The document summarizes an experiment that tested the effect of temperature on the growth of heterotrophic bacteria in mixed culture. Three reactors were set up at 20°C, 30°C, and 40°C and measurements of total suspended solids (TSS) and chemical oxygen demand (COD) were taken over time. The results showed that the bacteria grew best and had similar results at 20°C and 30°C, while growth was poorer at 40°C. The goal of determining the best temperature for growth of the mixed culture was achieved.

1. Growth of Bacteria With Various
Environment Temperatures
Sophia Della Rocca, Lauren
Todd, Shirin Udwadia
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2. Introduction
Objective: To determine the effect of increasing temperature
on a mixed culture of heterotrophic bacteria
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3. Materials and Methods
Media
● Water (2L)
● Starch pellets (2.222 g)
● Yeast Extract (0.4991 g)
● K2HPO4 (0.0440 g)
● Innocculate: 0.008 g from Septic tank
bacteria packet
Setup
● Stir bars
● Hot plates
● Foam plug
● Temperature Controllers
Methods
● TSS Test
● COD Test
● Filtration
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4. Calculations
● Dry weight (Table 1)
● Calculated TSS from linear regressions for each reactor (Figures 1-3 and
Tables 2-6)
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5. ● Calculated glucose COD concentration using COD standard calibration
curve (Figure 4 and Tables 7-11)
● Calculated glucose concentration from COD concentration using glucose
COD ratio (Tables 7-11)
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6. Results and Discussion
● Comparison of dry weight over
time for each reactor
● 40°C reactor performed the worst
while the 20°C and 30°C reactors
preformed about the same
6

7. ● For the majority of the time, the
glucose levels were nearly the
same
● 40°C was the highest at the end
● Both 20°C and 30°C were lower
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8. Errors and Improvements
● Starch pellets did not completely dissolve, even after the experiment was
completed
● Inoculation errors
● Temperature controllers not consistent
● Times with taking measurements
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9. Modeling and
Reactor Design
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10. 10

11. What could have been
(C
(cotto)
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12. Conclusion
● Goal: to find the best temperature for growth with a heterotrophic mixed
culture
● The 20°C and 30°C reactors yielded the most biomass and had very
similar results while the bacteria functioned poorly in the 40°C reactor
12

13. References
Adams, H., Todd, L., & Udwadia, S. (2020) “Lab 6: Methods of Organic Substrate Determination: COD.” BE 4101 Lab 6, November 9,
2020.
Cotto A, Looper JK, Mota LC, Son A. Quantitative Polymerase Chain Reaction for Microbial Growth Kinetics of Mixed Culture
System. J Microbiol Biotechnol. 2015 Nov;25(11):1928-35.
Drapcho, C. 2020. Lab 5 Methods of Biomass Determination: Optical Density (OD) and Biomass Dry Weight (or Total Suspended
Solids TSS). Unpublished Laboratory Notes, BE 4101, Clemson University, Clemson SC.
Drapcho, C. 2020. Lab 6: Methods of Organic Substrate Determination: COD. Unpublished Laboratory Notes, BE 4101, Clemson
University, Clemson SC.
Noor, Rashed & Islam, Zahidul & Munshi, Saurab & Rahman, Farjana. (2013). Influence of Temperature on Escherichia coli Growth in
Different Culture Media. Journal of Pure and Applied Microbiology. 7.
Shiloach J, Fass R. Growing E. coli to high cell density-a historical perspective on method development. Biotechnol Adv. 2005
Jul23(5):345-57. doi:10.1016/j.biotechadv.2005.04.004 p.350 bottom paragraph 13

14. References
Youen Pericault, Mikael Risberg, Maria Viklander, Annelie Hedström, Temperature performance of a heat-traced utilidor for sewer and
water pipes in seasonally frozen ground, Tunnelling and Underground Space Technology, Volume 97, 2020, 103261, ISSN
0886-7798, https://doi.org/10.1016/j.tust.2019.103261.
14

15. Appendix
Table 1: Initial data for TSS vs OD Linear Regression
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16. Figure 1: TSS vs OD Linear Regression for 40
degrees C
Figure 2: TSS vs OD Linear Regression for 30
degrees C
Figure 3: TSS vs OD Linear Regression for 20
degrees C
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17. Table 2: Initial data for TSS Calculation on 11/18 at 1:00 PM Table 3: Initial data for TSS Calculation on 11/18 at 8:00 PM
Table 4: Initial data for TSS Calculation on 11/19 at 8:00 AM
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18. Table 6: Initial data for TSS Calculation on 11/19 at 9:00 PM
Table 5: Initial data for TSS Calculation on 11/19 at 3:00 PM
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19. Figure 4: COD Calibration Curve from Lab 6
Table 7: Initial data for Glucose Concentration Calculation on 11/18 at 1:00 PM Table 8: Initial data for Glucose Concentration Calculation on 11/18 at 8:00 PM
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20. 20
Table 9: Initial data for Glucose Concentration Calculation on 11/19 at 8:00 AM Table 10: Initial data for Glucose Concentration Calculation on 11/19 at 3:00 PM
Table 11: Initial data for Glucose Concentration Calculation on 11/19 at 9:00 PM

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Figure 5: Stella Model of Forward Finite difference of
batch reactor with substrate and biomass
Figure 6: Forward Finite difference data for
batch reactor with Substrate and biomass
graphed on mg/L vs hours
Table 12: Forward Finite difference data
for batch reactor with Substrate and
biomass over 12 hour time period

22. 22
Fig. 7. Kinetics of single culture. Microbial growth
(biomass, closed circles) and substrate (glucose, open
circles) depletion curves for (B) E. coli K12. Microbial
growth kinetics of single culture were determined by
the absorbance experiments (points), and the fitting by
nonlinear regression (line) was based on the Monod
growth kinetics. (Cotto)
Fig. 8. Comparison of biomass (X)
monitoring by both UV-vis
spectrophotometry (absorbance, closed
circles) and qPCR assay E. coli K12 as a
single culture (Cotto)

23. Questions?
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24. Biosystems in Action!
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