lesson 3: measuring gene expression · lesson 3: measuring gene expression. ... in order to measure...

S. Dozier, B. Rana, ASHG GENA 2009 Cohort

Learning Cycle Stage(s): Explore/Explain/Elaborate/Evaluate

Adapted from: How to Turn on Genes: An Explora on of Differen al Gene Expression Sara Dozier, School of Science and Technology at San Diego High, CA Brinda Rana, University of California San Diego, CA

ASHG Concept(s) Addressed: Gene expression and regula on #10

Time Required: 125 minutes

Explore 1) Write or display the two statements below on the board.

a. Cardiac myocytes and neurons from the same person have different phenotypes because of differences in their gene expression profiles.

b. Tanning is the result of skin cells responding to the environment by changing their gene expres‐sion profile.

Ask students to divide into groups of four and present the following challenge: “How do you think scien sts originally tested the ideas that differences in gene expression explain phenotype differ‐ences among cell types and among cells of the same type in response to the environment? As a group, imagine that you are scien sts and come up with an experimental plan to test one of the hypotheses .” Emphasize that students should focus on general experimental design, including ap‐propriate controls, not technical details or specific techniques. Students should address the follow‐ing in their plans: c. What samples will they collect? d. Will they repeat the experiment? How? e. What molecule(s) will they look at to see if there are differences in gene expression? What

about that/those molecule(s) will they measure? f. Are any controls necessary?

2) Before students begin, ask volunteers to define what is meant when someone says that a gene is “expressed.” Review what a gene expression profile is as well.

3) As a class, discuss the designs groups came up with for their experiments. List on the board im‐portant parameters that students men on as the discussion unfolds. In each case, students should hone in on the idea of measuring some indica on of gene expres‐

sion (RNA levels, func onal protein levels, etc.). For the cell type hypothesis, gene expression should be measured in cardiac myocytes versus neurons from the same person. For the envi‐ronmental response hypothesis, gene expression should be measured in skin cells from the same individual with varying degrees of exposure to the sun (and thus tanning). Valid designs include sampling the same area before‐and‐a er exposure or sampling one area that has been exposed and one that hasn’t. Students may also men on measuring the degree of skin pig‐menta on itself. In both cases, students should also men on either analyzing replicate sam‐ples from a single subject, or repea ng the experiment with mul ple subjects. Ideally, both types of replicates would be done.

Explain 1) Have students complete Chapters 1‐3 of the DNA Microarray Virtual Lab (h p://

learn.gene cs.utah.edu/content/labs/microarray/) and take notes as they go.

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The Gene cist‐Educator Network of Alliances Project ● NSF EHR#0634296 ● www.ashg.org/educa on/gena.shtml

Lesson 3: Measuring Gene Expression


2) Project the ques ons at the end of the virtual lab for the whole class to see and work through them using a class discussion.

3) As a class, discuss the following ques ons: a. In order to measure gene expression with a microarray, what molecules do you need to isolate

from your sample? Students should iden fy RNA, and specifically, mRNA as the molecules of interest for mi‐

croarray experiments. b. How are the isolated molecules modified before the sample is applied to the array? Why?

mRNA is reverse transcribed into complementary DNA (cDNA) labeled with a fluorescent dye. For prac cal reasons, mRNA is not used directly because it is chemically unstable com‐pared to DNA. Adding a different fluorescent dye to each sample allows you to later deter‐mine the origin of cDNA samples bound to par cular microarry spots. Without any label, you would not be able to detect the bound cDNA at all. Alterna vely, if you labeled both samples with the same dye, you would be able to detect where the cDNA bound, but you would not be able to dis nguish the origin of the bound cDNA sample.

c. What do the spots on a microarray contain? Are the molecules within a single spot the same or different? What about the molecules in two neighboring spots? Each spot contains single‐stranded DNA probes designed to hybridize to cDNA from a spe‐

cific gene. The molecules within a single spot are iden cal, but two neighboring spots will have different molecules with different DNA sequences that have been deliberately engi‐neered to hybridize to cDNA from different genes.

d. What property of DNA does microarray technology take advantage of? Microarray technologies take advantage of the fact that single‐stranded DNA will base‐pair

or hybridize with complementary sequences (even if the two strands come from different sources).

e. Scien sts must be very careful to scan their microarrays in a certain orienta on. Why is it bad if they scan the array in the wrong orienta on? If you scan a microarray in the wrong orienta on, the database telling you what gene each

spot corresponds to will be incorrect. f. Using a microarray, would you be able to measure gene expression from a gene if the se‐

quence of that gene is not known? No, in order to exploit hybridiza on, you must know the sequence of what you are trying

to measure in order to design the probe you will include on the array. This is one of the limita ons of microarray technology (i.e., you can only measure the level of transcripts you already know about, you cannot discover new transcripts).

g. Using a microarray, would you be able to detect differences in gene expression between two samples that affect the level of func onal protein made, but not the level of mRNA ? No, mircoarrays can only detect differences in mRNA levels. If the difference in gene ex‐

pression occurs downstream of mRNA, it will not be iden fied on a microarray. h. In the example in the virtual lab, why is it important to compare skin cancer to healthy skin

cells specifically? For example, why can’t you compare the gene expression of skin cancer cells to healthy blood cells? If you don’t measure diseased and healthy samples of the same ssue type, you may mis‐

takenly link genes that are really differen ally expressed because of the difference in cell type to the development of cancer.

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Elaborate 1) Construct Macromodel Microarray simula on sets using the instruc ons in Appendix I and II . Con‐

struc ng a class set of six will take a few hours and requires the following materials (if you are con‐struc ng more than six for your class, each array requires one box, six ping pong balls of each col‐or, and up to four rare earth magnets). If you are not able to find red and green ping pong balls, white ping pong balls can be spray‐painted. However, this must be done at least a day in advance of construc ng the arrays. a. Six pizza boxes (medium or large) or copier paper box tops b. A roll of Velcro with adhesive backing c. A roll of magne c strips with adhesive backing d. 16 small rare earth magnets (no more than 5 cm in diameter) e. 36 red ping pong balls f. 36 green ping pong balls g. An exacto knife or box cu er h. A ruler i. Quart‐size plas c ziplock bags j. Permanent marker k. Heavy scissors (to cut the magne c strips)

2) Provide each group of four students with a Macromodel Microarray, the “normal ssue” and “cancer ssue” baggies for their assigned pa ent , and a copy of the Cancer Therapies sheet (Appendix III). Working in their groups, student should apply their samples to the array (see ps below), record their data, and then use their data to decide how the pa ent’s cancer should be treated. a. Students should start with the array slightly lted so that all of the “sample” (ping pong balls)

are in the corner with no spot. If any of the balls have stuck to each other, have students sepa‐rate them before beginning. What cells ini ate the tanning process a er sun exposure is de‐tected? What do these cells produce in response (and where within the cell), and how is their gene expression changed in the process?

b. Students should swirl the array in a circular mo on (not too vigorously) for approximately five seconds, then lt the box so that any unbound “sample” collects in the corner with no spot. If any ping pong balls are stuck to each other or are stuck to a spot only through interac on with another ball, students should separate the balls with their fingers and place those not bound to a spot in the unbound sample corner. Students may then swirl the box for another five se‐conds to maximize bound sample.

3) Ask one representa ve from each group to record his or her group’s treatment recommenda ons on the board (this can be done in a table with the drugs listed across the top and the pa ent num‐bers listed down the le side). Then ask each group to jus fy their recommenda ons to the rest of the class using the data they obtained from their array. The intended results for each pa ent are listed in Appendix IV. Note: Although the sample mix for each pa ent is intended to produce a par cular result, stu‐

dents should not be penalized if their actual array result, and therefore their pa ent recom‐menda ons, deviates from the intended result because of chance.

Evaluate A er students have completed the simula on, ask them to answer the ques ons in Appendix V

about how the simula on compares to actual microarray technology. Students may work in their

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groups, but each student should turn in his or her own answers to the ques ons.



Appendix I – Modifica ons to Construc ng Macromodel Microarrays The following instruc ons are modifica ons to the Macromodel of Microarray ac vity developed by the Gene c Sci‐ence Learning Center (h p://teach.gene cs.utah.edu/content/health/pharma/macromodel.html). The pa ent samples have been adapted from NOVA Teachers’ Ghost in Your Genes Classroom Ac vity (h p://www.pbs.org/wgbh/nova/teachers/ac vi es/3413_genes.html#learobje). 1) Construct enough array boxes such that each group of four students will have its own to work with. See Appendix II

for general construc on, but incorporate the following modifica ons: a. Velcro and magne c strips with adhesive backing are recommended, as they are easy to find and convenient

for construc ng the arrays. b. When cu ng the Velcro for the ping pong balls, use the ruler as a straight edge to guide the Exacto knife/box

cu er. c. To accommodate the number of ping pong balls in each pa ent’s samples, each spot (hook, pile, and magnet)

should be approximately 7 cm x 7cm (or 2.5 inches x 2.5 inches). Use a bowl rather than a cup to outline these larger spots.

d. If you are using magne c strips rather than ceramic magnets, they do not need to be placed under the magnet spot as they are low profile enough that the ping pong balls should roll over them freely.

e. Label the pile Velcro spots “BCL2,” the hook Velcro spots “EGFR,” and the magnet spots “ERB‐B2” with a per‐manent marker on the inside of each array.

2) Each student group will receive normal (green ping pong balls) and cancerous (red ping pong balls) breast ssue from a pa ent and must use the pa ent’s gene expression profile to determine how the pa ent should (or should not) be treated. For each pa ent, create the following mixes of ping pong balls (if you have more than six groups, you may have to create more than one set for a given pa ent) according to the general instruc ons in Appendix II. Separate “normal ssue” and “cancer ssue” in baggies labeled with the pa ent number and the ssue type:


Green (Normal Tissue)

Hook Pile Magnet None Hook Pile Magnet None

P1 2 2 0 2 0 2 2 2

P2 0 2 2 2 2 0 2 2

P3 2 0 2 2 0 2 2 2

P4 2 0 0 4 2 2 2 0

P5 0 2 0 4 2 2 2 0

P6 2 2 2 0 2 2 0 2

Red (Cancer Tissue)

http://gslc.genetics.utah.edu

Genetic Science Learning Center, 15 North 2030 East, Salt Lake City, UT 84112

Teacher References: Macromodel of Microarray

10 of 11© 2004 University of Utah

Cut four 2.0 cm x 2.0 cm pieces of both the pile and hook Velcro®.

In one corner of the box, paste the squares of hook Velcro® in a cluster to form a 4.0 cm x 4.0 cm square. Do the same with the pile

Velcro® in the opposite corner. Draw a circle around each cluster to represent spots on a microarray.

These will simulate the DNA segments of known sequence that are affi xed to a microarray. Label them Sequence #1 and Sequence #2 (or 1 and 2 for short).

Tape 1-2 ceramic magnets to the underside of the box lid or pizza box in a location that is a comfortable distance from the position of Sequences 1 and 2.

Detailed Preparation Guide

12 or more ping-pong balls, four different colors

1 high energy or rare earth magnet

copy paper box lid or clean pizza box

2 or more ceramic magnets

2.0 cm x 30.0 cm piece of Velcro® hook-and-

loop fastener

electrical tape, exacto knife, scissors, markers, ruler

2 clear containers large enough to hold 9-12 ping-pong balls (optional, not shown)

Creating The Box

klontok

Typewritten Text

Appendix II - Constructing Macromodel Microarrays

Creating The Balls

NOTE If you are having trouble getting the ping-pong balls to stick to the box, you may wish to place an additional 0.2 cm strip of Velcro® on the balls.

http://gslc.genetics.utah.edu

Genetic Science Learning Center, 15 North 2030 East, Salt Lake City, UT 84112

Teacher References: Macromodel of Microarray

11 of 11© 2004 University of Utah

Draw a circle on the right side of the box directly above the magnet.

Label this Sequence #3 (or 3).

Cut a 13 cm long pieces of both pile and hook Velcro®. Carefully cut off three 0.2 cm wide strips. Glue one thin strip of hook Velcro® to each of 3 ping-pong balls of the same color. (These will represent DNA segments of unknown sequence in solution.)

Glue one thin strip of the pile Velcro® to each of 3

ping-pong balls of a different color. (These will represent DNA segments of unknown sequence in solution.)

Using the exacto knife, slice a very small hole into the ping-pong ball of the third color. Insert the rare earth magnet inside.

Complete Box


Appendix III – Drugs Used for Cancer Treatment


Doxorubicin Brand Names: Adriamycin, Rubex What it is: chemotherapy drug How it works: Doxorubicin inhibits RNA syn‐thesis and causes DNA strand breakage. This slows or stops the growth of the cancer cells. Do not use if one or more is true: EGFR = upregulated in cancer cells

Fluorouracil Brand Name: Adrucil What it is: chemotherapy drug How it works: Fluorouracil binds with and deac vates a key enzyme (thymidylate syn‐thetase) in thymidine biosynthesis. This slows or stops the growth of the cancer cells. Do not use if one or more is true: EGFR = upregulated in cancer cells BCL2 = upregulated in cancer cells

Methotrexate Brand Names: Mexate, Folex What it is: chemotherapy drug How it works: Methotrexate binds to and inac vates the enzyme dihydrofolate reduc‐tase (DHFR), and inhibits the synthesis of purines and pyrimidines. This prevents the growth of cancer cells. Do not use if one or more is true: BCL2 = upregulated in cancer cells

Paclitaxel Brand Name: Taxol What it is: chemotherapy drug How it works: Paclitaxel binds to tubulin and blocks cell division. This slows or stops the growth of cancer cells. Do not use if one or more is true: BCL2 = upregulated in cancer cells ERB‐B2 = upregulated in cancer cells

Tamoxifen Brand Name: Nolvadex What it is: hormone (an estrogen) How it works: Tamoxifen binds to the estro‐gen receptor, preven ng cell growth. It also affects the cycling of the cell in the natural cell cycle. Do not use if one or more is true: ERB‐B2 = upregulated in cancer cells

Trastuzumab Brand Name: Hercep n What it is: monoclonal an body How it works: Hercep n binds to the ERB‐B2 growth factor receptor and prevents the cell from dividing. Do not use if one or more is true: ERB‐B2 = unaffected or downregulated in cancer cells


Appendix IV– Intended Results Based on the sample mixes for each pa ent, students are intended to find the following. Please note that due to chance (i.e., ball does not s ck to spot it in supposed to s ck to), students’ actual results may differ from the intend‐ed results for their pa ent. Students should not be penalized for sugges ng a different drug profile if this is the case as long as the profile corresponds to their actual results.


Gene Expression (“cancer” rela‐

ve to “normal”)

BCL2 EGFR ERB‐B2 Dox. Fluor. Metho. Pac. Tamox. Trast.

P1 Low Same High Y Y Y N N Y

P2 High Low Same Y N N N Y N

P3 Low High Same N N Y Y Y N

P4 Same High High N N Y N N Y

P5 High Same High Y N N N N Y

P6 Same Same Low Y Y Y Y Y N

Cancer Drugs


Appendix V– Student Ques ons 1) In this model, what does each pingpong ball represent? What does each spot represent? What does the interac‐

on (either through Velcro or magnets) between each ball and spot represent? 2) Did any of your sample s ck to each other rather than to an array spot? What might this represent in a real micro‐

array experiment? In a real microarray experiment, would this kind of interac on interfere with the results? Why or why not?

3) How are changes in the levels of gene expression represented in the model, and why do you think these par cular

genes were chosen for analysis?


lesson 3: measuring gene expression · lesson 3: measuring gene expression. ... in order to measure...

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