SMALL-LABS: Measuring Single-Molecule Intensity and Position in Obscuring Backgrounds
SMALL-LABS: Measuring Single-Molecule Intensity and Position in Obscuring Backgrounds
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DOI：
10.1016/j.bpj.2019.02.006
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发表时间：
2019-03-19
影响因子：
3.4
通讯作者：
Biteen, Julie S.
中科院分区：
文献类型：
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作者：
Isaacoff, Benjamin P.;Li, Yilai;Biteen, Julie S.
单分子和超分辨率成像依赖于对荧光分子发射的成功、灵敏和准确的检测。然而，尽管超分辨率显微镜被广泛采用，但单分子数据处理算法无法在存在随时间和空间显著波动的背景下提供对分子亮度和位置的准确测量。因此，包括模糊背景的样本或实验可能会严重甚至完全阻碍这一过程。到目前为止，还没有针对这个问题引入能够消除各种实验模式的模糊背景的通用数据分析方法。为了解决这一需求，我们提出了局部背景减去单分子精确定位(Small-Labs)算法，该算法可以整合到现有的单分子和超分辨率分析包中，无论背景的形状或亮度如何，都可以精确定位和测量单分子的强度。通过基于前景和背景的时间变化的差异(即，荧光团闪烁、漂白或移动)将前景与背景分开，能够实现准确的背景减去。我们详细介绍了小实验室的功能，并在模拟数据和活细胞单分子成像的真实数据上验证了小实验室算法的有效性。
Single-molecule and super-resolution imaging relies on successful, sensitive, and accurate detection of the emission from fluorescent molecules. Yet, despite the widespread adoption of super-resolution microscopies, single-molecule data processing algorithms can fail to provide accurate measurements of the brightness and position of molecules in the presence of backgrounds that fluctuate significantly over time and space. Thus, samples or experiments that include obscuring backgrounds can severely, or even completely, hinder this process. To date, no general data analysis approach to this problem has been introduced that is capable of removing obscuring backgrounds for a wide variety of experimental modalities. To address this need, we present the Single-Molecule Accurate LocaLization by LocAl Background Subtraction (SMALL-LABS) algorithm, which can be incorporated into existing single-molecule and super-resolution analysis packages to accurately locate and measure the intensity of single molecules, regardless of the shape or brightness of the background. Accurate background subtraction is enabled by separating the foreground from the background based on differences in the temporal variations of the foreground and the background (i.e., fluorophore blinking, bleaching, or moving). We detail the function of SMALL-LABS here, and we validate the SMALL-LABS algorithm on simulated data as well as real data from single-molecule imaging in living cells.