journal article·2023-10Open access

A High‐Density Raman Photometry for Tracking and Quantifying of AchE Activity in The Brain of Freely Moving Animals with Network

Zhonghui Zhang, Zhichao Liu, Peicong Wu, Xinhua Guo, Xiao Luo, Youjun Yang, Jinquan Chen, Yang Tian

Advanced Science· Volume 10· Issue 29

Abstract

Abstract A high‐density Raman photometry based on a dual‐recognition strategy is created for accurately quantifying acetylcholinesterase (AchE) activity in 24 brain regions of free‐moving animals with network. A series of 5‐ethynyl‐1,2,3,3‐tetramethyl‐based molecules with different conjugated structures and substitute groups are designed and synthesized for specific recognition of AchE by Raman spectroscopy. After systematically evaluating the recognition ability toward AchE, 2‐(4‐((4‐(dimethylamino)benzoyl)oxy)styryl)‐5‐ethynyl‐1,3,3‐trimethyl‐3H‐indol‐1‐ium (ET‐5) is finally optimized for AchE determination, which shows the highest selectivity, the greatest sensitivity, and the fastest response time among the investigated seven molecules. More interestingly, using the developed probe for AchE with high accuracy and sensitivity, the optimized AchE regulated by nitric oxide (NO) is discovered for promoting the neurogenesis of neural stem cells (NSCs). Benefiting from the high‐density photometry, it is found that the activity and distribution of AchE varied in 24 brain regions, and the levels of AchE activity in 24 brain regions of Alzheimer's mice (AD) are lower than those of normal mice. It is the first time that a functional network of AchE in 24 brain regions is established. It is also found that the loss of AchE functional network in AD mice is restored and reconstructed by the controlled release of AchE regulated by NO.
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Research context

OpenAlex topics: Cholinesterase and Neurodegenerative Diseases · Photoreceptor and optogenetics research · Computational Drug Discovery Methods

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

Affiliations

Shanghai Key Laboratory of Green Chemistry and Chemical Processes School of Chemistry and Molecular Engineering East China Normal University Dongchuan Road 500 Shanghai 200241 P.R. China

State Key Laboratory of Precision Spectroscopy East China Normal University Dongchuan Road 500 Shanghai 200241 P.R. China

State Key Laboratory of Supramolecular Structure and Materials College of Chemistry and Key Laboratory for Molecular Enzymology and Engineering of the Ministry of Education College of Life Science Jilin University Qianjin Road 2699 Changchun 130012 P.R. China

State Key Laboratory of Bioreactor Engineering Shanghai Key Laboratory of Chemical Biology School of Pharmacy East China University of Science and Technology Meilong Road 130 Shanghai 200237 P.R. China

Funding

National Natural Science Foundation of China

References (44)

Show source-provided references
1. 10.1038/3506758910.1038/35067589 ↗
2. 10.1038/2101003a010.1038/2101003a0 ↗
3. 10.1038/461895a10.1038/461895a ↗
4. 10.1038/nchembio0807-43510.1038/nchembio0807-435 ↗
5. 10.1038/nn78810.1038/nn788 ↗
6. 10.1002/advs.20200294410.1002/advs.202002944 ↗
7. 10.1073/pnas.95.23.1393510.1073/pnas.95.23.13935 ↗
8. 10.1111/j.1742-4658.2007.06237.x10.1111/j.1742-4658.2007.06237.x ↗
9. 10.1097/WAD.000000000000029110.1097/WAD.0000000000000291 ↗
10. 10.1177/07067437140590120210.1177/070674371405901202 ↗
11. 10.1002/anie.20070172410.1002/anie.200701724 ↗
12. 10.1021/jacs.8b1141410.1021/jacs.8b11414 ↗
13. 10.1021/acs.analchem.0c0277010.1021/acs.analchem.0c02770 ↗
14. 10.1021/acs.chemrev.6b0059610.1021/acs.chemrev.6b00596 ↗
15. 10.1002/anie.20201601410.1002/anie.202016014 ↗
16. 10.1002/anie.20201043110.1002/anie.202010431 ↗
17. 10.1038/ncomms131010.1038/ncomms1310 ↗
18. 10.1002/anie.20210619310.1002/anie.202106193 ↗
19. 10.1002/anie.20181428610.1002/anie.201814286 ↗
20. 10.1002/anie.20211163010.1002/anie.202111630 ↗
21. 10.1016/S0968-0896(99)00315-610.1016/S0968-0896(99)00315-6 ↗
22. 10.1002/advs.20210389610.1002/advs.202103896 ↗
23. 10.1016/S0022-2860(03)00318-110.1016/S0022-2860(03)00318-1 ↗
24. 10.1002/advs.20210165210.1002/advs.202101652 ↗
25. 10.1107/S010827019600802510.1107/S0108270196008025 ↗
26. 10.1021/jacs.5b0451110.1021/jacs.5b04511 ↗
27. 10.1016/j.nbd.2009.07.03010.1016/j.nbd.2009.07.030 ↗
28. 10.1002/adma.20180486110.1002/adma.201804861 ↗
29. 10.1038/s41467-021-22758-010.1038/s41467-021-22758-0 ↗
30. 10.1002/advs.20190182210.1002/advs.201901822 ↗
31. 10.1038/nn.459110.1038/nn.4591 ↗
32. 10.3389/fnins.2019.0008210.3389/fnins.2019.00082 ↗
33. 10.1002/advs.20220337110.1002/advs.202203371 ↗
34. 10.1038/s41592-019-0400-410.1038/s41592-019-0400-4 ↗
35. 10.1038/nmeth.377010.1038/nmeth.3770 ↗
36. 10.1126/science.abe193110.1126/science.abe1931 ↗
37. 10.1016/j.bbr.2006.09.00210.1016/j.bbr.2006.09.002 ↗
38. 10.1111/ejn.1202910.1111/ejn.12029 ↗
39. 10.1002/stem.44410.1002/stem.444 ↗
40. 10.1021/jacs.2c0185710.1021/jacs.2c01857 ↗
41. 10.1021/acs.bioconjchem.7b0082110.1021/acs.bioconjchem.7b00821 ↗
42. 10.1126/sciadv.aau349410.1126/sciadv.aau3494 ↗
43. 10.1038/nmeth.377010.1038/nmeth.3770 ↗
44. 10.1016/j.neuroscience.2013.09.05910.1016/j.neuroscience.2013.09.059 ↗