Skip to main content

CURRICULUM, INSTRUCTION, AND PEDAGOGY article

Front. Educ.
Sec. STEM Education
Volume 9 - 2024 | doi: 10.3389/feduc.2024.1380117
This article is part of the Research Topic Using Case Study and Narrative Pedagogy to Guide Students Through the Process of Science View all 4 articles

Learning From Feces: A Case Study Teaching Microbiome Analysis

Provisionally accepted
Aeisha Thomas Aeisha Thomas 1*Debra Davis Debra Davis 2*Jasmine Faue Jasmine Faue 1*Sierra Kicker Sierra Kicker 1*
  • 1 Crown College, St. Bonifacius, Minnesota, United States
  • 2 Wingate University, Wingate, North Carolina, United States

The final, formatted version of the article will be published soon.

    Microbiome data is increasingly important in health and environmental research. This data can be used to teach students both microbiology content as well as data science competencies. A narrative case study, Learning from Feces: the Effects of Antibiotics on Gut microbiomes, was developed where publicly available human gut microbiome data from infants treated with antibiotics is analyzed using the student-accessible, user-friendly DNA Subway Purple line. Students, through this case study, learn about microbiome analysis including how to choose samples and process sequence data through a pipeline and finally interpret and explain the biological relevance of this data. This case study was successfully implemented in Microbiology courses for both majors and non-majors as a multi-step module on microbiomes. This manuscript presents the case development process that includes undergraduate authors, learning objectives, teaching materials and the results of implementation. Reflections on the implementation in two different courses are shared with notes for future users. It is hoped that this case will be effective in student learning and helpful for other instructors, especially those with limited data science training and the time and financial resources required for a full wet lab.

    Keywords: microbiome, Case study teaching, antibiotic resistance, bioinformatics, DNA Subway

    Received: 01 Feb 2024; Accepted: 23 May 2024.

    Copyright: © 2024 Thomas, Davis, Faue and Kicker. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Aeisha Thomas, Crown College, St. Bonifacius, Minnesota, United States
    Debra Davis, Wingate University, Wingate, 28174, North Carolina, United States
    Jasmine Faue, Crown College, St. Bonifacius, Minnesota, United States
    Sierra Kicker, Crown College, St. Bonifacius, Minnesota, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.