Colony size optimisation in colony-based laser imaging for microbial source tracking

The colony-based laser scatter imaging provides a convincing solution to microbial source tracking. The optical scattering patterns of bacterial colonies are tightly correlated to the corresponding growth patterns. This relationship is manifested as the development of optical scattering patterns with the increment of colony size. An investigation was conducted into this relationship and the optimal range of colony size for improving the accuracy of microbial source tracking technique. All the bacterial samples from five host species were cultivated under the same conditions. The optical scattering patterns were recorded for the average colony diameter from 0.1 mm to 1.5 mm, using a bench top laser imaging system. Gabor wavelet was utilised to encode image signatures. Fuzzy-C-means was employed to cluster the colony patterns from the same host species. The experimental results demonstrate that the optimal range of the colony diameters is 0.8-1.0 mm. The corresponding identification rate of microbial source tracking is >80%.

[1]  Kenji Yamamoto,et al.  The mode transition of the bacterial colony , 2002 .

[2]  H. Berg,et al.  Complex patterns formed by motile cells of Escherichia coli , 1991, Nature.

[3]  A. Castle,et al.  Quantification of microcystin‐producing cyanobacteria and E. coli in water by 5′‐nuclease PCR , 2002, Journal of applied microbiology.

[4]  Bin Chen,et al.  Laser imaging for rapid Microbial Source Tracking , 2010, Int. J. Comput. Biol. Drug Des..

[5]  Euiwon Bae,et al.  Label‐free identification of bacterial microcolonies via elastic scattering , 2011, Biotechnology and bioengineering.

[6]  M. S. Zubairy,et al.  FAST CARS: Engineering a laser spectroscopic technique for rapid identification of bacterial spores , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[7]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[8]  J. Paul Robinson,et al.  Prediction of the light scattering patterns from bacteria colonies by a time-resolved reaction-diffusion model and the scalar diffraction theory , 2009, Defense + Commercial Sensing.

[9]  Tai Sing Lee,et al.  Image Representation Using 2D Gabor Wavelets , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  S. Lane,et al.  Reagentless identification of single bacterial spores in aqueous solution by confocal laser tweezers Raman spectroscopy. , 2004, Analytical chemistry.

[11]  J. Shapiro Thinking about bacterial populations as multicellular organisms. , 1998, Annual review of microbiology.

[12]  Joan B. Rose,et al.  Microbial Source Tracking: Current Methodology and Future Directions , 2002, Applied and Environmental Microbiology.

[13]  E. Ben-Jacob From snowflake formation to growth of bacterial colonies II: Cooperative formation of complex colonial patterns , 1997 .

[14]  Mitsugu Matsushita,et al.  Periodic Pattern Formation of Bacterial Colonies , 1999 .

[15]  T. Vicsek,et al.  Generic modelling of cooperative growth patterns in bacterial colonies , 1994, Nature.

[16]  J. Paul Robinson,et al.  Optical forward-scattering for detection of Listeria monocytogenes and other Listeria species. , 2007, Biosensors & bioelectronics.

[17]  B. S. Manjunath,et al.  Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..