journal article·2025-04-08

In Situ Monitoring of Membrane Protein Dynamics Using High-Throughput Red-Light-Activated Single-Molecule Tracking

Jinyang Liu, Xuebo Zhang, Bingjie Zhao, Huan Ling, Yanzhong Li, Kuangshi Sun, Song Chen, Yanxin Zhang, Tianli Zhai, Yunxiang Zhang, Fuyou Li, Qian Liu

ACS Nano· Volume 19· Issue 13
Publisher page

Abstract

Single-molecule tracking offers nanometer resolution for studying individual molecule dynamics but is often limited by sparse labeling to avoid signal overlap. We present Red-Light-Activated Single-molecule Tracking (RE-LAST) strategy to address this challenge utilizing a photoactivatable probe, SiR670. SiR670 combines traditional silicon rhodamine with a photocage called SO, quenching fluorescence via photoinduced electron transfer (PET). Red light triggers SiR670 excitation, generating singlet oxygen that oxidizes the SO cage, halting PET and restoring fluorescence. RE-LAST used red light for both activation and imaging, eliminating harmful UV exposure. This method enables high-throughput single-molecule tracking, achieving approximately 9 times more tracks than conventional methods and allowing detailed classification of CD56 membrane protein motion. Furthermore, in situ imaging of single live cells revealed the effects of triplet quencher and oxygen scavenging system (OSS) on membrane protein dynamics. While triplet quenchers like Trolox had minimal impact on protein movement patterns, OSS significantly accelerated protein movement and increased the proportion of mobile proteins. This approach provides a comprehensive method for investigating membrane protein dynamics in living cells, contributing to further developments in cellular and molecular biology.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Fluorescence Microscopy Techniques · Advanced biosensing and bioanalysis techniques · Analytical Chemistry and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemistry and Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials Institution

Fudan University

Institute of Translational Medicine, Institute of Translational Medicine

Shanghai Jiao Tong University

Funding

National Key Research and Development Program of China · National Natural Science Foundation of China

References (91)

Show source-provided references
1. 10.3390/molecules2820717610.3390/molecules28207176 ↗
2. 10.1038/s41580-021-00413-210.1038/s41580-021-00413-2 ↗
3. 10.1038/s41580-022-00524-410.1038/s41580-022-00524-4 ↗
4. 10.1038/s41573-021-00240-210.1038/s41573-021-00240-2 ↗
5. 10.1016/j.sbi.2017.10.01710.1016/j.sbi.2017.10.017 ↗
6. 10.1038/s43586-021-00038-x10.1038/s43586-021-00038-x ↗
7. 10.1146/annurev-anchem-091922-07305710.1146/annurev-anchem-091922-073057 ↗
8. 10.1038/s41467-020-17444-610.1038/s41467-020-17444-6 ↗
9. 10.1109/JSTQE.2016.256816010.1109/JSTQE.2016.2568160 ↗
10. 10.1021/jacs.2c1317210.1021/jacs.2c13172 ↗
11. 10.1038/s41467-020-14731-010.1038/s41467-020-14731-0 ↗
12. 10.1038/s41586-023-06709-x10.1038/s41586-023-06709-x ↗
13. 10.7554/eLife.4639310.7554/eLife.46393 ↗
14. 10.1039/c2an16219a10.1039/c2an16219a ↗
15. 10.1038/nmeth.117610.1038/nmeth.1176 ↗
16. 10.1038/s41596-020-00471-410.1038/s41596-020-00471-4 ↗
17. 10.1073/pnas.121517510910.1073/pnas.1215175109 ↗
18. 10.1002/anie.20170273110.1002/anie.201702731 ↗
19. 10.1038/s41467-019-12480-310.1038/s41467-019-12480-3 ↗
20. 10.1038/nmeth.403410.1038/nmeth.4034 ↗
21. 10.1038/srep1534810.1038/srep15348 ↗
22. 10.1038/s41592-018-0145-510.1038/s41592-018-0145-5 ↗
23. 10.1021/acs.chemrev.0c0066310.1021/acs.chemrev.0c00663 ↗
24. 10.1021/jacs.1c0999910.1021/jacs.1c09999 ↗
25. 10.1021/jacs.9b0623710.1021/jacs.9b06237 ↗
26. 10.1021/jacs.1c0417810.1021/jacs.1c04178 ↗
27. 10.1016/j.cbpa.2014.04.01510.1016/j.cbpa.2014.04.015 ↗
28. 10.1016/j.bpj.2010.06.00510.1016/j.bpj.2010.06.005 ↗
29. 10.1002/anie.20241311710.1002/anie.202413117 ↗
30. 10.1021/jacs.2c1196910.1021/jacs.2c11969 ↗
31. 10.1038/nchembio.155810.1038/nchembio.1558 ↗
32. 10.1038/s41589-018-0032-510.1038/s41589-018-0032-5 ↗
33. 10.1038/s41467-019-10119-x10.1038/s41467-019-10119-x ↗
34. 10.1139/v73-40110.1139/v73-401 ↗
35. 10.1021/jo00271a04310.1021/jo00271a043 ↗
36. 10.1021/jacs.0c0147310.1021/jacs.0c01473 ↗
37. 10.1039/D1CS00239B10.1039/D1CS00239B ↗
38. 10.1002/jcc.2288510.1002/jcc.22885 ↗
39. 10.1016/j.carbon.2020.05.02310.1016/j.carbon.2020.05.023 ↗
40. 10.1002/anie.20221176710.1002/anie.202211767 ↗
41. 10.1021/acsmaterialslett.1c0018310.1021/acsmaterialslett.1c00183 ↗
42. 10.1042/BJ2010159310.1042/BJ20101593 ↗
43. 10.1021/acs.analchem.9b0492610.1021/acs.analchem.9b04926 ↗
44. 10.1021/ja204781t10.1021/ja204781t ↗
45. 10.1038/nchem.154610.1038/nchem.1546 ↗
46. 10.1021/cr200201z10.1021/cr200201z ↗
47. 10.1002/anie.20221732610.1002/anie.202217326 ↗
48. 10.1021/jacs.0c0378610.1021/jacs.0c03786 ↗
49. 10.1039/C6RA28455H10.1039/C6RA28455H ↗
50. 10.1021/jacs.5b0024610.1021/jacs.5b00246 ↗
51. 10.1002/anie.20200959910.1002/anie.202009599 ↗
52. 10.1016/j.neuroscience.2021.02.02710.1016/j.neuroscience.2021.02.027 ↗
53. 10.1016/j.mam.2008.08.00610.1016/j.mam.2008.08.006 ↗
54. 10.1016/j.ccr.2020.21318210.1016/j.ccr.2020.213182 ↗
55. 10.1021/ja509967610.1021/ja5099676 ↗
56. 10.1021/acs.analchem.8b0130610.1021/acs.analchem.8b01306 ↗
57. 10.1021/acs.analchem.9b0486010.1021/acs.analchem.9b04860 ↗
58. 10.1039/b802497a10.1039/b802497a ↗
59. 10.1021/ja00279a00810.1021/ja00279a008 ↗
60. 10.1007/s00214-019-2515-110.1007/s00214-019-2515-1 ↗
61. 10.1002/jcc.2384010.1002/jcc.23840 ↗
62. 10.1007/s10910-014-0437-710.1007/s10910-014-0437-7 ↗
63. 10.1021/acs.joc.5b0174610.1021/acs.joc.5b01746 ↗
64. 10.1021/acsphotonics.2c0060610.1021/acsphotonics.2c00606 ↗
65. 10.1002/eji.20224986810.1002/eji.202249868 ↗
66. 10.7554/eLife.5734610.7554/eLife.57346 ↗
67. 10.1038/s41598-017-06238-410.1038/s41598-017-06238-4 ↗
68. 10.7554/eLife.7628110.7554/eLife.76281 ↗
69. 10.1021/jacs.7b0713910.1021/jacs.7b07139 ↗
70. 10.7554/eLife.0223010.7554/eLife.02230 ↗
71. 10.1038/s41598-021-88802-710.1038/s41598-021-88802-7 ↗
72. 10.1016/S0006-3495(91)82125-710.1016/S0006-3495(91)82125-7 ↗
73. 10.1038/s41467-022-30720-x10.1038/s41467-022-30720-x ↗
74. 10.1016/j.tcb.2012.07.00610.1016/j.tcb.2012.07.006 ↗
75. 10.1016/j.molcel.2020.05.03610.1016/j.molcel.2020.05.036 ↗
76. 10.1021/ja809117z10.1021/ja809117z ↗
77. 10.1021/ja509923e10.1021/ja509923e ↗
78. 10.1529/biophysj.107.11768910.1529/biophysj.107.117689 ↗
79. 10.1016/j.bpj.2014.08.02310.1016/j.bpj.2014.08.023 ↗
80. 10.1038/ncomms1217110.1038/ncomms12171 ↗
81. 10.1126/science.112734410.1126/science.1127344 ↗
82. 10.1529/biophysj.106.09111610.1529/biophysj.106.091116 ↗
83. 10.1038/nmeth.244810.1038/nmeth.2448 ↗
84. 10.1038/nmeth.357910.1038/nmeth.3579 ↗
85. 10.1021/acs.analchem.1c0017510.1021/acs.analchem.1c00175 ↗
86. 10.1371/journal.pbio.300267110.1371/journal.pbio.3002671 ↗
87. 10.1038/cdd.2011.1310.1038/cdd.2011.13 ↗
88. 10.1080/15548627.2019.163494410.1080/15548627.2019.1634944 ↗
89. 10.1016/j.dyepig.2022.11103110.1016/j.dyepig.2022.111031 ↗
90. 10.1016/j.bpj.2018.01.01210.1016/j.bpj.2018.01.012 ↗
91. 10.1093/bioinformatics/btu20210.1093/bioinformatics/btu202 ↗