Team:ETHZ Basel/Modeling/Imaging

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Revision as of 11:23, 15 July 2010

Setup of the Microscope

A fluorescence microscope with motorized x, y and z control, a motorized shutter and a 60× lens is used with appropriate fluorescence filters for the fluorescence signals. Light-emitting diode arrays are installed as light sources for red light (660 nm) and far-red light (748 nm) pulses.

Control of the Microscope

The microscope is connected to a workstation using the core drivers and interfaces of μManager (see Stuurman et al. (2007) or [http://www.micro-manager.org]). To provide a mechanism to change the cell's input signal depending on its fluorescence signal, we developed the microscope software μPlateImager, which enables for parallel acquisition of images and the modification of light input signals. μPlateImager uses the Java interface of the μManager core to control the microscope and can be configured by a separate platform-independent visual user interface. μPlateImager uses the undocumented Java MATLAB Interface (JMI) to connect to Matlab (The MathWorks, Natick, MA) based on the open source project matlabcontrol (see [http://code.google.com/p/matlabcontrol/]). The microscope thus can be closely controlled by standard Matlab scripts.

Image Analysis and Model Simulation

Regularly, a Matlab script is executed by μPlateImager, which triggers the microscope to take an out-of-focus image. Afterwards, the script invokes the cell detection and tracking algorithm. By comparing the change in the position of the E. lemming over several consecutive images, the direction of the E. lemming is estimated. Based on the difference between the estimated direction and the reference direction set by the user, the Matlab script triggers either a red light (660nm), a far-red light (748nm) or no pulse (see description of the control algorithm) to induce or repress tumbling.

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 == Image Analysis and Model Simulation ==
-Regularly, a Matlab script is executed by $\mu$PlateImager for every well in the microplate, which triggers the microscope to take an out-of-focus and a fluorescence image with a respective filter (see Supplementary Information). Afterwards, the script invokes the cytometry software Cell-ID \cite{Chernomoretz2008,Gordon2007} to detect and track the cells, and to estimate their fluorescence signal. For every well, one cell is selected and its fluorescence signal is used as the input signal for the realtime simulation of the \textit{in silico} part of the biological network (see Section~\ref{section:methodDescription}) using the stiff ODE solver ode15s of Matlab. Based on the output, the Matlab script triggers either a red light ($\unit[660]{nm}$), a far-red light ($\unit[748]{nm}$) or no pulse in the respective well. The images made, the estimated cell positions and properties, the estimated fluorescence signal and the applied light impulse are stored for every well to enable cell tracking and later analysis.
+Regularly, a Matlab script is executed by &mu;PlateImager, which triggers the microscope to take an out-of-focus image. Afterwards, the script invokes the cell detection and tracking algorithm. By comparing the change in the position of the E. lemming over several consecutive images, the direction of the E. lemming is estimated.
+Based on the difference between the estimated direction and the reference direction set by the user, the Matlab script triggers either a red light (660nm), a far-red light (748nm) or no pulse (see description of the control algorithm) to induce or repress tumbling.