Bridging the Gap in Flow Cytometry Training: A Practical Workflow for Teaching Autofluorescence Management in Immunology 2261098
Abstract Introduction Cellular autofluorescence, caused by endogenous biomolecules, can obscure low-intensity fluorophore emissions, leading to compromised data interpretation in flow cytometry. This issue is particularly challenging for trainees and early-career researchers, who may lack experience in spectral unmixing and tissue-specific background management. Methods We, therefore, developed a practical workflow that introduces researchers to autofluorescence as a consistent, tissue-dependent variable and provides structured guidance for improving panel design and data analysis. This workflow integrates unstained controls and autofluorescence extraction during unmixing to refine gating and improve dim-marker resolution (Cytek Aurora (16V—14B—10YG—8R), SpectroFlo software). Results Integrating this training into Core workflows improved researchers’ ability to distinguish true fluorescence from background signals and enhance their understanding of tissue-specific autofluorescence. The approach reduces troubleshooting time, increases reproducibility, and empowers users to apply autofluorescence management strategies to their own experiments independently. Conclusion This workflow addresses a critical blind spot in flow cytometry education by transforming autofluorescence from a confounding variable into a teachable and manageable feature of experimental design. It enhances data quality, supports reproducibility, and builds core competencies in flow cytometry for immunology research. Funding Source n/a Topic Categories Immunology Education and Communication (EDU)
Authors
- Shelby Ma
- Basudha Habisyasi
- Elena Galkina
- Alina Moriarty
- Kathleen Coleman
Institutions
- Old Dominion University (US)
Publication Details
- Journal
- The Journal of Immunology
- Published
- 2026-07-28
- DOI
- https://doi.org/10.1093/jimmun/vkag141.1030
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.00