Abstract
Understanding the complex elements affecting signal resolution in cytometry is key for quality experimental design and data. In this study, we incorporate autofluorescence as a contributing factor to our understanding of resolution in cytometry and corroborate its impact in fluorescence signal detection through mathematical predictions supported by empirical evidence. Our findings illustrate the critical importance of autofluorescence extraction via full spectrum unmixing in unmasking dim signals and delineating the expression and subset distribution of low abundance markers in discovery projects. We apply our findings to the precise definition of the tissue and cellular distribution of a weakly expressed fluorescent protein that reports on a low-abundance immunological gene. Exploiting the full spectrum coverage enabled by Aurora 5L, we describe a novel approach to the isolation of pure cell subset-specific autofluorescence profiles based on high dimensionality reduction algorithms. This method can also be used to unveil differences in the autofluorescent fingerprints of tissues in homeostasis and after immunological challenges.