神经网络辅助的单分子局部化显微镜,具有弱亲和性蛋白质标签.
Soohyen Jang1,2, Kaarjel K Narayanasamy1,3, Johanna V Rahm1
1Institute of Physical and Theoretical Chemistry, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany.
Biophysical reports
|September 8, 2023
概括
这项研究引入了使用神经网络和新型蛋白质标签的更快单分子局部化显微镜技术. 这种方法克服了活细胞成像中长时间采集和光漂白的局限性.
科学领域:
- 生物物理学的生物物理.
- 细胞生物学 细胞生物学
- 显微镜的使用方法
背景情况:
- 单分子局部化显微镜 (SMLM) 提供高空间分辨率,但由于采集时间长且光漂白而受到影响.
- 这些局限性阻碍了对活细胞中动态细胞过程的研究,原因是吞吐量低和信号降解.
研究的目的:
- 开发一种SMLM方法,大大缩短采集时间,克服光漂白.
- 为了使细胞动态的高时间分辨率活细胞成像.
主要方法:
- 集成DeepSTORM神经网络,从高密度数据中预测超分辨率图像,加速图像采集.
- 使用 HaloTag7 蛋白质标记与可交换配体 (xHTL) 进行连续光信号和光漂白抵抗.
- 将神经网络预测与直接蛋白质标签相结合,用于增强活细胞成像.
主要成果:
- 与传统的SMLM相比,获得时间缩短了约25倍.
- 在活细胞成像中显著提高时间分辨率.
- 在长时间内成功捕获了无信号损失的内质网膜动态.
结论:
- 深风暴和HaloTag7/xHTLs的结合方法有效地解决了SMLM的主要挑战.
- 这种方法显著提高了活细胞超分辨率显微镜的吞吐量和时间分辨率.
- 能够以高准确度对动态细胞事件进行长期观察.
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