This article is part of the AAI Teaching Tools series. More articles can be found in the Teaching Tools section. Archived articles can be found on the AAI website.
by Louis B. Justement, PhD, Professor of Microbiology, University of Alabama at Birmingham
The ImmunoReach–Cell Collective Partnership
Immunology is routinely taught through static diagrams, yet the immune system is not static: cells, tissues, and soluble mediators like chemokines and cytokines communicate continuously, and a single static figure cannot accurately depict the dynamic feed-forward and feedback loops that regulate the immune response over time. This challenge is compounded by the sheer complexity of the field, which involves numerous interacting organ systems, cell types, and a dense, specialized vocabulary.
To provide students with a better way to visualize and manipulate this dynamic complexity, ImmunoReach, an NSF-funded Research Coordination Network for Undergraduate Biology Education (RCN-UBE), partnered with Cell Collective, an open-source web-based platform where educators design modules to help students build, simulate, and share logical and constraint-based computational models spanning the molecular to the organismal level. The goal of this collaboration is to develop a suite of modules that can be used in diverse educational settings to teach immunology from a systems-based perspective.
Teaching Systems Immunology
ImmunoReach and Cell Collective provide educators with an open-source, research-grade platform on which to build immunology-focused modules that give students a hands-on way to practice systems thinking rather than memorizing disconnected facts. The gap this partnership addresses is longstanding. The 2011 AAAS Vision and Change report identified the ability to use modeling and simulation to understand biology as a system of interacting parts as a core competency for undergraduate life-science students.
Immunology is an ideal topic for developing these competencies because the discipline is defined by feedback loops among various cells and soluble mediators that cannot be adequately captured in static diagrams. The modules on Cell Collective are highly adaptable, designed for immunology educators teaching at any level, from introductory undergraduate courses through graduate and professional school programs, online, hybrid, or fully in person, for either lecture or lab settings.
Importantly, computer-based modeling can be deployed to enhance the foundational understanding of specific immune processes like complement activation, neutrophil migration to the site of infection, B cell affinity maturation, or T cell activation and differentiation, as well as applied concepts like immune-mediated autoimmune diseases and immunotherapy in advanced settings.
T Cell activation and Differentiation in Response to Pathogens
“Cytokines/chemokines and the Adaptive Immune Response to Pathogens,” a cytokine-focused lesson built through this partnership, has already been effectively piloted in three different classrooms: an introductory immunology course for second-year students at University of Alabama at Birmingham (MIC 275: Introduction to the Immune System), a medical microbiology course for upper-level Biosciences majors at Minnesota State University Moorhead (BIOL 438), and an immunology course for upper-level Biology and Health Science majors at Frostburg State University (BIOL 455), demonstrating that the approach scales across institution type and student background.
In practice, students use Cell Collective to construct simple node-and-arrow models; for example, connecting cytokines to receptors, then layering in pleiotropic, redundant, synergistic, and antagonistic regulatory effects, before building out full pathways such as cytokine-driven CD4+ T cell activation and differentiation into Th1, Th2, Th17, and regulatory T-cell subsets. Once a model is built, students run simulations and immediately see how a perturbation, like adding IL-12 versus IL-4, changes downstream outcomes such as macrophage activation or IgE-mediated responses to parasites. Because the models are logic-based and require no programming, instructors can adapt to existing lessons or build new ones tailored to their own course objectives.
When this cytokine-and-adaptive-immunity module was piloted with 42 undergraduates across the three institutions above, pre- to post-lesson quiz scores rose from an average of 60.4% to 89.0% (p < 0.0001), and 86% of students agreed or strongly agreed that the activity improved their understanding of the immune system as an interconnected whole.
Designing, Building and Testing Models
ImmunoReach is now inviting immunology educators to help develop, pilot, and assess additional modules, so this newsletter article also serves as an invitation to join that community. The long-term goal is to develop a suite of modules that can be used interchangeably to enable students not only to understand how the immune system works at a systems level, but also to apply this understanding in the context of immune-mediated diseases, and cancer, as well as immunotherapeutic approaches to treat those diseases.
The process involves individuals or teams of educators working together to design models that teach students about the immune system and its function, from foundational to applied levels. These models are then implemented on the Cell Collective platform and can be tested iteratively to allow for refinement of the module. Individuals are encouraged to publish their Cell-Collective, immunology focused lesson plans in an education-based peer-reviewed journal.
External Resources
ImmunoReach: https://immunoreach.net/
Cell Collective platform: https://cellcollective.org
Loecker SD, Taylor R, Pandey S, Justement L, Helikar T. 2026. Using Dynamic Model Building and Simulation to Understand Cytokines and the Adaptive Immune Response to Pathogens. CourseSource 13. https://doi.org/10.24918/cs.2026.18
American Association for the Advancement of Science (AAAS). 2011. Vision and Change in Undergraduate Biology Education: A Call to Action. AAAS, Washington, DC.
Acknowledgments
Thanks to the Helikar Lab (Dr. Tomas Helikar and Skylar Loecker, University of Nebraska-Lincoln), the Digital Twin Innovation Hub, and the ImmunoReach community (Dr. Sumali Pandey, Minnesota State University Moorhead and Dr. Rebekah Taylor, Frostburg State University) for their collaboration in developing and piloting this lesson. ImmunoReach is supported by NSF RCN-UBE grant #2316260.
