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

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

SLAS Technol

Department 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:

Published: June 2022

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.

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Source
http://dx.doi.org/10.1016/j.slast.2021.12.002DOI Listing

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