How Teaching Professor Tim Paustian used KBase to streamline teaching bioinformatics
An Educational Journey
Our learning goal for the bioinformatic part of the University of Wisconsin – Madison upper-level laboratory capstone course was to make metabolic predictions of isolates based upon sequence data and test those predictions. In past years, students used an assembly tool, Prodigal for gene prediction, and the KEGG functional database to develop metabolic maps. However, many students were unable to follow the workflow due to hardware limitations or struggles to install supporting software. Final data was often hard to interpret for novices, resulting in misconceptions and incorrect predictions.
Making Bioinformatics Accessible
In a conversation with Patricia Tran, a graduate student from Karthik Anantharaman‘s laboratory, she mentioned coming across KBase. I began to explore the tool and immediately realized its potential. KBase removes the busy work of dealing with bioinformatics tools through wrapping them to function as an Application (App) within the platform. In turn, this solves several common issues of working with bioinformatics software, such as installation and versioning.
Tools are collected in one place, eliminating the need to find them. As new tools come out, they are evaluated and added to improve or replace older tools. The KBase team and an active community of KBase developers handle updates to software and Apps, and help troubleshoot any requirements for an App to run on their servers. Having powerful computers behind KBase allows students to run computationally demanding programs in a graphical user interface, opening up much deeper analysis.
The Narrative is a concept similar to a Jupyter Notebook. The Narrative integrates data and analyses into a single workflow accessible through a graphical user interface or GUI. It also supports documentation through the use of Markdown cells that displays text and images within the workflow. This design results in a comprehensive, reproducible record of your analysis and conclusions that is shareable and publishable, in support of open, collaborative science.
The KBase Difference
Within KBase, I was able to create a Narrative workflow with detailed descriptions outlining each step based on my students’ knowledge and understanding. Students were able to use this Narrative and Apps for their workflows, going through the analysis from raw sequence read files to genome assembly and annotation. Next, students built metabolic models based on the annotated genomes and used the resulting model to predict nutritional requirements for their isolates. My students were then able to test their predictions in the laboratory.
KBase made it simple to run the tools with my students and displayed the results in an easy-to-understand format. Overall, students could focus on the science instead of getting lost in the details of running the tools. Assessments during and after the class demonstrated they had a deeper understanding of bioinformatic tools and how to use them. KBase made that possible.
About the Contributing Author
Dr. Tim Paustian is a Teaching Professor at the University of Wisconsin – Madison within the Department of Bacteriology. He instructs courses and labs including Biology of Microorganisms, Physiology of Microorganisms, and Physiological Diversity of Prokaryotes. Tim is a member of the KBase Educators Community and has contributed to the Metabolic Modeling Working Group and is an author on the KBase Educators Program publication. Tim has also contributed to a teaching workflow on RNAseq data to be released in Fall 2022.