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Goldstien L, Lavi Y, Atia L. ConfluentFUCCI for fully-automated analysis of cell-cycle progression in a highly dense collective of migrating cells. PLoS One 2024; 19:e0305491. [PMID: 38924026 PMCID: PMC11207131 DOI: 10.1371/journal.pone.0305491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 05/30/2024] [Indexed: 06/28/2024] Open
Abstract
Understanding mechanisms underlying various physiological and pathological processes often requires accurate and fully automated analysis of dense cell populations that collectively migrate. In such multicellular systems, there is a rising interest in the relations between biophysical and cell cycle progression aspects. A seminal tool that led to a leap in real-time study of cell cycle is the fluorescent ubiquitination-based cell cycle indicator (FUCCI). Here, we introduce ConfluentFUCCI, an open-source graphical user interface-based framework that is designed, unlike previous tools, for fully automated analysis of cell cycle progression, cellular dynamics, and cellular morphology, in highly dense migrating cell collectives. We integrated into ConfluentFUCCI's pipeline state-of-the-art tools such as Cellpose, TrackMate, and Napari, some of which incorporate deep learning, and we wrap the entire tool into an isolated computational environment termed container. This provides an easy installation and workflow that is independent of any specific operation system. ConfluentFUCCI offers accurate nuclear segmentation and tracking using FUCCI tags, enabling comprehensive investigation of cell cycle progression at both the tissue and single-cell levels. We compare ConfluentFUCCI to the most recent relevant tool, showcasing its accuracy and efficiency in handling large datasets. Furthermore, we demonstrate the ability of ConfluentFUCCI to monitor cell cycle transitions, dynamics, and morphology within densely packed epithelial cell populations, enabling insights into mechanotransductive regulation of cell cycle progression. The presented tool provides a robust approach for investigating cell cycle-related phenomena in complex biological systems, offering potential applications in cancer research and other fields.
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Affiliation(s)
- Leo Goldstien
- Department of Mechanical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Yael Lavi
- Department of Mechanical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Lior Atia
- Department of Mechanical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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Toscano E, Cimmino E, Pennacchio FA, Riccio P, Poli A, Liu YJ, Maiuri P, Sepe L, Paolella G. Methods and computational tools to study eukaryotic cell migration in vitro. Front Cell Dev Biol 2024; 12:1385991. [PMID: 38887515 PMCID: PMC11180820 DOI: 10.3389/fcell.2024.1385991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 05/13/2024] [Indexed: 06/20/2024] Open
Abstract
Cellular movement is essential for many vital biological functions where it plays a pivotal role both at the single cell level, such as during division or differentiation, and at the macroscopic level within tissues, where coordinated migration is crucial for proper morphogenesis. It also has an impact on various pathological processes, one for all, cancer spreading. Cell migration is a complex phenomenon and diverse experimental methods have been developed aimed at dissecting and analysing its distinct facets independently. In parallel, corresponding analytical procedures and tools have been devised to gain deep insight and interpret experimental results. Here we review established experimental techniques designed to investigate specific aspects of cell migration and present a broad collection of historical as well as cutting-edge computational tools used in quantitative analysis of cell motion.
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Affiliation(s)
- Elvira Toscano
- Department of Molecular Medicine and Medical Biotechnology, Università Degli Studi di Napoli “Federico II”, Naples, Italy
- CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy
| | - Elena Cimmino
- Department of Molecular Medicine and Medical Biotechnology, Università Degli Studi di Napoli “Federico II”, Naples, Italy
| | - Fabrizio A. Pennacchio
- Laboratory of Applied Mechanobiology, Department of Health Sciences and Technology, Zurich, Switzerland
| | - Patrizia Riccio
- Department of Molecular Medicine and Medical Biotechnology, Università Degli Studi di Napoli “Federico II”, Naples, Italy
| | | | - Yan-Jun Liu
- Institutes of Biomedical Sciences, Fudan University, Shanghai, China
| | - Paolo Maiuri
- Department of Molecular Medicine and Medical Biotechnology, Università Degli Studi di Napoli “Federico II”, Naples, Italy
| | - Leandra Sepe
- Department of Molecular Medicine and Medical Biotechnology, Università Degli Studi di Napoli “Federico II”, Naples, Italy
| | - Giovanni Paolella
- Department of Molecular Medicine and Medical Biotechnology, Università Degli Studi di Napoli “Federico II”, Naples, Italy
- CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy
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Holme B, Bjørnerud B, Pedersen NM, de la Ballina LR, Wesche J, Haugsten EM. Automated tracking of cell migration in phase contrast images with CellTraxx. Sci Rep 2023; 13:22982. [PMID: 38151514 PMCID: PMC10752880 DOI: 10.1038/s41598-023-50227-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 12/17/2023] [Indexed: 12/29/2023] Open
Abstract
The ability of cells to move and migrate is required during development, but also in the adult in processes such as wound healing and immune responses. In addition, cancer cells exploit the cells' ability to migrate and invade to spread into nearby tissue and eventually metastasize. The majority of cancer deaths are caused by metastasis and the process of cell migration is therefore intensively studied. A common way to study cell migration is to observe cells through an optical microscope and record their movements over time. However, segmenting and tracking moving cells in phase contrast time-lapse video sequences is a challenging task. Several tools to track the velocity of migrating cells have been developed. Unfortunately, most of the automated tools are made for fluorescence images even though unlabelled cells are often preferred to avoid phototoxicity. Consequently, researchers are constrained with laborious manual tracking tools using ImageJ or similar software. We have therefore developed a freely available, user-friendly, automated tracking tool called CellTraxx. This software makes it easy to measure the velocity and directness of migrating cells in phase contrast images. Here, we demonstrate that our tool efficiently recognizes and tracks unlabelled cells of different morphologies and sizes (HeLa, RPE1, MDA-MB-231, HT1080, U2OS, PC-3) in several types of cell migration assays (random migration, wound healing and cells embedded in collagen). We also provide a detailed protocol and download instructions for CellTraxx.
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Affiliation(s)
- Børge Holme
- SINTEF Industry, Forskningsveien 1, 0373, Oslo, Norway
| | - Birgitte Bjørnerud
- Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0379, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, 0379, Oslo, Norway
| | - Nina Marie Pedersen
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, 0379, Oslo, Norway
- Department of Molecular Cell Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0379, Oslo, Norway
- Department of Nursing, Health and Laboratory Science, Faculty of Health, Welfare and Organisation, Østfold University College, PB 700, NO-1757, Halden, Norway
| | - Laura Rodriguez de la Ballina
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, 0379, Oslo, Norway
- Department of Molecular Cell Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0379, Oslo, Norway
| | - Jørgen Wesche
- Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0379, Oslo, Norway
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, 0379, Oslo, Norway
- Department of Molecular Medicine, Institute of Basic Medical Sciences, University of Oslo, 0372, Oslo, Norway
| | - Ellen Margrethe Haugsten
- Department of Tumor Biology, Institute for Cancer Research, The Norwegian Radium Hospital, Oslo University Hospital, Montebello, 0379, Oslo, Norway.
- Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Montebello, 0379, Oslo, Norway.
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Taïeb HM, Bertinetti L, Robinson T, Cipitria A. FUCCItrack: An all-in-one software for single cell tracking and cell cycle analysis. PLoS One 2022; 17:e0268297. [PMID: 35793313 PMCID: PMC9258891 DOI: 10.1371/journal.pone.0268297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 04/26/2022] [Indexed: 11/18/2022] Open
Abstract
Beyond the more conventional single-cell segmentation and tracking, single-cell cycle dynamics is gaining a growing interest in the field of cell biology. Thanks to sophisticated systems, such as the fluorescent ubiquitination-based cell cycle indicator (FUCCI), it is now possible to study cell proliferation, migration, changes in nuclear morphology and single cell cycle dynamics, quantitatively and in real time. In this work, we introduce FUCCItrack, an all-in-one, semi-automated software to segment, track and visualize FUCCI modified cell lines. A user-friendly complete graphical user interface is presented to record and quantitatively analyze both collective cell proliferation as well as single cell information, including migration and changes in nuclear or cell morphology as a function of cell cycle. To enable full control over the analysis, FUCCItrack also contains features for identification of errors and manual corrections.
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Affiliation(s)
- Hubert M. Taïeb
- Department of Biomaterials, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
- * E-mail: (AC); (HMT)
| | - Luca Bertinetti
- Department of Biomaterials, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
- B CUBE Center for Molecular Bioengineering, TU Dresden, Dresden, Germany
| | - Tom Robinson
- Department of Theory and Bio-Systems, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
| | - Amaia Cipitria
- Department of Biomaterials, Max Planck Institute of Colloids and Interfaces, Potsdam, Germany
- Biodonostia Health Research Institute, Group of Bioengineering in Regeneration and Cancer, San Sebastian, Spain
- IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
- * E-mail: (AC); (HMT)
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