Samar Almarzooqi
Biology 110 Section 907
12/3/12
Lab Report
Bacterial Plasmid Antibiotic Resistance Genes in Chicken Farms
Introduction:
Bacterial contamination is often caused by the plasmids located within the
bacteria. Plasmids are “circular DNA molecules” separate from the chromosome that are
replicated and transmitted to daughter cells during mitosis (Hass and Ward, 2). Plasmids
often code for factors that allow the bacterium to live under environmental pressures.
One of the most important aspects of a plasmid is that they carry and spread antibiotic
resistance genes, making them immune to certain toxins. Bacteria with plasmids
containing antibiotic resistance genes have certain advantages because they are harder to
kill with antibiotics. Antibiotics are “produced by organisms such as fungi and bacteria”
and are utilized by scientists and researchers to prevent bacterial infections and
contamination (Hass and Ward, 2). One such example is the use of antibiotics in chicken
feed by chicken growers “in order to produce healthier chickens and prevent harmful
bacteria from getting into meat and eggs” (Hass and Ward, 2). Over time, the bacteria
develop antibiotic resistance, making it difficult to control their growth. As a result, the
frequency of antibiotic resistance amongst bacteria has increased.
Chicken farms use the antibiotic kanamycin, which helps to interfere with the
growth of bacteria. For the lab, three chicken farms, A, B, and C, experiencing problems
with Salmonella enteriditis, a bacteria contamination common to eggs, were examined.
S. enteriditis cause food poisoning and other health factors, which is why its growth
needs to be controlled and prevented. Scientists found that the bacteria contain plasmids
with antibiotic resistance to kanamycin, which means that they are resistant to the
antibiotic meant to keep them from growing. The three chicken farms, A, B, and C, were
isolated as the source of the contaminant eggs. Scientists and the FDA question whether
all three farms shared a common source for the bacterial contamination, or if the
kanamycin-resistant bacteria development occurs independently in each farm. (Hass and
Ward, 2).
Kanamycin resistance is controlled by three different genes that code for enzymes
that “chemically alter the kanamycin molecule” to make it inactive by disabling it from
reaching the ribosomes and keeping the bacteria from synthesizing proteins (Hass and
Ward, 3). The presence of kanamycin in chicken feed therefore has no affect on the
bacteria and does not prevent contamination due to the presence of the antibiotic
resistance in the plasmid.
Bacteria reproduce quickly and can grow “to very high concentrations under
optimal growth conditions” (Hass and Ward, 14). Samples of bacterial growth on agar
plates often lead to billions of bacteria per milliliter, or a “lawn” of bacterial growth,
which is uncountable. For this reason, in order to determine the concentration of
bacteria, a technique called serial dilution is used. Serial dilutions involve diluting the
bacterial sample so that colonies can be easily counted. The dilution is multiplicative,
diluting the sample by 1:10 in each step. With each dilution, 10 uL of bacteria to 90 uL
of dilutant is the ratio of bacteria to dilutant solution used. The concentration of bacteria
is decreased by the same constant each time, so using the equation B=N/D, where B=
the initial population size, N= number of colonies, and D= dilution factor, the original
concentration, B, of the bacteria can be determined for the (+/-) kanamycin bacteria
from the chicken farms (Graziano, 2012).
To examine the plasmid containing the kanamycin-resistance, PCR is used to
duplicate large amounts of specific DNA fragments. PCR utilizes the DNA polymerase
of bacteria who live in extreme conditions, meaning that their enzymes can function in
conditions that would normally denature proteins. DNA polymerase from the bacteria
Thermus aquaticus is often used, abbreviated Taq polymerase. With the involvement of
a DNA template and primers, new DNA can be replicated. PCR involves three different
parts: Denaturation, Annealing, and Elongation. In denaturation, the DNA is separated
by heating the solution to separate the double helix into two single strands. During
annealing, the DNA primers bind to the separate strands, which occurs once the solution
is cooled down to a lower temperature. In the final step, elongation, the solution is again
heated and the strands are elongated with the use of Taq polymerase, which binds free
nucleotides to their base pairs on the original template. This can be done many times to
create several copies of a DNA sequence (“Polymerase Chain Reaction”, 2012).
In order to determine the kanamycin-resistance plasmids from the bacteria
samples from the chicken farms, gel electrophoresis is used to create differing DNA
fragments and compare them to the known kanamycin-resistant genes. Gel
electrophoresis involves running a voltage across a gel with DNA inserted into different
wells. Over time, the DNA will travel from the negative end to the positive end because
DNA is negatively charged due to the phosphate groups present. Depending on the size
of the DNA fragments, the DNA will travel differing lengths. Larger DNA fragments
will travel a shorter length than the shorter DNA fragments. The gel used contains
DNA-binding dye and ethidium bromide, which bind to the DNA and allows the
fragments to be seen within the gel (Hass and Ward, 17).
The purpose of the lab was to determine whether the three chicken farms
containing the bacteria resistant to kanamycin shared a common source that caused
their bacteria to develop the resistance, or if the bacteria evolved to develop kanamycin
resistance independently. By observing factors like a shared food producer, supplier of
building materials, or source of laying hens, researchers can determine if the kanamycin
resistant bacteria came from a common source (Hass and Ward, 2). If no evidence links
the kanamycin-resistant bacteria, then the occurrence is unique and arises
independently within each farm. A solution to the rise of contamination must be
recommended in order to prevent further outbreak. By evaluating the frequency of
kanamycin-resistant bacteria, the severity of contamination can be determined and
further steps can be taken to prevent the outbreak from become more extreme. The
research questions guiding the lab procedures are:
1) Is the bacterial contamination at these three farms due to the same gene or different
genes?
2) What is the frequency of kanamycin resistant bacteria in the chicken farm cultures?
(Hass and Ward, 3)
With the understanding of how plasmids function in bacteria, our lab group
developed a null hypothesis that the kanamycin-resistance bacteria is due to differing
genes located in the plasmids that regulate enzymes that disable the kanamycin antibiotic.
The alternative hypothesis developed in the lab group was that the kanamycin-resistance
in bacteria is due to the same gene within the plasmid.
Methods and Materials:
The Procedure for the lab was taken from the Bio 110 handout, “Using Genes for
Antibiotic Resistance to Trace Sources of Bacterial Contaminations” by Hass and Ward.
Prior to the lab session, a prepared sample of bacteria from the farms A, B, and C were
taken and a serial dilution was prepared by placing 100 uL on +/- kanamycin plates. The
bacteria with kanamycin-resistant genes grew on the plates with kanamycin introduced,
and both the number of kanamycin-resistant and non-resistant bacteria were counted.
The bacteria containing the kanamycin resistance gene were then isolated and grown.
The plasmids from the bacteria were then inserted into the E. coli plasmid and grown on
non-kanamycin plates. The original bacterial cultures from each chicken farm each
underwent a serial dilution on two separate agar plate, +/- kanamycin. This was done in
order to determine the frequency of kanamycin resistant bacteria in the original bacterial
population. The data was provided to us in order to calculate the frequency of
kanamycin resistance at the chicken farms. The kanamycin resistance gene was then
transferred from the bacterial plasmid into E. coli plasmids in order to be able to study
the plasmid with a non-pathogenic bacterium.
During the lab session, bacterial colonies from the dilution plate with kanamycin
introduced were taken and put through PCR in order to replicate fragments of the DNA.
Then, the serial dilution plates were observed and lab groups counted the colonies on the
plate that yielded countable bacterial colonies for both the +/- kanamycin plates. By
comparing the number of bacterial colonies growing on the plate with kanamycin
compared to the plate without kanamycin for a serial dilution, a percentage can be
determined for the number of cells resistant to kanamycin. The products from PCR were
then loaded into a gel and underwent gel electrophoresis. The gel was created by
weighing 300 mg of agarose and mixed with 30 mL of 1x TAE buffer measured in a
graduated cylinder, was placed in a 125 mL Erlenmeyer flask. The flask was
microwaved for about 35 seconds and allowed to cool. Wearing disposable gloves, 1 uL
of ethidium bromide was added to the solution. The gel was then placed into the gel
electrophoresis machine within the slots. A current was then run through it, and once the
DNA fragments had traveled about halfway across the gel, a photograph was taken of
the gel. From the photograph of the completed gel, the size of the kanamycin resistance
genes from Farms A, B, and C could be determined and compared to the known sizes of
kanamycin resistance genes A, B, and C. The frequency of kanamycin resistance at the
chicken farms was also calculated, and the severity of the contamination was then
determined. Finally, a recommendation to the CDC was made on how to treat the
contamination problem.
Results:
Figure 1: Gel Electrophoresis of Plasmid A
Lab groups took pictures of individual plasmids that underwent gel electrophoresis. The
figure above shows the DNA fragments from the plasmid from the bacteria from Chicken
Farm A. The DNA fragments each traveled a different distance depending on size. The
gel includes a DNA ladder and controls A, B, and C for the three known kanamycin
genes. The DNA fragment from plasmid A is similar to the known kanamycin resistance
gene A; each DNA fragment traveled the same distance. The DNA ladder provides
sample to compare each other DNA fragment to and calculate the distance traveled.
Figure 2: Gel Electrophoresis of Plasmid B
The plasmid from the bacteria taken from Chicken Farm B is shown in the above figure.
The differing DNA fragments traveled different distances. The DNA ladder provides a
baseline to compare the other DNA fragments to. The known kanamycin resistant genes
A, B, and C are controls to compare the plasmid DNA from Farm B to. The plasmid from
Chicken Farm B is the same as the kanamycin resistant gene B according to the gel
above.
Figure 3: Gel Electrophoresis of Plasmid C
The plasmid from the bacteria taken from Chicken Farm C is figured above. The
plasmid, when compared to the three known kanamycin resistance genes, matches with
kanamycin resistant gene C. Similar to Figures 1 and 2, a DNA ladder and the three
controls A, B, and C for known kanamycin resistance genes are used.
Table 1: Number of Bacteria through Serial Dilutions for Chicken Farms A, B, and C
K (N= Number of Colonies)
Sample
Code
(Letter)
10^-2
10^-4
Farm A
Farm B
Farm C
lawn
432
120
20
11
21
10^-6
2
6
11
Non-K (N= Number of Colonies)
10^-2
lawn
lawn
lawn
10^-4
lawn
lawn
lawn
10^-6
496
1072
600
Data from different groups was compiled together in class data. The plates that were only
diluted by a small degree (10-2 and 10-4 ) were mostly not diluted enough to produce a countable
number of bacteria colonies, producing “lawns”. Bacteria from Farm B have the highest number
of colonies that grew on plates without the kanamycin resistance. Farm C has the highest
number of bacteria with the kanamycin resistance, with 11 colonies growing on 10-6 dilutant
plate and 21 colonies on the 10-4 dilutant plate.
Table 2: Countable Bacteria from Chicken Farms A, B, and C through Serial Titration
Sample Code (Letter)
Farm A
Farm B
Farm C
Number of viable bacteria in Original sample (B = N / D )
10^-2 10^-4
10^-6
4.98x10^9
1.08x10^10
6.11x10^9
The graph shows the number of viable bacteria calculated using the equation B =N/D from the
value from Table 1 to calculate the original number of bacteria from each farm before the
titration. The original concentration can only be calculated from 10-6 dilutant because the
other two contained lawns, which are uncountable. Farm B has the higher number of bacteria
from the original sample, Farm C has the second highest, and Farm A has the least amount of
original bacteria concentration.
Table 3: % Contamination of Bacteria from Chicken Farms A, B, and C
Farm A
Percent Contamination = level of bacterial
contamination x 100
0.133 %
Farm B
Farm C
0.187 %
0.61 %
Sample Code (Letter)
The % contamination represents the contamination efficiency of the bacteria from all three
farms, and contamination efficiency above 0% is attributed as successful. Farm C had the
most successful contamination rate (.61%) which means that .61% of the eggs from the farms
are contaminated. Farm B has the second highest percent contamination, .187%, and Farm A
has the least amount of percent contamination, .133%.
Table 4: Frequency of Antibiotic Resistant Bacteria in Chicken Farms A, B, and C
Sample Code (Letter)
Farm A
Farm B
Farm C
Frequency of antibiotic resistant bacteria = K / no K
10^-2
10^-4
10^-6
#VALUE! #VALUE!
0.004032258
#VALUE! #VALUE!
0.005597015
#VALUE! #VALUE!
0.018333333
The graph represents the frequency of antibiotic resistant bacteria compared to the bacteria
without the antibiotic resistance to kanamycin using the equation:
𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑘𝑎𝑛𝑎𝑚𝑦𝑐𝑖𝑛 𝑟𝑒𝑠𝑖𝑠𝑡𝑎𝑛𝑡 𝑏𝑎𝑐𝑡𝑒𝑟𝑖𝑎
𝐾
= 𝑛𝑜 𝐾 for the bacteria diluted to 10-6. Farm C
𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑏𝑎𝑐𝑡𝑒𝑟𝑖𝑎 𝑤𝑖𝑡ℎ𝑜𝑢𝑡ℎ 𝑘𝑎𝑛𝑎𝑚𝑦𝑐𝑖𝑛 𝑟𝑒𝑠𝑖𝑠𝑡𝑎𝑛𝑐𝑒
has the highest frequency of antibiotic resistance amongst the bacteria, 0.018, while Farm B
and A have similar frequencies, both smaller than that of Farm C, 0.006 and 0.004
respectively.
Sample Calculations:
Sample Equation 1: Table 2 Calculations
B= N/D
Farm A:
B= 496/ (1 x 10-6) = 4.98 x 109 bacteria
Sample Equation 2: Table 4 Calculations
Frequency of antibiotic resistant bacteria: K/no K
Farm A (10-6): 2/496= 0.004
Table 5: Identification of Plasmid Antibiotic Resistance for Chicken Farms A, B, and C
FARM
PLASMID
Plasmid B
Plasmid A
A
Plasmid C
X
X
B
C
X
Using the gel electrophoresis images in Figures 1, 2, and 3 of the plasmids from the
different Chicken Farms, the identity of the DNA fragments can be determined. Farm A
bacteria has resistance gene for kanamycin A. Farm B bacteria has the resistance gene for
kanamycin B. Farm C bacteria has the resistance gene for kanamycin C.
Table 6: Recommendation Guidelines for Bacterial Contamination at Egg Producing
Facilities

Level of Contamination
Bacterial contamination < 5%






Bacterial contamination between 6-30%
Bacterial contamination >31%

Standard Recommendations
Divert eggs to pasteurization facility until
contamination levels have been <1% for
8 weeks
Monitor farm weekly
Identify source(s) of contamination
Change antibiotic regime




Destroy all eggs until levels have been
<1% for 8 weeks
Identify and destroy infected individuals
Monitor farm weekly
Identify source(s) of contamination
Change antibiotic regime




Cull entire population
Disinfect entire facility
Identify source(s) of contamination
Submit contamination prevention plan
From “Using Genes for Antibiotic Resistance to Trace Sources of Bacterial
Contaminations” by Hass and Ward. Using the table above, one the level of
contamination has been determined for each farm, the steps above are the precautions that
need to be recommended to each farm.
Discussion:
From the data presented in the Results section, the research questions the lab sought to
answer can be explained and determined.
1) Is the bacterial contamination at these three farms due to the same gene or different
genes?
2) What is the frequency of kanamycin resistant bacteria in the chicken farm cultures?
The first question can be answered by interpreting the images for the gel
electrophoresis of the three plasmids from the three farms. For each gel, a sample of the
DNA fragment after PCR was conducted was placed in a well. A DNA ladder and three
controls of the three known kanamycin resistant gene in bacteria (A, B, and C) were also
placed in differing wells. By comparing the distance the plasmid from Farm A traveled, it
matches the distance traveled by the bacteria kanamycin resistance gene A. Both DNA
fragments, meaning that they are the same size, therefore the same gene. By observing
the images of gel electrophoresis for plasmids from Farms B and C, it can be determined
that the plasmid from Farm B contains gene B for the kanamycin resistance gene and
Farm C bacteria with kanamycin resistance contains gene C. Due to the differing genes
for kanamycin resistance genes amongst the three farms, the bacterial contamination is
due to separate genes. If they were due to the same genes, then all of the plasmids from
all three farms would have the same band distance after gel electrophoresis because they
would all be the same size. Because the source of contamination is due to separate genes,
then the contamination is unique to each farm and did not stem from a common source
like common feed producers or building material manufacturers each farm uses.
Therefore, each farm experienced a different source of contamination for bacteria S.
enteriditis, leading to separate antibiotic resistance genes to kanamycin in the chicken
feed. This conclusion supports the null hypothesis adapted by the group that the
kanamycin-resistance bacteria from the three farms stems from differing genes located in
the plasmids that regulate enzymes that disable the kanamycin antibiotic. The alternative
hypothesis that that the kanamycin-resistant bacteria is due to the same gene within the
plasmid does not hold true because as evidence by gel electrophoresis of the bacterial
DNA from the three farms, the genes for the kanamycin resistance are different.
The number of colonies of bacteria from the three farms growing on the plate with
kanamycin introduced represents the bacteria with the kanamycin resistance gene. A
serial dilution needed to be conducted because for both the 10-2 and 10-4 had lawns of
bacteria, making it uncountable. For the bacteria growing on the dilutant 10-6 plate, the
number of colonies could be counted for both the non-kanamycin plate and kanamycin
plates. Table 1 shows that Farm C had the greatest number of bacterial colonies that grew
on the plates with kanamycin, meaning that it had the greatest number of bacteria with
kanamycin resistance genes. From Table 1, the original number of colonies from each
farm were determined in Table 2 using the equation B=N/D. The values of B, the original
number of bacteria, are represented in Table 2. The bacterial concentration from the three
farms range from the highest concentration in Farm B, 1.08x1010 bacteria, to the lowest
concentration from Farm A, 4.98 x 109 bacteria. Farm C had the middle concentration of bacteria
in the original sample, 6.11 x 109 bacteria.
The original number of colonies of bacteria from each farm is used to determine the
percent contamination in Table 3. The percent contamination represents the percent efficiency of
the plasmid transfer from the S. enteriditis bacteria to the E. coli plasmid used in the lab due
to the danger of using the harmful bacteria contaminating the eggs and leading to
diseases. A percent contamination about 0% is classified as successful, but the higher
percentages represents a more successful and efficient transformation. Farm C had the
greatest percent contamination, 0.61%. Farm B had the second higher, 0.187% and Farm
A had the lowest percent contamination, 0.133%. All three bacteria samples from the
three farms were efficiently transformed into the E. coli, but the percentages are still very
low, all less than 1.0%. The sources of error in the transformation of the plasmid to the E.
coli plasmid can be due to error in the laboratory procedures. Incorrectly counting the
number of bacteria growing on the plates leads to an inaccurate original concentration of
bacteria, and because there were many colonies even in the serial dilution plates, lab
groups still had to count hundreds of colonies. Overestimating the number of bacterial
colonies growing on the non-kanamycin plate leads to a smaller percent contamination
value since the number of bacterial colonies growing on plates with kanamycin resistance
were easy distinguishable and countable.
Addressing the second research question of the lab, the frequencies of kanamycin
resistance in chicken farm cultures are shown in Table 4. As a class, the frequencies were
calculated since each lab group examined bacteria from one of the three farms. The
frequencies of antibiotic resistance were calculated by using the question: K/no K from
Table 1. Farm C had the highest frequency of antibiotic resistance to kanamycin amongst
the bacteria, 0.018. Farm B had the second highest, 0.006 frequency of antibiotic
resistance, and Farm A had the lowest frequency of antibiotic resistant bacteria,
0.004.The order Farm C, Farm B, Farm A represents both the ranking from highest to
lowest frequency and the ranking of percent contamination for the recombination of
efficient transformation.
Using the Table 6, recommendations need to be given to each farm depending on
the bacterial contamination percentage. All three farms had a level of contamination
<5%, which means that all three farms are recommended to follow the same steps to
make sure a contamination outbreak does not occur again. All three farms should move
all eggs produced to a pasteurization facility until percent contamination levels are below
1% for about 8 weeks. The farm needs to identify the sources of contamination, and since
the kanamycin resistant bacteria all had separate genes, A, B, or C, the source of
contamination is most likely not similar amongst the farms. The antibiotic regime of
kanamycin in the chicken feed needs to be changed since the bacteria have evolved to be
able to disable the kanamycin antibiotic from working, and a monitoring of the farm
would ensure that the eggs are not being subject to contamination again (Hass and Ward,
12).
Sources of error in the lab could have occurred in many different steps since the
lab required a lot of precise measurements to be conducted, especially in the PCR and gel
electrophoresis portion. For gel electrophoresis, similar quantities and concentrations of
DNA needed to be placed into the wells without contamination. Any error could
influence the behavior of the DNA strands once the current was run across the gel. If too
much DNA samples were placed into wells, then the DNA would not travel as far across
the gel electrophoresis not because of the size of the DNA fragments, but because of the
concentration and amount of DNA added to the wells. Other sources of error include
human error in counting the number of bacterial colonies on the plates. Any
miscalculation impacts the calculations for frequency and percent contamination of each
farm due to the bacterial development of the antibiotic resistance to kanamycin gene.
For future experiments to perform, it would be useful to further study the
development of antibiotic resistance in bacteria because if the development of antibiotic
resistance could be controlled and depleted, antibiotics would be more effective and new
treatment options would not have to be examined every time a strain of bacteria
developed resistance to antibodies. One such experiment could be comparing the
frequency of antibody resistance for two separate antibodies to determine the most useful
and efficient antibody to use for chicken feeders. A study conducted by Dr. Levy in “The
Spread of Antibiotic Resistant Bacteria from Chicken to Farmers” involved the usage of a
separate antibiotic, tetracycline, to determine the frequency of the development of
antibody resistance amongst the bacteria (Solomon, 2011). According to the study, within
a week of the introduction of the antibiotic to the chicken feed, almost all of the bacteria
contained tetracycline resistant genes. Depending on the antibiotic, there are different
rates of the development of the resistance, some much more easily than others. By
examining the differing frequencies of antibiotic resistance development for differing
antibiotics, a more effective antibiotic can be developed and used (Solomon, 2011). The
same procedures conducted in this lab would be conducted, but multiple times using
differing antibiotics. The frequencies of antibiotic resistance would be examined and the
bacteria with the least frequency would be the most successful antibiotic because the
bacteria is then less likely to develop resistance at a faster rate.
Conclusion:
From the results of frequencies of the antibiotic resistance kanamycin in the lab,
Farm C was determined to have highest frequency, 0.018. All three farms had percent
contaminations less than 5%, which means all three farms need to take similar steps to
prevent future or further breakout, which includes monitoring the eggs. From gel
electrophoresis, the kanamycin resistance genes for the bacteria from the three farms
was determined to be different, Farm A had gene A, Farm B had gene B, Farm C had
gene C. The null hypothesis was accepted because it was determined that bacterial
contamination at these three farms was due to different genes, and therefore did not stem
from a similar source. Further studies should be researched to determine the most
efficient use of antibiotics that limit the ability of the bacteria to develop the resistance
because antibiotics provide a way to prevent bacterial contamination.
Resources:
Cyr, R., 2002. Title of the tutorial being cited. In, Biology 110: Basic concepts and
biodiverity course website. Department of Biology, The Pennsylvania State
University. http://www.bio.psu.edu/
Cyr, R., Hass C., Woodward D., and Ward A., 2010. Using Genes for Antibiotic
Resistance to Trace Source(s) of Bacterial Contamination. In, Biology 110: Basic
concepts and biodiverity course website. Department of Biology, The
Pennsylvania State University. http://www.bio.psu.edu/
Graziano, Maria. “Serial Dilution.” Class lecture, Pennsylvania State University,
State College, PA, October 22, 2012.
“Polymerase Chain Reaction”. Cold Spring Harbor Laboratory, 2012. Web.
Solomon, Gina. The Spread of Antibiotic Resistant Bacteria from Chickens to Farmer.
Natural Resources Defense Council, 2011. Web.