Dynamic Monitoring of Organelle Interactions in Living Cells via Two-Color Digitally Enhanced Stimulated Emission Depletion Super-resolution Microscopy

扫描电镜 受激发射 超分辨显微术 显微镜 活体细胞成像 荧光显微镜 纳米技术 光学 荧光 化学 激光器 材料科学 物理 细胞 生物化学
作者
Xiaochun Shen,Luwei Wang,Yong Guo,Chenguang Wang,Wei Yan,Junle Qu
出处
期刊:Journal of Physical Chemistry Letters [American Chemical Society]
卷期号:16 (2): 596-603
标识
DOI:10.1021/acs.jpclett.4c03326
摘要

One of the most significant advances in stimulated emission depletion (STED) super-resolution microscopy is its capacity for dynamic super-resolution imaging of living cells, including the long-term tracking of interactions between various cells or organelles. Consequently, the multicolor STED plays a pivotal role in biological research. Despite the emergence of numerous fluorescent probes characterized by low toxicity, high stability, high brightness, and exceptional specificity, enabling dynamic imaging of living cells with multicolor STED, practical implementation of multicolor STED for live-cell imaging is influenced by several factors. These factors include the power and wavelength of the STED beam, the duration of imaging, the size of the imaging area, and the complexity of sample preparation. Presently, a major limitation of multicolor STED is the requirement for high STED power, which hinders the monitoring of interactions between different cells or organelles due to the associated irreversible optical damage. To address this issue, this paper emphasizes research findings based on the digitally enhanced STED (DE-STED) technique. This method overcomes the aforementioned challenge by utilizing low STED laser power to achieve prolonged two-color STED super-resolution imaging of living cells, effectively mitigating phototoxic effects and enhancing the capacity to observe intracellular dynamics. With a depletion laser power of less than 1 mW, we achieved a resolution of about 87 nm, close to that achievable with conventional high-power STED technology.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
kukurai发布了新的文献求助10
1秒前
早睡早起身体棒完成签到,获得积分10
1秒前
1秒前
2秒前
3秒前
HeAuBook举报Lee求助涉嫌违规
3秒前
QAQ发布了新的文献求助20
3秒前
LittleTT发布了新的文献求助10
3秒前
子云完成签到,获得积分10
3秒前
3秒前
4秒前
ss完成签到,获得积分10
5秒前
LEO发布了新的文献求助10
5秒前
5秒前
宝铭YUAN完成签到,获得积分10
5秒前
ssa发布了新的文献求助10
6秒前
无风完成签到 ,获得积分10
6秒前
王知颖发布了新的文献求助10
6秒前
6秒前
7秒前
antarctica完成签到,获得积分10
7秒前
缓慢听筠完成签到,获得积分10
7秒前
CodeCraft应助幸福遥采纳,获得10
7秒前
8秒前
研友_VZG7GZ应助呆萌的裙子采纳,获得10
8秒前
灰色的乌完成签到,获得积分10
8秒前
丰富的水卉完成签到,获得积分10
9秒前
9秒前
调皮皮带完成签到,获得积分10
9秒前
安详秀发发布了新的文献求助10
10秒前
酷波er应助童小肥采纳,获得10
10秒前
个性的红酒完成签到,获得积分20
11秒前
lu发布了新的文献求助10
11秒前
12秒前
12秒前
Akim应助缓慢听筠采纳,获得10
12秒前
李健的小迷弟应助养乐多采纳,获得10
13秒前
萱棚发布了新的文献求助10
14秒前
14秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Moody's Ratings Rising AI spending narrows the gap, but US hyperscalers retain edge over Chinese peers 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7696779
求助须知:如何正确求助?哪些是违规求助? 9256830
关于积分的说明 20005499
捐赠科研通 7271272
什么是DOI,文献DOI怎么找? 3292861
关于科研通互助平台的介绍 2448420
邀请新用户注册赠送积分活动 2298685