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Functional hyperspectral imaging captures subtle details of cell metabolism in olfactory neurosphere cells, disease-specific models of neurodegenerative disorders

机译：功能性高光谱成像捕获嗅觉神经球细胞中细胞代谢的细微细节，这是神经退行性疾病的疾病特异性模型

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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.
机译：高光谱成像使用光谱和空间图像信息进行目标检测和分类。在这项工作中，高光谱自发荧光成像被应用于患者嗅觉神经球来源的细胞，一种人类代谢疾病MELAS（线粒体肌病，脑病，乳酸性酸中毒，中风样综合征）的细胞模型。通过使用内源性对比剂，已经在活细胞的完整形态背景下检测到细微的代谢变化，这使得有可能在治疗前后将健康细胞与患病细胞区分开。天然荧光团，黄素，结合和游离的NADH和类维生素A的细胞图揭示了微妙的代谢特征，并有助于发现重要的细胞亚群，尤其是线粒体功能受损的亚群。综上所述，我们的结果表明，多光谱光谱成像提供了一种新的非侵入性方法来研究神经退行性疾病和其他疾病模型，并且为健康，疾病和治疗期间的新型细胞表征铺平了道路，并适当考虑了固有的细胞异质性。

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