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Article Dans Une Revue Frontiers in Cell and Developmental Biology Année : 2022

Coherent anti-Stokes Raman scattering cell imaging and segmentation with unsupervised data analysis

Tiffany Guerenne-del Ben
  • Fonction : Auteur
Vincent Sol
Jean-Michel Petit
  • Fonction : Auteur
Hideaki Kano
Philippe Leproux

Résumé

Coherent Raman imaging has been extensively applied to live-cell imaging in the last two decades, allowing to probe the intracellular lipid, protein, nucleic acid and water content with 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 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, as well, by considering cell clusters of various sizes.
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Dates et versions

hal-03726275 , version 1 (16-03-2023)

Identifiants

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Damien Boildieu, Tiffany Guerenne-del Ben, Ludovic Duponchel, Vincent Sol, Jean-Michel Petit, et al.. Coherent anti-Stokes Raman scattering cell imaging and segmentation with unsupervised data analysis. Frontiers in Cell and Developmental Biology, 2022, 10, pp.933897. ⟨10.3389/fcell.2022.933897⟩. ⟨hal-03726275⟩
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