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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: gibb0098@umn.edu.
    • †† 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 J2004Metagenomics: application of genomics to uncultured microorganismsMicrobiol Mol Biol Rev6866968510.1128/MMBR.68.4.669-685.200415590779539003 http://dx.doi.org/10.1128/MMBR.68.4.669-685.2004
2. Jackson KE, Jackson DW2013Using metagenomics to teach biodiversityJ Ecosyst Ecography031000e117[Online.] http://omicsonline.org/using-metagenomics-to-teach-biodiversity-2157-7625.1000e117.php?aid=18456.
3. Jurkowski A, Reid AH, Labov JB2007Metagenomics: a call for bringing a new science into the classroom (while it’s still new)CBE Life Sci Educ626026510.1187/cbe.07-09-0075180562942104496 http://dx.doi.org/10.1187/cbe.07-09-0075
4. Rappé MS, Giovannoni SJ2003The uncultured microbial majorityAnnu Rev Microbiol573699410.1146/annurev.micro.57.030502.09075914527284 http://dx.doi.org/10.1146/annurev.micro.57.030502.090759
5. Shade A, Caporaso JG, Handelsman J, Knight R, Fierer N2013A meta-analysis of changes in bacterial and archaeal communities with timeISME J71493150610.1038/ismej.2013.54235753743721121 http://dx.doi.org/10.1038/ismej.2013.54
6. Shade A, et al2012Fundamentals of microbial community resistance and resilienceFront Microbiol311910.3389/fmicb.2012.00417 http://dx.doi.org/10.3389/fmicb.2012.00417
7. Wang Y, et al2012A culture-independent approach to unravel uncultured bacteria and functional genes in a complex microbial communityPLoS One7111[Online.] http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047530.
8. Wooley JC, Godzik A, Friedberg I2010A primer on metagenomicsPLoS Comput Biol6113[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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/content/journal/jmbe/10.1128/jmbe.v16i1.780
2015-05-01
2017-10-17

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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