PT  - JOURNAL ARTICLE
AU  - Linh Huynh
AU  - Jacob G. Scott
AU  - Peter J. Thomas
TI  - Inferring Density-Dependent Population Dynamics Mechanisms through Rate Disambiguation for Logistic Birth-Death Processes
AID  - 10.1101/2022.05.10.491405
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.05.10.491405
4099  - http://biorxiv.org/content/early/2022/05/11/2022.05.10.491405.short
4100  - http://biorxiv.org/content/early/2022/05/11/2022.05.10.491405.full
AB  - Density dependence is important in the ecology and evolution of microbial and cancer cells. Typically, we can only measure net growth rates, but the underlying density-dependent mechanisms that give rise to the observed dynamics can manifest in birth processes, death processes, or both. Therefore, we utilize the mean and variance of cell number fluctuations to separately identify birth and death rates from time series that follow stochastic birth-death processes with logistic growth. Our method provides a novel perspective on stochastic parameter identifiability, which we validate by analyzing the accuracy in terms of the discretization bin size. We apply our method to the scenario where a homogeneous cell population goes through three stages: (1) grows naturally to its carrying capacity, (2) is treated with a drug that reduces its carrying capacity, and (3) overcomes the drug effect to restore its original carrying capacity. In each stage, we disambiguate whether it happens through the birth process, death process, or some combination of the two, which contributes to understanding drug resistance mechanisms. In the case of limited data sets, we provide an alternative method based on maximum likelihood and solve a constrained nonlinear optimization problem to identify the most likely density dependence parameter for a given cell number time series. Our methods can be applied to other biological systems at different scales to disambiguate density-dependent mechanisms underlying the same net growth rate.Mathematics Subject Classifications 60J27 · 92D25 · 62M10 · 60J25Competing Interest StatementThe authors have declared no competing interest.