20.109(F07): Journal article discussion

Journal articles to be discussed

• The news story by Erika Check called "RNA interference: hitting the on switch" published in Nature 2007 vol. 448 pp. 855-8
• The original paper by Long-Cheng Li et. al. "Small dsRNAs induce transcriptional activation in human cells" published in PNAS 2006 vol. 103 pp. 17337-42.

Questions to guide your reading

1.

Read the news story by Erika Check first, noting particularly the reporter's description of the scientists motivation and path to RNA activation. You will compare this description to how the scientific authors describe their path to RNAa in the introduction to the paper they wrote. Keep track of other reactions you have to the news story. Does it raise any questions for you? Is there anything surprising? Would you characterize the events as comedy or tragedy or neither?

2.

Next skim the whole scientific article.
This means read the abstract once. Read the first and last sentence of the introduction. Read the subdivision headings of the Results section. Look at all the figures and their legends. Read the first and last paragraph of the Discussion.

3.

Now it's time to really comb through the data.
We'll focus on the reported results, including the supplemental information. To help you organize the material, a few links and tables are given here.

3A. Experimental matrix

Treatments	Promoters examined	Cell types examined
dsRNA Aza-C (demethylase) IFN-alpha2a (nonspecific inducer)	E-cadherin p21 VEGF	PC3 and DU45 (human prostate cancer cell lines) Hela (human cervical carcinoma) MCF-7 (human breast cancer line) HEK293 (embryonic kidney line) LNCaP (human prostate cancer) J82 and T24 (bladder cancer)

3B: Experimental techniques

Western analysis

see this link for refresher info.
Data can be presented like this

sample western data, fig 10B

where the treatment variation is shown above the gel lanes, the intensity of the protein band is shown inside the boxes (a cutout of the whole blot to show just the relevant bands). GAPDH is a "housekeeping gene" whose level is rarely affected by experimental perturbations. Why is it important to include data for this gene product? Thinking back to when you performed your Western analysis, did you included a similar control?

RT-PCR (also sometimes called q-PCR)

see this link for some description of RNA measurement techniques including RT-PCR. You might also want to learn a little about standard PCR if you're not already familiar with this technique. Most biology textbooks describe PCR or you could look at some animations of the process, for example here, just follow the links through “techniques” and "amplifying DNA”.

sample RT-PCR data, fig 12A and 12B

Data can be presented as bands on a gel (top panel in sample figure) or normalized to some baseline and shown as bargraphs (bottom panel in the sample figure). The authors describe their RT-PCR protocol in the very last paragraph of the Materials & Methods section where they call it "semiquantitative." You should read that paragraph. In short: they isolate total RNA from their samples (as you did last time), convert the RNA to cDNA (as you will do next time), and then measure the amount made by PCR amplification, running the product on a gel. They use GAPDH as a control, as they did for Westerns. What if the PCR primers they used aren't all equally efficient at binding their cDNA template?

Cell physiology

Microscopic observation, though qualitative, can an important "sanity check" for the molecular results like Westerns and RT-PCR. Cell numbers can be compared after different treatments, and cell appearance can be noted. For example

sample microscopy data, fig 11

The cell type is shown to the left of the images, the treatment is shown above them and the magnification and a few experimental details are details are described in the figure legend. This can serve a useful model for your own lab report figures. Since the images are qualitative and indirect assessments of the cells response to the perturbations, how much weight do you give the data? Are there ways to make the data more or less convincing?

For next time

1. Calculate the volume for 4 ug, 2 ug, 1 ug and 0.5 ug of each RNA sample that you prepared. Show your work. Save a copy of your answer since you'll need to know this volume to perform your experiment.
2. Please familiarize yourself with the basics of microarrays by reading NCBI's primer on the technique.