A pH-driven transition of the cytoplasm from a fluid- to a solid-like state promotes entry into dormancy

Abstract

Cells can enter into a dormant state when faced with unfavorable conditions. However, how cells enter into and recover from this state is still poorly understood. Here, we study dormancy in different eukaryotic organisms and find it to be associated with a significant decrease in the mobility of organelles and foreign tracer particles. We show that this reduced mobility is caused by an influx of protons and a marked acidification of the cytoplasm, which leads to widespread macromolecular assembly of proteins and triggers a transition of the cytoplasm to a solid-like state with increased mechanical stability. We further demonstrate that this transition is required for cellular survival under conditions of starvation. Our findings have broad implications for understanding alternative physiological states, such as quiescence and dormancy, and create a new view of the cytoplasm as an adaptable fluid that can reversibly transition into a protective solid-like state.DOI: http://dx.doi.org/10.7554/eLife.09347.001

Relative distance between tracers as a measure of diffusivity within moving aggregates

“…Often, tracers move within domains of finite size, for example individual molecules inside single cells [7,17,31] or individual cells within cell aggregates [1,32].…”

“…2c) Often, the time-averaging is applied for the estimation of the diffusion coefficient in data where the statistics are not strong enough to deliver a reliable ensemble average. Examples for such cases are usually experiments in which a high effort is required to measure the trajectory of a single tracer, such as the study of the motion of individual tracers within cells or single cells themselves [7,8,[15][16][17]. However, as became apparent recently, care should be taken when interpreting the time-averaged data [18].…”

“…Similar measurements can be performed on a subcellular level with injected particles or tracing cell organelles as means of quantifiying the physical properties of the cell cytoplasm [7,8]. By assuming a random motion of cells within agglomerates or tracers in the cell cytoplasm one typically measures the mean squared displacement (MSD) and thus gets access to the diffusion constant and the scaling of diffusion.…”

Molecular simulations of cellular processes

“…As highlighted in this review, the input quantities of the latter methods can be experimentally measured or calculated from detailed particle-based simulations. The second challenge will likely trigger the development of accurate force fields (Leonarski et al 2013;Ivani et al 2016;Song et al 2017;Wang et al 2017a) that are transferable to different cell conditions (Rebelo et al 2013;Parry et al 2014;Joyner et al 2016;Munder et al 2016;Sun and Fang 2016), as well as diffusion-reaction schemes (Schöneberg et al 2014;Michalski and Loew 2016;Epstein and Xu 2016) and agent-based simulations (Azimi et al 2011).…”

“…Hence, they determine the macroscopic properties of the cytoplasm both in physiological conditions and under stress (Parry et al 2014;Joyner et al 2016;Munder et al 2016). These and the previous examples are clear evidence of the importance of chemical interactions between macromolecules, despite their weak strength, and suggest that they are as relevant as the specific interactions responsible for biomolecule folding and complex formation.…”