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Can We Quantify If It's a CURE?

Journal of microbiology & biology education·2023

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Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Tick Microbiome Characterization by Next-Generation 16S rRNA Amplicon Sequencing

Published on: August 25, 2018

Illuminating the "black boxes" of microbiome sequencing.

Lawrence S Blumer¹, Christopher W Beck²

¹Department of Biology, Morehouse College, Atlanta, Georgia, USA.

Journal of Microbiology & Biology Education

|July 6, 2026

Summary

This study introduces a new protocol for undergraduate microbiome research experiences (CUREs). It helps students visualize bacterial communities and understand DNA sequencing to taxonomy translation.

Keywords:

16S rDNA sequencing Oxford Nanopore Technologies bacterial microbiomes

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Published on: May 2, 2018

Area of Science:

Microbiology
Bioinformatics
Genomics

Background:

Microbiome research is increasingly integrated into undergraduate laboratory courses through course-based undergraduate research experiences (CUREs).
Current microbiome CUREs often present "black box" challenges for students, particularly in visualizing bacteria and understanding the translation of sequence data to taxonomic information.

Purpose of the Study:

To describe a protocol for evaluating cultured bacterial communities using Oxford Nanopore sequencing.
To enhance student understanding of microbiome analysis by illuminating opaque steps in typical CUREs.

Main Methods:

A protocol was developed for culturing bacterial communities.
Communities were sequenced using Oxford Nanopore technology.
Bioinformatics analysis involved using BLAST on sequencing reads for bacterial identification.

Main Results:

The protocol allows for the evaluation of bacterial communities through direct sequencing.
Student use of BLAST on sequencing reads successfully identified bacteria within the community.
This method demystifies the process of translating sequence data into bacterial taxonomy.

Conclusions:

The described protocol effectively addresses "black box" issues in undergraduate microbiome CUREs.
It provides a hands-on approach for students to visualize and identify bacteria in their samples.
This method improves learning outcomes related to microbiology and bioinformatics processes.