使用具有计算特异性的相位成像对未标记的神经突动力学进行多尺度测定,ACS Sensors

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使用具有计算特异性的相位成像对未标记的神经突动力学进行多尺度测定
ACS Sensors ( IF 8.2 ) Pub Date : 2021-04-21 , DOI: 10.1021/acssensors.1c00100
Mikhail E Kandel _{1,

2} , Eunjae Kim _{1,

2} , Young Jae Lee _{1,

3} , Gregory Tracy ₄ , Hee Jung Chung _{3,

4} , Gabriel Popescu _{1,

2,

5}

Affiliation

原代神经元培养已广泛用于研究神经元形态、神经生理学、神经退行性过程以及学习和记忆的突触可塑性的分子机制。然而，神经元独特的行为特性使得它们的研究具有挑战性，表型差异表现为神经元树枝化的微妙变化，而不是细胞计数等易于测定的特征。分析形态、生长和细胞内运输的需求推动了日益复杂的显微镜和图像分析技术的发展。由于其高对比度、高特异性输出，许多测定依赖于共焦荧光显微镜、遗传方法或抗体染色技术。这些方法通常限制了定量测量动态活动（例如细胞内运输和生长）的能力。在这项工作中，我们描述了一种具有抗体染色特异性的无标记活细胞成像方法，通过定量相位成像和深度卷积神经网络估计相关荧光信号。然后，使用计算推断的荧光图像生成语义分割图，注释活体未标记神经培养物的亚细胞区室。这些合成荧光图被进一步应用于研究海马神经元的延时发育，突出了细胞干物质生产与细胞核和神经突内动态运输活动之间的关系。我们的实施提供了一种高通量策略来动态分析神经网络树枝化，具有高特异性，并且没有与荧光标记相关的典型光毒性和光漂白限制。

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Multiscale Assay of Unlabeled Neurite Dynamics Using Phase Imaging with Computational Specificity

Primary neuronal cultures have been widely used to study neuronal morphology, neurophysiology, neurodegenerative processes, and molecular mechanism of synaptic plasticity underlying learning and memory. However, the unique behavioral properties of neurons make them challenging to study, with phenotypic differences expressed as subtle changes in neuronal arborization rather than easy-to-assay features such as cell count. The need to analyze morphology, growth, and intracellular transport has motivated the development of increasingly sophisticated microscopes and image analysis techniques. Due to its high-contrast, high-specificity output, many assays rely on confocal fluorescence microscopy, genetic methods, or antibody staining techniques. These approaches often limit the ability to measure quantitatively dynamic activity such as intracellular transport and growth. In this work, we describe a method for label-free live-cell cell imaging with antibody staining specificity by estimating the associated fluorescence signals via quantitative phase imaging and deep convolutional neural networks. This computationally inferred fluorescence image is then used to generate a semantic segmentation map, annotating subcellular compartments of live unlabeled neural cultures. These synthetic fluorescence maps were further applied to study the time-lapse development of hippocampal neurons, highlighting the relationships between the cellular dry mass production and the dynamic transport activity within the nucleus and neurites. Our implementation provides a high-throughput strategy to analyze neural network arborization dynamically, with high specificity and without the typical phototoxicity and photobleaching limitations associated with fluorescent markers.

更新日期：2021-05-28

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