Introduction

1, 2, 3, ... not as easy as you might think!

The ability to count might appear as an easy task at first sight. But just hold on for a minute and think about what you are actually doing while you are counting.
Let's assume you are counting the red traffic lights you encounter while being already late for work. First, you have to be able to perceive the red light. The light signal your eyes receive will be processed and you will count to ‘one’ in your mind. Already at this point it is becoming tricky. Imagine, the traffic light will be red for five minutes. Even when you are waiting in front of the traffic light for three minutes (while getting more, and more stressed…) it will still be the first one you encountered today. This means, you have to be able to remember and recognize the traffic light as the first one, even after stearing at it for several minutes. Now, the traffic light switches to green, you drive on, but, importantly, you have to keep in mind, that you already encountered one red traffic light today! When you reach the next crossing with a red traffic light, you will process the signal again, and this time count ‘two’.
However, we are human beings with highly developed sensory organs whose received signals are processed with the help of billions of neurons. With our project, we want to face the challenge to enable an one-cellular organism to perform this highly complex task.
From the example above it became clear, that counting requires several working elements (see also [http://www.ncbi.nlm.nih.gov/pubmed?term=Smolke%20DNA%20that%20counts%20science (1)]):

• A signal detector and processor.
• A time delay mechanism, to extend the time between signal detection and output generation, to make it longer than the signal duration. This element substitutes in some sense our ability to distinguish between the different input signal, e.g. remembering the first red traffic light as the first input signal, no matter how long it will stay red.
• A memory unit that will store the information about how many signals the system has received already.

whatever you want to count. Second, and now its getting more complicated, you have to process the signal. Let's assume you are human, so - after receiving the first signal - you say "one".
===Already existing synthetic

Meaning, either you have to able to remember and recognize the traffic light as the first one, even after stearing at it for three minutes, or, your ‘process of counting’ has to be slower than the maximal duration the traffic light can remain red.

The aim of our project is to design a genetic device working in E.coli able to count and memorize the occurrences of an input signal. This functionality is achieved by utilization of auto-inducing loops, that act as memory units, and an engineered riboregulator, acting as an AND gate. Each increase of the counter will result in a different state of the system that will subsequently lead to a defined output signal.

The design of the device is modular. This means, that both input and output signals can be changed freely, without disturbing the functionality of the memory system. Also, the design allows implementation of any number of memory units, as the AND gate design enables to extend the system in a hassle-free way.Therefore possible applications of our system range from a memory system of a Turing complete machine, through bacteria used as biosensors measuring the number of occurrences of an event in a process, to bacteria that can perform multi-step bioconversions sequentially all by themselves and without the need of changing them to another strain.

Our research is strongly dependent on modelling support. We have created a genetic algorithm that will enable us to predict and calculate parameters of the parts used in the design. The framework of the model will be made usable for other researchers via a cloud-based application. We have also generated a bi-stability model, that furthermore includes predictions about the stability of information stored in the bi-stable switches.