Schlachter S, Schwedler S, Esposito A, Kaminski Schierle G S, Moggridge G D, Kaminski C F
Department of Chemical Engineering and Biotechnology, University of Cambridge, Pembroke St, Cambridge, CB2 1RA, U.K.
Opt Express. 2009 Dec 7;17(25):22747-60. doi: 10.1364/OE.17.022747.
The ability to quantify the fluorescence signals from multiply labeled biological samples is highly desirable in the life sciences but often difficult, because of spectral overlap between fluorescent species and the presence of autofluorescence. Several so called unmixing algorithms have been developed to address this problem. Here, we present a novel algorithm that combines measurements of lifetime and spectrum to achieve unmixing without a priori information on the spectral properties of the fluorophore labels. The only assumption made is that the lifetimes of the fluorophores differ. Our method combines global analysis for a measurement of lifetime distributions with singular value decomposition to recover individual fluorescence spectra. We demonstrate the technique on simulated datasets and subsequently by an experiment on a biological sample. The method is computationally efficient and straightforward to implement. Applications range from histopathology of complex and multiply labelled samples to functional imaging in live cells.
在生命科学领域，对多重标记生物样品的荧光信号进行定量分析的能力是非常必要的，但由于荧光物质之间的光谱重叠以及自发荧光的存在，往往很难实现。为此人们开发了几种所谓的解混算法来解决这个问题。在此，我们提出一种新算法，该算法结合了寿命和光谱测量，无需事先了解荧光团标记的光谱特性即可实现解混。唯一的假设是荧光团的寿命不同。我们的方法将用于测量寿命分布的全局分析与奇异值分解相结合，以恢复各个荧光光谱。我们在模拟数据集上演示了该技术，随后在生物样品上进行了实验验证。该方法计算效率高且易于实现。其应用范围涵盖复杂多重标记样品的组织病理学研究以及活细胞中的功能成像。
