Speaker
Description
Natural killer (NK) cells eliminate stressed and transformed cells by integrating signals from activating and inhibitory receptors. Although “serial killing” has been widely discussed, two quantitative gaps remain. First, it is unclear whether apparent serial killers reflect stable, intrinsic cytotoxic capacity differences, stochastic encounter dynamics, or both, making the definition ambiguous: how many kills, or how many productive stimulations, are required before a cell is more than a stochastic outlier? Second, the effect of sequential stimulation is unresolved, with repeated engagements potentially reinforcing commitment or inducing exhaustion.
We combine multiscale modelling with Bayesian inference to link intracellular activation to population-level single-cell readouts under sequential stimulation. Using flow-cytometry CD107a degranulation measurements across four consecutive stimulations, we summarise response histories as a 16-state distribution and compare mechanistic hypotheses, including heterogeneity in cytotoxic capacity, dependence on prior responses, and a highly responsive subpopulation. Bayes factors and posterior uncertainty quantification provide a principled way to adjudicate between hypotheses and to suggest informative follow-up experiments for immune surveillance and immunotherapy.
