Browsing by Author "Harkin, Gary"

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Analysis of bacterial spatial patterns at the initial stage of biofilm formation
(1995) Hamilton, Martin A.; Johnson, K. R.; Camper, Anne K.; Stoodley, Paul; Harkin, Gary; Gillis, Richard J.; Shope, Paul A.
Assessing technician effects when extracting quantities from microscope images
(2003-04) Webb, D.; Hamilton, Martin A.; Harkin, Gary; Lawrence, S.; Camper, Anne K.; Lewandowski, Zbigniew
Consider an experiment where the response is based on an image; e.g., an image captured to a computer file by a digital camera mounted on a microscope. Suppose relevant quantitative measures are extracted from the images so that results can be analyzed by conventional statistical methods. The steps involved in extracting the measures may require that the technicians, who are processing the images, perform some subjective manipulations. In this case, it is important to determine the bias and variability, if any, attributable to the technicians' decisions. This paper describes the experimental design and statistical analyses that are useful for those determinations. The design and analysis are illustrated by application to two biofilm research projects that involved quantitative image analysis. In one investigation, the technician was required to choose a threshold level, then the image analysis program automatically extracted relevant measures from the resulting black and white image. In the other investigation, the technician was required to choose fiducial points in each of two images collected on different microscopes; then the image analysis program registered the images by stretching, rotating, and overlaying them, so that their quantitative features could be correlated. These investigations elucidated the effects of the technicians' decisions, thereby helping us to assess properly the statistical uncertainties in the conclusions for the primary experiments.
Author's response
(2002-02) Lewandowski, Zbigniew; Harkin, Gary; Beyenal, Haluk
Bacterial colonization of surfaces in flowing systems: methods and analysis
(1994) Camper, Anne K.; Hamilton, Martin A.; Johnson, K. R.; Stoodley, Paul; Harkin, Gary; Daly, Don Simone
Chemical effects of biofilm colonization on 304 stainless steel
(1996-05) Pendyala, Jyostna; Avci, Recep; Geesey, Gill G.; Stoodley, Paul; Hamilton, Martin A.; Harkin, Gary
Changes in the surface concentrations of the main alloying elements of an as‐received 304 stainless steel, exposed to a mixed culture of biofilm‐forming bacteria under flowing conditions, were observed using Auger electron spectroscopy. In the oxide film close to the bulk stainless steel, there was an enrichment in the relative concentration of Cr with a corresponding decrease in the relative Fe concentration as compared to a control coupon exposed only to sterile media. There were no changes observed in the relative Ni concentration.
A computer investigation of chemically mediated detachment in bacterial biofilms
(2003-05) Hunt, Stephen Michael; Hamilton, Martin A.; Sears, Joe; Harkin, Gary; Reno, Jason
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.
Evaluation of biofilm image thresholding methods
(2001-04) Yang, Xinmin; Beyenal, Haluk; Harkin, Gary; Lewandowski, Zbigniew
To evaluate biomass distribution in heterogeneous biofilms from their microscope images, it is often necessary to perform image thresholding by converting the gray-scale images to binary images consisting of a foreground of biomass material and a background of interstitial space. The selection of gray-scale intensity used for thresholding is arbitrary but under the control of the operator, which may produce unacceptable levels of variability among operators. The quality of numerical information extracted from the images is diminished by such variability, and it is desirable to find a method that improves the reproducibility of thresholding operation. Automatic methods of thresholding provide this reproducibility, but often at the expense of accuracy, as they consistently set thresholds that differ significantly from what human operators would chose. The performance of five automatic image thresholding algorithms was tested in this study; (1) local entropy; (2) joint entropy; (3) relative entropy; (4) Renyi’s entropy; and (5) iterative selection. Only the iterative selection method was satisfactory in that it was consistently setting the threshold level near that set manually. The extraction of feature information from biofilm images benefits from automatic thresholding and can be extended to other fields, such as medical imaging.
Influence of surface features on bacterial colonization and subsequent substratum chemical changes of 316l stainless steel
(1996-01) Geesey, Gill G.; Gillis, Richard J.; Avci, Recep; Daly, Don Simone; Hamilton, Martin A.; Shope, Paul A.; Harkin, Gary
Biofilm-forming bacteria were found to selectively colonize specific surface features of unpolished 316L stainless steel exposed to flowing aqueous media. Depending on the types of bacteria present, selective colonization resulted in significant depletion of Cr and Fe relative to Ni in the surface film at these features. No such depletion was observed on uncolonized surfaces exposed to sterile flowing aqueous medium. The results demonstrate that non-random, initial colonization of 316L stainless steel surfaces by these bacteria leads to changes in alloy elemental composition in the surface film that are enhanced with time. These chemical changes may be a critical step that weakens the oxide film at specific locations, allowing halides such as Cl− ions greater access to the underlying bulk alloy, and thereby facilitates localized attack and pit formation and propagation.
Quantifying biofilm structure
(1999) Lewandowski, Zbigniew; Webb, D.; Hamilton, Martin A.; Harkin, Gary
This article defines some quantitative parameters for describing the structure of a biofilm. The parameters can be calculated from a two-dimensional cross-sectional image on a plane parallel to the substratum within an in situ biofilm. Such images can be acquired using a confocal scanning laser microscope (CSLM). The parameters will eventually be used for eliciting relationships between the biofilm's structure and its biochemical function, and for computer model evaluation. The results shown here indicate that the structural parameters appear to be reaching steady-state conditions as the biofilm grows to a steady state.
Quantifying biofilm structure using image analysis
(2000-01) Yang, Xinmin; Beyenal, Haluk; Harkin, Gary; Lewandowski, Zbigniew
We have developed and implemented methods of extracting morphological features from images of biofilms in order to quantify the characteristics of the inherent heterogeneity. This is a first step towards quantifying the relationship between biofilm heterogeneity and the underlying processes, such as mass-transport dynamics, substrate concentrations, and species variations. We have examined two categories of features, areal, which quantify the relative magnitude of the heterogeneity and textural, which quantify the microscale structure of the heterogeneous elements. The feature set is not exhaustive and has been restricted to two-dimensional images to this point. Included in this paper are the methods used to extract the structural information and the algorithms used to quantify the data. The features discussed are porosity, fractal dimension, diffusional length, angular second moment, inverse difference moment and textural entropy. We have found that some features are better predictors of biofilm behavior than others and we discuss possible future directions for research in this area.
Quantifying biofilms structure: Facts and fiction
(2004-02) Beyenal, Haluk; Lewandowski, Zbigniew; Harkin, Gary
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.
Three-dimensional biofilm structure quantification
(2004-12) Beyenal, Haluk; Donovan, C.; Lewandowski, Zbigniew; Harkin, Gary
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.