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Gary Harkin

Publications and source records attributed to Gary Harkin.

3 recordsLinked to original sources

Three-dimensional biofilm structure quantification.

Quantitative parameters describing biofilm physical structure have been extracted from three-dimensional confocal laser scanning microscopy images and used to compare biofilm structures, monitor biofilm development, and quantify environmental factors affecting biofilm structure. Researchers have previously used biovolume, volume to surface ratio, roughness coefficient, and mean and maximum thicknesses to compare biofilm structures. The selection of these parameters is dependent on the availability of software to perform calculations. We believe it is necessary to develop more comprehensive parameters to describe heterogeneous biofilm morphology in three dimensions. This research presents parameters describing three-dimensional biofilm heterogeneity, size, and morphology of biomass calculated from confocal laser scanning microscopy images. This study extends previous work which extracted quantitative parameters regarding morphological features from two-dimensional biofilm images to three-dimensional biofilm images. We describe two types of parameters: (1) textural parameters showing microscale heterogeneity of biofilms and (2) volumetric parameters describing size and morphology of biomass. The three-dimensional features presented are average (ADD) and maximum diffusion distances (MDD), fractal dimension, average run lengths (in X, Y and Z directions), aspect ratio, textural entropy, energy and homogeneity. We discuss the meaning of each parameter and present the calculations in detail. The developed algorithms, including automatic thresholding, are implemented in software as MATLAB programs which will be available at site prior to publication of the paper.

Algorithms↗

Quantifying biofilm structure: facts and fiction.

There is no doubt among biofilm researchers that biofilm structure is important to many biofilm processes, such as the transport of nutrients to deeper layers of the biofilm. However, biofilm structure is an elusive term understood only qualitatively, and as such it cannot be directly correlated with any measurable parameters characterizing biofilm performance. To correlate biofilm structure with the parameters characterizing biofilm performance, such as the rate of nutrient transport within the space occupied by the biofilms, biofilm structure must first be quantified and expressed numerically on an appropriate scale. The task of extracting numerical parameters quantifying biofilm structure relies on using biofilm imaging and image analysis. Although defining parameters characterizing biofilm structure is relatively straightforward, and multiple parameters have been described in the computer science literature, interpreting the results of such analyses is not trivial. Existing computer software developed by several research groups, including ours, for the sole purpose of analyzing biofilm images helps quantify parameters from biofilm images but does nothing to help interpret the results of such analyses. Although computing structural parameters from biofilm images permits correlating biofilm structure with other biofilm processes, the meaning of the results is not obvious. The first step to understanding the quantification of biofilm structure, developing image analysis, methods to quantify information from biofilm images, has been made by several research groups. The next step is to explain the meaning of these analyses. This presentation explains the meaning of several parameters commonly used to characterize biofilm structure. It also reviews the authors' research and experience in quantifying biofilm structure and their attempts to quantitatively relate biofilm structure to fundamental biofilm processes.

Anti-Bacterial Agents↗

A computer investigation of chemically mediated detachment in bacterial biofilms.

A three-dimensional computer model was used to evaluate the effect of chemically mediated detachment on biofilm development in a negligible-shear environment. The model, BacLAB, combines conventional diffusion-reaction equations for chemicals with a cellular automata algorithm to simulate bacterial growth, movement and detachment. BacLAB simulates the life cycle of a bacterial biofilm from its initial colonization of a surface to the development of a mature biofilm with cell areal densities comparable to those in the laboratory. A base model founded on well established transport equations that are easily adaptable to investigate conjectures at the biological level has been created. In this study, the conjecture of a detachment mechanism involving a bacterially produced chemical detachment factor in which high local concentrations of this detachment factor cause the bacteria to detach from the biofilm was examined. The results show that the often observed 'mushroom'-shaped structure can occur if detachment events create voids so that the remaining attached cells look like mushrooms.

Algorithms↗