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The Effects of Various Factors on the Growth Rate of E. coli
There are times in our lives (as human beings) when people do not feel well. A doctor might diagnose them with a disease or an infection. There are also times when people do not feel clean. This could be a person’s feeling after exercising, sweating, or maybe he/she had not taken a shower in a couple days. In any of the preceding scenarios, bacteria most likely played a major role in initiating a person’s feeling of illness or squalor. “Sickness” can be caused from bacteria. Someone may be sick because they ate food contaminated with bacteria or they could have easily taken a sip from the cup of a friend and shared some sort of bacterial disease. Bacteria surrounds us everyday, every second. It is difficult for people to accept this fact because they want to believe they are clean, after they shower. In relative terms, a washed person is clean, but they are not free of bacteria. “Clean” is simply an image, because bacteria are covering all substances and objects that you use to be clean; toothbrushes, soap, and even toilet paper. We live in a world of bacteria, maybe even a world that evolved from bacteria.
These microscopic organisms reproduce quickly, sometimes even exponentially. In the experiment today, my class is observing and measuring data of how different factors can influence the rate at which bacteria grows. We will use Escherichia coli (E. coli) as our bacteria. It is a Gram-negative bacterium that resides in the intestines of humans (Laboratory Experiences, 34).
Before you can fully understand the experiment and it purpose, it is important to understand the phases bacteria go through when reproducing in various media. In general, a bacterial will go through four distinct phases; a lag phase, log phase, stationary phase, and a death phase. The lag phase shows how bacteria reproduce at a very slow rate at first. At this point, the cells are preparing for division. They are making sure to manufacture fats and proteins for the reproduction ahead. The second phase is the log (logarithmic or exponential) phase. The bacteria is now replicating rapidly and becoming so large in numbers that space is growing smaller, as is non-hazardous room and nutrient. Due to this rapid growth, the next step is the stationary phase. In this phase, about fifty percent of the new bacteria population will become inactive, and the other fifty percent will remain and continue replication (binary fission). The last stage of bacteria generational grow is the death stage. In the death stage, there is not enough nutrients for the entire population. This causes the death rate of E. coli to increase, and the division will slow as well. At some point, the birth rate will be lower than the death rate, and this is displayed in the graph at the leveling off, or downward slope. From this growth curve that bacteria produces, the mean generation time (MGT) can be calculated. This will be shown later in the results section of this report.
Various types of abiotic, “non-living chemical and physical factors (Biology, 1027)”, factors try to decide which will act as catalysts and which will limit the growth of the E. coli. There are many factors that could have an effect on the growth rate of bacteria, but we are only concerned withthree; aeration, temperature, and nutrients.
“The conditions for optimal growth-temperature, pH, salt concentrations, nutrient sources and so on- vary according to species. Refrigeration retards food spoilage because most microorganisms grow only very slowly at such low temperatures (Campbell, 507). Temperature acts as a catalyst for many things, and it helps speed up many chemical processes. It is stated in the lab manual ( 35) that 37 degrees Celsius is the optimal condition for E. coli and that E. coli has a doubling time of about 20 minutes at this temperature. From this information, I predict that the higher the temperature, the higher the MGT.
Our next variable that we are testing is the effect of different nutrients on E. coli. Our first type of media to test is MSG. MSG encourages growth and also contains glucose, a supplier of carbon. The second type of media used is MSGT, which has everything that MSG has, and a new chemical called tryptose. MSGT not only has carbon, but also has nitrogen, from the tryptose. The last variable that will be using is MSGTYE. It has everything that MSG contains, everything that MSGT contains, and consists of a yeast extract. I hypothesize that the MSGTYE will prove to have the fastest growing rate, and that MSG will have the slowest growth rate of the three. Nutrients (like carbon and nitrogen) have many functions for the growth of bacteria, and a yeast extract has other nutrients that could help MSGTYE have the greatest growth rate on E. coli.
The last tests will be done to find out the effects of aeration on the growth of bacteria. Different types of bacteria can live in environments with oxygen, and some without. In this lab, we will be making our conclusion based three flasks containing the E.coli. One flask will be a control flask, which will sit still and be exposed to the atmosphere. Another flask will be placed in a moving water bath. The water bath is used to mix different amounts of the atmosphere with E. coli. The third and final flask will be a “baffled” flask, which will be placed in a trembling water bath. A “baffled” flask is irregular shaped and therefore may accept different amounts of oxygen. I predict that the baffled flask will have the greatest growth rate, and that the control flask will have the lowest growth rate because the baffled flask has a greater chance of the air reacting with the E. coli.
Table 1 provides each culture condition and treatment for each category.
For the experiment, we will use the spectrophotometer to measure temperature, aeration, or nutrients effects on the growth of E. coli. The spectrophotometer works because it measures the absorbency of light in a solution. The more the population of the bacteria grows, the more light the solution will absorb, and the cloudier the solution will be.
First our class split up into three groups, one to observe the effects of aeration on the growth of E-coli, one to observe the effects of temperature, and another to observe the effects of nutrients. Each group followed the directions in the procedures section of the lab manual (Laboratory Experiences, Spring 2001). Using the results of the tests, we made graphs to determine the mean generation time.
My group was in charge of measuring the effects that the nutrients had on growth rate of E. coli. We started by getting all our flasks together. They were already prepared with the medium because of our limited lab time. We had six different flasks. Three of them were for the three types of media that we added to the medium (E. coli). The other three flasks contained “blank” medium. These blanks were used to zero the spectrophotometer, and each different nutrient had it’s own blank flask. So, the first thing we did was place a tube of the blank medium in the spectrophotometer and set the absorbance needle on zero. Then we added MSG (4 mL), by a use of a pipet, to a cultured flask and took the absorbency reading and recorded it. For the next media, we used a different blank flask to zero the spectrophotometer, and again added 4 mL to a cultured flask and took the absorbency reading at 600nm. We did this for all three of the nutrients; MSG, MSGT, and MSGTYE. It was very important that we remembered to use the corresponding blank flask for each type of media. After taking our initial readings, at 0 minutes, we waited for 15 minutes, then took another set of readings. We still made sure to re-zero the spectrophotometer before each nutrient. We took readings every 15 minutes, until the class was over.
For the temperature and aeration trials, the flasks of E. coli with tryptic soy broth (TSB) were measured the same way that the nutrient trials were tested. Before every sample, we had to re-zero the spectrophotometer with a “blank” flask, and then we took the reading from the cuvettes. As we did for the nutrient experiments, we also took the readings from the temperature and aeration samples every 15 minutes. The temperature flasks were prepared by exposing one flask to room temperature (25 degrees Celsius), another flask in a heated compartment (37 degrees Celsius), and the final flask in a lab oven at 33 degrees Celsius.
In the aeration samples, one flask was stationary exposed to the atmosphere. The second flask was put in a regular flask, and placed in a wavering water bath. The third cuvette, which was irregular shaped, was also placed in the quivering water bath. After treatment, all the samples were measured on the spectrophotometer, using the same procedure as the nutrient samples and temperature samples.
Every 15 minutes, my fellow students and I measured the light absorbency (at 600nm) of the growing E. coli and it’s varied conditions. From these findings, we were able to calculate the mean generation time (MGT), by graphing our spectrophotometer results and deduced an approximate time that correlated with the doubled initial absorbency. For example, the flask with the temperature of 37 degrees Celsius had an initial absorbency of .13. After doubling this number (.26), we looked at our growth curve (Figure 1.) and found at what time would the growth curve of 37 degrees reach an absorbency of .26. In this example, the mean generation time (MGT) was approximately 73 minutes. In simpler terms, for the growth of E. coli to double it’s initial population, at the given temperature of 37 degrees Celsius, it would take 73 minutes. Our results of all spectrophotometer readings are listed in Tables 2 through 4. Table 2 displays the outcome of the effects of different types of aeration on E. coli. Table 3 exhibits the readings for three different temperatures (25 , 33 , and 37 ), while Table 4 shows the absorbance variation with three types of media (MSG, MSGT, and MSGTYE). Following the tables, are Figures 1, 2 and 3. These graphs show the growth curves of E. coli after treatments. Although the curves may look like one absorbs more and one absorbs less, it is very difficult to make a judgment based on the appearance of the graph. Only when we calculated the MGT’s, were we able to realize which variable had the greatest effect and which had the least. Table 5 presents all of the approximate MGT’s for each variable, for each different trial of the variable.
Figure 1 shows the growth curve of E.coli in regards to different temperatures. The MGT for 37 was about 73 minutes. The MGT for 33 was about 75 minutes. The MGT for 25 showed that the population was still growing beyond 90 minutes. I hypothesized that the higher temperatures would produce the most growth, but from the calculated results, my hypothesis was refuted.
Figure 2 shows the growth curve of E. coli with the nutrients. I predicted that MSGTYE would have the highest growth rate. I was proven wrong again. The MGT of MSG, MSGT, and MSGTYE were about 5 minutes, 56 minutes, and 50 minutes, respectively. Even though I believed that MSGTYE was going to have the greatest growth, I also predicted that MSG was going to have the lowest growth and this proved to be true.
Figure 3 represents the effect of aeration on the growth of E. coli and I hypothesized that the baffled flask would have the highest growth rate and that the “control” flask would have the lowest growth rate. As scene in Table 5, the MGT for the normal flask in the shaky water bath was about 43 minutes. For the baffled flask, the MGT was about 50 minutes. Surprisingly, the control flask, the stationary flask, does not have a MGT because its population is still growing.
From this lab, I learned that temperature, for the growth of E. coli increases with lower the temperatures. For E. coli affected by nutrients, I deduced that carbon and nitrogen help make better conditions for the E. coli to grow, but it does not respond as optimality to yeast extract. For the effects of aeration, we can say that E. coli doesn’t necessarily need oxygen for growth.
Some errors in this experiment could have occurred at the spectrophotometers readings. Students may have forgotten to re-zero the spec 20 before each new sample. Another source of error could be how temperature affects the bacteria. A student could have held a cuvette long enough to make the solution a little bit warmer, which could effect the growth curve for that sample.
For future research in this field, I would someday like to see if they could make a substance that would remove bacteria from skin. I could also see a substance that a human could digest to make the body resist all bacterial diseases. Although this seems crazy, bacteria can be limited by many factors. We live in the age of technology, and I believe that at this point, anything is possible.
Campbell, N.A., Reece, J.B., Mitchell, L.G. 1999. Biology. Menlo, CA: Addison
Wesley Longman, Inc.
Gregg, G., Hooke, A.M., McClure, J., Solomon, N.G. 2001. Laboratory Experiences for
Biological Concepts: Stucture, Function, Cellular, and Molecular Biology.
Oxford, OH: Miami University.
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