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.
Keywords: Hyperspectral; MELAS; Metabolic imaging; Molecular analysis; Neurodegenerative disorders.
Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.