Rho and F-actin self-organize within an artificial cell cortex

Landino, Jennifer; Leda, Marcin; Michaud, Ani; Swider, Zachary T.; Prom, Mariah J.; Field, Christine M.; Vecchiarelli, Anthony G.; Goryachev, Andrew B.; Miller, Ann L.

doi:10.1016/j.cub.2021.10.021

Cited by 25 publications

(38 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cortical excitability is absent in immature X. laevis oocytes, but clearly evident in developing embryos and in artificially activated eggs several hours after activation (Bement et al ., 2015). Similar oscillatory dynamics have also been reported using synthetic cortices based on supported lipid bilayers and activated egg cytoplasm (Landino et al, 2021). However, when and how the transition to cortical excitability occurs remains unknown.…”

Section: Resultssupporting

confidence: 82%

“…Similar oscillatory dynamics have also been reported using synthetic cortices based on supported lipid bilayers and activated egg cytoplasm (Landino et al, 2021). However, when and how the transition to cortical excitability occurs remains unknown.…”

Section: Egg Activation Initiates Cortical Excitabilitysupporting

confidence: 72%

“…Moreover, UtrCH-labeled samples also allow quantification of informative wave metrics, namely, wave period (time between consecutive waves), temporal width, and peak-to-trough wave amplitude, all of which can be determined by following UtrCH fluorescence over time (Supplemental Figure 1A). As reported previously, these measurements can be made with sub-frame accuracy by simultaneously measuring n sub-regions of a field of view and averaging the results (Landino et al 2021; Supplemental Figure 1B). In the experiments and analyses below, we have incorporated this approach into an analysis pipeline using the free and open-source language Python 3, and further expanded it to allow analysis of changing wave properties over time (Supplemental Figure 1C).…”

Section: Resultsmentioning

confidence: 98%

“…However, these waves were low in amplitude relative to the excitable F-actin waves outside of the furrow and were largely obscured by the thick cables of F-actin that make up the contractile ring (yellow arrowheads, Figure 6A; Video 11, Video 12). Because the cables were stable over space and time relative to the traveling waves, calculating the change in fluorescence over time in each pixel (also known as a difference subtraction; Bement et al ., 2015; Landino et al ., 2021) allowed better visualization and quantification of waves in the cleavage furrow (Figure 6A, A’; Video 11, Video 12). When compared to non-furrow waves, there was no significant difference in the wave period or temporal width (Figure 6B, C).…”

Section: Resultsmentioning

confidence: 99%

“…Plasmids were linearized following the open reading frame and used as a template for mRNA synthesis using the mMessage Machine SP6 kit (Ambion), mRNAs were polyadenylated using a Poly(A) tailing kit (Ambion) and purified with a phenol-chloroform extraction and isopropanol precipitation. Alexa Fluor® 647-conjugated UtrCH protein was generated as described previously (Landino et al . 2021).…”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

Cell cycle and developmental control of cortical excitability in Xenopus laevis

Swider

Michaud

Leda

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

Interest in cortical excitability – the ability of the cell cortex to generate traveling waves of protein activity – has grown considerably over the past twenty years. Attributing biological functions to cortical excitability requires an understanding of the natural behavior of excitable waves and the ability to accurately quantify wave properties. Here we have investigated and quantified the onset of cortical excitability in X. laevis eggs and embryos, and the changes in cortical excitability throughout early development. We found that cortical excitability begins to manifest shortly after egg activation. Further, we identified a close relationship between wave properties – such as wave frequency and amplitude – and cell cycle progression as well as cell size. Finally, we identified quantitative differences between cortical excitability in the cleavage furrow relative to non-furrow cortical excitability and showed that these wave regimes are mutually exclusive.

show abstract

Section: Resultssupporting

confidence: 82%

Section: Egg Activation Initiates Cortical Excitabilitysupporting

confidence: 72%

Section: Resultsmentioning

confidence: 98%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Cell cycle and developmental control of cortical excitability in Xenopus laevis

Swider

Michaud

Leda

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Benefits and challenges of reconstituting the actin cortex

Waechtler,

Jayasankar,

Morin

et al. 2024

Cytoskeleton

View full text Add to dashboard Cite

The cell's ability to change shape is a central feature in many cellular processes, including cytokinesis, motility, migration, and tissue formation. The cell constructs a network of contractile proteins underneath the cell membrane to form the cortex, and the reorganization of these components directly contributes to cellular shape changes. The desire to mimic these cell shape changes to aid in the creation of a synthetic cell has been increasing. Therefore, membrane‐based reconstitution experiments have flourished, furthering our understanding of the minimal components the cell uses throughout these processes. Although biochemical approaches increased our understanding of actin, myosin II, and actin‐associated proteins, using membrane‐based reconstituted systems has further expanded our understanding of actin structures and functions because membrane–cortex interactions can be analyzed. In this review, we highlight the recent developments in membrane‐based reconstitution techniques. We examine the current findings on the minimal components needed to recapitulate distinct actin structures and functions and how they relate to the cortex's impact on cellular mechanical properties. We also explore how co‐processing of computational models with wet‐lab experiments enhances our understanding of these properties. Finally, we emphasize the benefits and challenges inherent to membrane‐based, reconstitution assays, ranging from the advantage of precise control over the system to the difficulty of integrating these findings into the complex cellular environment.

show abstract