Teaching an evolving field: Lessons from mosquitos

Deep beneath London, in the Underground, a unique subspecies of mosquito thrives by feeding on unsuspecting commuters. This is not a vampire story, but a mosquito population genetically and behaviorally distinct from those aboveground. Urban legend frames this as rapid evolution that the circumstances of their domicile influenced their divergence. But this theory has been largely debunked: the Underground simply provided a niche where an already distinct strain could thrive.

Like those mosquitoes, educators must adapt to changing environments. For both mosquitoes and faculty, survival often means letting go of what no longer works and embracing new approaches.

Courtesy of Danielle Guarracino

Professor Danielle Guarracino works with undergraduate students Susan Knox and Jay Decker in a biochemistry lab at the College of New Jersey in spring 2016.

The most significant shift in my teaching came during the COVID-19 pandemic. Like many instructors, I moved fully online in spring 2021.

I partnered with a computational chemistry colleague to redesign our biochemistry lab. Students used visual molecular dynamics, or VMD, software to study protein structures and analyze the interaction between the SARS-CoV-2 spike protein and the angiotensin-converting enzyme 2, or ACE2, receptor, which is key to COVID-19 infection. They measured amino acid interactions, then designed peptide-based inhibitors. Each team presented their work and wrote a proposal for a science-educated nonexpert.

This project connected course concepts to a real-world problem and gave students space for creativity and ownership. Survey data showed that 91% of students felt the project improved their overall learning. Students especially valued visualizing protein interactions and connecting them to real-world impact.

Students appreciated that “(V)isualization … and being able to closely relate it back to my coursework (was my favorite part) … I felt like I understood the protein complex so much better!”

Using hands-on manipulation of three-dimensional protein images, combined with real-world application, appealed to students.

Later, I taught an in-person advanced biochemistry course built around the peptide research performed by my group. In spring 2024, I again collaborated with a computational colleague to introduce artificial intelligence to helical peptide design. Students used AlphaFold to predict peptide structure, then compared those predictions with experimental data from circular dichroism spectroscopy,  helical patterns in peptides exposed to circularly polarized light. They also tested antimicrobial activity, linking structure to function, as each peptide was designed to be an amphiphilic helix.

Student response was overwhelmingly positive, with 90% reporting that the project supported their learning of peptidomimetics. Many noted the value of conducting research while learning core concepts, bridging the “lessons from class” with “really unique (research) experiences.”

Combining AI with experimental procedures in a novel class-based research project increased student interest and engagement.

Therefore, like those mosquitoes, educators must continue to adapt. As student needs and scientific tools evolve, our teaching must evolve with them. The most exciting part of teaching biochemistry is that discovery never stands still, and neither can we.