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Updated: Jan 20, 2026

Quantification of Efferocytosis by Single-cell Fluorescence Microscopy
Published on: August 18, 2018
Quantification of Low Copy Number Proteins in Single Cells
Meng Shi1,2, Xuhui Geng1, Chengye Wang3
1Department of Instrumentation & Analytical Chemistry, CAS Key Laboratory of Separation Sciences for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , China.
We developed a sensitive method to detect low copy number proteins in single cells using laser-induced fluorescence. This technique quantifies active caspase3 proteins, revealing significant cellular heterogeneity.
Area of Science:
- Biochemistry
- Analytical Chemistry
- Cell Biology
Background:
- Quantifying low copy number intracellular proteins in single cells is challenging.
- Existing methods often lack the sensitivity or selectivity required for such analyses.
Purpose of the Study:
- To develop an ultrasensitive and highly selective method for quantifying low copy number intracellular proteins in single cells.
- To demonstrate the method's capability by measuring active caspase3 protein levels in Jurkat cells.
Main Methods:
- Utilized a low-cost laser-induced fluorescence (LIF) detector and a BV605 fluorescent probe.
- Employed capillary electrophoresis (CE)-LIF analysis with in situ lysis for single-cell protein quantification.
- Separated and distinguished proteins based on retention time differences.
Main Results:
- Achieved detection of approximately seven active caspase3 protein molecules in a 91 pL detection volume.
- Quantified active caspase3 molecules in 98 single Jurkat cells, ranging from 629 to 12171 molecules.
- Demonstrated significant heterogeneity in protein levels among cells from the same batch.
Conclusions:
- The developed CE-LIF method offers high sensitivity and selectivity for single-cell protein quantification.
- The technique can be extended to quantify other low copy number proteins with appropriate antibodies.
- This low-cost system holds promise for early cancer diagnosis, disease pathway research, and high-throughput applications.
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