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Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes
BACKGROUND: DNA melting curve analysis using double-stranded DNA-specific dyes such as SYTO9 produce complex and reproducible melting profiles, resulting in the detection of multiple melting peaks from a single amplicon and allowing the discrimination of different species. We compare the melting cur...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1851973/ https://www.ncbi.nlm.nih.gov/pubmed/17391531 http://dx.doi.org/10.1186/1471-2105-8-107 |
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author | Rasmussen, John P Saint, Christopher P Monis, Paul T |
author_facet | Rasmussen, John P Saint, Christopher P Monis, Paul T |
author_sort | Rasmussen, John P |
collection | PubMed |
description | BACKGROUND: DNA melting curve analysis using double-stranded DNA-specific dyes such as SYTO9 produce complex and reproducible melting profiles, resulting in the detection of multiple melting peaks from a single amplicon and allowing the discrimination of different species. We compare the melting curves of several Naegleria and Cryptosporidium amplicons generated in vitro with in silico DNA melting simulations using the programs POLAND and MELTSIM., then test the utility of these programs for assay design using a genetic marker for toxin production in cyanobacteria. RESULTS: The SYTO9 melting curve profiles of three species of Naegleria and two species of Cryptosporidium were similar to POLAND and MELTSIM melting simulations, excepting some differences in the relative peak heights and the absolute melting temperatures of these peaks. MELTSIM and POLAND were used to screen sequences from a putative toxin gene in two different species of cyanobacteria and identify regions exhibiting diagnostic melting profiles. For one of these diagnostic regions the POLAND and MELTSIM melting simulations were observed to be different, with POLAND more accurately predicting the melting curve generated in vitro. Upon further investigation of this region with MELTSIM, inconsistencies between the melting simulation for forward and reverse complement sequences were observed. The assay was used to accurately type twenty seven cyanobacterial DNA extracts in vitro. CONCLUSION: Whilst neither POLAND nor MELTSIM simulation programs were capable of exactly predicting DNA dissociation in the presence of an intercalating dye, the programs were successfully used as tools to identify regions where melting curve differences could be exploited for diagnostic melting curve assay design. Refinements in the simulation parameters would be required to account for the effect of the intercalating dye and salt concentrations used in real-time PCR. The agreement between the melting curve simulations for different species of Naegleria and Cryptosporidium and the complex melting profiles generated in vitro using SYTO9 verified that the complex melting profile of PCR amplicons was solely the result of DNA dissociation. Other data outputs from these simulations were also used to identify the melting domains that contributed to the observed melting peaks for each of the different PCR amplicons. |
format | Text |
id | pubmed-1851973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18519732007-04-13 Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes Rasmussen, John P Saint, Christopher P Monis, Paul T BMC Bioinformatics Research Article BACKGROUND: DNA melting curve analysis using double-stranded DNA-specific dyes such as SYTO9 produce complex and reproducible melting profiles, resulting in the detection of multiple melting peaks from a single amplicon and allowing the discrimination of different species. We compare the melting curves of several Naegleria and Cryptosporidium amplicons generated in vitro with in silico DNA melting simulations using the programs POLAND and MELTSIM., then test the utility of these programs for assay design using a genetic marker for toxin production in cyanobacteria. RESULTS: The SYTO9 melting curve profiles of three species of Naegleria and two species of Cryptosporidium were similar to POLAND and MELTSIM melting simulations, excepting some differences in the relative peak heights and the absolute melting temperatures of these peaks. MELTSIM and POLAND were used to screen sequences from a putative toxin gene in two different species of cyanobacteria and identify regions exhibiting diagnostic melting profiles. For one of these diagnostic regions the POLAND and MELTSIM melting simulations were observed to be different, with POLAND more accurately predicting the melting curve generated in vitro. Upon further investigation of this region with MELTSIM, inconsistencies between the melting simulation for forward and reverse complement sequences were observed. The assay was used to accurately type twenty seven cyanobacterial DNA extracts in vitro. CONCLUSION: Whilst neither POLAND nor MELTSIM simulation programs were capable of exactly predicting DNA dissociation in the presence of an intercalating dye, the programs were successfully used as tools to identify regions where melting curve differences could be exploited for diagnostic melting curve assay design. Refinements in the simulation parameters would be required to account for the effect of the intercalating dye and salt concentrations used in real-time PCR. The agreement between the melting curve simulations for different species of Naegleria and Cryptosporidium and the complex melting profiles generated in vitro using SYTO9 verified that the complex melting profile of PCR amplicons was solely the result of DNA dissociation. Other data outputs from these simulations were also used to identify the melting domains that contributed to the observed melting peaks for each of the different PCR amplicons. BioMed Central 2007-03-29 /pmc/articles/PMC1851973/ /pubmed/17391531 http://dx.doi.org/10.1186/1471-2105-8-107 Text en Copyright © 2007 Rasmussen et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Rasmussen, John P Saint, Christopher P Monis, Paul T Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes |
title | Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes |
title_full | Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes |
title_fullStr | Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes |
title_full_unstemmed | Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes |
title_short | Use of DNA melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time PCR using intercalating dyes |
title_sort | use of dna melting simulation software for in silico diagnostic assay design: targeting regions with complex melting curves and confirmation by real-time pcr using intercalating dyes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1851973/ https://www.ncbi.nlm.nih.gov/pubmed/17391531 http://dx.doi.org/10.1186/1471-2105-8-107 |
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