|
|
|||||||
Articles |


,
Departments of *Biology and
Mathematics and
Genome Consortium for Active Teaching, Davidson College, Davidson, NC 28035-7118;
Howard Hughes Medical Institute Biotechnology Education and Outreach Program, University of Illinois at Urbana-Champaign, Urbana, IL 61801; ||Hinsdale Central High School, Hinsdale, IL 60521; and ¶Montgomery County Public School District, Rockville, MD 20850
Submitted July 5, 2006; Revised August 15, 2006; Accepted August 28, 2006
Monitoring Editor: Barbara Schulz
| ABSTRACT |
|---|
|
|
|---|
| INTRODUCTION |
|---|
|
|
|---|
We have developed a wet lab simulation that is part of a 2- to 3-d DNA microarray module that teaches high school students about DNA microarrays. Our goals included 1) providing an interactive way to experience how microarrays are used to study gene expression; 2) teaching students that DNA microarrays can measure the activity of many genes simultaneously; and 3) enabling students to discover that genes are differentially regulated (expressed differently under different conditions). This module uses a wet lab simulation (in combination with a paper lab exercise; Zanta, 2004, 2006) to teach students how DNA microarray experiments are performed. Furthermore, through the simulation, students learn that genes are differentially regulated. In preliminary testing, the microarray simulation facilitated active, hands-on learning; the students enjoyed the lab; and they significantly improved their scores on surveys conducted before and after the simulation. The simulation is very reliable and fits within a 45-min class period. The reagents are inexpensive and can be prepared once for multiple classes. In today's educational testing climate, for a new biology module to be incorporated into the curriculum, it must address some of the National Science Education Standards (NRC, 1996) that appear on standardized tests. The microarray simulation uses a case study in cancer biology to help students address several education standards covered in end-of-year tests (see Supplemental Material 1).
A recent study by the NRC (2005) found that U.S. high school classrooms frequently lack challenging and meaningful laboratory experiences for students. The NRC report outlined what constitutes a good lab. Students should have hands-on and minds-on opportunities to learn. Furthermore, college faculty often complain that entering students are poorly prepared for modern biology. Therefore, there is a need for curricular materials that will help high school teachers provide high-quality, interesting lab experiences for their students and help prepare them for college biology courses. This article describes a simulation that can be used for large numbers of students. The simulation has been used with >100 high school teachers in national workshops, with two teachers and 338 students in Hinsdale, IL, and with four high school teachers and
150 students in the Montgomery County School District in Maryland. The appendices in the Supplemental Material online provide the wet lab handouts and all assessment tools; the paper lab exercise is also available online (Zanta, 2004). The simulation has been commercialized by Genisphere (Hatfield, PA) with the agreement that we would be able to publish a "how to create your own" version.
DNA Microarray Methodology
DNA microarrays are a high-throughput method used to survey the relative amount of transcription (gene expression) for every gene in a genome. DNA microarrays (sometimes referred to as gene chips) do not allow absolute levels of quantification of gene expression (e.g., 250 mRNA molecules per cell). However, DNA chips do allow investigators to determine how much mRNA was produced in a sample relative to the amount of mRNA produced by a control population. An example study might compare lung cancer tissue to healthy lung tissue in order to determine whether there is an increase (induction) or decrease (repression) of gene expression and, if so, by how much. The relative amounts of mRNA produced by a particular gene in two samples can be used to produce a ratio that indicates the differences in transcription. For example, if Gene A produced 250 mRNA molecules in healthy lung cells and 1000 mRNAs in lung cancer cells, then Gene A is induced fourfold in lung cancer (i.e., 1000 ÷ 250 = 4). Conversely, perhaps healthy cells produce 4000 mRNA molecules from Gene B but lung cancer cells only produce 500, then Gene B is repressed eightfold in cancer cells (i.e., 4000 ÷ 500 = 8). However, some genes will not show differences in the level of transcription between the lung cancer cells and healthy lung cells, and thus their ratio of gene regulation will be approximately one. If we wanted to understand the causes of lung cancer, we might want to focus on Gene A and Gene B rather than the hundreds that were equivalent in the two tissues.
Scientists and clinicians are collaborating to improve the diagnosis of diseases such as lung cancer. Currently, diagnoses are made in broad categories based on clinical observations, and all patients are treated the same within a category. Using DNA chips, many investigators believe medicine can become personalized such that each patient will be prescribed medical treatment that will best match his or her illness. Within their lifetimes, today's high school students will probably benefit clinically from DNA chipbased diagnosis. Approximately 1 of 3 women and 1 of 2 men in the United States will develop cancer (American Cancer Society, 2006), and many of them may be diagnosed with DNA microarrays.
With this great potential for social impact, it is important that high school students understand gene chips, regardless of their posthigh school career plans. The wet lab simulation and accompanying case study provide a realistic scenario that is easy for students to follow and makes the cancer scenario relevant to their lives. The student-friendly microarray module that we have developed can easily be integrated into high school, community college, and introductory college biology curricula. As an introduction to the gene chip methodology, students read the handouts we have produced (see Supplemental Material 3) and view a free animation (Campbell, 2000; Figure 1). DNA microarrays that measure gene activity require many steps, all of which are too small to observe by eye. Therefore, a paper microarray lab (Zanta, 2004) combined with the animation provide a good foundation that prepares students for the wet lab simulation.
|
| MATERIALS AND METHODS |
|---|
|
|
|---|
|
|
Glass Slides
Any glass slide might work, but we have good results with slides that are covered with a hydrophobic mask with holes in the mask; these are reusable. We chose the 10 x 5-mm hole mask because it provided a compromise of spot size and number of spots per slide (Figure 2). There are multiple suppliers, such as Tekdon (Myakka City, FL), Scientific Devices (Perth Amboy, NJ), and Proscitech (Kirwan, Queensland, Australia; respectively, at http://www.tekdon.com/Microscope_slides2.html, http://www.scientificdevice.com/intl_product_pages/iprinted_microscope_slides.htm, and http://www.proscitech.com.au/catalogue/g1.asp). Alternatively, permanent marker or waxed pencil could be used to draw masks for each spot on a regular glass microscope slide.
Simulated cDNA Probes
The hybridization solution is simply 0.1 M NaOH. This is the only potential hazard in the simulation because a strong base can be caustic. For this reason, students and teachers should wear gloves during the lab and wash their hands at the end of lab.
Student Assessment
Formal assessment was conducted after the paper and wet lab exercises with 158 high school Honors Biology students (primarily in ninth grade) in Hinsdale, IL. Formal assessment consisted of pre- and posttests to measure student knowledge of microarrays and to get objective feedback on the microarray module (see Supplemental Material 3). A total of 138 students completed the pretest and 75 completed the posttest. Each question had a total value of 2 points and was scored for 0, 1, or 2 points based on the quality of the answer. Total pretest scores ranged from 0 to 6 (075% correct). Total posttest scores ranged from 1 to 8 points (12.5100% correct). Fifty-five students took both tests and recorded their names on their papers, which allowed us to measure their results for individual student gains using a paired t test. For the entire dataset, significant differences were calculated using a Z-test for each question, and the totals are shown in Table 2. Since that time, an additional 180 students have used the microarray module, but they did not participate in the formal assessment. Informal assessment was conducted in the Maryland high schools, and anecdotal evidence supported the findings from the formal assessment in Illinois.
|
| RESULTS AND DISCUSSION |
|---|
|
|
|---|
|
The students followed a detailed protocol that explained the technical aspects of the simulation (see Supplemental Material 4). In brief, single drops of melted agarose with pH indicators were placed on a microscope slide in circles prenumbered 16. The spots cooled and gelled in <1 min. Students placed their slides in containers of "mixed labeled cDNA hybridization solution" and watched the colors develop. After 1 min, the colors were recorded. Digital images were taken to accurately recall the colors (Figure 4). When the agarose and dyes were reheated because the master solutions were made in advance, sometimes the dyes were not evenly mixed, and the gene spots looked speckled.
|
Students can be asked to answer a series of questions that focus their attention on the meaning of the colors: Which genes were induced? Which genes were repressed? Were any genes transcribed similarly in the two samples? What were the molecular causes for their color differences? Were all the induced genes activated to the same degree? What about the repressed genes? Once students have answered these questions, they can be queried to explain how two lung samples could display differential gene regulationa major educational objective of this module. They can be reminded that all cells contain the same genes, but different tissues transcribe genes differently. From this discussion, they can be guided to realize that loss of gene regulation is a key component of cancer formationanother important educational objective. Advanced students could be encouraged to learn about oncogenes and tumor suppressors, which are described in textbooks used in advanced placement (AP) biology courses. Once they have learned about tumor suppressors and oncogenes, students can be asked to speculate if any of the six genes in their simulation might be oncogenes or tumor suppressors. From this point, students may ask how some cancers can run in families, which can lead to a discussion of how many mutations are required for cancers to form (at least two recessive mutations of tumor suppressors and at least one dominant oncogene mutation).
Students can be encouraged to convert their colors to quantitative ratios (Campbell and Heyer, 2006b). Note that colors will not always fall exactly into one of the colors in the online chart so students should be encouraged to estimate the best ratio. This may help them realize that the ratios are not all multiples of 2 and are actually part of a continuum composed of fractions as well (e.g., 3.5-fold repressed). An additional mathematical module allows students to deepen their understanding of DNA microarrays. The mathematical module lets students analyze their ratios for variance, which they visualize graphically, use their ratios for clustering genes and tissue samples, and use their wet lab simulation data to diagnose a cancer sample with the aid of mathematical methods (Heyer and Campbell, 2006). This mathematical module provides a real-world context for basic math skills and emphasizes the need to integrate biology with mathematics.
Assessment Data
Student Assessment.
Assessment was carried out at Hinsdale Central High School in Illinois. Students completed a pretest before carrying out the complete microarray module (introduction/animation, paper activity, and wet lab simulation) and a posttest after completing the module (see Figure 3). Only 2 of the 55 Illinois students who were tracked on both pre- and posttests had worse scores on the posttest than on the pretest, and these scores varied by only 1 and 2 points. The average score for the pretest was 1 point out of a total of 8 possible points (n = 138), whereas the posttest average was 4.8 points (n = 75). Each question in the test showed a significant improvement from the pretest average to the posttest average (Table 1). When the learning gains were measured for the 55 students who signed both tests, we found p values ranging from 1 x 1011 to essentially zero. Students had little prior knowledge of microarrays and gained an understanding of microarrays after carrying out the paper and wet lab activities.
Open-ended feedback from the posttest survey was overwhelmingly positive for these laboratory activities (see Box 1). One student commented to her teacher that she really liked the microarray simulationit was her favorite lab because she saw how it connected with what they were studying in class. When asked what they did not like about the activity, one student replied "There is nothing I liked least. Every part was great and I enjoy doing lab experiments." Regarding the prelab paper microarray activity, one student commented, "I felt that I understood everything better because of the prelab. I enjoyed actually understanding this lab." Several students noted that they enjoyed doing the lab on cancer because it affects their lives.
Box 1. Anonymous student comments when asked "What did you enjoy most about this microarray unit?"
|
We were surprised to see so few negative comments about the laboratory when the students were asked for their least favorite part of the lab and suggestions for improvement. When asked what they liked least about the activities and suggestions for improvement, the majority of students noted that there was nothing to improve. Many said the entire module was great and wrote nothing in this space. On the 75 posttests, the major suggestions for improvement were as follows:
When asked what they liked least about the microarray unit, the only feedback was as follows:
The quantitative results show that after completing these activities, the Illinois students (and presumably the Maryland students as well) gained a greater understanding of the use of DNA microarrays to study gene expression. The students seemed to be deeply engaged in the activity that used lung cancer as an example scenario. Because this is a complex topic, we suggest that teachers use prelab exercises to facilitate deeper understanding of the concepts before the wet lab microarray simulation. After the wet lab microarray simulation, a teacher could facilitate a thoughtful class discussion to ensure that students have a thorough understanding of microarrays, differential gene regulation, and gene expression in cancer. Experience has shown us that repetition of concepts can lead to a more meaningful understanding of complex topics.
Teacher Assessment. Teachers who have used this wet lab simulation reported that it was easy to do, would easily fit into their class periods, and was realistic enough that students could understand the key steps in a DNA microarray experiment and data analysis. Combining the teacher responses with student assessment data above, the simulation provides a needed boost to modernize a typical high school curriculum.
Of the 14 teachers who tested the full microarray module at the University of Illinois Biotechnology Education and Outreach Program Genomics workshop, all were enthusiastic about the learning activities. One teacher noted that the "simple prelabs make you really consider what is happening during the activity." Some additional positive comments on the microarray module included the following:
The suggestions for improvement and negative comments were:
Only one teacher noted that he/she would like to use the microarray activities but felt it might be too difficult to fit these extra exercises into the existing curriculum. The remaining teachers were positive about incorporating the microarray module into their curricula. One teacher commented that he/she was "not sure about [using the microarray simulation in the classroom]I don't like to mislead students." This comment is interesting in that it could apply to many molecular biology laboratories that are used in high school classrooms and could provide an opportunity to discuss the benefits and limitations of laboratory simulations. Many of these activities are simulations that do not utilize the same reagents and equipment used in current scientific laboratories because of time and financial constraints. However, in order to offer an engaging laboratory experience within the time frame of a typical 45- to 55-min high school class, a simulation is sometimes the best option. Schools that have block schedules (classes of 8090 min) may be able to do the entire module in a single day, although spreading it over 2 days may prevent student overload and enhance student comprehension.
| CONCLUSIONS |
|---|
|
|
|---|
| ACKNOWLEDGMENTS |
|---|
| FOOTNOTES |
|---|
Address correspondence to: A. Malcolm Campbell (macampbell{at}davidson.edu)
| REFERENCES |
|---|
|
|
|---|
American Cancer Society (2006). Cancer Facts and Figures 2006. http://www.cancer.org/downloads/STT/CAFF2006PWSecured.pdf (accessed 19 June 2006).
Brewster, J. L., Beason, K. B., Eckdahl, T. T., and Evans, I. M. (2004). The microarray revolution: perspectives from educators. Biochem. Mol. Biol. Educ 32(4), 217227.
Campbell, A. M. (2000). DNA Microarray Animation. www.bio.davidson.edu/Courses/genomics/chip/chip.html (accessed 12 June 2006).
Campbell, A. M., Eckdahl, T. T., Fowlks, E., Heyer, L. J., Hoopes, L.L.M., Ledbetter, M. L., and Rosenwald, A. G. (2006). Genome Consortium for Active Teaching (GCAT). Science 311, 11031104.
Campbell, A. M., and Heyer, L. J. (2006a). Discovering Genomics, Proteomics, and Bioinformatics, 2nd ed., San Francisco: Benjamin Cummings, 447 pp..
Campbell, A. M., and Heyer, L. J. (2006b). Quantifying Gene Chip Colors. www.bio.davidson.edu/people/macampbell/LRSD/colors.html (accessed 13 June 2006).
Chattopadhyay, A. (2005). Understanding of genetic information in higher secondary students in northeast India and the implications for genetics education. Cell Biol. Educ 4, 97104.
Genome Consortium for Active Teaching (GCAT). (2006a). GCAT Home Page. www.bio.davidson.edu/GCAT (accessed 12 June 2006).
Genome Consortium for Active Teaching (2006b). GCAT DNA Chip Simulations: Dry Lab and Wet Lab Curricula. www.bio.davidson.edu/projects/GCAT/HSChips/HSchips.html (accessed 13 June 2006).
Heyer, L. J., and Campbell, M. A. (2006). Value Added: Blending Math into a High School Genomics Lab. http://gcat.davidson.edu/Online_Genomics/hs_kit_math_module.pdf (accessed 10 August 2006).
Kakiuchi, S. (2004). Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839). Hum. Mol. Genet 13((24)), 30293043.
National Research Council (1996). National Science Education Standards, Washington, DC: National Academy Press.
National Research Council (2002). Learning and Understanding: Improving Advanced Study of Mathematics and Science in U.S. High Schools: Report of the Content Panel for Biology, by the Committee on Programs for Advanced Study of Mathematics and Science in American High Schools, ed. Wood, W. B. Washington, DC: National Academy Press.
National Research Council (2005). America's Lab Report: Investigations in High School Science, eds. Singer, S. R. Hilton, M. L. and Schweingruber, H. A. Washington, DC: National Research Council.
Zanta, C. A. (2004). Gene Chips for High SchoolsPaper Exercise. www.bio.davidson.edu/people/macampbell/LRSD/LRSD_ChipsPaper.html (accessed July 5 2006).
Zanta, C. A. (2006). Using Gene Chips to Study the Genetics of Lung Cancer: A DNA Macroarray Lab. http://www.bio.davidson.edu/people/macampbell/LRSD/Full_Handout.doc (accessed 5 July 2006).
This article has been cited by other articles:
![]() |
A. M. Campbell, W. T. Hatfield, and L. J. Heyer Make Microarray Data with Known Ratios CBE Life Sci Educ, September 1, 2007; 6(3): 196 - 197. [Full Text] [PDF] |
||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | ARCHIVE | SEARCH | TABLE OF CONTENTS |