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Genetically encoded biosensor for monitoring spatiotemporal dynamics of CCR2 ligands in culture and in vivo

Nature Methods volume 22, pages 1731–1741 (2025)Cite this article

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Abstract

Chemokines regulate immune cell migration in development, homeostasis and inflammation, but the precise spatiotemporal pattern of chemokine release in vivo remains elusive due to the constraints of existing detection methodologies. Here, we report the engineering and characterization of a genetically encoded green fluorescent chemokine sensor, named CRAFi-CCR2, which utilizes the CCR2 receptor as a sensing moiety. In astrocytes, hCRAFi-CCR2, derived from the human CCR2B receptor, exhibited ~300% increase in fluorescence in response to mCCL2, with nanomolar affinity (2.5 nM). Activation of hCRAFi-CCR2 did not affect downstream signaling pathways, such as calcium mobilization and receptor internalization. Using this sensor, we performed 17–20 h of real-time imaging to observe endogenous mCCL2 release under inflammatory conditions, both in cell culture and in mice. In mouse brain, we observed spatial heterogeneity of CCL2 signal response on a scale of about 20–50 µm, highlighting the complexity of the immune system’s spatiotemporal signaling.

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Fig. 1: Development of the CCR2-based chemokine sensors.
Fig. 2: Characterization of hCRAFi-CCR2 in HEK cells.
Fig. 3: Characterization of hCRAFi-CCR2 in primary mouse neuronal and astrocyte cultures.
Fig. 4: Detection of endogenous CCR2 ligand release in cultured astrocytes stimulated with inflammatory stimuli.
Fig. 5: Detection of endogenous CCR2 ligands in the blood of mice stimulated with inflammatory stimuli.
Fig. 6: In vivo spatiotemporal dynamics of mCCL2 during LPS-evoked systemic inflammation and laser-induced ablation injury.

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Data availability

All essential raw datasets, including files for supplementary figures, the mass spectrometry proteomics data including raw datasets, and raw unprocessed images, are available at figshare via https://figshare.com/projects/CRAFi-CCR2/242891 (ref. 63). The rest of the files are available from the corresponding author upon request, as the total size of the files acquired for this study exceeds the 20-GB limit of the figshare repository. All plasmids used in this study are available from WeKwikGene (https://wekwikgene.wllsb.edu.cn/publications/1173; accession number 0001173-0001182) and Addgene. Source data are provided with this paper.

Code availability

Custom MATLAB codes used for data acquisition are available at https://github.com/MingCShare/xyzRegist/.

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Acknowledgements

We thank F. Li, S. Papadaki and Y. Y. Han from the laboratory of K.D.P. for their management support; Y. P. Gao, M. H. Liao, F. Xiao and L. M. Zheng, G.C. Fang from the Imaging Core at Westlake University for their technical support with the Nikon and Zeiss confocal microscopes; S. S. Liu from the Core Facilities at Zhejiang University School of Medicine for assistance with the two-photon microscope; F. Yang at Zhejiang University School of Medicine for support in generating the 3D model of hCRAFi-CCR2 sensor using AlphaFold2; M. Z. Fan and J. Hu from the Mass Spectrometry & Metabolomics Core Facility at Westlake University for assistance and discussion with LC–MS/MS analysis; D. Y. Gu from the Instrumentation and Service Center for Molecular Sciences at Westlake University for assistance with spectra measurement; and the Laboratory Animal Resources Center, Biomedical Research Core Facilities, Flow Cytometry Core, Westlake Center for Micro/Nano Fabrication. This work was supported by start-up funding from the Foundation of Westlake University, Westlake Laboratory of Life Sciences and Biomedicine, National Natural Science Foundation of China grants W2432024 and 32171093; and the ‘Pioneer’ and ‘Leading Goose’ R&D Program of Zhejiang 2024SSYS0031 (to K.D.P.), the Young Scientist Program of National Natural Science Foundation of China (grant 32100897 to X.X.), the National Natural Science Foundation of China (32371150 to M.J.) and STI2030-Major project 2021ZD0202200, Subject 2021ZD0202203 (to M.J.).

Author information

Author notes

  1. These authors contributed equally: Chenyu Wang, Xun Guo.

Authors and Affiliations

  1. School of Life Sciences, Westlake University, Hangzhou, China

    Xian Xiao, Xun Guo, Qiuling Qian, Guoteng Liang, Xiaoting Sun & Kiryl D. Piatkevich

  2. Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China

    Xian Xiao, Xun Guo, Qiuling Qian, Guoteng Liang, Xiaoting Sun & Kiryl D. Piatkevich

  3. Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China

    Xian Xiao, Xun Guo, Qiuling Qian, Guoteng Liang, Xiaoting Sun & Kiryl D. Piatkevich

  4. Basic Medical Sciences, Capital Medical University, Beijing, China

    Chenyu Wang & Fengxue Xi

  5. Beijing Institute for Brain Research, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China

    Chenyu Wang, Fengxue Xi & Miao Jing

  6. Chinese Institute for Brain Research, Beijing, China

    Chenyu Wang, Fengxue Xi & Miao Jing

  7. Lingang Laboratory, Shanghai, China

    Ming Chen

  8. CellSorter KFT, Budapest, Hungary

    Balint Szabo

  9. Eötvös University (ELTE), Department of Biological Physics, Budapest, Hungary

    Balint Szabo

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Contributions

X.X. and K.D.P. initiated the project, made high-level designs and plans, and interpreted the data. X.X. developed the sensors with help from G.L. B.S. and X.X. developed the iDrug system. X.X. performed cell culture characterization. X.X. and Q.Q. performed affinity characterization. F.X. performed fast sensor kinetic measurements; X.G., X.S. and X.X. performed immunohistochemistry analysis. C.W., M.J., M.C. and X.X. performed two-photon in vivo experiments and analysis. X.X. and K.D.P., with help from M.J., wrote the manuscript. K.D.P. oversaw all aspects of the project.

Corresponding author

Correspondence to Kiryl D. Piatkevich.

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Competing interests

B.S. is the founder of CellSorter KFT, which is developing an automated micropipette. X.X. and K.D.P. are inventors on a patent application covering the design and application of the sensors. The other authors declare no competing interests.

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Supplementary Notes 1–5, Supplementary Tables 1–4 and Supplementary Figs. 1–22.

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Supplementary Video 1

Drug-delivery system for PCR mutant library screening. To screen the variants efficiently and economically, we modified the CellSorter from cell picking into a drug-delivery system. During screening, cells were first imaged for 10–20 s to record the baseline fluorescence, and then the manipulator-guided glass pipette was lowered down into the well, 300–400 µm above the cells. Drugs were puffed to the cells through a 70-µm diameter glass capillary connected to the syringe pump, and time-lapse movies were recorded. This video shows how the manipulator-guided glass pipette moves from one well to another well to deliver drugs in an automatic mode.

Supplementary Video 2

Fluorescence response of hCRAFi-CCR2 sensor in HEK cells using the drug-delivery system. Images were acquired at 1 Hz.

Supplementary Video 3

In vivo two-photon imaging of the dynamics of fluorescence intensity for the hCRAFi-CCR2 sensor in mouse visual cortex after LPS challenge. The total time duration is 46 h. Images were acquired at 10-min intervals. Left, raw images showing the hCRAFi-CCR2 fluorescence intensity changes; right, calculated fluorescence response (∆F/F). Lines represent boundaries of the identified signal specific patches.

Supplementary Video 4

In vivo two-photon imaging of the dynamics of fluorescence intensity for hCRAFi-CCR2 sensor or null mutant in mouse visual cortex after laser-induced ablation. Images were acquired at 15-min intervals.

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Xiao, X., Wang, C., Guo, X. et al. Genetically encoded biosensor for monitoring spatiotemporal dynamics of CCR2 ligands in culture and in vivo. Nat Methods 22, 1731–1741 (2025). https://doi.org/10.1038/s41592-025-02742-y

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