Localizing single molecules in three dimensions - a brief review.

Localizing single molecules in three dimensions - a brief review.
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在三个维度上定位单个分子 - 简要回顾。

DOI:
10.1109/acssc.2008.5074362
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发表时间:
2008
期刊:
Conference record. Asilomar Conference on Signals, Systems & Computers
影响因子:
--
通讯作者:
Ober,RaimundJ
Ober,RaimundJ
中科院分区:
--
文献类型:
--
作者:
Ram,Sripad;Prabhat,Prashant;Chao,Jerry;Abraham,AnishV;Ward,ESally;Ober,RaimundJ

文献摘要

相似文献

在活细胞环境中进行三维(3D)单分子跟踪有望揭示重要的新生物学见解。然而,传统的基于显微镜的成像技术并不适合于细胞中单个分子的快速3D跟踪。以前,我们开发了一种成像方式多焦平面显微镜(MUM),以三维活细胞中的快速细胞内动力学成像。最近,我们已经报道了一种算法,MUM定位算法(MUMLA),用于使用MUM成像的点源的3D定位。在这里,我们提出了我们的结果MUM和MUMLA的审查。我们已经通过模拟和实验数据验证了MUMLA,并表明量子点(QD)的3D位置可以在很宽的空间范围内以高的空间精度确定。我们已经计算出的Cramer-Rao下限的问题,确定从MUM和传统的显微镜的点源的三维位置。我们的分析表明,MUM克服了传统显微镜的深度分辨能力差,从而为在活细胞环境中高精度跟踪纳米颗粒铺平了道路。我们还表明,MUMLA的性能始终接近Cramer-Rao下界。
Single molecule tracking in three dimensions (3D) in a live cell environment holds the promise of revealing important new biological insights. However, conventional microscopy based imaging techniques are not well suited for fast 3D tracking of single molecules in cells. Previously we developed an imaging modality multifocal plane microscopy (MUM) to image fast intracellular dynamics in 3D in live cells. Recently, we have reported an algorithm, the MUM localization algorithm (MUMLA), for the 3D localization of point sources that are imaged using MUM. Here, we present a review of our results on MUM and MUMLA. We have validated MUMLA through simulated and experimental data and have shown that the 3D-position of quantum dots (QDs) can be determined with high spatial accuracy over a wide spatial range. We have calculated the Cramer-Rao lower bound for the problem of determining the 3D location of point sources from MUM and from conventional microscopes. Our analyses shows that MUM overcomes the poor depth discrimination of the conventional microscope, and thereby paves the way for high accuracy tracking of nanoparticles in a live cell environment. We have also shown that the performance of MUMLA comes consistently close to the Cramer-Rao lower bound.