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Tissue Homogenization and Cell Lysis01:32

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Innovative Method for Fully Automated, Enzyme-Free Tissue Dissociation and Preparation for Single-Cell Analysis.

Sarah Planchak1, E Celeste Welch1,2, Benjamin Phelps1

  • 1Center for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912 USA.

Cellular and Molecular Bioengineering
|September 18, 2025
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Summary
This summary is machine-generated.

This study introduces an automated, enzyme-free electrical tissue dissociation method for single-cell analysis. It significantly improves cell yield and preserves cellular integrity compared to traditional methods.

Keywords:
AutomationCell spheroidElectric fieldsRNA sequencingSingle-cell analysisTissue dissociation

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Area of Science:

  • Biotechnology
  • Single-cell analysis
  • Cellular biology

Background:

  • Tissue dissociation is crucial for single-cell analysis but conventional methods cause variability and cell damage.
  • Enzymatic and mechanical dissociation alter transcriptomic profiles, impacting downstream applications.
  • Existing electrical dissociation methods require further characterization and optimization.

Purpose of the Study:

  • To develop and validate a fully automated, enzyme-free electrical tissue dissociation method.
  • To provide a standardized and scalable alternative to conventional dissociation techniques.
  • To assess the impact of electrical dissociation on cell viability, transcriptomic profiles, and immune cell populations.

Main Methods:

  • An automated system integrating electric field-based dissociation, purification, and centrifugation was developed.
  • A square wave oscillating electric field (100 V/cm) was applied for rapid tissue dissociation (≤5 minutes).
  • Methods included bulk RNA sequencing, flow cytometry, and dissociation of glioblastoma spheroids and mouse spleen tissue.

Main Results:

  • The electrical dissociation method achieved a 10x increase in live cell yield compared to automated enzymatic/mechanical methods.
  • A high single-cell recovery rate (96±2%) was observed in glioblastoma spheroids.
  • Transcriptomic analysis showed minimal gene expression changes (R²=0.997), and flow cytometry confirmed preservation of immune cell populations.

Conclusions:

  • The automated electrical dissociation method offers a standardized, scalable, and gentle approach for single-cell analysis.
  • This technology reduces operator variability and maintains cellular integrity, crucial for high-throughput applications.
  • It presents a robust solution for advancing diagnostics, drug discovery, and precision medicine.