Evidence map›Paper›PMID 41467035›Full record

ArticleBiology methods & protocols2025

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

Kathryn Whitehead, Sarah Planchak, Trinity Williams, Julia Xia, Soeun Park, Alejandra Hernandez Moyers, Shreyas Shah, Lloyd Bwanali, Anubhav Tripathi

Abstract read
In one paragraph

Article in Biology methods & protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kathryn WhiteheadCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.ORCID https://orcid.org/0009-0001-1635-946X
Sarah PlanchakCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.ORCID https://orcid.org/0009-0005-0135-4542
Trinity WilliamsCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.
Julia XiaCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.
Soeun ParkCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.
Alejandra Hernandez MoyersCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.
Shreyas ShahApplied Genomics, Revvity, Hopkinton, MA 01748, United States.
Lloyd BwanaliApplied Genomics, Revvity, Hopkinton, MA 01748, United States.
Anubhav TripathiCenter for Biomedical Engineering, School of Engineering, Brown University, Providence, RI 02912, United States.ORCID https://orcid.org/0000-0002-8915-2320

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

automated DNA library preparationcancer cell detectioncell lysisDNA extraction automationhigh-throughput genomicslow-input sequencingoncology diagnostics

Identifiers

PMID41467035
PMCPMC12744386

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.