Evidence map›Paper›PMID 35058199›Full record

ArticleSLAS technology2022

High-throughput sample processing for methylation analysis in an automated, enclosed environment.

Alejandro Stark, Thomas R Pisanic, James G Herman, Tza-Huei Wang

Abstract read
In one paragraph

Article in SLAS technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
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  5. Article
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

4 authors.

Alejandro StarkDepartment of Mechanical Engineering. Johns Hopkins University. Baltimore, MD 21218, , USA.
Thomas R PisanicDepartment of Biomedical Engineering. Johns Hopkins University. Baltimore, MD 21218, USA; Johns Hopkins Institute for NanoBioTechnology. Baltimore, MD 21218, USA.
James G HermanThe UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
Tza-Huei WangDepartment of Mechanical Engineering. Johns Hopkins University. Baltimore, MD 21218, , USA; Department of Biomedical Engineering. Johns Hopkins University. Baltimore, MD 21218, USA; Johns Hopkins Institute for NanoBioTechnology. Baltimore, MD 21218, USA. Electronic address: thwang@jhu.edu.

Funding

Ultrasensitive Detection of Tumor Specific DNA Methylation Changes for the Early Detection of Lung Cancer U01CA214165 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI HERMAN, JAMES G., WANG, TZA-HUEI JEFF · 2016 to 2021
$3.1M
NCI NIH HHS U01 CA214165
6 · The paper itself

Abstract

Variation in methylcytosine is perhaps the most well-studied epigenetic mechanism of gene regulation. Methods that have been developed and implemented for assessing DNA methylation require sample DNA to be extracted, purified and chemically-processed through bisulfite conversion before downstream analysis. While some automated solutions exist for each of these individual process steps, a fully integrated solution for accomplishing the entire process in a high-throughput manner has yet to be demonstrated. Thus, sample processing methods still require numerous manual steps that may reduce sample throughput and precision, while increasing the risk of contamination and human error. In this work, we present an integrated, automated solution for performing the entire sample preparation process, including DNA extraction, purification, bisulfite conversion and PCR plate preparation within in an enclosed environment. The method employs silica-coated magnetic particles that eliminate the need for a centrifuge or vacuum manifold, thereby reducing the complexity and cost of the required automation platform. Toward this end, we also compare commercial DNA extraction and bisulfite conversion kits to identify a protocol suitable for automation to significantly improve genomic and bisulfite-treated DNA yields over manufacturer protocols. Overall, this research demonstrated development of an automated protocol that offers the ability to generate high-quality, bisulfite-treated DNA samples in a high-throughput and clean environment with minimal user intervention and comparable yields to manual processing.

Indexed as

DNADNA MethylationHumansPolymerase Chain ReactionSpecimen HandlingDNACytosine methylationEpigeneticsLab automationLiquid handling platform applicationsMethylation-on-beads

Identifiers

PMID35058199
PMCPMC13403162

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.