Replicative age differentially predicts metabolic competence across industrial yeasts at single-cell resolution

In industrial yeast fermentations, population-level viability assays routinely report healthy cultures even as aged, metabolically compromised mother-cell subpopulations go undetected. Replicative age contributes to this hidden heterogeneity, but its link to a cell's metabolic competence has been difficult to measure simultaneously in the same cell by high-throughput flow cytometry. Here, we introduce a dual-parameter flow cytometry workflow combining bud-scar labeling with a recombinant His6-SUMO-mCherry-chitin-binding domain fusion protein (~610 nm emission) and 5(6)-carboxyfluorescein diacetate (CFDA)-based viability detection (~525 nm), providing spectral orthogonality without computational autofluorescence correction. We applied it to four industrially relevant yeasts: Saccharomyces pastorianus W-34/70, S. cerevisiae var. diastaticus BE-134, S. cerevisiae var. chevalieri LA-01, and Komagataella phaffii X33. In S. pastorianus, viability declined monotonically from 88 % in daughter cells to 5 % in the oldest resolved mother-cell class; longitudinal monitoring over 96 h captured a progressive widening of this gradient masked at the population level. Among S. cerevisiae variants, age-dependent gradients were weaker and strain-specific, while in K. phaffii reliable discrimination required exponential growth. Replicative age is thus a strain-dependent predictor of metabolic competence rather than a universally conserved one, and the workflow offers brewers and bioprocess developers a practical tool for age-resolved fermentation monitoring and pitching-yeast assessment.