Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features.
Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features.
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DOI：
10.1038/srep23453
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发表时间：
2016-03-31
影响因子：
4.6
通讯作者：
Goldys EM
中科院分区：
文献类型：
--
作者：
Gosnell ME;Anwer AG;Mahbub SB;Menon Perinchery S;Inglis DW;Adhikary PP;Jazayeri JA;Cahill MA;Saad S;Pollock CA;Sutton-McDowall ML;Thompson JG;Goldys EM
能够处理复杂生物异质性的自动化和公正的非侵入性细胞监测方法对于生物学和医学来说至关重要。无标记细胞成像提供有关细胞内内源性自发荧光代谢物、酶和辅助因子的信息。然而，从自发荧光成像中提取高含量信息迄今为止是不可能的。在这里，我们通过使用新颖的图像处理和宽视野荧光显微镜的简单多光谱升级来定量表征不同组织类型（活的或固定的）中的细胞群。我们的最佳区分方法可以实现统计假设检验和直观可视化，使以前无法检测到的差异变得清晰可见。通过分析分类决定因子 (CD) 抗原表达来验证无标记分类。我们方法的多功能性通过检测癌症中的基因突变、非侵入性监测 CD90 表达、无标记跟踪干细胞分化、识别具有不同功能特征的干细胞亚群、糖尿病组织诊断以及评估植入前胚胎的状况来说明。
Automated and unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biology and medicine. Label-free cell imaging provides information about endogenous autofluorescent metabolites, enzymes and cofactors in cells. However extracting high content information from autofluorescence imaging has been hitherto impossible. Here, we quantitatively characterise cell populations in different tissue types, live or fixed, by using novel image processing and a simple multispectral upgrade of a wide-field fluorescence microscope. Our optimal discrimination approach enables statistical hypothesis testing and intuitive visualisations where previously undetectable differences become clearly apparent. Label-free classifications are validated by the analysis of Classification Determinant (CD) antigen expression. The versatility of our method is illustrated by detecting genetic mutations in cancer, non-invasive monitoring of CD90 expression, label-free tracking of stem cell differentiation, identifying stem cell subpopulations with varying functional characteristics, tissue diagnostics in diabetes, and assessing the condition of preimplantation embryos.