Remote Undergrad Research Project Builds Multiple Skills
Projects involving data mining and bioinformatics tools, like the Organonitrogen Degradation Database (ONDB) project, allow undergraduate students to engage in remote research experiences that develop their literature analysis, computational and scientific collaboration skills. Studies demonstrate that providing research experiences for undergraduate students , which are important for careers in health care and STEM industries. However, the COVID-19 pandemic led to the cancellation of many traditional undergraduate research programs, due to campus closures and physical distancing restrictions. Modern biology increasingly relies on programming and bioinformatics skills to address research questions, and the crisis has provided an opportunity to create remote research experiences that address both traditional and quantitative research skills.
For the ONDB project, participants worked with an interdisciplinary team of scientists to create an interactive web application with information about organonitrogen compounds considered environmental pollutants (such as urea, cyanoguanidine and biuret) and their microbial degradation pathways. The project allowed students to engage in a variety of bioinformatics activities, including basic R programming, database searches and computational predictions of microbial metabolism. It also helped students develop general research skills, like the ability to analyze literature and collaborate effectively. Developing the ONDB was valuable not only as an undergraduate research experience, but also as a resource for scientists and citizens who need quick access to information about the fate and degradation of organonitrogen compounds in the environment.
Analyzing Research Literature
Reading and analyzing scientific literature effectively is essential for conducting research. Many students rush through this process due to their desire to start doing experiments. One of the goals of the ONDB project was to teach participants how to locate, read and analyze research papers. Prior to selecting a compound for entry into the database, students conducted extensive literature research to identify its properties and microbial degradation pathways. The ONDB team designed a and to provide tips for interpreting scientific papers. Additionally, students participated in biweekly, journal-club style discussions with mentors and peers. This approach helped participants learn how to interpret figures and how to connect the hypotheses posed in an article with the data.
During the journal club discussions, students practiced summarizing the paper's main findings and evaluating whether the information presented was relevant for inclusion in the database. However, some students were afraid to contribute to the discussion because they feared their assumptions or comments were wrong. Other students reported being challenged by the number of papers available in public databases, as well as the vast amount of information and jargon presented in these articles. Over time, participation in journal clubs made students feel more comfortable summarizing data, asking questions and contributing ideas to research discussions. Toward the end of the ONDB project, participants described improvements in their ability to read and interpret papers. They also reported confidence in sorting through information and assessing the relevance of published data to their research projects.
The database searching and literature analysis tools developed by the ONDB team can be easily incorporated into lecture courses. The are valuable to teach students how to locate articles and other relevant information using different types of public databases. This activity, followed by journal clubs, helps students improve their literature analysis and data interpretation skills.
Communicating and Collaborating Effectively
Communicating and collaborating across disciplines is essential to solve complex challenges in STEM. The ONDB team promoted effective communication and collaboration skills by organizing students into interdisciplinary research teams. Each participant was assigned one of these "domains of expertise":
- Programming and web applications.
- Scientific content.
- ONDB design.
- User interface.
The "domain of expertise" approach was well received by students because it allowed them to contribute to the project by focusing on a skill of interest. Although all participants had to complete the basic programming and bioinformatics tutorials during the first weeks of the research experience, having a “domain of expertise” encouraged students to take ownership of the project and develop accountability and independent learning habits. This organization also allowed them to experience a modern research environment, where scientists of different disciplines collaborate to complete a project.
A drawback of the "domain of expertise" approach is that some students did not get a chance to continue practicing a given skill once they were assigned a more specialized role within the project. Initially, some participants struggled with their "expert" roles because they were still learning and feared sharing ideas and suggestions. A useful exercise to build students’ confidence and strengthen scientific identity was having each "expert" provide weekly updates to the ONDB team, by email or as brief presentations at lab meetings. Constant communication with collaborators helped participants feel more comfortable asking questions and sharing ideas with their peers. Students reported benefiting from diversity of thought and constructive criticism when collaborating and communicating with senior scientists and "expert" participants. They also described feeling more prepared when summarizing and presenting their work to a diverse audience.
Integrating Computational Skills With Biological Knowledge
The ONDB project integrates computational skills with biological knowledge by using bioinformatics tools to investigate the microbial degradation of common organonitrogen compounds currently considered environmental pollutants. The current lack of accessibility and social distancing restrictions in research laboratories presents an ideal opportunity for faculty to have students learn a programming language or explore a computational tool that could benefit their projects when away from the bench. Unfortunately, computational skills are often limited or completely missing from undergraduate biology courses and research experiences. Life science instructors feel uncomfortable incorporating bioinformatics exercises into their classes, due to . Similarly, students can be easily intimidated by the quantitative nature of bioinformatics analyses and opt out of projects involving significant computational approaches. To help overcome these challenges, the ONDB research team created a that provide a framework for instructors with limited experience to integrate bioinformatics activities into their undergraduate classes.
Mastering multiple computational skills in a short period of time was often overwhelming and challenging for the undergraduate researchers. The team structure established for the project was effective at providing support and timely feedback for participants. Students could talk to each other frequently and consult with mentors to troubleshoot and solve programming issues. A disadvantage of the team approach was that sometimes students asked for external help too quickly rather than trying to find solutions independently. This problem was resolved as students practiced and became experienced with R.
The most common challenges with programming consisted of syntax errors and remembering important functions. Other obstacles included importing, cleaning and wrangling data into the appropriate formats. Looking at R tutorials and scripts written to accomplish similar tasks was a useful approach for students. Comparing their work to existing documentation improved students’ ability to piece together diverse functions into custom pipelines to perform desired types of analyses for their research project.
The ONDB exercises are ideal for teaching database searching, computational predictions and basic R programming. These exercises can be used as units or individual modules in undergraduate biochemistry or microbiology courses. Alternatively, multi-week projects similar to the ONDB experience provide a convenient choice for distance learning while encouraging students to use computational tools to answer biological questions.
Students exposed to bioinformatics in their biology courses or through a research experience can seek out further training in this discipline by taking specialized bioinformatics courses. Additionally, basic programming and data analytics skills gained from these types of research experiences are directly transferable to other sectors, such as data science—.
The Organonitrogen Biodegradation Database activities provide an opportunity for students to learn computational skills, scientific communication and contribute to an interdisciplinary research team. The remote learning nature of the ONDB project makes research available to all students regardless of location or access to laboratory facilities. The modules and worksheets developed by this team can be adapted to face-to-face or hybrid classrooms, as well as all levels of instruction.
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