Inferring average generation via division-linked labeling

TL;DR

This paper introduces a label-based method to estimate the average generation number of proliferating cells without continuous monitoring, relying on heritable label changes and measurable proportions of labeled cells.

Contribution

The authors propose a novel, model-independent estimator for average cell generations using division-linked labels, validated through data comparison and simulations.

Findings

Estimator accurately predicts average generations

Does not require knowledge of cell cycle or death rates

Enables new experimental design strategies

Abstract

For proliferating cells subject to both division and death, how can one estimate the average generation number of the living population without continuous observation or a division-diluting dye? In this paper we provide a method for cell systems such that at each division there is an unlikely, heritable one-way label change that has no impact other than to serve as a distinguishing marker. If the probability of label change per cell generation can be determined and the proportion of labeled cells at a given time point can be measured, we establish that the average generation number of living cells can be estimated. Crucially, the estimator does not depend on knowledge of the statistics of cell cycle, death rates or total cell numbers. We validate the estimator and illustrate its features through comparison with published data and physiologically parameterized stochastic simulations, using it to suggest new experimental designs.