Cell2Read: an automated workflow to generate sequencing-ready DNA libraries from human cell suspensions

Area of Science:

• Genomics
• Molecular Biology
• Biotechnology

Background:

• Next-generation sequencing (NGS) requires efficient sample preparation, especially from limited cell inputs.
• Current methods can be labor-intensive and may struggle with low cell numbers or diverse sample types.
• Automated solutions are needed to improve reproducibility and accessibility in genomic analysis.

Purpose of the Study:

• To introduce and validate Cell2Read, a novel automated workflow for integrated cell lysis and sample preparation for NGS.
• To assess the performance of Cell2Read with low cell inputs and various cell types.
• To evaluate the method's suitability for analyzing heterogeneous cell populations, including those relevant to oncology.

Main Methods:

• Development of an automated platform integrating cell lysis, DNA extraction, and library preparation.
• Optimization of diffusion kinetics and thermal geometries for low-input cell processing.
• Testing across multiple human cell lines (HepG2, Caov3, HEY A8, OVCAR 8, MDA-MB-231) and primary cells.
• Evaluation of sequencing integrity, DNA yield, quality scores, GC bias, and alignment rates.
• Assessment of performance with heterogeneous cell suspensions, including spiked cancer cells.

Main Results:

• Cell2Read successfully processed cell suspensions as low as 1500 cells without compromising sequencing integrity.
• Consistent DNA yield (≥10 ng) and high sequencing quality (alignment rates >95% for ≥3125 cells) were achieved.
• The method demonstrated reproducibility across diverse cell types and comparable performance to manual protocols.
• Non-biased sequencing of heterogeneous cell suspensions was achieved, with DNA representation proportional to cancer cell concentration.
• The system yielded high-quality genomic data from low-input samples, suitable for clinical diagnostics and research.

Conclusions:

• Cell2Read provides a technically validated, scalable, and automated solution for NGS sample preparation.
• The workflow significantly expands accessibility to genomic analysis from low-input human samples.
• Its robustness and reproducibility make it ideal for oncology research and clinical diagnostics.
• Cell2Read ensures high-quality, unbiased sequencing data, supporting accurate genomic profiling.