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Updated: Aug 1, 2026
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A Label-free Technique for the Spatio-temporal Imaging of Single Cell Secretions
Published on: November 23, 2015
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Deciphering single-cell protein secretion and gene expressions by constructing cell-antibody conjugates
Yachao Li1, Wannan Li1, Jiashang Chen1
1State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China.
Bioorganic Chemistry
|December 1, 2023
Summary
This study introduces Cellab-seq, a novel method to simultaneously analyze secreted proteins and gene activity. This technique enhances understanding of cellular heterogeneity and its role in disease.
Area of Science:
- Immunology
- Molecular Biology
- Genomics
Background:
- Secreted proteins are crucial for immune responses, tumor cell interactions, inflammation, and metabolism.
- Understanding the link between secreted protein diversity and transcriptional states is key to studying cellular heterogeneity.
- Current methods lack the ability to comprehensively analyze both secreted proteins and transcriptome simultaneously.
Purpose of the Study:
- To develop a novel sequencing methodology for joint characterization of secreted proteins and transcriptome.
- To investigate the relationship between gene expression and secreted protein activity in NK cells.
- To provide a tool for deeper insights into cellular dynamics for disease research.
Main Methods:
- Developed Cellab-seq, a cell-antibody conjugate-based sequencing methodology.
- Employed a chemoenzymatic strategy to create cell-antibody conjugates.
- Incorporated barcode detection antibodies for capturing secreted proteins and their signal transduction.
Main Results:
- Successfully applied Cellab-seq to analyze NK cells.
- Demonstrated the capability to jointly characterize secreted proteins and transcriptome.
- Provided insights into how gene expression influences secreted protein activity in NK cells.
Conclusions:
- Cellab-seq offers a powerful strategy for a nuanced understanding of cellular dynamics.
- This methodology can advance research in diverse physiological conditions.
- The findings contribute to the prevention, diagnosis, and treatment of diseases.
