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Contents 1 Team Members 2 Introduction to Synthetic Biology 3 Choosing the Project 3.1 Step 1: Brainstorming 3.2 Step 2: Preferred Projects 4 The Project 4.1 System Models 4.2 Simulations 4.3 Sensitivity Analysis 5 Lab Work 5.1 Cloning Plan 5.2 Lab Notes

Team Members

For the International Competition on Genetically Engineered Machines, the teams should be composed of both biologist and engineers. That way, the engineers will try to develop new systems in a bottom-up fashion and run numerical simulations, while the biologists will be able to assess the feasibility of such systems, and construct them from biological parts.

Instructors:

Sven Panke

Joerg Stelling

Students:

Martin Brutsche

Katerina Dikaiou

Raphael Guebeli

Sylke Hoehnel

Nan Li

Stefan Luzi

Graduate Students:

Christos Bergeles

Tim Hohm

Christian Kemmer

Joseph Knight

Markus Uhr

Introduction to Synthetic Biology

In order to get an initial understanding of the concepts of synthetic biology, we read and presented publications on various topics. A representative list of the topics that we examined on this “boot-camp”, can be found below, together with their respective presentations.

Choosing the Project

Step 1: Brainstorming

Initially, we wanted to come up with as many ideas as possible, in order to be able to choose among them the best, and find a cool project to carry out. For this reason, we had brainstorming sessions. We split up in three teams, and each team tried to come up with many fancy and showy ideas, which was facilitated by keeping in mind the following brainstorming guidelines:

1. Defer judgment - the rules of nature don't apply
2. Encourage wild ideas
3. Build on the ideas of others
4. Be visual
5. Go for quantity
6. Stay focused on topic

The ideas that we came up with, as were presented in the following meetings, were:

• PID Controller: Design a PID controller out of biological elements. The P component can be a simple

output to a regulatory protein, and the I component can be the overall protein production at a time period. What can the D component be?

• Motion Detector: Cells are grown on a petri dish. Below the dish, moving images are displayed. A 3-

state automaton is proposed. Output A is created when light is present. Output B is created when light is absent. Moving patterns will cause some cells to create both outputs over time. This will result in some “inspector” cells producing output C, by collecting outputs A and B.

• Analog-to-Digital Converter: Compare the level of protein concentration with thresholds, and digitize

the output.

• Neural Network: Create a sort of biological neural network with bacteria. We should address the issue

of learning, and find a way to incorporate the feedback in the cell decision making process. Directed evolution can be a sort of feedback, but we want to avoid this. (This idea was the basis for the “learning project”)

• Central Pattern Generation: Coordinate two oscillators, so that they are in phase. This can be achieved

through diffusion between the different cell types. (This idea was the basis for the “spatial oscillations project”).

• Paramedic Cells: Some cells are able to detect signals coming from other cells, and create food for

them, or create proteins in order to save them and make them function better.

• Cell Batteries: Cells are able to create and store large quantities of ATP, during a “storing process”.

Afterwards, they can detect a signal and give back all the energy they stored, in a short burst, like a capacitor. Other ideas are that the cells can “blow up” and emit large amounts of GFP, based on the ATP that they have accumulated.

• Flashing Bacteria: Cells are grown on a light pattern. The cells that are on the bright parts of the

image are oscillating in phase, while the others are remaining dark. This results in the observation of a flashing pattern.

• Biocam: Visible to Fluorescent light converter.
• BioCD: “Print” cells on a film, then read them out and “reconstruct” the original data. Basically, it is

an analog to digital converter, followed by a system that can interpret the digitized data. (This idea was the basis for the “Music of life project”, where cells would produce fluorescent proteins based on an analog input. Then, the amount and type of fluorescence would code some music).

• Clock: A follow-the-leader system. We have to groups of cells. The first group creates something that

repels the second group. The second group creates a protein that attracts the first group. This way, they first group wants to “catch” the second group, whereas the second group wants to “avoid” the first group. This results in them moving around. We can say that the second group is the leader, and the first group exhibits a “follow-the-leader” behavior.

• Sensors: Various systems that can sense PH, pressure, temperature, meat quality, moisture e.t.c have

been proposed.

Step 2: Preferred Projects

We decided that three of the above ideas were worth a deeper examination. Namely, we split again in three teams, so that we can come up with an initial system, with remarks on its feasibility and coolness. Our results were presented on all the team members, so that we could then limit the potential projects down to two and one, and proceed with constructing the DNA sequence. The three projects and the presentations that we did were:

1. Spatial Oscillations: Should I put something here?
2. Music of Life: The basic idea is that instead of having an analog-to-digital converter with four outputs -three fluorescent proteins, and no output-, we can have two switches. When switch A is on, RFP is produced. When switch B is on, GFP is produced. When both switches A and B are on, a yellowish output is observed. By recording these outputs, we can later create music, by assigning each fluorescent protein to a chord. For example, RFP would correspond to a G chord. The strength of the fluorescence can signify the strength of the chord. If the cells are placed on a spinning disk, we can have something like a vinyl player. A camera is observing the cells, and created music on the fly.
3. Learning: Based on the idea of the neural network, we want to create a biological system, where the cells can learn a specific behavior. In order to simplify the system, we decided that the cells can learn to recognize a specific type of other cells. We divide the process in a learning phase, and a recognition phase. First, cells A are put together with cells B. Then, cells A are “learning” to recognize cells B. If afterwards they are put in a petri dish with cells B, they will emit GPF. Otherwise, they will stay dark.

We decided that ideas one and three were worth further exploration. Idea two, even though it was fancy, it was fairly simple, as, creating two switches is a straightforward and well understood process. As a result, it was discarded. We could try to make the system more complex, but making something more complex just for the shake of it, is not a good engineering approach ;)

The Project

We decided to proceed with the Learning Project. Our goal is to design an E.coli strain, able to distinguish between two chemical substances after an assigned learning process, induced by an external chemical signal. After the bacterial strain was taken to a testing phase, the output will result in either yellow or cyan fluorescence, depending on whether the bacteria recognized the same chemical substance in the testing phase as it was trained in the learning phase or a different one. We aim to implement our system using a toggle switch consisting of different repressor and activator proteins coupled with double regulatory regions.

System Models

Simulations

Sensitivity Analysis

Lab Work

Here we can write when each one will be available. For example:

• Christos: Can be available everyday after 17:30, till 00:00. Weekends as well. If that is not possible, I will take days off, one per week, to work in the lab (if supervisor agrees, that is...)

Cloning Plan

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Lab Notes

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Week 1       06.08.07 - 12.08.07
detailed lab notes
Week 2       13.08.07 - 19.08.07
detailed lab notes
Week 3       20.08.07 - 26.08.07
detailed lab notes
Week 4       27.08.07 - 02.09.07
detailed lab notes