SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging
Abstract Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imagi...
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| Format: | Article |
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Nature Portfolio
2024-03-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-024-46989-z |
| _version_ | 1827301054961680384 |
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| author | Rui Chen Jiasu Xu Boqian Wang Yi Ding Aynur Abdulla Yiyang Li Lai Jiang Xianting Ding |
| author_facet | Rui Chen Jiasu Xu Boqian Wang Yi Ding Aynur Abdulla Yiyang Li Lai Jiang Xianting Ding |
| author_sort | Rui Chen |
| collection | DOAJ |
| description | Abstract Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imaging noise and resolution. Here, we propose SpiDe-Sr, a super-resolution network embedded with a denoising module for IMC spatial resolution enhancement. SpiDe-Sr effectively resists noise and improves resolution by 4 times. We demonstrate SpiDe-Sr respectively with cells, mouse and human tissues, resulting 18.95%/27.27%/21.16% increase in peak signal-to-noise ratio and 15.95%/31.63%/15.52% increase in cell extraction accuracy. We further apply SpiDe-Sr to study the tumor microenvironment of a 20-patient clinical breast cancer cohort with 269,556 single cells, and discover the invasion of Gram-negative bacteria is positively correlated with carcinogenesis markers and negatively correlated with immunological markers. Additionally, SpiDe-Sr is also compatible with fluorescence microscopy imaging, suggesting SpiDe-Sr an alternative tool for microscopy image super-resolution. |
| first_indexed | 2024-04-24T16:16:33Z |
| format | Article |
| id | doaj.art-7136ac4011884686a4468ef3583bd5e5 |
| institution | Directory Open Access Journal |
| issn | 2041-1723 |
| language | English |
| last_indexed | 2024-04-24T16:16:33Z |
| publishDate | 2024-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj.art-7136ac4011884686a4468ef3583bd5e52024-03-31T11:24:59ZengNature PortfolioNature Communications2041-17232024-03-0115111610.1038/s41467-024-46989-zSpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imagingRui Chen0Jiasu Xu1Boqian Wang2Yi Ding3Aynur Abdulla4Yiyang Li5Lai Jiang6Xianting Ding7Department of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityDepartment of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityDepartment of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityDepartment of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityDepartment of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityState Key Laboratory of Systems Medicine for Cancer, Institute for Personalized Medicine, Shanghai Jiao Tong UniversityDepartment of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityDepartment of Anesthesiology and Surgical Intensive Care Unit, Xinhua Hospital, School of Medicine and School of Biomedical Engineering, Shanghai Jiao Tong UniversityAbstract Spatial proteomics elucidates cellular biochemical changes with unprecedented topological level. Imaging mass cytometry (IMC) is a high-dimensional single-cell resolution platform for targeted spatial proteomics. However, the precision of subsequent clinical analysis is constrained by imaging noise and resolution. Here, we propose SpiDe-Sr, a super-resolution network embedded with a denoising module for IMC spatial resolution enhancement. SpiDe-Sr effectively resists noise and improves resolution by 4 times. We demonstrate SpiDe-Sr respectively with cells, mouse and human tissues, resulting 18.95%/27.27%/21.16% increase in peak signal-to-noise ratio and 15.95%/31.63%/15.52% increase in cell extraction accuracy. We further apply SpiDe-Sr to study the tumor microenvironment of a 20-patient clinical breast cancer cohort with 269,556 single cells, and discover the invasion of Gram-negative bacteria is positively correlated with carcinogenesis markers and negatively correlated with immunological markers. Additionally, SpiDe-Sr is also compatible with fluorescence microscopy imaging, suggesting SpiDe-Sr an alternative tool for microscopy image super-resolution.https://doi.org/10.1038/s41467-024-46989-z |
| spellingShingle | Rui Chen Jiasu Xu Boqian Wang Yi Ding Aynur Abdulla Yiyang Li Lai Jiang Xianting Ding SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging Nature Communications |
| title | SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging |
| title_full | SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging |
| title_fullStr | SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging |
| title_full_unstemmed | SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging |
| title_short | SpiDe-Sr: blind super-resolution network for precise cell segmentation and clustering in spatial proteomics imaging |
| title_sort | spide sr blind super resolution network for precise cell segmentation and clustering in spatial proteomics imaging |
| url | https://doi.org/10.1038/s41467-024-46989-z |
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