MRSA Case Study*

 

Measuring Resistance

Katelyn was excited to start her summer job in her microbiology professor’s research laboratory. She had enjoyed Dr. Johnson’s class, and when she saw the flyer recruiting undergraduate lab assistants for the summer, she had jumped at the opportunity. She was looking forward to making new discoveries in the lab. On her first day, she was supposed to meet with Dr. Johnson to talk about what she would be doing. She knew the lab focused on antibiotic resistance in Staphylococcus aureus especially MRSA (methicillin-resistant S. aureus).

 

She still remembered the scare her family had last year when her little brother, Jimmy, got so sick. He had been playing in the neighborhood playground and cut his lip when he fell off the jungle gym. Of course, he always had cuts and scrapes—he was a five-year-old boy! This time though his lip swelled up and he developed a fever. When her mother took him to the doctor, the pediatrician said the cut was infected and had prescribed cephalothin, an antibiotic related to penicillin, and recommended flushing the cut regularly to help clear up the infection.

 

Two days later, Jimmy was in the hospital with a fever of 103°F, coughing up blood and having trouble breathing. The emergency room doctors told the family that Jimmy had developed pneumonia. They started him on IV antibiotics, including ceftriaxone and nafcillin, both also relatives of penicillin.

 

It was lucky for Jimmy that one of the doctors decided to check for MRSA, because that is what it was! MRSA is resistant to most of the penicillin derivatives. Most cases of MRSA are hospital-acquired from patients who are already susceptible to infection, but the ER doctor explained that community-acquired MRSA was becoming more common. The doctor then switched the treatment to vancomycin, a completely different kind of antibiotic, and Jimmy got better quickly after that.

 

Katelyn had dropped Jimmy off at swimming lessons just before coming to work at the lab. As she waited in the hallway for Dr. Johnson, she hoped that she would be at least a small part of helping other people like Jimmy deal with these scary resistant microbes. She was surprised when the professor burst out of the lab, almost running into her.

 

“Hi Katelyn, I’m really sorry but I have to run to a meeting right now—they sprung it on me last minute. There are bunches of plates in the incubator right now that need their zones of inhibition measured. I’ll be back in a few hours,” Dr. Johnson said as he rushed down the hallway with a stack of folders. Katelyn dug out her old lab notebook to look up what she was supposed to do. She found the lab where she and her fellow students had examined the antimicrobial properties of antibiotics using the Kirby-Bauer disk diffusion technique. Looking at the plates Dr. Johnson had told her about, she saw they had all been “lawned,” or completely coated with microbes to make a thick hazy layer over the agar surface. She could also see paper disks with letters on them, and some of the disks had clear zones around them where the microbe had been inhibited (Fig. 1). Her notebook explained how to measure the zone of inhibition around the disks (Fig. 2).

 

Plate 1.

Plate 2.

Plate 3.

S. aureus

PE

CE

ME

VA

S. aureus

PE

CE

ME

VA

S. aureus

PE

CE

ME

VA

PE

CE

ME

MRSA

VA

PE

CE

ME

MRSA

VA

PE

CE

ME

MRSA

VA

 

Figure 2. Katelyn’s diagram of how to measure a zone of inhibition from her microbiology lab notebook.

 

Exercise 1

 

Measure the zones of inhibition for each antibiotic on the plates shown in Figure 1 and note the measurements in the spaces in Table 1 below. (Note: Th e Kirby-Bauer method is standardized so that no zone of inhibition is scored as a 0, and all others include the disk as part of the zone.)

 

Key: PE = penicillin, ME = methicillin, CE = cephalothin, and VA = vancomycin

 

Plate		S. aureus	MRSA
1	PE
	ME
	CE
	VA
2	PE
	ME
	CE
	VA
3	PE
	ME
	CE
	VA

 

 

An average, or mean (x), is a measure of central tendency in the data, or what value occurs in the middle of the data set. The mean is calculated by adding up all the values for a given set of data, then dividing by the sample size

 

Average

 

Standard deviation measures the spread of the data—as in how variable the data set is. The standard deviation (s ) is calculated by the following:

 

Standard deviation

 

Standard error measures the difference between the sample you have taken and the whole population of values. The standard error (SE) is calculated as follows:      s

 

Standard error SE=

 

Exercise 2

 

In Table 2 below calculate and record the averages and standard errors for each antibiotic in S. aureus and MRSA.

 

	S. aureus		MRSA
	Average	SE	Average		SE
PE
ME
CE
VA

 

Exercise 3

 

Now, redraw Tables 1 and 2 into a single, more organized table. Be sure to label the table appropriately.

 

Click here to redraw table.

 

 

 

Exercise 4

 

Graph the results from Table 2. Be sure to label the figure and the axes correctly.

 

Graph the results here.

 

 

 

 

Questions

 

1. What do you think the experimental question is?

 

2. What hypotheses can you come up with to answer the experimental question? Click here to enter text.

 

3. If your hypothesis is correct, what would the plates look like (i.e., what predictions would you make for each hypothesis)? Click here to enter text.

 

4. Is the experiment you just collected data for an appropriate test of the experimental question you came up with in your answer to Question 1? Click here to enter text.

 

5. Which antibiotics where most effective against S. aureus? Which antibiotics where most effective against MRSA? Click here to enter text.

 

6. When comparing the antibiotics effective against both, were there differences in effectiveness? Click here to enter text.

 

What other questions do the data shown in Figure 1 make you think of? Click here to enter text.

 

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