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

Cell2Read is a novel automated method for complete integration of cell lysis and sample preparation for next-generation sequencing (NGS). It optimizes diffusion kinetics and complex thermal geometries to allow for effective use down to low inputs of cells. This allows for DNA analysis from a low cellular input, whether this be for in vitro analysis or diagnostic applications from dissociated tumor biopsies. We demonstrate that the system can process input cell suspensions as low as 1500 cells without compromising sequencing integrity. We also demonstrate the breadth of the protocol in its ability to repeatably process many cell types, including HepG2, Caov3, HEY A8, OVCAR 8, MDA-MB-231, and Human Primary Ovarian Epithelial Cells. The workflow integrates and fully automates cell lysis, DNA extraction, and library preparation into a single automated platform, offering high sensitivity and reproducibility. Our results show that the system yields consistent DNA quantities (≥10 ng) with high sequencing quality, even at low cell inputs, with alignment rates exceeding 95% for inputs of 3125 cells or greater. The automated method's sequencing performance was comparable to manual protocols, with no significant differences in quality scores or GC bias across processing methods. We also demonstrated effective, non-biased sequencing of heterogeneous cell suspensions, through comprehensive testing of spiked concentrations of cancerous cells with non-cancerous ovarian cells. Sequencing output showed proportional DNA representation of cancer markers to the concentration of cancer cells inputted. The Cell2Read workflow offers a technically validated, scalable solution that expands accessibility to genomic analysis and supports reproducible, high-quality sequencing from low-input human samples. This robustness across a range of cell types, makes Cell2Read an ideal solution for sequencing applications, including oncology research and clinical diagnostics.

Authors

Institutions

Publication Details

Journal
Biology Methods and Protocols
Published
2025-01-01
DOI
https://doi.org/10.1093/biomethods/bpaf091
Citations
1
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.94

Funders

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

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

Julia Xia, Soeun Park, Shreyas Shah, Anubhav Tripathi et al.
1 citations
Biology Methods and Protocols
Cancer Genomics and Diagnostics
0.94
article

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

Julia Xia, Soeun Park, Shreyas Shah, Anubhav Tripathi, Lloyd Bwanali, Kathryn Whitehead, Tom Williams, Sarah Planchak, Alejandra Hernandez Moyers
article en
1 citations

Abstract

Cell2Read is a novel automated method for complete integration of cell lysis and sample preparation for next-generation sequencing (NGS). It optimizes diffusion kinetics and complex thermal geometries to allow for effective use down to low inputs of cells. This allows for DNA analysis from a low cellular input, whether this be for in vitro analysis or diagnostic applications from dissociated tumor biopsies. We demonstrate that the system can process input cell suspensions as low as 1500 cells without compromising sequencing integrity. We also demonstrate the breadth of the protocol in its ability to repeatably process many cell types, including HepG2, Caov3, HEY A8, OVCAR 8, MDA-MB-231, and Human Primary Ovarian Epithelial Cells. The workflow integrates and fully automates cell lysis, DNA extraction, and library preparation into a single automated platform, offering high sensitivity and reproducibility. Our results show that the system yields consistent DNA quantities (≥10 ng) with high sequencing quality, even at low cell inputs, with alignment rates exceeding 95% for inputs of 3125 cells or greater. The automated method's sequencing performance was comparable to manual protocols, with no significant differences in quality scores or GC bias across processing methods. We also demonstrated effective, non-biased sequencing of heterogeneous cell suspensions, through comprehensive testing of spiked concentrations of cancerous cells with non-cancerous ovarian cells. Sequencing output showed proportional DNA representation of cancer markers to the concentration of cancer cells inputted. The Cell2Read workflow offers a technically validated, scalable solution that expands accessibility to genomic analysis and supports reproducible, high-quality sequencing from low-input human samples. This robustness across a range of cell types, makes Cell2Read an ideal solution for sequencing applications, including oncology research and clinical diagnostics.

Biology Methods and ProtocolsVol. 10(1)
Brown University (US), ID Genomics (United States) (US), Zero to Three (US)
Brown University
Openalex Percentile: Top 18%
Cancer Genomics and Diagnostics
0.94
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.