biochemical engineering lab

Growth of Escherichia Coli in a 5 Litre Batch Vessel

College of Engineering and Physical Sciences

School of Chemical Engineering

University of Birmingham

Mustafa Iqbal - 1323293Laboratory Group 7: Zareen Zainal Azwar, Connor Hindley, Colin Francis Jayen and Matthew Parker

31st March 2013Word Count: 1270

Fermentation is an essential part of Biochemical Processing. Through the fermentation, use and preservation of live cultures on site, processes achieve bio catalytic benefits and cost reductions.

However as organisms the cultures tended in fermenters require particular attention, both in design and in practice, as they are susceptible to discerning factors such as temperature and pH.

Therefore the experiment simulated a 5 litre batch fermentation of E. coli under controlled conditions. Samples were taken, and assumed to represent the whole population due to the use of agitation to achieve presumed perfect mixing. The samples were analysed using equipment such

as spectrophotometers and glucose meters. From the data, conclusions were reached on the metabolic behavior of the cells, and it was decided that a continuous or semi-batch process

should be used to disallow the depletion of substrate; a major factor in cell growth. Another factor affected was DO2 levels, which plummeted to as low as 20%, suggesting an increased

flow rate of air would be beneficial. Furthermore, the data was hindered to the use of OD650nm values to represent the cell number when they were an indirect measurement. Hence it was

suggested to use direct methods such as counting cultures.

Contents1. Introduction......................................................................................................................................2

1.1 Aims and Objectives................................................................................................................2

2. Materials and Methods.....................................................................................................................2

2.1 Batch Vessel..................................................................................................................................2

2.2 Analysis Workspace......................................................................................................................3

3. Results..............................................................................................................................................3

4. Analysis...........................................................................................................................................6

4.1 Specific Growth Rate.....................................................................................................................6

4.2 Mean Doubling Time.....................................................................................................................6

4.3 Final Cell Yield..............................................................................................................................7

4.4 Discussion......................................................................................................................................7

5. Conclusion.......................................................................................................................................8

Appendix..................................................................................................................................................8

Appendix A..........................................................................................................................................8

Appendix B..........................................................................................................................................9

References..............................................................................................................................................10

Tables and FiguresFigure 1: Batch Vessel basic configuration. (University of Birmingham, 2014a)

Figure 2: Analysis workspace configuration. (University of Birmingham, 2014a)

Figure 3: Plot of Glucose concentration, DO2, Dry Cell Weight, OD650nm and pH against Time. (University of Birmingham, 2014a)

Figure 4: Growth Curve. (University of Birmingham, 2014a)

Figure 5: Graphical solution for specific growth rate. (University of Birmingham, 2014a)

Table 1: List of equipment and their purposes. (University of Birmingham, 2014a)

Table 2: OD650nm, glucose, pH and DO2% data. (University of Birmingham, 2014a)

Table 3: Dry Cell Weight data. (University of Birmingham, 2014a)

Table 4: OD650nm, glucose concentration, pH and DO2 data from Chemical Engineering Lab group 7. (University of Birmingham, 2014a)

Table 5: Dry Cell Weight data from Chemical Engineering Lab group 7. (University of Birmingham, 2014a)


1. Introduction1.1 Aims and Objectives

The aim of the experiment was to observe and analyse how factors such as dissolved oxygen levels are affected during the fermentation of a bacterial culture.

The objective of the experiment was to grow Escheria Coli in a submerged culture and monitor its growth, dissolved oxygen levels, pH and glucose utilisation. (University of Birmingham, 2014a)

2. Materials and MethodsThe experiment was conducted in two premises. Firstly the batch reactor from which to withdraw

samples. Secondly a workspace in which to analyse the sample using various methods. These premises are outlined in Figures 1 and 2 respectively.

2.1 Batch Vessel

Figure 1: Batch Vessel basic configuration. (University of Birmingham, 2014a)

The fermenter was initially set to a temperature of 37°C, a pH of 7, an impeller speed of 600 rpm and a DO2 level of 100% with head pressure at 2-3 psi. Further detail on Figure 1 is available in Appendix A.

After the fermenter was configured and running correctly, two hourly samples were taken. The results from these samples can be seen in Appendix B, whereas the results used for the report were taken from a different, model set of 8 hourly samples. When taking samples, part of the culture was drawn through the sampling connection. In order to avoid contamination of the fresh sample from dead cells stuck to the inside of the sample connection, a syringe was used to force air through the sampling connection back into the vessel, removing any dead cells. Ethanol was applied to any surfaces that were required to be air tight, such as the top of the replacement sampling tube which

1Mustafa Iqbal 1323293


would then screw into the sampling connection. (University of Birmingham, 2014a) Furthermore it has been assumed that there was no contamination; as otherwise the results are invalid.

2.2 Analysis Workspace

Figure 2: Analysis workspace configuration. (University of Birmingham, 2014a)

The purpose of each piece of equipment in Figure 2 is outlined in Table 1.

Table 1: List of equipment and their purposes. (University of Birmingham, 2014a)

Equipment PurposeVirkon Disinfectant.

Vortex Mixer Even and complete mixing of samples.Test Tube rack Secure suspension of test tube samples.Bunsen Burner Sterilise equipment.

Spectrophotometer Record optical density of samples.Centrifuge Calculate dry cell weight of samples.

Petri dishPremade with agar, support culture from

sample.

Sterile workspaceWiped down with Virkon in order to prevent

contamination of the samples.Spreaders Spread samples evenly over petri dish.

Mechanical Pipettes and assorted nibs

Different pipettes required different nibs as they were of different specifications. Used to

accurately transfer portions of sample/diluent to test tubes for analysis.

Mass BalanceRecording dry weight for calculation of dry cell

weight.

Glucose meterMeasurement of glucose to calculate glucose

utilisation.



3. ResultsThe following tables summarise the data recorded.

Table 2: OD650nm, glucose, pH and DO2% data. (University of Birmingham, 2014a)

Time (hours)

OD650nm

Glucose concentration

(mM)

Glucose concentration (g/L)

pHDO2 (%)

0 0.477 87 15.67 6.5 98.3

1 1.23 81 14.59 6.44 91.7

2 4.5 68 12.25 6.35 70.3

3 11 25.7 4.63 6.33 21.2

4 22.3 0 0 5.88 65.5

5 25.8 0 0 6.11 95.1

6 23.7 0 0 6.09 96.9

7 24.1 0 0 6.12 98

8 20.2 0 0 6.13 98.1

From Table 2 it is clear some trends occurred, these will be further elaborated when displayed in graphical form.

Table 3: Dry Cell Weight data. (University of Birmingham, 2014a)

Dry Cell WeightTime 0 hours

Weight: Tube only (mg)

Weight: Tube + Cells (mg)

Average weight loss of tubes (mg)

Dry cell weight (g/L)

Tube 1 963.2 960.8 4.37 1.97Tube 2 961.9 959.9 4.37 2.37Tube 3 967.7 965.8 4.37 2.47Tube 4 955.5 953.3 4.37 2.17Mean 962.075 959.95 4.37 2.241666667

Standard Deviation

4.363699692 4.448876263 0 0.192028644

Time 8 hoursWeight: Tube

only (mg)Weight: Tube +

Cells (mg)Average weight loss of

tubes (mg)Dry cell

weight (g/L)Tube 1 963.2 970 4.37 11.17Tube 2 958.5 965 4.37 10.87Tube 3 958.6 965.7 4.37 11.47Tube 4 963.2 969 4.37 10.17Mean 960.875 967.425 4.37 10.91666667

Standard Deviation

2.325268802 2.119404397 0 0.482182538

Tubes without cells (Used to calculate average weight loss of tubes)Weight - pre-

dried (mg)Weight - dried

(mg)Weight loss (mg)

Tube 1 966.3 958.1 8.20Tube 2 957.4 954.9 2.50



Tube 3 964.1 961.7 2.40

The dry cell weights were calculated using by taking several 1ml samples of the cells and placing them in sterile Eppendorf tubes of known mass. These samples were then centrifuged for 10 minutes at 10,000 rpm to calculate the dry cell weight. However, as the Eppendorf tube loses mass, some empty Eppendorf tubes of known mass were also included to calculate an average for this loss of mass (4.37mg) and include it in the dry cell weight calculations. Mean and Standard Deviations have also been included. (University of Birmingham, 2014a)

From the data in tables 1 and 2, the following graph can be plotted.

Figure 3: Plot of Glucose concentration, DO2, Dry Cell Weight, OD650nm and pH against Time. (University of Birmingham, 2014a)

From Figure 3, time and OD650 can be plotted against each other to obtain the growth curve, as seen in Figure 4.

Figure 4: Growth Curve. (University of Birmingham, 2014a)

4. Analysis4.1 Specific Growth Rate Calculation

It is known that:


Lag phaseExponential Phase

Stationary phaseDeath phase


d CC

dt=rG=μCC (1)

Where:

CC=Cell Concentration(g L−1)

rG=Growth Rate (g L−1hou r−1)

μ=Specific Growth Rate ( hour−1 )

t=Time (hours )

Integrating (1) between the limits CC=CC 0 at t=0 and CC=CC at t=t results in the following equation.

ln ( CCC 0

)=μt (2)

Rearranges to give C=CC 0eμt (3)

In the case of the experiment the cell number is assumed to be well represented by OD650nm values. Therefore CC values can be approximated to OD650nm values at any given time.

In order to calculate the specific growth rate the exponential phase of the graph in Figure 4 must be considered. As in the said phase the curve follows equation (3), and therefore can be solved for μ. This has been done in Figure 5, by plotting OD650 values between the times of 1 and 4 hours, and plotting an exponential trend line. Giving μ=1.0077 hou r−1.


0 1 2 3 4 5 6 7 80

5

10

15

20

25

30

Growth Curve

Time (Hours)

OD6

50nm


1 1.5 2 2.5 3 3.5 40

5

10

15

20

25f(x) = 0.477 exp( 1.00765297920447 x )

Graphical Soluton of Specific Growth Rate

Time (Hours)

OD6

50nm

Figure 5: Graphical solution for specific growth rate. (University of Birmingham, 2014a)

The equation of the trend line is in the form CC=CC 0eμt .This is solved graphically as y

represents OD650 values or CC, the 0.477 represents the value of CC 0 i.e. the OD650 value at t = 0. Concluding that μ is 1.0077.

4.2 Mean Doubling Time CalculationDoubling time is calculated from the following equation.

At doubling time,t d, CC0

=2.

Therefore subbing into (2) gives:

t d=ln (2 )

μ=

ln (2 )1.0077 hou r−1

=0.688 hours=41 minutes∧18 seconds

(University of Birmingham, 2014b)

4.3 Final Cell Yield CalculationFinal cell yield is given by:

Y C /S=Mass of new cells formed

Mass of substrate consumed=

−ΔCC

ΔCS

(3)

Where:

Y C /S=Final CellYield

ΔCC=Change∈cell concentration(g L−1)

ΔCS=Change∈substrate concentration(g L−1)

Remembering that substrate is equivalent to the nutrients, i.e. glucose.

Therefore ΔCC=CC−CC 0=10.92 g/ L−2.24 g /L=8.68 g/ L



And ΔCS=CS−CS 0=0 g/ L−15.67 g/ L=−15.67 g /L

Therefore substituting into (3):

Y C /S=−8.68 g/ L−15.67 g/ L

=0.554(3 s . f .)

(University of Birmingham, 2014b)

4.4 DiscussionFrom Figure 3 several observations can be made. Regarding the glucose concentration, note that

due to the process being a batch process after the initial input of substrate no further substrate was supplied. Therefore the rate of consumption of substrate is given by the gradient of the glucose concentration curve in Figure 3. Glucose concentration decreases from 15.67 g/L at a time of 0 hours to 0 g/L after 4 hours of fermentation. Between the times of 2 and 3 hours the concentration of glucose depletes at a much faster rate than between the times of 0 and 2 hours, these trends could embody the exponential and lag phases respectively. Then between 3 and 4 hours the gradient of glucose concentration increases slightly again, but still remains negative, suggesting a lower rate of consumption. This behaviour represents the cells propagating through the lag phase, exponential phase and stationary phase. After a time of 4 hours, with glucose concentration at 0 g/L it is expected for the final phase, the death phase, to occur in the cells as they have depleted the substrate and so no further generation can occur.

Dissolve Oxygen levels (DO2) represent the physical distribution of oxygen molecules in water. Cells consume oxygen in their respiration, decreasing DO2 levels. (Eutech, 2007) At a time of 0 hours the percentage of DO2 is near 100, this is short-lived as the cells finish their lag phase after an hour and begin to proliferate exponentially; represented by the exponential decline in DO2% between 1 and 3 hours. At a time of 3 hours DO2% reaches a minimum of 20%, representing a scarcity of oxygen in the solution. The DO2% begins to rise exponentially again between the times of 3 and 5 hours, before stabilising around 98% at 8 hours. The sudden resurge of DO2 at a time of 3 hours coincides an hour before the occurrence of substrate depletion (at 4 hours).

The pH is observed to slowly drop from 6.5 to 6.3 between 0 and 3 hours. After which it drops rapidly to a minimum of 5.9 at 4 hours. The sudden flood of less alkaline/more acidic conditions concur exactly with substrate depletion at 4 hours. Anaerobic respiration due to lack of oxygen is also a cause, as lactic acid is produced. After 4 hours death phase begins and pH begins to climb, stabilising at 6.13 at 8 hours. This is due to the death of cells producing organoacids which causes the pH to become more acidic. However an experiment by Don (2008) suggests the tolerant range of pH for E. coli is between pH 2 and 7, therefore the pH of 5.88 observed in the culture at a time of 4 hours should not inhibit the growth. Nevertheless it may not be optimal. (University of Birmingham, 2014a)

Dry cell weight was only measured at the times of 0 hours and 8 hours, as the data is discrete with a large interval the plot on Figure 3 does not include a trend line as the true development of dry cell weight would be related to the cell kinetics (metabolism), opposed to a linear line.

The OD650nm data supports the previous claims, as all 4 phases of cell metabolism can be perceived in Figure 3 when compared with over factors and even clearer in the growth curve, Figure 4. Hence it is shown that the lag phase occurs between 0 and 2 hours, the exponential phase occurs between 2 and 4 hours, the stationary phase occurs between 4 and 7 hours, and therein the death phase occurs 7 hours onward. This has been annotated on Figure 4. Note that realistically the stationary phase would be represented by a duration in which the cell number (represented by OD650nm) remained constant, however from Figure 4 this has been assumed from the average OD650 values between 5 and 7 hours. In order to improve upon the accuracy of this phase categorisation samples



could have been taken in shorter intervals to better observe this phenomenon. Hence the highlighted areas in Figure 4 are rough estimates.

5. ConclusionIn order to improve cell yields a semi-batch or continuous operation should be performed, as to

introduce a constant supply of substrate to the cells and prevent the depletion of substrate as witnessed in the experiment.

The fermentation benefits the culture as it is under controlled conditions and not subject to the unpredictable implications of nature. The use of computer systems combined with equipment such as the heating jacket and impeller enabled controlled environments and their monitoring, which enabled the experiment to observe, record and identify the major factors affecting or affected in fermentation. In this case, substrate concentration and DO2 levels were directly affected, which in turn caused implications for the pH. However further factors such as the temperature (maintained at 37°C), pressure (maintained between 2-3 psi), air flow rate and impeller speed (maintained at 600 rpm) could be adjusted to investigate their effects.

The use of OD650nm values to represent cell number and plot the growth curve was an indirect measurement and therefore an inaccuracy, as they may not represent the true nature of cell number. Therefore in order to improve accuracy direct measurement methods such as the use of a counting chamber of counting the number of colonies should be used to obtain cell number. (University of Birmingham, 2014a)



AppendixAppendix A

The control unit as shown in Figure 1 enabled the experiment to set conditions such as temperature and air flow rate. For example, temperature control was achieved through the use of a heating jacket and a cooling finger. The unit automatically logged all the data from the sensory equipment in use such as pH from the pH electrode, technically defined as a glass steam sterilisation electrode. The agitation of the culture is expected to affect DO levels.

Some additional features were used that are not in Figure 2. Air flow was controlled using a needle valve, wherein both the inlet and outlet of air were sterilised with O.2-micron air filters. A glucose addition flash was also connected to supply glucose. Antifoam was used to prevent overspill and risk of contamination. (University of Birmingham, 2014a)

Appendix BTable 4: OD650nm, glucose concentration, pH and DO2 data from Chemical Engineering Lab group 7. (University of Birmingham, 2014a)

Time (hours)

OD650nm

Glucose concentration (mM)

Glucose concentration (g/L)

pHDO2 (%)

0 0.536 18.3 3.30 6.3 15.5

1 1.274 0.7 0.135.86

2.8

Table 5: Dry Cell Weight data from Chemical Engineering Lab group 7. (University of Birmingham, 2014a)

Dry Cell WeightTime 0 hours

Weight: Tube only (mg)

Weight: Tube + Cells (mg)

Average weight loss of tubes (mg)

Dry cell weight (g/L)

Tube 1 0.9398 1.9192 4.37 5.35Tube 2 0.9453 1.9212 4.37 5.34Tube 3 0.9392 1.9293 4.37 5.36

Time 1 hourWeight: Tube

only (mg)Weight: Tube +

Cells (mg)Average weight loss of

tubes (mg)Dry cell weight

(g/L)Tube 1 0.9052 1.9528 4.37 5.41Tube 2 0.9466 1.9566 4.37 5.38Tube 3 0.9436 1.9468 4.37 5.37

ReferencesDom, S.M. (2008). Optimal Conditions for the Growth of E Coli. Last accessed 3rd April 2014.

Eutech. (2007). Introduction to Dissolved Oxygen. Available: http://www.eutechinst.com/techtips/tech-tips15.htm. Last accessed 3rd April 2014.

University of Birmingham. (2014a) Chemical and Biochemical Processes Fermentation Lab. School of Chemical Engineering. College of Engineering and Physical Sciences.



University of Birmingham. (2014b) Chemical and Biochemical Processes Lectures 1-5. School of Chemical Engineering. College of Engineering and Physical Sciences.


biochemical engineering lab

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