Dataset Information

Cancer Site-Specific Multiple microRNA Quantification by Droplet Digital PCR.

ABSTRACT: Archival formalin-fixed paraffin-embedded (FFPE) tissues represent an extraordinary source of smallRNAs, including microRNAs (miRNAs). Contrary to other RNA molecules, miRNAs are stable, nuclease-resistant and quantifiable even in low quality samples. The accurate assessment of miRNA levels in archival samples is of great interest for many pathological conditions, including cancer. In human tumors, microRNA expression is type-specific and can be used as diagnostic, prognostic or response-to-treatment biomarker. In this study, we provide a method for multiple miRNA quantification in 96-well plates, using EvaGreen-based droplet digital PCR technology and miRCURY LNA miRNA assays. This approach allows the absolute quantification of a customizable panel of miRNAs at the same time and under identical experimental conditions, to be used for diagnostic or prognostic applications.

SUBMITTER: Laprovitera N

PROVIDER: S-EPMC6196277 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

Cancer Site-Specific Multiple microRNA Quantification by Droplet Digital PCR.

Laprovitera Noemi N Grzes Maria M Porcellini Elisa E Ferracin Manuela M

Frontiers in oncology 20181015

Archival formalin-fixed paraffin-embedded (FFPE) tissues represent an extraordinary source of smallRNAs, including microRNAs (miRNAs). Contrary to other RNA molecules, miRNAs are stable, nuclease-resistant and quantifiable even in low quality samples. The accurate assessment of miRNA levels in archival samples is of great interest for many pathological conditions, including cancer. In human tumors, microRNA expression is type-specific and can be used as diagnostic, prognostic or response-to-trea ...[more]

PMID: 30374423

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Project description:Bacteria can be considered as biological nanofactories that manufacture a cornucopia of bioproducts most notably recombinant proteins. As such, they must perfectly match with appropriate plasmid vectors to ensure successful overexpression of target genes. Among many parameters that correlate positively with protein productivity plasmid copy number plays pivotal role. Therefore, development of new and more accurate methods to assess this critical parameter will result in optimization of expression of plasmid-encoded genes. In this study, we present a simple and highly accurate method for quantifying plasmid copy number utilizing an EvaGreen single colour, droplet digital PCR. We demonstrate the effectiveness of this method by examining the copy number of the pBR322 vector within Escherichia coli DH5? cells. The obtained results were successfully validated by real-time PCR. However, we observed a strong dependency of the plasmid copy number on the method chosen for isolation of the total DNA. We found that application of silica-membrane-based columns for DNA purification or DNA isolation with use of bead-beating, a mechanical cell disruption lead to determination of an average of 20.5 or 7.3 plasmid copies per chromosome, respectively. We found that recovery of the chromosomal DNA from purification columns was less efficient than plasmid DNA (46.5 ± 1.9% and 87.4 ± 5.5%, respectively) which may lead to observed differences in plasmid copy number. Besides, the plasmid copy number variations dependent on DNA template isolation method, we found that droplet digital PCR is a very convenient method for measuring bacterial plasmid content. Careful determination of plasmid copy number is essential for better understanding and optimization of recombinant proteins production process. Droplet digital PCR is a very precise method that allows performing thousands of individual PCR reactions in a single tube. The ddPCR does not depend on running standard curves and is a straightforward and reliable method to quantify the plasmid copy number. Therefore we believe that the ddPCR designed in this study will be widely used for any plasmid copy number calculation in the future.

Dataset Information

Cancer Site-Specific Multiple microRNA Quantification by Droplet Digital PCR.

Publications

Cancer Site-Specific Multiple microRNA Quantification by Droplet Digital PCR.

Similar Datasets

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