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corrected publication 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Proximity labeling (PL) techniques have advanced neuroscience by revealing the molecular interactions that govern neural circuits. From foundational tools such as BioID and APEX to recent innovations such as TurboID and light-activated systems, PL enables precise mapping of protein–protein interactions within living cells. Recent applications have identified dynamic protein networks in synaptic remodeling, calcium-dependent signaling and disease states, such as neurodegenerative and psychiatric disorders. These studies not only deepen our comprehension of the molecular architecture of the brain but also uncover novel therapeutic targets. By integrating PL with cutting-edge multi-omics strategies and advanced imaging technologies, researchers can decode the intricate interplay between structural and functional neural networks. As PL technologies continue to evolve, they bridge molecular and cellular neuroscience, offering a useful framework for unraveling the complexity of brain networks. Here, in this Review, we underscore the potential of PL in neuroscience, furthering our understanding of the molecular basis of neural connectivity in both health and disease.

Understanding how the brain works is a big challenge in neuroscience. This article discusses how researchers are using new methods to better understand these connections and brain functions. The study focuses on a technique called proximity labeling (PL), which helps to identify proteins that interact closely within cells. PL uses special enzymes to tag nearby proteins, making it easier to study their interactions. This method is important because it can capture interactions that other techniques might miss, especially in complex areas like the brain. Researchers have used PL to study different parts of the brain and how they work together. For example, they have identified proteins involved in synapse formation and proteins altered in neurological disorders such as autism. The findings show that PL is a powerful tool for studying the brain’s molecular landscape.

This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.

Details

Title
Bridging molecular and cellular neuroscience with proximity labeling technologies
Author
Lee, Jun-Gyu 1   VIAFID ORCID Logo  ; Jeong, Inyoung 2   VIAFID ORCID Logo  ; Kim, Kwang-eun 3   VIAFID ORCID Logo 

 Organelle Medicine Research Center, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea (ROR: https://ror.org/01wjejq96) (GRID: grid.15444.30) (ISNI: 0000 0004 0470 5454) 
 Department of Chemistry, Seoul National University, Seoul, Republic of Korea (ROR: https://ror.org/04h9pn542) (GRID: grid.31501.36) (ISNI: 0000 0004 0470 5905); Department of Chemistry, Princeton University, Princeton, NJ, USA (ROR: https://ror.org/00hx57361) (GRID: grid.16750.35) (ISNI: 0000 0001 2097 5006) 
 Organelle Medicine Research Center, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea (ROR: https://ror.org/01wjejq96) (GRID: grid.15444.30) (ISNI: 0000 0004 0470 5454); Department of Chemistry, Seoul National University, Seoul, Republic of Korea (ROR: https://ror.org/04h9pn542) (GRID: grid.31501.36) (ISNI: 0000 0004 0470 5905); Department of Convergence Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea (ROR: https://ror.org/01wjejq96) (GRID: grid.15444.30) (ISNI: 0000 0004 0470 5454); Department of Global Medical Science, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea (ROR: https://ror.org/01wjejq96) (GRID: grid.15444.30) (ISNI: 0000 0004 0470 5454) 
Pages
1492-1505
Section
Review Article
Publication year
2025
Publication date
Jul 2025
Publisher
Springer Nature B.V.
ISSN
12263613
e-ISSN
20926413
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3236301130
Copyright
corrected publication 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.