An integrated microbiome project for charactering microbial diversity in classroom based on virtual simulation experiments.
Hao SunPinmei WangYudong LiPublished in: Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology (2023)
Microbiome study requires both molecular techniques and bioinformatics skills, which are challenging for biologists to participate in this growing field. To introduce microbiome concepts and skills to students, a 6-week wet-lab and bioinformatics course for undergraduates was implemented through the project-based learning (PBL) approach. In the saliva microbiome project, students collected their saliva samples, performed DNA extraction and PCR amplification, followed by metagenomic analysis to compare the diversity and abundances of microbes among samples. First, students are required to practice molecular techniques and bioinformatics analysis skills in a virtual simulation lab. To our knowledge, our study is the first one to incorporate a virtual lab into microbiome experience. Then, students applied their recently acquired skills to produce and analyze their own 16S amplicon sequencing data and reported their results via a scientific report. The student learning outcomes show that the Virtual lab can improve students' laboratory techniques and research capabilities. Moreover, a simple pipeline to analyze 16S rRNA gene amplicon sequencing data is introduced in a step-by-step manner that helps students to develop analysis skills. This project can be modified as either a virtual course or a module within another course such as microbiology, molecular biology, and bioinformatics. Our study provides evidence on the positive impact of virtual labs on learning outcomes in undergraduate science education.
Keyphrases
- high school
- quality improvement
- medical students
- healthcare
- primary care
- public health
- microbial community
- metabolic syndrome
- randomized controlled trial
- type diabetes
- dna methylation
- adipose tissue
- gene expression
- genome wide
- bioinformatics analysis
- single cell
- skeletal muscle
- weight loss
- big data
- study protocol
- insulin resistance
- infectious diseases
- glycemic control
- genome wide identification