Instrument-agnostic optimization of autofluorescence bands for label-free cell sorting

Label-free cell sorting is attractive where validated antibodies or transgenic reporters are scarce or undesirable, yet most autofluorescence (AF) gates are chosen ad hoc and rarely transfer across instruments. We present a spectral-to-sorter framework that learns discriminative emission bands from single-cell AF spectra and compiles them into ready-to-use settings on standard flow cytometers—using only standard lasers and commercially available filters, without custom hardware modifications. In rainbow trout testis, the approach resolved two major populations and nominated a short-edge-starting, wide emission band under 561-nm excitation as a robust operating regime. Implemented on a conventional sorter, the lower AF gate increased the fraction of type A spermatogonia by ~ 1.8× relative to bulk, whereas the higher AF gate fell to ≤ 20% of the total level; RT-qPCR of germ and somatic markers corroborated the enrichment. Band choices and operating performance were consistent across independently collected monthly cohorts. By turning spectra into instrument-specific band settings, this framework makes AF-based sorting portable and reproducible within a given biological system, and opens a practical route to antibody- and transgene-free enrichment in non-model systems.