Dataset Information

A real-time PCR array for hierarchical identification of Francisella isolates.

ABSTRACT: A robust, rapid and flexible real-time PCR assay for hierarchical genetic typing of clinical and environmental isolates of Francisella is presented. Typing markers were found by multiple genome and gene comparisons, from which 23 canonical single nucleotide polymorphisms (canSNPs) and 11 canonical insertion-deletion mutations (canINDELs) were selected to provide phylogenetic guidelines for classification from genus to isolate level. The specificity of the developed assay, which uses 68 wells of a 96-well real-time PCR format with a detection limit of 100 pg DNA, was assessed using 62 Francisella isolates of diverse genetic and geographical origins. It was then successfully used for typing 14 F. tularensis subsp. holarctica isolates obtained from tularemia patients in Sweden in 2008 and five more genetically diverse Francisella isolates of global origins. When applied to human ulcer specimens for direct pathogen detection the results were incomplete due to scarcity of DNA, but sufficient markers were identified to detect fine-resolution differences among F. tularensis subsp. holarctica isolates causing infection in the patients. In contrast to other real-time PCR assays for Francisella, which are typically designed for specific detection of a species, subspecies, or strain, this type of assay can be easily tailored to provide appropriate phylogenetic and/or geographical resolution to meet the objectives of the analysis.

SUBMITTER: Svensson K

PROVIDER: S-EPMC2793073 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature

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A real-time PCR array for hierarchical identification of Francisella isolates.

Svensson Kerstin K Granberg Malin M Karlsson Linda L Neubauerova Vera V Forsman Mats M Johansson Anders A

PloS one 20091221 12

A robust, rapid and flexible real-time PCR assay for hierarchical genetic typing of clinical and environmental isolates of Francisella is presented. Typing markers were found by multiple genome and gene comparisons, from which 23 canonical single nucleotide polymorphisms (canSNPs) and 11 canonical insertion-deletion mutations (canINDELs) were selected to provide phylogenetic guidelines for classification from genus to isolate level. The specificity of the developed assay, which uses 68 wells of ...[more]

PMID: 20027310

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Project description:BackgroundThere are currently many different methods for processing and summarizing probe-level data from Affymetrix oligonucleotide arrays. It is of great interest to validate these methods and identify those that are most effective. There is no single best way to do this validation, and a variety of approaches is needed. Moreover, gene expression data are collected to answer a variety of scientific questions, and the same method may not be best for all questions. Only a handful of validation studies have been done so far, most of which rely on spike-in datasets and focus on the question of detecting differential expression. Here we seek methods that excel at estimating relative expression. We evaluate methods by identifying those that give the strongest linear association between expression measurements by array and the "gold-standard" assay. Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is generally considered the "gold-standard" assay for measuring gene expression by biologists and is often used to confirm findings from microarray data. Here we use qRT-PCR measurements to validate methods for the components of processing oligo array data: background adjustment, normalization, mismatch adjustment, and probeset summary. An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question.ResultsWe initially identify three of six popular methods that consistently produced the best agreement between oligo array and RT-PCR data for medium- and high-intensity genes. The three methods are generally known as MAS5, gcRMA, and the dChip mismatch mode. For medium- and high-intensity genes, we identified use of data from mismatch probes (as in MAS5 and dChip mismatch) and a sequence-based method of background adjustment (as in gcRMA) as the most important factors in methods' performances. However, we found poor reliability for methods using mismatch probes for low-intensity genes, which is in agreement with previous studies.ConclusionWe advocate use of sequence-based background adjustment in lieu of mismatch adjustment to achieve the best results across the intensity spectrum. No method of normalization or probeset summary showed any consistent advantages.

Dataset Information

A real-time PCR array for hierarchical identification of Francisella isolates.

Publications

A real-time PCR array for hierarchical identification of Francisella isolates.

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