Multidisciplinary research and education with open tools

Abstract

Modern scientific research is often multidisciplinary, involving scientists from two or more backgrounds. A multidisciplinary approach is frequently necessary to advance our knowledge in a diverse range of fields, from genomics to climate change. Many of the projects undertaken in these areas involve a combination of field, lab, and computational analysis components. Our research initiatives demonstrate how the principles of active learning -performing tasks while engaging in analysis, synthesizing and evaluating the tasks being performed [10] -can be applied to undergraduate science education using 16S rRNA metagenomics as the basis. Beginning with development of the scientific questions, students work through the entire process of designing, testing and implementing physical and digital sampling protocols, hardware and software platforms for collecting geographically coded (geocoded) environmental metadata, and lab protocols; they work in the field taking samples and in the lab preparing them; they perform the computational analysis of the sequencer output and synthesis of metadata and metagenomic data; and finally they disseminate the results. The students come primarily from backgrounds in computer science, biology, geology, and physics. This broad range makes it possible to select teams that cover many of the traditionally underrepresented groups in science. Working together for a year or more, the students learn the science, vocabularies, skill sets, etc. of all the disciplines, as well as how their own discipline, in conjunction with others, contributes to addressing large, complex questions.

Microbiomes for All

“…These include project-based, upper-level laboratory courses and intensive summer research programs where students self-select for participation and may have a number of pre-requisites to meet. Implementations such as these tend to be small sections with multiple experienced instructors who work closely with students to help them master complex sample preparation and sequencing protocols (Edwards et al, 2013;Rundell et al, 2014;Muterspaw et al, 2015). In a smaller class with expert support and sufficient access to computers, it is also feasible to carry out sequence filtering and processing using command line interface and pipelines such as QIIME2 (Bolyen et al, 2019).…”