Evaluation of normalization strategies for qPCR quantitation of intracellular viral DNA: The example of Vaccinia virus

Genomic Core Facility, IRBA La Tronche, BP87, 38702 La Tronche, France.
Journal of virological methods (Impact Factor: 1.78). 09/2012; 186(1-2):176-183. DOI: 10.1016/j.jviromet.2012.08.022
Source: PubMed

ABSTRACT Quantitation of intracellular viral genomes is critical in both clinical and fundamental virology. Quantitative real time PCR (qPCR) is currently the gold standard to detect and monitor virus infections, due to its high sensitivity and reproducibility. The reliability of qPCR data depends primarily on the technical process. Normalization, which corrects inter-sample variations related to both pre-analytical and qPCR steps, is a key point of an accurate quantitation. Total DNA input and qPCR-measured standards were evaluated to normalize intracellular Vaccinia virus (VACV) genomes. Three qPCR assays targeting either a single-copy chromosomic gene, a repeated chromosomic DNA sequence, or a mitochondrial DNA sequence were compared. qPCR-measured standards, unlike total DNA input, allowed for accurate normalization of VACV genome, regardless of the cell number. Among PCR-measured standards, chromosomic DNA and mitochondrial DNA were equivalent to normalize VACV DNA and multi-copy standards displayed lower limits of quantitation than single-copy standards. The combination of two qPCR-measured standards slightly improved the reliability of the normalization. Using one or two multi-copy standards must be favored for relative quantitation of intracellular VACV DNA. This concept could be applied to other DNA viruses.

Download full-text


Available from: Thomas Poyot, Jul 07, 2015
1 Follower
31 Reads
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Real-time PCR is becoming the method of choice for precise quantification of minute amounts of nucleic acids. For proper comparison of samples, almost all quantification methods assume similar PCR efficiencies in the exponential phase of the reaction. However, inhibition of PCR is common when working with biological samples and may invalidate the assumed similarity of PCR efficiencies. Here we present a statistical method, Kinetic Outlier Detection (KOD), to detect samples with dissimilar efficiencies. KOD is based on a comparison of PCR efficiency, estimated from the amplification curve of a test sample, with the mean PCR efficiency of samples in a training set. KOD is demonstrated and validated on samples with the same initial number of template molecules, where PCR is inhibited to various degrees by elevated concentrations of dNTP; and in detection of cDNA samples with an aberrant ratio of two genes. Translating the dissimilarity in efficiency to quantity, KOD identifies outliers that differ by 1.3-1.9-fold in their quantity from normal samples with a P-value of 0.05. This precision is higher than the minimal 2-fold difference in number of DNA molecules that real-time PCR usually aims to detect. Thus, KOD may be a useful tool for outlier detection in real-time PCR.
    Nucleic Acids Research 10/2003; 31(17):e105. · 9.11 Impact Factor
  • The Lancet 05/1986; 1(8486):908-9. DOI:10.1016/S0140-6736(86)91008-1 · 45.22 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: A new biochemical method for estimating the virtual number of mitochondria (mt) per cell was developed and used together with a plasmid probe to measure mt DNA/mitochondrion and mt DNA/cell. These methods were used in five cell types from four mammalian species. Mt DNA/mitochondrion was essentially constant in all cell types (mean 2.6 +/- 0.30 SE mitochondrial DNA molecules/mt). Mt DNA molecules/cell encompassed an eight-fold range between various cell types (low 220 +/- 6.2; high 1,720 +/- 162 mt DNA molecules/cell). Virtual mt number/cell ranged from 83 +/- 17 to 677 +/- 80 (SE) mt/cell in various cell types. All five mammalian virtual mitochondria contained the same genomic mass. The number of virtual mitochondria per cell and amount of mt DNA per cell appear to be closely regulated within a given cell type but differ widely from cell type to cell type.
    Journal of Cellular Physiology 09/1988; 136(3):507-13. DOI:10.1002/jcp.1041360316 · 3.84 Impact Factor
Show more