Coherent anti-Stokes Raman scattering cell ...
Document type :
Article dans une revue scientifique: Article original
Permalink :
Title :
Coherent anti-Stokes Raman scattering cell imaging and segmentation with unsupervised data analysis
Author(s) :
Boildieu, Damien [Auteur]
XLIM [XLIM]
Guerenne-Del Ben, Tiffany [Auteur]
PEIRENE [PEIRENE]
Duponchel, Ludovic [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Sol, Vincent [Auteur]
PEIRENE [PEIRENE]
Petit, Jean-Michel [Auteur]
PEIRENE [PEIRENE]
Champion, Éric [Auteur]
Université de Limoges [UNILIM]
Kano, Hideaki [Auteur]
Kyushu University
Helbert, David [Auteur]
XLIM [XLIM]
Magnaudeix, Amandine [Auteur]
Université de Limoges [UNILIM]
Leproux, Philippe [Auteur]
XLIM [XLIM]
Carré, Philippe [Auteur]
XLIM [XLIM]
XLIM [XLIM]
Guerenne-Del Ben, Tiffany [Auteur]
PEIRENE [PEIRENE]
Duponchel, Ludovic [Auteur]
Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement (LASIRE) - UMR 8516
Sol, Vincent [Auteur]
PEIRENE [PEIRENE]
Petit, Jean-Michel [Auteur]
PEIRENE [PEIRENE]
Champion, Éric [Auteur]
Université de Limoges [UNILIM]
Kano, Hideaki [Auteur]
Kyushu University
Helbert, David [Auteur]
XLIM [XLIM]
Magnaudeix, Amandine [Auteur]
Université de Limoges [UNILIM]
Leproux, Philippe [Auteur]
XLIM [XLIM]
Carré, Philippe [Auteur]
XLIM [XLIM]
Journal title :
Frontiers in Cell and Developmental Biology
Volume number :
10
Publication date :
2022
ISSN :
2296-634X
HAL domain(s) :
Planète et Univers [physics]/Sciences de la Terre
English abstract : [en]
Coherent Raman imaging has been extensively applied to live-cell imaging in the last 2 decades, allowing to probe the intracellular lipid, protein, nucleic acid, and water content with a high-acquisition rate and sensitivity. ...
Show more >Coherent Raman imaging has been extensively applied to live-cell imaging in the last 2 decades, allowing to probe the intracellular lipid, protein, nucleic acid, and water content with a high-acquisition rate and sensitivity. In this context, multiplex coherent anti-Stokes Raman scattering (MCARS) microspectroscopy using sub-nanosecond laser pulses is now recognized as a mature and straightforward technology for label-free bioimaging, offering the high spectral resolution of conventional Raman spectroscopy with reduced acquisition time. Here, we introduce the combination of the MCARS imaging technique with unsupervised data analysis based on multivariate curve resolution (MCR). The MCR process is implemented under the classical signal non-negativity constraint and, even more originally, under a new spatial constraint based on cell segmentation. We thus introduce a new methodology for hyperspectral cell imaging and segmentation, based on a simple, unsupervised workflow without any spectrum-to-spectrum phase retrieval computation. We first assess the robustness of our approach by considering cells of different types, namely, from the human HEK293 and murine C2C12 lines. To evaluate its applicability over a broader range, we then study HEK293 cells in different physiological states and experimental situations. Specifically, we compare an interphasic cell with a mitotic (prophase) one. We also present a comparison between a fixed cell and a living cell, in order to visualize the potential changes induced by the fixation protocol in cellular architecture. Next, with the aim of assessing more precisely the sensitivity of our approach, we study HEK293 living cells overexpressing tropomyosin-related kinase B (TrkB), a cancer-related membrane receptor, depending on the presence of its ligand, brain-derived neurotrophic factor (BDNF). Finally, the segmentation capability of the approach is evaluated in the case of a single cell and also by considering cell clusters of various sizes.Show less >
Show more >Coherent Raman imaging has been extensively applied to live-cell imaging in the last 2 decades, allowing to probe the intracellular lipid, protein, nucleic acid, and water content with a high-acquisition rate and sensitivity. In this context, multiplex coherent anti-Stokes Raman scattering (MCARS) microspectroscopy using sub-nanosecond laser pulses is now recognized as a mature and straightforward technology for label-free bioimaging, offering the high spectral resolution of conventional Raman spectroscopy with reduced acquisition time. Here, we introduce the combination of the MCARS imaging technique with unsupervised data analysis based on multivariate curve resolution (MCR). The MCR process is implemented under the classical signal non-negativity constraint and, even more originally, under a new spatial constraint based on cell segmentation. We thus introduce a new methodology for hyperspectral cell imaging and segmentation, based on a simple, unsupervised workflow without any spectrum-to-spectrum phase retrieval computation. We first assess the robustness of our approach by considering cells of different types, namely, from the human HEK293 and murine C2C12 lines. To evaluate its applicability over a broader range, we then study HEK293 cells in different physiological states and experimental situations. Specifically, we compare an interphasic cell with a mitotic (prophase) one. We also present a comparison between a fixed cell and a living cell, in order to visualize the potential changes induced by the fixation protocol in cellular architecture. Next, with the aim of assessing more precisely the sensitivity of our approach, we study HEK293 living cells overexpressing tropomyosin-related kinase B (TrkB), a cancer-related membrane receptor, depending on the presence of its ligand, brain-derived neurotrophic factor (BDNF). Finally, the segmentation capability of the approach is evaluated in the case of a single cell and also by considering cell clusters of various sizes.Show less >
Audience :
Non spécifiée
Popular science :
Non
Administrative institution(s) :
ENSCL
CNRS
Université de Lille
CNRS
Université de Lille
Collections :
Research team(s) :
Propriétés magnéto structurales des matériaux (PMSM)
Submission date :
2024-02-21T17:11:51Z
2024-02-23T11:59:15Z
2024-02-23T11:59:15Z
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