【Sensor. Actuat. B-chem.】山东大学于晓强|基于荧光寿命成像的线粒体-溶酶体双靶向探针：实现纳秒级（约1 ns）寿命区分与细胞损伤及自噬过程可视化
【Sensor. Actuat. B-chem.】山东大学于晓强|基于荧光寿命成像的线粒体-溶酶体双靶向探针：实现纳秒级（约1 ns）寿命区分与细胞损伤及自噬过程可视化
文章标题：A dual-targeted probe of mitochondria and lysosomes based on fluorescence lifetime imaging for visualizing cellular damage and autophagy processes
文章作者：Haiyang Yu, Mingyue Cao, Jie Huang, Xiaoyan Gao, Zhiqiang Liu, Peng Gao, Xiaoqiang Yu
第一部分：研究动因
在细胞生物学与生物医学领域，利用小分子荧光探针实时监测线粒体和溶酶体等细胞器的动态相互作用是当前的主流研究方向。传统的双细胞器显影多依赖双探针共染色法或双发射通道的单探针策略。然而，这些现有方法存在明显的关键短板：不仅面临光谱串扰、累积细胞毒性高的难题，且由于不同探针在细胞内的摄取速率与分布不均，难以实现两类细胞器的同步精确动态监控；此外，现有的单分子探针多依赖极性或粘度响应，极易受到复杂微环境信号干扰，缺乏连续定量评估能力。为此，本文旨在开发一种基于荧光寿命成像（FLIM）的单分子双靶向探针，利用线粒体基质与溶酶体腔微环境的pH差异引发纳秒级荧光寿命转变，消除光谱串扰与摄取偏差，实现对线粒体与溶酶体的高分辨率区分及线粒体自噬与细胞损伤过程的实时定量追踪，为细胞自噬机制研究与相关疾病诊断提供高时空精度的分子工具。
Scheme 1. The design of probe QNN.
第二部分：研究实施方案与关键实验结果
整体技术路线基于D-π-A推拉电子构型与微环境pH敏感响应机制，设计并合成了单分子双靶向荧光探针QNN及对照分子QNL与QNB。探针以二甲基氨基-萘基为电子供体，N-烷基吡啶阳离子为电子受体并兼作线粒体靶向基团，同时创新性地引入末端季铵盐/胺基（-）作为溶酶体靶向与pH敏感响应单元。QNN与已有方法的本质区别在于利用弱碱性线粒体基质（pH 7.7–7.9）与强酸性溶酶体腔（pH 4.5–5.5）的酸碱度差异，诱导探针产生显著的荧光寿命转变，突破了传统依赖极性/粘度或双色双通道的靶向局限，首次在单一分子内实现了基于pH控制的线粒体与溶酶体荧光寿命精准分离。
Scheme 2. Synthetic routes of QNL, QNB, QNN.
实验对HeLa、COS-7和L929细胞进行了多维度验证。MTT细胞毒性实验显示，2 μM染色浓度下的QNN毒性极低，细胞存活率显著优于QNL和QNB（约87%）；光稳定性测试表明，QNN在连续100次扫描后仍保留约80% 的初始荧光强度，优于商业探针MTG和LTG。共定位实验证实QNN具备优异的双靶向性，与线粒体探针MTG及溶酶体探针LTG的皮尔逊相关系数（PCC）分别达0.91和0.89（对比分子QNL与QNB仅能单靶向线粒体，PCC分别为0.98和0.95）。在FLIM成像中，线粒体区域（弱碱性）荧光寿命为800–1800 ps（平均约1377 ps），溶酶体区域（强酸性）荧光寿命为1500–2100 ps（平均约2078 ps），两者形成了约1 ns的清晰寿命窗口差异。
Fig.1 (a) Fluorescence absorption and emission spectra of probe QNL, QNB and QNN in 1,4-dioxane; (b) Fluorescence lifetime change curves at a function of the 1,4-dioxane/water mixture composition of probe QNN, with the water increase from 20 to 100%; (c) Fluorescence lifetime change curves at a function of the 1,4-dioxane/PEG mixture composition of probe QNN, with the PEG increase from 20% to 100%; (d) Fluorescence lifetime change curves of probe QNN in different organic acid-base conditions. Concentration: 10 μM. λex = 488 nm.
Fig.2 Confocal imaging of 1 μM QNL/QNB and 2 μM QNN of HeLa cells (d,e,f), the former stained for 15 minutes; the latter stained for 20 minutes; brightfield (a,b,c) and overlay (g,h,i) images. Scale bar = 10 μm. λex = 488 nm, λem = 550-650 nm.
Fig.3 Co-localization research results of different fluorescent markers with QNL/QNB/QNN. (a) The co-localization analysis of MTG and QNL. From left to right, bright field, green channel for MTG, the red channel for QNL, the merged of green and red channel, and the enlarged image (enlarged). Pearson correlation coefficient (PCC): 0.98; (b) The co-localization analysis of MTG and QNB. From left to right, bright field, green channel for MTG, the red channel for QNB, the merged of green and red channel, and the enlarged image (enlarged). Pearson correlation coefficient (PCC): 0.95; (c) The co-localization analysis of MTG and QNN. From left to right, bright field, green channel for MTG, the red channel for QNN, the merged of green and red channel, and the enlarged image (enlarged). Pearson correlation coefficient (PCC): 0.91; (d) The co-localization analysis of LTG and QNN. From left to right, bright field, green channel for LTG, the red channel for QNN, the merged of green and red channel, and the enlarged image (enlarged). Pearson correlation coefficient (PCC): 0.89. The normalized colocalization fluorescence intensity distributions are placed on the right side of the figure. Scale bar: 10 μm. MTG: 200 nM, λex = 488 nm, λem = 500-570 nm. LTG: 200 nM, λex = 488 nm, λem = 500-570 nm. QNL: 1 μM, λex = 488 nm, λem = 550-650 nm. QNB: 1 μM, λex = 488 nm, λem = 550-650 nm. QNN: 2 μM, λex = 488 nm, λem = 550-650 nm
在动态追踪与功能验证流程中，研究人员采用CCCP（10–20 μM）诱导线粒体损伤与自噬，并结合氯喹升高溶酶体pH进行反向干预。结果成功解析了自噬不同阶段的荧光寿命特征：未参与自噬的线粒体寿命约为1550 ps，部分包裹线粒体的自噬溶酶体寿命约为1800 ps，准备接触线粒体的溶酶体寿命达2400 ps，而完全参与自噬的溶酶体平均寿命稳定在1900 ps。该方案实现了“探针合成→光物理表征→共定位与毒性评估→FLIM动态定量成像”的完整闭环，证实其能无标记、无串扰地定量区分健康与损伤细胞群，精准捕获细胞自噬全过程。
Fig.4 (a) The CLSM imaging, Intensity imaging, and FLIM imaging of QNN, where white arrows indicate regions #1 and #2 with different fluorescence lifetime ranges, respectively; (b) the fluorescence lifetime distribution corresponding to figure a; (c) the fluorescence lifetime decay curves of regions #1 and #2, along with their corresponding lifetime times τ and χ2 values; (d) fluorescence lifetime and corresponding photon counts for different cellular regions; (e) imaging results of Part1 and Part 2; (f) the normalized fluorescence lifetime distribution curves of the two parts. Scale bar: 5 μm. QNN: 2 μM, λex = 488 nm, λem = 550-650 nm.
Fig.5 (a) Long-term tracking of mitochondrial and lysosomal fluorescence lifetime imaging using the QNN probe; (b) fluorescence lifetime images at different damage levels; (c) Normalized fluorescence lifetime distribution curves for different damaged regions (#1, #2, #3). Scale bar: 5 μm. QNN: 2 μM, λex = 488 nm, λem = 550-650 nm.
Fig.6 (a) FLIM image acquired immediately after 1-hour exposure to 20 μM CCCP; (b) Magnified views of ROI 1 and ROI 2, along with the corresponding fluorescence lifetime decay curves from regions #1, #2, and #3; (c) Magnified fluorescence lifetime images of different parts, along with bar graphs of their corresponding average lifetimes. Scale bar: 5 μm. QNN: 2 μM, λex = 488 nm, λem = 550-650 nm.
第三部分：创新与提升
本文的核心创新在于开发了首个基于pH响应与荧光寿命成像（FLIM）的单分子双靶向探针QNN，开创性地解决了线粒体与溶酶体同步成像中的光谱串扰与摄取不均问题。相比传统双探针共染色及双通道发射策略，QNN在单一分子内实现了线粒体与溶酶体间约1 ns（1377 ps对比2078 ps）的超高分辨率寿命分离，将连续100次扫描后的抗光漂白稳定性提升至80%，并大幅降低了多探针累积细胞毒性。这些量化提升全面回应了第一部分提出的传统染色毒性大、光谱干扰强及定量能力不足等痛点。尽管作者明确指出该技术受限于FLIM系统固有的采集速度较慢等瓶颈，但其在生物微环境高精度无损定量追踪领域的突破，仍为细胞损伤机制研究与自噬诊断提供了极具前景的全新工具。
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