Filopodia-mediated basement membrane assembly at pre-invasive tumor boundaries

Ductal carcinoma in situ (DCIS) is a pre-invasive stage of breast cancer, where the tumor is encapsulated by a basement membrane (BM). At the invasive phase, the BM barrier is compromised enabling tumor cells to escape into the surrounding stroma. The molecular mechanisms that establish and maintain an epithelial BM barrier in vivo are poorly understood. Myosin-X (MYO10) is a filopodia-inducing motor protein implicated in metastasis and poor clinical outcome in patients with invasive breast cancer (IBC). We compared MYO10 expression in patient-matched normal breast tissue and DCIS lesions and found elevated MYO10 expression in DCIS samples, suggesting that MYO10 might facilitate the transition from DCIS to IBC. Indeed, MYO10 promoted the formation of filopodia and cell invasion in vitro and positively regulated the dissemination of individual cancer cells from IBC lesions in vivo. However, MYO10-depleted DCIS xenografts were, unexpectedly, more invasive. In these xenografts, MYO10 depletion compromised BM formation around the lesions resulting in poorly defined tumor borders and increased cancer cell dispersal into the surrounding stroma. Moreover, MYO10-depleted tumors showed increased EMT-marker-positive cells, specifically at the tumor periphery. We also observed cancer spheroids undergoing rotational motion and recruiting BM components in a filopodia-dependent manner to generate a near-continuous extracellular matrix boundary. Taken together, our data identify a protective role for MYO10 in early-stage breast cancer, where MYO10-dependent tumor cell protrusions support BM assembly at the tumor-stroma interface to limit cancer progression, and a pro-invasive role that facilitates cancer cell dissemination at later stages.

Emilia Peuhu,  Guillaume Jacquemet, Colinda LGJ Scheele, Aleksi Isomursu, Ilkka Paatero, Kerstin Thol, Maria Georgiadou, Camilo Guzmán, Satu Koskinen, Asta Laiho, Laura L Elo, Pia Boström, Pauliina Hartiala, Jacco van Rheenen, Johanna Ivaska

Read our paper on biorxiv

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 pipeline developed as an ImageJ/Fiji macro 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.

Joanna W Pylvänäinen, Romain F Laine, Sujan Ghimire, Gautier Follain, Ricardo Henriques, Guillaume Jacquemet

Read our paper on biorxiv

TrackMate 7: integrating state-of-the-art segmentation algorithms into tracking pipelines

TrackMate is an automated tracking software used to analyze bioimages and is distributed as a Fiji plugin. Here, we introduce a new version of TrackMate. TrackMate 7 is built to address the broad spectrum of modern challenges researchers face by integrating state-of-the-art segmentation algorithms into tracking pipelines. We illustrate qualitatively and quantitatively that these new capabilities function effectively across a wide range of bio-imaging experiments.

Dmitry Ershov, Minh-Son Phan, Joanna W. Pylvänäinen, Stéphane U. Rigaud, Laure Le Blanc, Arthur Charles-Orszag, James R. W. Conway, Romain F. Laine, Nathan H. Roy, Daria Bonazzi, Guillaume Duménil, Guillaume Jacquemet, Jean-Yves Tinevez

Read our paper here

Myosin-X and talin modulate integrin activity at filopodia tips

Filopodia assemble unique integrin-adhesion complexes to sense the extracellular matrix. However, the mechanisms of integrin regulation in filopodia are poorly defined. Here, we report that active integrins accumulate at the tip of myosin-X (MYO10)-positive filopodia, while inactive integrins are uniformly distributed. We identify talin and MYO10 as the principal integrin activators in filopodia. In addition, deletion of MYO10’s FERM domain, or mutation of its β1-integrin-binding residues, reveals MYO10 as facilitating integrin activation, but not transport, in filopodia. However, MYO10’s isolated FERM domain alone cannot activate integrins, potentially because of binding to both integrin tails. Finally, because a chimera construct generated by swapping MYO10-FERM by talin-FERM enables integrin activation in filopodia, our data indicate that an integrin-binding FERM domain coupled to a myosin motor is a core requirement for integrin activation in filopodia. Therefore, we propose a two-step integrin activation model in filopodia: receptor tethering by MYO10 followed by talin-mediated integrin activation.

Mitro Miihkinen, Max L.B. Grönloh, Ana Popović, Helena Vihinen, Eija Jokitalo, Benjamin T. Goult, Johanna Ivaska, GuillaumeJacquemet

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Democratising deep learning for microscopy with ZeroCostDL4Mic

Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources to train DL networks leads to an accessibility barrier that novice users often find difficult to overcome. Here, we present ZeroCostDL4Mic, an entry-level platform simplifying DL access by leveraging the free, cloud-based computational resources of Google Colab. ZeroCostDL4Mic allows researchers with no coding expertise to train and apply key DL networks to perform tasks including segmentation (using U-Net and StarDist), object detection (using YOLOv2), denoising (using CARE and Noise2Void), super-resolution microscopy (using Deep-STORM), and image-to-image translation (using Label-free prediction – fnet, pix2pix and CycleGAN). Importantly, we provide suitable quantitative tools for each network to evaluate model performance, allowing model optimisation. We demonstrate the application of the platform to study multiple biological processes.

Read our paper published in Nature Communications

Read our press release on the Turku Bioscience website

Access ZeroCostDL4Mic on github

Lucas von Chamier, Romain F. Laine, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-Pérez, Pieta K. Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L. Jones, Loïc A Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques

Automated cell tracking using StarDist and TrackMate

The ability of cells to migrate is a fundamental physiological process involved in embryonic development, tissue homeostasis, immune surveillance, and wound healing. Therefore, the mechanisms governing cellular locomotion have been under intense scrutiny over the last 50 years. One of the main tools of this scrutiny is live-cell quantitative imaging, where researchers image cells over time to study their migration and quantitatively analyze their dynamics by tracking them using the recorded images. Despite the availability of computational tools, manual tracking remains widely used among researchers due to the difficulty setting up robust automated cell tracking and large-scale analysis. Here we provide a detailed analysis pipeline illustrating how the deep learning network StarDist can be combined with the popular tracking software TrackMate to perform 2D automated cell tracking and provide fully quantitative readouts. Our proposed protocol is compatible with both fluorescent and widefield images. It only requires freely available and open-source software (ZeroCostDL4Mic and Fiji), and does not require any coding knowledge from the users, making it a versatile and powerful tool for the field. We demonstrate this pipeline’s usability by automatically tracking cancer cells and T cells using fluorescent and brightfield images. Importantly, we provide, as supplementary information, a detailed step-by-step protocol to allow researchers to implement it with their images.

Elnaz Fazeli, Nathan H. Roy, Gautier Follain, Romain F. Laine, Lucas von Chamier, Pekka E. Hänninen, John E. Eriksson, Jean-Yves Tinevez, Guillaume Jacquemet

Link to our biorXiv preprint

Filopodia in cell adhesion, 3D migration and cancer cell invasion

This review discusses recent advances in our understanding of the role filopodia and filopodia-like structures in cell adhesion and three dimensional (3D) cell migration both in vitro and in vivo. In particular, we focus on recent advances demonstrating that filopodia are involved in substrate tethering and environment sensing in vivo. We further discuss the emerging role of filopodia and filopodial proteins in tumor dissemination as mounting in vitroin vivo and clinical evidence suggest that filopodia drive cancer cell invasion and highlight filopodia proteins as attractive therapeutic targets. Finally, we outline outstanding questions that remain to be addressed to elucidate the role of filopodia during 3D cell migration.

Guillaume Jacquemet, Hellyeh Hamidi & Johanna Ivaska

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Fluctuation-Based Super Resolution Traction Force Microscopy

Cellular mechanics play a crucial role in tissue homeostasis and are often misregulated in disease. Traction force microscopy is one of the key methods that has enabled researchers to study fundamental aspects of mechanobiology; however, traction force microscopy is limited by poor resolution. Here, we propose a simplified protocol and imaging strategy that enhances the output of traction force microscopy by increasing i) achievable bead density and ii) the accuracy of bead tracking. Our approach relies on super-resolution microscopy, enabled by fluorescence fluctuation analysis. Our pipeline can be used on spinning-disk confocal or widefield microscopes and is compatible with available analysis software. In addition, we demonstrate that our workflow can be used to gain biologically relevant information and is suitable for fast long-term live measurement of traction forces even in light-sensitive cells. Finally, using fluctuation-based traction force microscopy, we observe that filopodia align to the force field generated by focal adhesions.

Aki Stubb, Romain F. Laine, Mitro Miihkinen, Hellyeh Hamidi, Camilo Guzmán, Ricardo Henriques, Guillaume Jacquemet*, Johanna Ivaska*

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Produce cell-derived matrices for migration studies

Cell-derived matrices for studying cell proliferation and directional migration in a complex 3D microenvironment

2D surfaces offer simple analysis of cells in culture, yet these often yield different cell morphologies and responses from those observed in vivo. Considerable effort has therefore been expended on the generation of more tissue-like environments for the study of cell behavior in vitro. Purified matrix proteins provide a 3D scaffold that better mimics the in vivo situation; however, these are far removed from the complex tissue composition seen in vivo. Cell-derived matrices (CDMs) offer a more physiologically relevant alternative for studying in vivo-like cell behavior in vitro. In the protocol described here, fibroblasts cultured on gelatin-coated surfaces are maintained in the presence of ascorbic acid to strengthen matrix deposition over 1–3 weeks. The resulting fibrillar CDMs are denuded of cells, and other cells are subsequently cultured on them, after which their behavior is monitored. We also demonstrate how to use CDMs as an in vivo-relevant reductionist model for studying tumor-stroma-induced changes in carcinoma cell proliferation and migration.

Riina Kaukonen, Guillaume Jacquemet, Hellyeh Hamidi & Johanna Ivaska

Tracking filopodia using FiloQuant

FiloQuant reveals increased filopodia density during breast cancer progression

Defective filopodia formation is linked to pathologies such as cancer, wherein actively protruding filopodia, at the invasive front, accompany cancer cell dissemination. Despite wide biological significance, delineating filopodia function in complex systems remains challenging and is particularly hindered by lack of compatible methods to quantify filopodia properties. Here, we present FiloQuant, a freely available ImageJ plugin, to detect filopodia-like protrusions in both fixed- and live-cell microscopy data. We demonstrate that FiloQuant can extract quantifiable information, including protrusion dynamics, density, and length, from multiple cell types and in a range of microenvironments. In cellular models of breast ductal carcinoma in situ, we reveal a link between filopodia formation at the cell–matrix interface, in collectively invading cells and 3D tumor spheroids, and the in vitro invasive capacity of the carcinoma. Finally, using intravital microscopy, we observe that tumor spheroids display filopodia in vivo, supporting a potential role for these protrusions during tumorigenesis.

Guillaume Jacquemet , Ilkka Paatero, Alexandre F. Carisey, Artur Padzik, Jordan S. Orange, Hellyeh Hamidi & Johanna Ivaska

Filopodia Quantification Using FiloQuant

Filopodia are fingerlike membrane protrusions that are extended by cells in vitro and in vivo. Due to important roles in sensing the extracellular microenvironment, filopodia and filopodia-like protrusions have been implicated in numerous biological processes including epithelial sheet zippering in development and wound healing and in cancer progression. Recently, there has been an explosion in the number of software available to analyze specific features of cell protrusions with the aim of gaining mechanistic insights into the action of filopodia and filopodia-like structures. In this methods chapter, we highlight an open-access software called FiloQuant that has been developed to specifically quantify the length, density, and dynamics of filopodia and filopodia-like structures from in vitro and in vivo generated samples. We provide step-by-step protocols on (i) how to install FiloQuant in the ImageJ platform (Fiji), (ii) how to quantify filopodia and filopodia-like protrusions from single images using FiloQuant, and (iii) how to track filopodial protrusions from live-cell imaging experiments using FiloQuant and TrackMate.

Guillaume Jacquemet, Hellyeh Hamidi & Johanna Ivaska