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Hyperspectral imaging uses spectral and spatial image information for target detection and classification. In this work hyperspectral autofluorescence imaging was applied to patient olfactory neurosphere-derived cells, a cell model of a human metabolic disease MELAS (mitochondrial myopathy, encephalomyopathy, lactic acidosis, stroke-like syndrome). By using an endogenous source of contrast subtle metabolic variations have been detected between living cells in their full morphological context which made it possible to distinguish healthy from diseased cells before and after therapy. Cellular maps of native fluorophores, flavins, bound and free NADH and retinoids unveiled subtle metabolic signatures and helped uncover significant cell subpopulations, in particular a subpopulation with compromised mitochondrial function. Taken together, our results demonstrate that multispectral spectral imaging provides a new non-invasive method to investigate neurodegenerative and other disease models, and it paves the way for novel cellular characterisation in health, disease and during treatment, with proper account of intrinsic cellular heterogeneity.
|Number of pages||8|
|Journal||Biochimica et Biophysica Acta - Molecular Cell Research|
|Publication status||Published - Jan 2016|
Bibliographical noteCopyright the Author(s) 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
- metabolic imaging
- molecular analysis
- neurodegenerative disorders