Blebs promote cell survival by assembling oncogenic signalling hubs

Weems, Andrew D.; Welf, Erik S.; Driscoll, Meghan; Zhou, Felix; Mazloom-Farsibaf, Hanieh; Chang, Bo-Jui; Murali, Vasanth Siruvallur; Gihana, Gabriel M; Bg, Weiss; Chi, Joseph; Rajendran, Divya; Dean, Kevin M.; Fiolka, Reto; Danuser, Gaudenz

doi:10.1038/s41586-023-05758-6

Cited by 49 publications

(54 citation statements)

References 81 publications

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“…The temporal autocorrelation curves of mean curvature and Septin intensity showed a high level of similarity, suggesting co-fluctuation of the two surface signals. Indeed, we had previously shown that surface regions of high Septin intensity with negative surface curvature for at least 30s display a correlation between negative curvature value and Septin intensity 38 . Whilst the majority of Septin pulses endured only one cycle of bleb formation and retraction, de novo formation of stable Septin structures appeared to be driven by several Septin pulses occurring in short succession.…”

Section: Individual Blebs Dynamically Recruit Septins To Local Surfac...mentioning

confidence: 91%

“…One such process is the assembly of Septin protein polymers at sites of negative curvature (from a cell-external perspective) emerging at the bleb necks. Our previous work 38 has shown that disrupting the bleb cycle diminishes Septin assembly at the cell surface. Here we now exploit the ability of u-Unwrap3D to track individual bleb cycles and quantify Septin accumulation by remapping surface morphology and a fluorescent marker of Septins to an appropriate 2D representation.…”

Section: Individual Blebs Dynamically Recruit Septins To Local Surfac...mentioning

confidence: 98%

“…Whilst the majority of Septin pulses endured only one cycle of bleb formation and retraction, de novo formation of stable Septin structures appeared to be driven by several Septin pulses occurring in short succession. We thus hypothesized that these were formed by iterative blebdriven curvature generation events resulting in local levels of Septin oligomers surpassing a threshold necessary for inter-oligomer polymerization and enabling stabilization through formation of higher-order structures 38 . The ability to spatiotemporally track individual blebs enabled us now to quantitatively test this model.…”

Section: Individual Blebs Dynamically Recruit Septins To Local Surfac...mentioning

confidence: 99%

“…This approach is robust to mesh quality and sampling errors, however deformations must be small between timepoints. For example, long or thin cell surface structures such as lamellipodia and filopodia suffer voxel undersampling, limiting the registration to cell surfaces with largely globular features such as blebs 38 . This problem could be remedied by mapping the 3D surface to the unit sphere [39][40][41] .…”

mentioning

confidence: 99%

“…Unfortunately, this strategy requires closed surface topologies with no holes (genus-0 surfaces), which is not generally guaranteed in live-cell microscopy. Alternatively, one can selectively segment surface motifs and track these in 3D whilst mapping surface-proximal molecular signal intensity 38,[45][46][47] . Like the 3D surface tracking, this .…”

mentioning

confidence: 99%

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Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Zhou

Weems

Gihana

et al. 2023

Preprint

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Signal transduction and cell function are governed by the spatiotemporal organization of membrane-associated molecules. Despite significant advances in visualizing molecular distributions by 3D light microscopy, cell biologists still have limited quantitative understanding of the processes implicated in the regulation of molecular signals at the whole cell scale. In particular, complex and transient cell surface morphologies challenge the complete sampling of cell geometry, membrane-associated molecular concentration and activity and the computing of meaningful parameters such as the cofluctuation between morphology and signals. Here, we introduce u-Unwrap3D, a framework to remap arbitrarily complex 3D cell surfaces and membrane-associated signals into equivalent lower dimensional representations. The mappings are bidirectional, allowing the application of image processing operations in the data representation best suited for the task and to subsequently present the results in any of the other representations, including the original 3D cell surface. Leveraging this surface-guided computing paradigm, we track segmented surface motifs in 2D to quantify the recruitment of Septin polymers by blebbing events; we quantify actin enrichment in peripheral ruffles; and we measure the speed of ruffle movement along topographically complex cell surfaces. Thus, u-Unwrap3D provides access to spatiotemporal analyses of cell biological parameters on unconstrained 3D surface geometries and signals.

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Section: Individual Blebs Dynamically Recruit Septins To Local Surfac...mentioning

confidence: 91%

Section: Individual Blebs Dynamically Recruit Septins To Local Surfac...mentioning

confidence: 98%

Section: Individual Blebs Dynamically Recruit Septins To Local Surfac...mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Zhou

Weems

Gihana

et al. 2023

Preprint

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Cancer Metastasis‐on‐a‐Chip for Modeling Metastatic Cascade and Drug Screening

Brooks,

Zhang,

Chen

et al. 2024

Adv Healthcare Materials

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Microfluidic chips are valuable tools for studying intricate cellular and cell‐microenvironment interactions. Traditional in vitro cancer models lack accuracy in mimicking the complexities of in vivo tumor microenvironment. However, cancer‐metastasis‐on‐a‐chip (CMoC) models combine the advantages of three dimensional (3D) cultures and microfluidic technology, serving as powerful platforms for exploring cancer mechanisms and facilitating drug screening. These chips are able to compartmentalize the metastatic cascade, deepening our understanding of its underlying mechanisms. This article provides an overview of current CMoC models, focusing on distinctive models that simulate invasion, intravasation, circulation, extravasation, and colonization, and their applications in drug screening. Furthermore, we discuss challenges faced by CMoC and microfluidic technologies, while exploring promising future directions in cancer research. The ongoing development and integration of these models into cancer studies are expected to drive transformative advancements in the field.This article is protected by copyright. All rights reserved

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Surviving the Storm: The Role of Poly‐ and Depolyploidization in Tissues and Tumors

Zhao,

He,

Zhao

et al. 2024

Advanced Science

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Polyploidization and depolyploidization are critical processes in the normal development and tissue homeostasis of diploid organisms. Recent investigations have revealed that polyaneuploid cancer cells (PACCs) exploit this ploidy variation as a survival strategy against anticancer treatment and for the repopulation of tumors. Unscheduled polyploidization and chromosomal instability in PACCs enhance malignancy and treatment resistance. However, their inability to undergo mitosis causes catastrophic cellular death in most PACCs. Adaptive ploid reversal mechanisms, such as multipolar mitosis, centrosome clustering, meiosis‐like division, and amitosis, counteract this lethal outcome and drive cancer relapse. The purpose of this work is to focus on PACCs induced by cytotoxic therapy, highlighting the latest discoveries in ploidy dynamics in physiological and pathological contexts. Specifically, by emphasizing the role of “poly‐depolyploidization” in tumor progression, the aim is to identify novel therapeutic targets or paradigms for combating diseases associated with aberrant ploidies.

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Blebs promote cell survival by assembling oncogenic signalling hubs

Cited by 49 publications

References 81 publications

Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D

Cancer Metastasis‐on‐a‐Chip for Modeling Metastatic Cascade and Drug Screening

Surviving the Storm: The Role of Poly‐ and Depolyploidization in Tissues and Tumors

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