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Three-Dimensional Visualizations in Teaching Genomics and Bioinformatics: Mutations in HIV Envelope Proteins and Their Consequences for Vaccine Design

    Author: KATHY M. TAKAYAMA1
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    Affiliations: 1: School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, NSW 2052, Australia
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • *Corresponding author. Mailing address: School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia. Phone: 61-2-9385-1592. Fax: 61-2-9385-1591. E-mail: k.takayama@unsw.edu.au.
    • Copyright © 2004, American Society for Microbiology
    Source: J. Microbiol. Biol. Educ. May 2004 vol. 5 no. 1 3-12. doi:10.1128/jmbe.v5.72
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    Abstract:

    This project addresses the need to provide a visual context to teach the practical applications of genome sequencing and bioinformatics. Present-day research relies on indirect visualization techniques (e.g., fluorescence-labeling of DNA in sequencing reactions) and sophisticated computer analysis. Such methods are impractical and prohibitively expensive for laboratory classes. More importantly, there is a need for curriculum resources that visually demonstrate the application of genome sequence information rather than the DNA sequencing methodology itself. This project is a computer-based lesson plan that engages students in collaborative, problem-based learning. The specific example focuses on approaches to Human Immunodeficiency Virus-1 (HIV-1) vaccine design based on HIV-1 genome sequences using a case study. Students performed comparative alignments of variant HIV-1 sequences available from a public database. Students then examined the consequences of HIV-1 mutations by applying the alignments to three-dimensional images of the HIV-1 envelope protein structure, thus visualizing the implications for applications such as vaccine design. The lesson enhances problem solving through the application of one type of information (genomic or protein sequence) into concrete visual conceptualizations. Assessment of student comprehension and problem-solving ability revealed marked improvement after the computer tutorial. Furthermore, contextual presentation of these concepts within a case study resulted in student responses that demonstrated higher levels of cognitive ability than was expected by the instructor.

Key Concept Ranking

Viral Proteins
0.73616606
Sequence Alignment
0.63557315
Genetic Variation
0.53363806
Sequence Analysis
0.5287836
0.73616606

References & Citations

1. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE2000The protein data bankNucleic Acids Res2823524210.1093/nar/28.1.235 http://dx.doi.org/10.1093/nar/28.1.235
2. Campbell AM, Heyer LJ2003Discovering genomics, proteomics, and bioinformaticsBenjamin Cummings (Pearson Education)San Francisco, Calif
3. Charlin B, Mann K, Hansen P1998The many faces of problem-based learning: a framework for understanding and comparisonMed Teacher2032333010.1080/01421599880742 http://dx.doi.org/10.1080/01421599880742
4. Chinn CA, Malhotra BA2002Epistemologically authentic inquiry in schools: a theoretical framework for evaluating inquiry tasksSci Educ8617521810.1002/sce.10001 http://dx.doi.org/10.1002/sce.10001
5. Coffin JM1995HIV population dynamics in vivo: implications for genetic variation, pathogenesis, and therapyScience26748348910.1126/science.78249477824947 http://dx.doi.org/10.1126/science.7824947
6. Dori YJ, Barak M2001Virtual and physical molecular modeling: fostering model perception and spatial understandingEduc Technol Society46174
7. Douthright J1994Undergraduate microbiology curriculum recommendationsASM News60460461
8. Glaser F, Pupko T, Paz I, Bell RE, Bechor-Shental D, Martz E, Ben-Tal N2003ConSurf: identification of functional regions in proteins by surface mapping of phylogenetic informationBioinformatics19163164[Online.] http://consurf.tau.ac.il/10.1093/bioinformatics/19.1.163 http://dx.doi.org/10.1093/bioinformatics/19.1.163
9. Goodwin L, Miller JE, Cheetham RD1991Teaching freshmen to think—does active learning work?BioScience4171972210.2307/1311767 http://dx.doi.org/10.2307/1311767
10. Harland T2003Vygotsky’s zone of proximal development and problem-based learning: linking a theoretical concept with practice through action researchTeaching Higher Educ826327210.1080/1356251032000052483 http://dx.doi.org/10.1080/1356251032000052483
11. Herrington J, Herrington A1998Authentic assessment and multimedia: how university students respond to a model of authentic assessmentHigher Educ Res Dev1730532210.1080/0729436980170304 http://dx.doi.org/10.1080/0729436980170304
12. Hoffman EA2001Successful application of active learning techniques to introductory microbiologyMicrobiol Educ2511
13. Hollingsworth RW, McLoughlin C2001Developing science students’ metacognitive problem solving skills onlineAustralian J Educ Technol175063
14. Krane DE, Raymer ML2003Fundamental concepts of bioinformaticsBenjamin Cummings (Pearson Education)San Francisco, Calif
15. Kwong PD, Wyatt R, Majeed S, Robinson J, Sweet RW, Sodroski J, Hendrickson WA2000Structures of HIV-1 Gp120 envelope glycoproteins from laboratory-adapted and primary isolatesStructure8132910.1016/S0969-2126(00)00547-5 http://dx.doi.org/10.1016/S0969-2126(00)00547-5
16. Kwong PD, Wyatt R, Robinson J, Sweet RW, Sodroski J, Hendrickson WA1998Structure of an HIV gp120 envelope glycoprotein in complex with the CD4 receptor and a neutralizing human antibodyNature39364865910.1038/314059641677 http://dx.doi.org/10.1038/31405
17. Linn RL, Baker EL, Dunbar SB1991Complex, performance-based assessment: expectations and validation criteriaEduc Res201521
18. Mansky LM, Temin HM1995Lower in vivo mutation rate of human immunodeficiency virus type 1 than that predicted from the fidelity of purified reverse transcriptaseJ Virol69508750947541846
19. Markham RB, Wang W-C, Weisstein AE, Wang Z, Munoz A, Templeton A, Margolick J, Vlahov D, Quinn T, Farzadegan H, Yu X-F1998Patterns of HIV-1 evolution in individuals with differing rates of CD4 T cell declineProc Natl Acad Sci USA95125681257310.1073/pnas.95.21.125689770526 http://dx.doi.org/10.1073/pnas.95.21.12568
20. Martinez MA, Sala M, Vartanian JP, Wain-Hobson S1995Reverse transcriptase and substrate dependence of the RNA hypermutagenesis reactionNucleic Acids Res142573257810.1093/nar/23.14.2573 http://dx.doi.org/10.1093/nar/23.14.2573
21. Martz E2002Protein Explorer: easy yet powerful macromolecular visualizationTrends Biochem Sci27107109[Online.] http://molvis.sdsc.edu/protexpl/index.htm/10.1016/S0968-0004(01)02008-411852249 http://dx.doi.org/10.1016/S0968-0004(01)02008-4
22. Meyer CA1992What’s the difference between authentic and performance assessment?Educ Leadership493940
23. Miller JE, Cheetham RD1990Teaching freshmen to think—active learning in introductory biologyBioScience4038839110.2307/1311217 http://dx.doi.org/10.2307/1311217
24. Mulder I, Swaak J, Kessels J2002Assessing group learning and shared understanding in technology-mediated interactionEduc Technol Society53547
25. Oliver R, Omari A1999Using online technologies to support problem-based learning: learners’ responses and perceptionsAustralian J Educ Technol155879
26. Palloff RM, Pratt K1999Building learning communities in cyberspace: effective strategies for the online classroom110128Jossey-BassSan Francisco, Calif
27. Preston BD, Dougherty JP1996Mechanisms of retroviral mutationTrends Microbiol4162110.1016/0966-842X(96)81500-98824790 http://dx.doi.org/10.1016/0966-842X(96)81500-9
28. Reeves TC, Okey JR1996Alternative assessment for constructivist learning environments191202 Wilson BGConstructivist learning environments: case studies in instructional designEducational Technology PublicationsEnglewood Cliffs, N.J
29. Richardson DC, Richardson JS2002Teaching molecular 3-D literacyBiochem Mol Biol Educ30212610.1002/bmb.2002.494030010005 http://dx.doi.org/10.1002/bmb.2002.494030010005
30. Sears DW2002Using inquiry-based exercises and interactive visuals to teach protein structure/function relationshipsBiochem Mol Biol Educ3020810.1002/bmb.2002.494030030081 http://dx.doi.org/10.1002/bmb.2002.494030030081
31. Shavelson RJ, Baxter GP, Pine J1991Performance assessment in scienceAppl Measurement Educ434710.1207/s15324818ame0404_7 http://dx.doi.org/10.1207/s15324818ame0404_7
32. Tobias S, Hake RR1988Professors as physics students: what can they teach us?Am J Phys5678679410.1119/1.15486 http://dx.doi.org/10.1119/1.15486
33. White B, Kim S, Sherman K, Weber N2002Evaluation of molecular visualization software for teaching protein structure: differing outcomes from lecture and labBiochem Mol Biol Educ3013013610.1002/bmb.2002.494030020026 http://dx.doi.org/10.1002/bmb.2002.494030020026
34. Wiggins G1993Assessing student performance: exploring the purpose and limits of testingJossey-BassSan Francisco, Calif
35. Wiggins G1989A true test: toward a more authentic and equitable assessmentPhi Delta Kappan70703
36. Willian KR2002Using three-dimensional imaging of proteins: examples of class activities and subsequent assessmentsBiochem Mol Biol Educ3020921010.1002/bmb.2002.494030030080 http://dx.doi.org/10.1002/bmb.2002.494030030080
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2004-05-01
2017-11-17

Abstract:

This project addresses the need to provide a visual context to teach the practical applications of genome sequencing and bioinformatics. Present-day research relies on indirect visualization techniques (e.g., fluorescence-labeling of DNA in sequencing reactions) and sophisticated computer analysis. Such methods are impractical and prohibitively expensive for laboratory classes. More importantly, there is a need for curriculum resources that visually demonstrate the application of genome sequence information rather than the DNA sequencing methodology itself. This project is a computer-based lesson plan that engages students in collaborative, problem-based learning. The specific example focuses on approaches to Human Immunodeficiency Virus-1 (HIV-1) vaccine design based on HIV-1 genome sequences using a case study. Students performed comparative alignments of variant HIV-1 sequences available from a public database. Students then examined the consequences of HIV-1 mutations by applying the alignments to three-dimensional images of the HIV-1 envelope protein structure, thus visualizing the implications for applications such as vaccine design. The lesson enhances problem solving through the application of one type of information (genomic or protein sequence) into concrete visual conceptualizations. Assessment of student comprehension and problem-solving ability revealed marked improvement after the computer tutorial. Furthermore, contextual presentation of these concepts within a case study resulted in student responses that demonstrated higher levels of cognitive ability than was expected by the instructor.

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Figures

Image of FIG. 1

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FIG. 1

Biology Workbench nucleotide sequence alignment demonstrating subject 1 HIV-1 clone diversity at visit number 1. The alignment was obtained using the boxshade function in Biology Workbench.

Source: J. Microbiol. Biol. Educ. May 2004 vol. 5 no. 1 3-12. doi:10.1128/jmbe.v5.72
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Image of FIG. 2

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FIG. 2

Biology Workbench protein sequence alignment demonstrating subject 1 HIV-1 clone diversity at visit number 1. The alignment was obtained using the boxshade function in Biology Workbench.

Source: J. Microbiol. Biol. Educ. May 2004 vol. 5 no. 1 3-12. doi:10.1128/jmbe.v5.72
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Image of FIG. 3

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FIG. 3

3-D structure summarizing data from multiple sequence alignment of subject 1, visit 1 HIV-1 protein sequences modeled on HIV-1 gp120 core complexed with the CD4 receptor and a neutralizing human antibody. Magenta (spacefill) residues represent highly conserved regions; blue (spacefill) residues represent variable regions of gp120. The CD4 receptor, antibody light chain, and antibody heavy chain are indicated.

Source: J. Microbiol. Biol. Educ. May 2004 vol. 5 no. 1 3-12. doi:10.1128/jmbe.v5.72
Download as Powerpoint

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