A new model to simulate and analyze proliferating cell populations in BrdU labeling experiments

Background: This paper presents a novel model for proliferating cell populations in labeling experiments. It is especially tailored to the technique of Bromodeoxyuridine (BrdU), which is taken up by dividing cells and thus accumulates with increasing division number during uplabeling. The study of the evolving label intensities of BrdU labeled cell populations is aimed at quantifying proliferation properties such as division and death rates. Results: In contrast to existing models, our model considers a labeling efficacy that follows a distribution, rather than a uniform value. It thereby allows to account for noise as well as possibly space-dependent heterogeneity in the effective label uptake of the individual cells in a population. Furthermore, it enables more informative comparison with experimental data: The population-level label distribution is provided as a model output, thereby increasing the information content compared to existing models that give the fraction of labeled cells or the mean label intensity. We employ our model to study some naturally arising examples of heterogeneity in label uptake, which are not covered by existing models. With simulations of noisy and spacially heterogeneous label uptake, we demonstrate that our model contributes a more realistic quantitative description of labeling experiments. Conclusion: The presented model is to our knowledge the first one that predicts the full label distribution for BrdU labeling experiments. Thus, it can exploit more information, namely the full intensity distribution, from labeling measurements, and thereby opens up new quantitative insights into cell proliferation.