Filamentous fungal colonies show a remarkable diversity of different mycelial branching patterns. To date, the characterization of this biostructural complexity has been based on subjective descriptions. Here, computerized image analysis in conjunction with video microscopy has been used to quantify several aspects of fungal growth and differentiation. This was accomplished by applying the new branch of mathematics called Fractal Geometry to this biological system, to provide an objective description of morphological and biochemical complexity. The fractal dimension is useful for describing irregularity and shape complexity in systems that appear to display scaling correlations (between structural units) over several orders of length or size. The branching dynamics of Pycnoporus cinnabarinus have been evaluated using fractals in order to determine whether there was a correlation between branching complexity and the amount of extracellular phenol-oxidase that accumulated during growth.
A non-linear branching response was observed when colonies were grown in the presence of the aminoanthraquinone dye, Remazol Brilliant Blue R. Branching complexity could be used to predict the generalized yield of phenol-oxidase that
accumulated in submerged culture, or identify paramorphogens that could be used to improve yield. A method to optimize growth of discrete fungal colonies for microscopy and image analysis on microporous membranes revealed secretion sites of the phenoloxidase, laccase as well as the intracellular enzyme, acid phosphatase. This method was further improved using microwave-accelerated heating to detect tip and sheath bound enzyme.
The spatial deposition of secreted laccase and acid phosphatase displayed antipersistent scaling in deposition and/or secretion pattern. To overcome inherent statistical limitations of existing methods, a new signal processing tool, called wavelets were applied to analyze both one and two-dimensional data to measure fractal scaling. Two-dimensional wavelet packet analysis (2-d WPA) measured the (i) mass fractal dimension of binary images, or the (ii) self-affine dimension of grey-scale images. Both 1- and 2-d WPA showed comparative accuracy with existing methods yet offered improvements in computational efficiency that were inherent with this multiresolution technique.
The fractal dimension was shown to be a sensitive indicator of shape complexity. The discovery of power law scaling was a hallmark of fractal geometry and in many cases returned values that were indicative of a self-organized critical state. This meant that the dynamics of fungal colony branching equilibrium. Hence there was potential for biostructural changes of all sizes, which would allow the system to efficiently adapt to environmental change at both the macro and micro levels.
| Identifer | oai:union.ndltd.org:ADTP/216524 |
| Date | January 1997 |
| Creators | Jones, Cameron Lawrence, cajones@swin.edu.au |
| Publisher | Swinburne University of Technology. |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | http://www.swin.edu.au/), Copyright Cameron Lawrence Jones |
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