1. Team 3
March 31, 2014

2.  The purpose of this study is to create
and validate a mathematical model of
a growth curve of bacterial behavior
after thermal shock at various
temperatures

3.  Escherichia coli (E. coli) is a type of bacteria
commonly found in the intestinal tracts of
large mammals
 The growth and decay rate are also affected
by:
 Temperature
 Initial concentration of bacteria
 Presence of antibacterial substances
 pH levels
 Oxidation reduction potential

4.  In our experiment, we demonstrate how the
growth curve is affected by thermal shock
 E. Coli grows well between 21oC to 50oC with
an optimum at about 37oC .
 E. coli can divide every 20 minutes
 At temperatures of 0°C (32°F) E. coli are
unable to divide, keeping the population
stable
 E. coli is killed above 70°C (160°F)

5.  Lag phase: the population remains temporarily
unchanged
 Log phase: the cells divide at a constant rate
depending on temperature conditions
 Stationary phase: the population
growth is limited by
temperature
 Death phase: the
number of cells decreases
The E.coli Growth Curve

6.  The growth curves of colonies shocked
at temperatures (45-650C) demonstrate
longer lag times but accelerated
exponential growth when compared to
a control grown at 37°C

7. WE WILL APPLY THIS
EQUATION TO CREATE THE
GROWTH CURVE MODEL[17]
Where:
 (Nmin) = minimum
population of E.coli
 (Nmax) = maximum
population of E.coli
 r = Temperature-dependent
constant
 C= Adjustment factor
 N= number colonies at time t

8. Materials and Equipment
 Spectrophotometer and cuvettes
 Inoculation Loop
 1000μL and 100μL micropipettes
 Beakers and hot plates
 Incubator (37oC)
 Reagents:
 Distilled water and deionized water
 Culture of E.Coli
 Nutrient broth as a food source

9. Thermal Shock:
 Initially raise bacterial environment
temperature to 450C, 550C, 600C, and 700C
 Growth continued at 370C after thermal shock
 Control group grown at 370C
Measure growth
 Create a concentration ladder
 Measure cloudiness in a test tube as the number
of cells increase (turbidity) using a
spectrophotometer

10.  Mintab and MATLAB software
 Plot mathematical growth curve and
experimental growth curves
 Regression analysis

11. [1] J. E. Bailey, "Mathematical Modeling and Analysis in Biochemical Engineering: Past Accomplishments and Future Opportunities,"
Institute of Biotechnology, 1998, pp. 8-20.
[2] J. Baranyi, "A non-autonomous differential equation to model bacterial growth," T. A. Roberts, ed., Food Microbiology, 1993, pp. 43-59.
[3] J. Baranyi, "A Review Paper: A Dynamic Approach to Predicting Bacterial Growth in Food," T. A. Roberts, ed., International Journal of
Food Microbiology, 1994, pp. 227-294.
[4] J. Baranyi, "Mathematics of predictive food microbiology," T. A. Roberts, ed., Food Microbiology, 1995, pp. 199-218.
[5] M. Berney, H. U. Weilenmann, J. Ihssen et al., “Specific growth rate determines the sensitivity of Escherichia coli to thermal, UVA, and
solar disinfection,” Applied and Environmental Microbiology, vol. 72, no. 4, pp. 2586-2593, Apr, 2006.
[6] M. P. Doyle, “ESCHERICHIA-COLI O157 - H7 AND ITS SIGNIFICANCE IN FOODS,” International Journal of Food Microbiology, vol.
12, no. 4, pp. 289-302, Apr, 1991.
[7] J. S. Edwards, "In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data," R. U. Ibarra, ed.,
Nature, 2001.
[8] H. Fujikawa, "A new logistic model for Escherichia coli growth at constant and dynamic temperatures,“ Morozumi, Satoshi A. Kai, ed.,
Food Microbiology, 2004, pp. 501-509.
[9] R. Ibarra, "Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth," J. S. Edwards, ed., Nature,
2002.
[10] A. G. Marr, "Growth Rate of Escherichia Coli," 2, American Society for Microbiology, 1991.
[11] J. M. Monk, P. Charusanti, R. K. Aziz et al., “Genome-scale metabolic reconstructions of multiple Escherichia coli strains highlight
strain-specific adaptations to nutritional environments,” Proceedings of the National Academy of Sciences of the United States of America,
vol. 110, no. 50, pp. 20338-20343, Dec, 2013.
[12] D.-H. Oh, "A New Secondary Model Developed for the Growth Rate of Escherichia coli O157:H7 in Broth," T. Ding, ed., Indian Journal
of Microbiology, 2012, pp. 99-101.
[13] M. O. Olanya, "Effects of temperatures and storage time on resting populations of Escherichia coli O157:H7 and Pseudomonas
fluorescens in vitro," D. O. Ukuku, ed., Food Control, 2014, pp. 128-134
[14] O. Rodriguez-Gonzalez, "Escherichia coli<font class=""> O157:H7 subjected to pulsed electric fields in milk," M. Walkling-Ribeiro, ed.,
International Dairy Journal, 2011, pp. 953-962.
[15] J. Samelis, and J. N. Sofos, “Role of glucose in enhancing the temperature-dependent growth inhibition of Escherichia coli O157 : H7
ATCC 43895 by a Pseudomonas sp,” Applied and Environmental Microbiology, vol. 68, no. 5, pp. 2600-2604, May, 2002.
[16] L. J. Tranvik, and M. G. Hofle, “BACTERIAL-GROWTH IN MIXED CULTURES ON DISSOLVED ORGANIC-CARBON FROM
HUMIC AND CLEAR WATERS,”Applied and Environmental Microbiology, vol. 53, no. 3, pp. 482-488, Mar, 1987.
[17] G. D. Wang, "Survival and growth of Escherichia coli O157:H7 in unpasteurized and pasteurized milk.," T. Zhao, ed., Journal of Food
Protection, 1997, pp. 610-613.
.