小柯机器人

光激活定位显微镜中多次闪烁伪影的校正
2022-05-15 14:15

英国伯明翰大学Dylan M. Owen、英国布里斯托大学Patrick Rubin-Delanchy和丹麦奥胡斯大学Louis G. Jensen研究组合作开发出光激活定位显微镜中多次闪烁伪影的校正方法。相关论文于2022年5月11日发表在《自然—方法学》杂志上。

他们提出了一个“基于模型的校正”(MBC) 工作流程,使用对闪烁动力学的无校准估计和基于模型的聚类来生成一组校正的定位坐标,这些坐标代表具有增强的定位精度的真实底层荧光团位置,优于art状态。校正后的数据可以可靠地测试空间随机性或通过其他聚类方法进行分析,并且每个簇的荧光团绝对数量等描述符现在可以量化,他们使用模拟数据和具有已知基本事实的实验数据进行验证。使用 MBC,他们确认接头蛋白,即 T 细胞激活的接头,聚集在 T 细胞免疫突触处。

据了解,光激活定位显微镜 (PALM) 通过光激活荧光蛋白产生一系列定位坐标。然而,观察结果会受到荧光团多次闪烁的影响,并且由于定位错误,每个蛋白质在不同位置被包含在数据集中的次数未知。这会导致在数据中观察到人工聚类。

附:英文原文

Title: Correction of multiple-blinking artifacts in photoactivated localization microscopy

Author: Jensen, Louis G., Hoh, Tjun Yee, Williamson, David J., Griffi, Juliette, Sage, Daniel, Rubin-Delanchy, Patrick, Owen, Dylan M.

Issue&Volume: 2022-05-11

Abstract: Photoactivated localization microscopy (PALM) produces an array of localization coordinates by means of photoactivatable fluorescent proteins. However, observations are subject to fluorophore multiple blinking and each protein is included in the dataset an unknown number of times at different positions, due to localization error. This causes artificial clustering to be observed in the data. We present a ‘model-based correction’ (MBC) workflow using calibration-free estimation of blinking dynamics and model-based clustering to produce a corrected set of localization coordinates representing the true underlying fluorophore locations with enhanced localization precision, outperforming the state of the art. The corrected data can be reliably tested for spatial randomness or analyzed by other clustering approaches, and descriptors such as the absolute number of fluorophores per cluster are now quantifiable, which we validate with simulated data and experimental data with known ground truth. Using MBC, we confirm that the adapter protein, the linker for activation of T cells, is clustered at the T cell immunological synapse.

DOI: 10.1038/s41592-022-01463-w

Source: https://www.nature.com/articles/s41592-022-01463-w

Nature Methods:《自然—方法学》,创刊于2004年。隶属于施普林格·自然出版集团,最新IF:47.99
官方网址:https://www.nature.com/nmeth/
投稿链接:https://mts-nmeth.nature.com/cgi-bin/main.plex


本期文章:《自然—方法学》:Online/在线发表

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