Imaging cell architecture and dynamics DOI
Lucy Collinson, Guillaume Jacquemet

Journal of Cell Science, Год журнала: 2024, Номер 137(20)

Опубликована: Окт. 15, 2024

Язык: Английский

TRIM9 Controls Growth Cone Responses to Netrin Through DCC and UNC5C DOI
Sampada P. Mutalik, Chris T. Ho,

Ellen C. O’Shaughnessy

и другие.

Journal of Neurochemistry, Год журнала: 2025, Номер 169(1)

Опубликована: Янв. 1, 2025

ABSTRACT The guidance cue netrin‐1 promotes both growth cone attraction and repulsion. How elicits diverse axonal responses, beyond engaging the netrin receptor DCC UNC5 family members, remains elusive. Here, we demonstrate that murine induces biphasic responses in cortical neurons: Attraction at lower concentrations repulsion higher using a microfluidic‐based gradient bath application of netrin‐1. We find repulsive turning is blocked by knockdown UNC5C, whereas attractive impaired DCC. TRIM9 brain‐enriched E3 ubiquitin ligase previously shown to bind cluster plasma membrane regulate netrin‐dependent responses. However, whether also regulated remained be seen. In this study, show localizes interacts with receptor, UNC5C. deletion Trim9 alters axon changes cones size response was required for netrin‐1‐dependent surface levels UNC5C during morphogenesis. regulates area negatively FAK activity absence Together, our work demonstrates image

Язык: Английский

Процитировано

2

TRIM9 controls growth cone responses to netrin through DCC and UNC5C DOI Open Access
Sampada P. Mutalik,

Ellen C. O’Shaughnessy,

Chris T. Ho

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Май 8, 2024

Abstract The guidance cue netrin-1 promotes both growth cone attraction and repulsion. How elicits these diverse axonal responses, beyond engaging the attractive receptor DCC repulsive receptors of UNC5 family, remains elusive. Here we demonstrate that murine induces biphasic responses in cortical neurons: at lower concentrations repulsion higher using a microfluidic-based gradient bath application netrin-1. TRIM9 is brain-enriched E3 ubiquitin ligase previously shown to bind cluster plasma membrane regulate netrin-dependent responses. However, whether also regulated remained be seen. In this study, show localizes interacts with netrin receptor, UNC5C, deletion Trim9 alters was required for netrin-1-dependent changes surface levels total UNC5C during morphogenesis. We regulates area negatively FAK activity absence investigate dynamics pH-mScarlet fused extracellular domain UNC5C. Minutes after addition, drop TRIM9-independent fashion, however mobility Together work demonstrates

Язык: Английский

Процитировано

2

Deciphering the nanoscale architecture of presynaptic actin using a micropatterned presynapse-on-glass model DOI Creative Commons

Sofia Tumminia,

Louisa Mezache,

Theresa Wiesner

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 5, 2024

Abstract Chemical synapses are fundamental units for the transmission of information throughout nervous system. The cyto-skeleton allows to build, maintain and transform both pre- postsynaptic contacts, yet its organization role unique synaptic nanostructures still poorly understood. Here we present a presynapse-on-glass model where presynaptic specializations robustly induced along axons cultured neurons by micropatterned dots neuroligin, allowing controlled orientation easy optical visualization functional presynapses. We demonstrate relevance usefulness this study actin architecture, showing that majority presynapses enriched in actin, with enrichment being correlated higher cycling activity. confirm our previous results on bead-induced identifying same distinct with-in presynapses: corrals, rails mesh. Furthermore, leverage model, visualizing arrangement these structures relative active zone nanoclusters using multicolor 3D Single Molecule Localization Microscopy (SMLM), sub-diffractive localization exocytic events correlative live-cell SMLM approach.

Язык: Английский

Процитировано

1

Highly adaptable deep-learning platform for automated detection and analysis of vesicle exocytosis DOI Creative Commons

Abed Alrahman Chouaib,

Hsin‐Fang Chang,

Omnia M. Khamis

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Авг. 6, 2024

Abstract Vesicle exocytosis is a fundamental component of intercellular communication, in all organisms. It has been studied for decades, using various imaging tools. Nevertheless, research still limited by the lack reliable automated analysis procedures. To address this, we developed Intelligent Exocytosis Analysis Platform (IVEA), nearly universal solution analyzing acquired with live cell imaging. IVEA applicable to wide variety experimental model systems, microscopes and reporter fluorophores. combines state-of-the-art deep-learning computer vision regimes enable fully large data. runs as FIJI plugin does not require prior training or human intervention. 60 times faster than manual able detect rare events often missed eye. Overall, represents breakthrough cellular secretory mechanisms transformative potential field.

Язык: Английский

Процитировано

0

Deep learning detection of dynamic exocytosis events in fluorescence TIRF microscopy DOI Creative Commons
Hugo Lachuer, Emmanuel Moebel, Anne‐Sophie Macé

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Сен. 12, 2024

Abstract Segmentation and detection of biological objects in fluorescence microscopy is paramount importance cell imaging. Deep learning approaches have recently shown promise to advance, automatize accelerate analysis. However, most the interest has been given segmentation static 2D/3D images whereas dynamic processes obtained from time-lapse acquisitions less explored. Here we adapted DeepFinder, a U-net originally designed for 3D noisy cryo-electron tomography (cryo-ET) data, rare exocytosis events (termed ExoDeepFinder) observed temporal series 2D Total Internal Reflection Fluorescent Microscopy (TIRFM) images. ExoDeepFinder achieved good absolute performances with relatively small training dataset 60 cells/∼12000 events. We rigorously compared deep unsupervised conventional methods literature. outcompeted tested methods, but also exhibited greater plasticity experimental conditions when under drug treatments after changes line or imaged reporter. This robustness unseen did not require re-training demonstrating generalization capability ExoDeepFinder. ExoDeepFinder, as well annotated datasets, were made transparent available through an open-source software Napari plugin can directly be applied custom user data. The apparent detect open new opportunities future deep-learning guided analysis live-cell

Язык: Английский

Процитировано

0

Imaging cell architecture and dynamics DOI
Lucy Collinson, Guillaume Jacquemet

Journal of Cell Science, Год журнала: 2024, Номер 137(20)

Опубликована: Окт. 15, 2024

Язык: Английский

Процитировано

0