Compositional Analysis of Mouse Sperm Subpopulations During Capacitation In Vitro

Mammalian sperm must undergo capacitation to become competent for fertilization, yet this process is marked by substantial phenotypic heterogeneity among sperm cells. How such variability emerges and how it relates to fertilizing potential remain unresolved, in part because sperm subpopulations are typically analyzed independently despite being intrinsically interdependent. Here, we combine large-scale single-cell spectral flow cytometry with compositional statistical modeling to quantify how sperm population structure responds to controlled capacitation signals in vitro. Using cauda epididymal mouse sperm, we implemented a two-dimensional assay that systematically varies extracellular bicarbonate and free calcium-key regulators of capacitation-and classified millions of individual cells into four irreversible physiological states defined by cell viability and acrosome reaction status. We show that bicarbonate and calcium interact nonlinearly to redistribute sperm across these subpopulations, revealing structured responses that would be otherwise obscured in measurements lacking single-cell resolution. Elevated intracellular calcium was associated with increased cell death, while the highest proportions of live, acrosome-reacted sperm occurred under relatively low extracellular calcium conditions. To enable subpopulation-level analysis, we applied a hierarchical Dirichlet-multinomial regression model that accounts for multinomial sampling noise and between-male variability, yielding posterior probability surfaces that describe how sperm subpopulations reallocate across functional states as microenvironmental signaling conditions change. Together, these results demonstrate that capacitation is a stochastic, cell-population level process shaped by structured phenotypic heterogeneity. This framework provides a quantitative foundation for linking sperm subpopulation composition to measures of fertility competence and for improving existing interpretation of flow cytometry-based assessments of male fertility.