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Exploring Metagenomics in the Laboratory of an Introductory Biology Course

    Authors: Brian B. Gibbens1,††,*, Cheryl L. Scott1,††, Courtney D. Hoff1, Janet L. Schottel2
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    Affiliations: 1: Department of Biology Teaching and Learning; 2: Department of Biochemistry, Molecular Biology & Biophysics, University of Minnesota, St. Paul, MN 55108
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Published 01 May 2015
    • Supplemental materials available at http://jmbe.asm.org
    • *Corresponding author. Mailing address: 223E Snyder, 1445 Gortner Avenue, St. Paul, MN 55108. Phone: 612-625-2830. Fax: 612-624-2785. E-mail: [email protected].
    • †† Brian Gibbens and Cheryl Scott contributed equally to this manuscript.
    • ©2015 Author(s). Published by the American Society for Microbiology.
    Source: J. Microbiol. Biol. Educ. May 2015 vol. 16 no. 1 34-40. doi:10.1128/jmbe.v16i1.780
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    Abstract:

    Four laboratory modules were designed for introductory biology students to explore the field of metagenomics. Students collected microbes from environmental samples, extracted the DNA, and amplified 16S rRNA gene sequences using polymerase chain reaction (PCR). Students designed functional metagenomics screens to determine and compare antibiotic resistance profiles among the samples. Bioinformatics tools were used to generate and interpret phylogenetic trees and identify homologous genes. A pretest and posttest were used to assess learning gains, and the results indicated that these modules increased student performance by an average of 22%. Here we describe ways to engage students in metagenomics-related research and provide readers with ideas for how they can start developing metagenomics exercises for their own classrooms.

Key Concept Ranking

Microbial Ecology
0.85904425
16s rRNA Sequencing
0.51056224
0.85904425

References & Citations

1. Handelsman J 2004 Metagenomics: application of genomics to uncultured microorganisms Microbiol Mol Biol Rev 68 669 685 10.1128/MMBR.68.4.669-685.2004 15590779 539003 http://dx.doi.org/10.1128/MMBR.68.4.669-685.2004
2. Jackson KE, Jackson DW 2013 Using metagenomics to teach biodiversity J Ecosyst Ecography 03 1000e117 [Online.] http://omicsonline.org/using-metagenomics-to-teach-biodiversity-2157-7625.1000e117.php?aid=18456.
3. Jurkowski A, Reid AH, Labov JB 2007 Metagenomics: a call for bringing a new science into the classroom (while it’s still new) CBE Life Sci Educ 6 260 265 10.1187/cbe.07-09-0075 18056294 2104496 http://dx.doi.org/10.1187/cbe.07-09-0075
4. Rappé MS, Giovannoni SJ 2003 The uncultured microbial majority Annu Rev Microbiol 57 369 94 10.1146/annurev.micro.57.030502.090759 14527284 http://dx.doi.org/10.1146/annurev.micro.57.030502.090759
5. Shade A, Caporaso JG, Handelsman J, Knight R, Fierer N 2013 A meta-analysis of changes in bacterial and archaeal communities with time ISME J 7 1493 1506 10.1038/ismej.2013.54 23575374 3721121 http://dx.doi.org/10.1038/ismej.2013.54
6. Shade A, et al 2012 Fundamentals of microbial community resistance and resilience Front Microbiol 3 1 19 10.3389/fmicb.2012.00417 http://dx.doi.org/10.3389/fmicb.2012.00417
7. Wang Y, et al 2012 A culture-independent approach to unravel uncultured bacteria and functional genes in a complex microbial community PLoS One 7 1 11 [Online.] http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047530.
8. Wooley JC, Godzik A, Friedberg I 2010 A primer on metagenomics PLoS Comput Biol 6 1 13 [Online.] http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000667. 10.1371/journal.pcbi.1000667 http://dx.doi.org/10.1371/journal.pcbi.1000667

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2015-05-01
2019-06-24

Abstract:

Four laboratory modules were designed for introductory biology students to explore the field of metagenomics. Students collected microbes from environmental samples, extracted the DNA, and amplified 16S rRNA gene sequences using polymerase chain reaction (PCR). Students designed functional metagenomics screens to determine and compare antibiotic resistance profiles among the samples. Bioinformatics tools were used to generate and interpret phylogenetic trees and identify homologous genes. A pretest and posttest were used to assess learning gains, and the results indicated that these modules increased student performance by an average of 22%. Here we describe ways to engage students in metagenomics-related research and provide readers with ideas for how they can start developing metagenomics exercises for their own classrooms.

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Figures

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FIGURE 1.

Pre-/posttest results. The average percentage of correct answers that students earned on the pre-/posttests are shown for the whole test and for each question. The pretest was administered on the first day of class, before students had undertaken the metagenomics modules. The posttest was administered on the last day of class, four weeks after the modules were completed. n = 504; * indicates a value < 0.05; ** indicates a value < 0.0001.

Source: J. Microbiol. Biol. Educ. May 2015 vol. 16 no. 1 34-40. doi:10.1128/jmbe.v16i1.780
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