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Single-particle tracking (SPT) is a powerful technique for probing the diverse physical properties of the cytoplasm. Genetically encoded nanoparticles provide an especially convenient tool for such investigations, as they can be expressed and tracked in cells via fluorescence. Among these, 40-nm genetically encoded multimerics (GEMs) provide a unique opportunity to explore the cytoplasm. Their size corresponds to that of ribosomes and big protein complexes, allowing us to investigate the effects of the cytoplasm on the diffusivity of these objects while excluding the influence of chemical interactions during stressful events and pathological conditions. However, the effects of GEM expression levels on the measured cytoplasmic diffusivity remain largely uncharacterized in mammalian cells. To optimize the GEMs tracking and assess expression level effects, we developed a doxycycline-inducible GEM expression system and compared it with a previously reported constitutive expression system. The inducible GEM expression system reduced the number of GEM particles from 2000 to as low as 5–500 per average 2D cell cytoplasmic area, depending on doxycycline concentration and incubation time. This optimization enabled adjustment of particle density for imaging and improved homogeneity across the cell population. Moreover, we enhanced the analysis of GEM diffusivity by incorporating an effective diffusion coefficient that accounts for the type of motion and by quantifying motion heterogeneity through standard deviations of particle displacements within and between cells.
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Spatial heterogeneity of the cytosol revealed by machine learning-based 3D particle tracking
The spatial structure and physical properties of the cytosol are not well understood. Measurements of the material state of the cytosol are challenging due to its spatial and temporal heterogeneity. Recent development of genetically encoded multimeric nanoparticles (GEMs) has opened up study of the cytosol at the length scales of multiprotein complexes (20–60 nm). We developed an image analysis pipeline for 3D imaging of GEMs in the context of large, multinucleate fungi where there is evidence of functional compartmentalization of the cytosol for both the nuclear division cycle and branching. We applied a neural network to track particles in 3D and then created quantitative visualizations of spatially varying diffusivity. Using this pipeline to analyze spatial diffusivity patterns, we found that there is substantial variability in the properties of the cytosol. We detected zones where GEMs display especially low diffusivity at hyphal tips and near some nuclei, showing that the physical state of the cytosol varies spatially within a single cell. Additionally, we observed significant cell-to-cell variability in the average diffusivity of GEMs. Thus, the physical properties of the cytosol vary substantially in time and space and can be a source of heterogeneity within individual cells and across populations.
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- PAR ID:
- 10176272
- Date Published:
- Journal Name:
- Molecular Biology of the Cell
- Volume:
- 31
- Issue:
- 14
- ISSN:
- 1059-1524
- Page Range / eLocation ID:
- 1498 to 1511
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1091/mbc.E20-03-0210
