Biology subjects

Mirvis, M.

Publications and source records attributed to Mirvis, M..

5 recordsLinked to original sources

bioRxiv2026

Size-dependent nucleus-vacuole interactions in budding yeast demonstrate a role for steric packing in organelle shape and positioning

Although organelles are often studied one at a time, whole-cell imaging studies show that organelles take up a large part of the cell volume such that they are crowded together. Here we use whole cell soft X-ray tomography imaging to investigate how such crowding affects organelle size scaling, position, and shape, focusing on the nucleus and vacuole of budding yeast. We find that, as the vacuole enlarges beyond normal range, the nucleus loses its normal scaling relation with respect to cell volume, becomes displaced from its normal position near the cell center, and becomes progressively deformed from a sphere into a pancake shape. Using a whole-cell integrated shape modeling framework, we find that these changes are statistically correlated and give rise to distinct modes in cell organization space. Using a simplified mechanical model for two initially spherical compartments contained inside a confined intracellular space, we are able to recapitulate the effects seen in the experimental data, indicating that these observations are consistent with a purely mechanical interaction. Taken together, our work indicates that, in addition to the well-known protein-based organelle-organelle interactions, physical steric packing of organelles inside a limited cellular volume also plays a large role in the inter-organelle relationships and the overall geometry of the cell.

cell biology↗

bioRxiv2025

A scoping study of the whole-cell imaging literature: a foundational corpus, potential for data-mining and research synthesis, and a call for standardization of an emerging field

The level of cellular organization bridging the mesoscale and whole-cell scale is coming into focus as a new frontier in cell biology. Great progress has been made in unraveling the complex physical and functional interconnectivity of organelles, but how the entire organelle network is spatially arranged within the cytoplasm is only beginning to be explored. Drawing on cross-disciplinary research synthesis methods, we systematically curated the whole-cell volumetric imaging literature, resulting in a corpus consisting of 89 studies and 118 image datasets. We describe the trajectory and current state of the field between 2004 and 2024. A broad characterization, or "scoping review", of bibliometrics, study design, and reporting practices shows accelerating technological development and research output. We find high variability in study design and reporting practices, including imaging modality, model organism, cellular contexts, organelles imaged, and analyses. Due to the laborious, low-throughput nature of most volumetric imaging methods, we find trends toward small sample sizes (<10 cells) and small cell types. We describe common quantitative analyses across studies, including volumetric ratios of organelles and inter-organelle contact analyses. This work establishes the initial iteration of a growing dataset of whole-cell imaging literature and data, and motivates a call for standardized whole-cell imaging study design, reporting, and data sharing practices in the context of an emerging sub-field of cell biology. Our curated dataset now provides the basis for a plethora of future aggregate and comparative analyses to reveal larger patterns and generalized hypotheses about the systems behavior and regulation of whole-cell organelle networks. More broadly, we showcase the potential of new rigorous secondary research methods to strengthen cell biologys literature review and reproducibility toolkit, create new avenues for discovery, and promote open research practices that support secondary data-reuse and integration.

cell biology↗

bioRxiv2024

Automated segmentation of soft X-ray tomography: native cellular structure with sub-micron resolution at high throughput for whole-cell quantitative imaging in yeast

Soft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at sub-optical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based auto-segmentation pipeline to segment and label cellular structures in hundreds of cells across three Saccharomyces cerevisiae strains. This task-based pipeline employs manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the 3D whole-cell morphometric characteristics of wild-type, VPH1-GFP, and vac14 strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts. Significance StatementO_LISoft X-ray tomography offers many powerful features for whole-cell multi-organelle imaging, but, like other high resolution volumetric imaging modalities, is typically limited by low throughput due to laborious segmentation. C_LIO_LIAuto-segmentation for soft X-ray tomography overcomes this limitation, enabling statistical 3D morphometric analysis of multiple organelles in whole cells across cell populations. C_LIO_LIThe combination of high 3D resolution of SXT data with statistically useful throughput represents an avenue for more thorough characterizations of cells in toto and opens new mesoscale biological questions and statistical whole-cell modeling of organelle and cell morphology, interactions, and responses to perturbations. C_LI

cell biology↗

bioRxiv2021

The short flagella 1 (SHF1) gene in Chlamydomonas encodes a Crescerin TOG-domain protein required for late stages of flagellar growth.

Length control of flagella represents a simple and tractable system to investigate the dynamics of organelle size. Models for flagellar length control in the model organism, Chlamydomonas reinhardtii have focused on the length-dependence of the intraflagellar transport (IFT) system which manages the delivery and removal of axonemal subunits at the tip of the flagella. One of these cargoes, tubulin, is the major axonemal subunit, and its frequency of arrival at the tip plays a central role in size control models. However, the mechanisms determining tubulin dynamics at the tip are still poorly understood. We discovered a loss-of-function mutation that leads to shortened flagella, and found that this was an allele of a previously described gene, SHF1, whose molecular identity had not previously been determined. We found that SHF1 encodes a Chlamydomonas ortholog of Crescerin, previously identified as a cilia-specific TOG-domain array protein that can bind tubulin via its TOG domains and increase tubulin polymerization rates. In this mutant, flagellar regeneration occurs with the same initial kinetics as wild-type cells, but plateaus at a shorter length. Using a computational model in which the flagellar microtubules are represented by a differential equation for flagellar length combined with a stochastic model for cytoplasmic microtubule dynamics, we found that our experimental results are best described by a model in which Crescerin/SHF1 binds tubulin dimers in the cytoplasm and transports them into the flagellum. We suggest that this TOG-domain protein is necessary to efficiently and preemptively increase intra-flagella tubulin levels to offset decreasing IFT cargo at the tip as flagellar assembly progresses.

cell biology↗

bioRxiv2018

Heterogeneous Dynamics and Mechanisms of Primary Cilium Disassembly in Mammalian Cells

The primary cilium is a central signaling hub in cell proliferation and differentiation, and is built and disassembled every cell cycle in most animal cells. Disassembly is critically important: misregulation or delay of disassembly leads to cell cycle defects. The physical means by which cilia are disassembled are poorly understood, and thought to involve resorption of disassembled components into the cell body. To investigate cilium disassembly in mammalian cells, we used rapid live-cell imaging to comprehensively characterize individual disassembly events. The predominant mode of disassembly was rapid cilium loss via deciliation, in which the membrane and axoneme of the cilium was shed from the cell. Gradual resorption was also observed, as well as events in which a period of gradual resorption ended with rapid deciliation. Deciliation resulted in intact shed cilia that could be recovered from culture medium and contained both membrane and axoneme proteins. We modulated levels of katanin and intracellular calcium, two putative regulators of deciliation, and found that excess katanin promotes disassembly by deciliation, independently of calcium. Together, these results demonstrate that mammalian ciliary disassembly involves a tunable decision between deciliation and resorption.

cell biology↗