controlled? The team decided that a two cell system, one producing AHL and the other producing AiiA, would lead to the best population wide oscillations, perhaps also enabling control over the amplitude and frequency of the oscillations as well. As the AHL molecules are released into the surrounding solution, it is the signal by which the other cell knows to begin production of AiiA. In a population dynamics sense, the number of sheep (AHL) available will determine the growth of foxes (AiiA). Thus, our design contained LuxR and AiiA protein coding regions regulated by a pLuxR promoter. Again, the team hoped that leaky expression of LuxR would enable the feedback mechanism to start working once AHL was introduced into the system from the prey cells.

According to the extensive modelling and the similarities between the biological oscillator and the Lotka-Volterra model, a sinusoidal theoretical output was predicted that would continue for more than 10 oscillations. Moreover, by changing certain key parameters, the frequency and amplitude could easily be changed. However, tweaking biological parameters in living systems has posed a serious problem, and should be the investigation of a future project. </hide> </showhide>