Empirical Bayes method using surrounding pixel information for number and brightness analysis
Empirical Bayes method using surrounding pixel information for number and brightness analysis
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DOI：
10.1016/j.bpj.2021.03.033
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发表时间：
2021-06-01
影响因子：
3.4
通讯作者：
Kinjo, Masataka
中科院分区：
文献类型：
--
作者：
Fukushima, Ryosuke;Yamamoto, Johtaro;Kinjo, Masataka
数目和亮度（N&B）分析可用于监测细胞中荧光标记蛋白质的浓度和寡聚状态的空间分布。N&B分析基于使用矩量法（MoM）对荧光图像的统计分析。此外，N&B分析可以确定颗粒数和颗粒亮度，其分别指示浓度和低聚状态。然而，在荧光蛋白的实际实验中，由于低激发和有限数量的图像，统计准确度和精度是有限的。在这项研究中，我们采用最大似然（ML）估计和最大后验（MAP）估计加上经验贝叶斯（EB）方法（简称EB-MAP）。在EB-MAP中，我们为像素构造了一个简单的先验分布，以利用周围像素的信息。为了评估我们的方法的准确性和精度，我们进行了模拟和实验，并比较MoM，ML和EB-MAP的结果。结果表明，矩量法估计的颗粒数有许多离群值。异常值妨碍了空间分布和细胞结构的可见性。相比之下，EB-MAP抑制了异常值的数量，并显着提高了可见性。EB-MAP的精度是更好的一个数量级的颗粒数量和1.5倍更好的颗粒亮度相比，矩量法。所提出的方法（EB-MAP-N&B）适用于荧光成像的研究，并将有助于准确地识别细胞中的浓度和寡聚状态的变化。我们的研究结果具有重要意义，因为定量的浓度和寡聚状态将有助于了解细胞中分子机制的动态过程。
Number and brightness (N&B) analysis is useful for monitoring the spatial distribution of the concentration and oligomeric state of fluorescently labeled proteins in cells. N&B analysis is based on the statistical analysis of fluorescence images by using the method of moments (MoM). Furthermore, N&B analysis can determine the particle number and particle brightness, which indicate the concentration and oligomeric state, respectively. However, the statistical accuracy and precision are limited in actual experiments with fluorescent proteins, owing to low excitation and the limited number of images. In this study, we applied maximum likelihood (ML) estimation and maximum a posteriori (MAP) estimation coupled with the empirical Bayes (EB) method (referred to as EB-MAP). In EB-MAP, we constructed a simple prior distribution for a pixel to utilize the information of the surrounding pixels. To evaluate the accuracy and precision of our method, we conducted simulations and experiments and compared the results of MoM, ML, and EB-MAP. The results showed that MoM estimated the particle number with many outliers. The outliers hampered the visibility of the spatial distribution and cellular structure. In contrast, EB-MAP suppressed the number of outliers and improved the visibility notably. The precision of EB-MAP was better by an order of magnitude in terms of particle number and 1.5 times better in terms of particle brightness compared with those of MoM. The proposed method (EB-MAP-N&B) is applicable to studies on fluorescence imaging and would aid in accurately recognizing changes in the concentration and oligomeric state in cells. Our results hold significant importance because quantifying the concentration and oligomeric state would contribute to the understanding of dynamic processes in molecular mechanism in cells.