Pylvänäinen, J. | Search bioRxiv

bioRxiv2025

Filopodome proteomics identifies CCT8 as a MYO10 interactor critical for filopodia functions

Cancer cells utilize filopodia to explore, adhere to, and invade their surrounding microenvironment, yet the protein networks that organize these protrusions remain incompletely defined. To uncover the molecular machinery underlying MYO10-positive filopodia, we targeted the fast biotin ligase TurboID to the filopo-dia tip-localized motor protein MYO10. Proximity biotinylation in two cell types revealed hundreds of potential MYO10 interactors. Surprisingly, there was limited overlap between the cell lines, indicating a previously unknown level of cell-type specificity in filopodia composition. A targeted microscopy and siRNA screen identified MINK1, SCRIB, CSNK1A1, and CCT8 as new regulators of filopodia formation. Focusing on one common interactor between cell lines, CCT8, known as a subunit of the chaperonin TRiC (TCP1 Ring Complex), we found that CCT8 associates with the MYO10 motor domain and regulates MYO10 filopodia independently of TRiC. Depleting CCT8 affected filopodia dynamics and impaired cell spreading, migration, and invasion in breast cancer cells. These findings establish CCT8 as a TRiC-independent regulator of MYO10 filopodia across different cancer cell types, highlight the surprising cell-type-specificity of filopodia composition, and provide a strategy and resource for studying filopodia in various biological contexts.

cell biology↗

bioRxiv2022

Fast4DReg: Fast registration of 4D microscopy datasets

Unwanted sample drift is a common issue that plagues microscopy experiments, preventing accurate temporal quantification of biological processes. While multiple methods and tools exist to correct images post-acquisition, performing drift correction of large 3D videos using open-source solutions remains challenging and time-consuming. Here we present a new tool developed for ImageJ/Fiji called Fast4DReg that can quickly correct axial and lateral drift in 3D video microscopy datasets. Fast4DReg works by creating intensity projections along multiple axes and estimating the drift between frames using 2D cross-correlations. Using synthetic and acquired datasets, we demonstrate that Fast4DReg performs better than other state-of-the-art open-source drift correction tools and significantly outperforms them in speed (5x to 60x). We also demonstrate that Fast4DReg can be used to register misaligned channels in 3D using either calibration slides or misaligned images directly. Altogether Fast4DReg provides a quick and easy-to-use method to correct 3D imaging data before further visualization and analysis. Fast4DReg is available on GitHub.

bioinformatics↗