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A kinetic-based sigmoidal model for the polymerase chain reaction and its application to high-capacity absolute quantitative real-time PCR.

Rutledge RG, Stewart D - BMC Biotechnol. (2008)

Bottom Line: Comparison with the LinReg and Miner automated qPCR data processing packages further demonstrated the superior performance of this kinetic-based methodology.The computational simplicity and recursive nature of LRE quantification also makes it amenable to software implementation, as demonstrated by a prototypic Java program that automates data analysis.This in turn introduces the prospect of conducting absolute quantification with little additional effort beyond that required for the preparation of the amplification reactions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Natural Resources Canada, Canadian Forest Service, 1055 du PEPS, Quebec, Quebec G1V 4C7, Canada. Bob.Rutledge@NRCan.gc.ca

ABSTRACT

Background: Based upon defining a common reference point, current real-time quantitative PCR technologies compare relative differences in amplification profile position. As such, absolute quantification requires construction of target-specific standard curves that are highly resource intensive and prone to introducing quantitative errors. Sigmoidal modeling using nonlinear regression has previously demonstrated that absolute quantification can be accomplished without standard curves; however, quantitative errors caused by distortions within the plateau phase have impeded effective implementation of this alternative approach.

Results: Recognition that amplification rate is linearly correlated to amplicon quantity led to the derivation of two sigmoid functions that allow target quantification via linear regression analysis. In addition to circumventing quantitative errors produced by plateau distortions, this approach allows the amplification efficiency within individual amplification reactions to be determined. Absolute quantification is accomplished by first converting individual fluorescence readings into target quantity expressed in fluorescence units, followed by conversion into the number of target molecules via optical calibration. Founded upon expressing reaction fluorescence in relation to amplicon DNA mass, a seminal element of this study was to implement optical calibration using lambda gDNA as a universal quantitative standard. Not only does this eliminate the need to prepare target-specific quantitative standards, it relegates establishment of quantitative scale to a single, highly defined entity. The quantitative competency of this approach was assessed by exploiting "limiting dilution assay" for absolute quantification, which provided an independent gold standard from which to verify quantitative accuracy. This yielded substantive corroborating evidence that absolute accuracies of +/- 25% can be routinely achieved. Comparison with the LinReg and Miner automated qPCR data processing packages further demonstrated the superior performance of this kinetic-based methodology.

Conclusion: Called "linear regression of efficiency" or LRE, this novel kinetic approach confers the ability to conduct high-capacity absolute quantification with unprecedented quality control capabilities. The computational simplicity and recursive nature of LRE quantification also makes it amenable to software implementation, as demonstrated by a prototypic Java program that automates data analysis. This in turn introduces the prospect of conducting absolute quantification with little additional effort beyond that required for the preparation of the amplification reactions.

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Optical calibrations of five reaction formulations supplemented with various quantities of SYBR Green I. Spreadsheet summary of the lambda gDNA (primer pair K7B-K12) optical calibrations conducted for the five reaction formulations used for LRE quantification in this study. Based on data presented in Figure 2, these formulations were designed to assess the impact of SYBR Green I quantity, the highest supplemented quantity (2.0X) estimated to be > 10X than that present in these three commercial formulations. Each row of values was derived from an individual amplification run (see additional file 3 for more details). (A) QuantiTect 0X SYBR Green I. (B) QuantiTect 0.2X SYBR Green I. (C) DyNAmo 0.5X SYBR Green I. (D) DyNAmo 1.5X SYBR Green I. (E) FullVelocity 2.0X SYBR Green I. Lam: lambda gDNA quantity in femtograms, QT: QuantiTect, DyNa: DyNAmo; FV: FullVelocity, SG: SYBR Green I, SD: standard deviation, CV: coefficient of variation (SD/Average × 100%).
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Figure 6: Optical calibrations of five reaction formulations supplemented with various quantities of SYBR Green I. Spreadsheet summary of the lambda gDNA (primer pair K7B-K12) optical calibrations conducted for the five reaction formulations used for LRE quantification in this study. Based on data presented in Figure 2, these formulations were designed to assess the impact of SYBR Green I quantity, the highest supplemented quantity (2.0X) estimated to be > 10X than that present in these three commercial formulations. Each row of values was derived from an individual amplification run (see additional file 3 for more details). (A) QuantiTect 0X SYBR Green I. (B) QuantiTect 0.2X SYBR Green I. (C) DyNAmo 0.5X SYBR Green I. (D) DyNAmo 1.5X SYBR Green I. (E) FullVelocity 2.0X SYBR Green I. Lam: lambda gDNA quantity in femtograms, QT: QuantiTect, DyNa: DyNAmo; FV: FullVelocity, SG: SYBR Green I, SD: standard deviation, CV: coefficient of variation (SD/Average × 100%).

Mentions: An illustration of this approach is presented in Figure 6, which summarizes optical calibrations conducted with five reaction formulations supplemented with various quantities of SYBR Green I. Derived from the analyses of 32 individual amplification runs, this large dataset provides a general indication of the variances generated by each LRE parameter, culminating in an OCF average CV of ± 21.3% across all five reaction formulations. All things being equal, this should be indicative of the resolution that a LRE-based quantitative assay can achieve. Indeed, similar variances were generated by repeated quantifications of eleven mRNA targets, as described in the next section. Of greater significance, however, is the ability to use optical calibration to establish an absolute quantitative scale.


A kinetic-based sigmoidal model for the polymerase chain reaction and its application to high-capacity absolute quantitative real-time PCR.

Rutledge RG, Stewart D - BMC Biotechnol. (2008)

Optical calibrations of five reaction formulations supplemented with various quantities of SYBR Green I. Spreadsheet summary of the lambda gDNA (primer pair K7B-K12) optical calibrations conducted for the five reaction formulations used for LRE quantification in this study. Based on data presented in Figure 2, these formulations were designed to assess the impact of SYBR Green I quantity, the highest supplemented quantity (2.0X) estimated to be > 10X than that present in these three commercial formulations. Each row of values was derived from an individual amplification run (see additional file 3 for more details). (A) QuantiTect 0X SYBR Green I. (B) QuantiTect 0.2X SYBR Green I. (C) DyNAmo 0.5X SYBR Green I. (D) DyNAmo 1.5X SYBR Green I. (E) FullVelocity 2.0X SYBR Green I. Lam: lambda gDNA quantity in femtograms, QT: QuantiTect, DyNa: DyNAmo; FV: FullVelocity, SG: SYBR Green I, SD: standard deviation, CV: coefficient of variation (SD/Average × 100%).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2397388&req=5

Figure 6: Optical calibrations of five reaction formulations supplemented with various quantities of SYBR Green I. Spreadsheet summary of the lambda gDNA (primer pair K7B-K12) optical calibrations conducted for the five reaction formulations used for LRE quantification in this study. Based on data presented in Figure 2, these formulations were designed to assess the impact of SYBR Green I quantity, the highest supplemented quantity (2.0X) estimated to be > 10X than that present in these three commercial formulations. Each row of values was derived from an individual amplification run (see additional file 3 for more details). (A) QuantiTect 0X SYBR Green I. (B) QuantiTect 0.2X SYBR Green I. (C) DyNAmo 0.5X SYBR Green I. (D) DyNAmo 1.5X SYBR Green I. (E) FullVelocity 2.0X SYBR Green I. Lam: lambda gDNA quantity in femtograms, QT: QuantiTect, DyNa: DyNAmo; FV: FullVelocity, SG: SYBR Green I, SD: standard deviation, CV: coefficient of variation (SD/Average × 100%).
Mentions: An illustration of this approach is presented in Figure 6, which summarizes optical calibrations conducted with five reaction formulations supplemented with various quantities of SYBR Green I. Derived from the analyses of 32 individual amplification runs, this large dataset provides a general indication of the variances generated by each LRE parameter, culminating in an OCF average CV of ± 21.3% across all five reaction formulations. All things being equal, this should be indicative of the resolution that a LRE-based quantitative assay can achieve. Indeed, similar variances were generated by repeated quantifications of eleven mRNA targets, as described in the next section. Of greater significance, however, is the ability to use optical calibration to establish an absolute quantitative scale.

Bottom Line: Comparison with the LinReg and Miner automated qPCR data processing packages further demonstrated the superior performance of this kinetic-based methodology.The computational simplicity and recursive nature of LRE quantification also makes it amenable to software implementation, as demonstrated by a prototypic Java program that automates data analysis.This in turn introduces the prospect of conducting absolute quantification with little additional effort beyond that required for the preparation of the amplification reactions.

View Article: PubMed Central - HTML - PubMed

Affiliation: Natural Resources Canada, Canadian Forest Service, 1055 du PEPS, Quebec, Quebec G1V 4C7, Canada. Bob.Rutledge@NRCan.gc.ca

ABSTRACT

Background: Based upon defining a common reference point, current real-time quantitative PCR technologies compare relative differences in amplification profile position. As such, absolute quantification requires construction of target-specific standard curves that are highly resource intensive and prone to introducing quantitative errors. Sigmoidal modeling using nonlinear regression has previously demonstrated that absolute quantification can be accomplished without standard curves; however, quantitative errors caused by distortions within the plateau phase have impeded effective implementation of this alternative approach.

Results: Recognition that amplification rate is linearly correlated to amplicon quantity led to the derivation of two sigmoid functions that allow target quantification via linear regression analysis. In addition to circumventing quantitative errors produced by plateau distortions, this approach allows the amplification efficiency within individual amplification reactions to be determined. Absolute quantification is accomplished by first converting individual fluorescence readings into target quantity expressed in fluorescence units, followed by conversion into the number of target molecules via optical calibration. Founded upon expressing reaction fluorescence in relation to amplicon DNA mass, a seminal element of this study was to implement optical calibration using lambda gDNA as a universal quantitative standard. Not only does this eliminate the need to prepare target-specific quantitative standards, it relegates establishment of quantitative scale to a single, highly defined entity. The quantitative competency of this approach was assessed by exploiting "limiting dilution assay" for absolute quantification, which provided an independent gold standard from which to verify quantitative accuracy. This yielded substantive corroborating evidence that absolute accuracies of +/- 25% can be routinely achieved. Comparison with the LinReg and Miner automated qPCR data processing packages further demonstrated the superior performance of this kinetic-based methodology.

Conclusion: Called "linear regression of efficiency" or LRE, this novel kinetic approach confers the ability to conduct high-capacity absolute quantification with unprecedented quality control capabilities. The computational simplicity and recursive nature of LRE quantification also makes it amenable to software implementation, as demonstrated by a prototypic Java program that automates data analysis. This in turn introduces the prospect of conducting absolute quantification with little additional effort beyond that required for the preparation of the amplification reactions.

Show MeSH
Related in: MedlinePlus