Two-photon-enabled near-infrared proximity labeling maps protein neighborhoods in vivo
4 affiliations
- 1Department of Biomedical Engineering,Guangdong Provincial Key Laboratory of Advanced Biomaterials
- 2Southern University of Science and Technology
- 3Shenzhen Key Laboratory of Gene Regulation and Systems Biology, and Brain Research Center, Department of Neuroscience, School of Life Sciences
- 4Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, The NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences, Guangzhou Medical University
Abstract
Native molecular neighborhoods govern biological processes and disease, yet existing approaches trade off penetration, precision, and native compatibility. Photocatalytic proximity labeling (PL) offers nanoscale, genetics-free precision but is limited by visible-light activation in optically opaque tissue. Here, we report 2PMap, a two-photon near-infrared PL platform driven by a sensitizer with a twophoton absorption cross-section nearly two orders of magnitude above conventional photocatalysts, enabling 850 nm continuous-wave excitation without pulsed lasers. In optically opaque samples, 2PMap achieved higher proteome coverage than conventional visible-light PL. In an early-stage Alzheimer’s disease mouse model, peptide-guided 2PMap produced the first proximity scale map of connective tissue growth factor (CTGF) in living brain tissue, capturing an 80-node network spanning extracellular-matrix, vascular, immune, and neuronal components within a microenvironment inaccessible to existing PL methods. 2PMap thus provides a genetics-free, modular platform for spatial proteomic mapping, extending molecular cartography to previously inaccessible living systems.
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BibTeX
@misc{yang2026twophotonenabled,
title = {{Two-photon-enabled near-infrared proximity labeling maps protein neighborhoods in vivo}},
author = {Jingkai Yang and Ziyu Wang and Tao Deng and Zimo Yao and Ziyi Xu and Zexi Tang and Jiahui Lv and Li Cheng and Yanping Sun and Hongjun Xiao and Jiaxin Li and Guanghui Wang and Mingkun Lv and Tong Li and Hancheng Song and Kun Song and Pan-Lin Shao and Bo Zhang},
howpublished = {ChemRxiv},
year = {2026},
month = oct,
doi = {10.26434/chemrxiv.15010771/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010771/v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Two-photon-enabled near-infrared proximity labeling maps protein neighborhoods in vivo
AU - Jingkai Yang
AU - Ziyu Wang
AU - Tao Deng
AU - Zimo Yao
AU - Ziyi Xu
AU - Zexi Tang
AU - Jiahui Lv
AU - Li Cheng
AU - Yanping Sun
AU - Hongjun Xiao
AU - Jiaxin Li
AU - Guanghui Wang
AU - Mingkun Lv
AU - Tong Li
AU - Hancheng Song
AU - Kun Song
AU - Pan-Lin Shao
AU - Bo Zhang
PY - 2026
DA - 2026/10/21
PB - ChemRxiv
DO - 10.26434/chemrxiv.15010771/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010771/v1
AB - Native molecular neighborhoods govern biological processes and disease, yet existing approaches trade off penetration, precision, and native compatibility. Photocatalytic proximity labeling (PL) offers nanoscale, genetics-free precision but is limited by visible-light activation in optically opaque tissue. Here, we report 2PMap, a two-photon near-infrared PL platform driven by a sensitizer with a twophoton absorption cross-section nearly two orders of magnitude above conventional photocatalysts, enabling 850 nm continuous-wave excitation without pulsed lasers. In optically opaque samples, 2PMap achieved higher proteome coverage than conventional visible-light PL. In an early-stage Alzheimer’s disease mouse model, peptide-guided 2PMap produced the first proximity scale map of connective tissue growth factor (CTGF) in living brain tissue, capturing an 80-node network spanning extracellular-matrix, vascular, immune, and neuronal components within a microenvironment inaccessible to existing PL methods. 2PMap thus provides a genetics-free, modular platform for spatial proteomic mapping, extending molecular cartography to previously inaccessible living systems.
ER -