automated counting of microbial colonies on rehydratable film media mehrdad saadat biology 4400...
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Automated Counting of Microbial Colonies on
Rehydratable Film Media
Mehrdad Saadat
Biology 4400
Spring Semester 1999
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Automated Counting of Microbial Colonies on
Rehydratable Film Media
I. Background
II. Methods and Results
III. Conclusions
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Background
• Use of Petri dishes
– Every day, biologists use petri dishes filled
with media to culture bacteria– One use for culturing is enumeration
– A simple formula can be applied to a set of
cells grown on media to enumerate the number
of cells in the original sample being tested
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Background
• BioCount
– Developed by Apogee Systems
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Background
• BioCount
– This is a scanner based system used for detecting and enumerating bacterial colonies in petri dishes
– The system uses raster imaging to detect curvatures on a given media
– The program then accepts a set of curvatures as a colony
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Background
• Previous Results– The BioCount system has proven to be
reliable in counting colonies on mFC agar
– Paula Tennant-Clegg showed in her research that the BioCount system could accurately count coliform colonies on mFC agar when properly cultured
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Background
• Rehydratable Film Media– Recently the 3M company has developed
the Petrifilm®
– This is a much easier and faster way of plating for several reasons: no need to spend hours making a selective
media
no accidents in “cutting into” the agar while
streak plating
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Background
• Can the BioCount system be adapted for use with Petrifilms?
• If so, it provides a possibility for– More rapid analysis
– Greater objectivity: Elimination of variability associated with manual counts
– Automated documentation
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Methods and Results
• Objectives of this Project– Determine the Biocount® parameters for
optimal counts of total aerobic Petrifilms
– Compare manual and automated colony counts
– Identify possible causes of false positive and false negative errors in the automated counts
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Methods and Results
• Procedure– First: Prepare a fresh culture of aerobic
bacteriaBacillus subtilis, Enterococcus
fecalis, Staphylococcus aureus
– Once a turbid broth was obtained, it could be diluted down to give a desired concentration of bacterial cells (10-14)
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Methods and Results
• Procedure (cont.)– One ml of the dilution was then plated on the
Petrifilm aseptically using a pipette
– Proper procedure was followed to cover the film and incubate it at the temperature given by 3M™ (approximately 33º C)
– After 24 hours the films were removed from the incubator
– At this time colonies were manually counted
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Methods and Results
• Procedure (cont.)
– The films were then scanned by the
desktop scanner, four films at a time
– Once plated and counted by hand, the
colonies were scanned using a typical
desktop scanner by HP at 150 dpi
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Methods and Results
• Hypothesis:
There is not a significant difference in the
count of bacterial colonies on a Petrifilm
between a manual count and that of one
done by an automated system
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Methods and Results
• Parameters
– Using the parameters tool, I attempted to
optimize the parameters so that the
program would detect an almost exact
number of colonies on a given film — if
this were to work I would then test the
same parameters on another film.
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Methods and Results
• Parameters (cont.)– Optimal parameters should pass two
tests:• They must only allow for detection of few, if
any false positives nor any false negatives. • They must accurately count the present
colonies
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Methods and Results
• Parameters (cont.)– Minimum Peak Size: 6
– Radius Step: 1
– Vector Radius Maximum: 3
– Gray Threshhold: 135
– Radius Power: 1.01
– RGB color settings: 240, 169, 25
– Intensity settings: 2.15, 1.25, .08
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Methods and Results
• We already knew that the program was set to utilize a gray scale in order to detect colonies
• We also know that if we pointed to a given colony with the computer’s mouse, and used the right button of the mouse to click on the colony, we would set the gray-scale parameters to that colony’s colors
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• An area of the film may be enlarged to give more distinct colonies
• When enlarged the colonies were not all the same color and there was a gradient of colors within a given colony.
• This appeared to be a major source of error in optimizing the system
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Methods and ResultsManual Automated
Film # Count Count Difference --------- ------------- --------------- --------------
1 745 707 38
2 286 323 17
3 525 509 16
4 498 475 23
5 442 504 62
6 387 433 46
7 240 332 92
8 413 500 87
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Methods and Results
• Statistical Analysis: t-test
t = 1.582– At a 95% confidence level, the deviation
between the automated and manual count is not significant
– Therefore, the data support the hypothesis
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Conclusions
• Overall, there is good agreement between manual and automated colony counts on total aerobic Petrifilms
• If we were to choose a dark colony as our basis for a gray-scale, the program would detect anything below this level of darkness
• If we were to choose a light colony the program would detect, light colonies, as well as dark colonies, but it would also detect many false
positives and background interference.
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Conclusions• Areas for future work
– Microbiology research: Find ways to promote colony growth with greater uniformity of color
– Computer research: Enhance the colony detection method to handle color gradients within colonies