Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics
The constantly evolving nature of genomics provides new challenges for students in Public Health as they try to understand how genomic information relates to health and disease. As Public Health curricula attempt to keep pace with the most recent advances in genomics, students should gain experience...
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American Society for Microbiology
2020
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oai:doaj.org-article:fd8090ab209b4a80be2a6f8672ff7a532021-11-15T15:04:42ZTesting the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics10.1128/jmbe.v21i1.20191935-78851935-7877https://doaj.org/article/fd8090ab209b4a80be2a6f8672ff7a532020-01-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/jmbe.v21i1.2019https://doaj.org/toc/1935-7877https://doaj.org/toc/1935-7885The constantly evolving nature of genomics provides new challenges for students in Public Health as they try to understand how genomic information relates to health and disease. As Public Health curricula attempt to keep pace with the most recent advances in genomics, students should gain experience with analyzing genomic data and applying genomic tools to the study of health-related issues. To advance undergraduate and graduate student education and provide a more comprehensive view of genomics, we developed an educational project including both pedagogic and research components to characterize skin microbial communities (microbiomes) using targeted amplicon sequencing of their genomes (metataxonomy). All students completed the lab procedures, analyzed 16S rRNA genomic data (formative assessments), and wrote a five-page scientific report summarizing and discussing their results (summative assessment). Student grades for the summative assessment ranged from 31.5 to 40 (out of 40) points. They also successfully completed two practicums (problem sets) focused on microbiome sequence data and responded to 12 minute-papers related to genomic topics covered in class. In all these exercises the 2019 students outperformed 2018 students, who did not participate in this educational lab project. By fulfilling all the requirements of this project-based learning experience, students better understood the complexity of genomics and acquired a valuable set of marketable experience and skills in molecular technologies, bioinformatics and statistics (quantitative skills). Additionally, students were able to generate new valuable microbial 16S rRNA genomic data and test hypotheses about the composition and diversity of the microbes living on our skin (microbiota).Marcos Pérez-LosadaKelly M. CrandallKeith A. CrandallAmerican Society for MicrobiologyarticleSpecial aspects of educationLC8-6691Biology (General)QH301-705.5ENJournal of Microbiology & Biology Education, Vol 21, Iss 1 (2020) |
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Special aspects of education LC8-6691 Biology (General) QH301-705.5 |
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Special aspects of education LC8-6691 Biology (General) QH301-705.5 Marcos Pérez-Losada Kelly M. Crandall Keith A. Crandall Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics |
description |
The constantly evolving nature of genomics provides new challenges for students in Public Health as they try to understand how genomic information relates to health and disease. As Public Health curricula attempt to keep pace with the most recent advances in genomics, students should gain experience with analyzing genomic data and applying genomic tools to the study of health-related issues. To advance undergraduate and graduate student education and provide a more comprehensive view of genomics, we developed an educational project including both pedagogic and research components to characterize skin microbial communities (microbiomes) using targeted amplicon sequencing of their genomes (metataxonomy). All students completed the lab procedures, analyzed 16S rRNA genomic data (formative assessments), and wrote a five-page scientific report summarizing and discussing their results (summative assessment). Student grades for the summative assessment ranged from 31.5 to 40 (out of 40) points. They also successfully completed two practicums (problem sets) focused on microbiome sequence data and responded to 12 minute-papers related to genomic topics covered in class. In all these exercises the 2019 students outperformed 2018 students, who did not participate in this educational lab project. By fulfilling all the requirements of this project-based learning experience, students better understood the complexity of genomics and acquired a valuable set of marketable experience and skills in molecular technologies, bioinformatics and statistics (quantitative skills). Additionally, students were able to generate new valuable microbial 16S rRNA genomic data and test hypotheses about the composition and diversity of the microbes living on our skin (microbiota). |
format |
article |
author |
Marcos Pérez-Losada Kelly M. Crandall Keith A. Crandall |
author_facet |
Marcos Pérez-Losada Kelly M. Crandall Keith A. Crandall |
author_sort |
Marcos Pérez-Losada |
title |
Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics |
title_short |
Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics |
title_full |
Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics |
title_fullStr |
Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics |
title_full_unstemmed |
Testing the “Grandma Hypothesis”: Characterizing Skin Microbiome Diversity as a Project-Based Learning Approach to Genomics |
title_sort |
testing the “grandma hypothesis”: characterizing skin microbiome diversity as a project-based learning approach to genomics |
publisher |
American Society for Microbiology |
publishDate |
2020 |
url |
https://doaj.org/article/fd8090ab209b4a80be2a6f8672ff7a53 |
work_keys_str_mv |
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