Adil Sabir

Bio 110H

24 November 2014

Antibiotic Resistance Lab Report

I. Introduction

Bacterial plasmids are small, circular molecules of DNA that can be found in

bacteria (Hass, Richter, Ward, 2014). Plasmids are physically separate and can replicate

independently from the bigger bacterial chromosome; they are replicated by enzymes and

transmitted to daughter cells during the process of cell division. Plasmids can be transferred by

the process of transformation and conjugation (R. Giraldo, 2014). In the presence of some

antibiotics, which are used to treat diseases, plasmids that have a selective advantage where some

can contain genes that are resistant to the antibiotic (Hass, Richter, Ward, 2014). Through

humans’ frequent use of antibiotics, we have significantly increased the frequency of antibiotic

resistant genes.

Cattle farmers and growers feed their livestock sub­therapeutic amounts of antibiotics to

function as a growth enhancer (Hass, Richter, Ward, 2014). One of the most frequently used

antibiotics is tetracycline. Tetracycline is a drug that is commonly used to treat bacterial

infections such as urinary tract infections, chlamydia, and acne (Drugs.com “tetracycline

antibiotics”, 2014). Tetracycline affects bacterial growth because it interacts and interferes with

a group of ribosomes that are responsible for translation therefore, inhibiting protein synthesis

(Hass, Richter, Ward, 2014). Since plasmids can spread by transformation and conjugation,

bacteria that are resistant to antibiotics can reproduce rapidly in the presence of antibiotics.

Reports of severe gastroenteritis caused by consumption of raw or undercooked meat led

the FDA to investigate this outbreak (Hass, Richter, Ward, 2014). Scientists discovered that the

Escherichia coli bacteria, which contains tetracycline resistant genes, was responsible for the

outbreak. Three cattle farms, Speedy’s Beef Farm (Farm A), Calli’s Cows and Bulls (Farm B),

and Green Acres Cattle (Farm C) were all contaminated by the Escherichia coli bacteria. A

pressing question we must ask is whether each occurrence of tetracycline resistant bacteria is

unique to each farm, or whether there is a shared source of contamination for these three farms.

Scientists already know that three different genes are commonly known to be responsible for

tetracycline resistance. These genes have risen independently of each other and can be

differentiated by their individual sizes (Hass, Richter, Ward, 2014). It is important for us to know

which specific gene is present at which farm because they require different treatments.

Bacteria reproduce rapidly and can grow to very high concentrations which can

sometimes be uncountable and are referred to as a “lawn.” For this reason, we used the technique

of serial dilution to easily count the number of colonies. Serial dilution is multiplicative; with

each dilution, we added 10 uL of bacteria to 90 uL of solution. Using the equation B=N/D where

B is the initial population size, N is the number of colonies, and D is the dilution factor, the

original concentration of bacteria can be calculated and can be found in the results section (Hass,

Richter, Ward, 2014).

To examine the plasmids containing Tetracycline resistant genes, we used a polymerase

chain reaction (PCR) to replicate large amounts of specific DNA fragments. PCR utilizes the

DNA polymerase in bacteria and allows their enzymes to function at extreme temperatures

which they would normally be denatured in. The DNA polymerase we used in this experiment

was called Taq polymerase. PCR occurs in three steps; in the first, called denaturation, DNA is

heated and separated into two strands. In the next step, annealing, the strands are cooled down

and DNA primers bind to each end. Finally, in elongation, Taq polymerase binds free

nucleotides to their base pairs and elongates the strand (Hass, Richter, Ward, 2014).

To determine the tetracycline resistant genes from the samples of the cattle farms, we

used gel electrophoresis to create distinct DNA fragments and compare them to the known

tetracycline resistant genes. To do this, we ran a voltage across a gel with DNA placed into

different wells. The DNA will travel from the negative end to the positive end; larger molecules

will travel shorter distances while shorter molecules will travel further. We can then compare the

sizes of these samples to the known sizes of Tetracycline resistant genes.

The two main purposes in performing this lab and that guide our procedure is to

determine whether the tetracycline resistant bacteria present was unique to each farm or came

from a shared source of contamination as well as to determine the frequency of tetracycline

resistant bacteria at each farm (Hass, Richter, Ward, 2014). By comparing factors such as

tetracycline resistance frequency and gene size, we can determine if the tetracycline resistant

bacteria came from a common source. By determining the frequency of tetracycline resistant

bacteria, we can then determine the severity of contamination and take the necessary further

steps.

After understanding the function that plasmids serve in bacteria, we developed a

hypothesis that the tetracycline resistant bacteria is due to differing genes located within a

plasmid that neutralize enzymes which regulate the tetracycline antibiotic.

II. Materials and Methods

The methods for this lab are explained in the Biology 110 Lab Manual. We begin

by taking three tetracycline plates and labeling each adequately with our name, date, section, and

dilution factor (10^­2, 10^­4, and 10^­6). We then took three empty, sterile microtubes, added

990 uL of water to each, and performed our appropriate dilutions with each different dilution

factor. We then lined up our three petri dishes and using a pipettor, inoculated each dish with 100

uL of sample bacteria based on appropriate dilution factor and using a new pipette tip for each.

Then, using glass beads, we shook the dish back and forth starting with the 10^­6 dish and

working down to effectively spread the bacteria throughout the agar. After disposing of the beads

in the biohazard bag, we stacked our petri dishes, taped them together, and labeled them.

During the next lab, we put the bacterial colonies from the plates through PCR to

replicate fragments of DNA. We began by using the orange, blue, and yellow primers that were

provided and mixed these primers with the colonies; orange to colony one, blue to colony two,

and yellow to colony three. We then proceeded to load these tubes into the PCR. Next, we

counted the number of colonies growing on the tetracycline plate as well as the non­tetracycline

plate. By comparing these two totals, we can determine the percentage of cells resistant to

tetracycline.

After PCR, the products underwent gel electrophoresis. We made the gel by weighing out

300 mg of agarose and mixing it with 30 mL of 1x TAE buffer, measured in a graduated

cylinder, into a 125 mL Erlenmeyer flask. After swirling the mixture, we heated it for 35 seconds

and let the solution cool for two minutes. After cooling, we put on disposable gloves and added 1

uL of ethidium bromide to the solution. We then poured our molten agarose into the gel tray after

making sure the dams were snugly wedged into place. After allowing the gel to harden, we

poured the electrode buffer into the unit and removed the comb. We loaded 5 uL of PCR DNA

ladder into the first well, and then 15 uL from our six colored tubes into the preceding six wells

and ran a current through it. Once the DNA fragments had traveled halfway across the gel, a

photograph of the gel was taken. From the photo, we could tell the sizes of the tetracycline

resistant genes from the three farms and compare this to the sizes of the known resistant genes.

We then determined the frequency of tetracycline resistance and made a recommendation to the

FDA on how to treat the problem (Hass, Richter, Ward, 2014).

III. Results

Each lab group took pictures of individual plasmids after undergoing gel electrophoresis. This

picture shows our plasmid sample from Farm B, or Calli’s Cows and Bulls.

Table 1: Number of Bacterial Colonies on +/­ Tetracycline Dilution Plates (Farm B)

Treatment Dilution Dilution Dilution

10^­2 10^­4 10^­6

Volume Plated 100 uL 100 uL 100 uL

Tetracycline 0 92 15

No Tetracycline Lawn 500 66

(Hass, Richter, Ward, 2014)

Table 2: Number of Countable Bacteria (Farm B)

Number of Bacteria in

Original Sample

(B=N/D)

Number of Bacteria

in Original Sample

(B=N/D)

Number of Bacteria

in Original Sample

(B=N/D)

Dilution Factor 10^­2 10^­4 10^­6

Tetracycline 0 9.2x10^5 1.5x10^7

No Tetracycline Lawn 5.0x10^6 6.6x10^7

B=N/D

Frequency= (B tetracycline/B non tetracycline)x100

=((N tetracycline/D tetracycline)/(N non tetracycline/D non tetracycline))x100

Sample Calculation for Farm B Group 1:

((92/10^­4)/(66/10^­6))x100

=1.39%

Farm B Group 2= .016%

Farm B Group 3= .028%

Avg for Farm B= .48%

Table 3: Summary of Tetracycline Resistance in Beef Farms

Group Beef Farm Tetracycline Resistant Gene

Tetracycline Resistant Gene

Tetracycline Resistant Gene

Frequency of Resistance

Comments

1 (A) 2(B) 3(C)

1 A X .11% Image did not show up well but a better image was given

2 B X .48%

3 C X .13%

4 B X .09% Band lined up with plasmid but also with another band that had no reference.

(Hass, Richter, Ward, 2014)

Table 4: Recommendation Guidelines for Bacterial Contamination at Meat Producing Facilities

Level of Contamination Standard Recommendations

If the Bacterial contamination is < 1% Send all meat to a pasteurization facility elsewhere until contamination levels are leveled out to < 1% for 8 weeks or longer

Farm must be monitored weekly The source of contamination must be

identified Antibiotic regime must be changed

If the Bacterial contamination is between 2% and 30%

All meat must be disposed of safely until contamination levels are reduced to <1% for 8 or more weeks

All those infected must be identified and properly treated

Farm must be monitored weekly The source of contamination must be

identified Antibiotic regime must be changed

If the Bacterial contamination is > 31% Entire infected population must be identified and treated

All meat must be disposed of in an orderly, safe fashion

Entire facility must be completely disinfected

The source of contamination must be identified

A contamination prevention plan that entails how appropriate steps will be taken to hinder contamination in the future must be submitted

(Hass, Richter, Ward, 2014)

IV. Discussion

After analyzing the data present in our results, we can then answer and explain the

research questions: Is the bacterial contamination at each farm due to the same gene or

genes independent of each other? And what is the frequency of tetracycline resistant

bacteria at each farm?

We can answer the first question by interpreting the images of the gel

electrophoresis of the plasmids from the three different farms. Since the photo for Farm B

was presented in the results section, we can use this image as our example. By comparing

the distance that the plasmid from Farm B traveled to the distance that the tetracycline

resistant gene B traveled, we can see that these distances are identical. We know that the

distance traveled is based off size; smaller plasmids will travel further distances and vice

versa. We can infer that the these plasmids are the same size and therefore, the same

gene. In farms A and C, we observed different band patterns than Farm B, however the

distance traveled in Farm A matched that of Gene A and the distances in Farm C matched

that of Gene C. With this information, we can conclude that all of three farms matched

with different tetracycline resistant genes and did not come from a common source of

contamination. This conclusion supports our hypothesis that the tetracycline resistant

bacteria from the three farms all come from different genes.

To address the second question, we can reference Table 4 which provides the

frequency of resistance for each individual farm. We were able to calculate the frequency

by using the formula: Frequency= (B tetracycline/B non tetracycline)x100 and then

expanding it to Frequency=((N tetracycline/D tetracycline)/(N non tetracycline/D non

tetracycline))x100. While our lab group only calculated the frequency for Farm B, the

other groups in the class calculated the frequencies for Farm A and Farm C. While one

group of Farm B had the lowest frequency at .09%, the other group of Farm B had the

highest frequency at .48%.

Using Table 4, we can determine the severity of the level of contamination and

the necessary steps we will have to take once we know these levels. All three farms had a

level of contamination that was less than 1%, therefore all farms are recommended to

follow the same steps. They should all move the meat that is currently in at the farm to an

alternative facility until the contamination levels at at a constant 1% or less for 8 or more

weeks . The farm should also be monitored weekly and change its antibiotic regime. Most

importantly, the source of contamination should be identified and eliminated to ensure

that it does not cause contamination again (Hass, Richter, Ward, 2014). While all three

farms had different sources of contamination and different tetracycline resistant genes,

they all must take similar steps to prevent further or future outbreaks.

Sources of error in this lab could have existed in numerous places. Most

obviously, we could have forgotten to wipe down our lab station before performing the

experiment. This could have led to contamination and could have skewed our results. A

common source of human error could have simply been in counting the colonies of

bacteria. This would have skewed the numbers for the frequency of resistant genes and

the level of contamination. Another error that could have occurred is in the precise

measurement we had to take during serial dilutions, PCR, and gel electrophoresis. If we

measured too much or too little of something, it could have affected our DNA replication

in PCR or how far the plasmids traveled in electrophoresis. This could have a great

influence on our results.

For future experiments, we can further test and examine the frequency of

antibiotic resistant plasmids and genes. This is a very important topic because if the

frequency for an antibiotic resistant gene increases to a very high number, then we have

no method of treating the infected organism or product. One possible experiment could

be to examine a gene with antibiotic resistance and try to determine what exactly makes it

resistant and if there are any selective pressures to make the gene act a certain way, and

also if there are ways that we can manipulate the gene to make it non­resistant (“AUPA”,

Tufts). If we can figure out why genes are resistant and nonresistant and manipulate them

to behave a certain way, it would be a huge breakthrough for the medical community and

we could treat infected patients more effectively.

Works Cited

Biology 110 Laboratory Manual 2014

Del Solar, Gloria, Rafael Giraldo, Maria J. Ruiz­Echevarria, Manuel Espinosa, and Ramon

Diaz­Orejas. "Replication and Control of Circular Bacterial Plasmids." N.p., n.d. Web. 22

Nov. 2014.

Nature.com. Nature Publishing Group, n.d. Web. 29 Nov. 2014.

"Tetracycline (Antibiotics) Uses, Dosage, Side Effects ­ Drugs.com." Tetracycline (Antibiotics)

Uses, Dosage, Side Effects ­ Drugs.com. N.p., n.d. Web. 29 Nov. 2014.