2020
DOI: 10.1091/mbc.e20-03-0210
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Spatial heterogeneity of the cytosol revealed by machine learning-based 3D particle tracking

Abstract: The structure of the cytosol across different length scales is a debated topic in cell biology. Here we present tools to measure the physical state of the cytosol by analyzing the 3D motion of nanoparticles expressed in cells. We find evidence that the physical structure of the cytosol is a fundamental source of variability in biological systems.

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Cited by 20 publications
(20 citation statements)
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“…While cell-averaged concentrations provide a single easily interpretable number, its obvious limitation is that it is just cell-averaged. Mitochondria, lysosomes, and nucleoli have a higher protein content than the cytosol or the nucleus [6], and the space immediately next to the membrane may experience a different extent of crowding (A. Minton, personal communication); even the bulk cytosol is highly heterogenous [40]. Thus, not all processes can be equally well captured by space-averaged measurements.…”
Section: Quantification Of Macromolecular Crowding In Living Cellsmentioning
confidence: 99%
“…While cell-averaged concentrations provide a single easily interpretable number, its obvious limitation is that it is just cell-averaged. Mitochondria, lysosomes, and nucleoli have a higher protein content than the cytosol or the nucleus [6], and the space immediately next to the membrane may experience a different extent of crowding (A. Minton, personal communication); even the bulk cytosol is highly heterogenous [40]. Thus, not all processes can be equally well captured by space-averaged measurements.…”
Section: Quantification Of Macromolecular Crowding In Living Cellsmentioning
confidence: 99%
“…The complexity of the cytoplasmic milieu could influence molecules’ behavior locally. Indeed, spatiotemporal heterogeneity in the diffusion of particles has been observed in multiple contexts such as E. coli, fungi, mammalian cells and even Xenopus egg extract using methods ranging from fluorescence correlation spectroscopy (FCS) to particle tracking (Bakshi et al, 2011; Baum et al, 2014; Dross et al, 2009; Huang et al, 2021; Manley et al, 2008; McLaughlin et al, 2020; Scipioni et al, 2018; Xiang et al, 2020).…”
Section: Introductionmentioning
confidence: 99%
“…Because each particle contains tens of fluorescent proteins, they can be tracked for relatively long periods of time without photobleaching. Additionally, the near-diffusive movements of GEMs suggest they do not interact strongly with eukaryotic cellular components, making them ideal reagents for rheological studies (Delarue et al, 2018; McLaughlin et al, 2020). Critically, their relatively large size and slow diffusion rates - comparable to large protein complexes such as ribosomes - allow GEMs to be tracked using modern high-speed cameras (which is still not attainable for individual fluorescent proteins).…”
Section: Introductionmentioning
confidence: 99%
“…The characterization of the rheological properties of an ensemble of biomolecules and their surrounding environment is important to understand molecule dynamics and macromolecular assembly (Delarue et al, 2018;Golkaram and Loos, 2019). Taking advantage of a recently developed technique that uses genetically encoded multimeric nanoparticles (GEMs), it was observed that the polarized growing zone of fungi is a crowded environment packed with macromolecules, resulting in a low local diffusivity for cytoplasmic biomolecules (Delarue et al, 2018;McLaughlin et al, 2020); this might favor the interaction of each macromolecular component with others and the formation of a functional complex that persists over a long period of time (Grimaldo et al, 2019). In S. cerevisiae, the polarisome components display local condensation behavior at the polarized tip (dense phase), which shows a dynamic exchange of polarisome proteins with the cytosolic pool (dilute phase), such as described above during cell cycle progression.…”
Section: Coordination Between Polarisome Condensation and Actin Polymerizationmentioning
confidence: 99%