Ultra-sensitive fluorescence-activated droplet single-cell sorting based on Tetramer-HCR-EvaGreen amplification

The current single-cell analysis technologies such as fluorescence-activated cell sorting (FACS) and fluorescence-activated droplet sorting (FADS) could decipher the cellular heterogeneity but were constrained by low sorting performance and cell viability. Here, an ultra-sensitive single-cell sorting platform has been developed by integrating the FADS technology with Tetramer-HCR-EvaGreen (THE) fluorescence signal amplification. The THE system produced much higher fluorescence signal than that of the single Tetramer or Tetramer-HCR signal amplification. Upon application to target MCF-7 cells, the platform exhibited high efficacy and selectivity while maintaining more than 95% cell viability. The THE-FADS achieved sorting efficiencies of 55.5% and 50.3% with purities of 91% and 85% for MCF-7 cells in PBS solutions and simulated serum samples, respectively. The sorted MCF-7 cells showed similar proliferation together with CK19 and EGFR mRNA expression compared with the control cells. The established THE-FADS showed the promising prospects to cellular heterogeneity understanding and personalized medicine.

Authors

Institutions

Publication Details

Journal
Microsystems & Nanoengineering
Published
2025-01-16
DOI
https://doi.org/10.1038/s41378-024-00861-8
Citations
4
Primary Topic
Innovative Microfluidic and Catalytic Techniques Innovation
Type
article
Field-Weighted Citation Impact
2.70

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ultra-sensitive fluorescence-activated droplet single-cell sorting based on Tetramer-HCR-EvaGreen amplification

Xianqiang Mi, Lele Zhou, Y. Xu, Long Chen et al.
4 citations
Microsystems & Nanoengineering
Innovative Microfluidic and Catalytic Techniques Innovation
2.70
article

Ultra-sensitive fluorescence-activated droplet single-cell sorting based on Tetramer-HCR-EvaGreen amplification

Xianqiang Mi, Lele Zhou, Y. Xu, Long Chen, Yifan Liu, Rong Zhang, Ding Ma
article en
4 citations

Abstract

The current single-cell analysis technologies such as fluorescence-activated cell sorting (FACS) and fluorescence-activated droplet sorting (FADS) could decipher the cellular heterogeneity but were constrained by low sorting performance and cell viability. Here, an ultra-sensitive single-cell sorting platform has been developed by integrating the FADS technology with Tetramer-HCR-EvaGreen (THE) fluorescence signal amplification. The THE system produced much higher fluorescence signal than that of the single Tetramer or Tetramer-HCR signal amplification. Upon application to target MCF-7 cells, the platform exhibited high efficacy and selectivity while maintaining more than 95% cell viability. The THE-FADS achieved sorting efficiencies of 55.5% and 50.3% with purities of 91% and 85% for MCF-7 cells in PBS solutions and simulated serum samples, respectively. The sorted MCF-7 cells showed similar proliferation together with CK19 and EGFR mRNA expression compared with the control cells. The established THE-FADS showed the promising prospects to cellular heterogeneity understanding and personalized medicine.

Microsystems & NanoengineeringVol. 11(1)
Chinese Academy of Sciences (CN), ShanghaiTech University (CN), Shanghai Advanced Research Institute (CN), Shanghai Institute of Microsystem and Information Technology (CN), Shanghai Clinical Research Center (CN), University of Chinese Academy of Sciences (CN)
Science and Technology Commission of Shanghai Municipality, National Science and Technology Development Agency, National Key Research and Development Program of China
Openalex Percentile: Top 12%
Innovative Microfluidic and Catalytic Techniques Innovation
2.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.