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Killer-cell Immunoglobulin-like Receptor gene linkage and copy number variation analysis by droplet digital PCR.

ABSTRACT: The Killer-cell Immunoglobulin-like Receptor (KIR) gene complex has considerable biomedical importance. Patterns of polymorphism in the KIR region include variability in the gene content of haplotypes and diverse structural arrangements. Droplet digital PCR (ddPCR) was used to identify different haplotype motifs and to enumerate KIR copy number variants (CNVs). ddPCR detected a variety of KIR haplotype configurations in DNA from well-characterized cell lines. Mendelian segregation of ddPCR-estimated KIR2DL5 CNVs was observed in Gambian families and CNV typing of other KIRs was shown to be accurate when compared to an established quantitative PCR method.

SUBMITTER: Roberts CH

PROVIDER: S-EPMC4062048 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Killer-cell Immunoglobulin-like Receptor gene linkage and copy number variation analysis by droplet digital PCR.

Roberts Chrissy H CH Jiang Wei W Jayaraman Jyothi J Trowsdale John J Holland Martin J MJ Traherne James A JA

Genome medicine 20140305 3

The Killer-cell Immunoglobulin-like Receptor (KIR) gene complex has considerable biomedical importance. Patterns of polymorphism in the KIR region include variability in the gene content of haplotypes and diverse structural arrangements. Droplet digital PCR (ddPCR) was used to identify different haplotype motifs and to enumerate KIR copy number variants (CNVs). ddPCR detected a variety of KIR haplotype configurations in DNA from well-characterized cell lines. Mendelian segregation of ddPCR-estim ...[more]

PMID: 24597950

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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.

Project description:BackgroundPlasmids are widely used for molecular cloning or production of proteins in laboratory and industrial settings. Constant modification has brought forth countless plasmid vectors whose characteristics in terms of average plasmid copy number (PCN) and stability are rarely known. The crucial factor determining the PCN is the replication system; most replication systems in use today belong to a small number of different classes and are available through repositories like the Standard European Vector Architecture (SEVA).ResultsIn this study, the PCN was determined in a set of seven SEVA-based expression plasmids only differing in the replication system. The average PCN for all constructs was determined by Droplet Digital PCR and ranged between 2 and 40 per chromosome in the host organism Escherichia coli. Furthermore, a plasmid-encoded EGFP reporter protein served as a means to assess variability in reporter gene expression on the single cell level. Only cells with one type of plasmid (RSF1010 replication system) showed a high degree of heterogeneity with a clear bimodal distribution of EGFP intensity while the others showed a normal distribution. The heterogeneous RSF1010-carrying cell population and one normally distributed population (ColE1 replication system) were further analyzed by sorting cells of sub-populations selected according to EGFP intensity. For both plasmids, low and highly fluorescent sub-populations showed a remarkable difference in PCN, ranging from 9.2 to 123.4 for ColE1 and from 0.5 to 11.8 for RSF1010, respectively.ConclusionsThe average PCN determined here for a set of standardized plasmids was generally at the lower end of previously reported ranges and not related to the degree of heterogeneity. Further characterization of a heterogeneous and a homogeneous population demonstrated considerable differences in the PCN of sub-populations. We therefore present direct molecular evidence that the average PCN does not represent the true number of plasmid molecules in individual cells.

Dataset Information

Killer-cell Immunoglobulin-like Receptor gene linkage and copy number variation analysis by droplet digital PCR.

Publications

Killer-cell Immunoglobulin-like Receptor gene linkage and copy number variation analysis by droplet digital PCR.

Similar Datasets

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