The state trajectory of cell


T. Náhlík


Institute of Physical Biology, University of Southern Bohemia in České Budějovice


Cells are living unrepeatable objects. If we want to know how they are living and evolving in time we cannot do it through invasive techniques, which modify or kill the cell. In non-invasive techniques, the content of the data is given and we have to maximize information gain. We extract from the dataset by information entropy approach. A general image, acquired by any generic microscopic techniques, is subjected to transformation which evaluates the information contribution of each point in the image. Resulting values may also be used for construction of the cell or, differently said, to objective assessment of individual cell state.

As model example we used the Belousov – Zhabotinsky reaction. The 3D plot of red vs. green vs. blue channel shows that individual attractors may be discriminated and that many state trajectories may be constructed using different entropies. The color channels and different Rényi entropy coefficients may be combined to best discriminate individual states.  The same approach we use for state analysis of cells. S. cerevisiae cell was observed using video enhanced microscopy in brightfield regime. Resulting images are grayscale. We segmented the histogram and to each part we assigned different colors. By this transformation individual features in the cell were significantly better visible then in original and state trajectory may be plotted. We used this approach also for analysis of coloured, phase contrast image of HeLa and MG63 cells. Here, more channels with significantly different information content are obtained and for the construction of the state trajectory are more possibilities. The question remains whether discriminateable parts of the cell – organelles etc. - are subsystems of   the cell and should be assigned their own state trajectories or whether the cell is the elementary system. To prove this idea, we separated only one organelle from the image of whole cell and try to plot the state trajectory. The question could not be unanimously answered at state of the art of the method.

There are mainly technical limits to the identification of the state trajectory given by instrument time and dynamical resolution, information channel properties etc.  So we are able to construct state trajectories only for simple objects and simple cells identified manually. The progress in developing methods of automated cell and cell feature extraction is reported