A Curricular Bioinformatics Approach to Teaching Undergraduates to Analyze Metagenomic Datasets Using R

Integrating computational skills in undergraduate Microbiology curricula in developing countries

The employability of young graduates has gained increasing significance in the labour market of the 21st century. Universities turn out millions of graduates annually, but at the same time, employers highlight their lack of the requisite skills for sustainable employment. We live today in a world of data, and therefore courses that feature numerical and computational tools to gather and analyse data are to be sourced for and integrated into life sciences' curricula as they provide a number of benefits for both the students and faculty members that are engaged in teaching the courses. The lack of this teaching in undergraduate Microbiology curricula is devastating and leaves a knowledge gap in the graduates that are turned out. This results in an inability of the emerging graduates to compete favourably with their counterparts from other parts of the world. There is a necessity on the part of life science educators to adapt their teaching strategies to best support students' curricula that prepare them for careers in science. Bioinformatics, Statistics and Programming are key computational skills to embrace by life scientists and the need for training beginning at undergraduate level cannot be overemphasized. This article reviews the need to integrate computational skills in undergraduate Microbiology curricula in developing countries with emphasis on Nigeria.

An integrated microbiome project for charactering microbial diversity in classroom based on virtual simulation experiments

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.

Communicating the Utility of the Microbiome and Bioinformatics to Small Flock Poultry Producers

The use of “omics” has become widespread across poultry production, from breeding to management to bird health to food safety and everywhere in between.  While the conventional poultry industry has become more exposed to the power and utility of “omic” technologies, smaller poultry flock producers typically do not have this same level of experience. Because smaller, nonconventional poultry production is a growing portion of the overall poultry market, it is important that they also have educational access to these research tools and the resultant data. While small flock producers are dedicated and knowledgeable farmers, their knowledge of these newer technologies may be limited at best, and it is the task of academic researchers to communicate the importance of these “omic” tools and how the omic data can improve a variety of different aspects of their operations. This review discusses ways to effectively communicate complex microbiota and microbial genome sequence data to small flock producers and transforming this data into meaningful and applicable information that they can utilize to inform beneficial management decisions.

Resequencing of Microbial Isolates: A Lab Module to Introduce Novices to Command-Line Bioinformatics

Familiarity with genome-scale data and the bioinformatic skills to analyze it have become essential for understanding and advancing modern biology and human health, yet many undergraduate biology majors are never exposed to hands-on bioinformatics. This paper presents a module that introduces students to applied bioinformatic analysis within the context of a research-based microbiology lab course. One of the most commonly used genomic analyses in biology is resequencing: determining the sequence of DNA bases in a derived strain of some organism, and comparing it to the known ancestral genome of that organism to better understand the phenotypic differences between them. Many existing CUREs - Course Based Undergraduate Research Experiences - evolve or select new strains of bacteria and compare them phenotypically to ancestral strains. This paper covers standardized strategies and procedures, accessible to undergraduates, for preparing and analyzing microbial whole-genome resequencing data to examine the genotypic differences between such strains. Wet-lab protocols and computational tutorials are provided, along with additional guidelines for educators, providing instructors without a next-generation sequencing or bioinformatics background the necessary information to incorporate whole-genome sequencing and command-line analysis into their class. This module introduces novice students to running software at the command-line, giving them exposure and familiarity with the types of tools that make up the vast majority of open-source scientific software used in contemporary biology. Completion of the module improves student attitudes toward computing, which may make them more likely to pursue further bioinformatics study.