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A Pointer

For my Microbiology students….

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“I feel kinda sick”

As we finish up the year dividing out time between Immunology and Epidemiology, you may find it useful or just interesting to take a look at the online Epidemiology course offered at Coursera. It is a six-part course taught by Lorraine Alexander and Karin Yeatts of the University of North Carolina, Chapel Hill.

As all Coursera classes, this is 100% free unless you would like to receive a signed certificate of completion.

Enjoy.

 
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Posted by on November 21, 2014 in Uncategorized

 

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Epidemiology: Should farmers try to do more work near noon?

The CDC has a wealth of classroom information (case studies, discussion material) regarding epidemiology. No surprise there. It’s what they do.

In my Microbiology class we’re starting a unit on epidemiology that students are working on in their free time either alone or in groups. We will talk about the project as questions come up, but mostly, I wanted people to have an opportunity to think freely – i.e. without me forcing my own ideas on them.

In my Ecology (population genetics, etc) class, we just spent some time last week discussing how data is just data, and in the absence of a reason to mistrust it, it probably makes sense to assume that the data is correct. However, this leaves the interpretation of the data up for much debate. ‘How so?’ I was asked. ‘Because people run experiments with certain ideas in mind that they would like to support or undermine. There can be many ways to misinterpret data.’

With this in mind, I ask you…

Should farmers try doing more work near noon?

Data suggests that this is the safest time of day. Yet, anecdotally, fewer farmers are putting time in the field at this hour than any other hour of the day(8am-8pm). What’s going on?

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Posted by on April 21, 2014 in Uncategorized

 

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An Epidemiological Method: Using RFLP to Identify Strains of Pathogens

An excellent classroom resource for a case study in epidemiology is presented by the CDC. This study walks students through an outbreak of E. coli O157:H7 in Michigan.

The purpose of this study is to provide student investigators with the opportunity to walk through the procedures and rationale behind investigating the etiology and to develop experiments testing hypotheses generated by the students.

I am using this exercise as an end-of-semester project for my microbiology students to work through collaboratively now that we have completed our discussion of Paul Offit’s Vaccinated.

The study begins:

PART I – OUTBREAK DETECTION

 

Escherichia coli O157:H7 was first identified as a human pathogen in 1982 in the United States of America, following an outbreak of bloody diarrhea associated with contaminated hamburger meat. Sporadic infections and outbreaks have since been reported from many parts of the world, including North America, Western Europe, Australia, Asia, and Africa. Although other animals are capable of carrying and transmitting the infection, cattle are the primary reservoir for E. coli O157:H7. Implicated foods are typically those derived from cattle (e.g., beef, hamburger, raw milk); however, the infection has also been transmitted through contact with infected persons, contaminated water, and other contaminated food products.

Infection with E. coli O157:H7 is diagnosed by detecting the bacterium in the stool. Most laboratories that culture stool do not routinely test for E. coli O157:H7, but require a special request from the health care provider. Only recently has E. coli O157:H7 infection become nationally notifiable in the U.S. Outside the U.S., reporting is limited to a few but increasing number of countries.

In the last week of June 1997, the Michigan Department of Community Health (MDCH) noticed an increase in laboratory reports of E. coli O157:H7 infection. Fifty-two infections had been reported that month, compared with 18 in June of 1996. In preliminary investigations, no obvious epidemiologic linkages between the patients were found.   The increase in cases continued into July.

Students are then asked a number of introductory questions and then presented with the following problem:

Compare the DNA fingerprints in Figure 2 from seven of the Michigan E. coli O157:H7 cases. Each isolate has its own vertical lane (i.e., column). Controls appear in lanes #1, 5, and 10. Which Michigan isolates appear similar?

This question requires some background in DNA Fingerprinting (aka Restriction Fragment Length Polymorphisms, or RFLPs), which I want to take some time to explain.

As the source material states, The purpose of this test is to identify common strains of organisms through their DNA banding pattern. “Different DNA composition will result in different PFGE banding patterns. Bacteria descended from the same original parent will have virtually identical DNA and their DNA fingerprints will be indistinguishable. Identification of a cluster of isolates with the same PFGE pattern suggests that they arose from the same parent and could be from the same source. “ (emphasis mine).

The method involves two core techniques. First, DNA from the target organism must be isolated and cut with one or more restriction enzyme(s). This will create a number of DNA fragments, where the precise number and size of fragments is determined by the sequence of that organism’s DNA.

As an example, let’s imagine a 10,000 base pair (bp) chromosome that we intend to cut with the restriction enzyme, EcoRI. EcoRI recognizes and cuts double stranded DNA at a specific sequence of 6 bases.

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Figure: DNA cut by the Restriction Enzyme, EcoRI. A. DNA sequence with EcoRI recognition site highlighted and cut pattern illustrated. B. Enzyme binds to DNA at the recognition site. C. DNA has been cleaved.

On average, this enzyme will cut a random sequence of DNA every 4096 bases (this can be estimated by 4 raised to the power of n, where n = the number of bases in the enzyme’s recognition sequence , or 46 = 4096 in this case.) In our example, this suggests that a 10,000 bp chromosome will have two EcoRI sites by random chance.

The circular chromosome should be cut twice by this enzyme, resulting in two fragments of DNA (see note #2, below). Let’s say the two bands are 4000 bp and 6000 bp.

We can see these two fragments by running them through agarose, which works as a molecular sieve, to separate the two fragments by size

How does this work?

DNA is a negatively charged molecule with that charge spread uniformly across the length of the fragment. Therefore, there is no difference in charge between our two fragments, except in proportion to their length. This means that as they run through the sieve, the only difference between the molecules comes from their lengths. As any sieve, smaller objects go through easier, while larger ones are held up.

ImageThe result is that the two fragments will appear as distinct bands on a gel, with the smaller fragment running farther through the agarose that the larger. (here, the smaller band at the bottom of the gel has migrated farther toward the positive electrode)

If someone new were to become infected with this bacteria, we could isolate it from them, digest the DNA and get the same banding pattern. A closely related bacteria may have one additional EcoRI site. This would result in one of the two bands being cut into two smaller fragments, meaning that the two strains could be easily distinguished.

Back to the question posed above…

Given this, examine the following compilation of samples. Controls appear in lanes #1, 5, and 10. Which of the remaining isolates appear similar?

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Definitions:

  1. Restriction Enzyme or Restriction Endonuclease– an enzyme that can recognize and cut DNA.
  2. Recognition Sequence – the sequence of bases that a restriction enzyme recognizes and binds to.

 

Notes:

  1. In my example, we are using the restriction enzyme, EcoRI, to cut DNA from E. coli. As the name suggests, EcoRI actually derives from E.coli, where it functions as a defence against invading DNA, i.e. a virus. In order to do this successfully, E. coli will either not have any EcoRI restriction sites in its own DNA, or it will protect them by methylation so that the enzyme does not destroy the host’s own DNA. I am ignoring the possibility that the DNA we are dealing with in our experiment may not be cleavable with this enzyme.
  2. Also note, that bacterial chromosomes are circular, rather than linear – interestingly, this means that they are not actually ‘chromosomes’ at all. Again, let’s ignore this.
 
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Posted by on April 18, 2014 in Uncategorized

 

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epidemiology

I’m looking forward to discussing a bit of epidemiology in my Microbiology class on Tuesday. I’ve been looking at the CDC’s Epidemic Intelligence Service website and a package of case studies obtained from them and I think we can manage at least some of the broader questions without losing valuable time that I am itching to discuss immunology.

While researching, I came across this site by Google that uses search engine terms as a method for tracking flu worldwide. The data is used to create a map like the one shown below.

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Previous years’ information yielded these data illustrating spikes in flu during the winter months last year.

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Posted by on November 8, 2013 in Uncategorized

 

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