Laser and optical based methods for detecting and characterising microorganisms

Krishnan, Anand (2008) Laser and optical based methods for detecting and characterising microorganisms. PhD thesis, University of Glasgow.

Abstract

This work investigated novel optical methods of characterizing the activity of microorganisms. Two different systems are studied in detail in this work. The possibility of using line scan speckle systems and imaging systems to understand the microbial behaviour, growth and motility was investigated. Conventionally, the growth and viability of microorganisms are determined by swabbing, plating and incubation, typically at 37degreesC for at least 24 hours. The proposed system allows real-time quantification of morphology and population changes of the microorganisms.
An important aspect of the line scan system is the dynamic biospeckle. Dynamic speckle can be obtained from the movement of particles suspended in liquids. The speckle patterns show fluctuations in space and time which may be correlated with the activity of the constituents in the suspension. Initially the speckle parameters were standardized to non-motile and inert specimens such as polystyrene microspheres and suspensions of Staphylococcus aureus. The same optical systems and parameters were later tested on motile, active and live organisms of Escherichia coli.
The experimental results that are presented describe the time history of the dynamic speckle pattern. A number of algorithms were used to analyse the intensity data. A 2D-FFT algorithm was used to evaluate the space and time-varying autocorrelation. Analysis of the speckle data in the Fourier domain provided insight into the motility of the organisms in broth. The mathematical analysis also gave further insight into the culture broth evaporation and its particle sedimentation characteristics at 37degreesC. These features correlated with the periodic motions associated with the organism and may therefore provide a signature for the organism and a means of monitoring. These results aided the developemnt of imaging bacterial detection systems which were discussed in the second half of the work.
The second experimental system focuses on quantifying the morphology and population dynamics of Euglena gracilis under ambient conditions through image processing. Unlike many other cell systems, Euglena cells change from round to long to round cell shape and these different cell shapes were analyzed over time. In the morphological studies of single Euglena cells, image processing tools and filtering techniques were used and different parameters identified and their efficiency at determining cell shape compared. The best parameter for processing the images and its effectiveness in detecting even the interior motions of constituents within a dead cell was found. The efficiency of the measurement parameters in following sequences of shape changes of the Euglena cell was compared with the visual assessment tests from 12 volunteers and other simple measurement methods including parameters relating to the cells eccentricity, and image processing in the space and frequency domains. One of the major advantages of this system is that living cells can be examined in their natural state without being killed, fixed, and stained. As a result, the dynamics of ongoing biological processes in live cells can be observed and recorded in high contrast and sharp clarity. The population statistics of Euglena gracilis was done in liquid culture. A custom built microscopy system was employed and the laser beam was coupled with a dark field illumination system to enhance the contrast of the images. Different image filters were employed for extracting useful information on the population statistics. Similarly as with the shape study of the Euglena cell, different parameters were identified and the best parameter was selected. The population study of the Euglena cells provided a detection system that indicated the activity of the population.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Subjects: Q Science > QR Microbiology; T Technology > TJ Mechanical engineering and machinery; Q Science > QA Mathematics
• Colleges/Schools: College of Science and Engineering > School of Engineering
• Supervisor's Name: Watson, Dr. Ian
• Date of Award: 2008
• Depositing User: Mrs Marie Cairney
• Unique ID: glathesis:2008-436
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 24 Oct 2008
• Last Modified: 10 Dec 2012 13:18
• URI: https://theses.gla.ac.uk/id/eprint/436