Harish Venkatachalapathy, Cole Brzakala, Eric Batchelor, Samira M Azarin, Casim A Sarkar
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引用次数: 0
Abstract
Energy landscapes can provide intuitive depictions of population heterogeneity and dynamics. However, it is unclear whether individual cell behavior, hypothesized to be determined by initial position and noise, is faithfully recapitulated. Using the p21-/Cdk2-dependent quiescence-proliferation decision in breast cancer dormancy as a testbed, we examined single-cell dynamics on the landscape when perturbed by hypoxia, a dormancy-inducing stress. Combining trajectory-based energy landscape generation with single-cell time-lapse microscopy, we found that a combination of initial position and velocity on a p21/Cdk2 landscape, but not position alone, was required to explain the observed cell fate heterogeneity under hypoxia. This is likely due to additional cell state information such as epigenetic features and/or other species encoded in velocity but missing in instantaneous position determined by p21 and Cdk2 levels alone. Here, velocity dependence manifested as inertia: cells with higher cell cycle velocities prior to hypoxia continued progressing along the cell cycle under hypoxia, resisting the change in landscape towards cell cycle exit. Such inertial effects may markedly influence cell fate trajectories in tumors and other dynamically changing microenvironments where cell state transitions are governed by coordination across several biochemical species.
期刊介绍:
npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology.
We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.