From 2010.igem.org

Information Processing Overview

Information processing principle of E. lemming. Tumbling / directed movement rates are monitored by image processing algorithms, which are linked to the light-pulse generator. Therefore, E. coli tumbling is induced or suppressed simply by pressing a light switch! This synthetic network enables control of single E. lemming cells.

The two key players in our information processing approach. The microscope (upper figure) is used for imaging the cell and the joystick (lower figure) is used for defining E. lemming's reference direction.

Although the synthetic network we implemented makes the tumbling frequency of E. coli cells dependent on red and far-red light, the biological part alone is not sufficient to control the swimming direction of E. lemming. Thus, it is complemented by a complex in silico network centered around a controller which guides the cell towards the desired destination.

E. Lemming cells are imaged using microscopy techniques. The resulting images are processed by fast cell detection and cell tracking algorithms, which determine the actual movement direction of the chosen bacterium. The desired reference direction is visualized and set by the input of the user, which is translated by the the controller algorithm into series of light pulses (red light and far-red light) . Therefore, by time-dependently changing the tumbling frequency, the cell is forced to swim in a desired direction in real time.

Microscopy

The cells are placed in a 50 μm high flow channel restricting their movement to the x/y-plane, thus preventing them from swimming out of focus. They are imaged by an automated microscope in bright field with 40x magnification approximately every 0.3s.

Information Flow

The image from the microscope is acquired by an opensource microscopy software and sent via a local network or internet to the controller workstation, which processes the data with the E. lemming Matlab / Simulink Toolbox. This information flow approach enables rapid and automated control of E. lemming.

Cell Detection

In the controller workstation, the images are pre-processed by the Matlab Toolbox and the cells are detected and tracked in real-time, by means of fast image processing algorithms developed by our team. From the change of position between the microscope frames, the current direction of E.lemming is estimated.

Visualization

The Toolbox is connected to either a joystick or a keyboard with which the user can choose the cell he/she wants to control and interactively change the reference direction for the E.lemming in real time. Finally, the microscope image is post-processed to show the position of all cells, the selected cell and its current and reference direction, and visualized on the computer screen or with a beamer. The section on visualization offers more information how this has been accomplished.

Controller

To control E. lemming, the modeling subteam implemented five different control algorithms, based on the same template. The current direction of E. lemming, together with the desired direction set by the user and the time-point of the simulation form the inputs of the algorithms, while boolean values for red light and far-red light represent the outputs. Furthermore the controller detects if a cell is swimming out of the field of vision of the microscope and automatically adjusts the position of the x/y-stage.

E. lemming Game

To demonstrate the capabilities of the comprehensive information processing approach, a simple game was implemented, which uses E. coli microscopy images and applies the visualization approach to create the
E. lemming Game. Please notice, that this is not the main goal of the E. lemming project, but a sidekick to illustrate further applications of the information processing pipeline.