- Estimation
via "sigmoidal" or
"logistic" curve fitting models
- Estimation via
"theoretical
sigmoidal fit" (all fluorescence
data points, Liu &
Saint 2002)
- Estimation via
"experimental
four parametric sigmoidal model fit"
(all data points, Tichopad et al. 2002)
- Estimation
via "experimental
four parametric logistic model fit" (all fluorescence data
points, Tichopad et al. 2003)
- ERRATUM:
correction of Figure 2 Tichopad et al. 2003
- PCR
Efficiency estimation via
"experimental four parametric sigmoidal model fit" (all data
points, Tichopad et
al. MCP 2004 - Inhibition of real-time RT–PCR
quantification due to tissue-specific contaminants)
- Locked nucleic acid (LNA)
single nucleotide
polymorphism (SNP) genotype analysis and validation using real-time PCR
using a SDM method (Johnson et al. 2004)
- Sigmoidal curve-fitting
redefines quantitative real-time PCR with the prospective of developing
automated high-throughput applications. (Rutledge 2004)
- Improved real-time RT-PCR
method for high-throughput measurements using second derivative
calculation and double correction. (Luu The et al. 2005)
- Gene expression of
HIF-1 α and XRCC4 measured in human
samples by real-time RT-PCR using the sigmoidal
curve-fitting method (Hao-Qiu et al., 2007)
- Model
based analysis of real-time PCR data from DNA binding dye
protocols (Alvarez et al., 2007)
- A
kinetic-based sigmoidal model for the polymerase chain reaction and its
application to high-capacity absolute quantitative real-time PCR
(Rutledge & Stewart, 2008)
- A new real-time PCR
method to overcome significant quantitative inaccuracy due to slight
amplification inhibition (Guescini et al., 2008)
- Highly accurate
sigmoidal fitting of real-time PCR data by introducing a
parameter for asymmetry. (Spiess et al., 2008)
- qPCR: an R package for sigmoidal
model selection in
quantitative real-time polymerase chain reaction analysis (Ritz &
Spiess, 2008)
- Critical evaluation of
methods used to
determine amplification efficiency refutes the exponential character of
real-time PCR (Rutledge & Stewart 2008)
- Assessing the performance
capabilities of LRE-based assays for absolute quantitative real-time
PCR (Rutledge
RG, Stewart, 2010).
- WEB
INTERFACE - Cy0 is a new method in Real-time PCR analysis that
does not
require the assumption of equal efficiency between unknowns and
standard curve (Michele Guescini, Davide Sisti, & Renato
Panebianco, 2010)
- Improving qPCR efficiency in
environmental samples by selective removal of humic acids with DAX-8
(Schriewer
A, Wehlmann A, Wuertz S. 2011)
Estimation
via "theoretical
sigmoidal fit" (all
fluorescence data points)
Liu W & Saint
DA (2002)
Validation of a
quantitative method for real time PCR kinetics.
Biochem Biophys Res
Commun. 2002 294(2): 347-353
Real time
RT-PCR is the most sensitive method for quantitation of gene expression
levels. The accuracy can be dependent on the mathematical model on
which the quantitative methods are based. The generally accepted
mathematical model assumes that amplification effciencies are equal at
the exponential phase of the reactions for the
same amplicon. However, no methods are available to test the
assumptions regarding amplification effciency before one starts the
real
time PCR quantitation. Here we further develop and test the validity of
a new mathematical model which dynamically its real time PCR data with
good correlation (r2 = 0.9995, n = 50). The method is
capable of measuring cycle-by-cycle PCR amplification effciencies
and demonstrates that these hange dynamically. Validation of the method
revealed the intrinsic relationship between the initial amount of gene
transcript and kinetic parameters. A new quantitative method is
proposed which represents a simple but accurate quantitative method.
Estimation via
"experimental
four parametric sigmoidal model fit"
(all
fluorescence data points)
Improving
quantitative real-time RT-PCR
reproducibility by
boosting primer-linked amplification efficiency.
Ales Tichopad,
Anamarija Dzidic & Michael W. Pfaffl
Biotechnology
Letters 24:
2053-2056 (2002)
Polymerase
chain reaction amplification of product of reverse transcribed RNA
is a modern approach to quantify gene expression. Several commercial
platforms are in current use and much effort is
made to enhance the precision of their quantitative outputs. Generally,
optimization of polymerase performance and search for closer computing
algorithms are two major ways to achieve it.
Often, data show that selection of primers can alter the performance
of polymerase chain reaction. To test how this affects reaction
reproducibility, mathematical model was applied describing a full
kinetic of the reactions where just primers were varied. Statistical
consideration of parameters yielded by this model revealed, that
reactions with higher amplification efficiency – primed by “good”
primers – run with lower variability and they are therefore better
suited for measurement purposes.
4 parametric sigmoidal
model
Model is
described by equation [1]. One fluorescence data set from this study
was used as an example. In this model, y0 is the ground fluorescence, a
is the difference between maximal fluorescence acquired in the run and
the ground fluorescence, x0 is the first derivative maximum of
the function or the inflexion point of the curve and b describes the
slope of curve.
equation [1]
Estimation
via "experimental four parametric
logistic model fit"
(all fluorescence data points)
Standardized
determination of
real-time PCR effciency from a single reaction set-up.
Ales Tichopad,
Michael Dilger, Gerhard Schwarz & Michael W.
Pfaffl (2003)
Nucleic Aids
Research 31(20): e122 (2003)

The
paper has been
frequently cited by other researchers: => 411 times until
April 2016
We propose a
computing method for
the estimation of real-time PCR amplifcation effciency. It
is based on a statistic delimitation of the beginning of exponentially
behaving observations in real-time PCR kinetics. PCR ground
fluorescence phase, nonexponential and plateau phase were excluded
from the calculation process by separate mathematical algorithms. We
validated the method on experimental data on multiple targets obtained
on the LightCycler platform. The developed method
yields results of higher accuracy than the currently used method of
serial dilutions for amplification effciency estimation.
The single reaction set-up estimation is sensitive to differences
in starting concentrations of the target sequence in samples.
Furthermore, it resists the subjective influence of researchers,
and the estimation can therefore be fully instrumentalized.
Figure 1:
Plot of fluorescence observations from LightCycler (Roche Diagnostics).
Forty observations give a sigmoid trajectory that can be described by
full data fit (four parametric logistic model). Ground phase can be
well linearly regressed (inlay). Following data of n > 7 are
considered exponentially behaved and can be fitted by exponential
model. Various model fits are designated in legend within figure. FDM
and SDM denote position of first and second derivative maximum within
full data fit.
Figure 2:
Flowchart of statistical estimation of the exponential phase beginning
based on inspection of externally studentised residuals.
ERRATUM download PDF tichopad-et-al-nar-2003-figure-2.pdf
A
quantitative approach for polymerase chain reactions based on a hidden
Markov model.
Lalam N.
J Math Biol. 2009 59(4): 517-533
Polymerase chain
reaction (PCR) is a major DNA amplification technology from molecular
biology. The quantitative analysis of PCR aims at determining the
initial amount of the DNA molecules from the observation of typically
several PCR amplifications curves. The mainstream observation scheme of
the DNA amplification during PCR involves fluorescence intensity
measurements. Under the classical assumption that the measured
fluorescence intensity is proportional to the amount of present DNA
molecules, and under the assumption that these measurements are
corrupted by an additive Gaussian noise, we analyze a single
amplification curve using a hidden Markov model (HMM). The unknown
parameters of the HMM may be separated into two parts. On the one hand,
the parameters from the amplification process are the initial number of
the DNA molecules and the replication efficiency, which is the
probability of one molecule to be duplicated. On the other hand, the
parameters from the observational scheme are the scale parameter
allowing to convert the fluorescence intensity into the number of DNA
molecules and the mean and variance characterizing the Gaussian noise.
We use the maximum likelihood estimation procedure to infer the unknown
parameters of the model from the exponential phase of a single
amplification curve, the main parameter of interest for quantitative
PCR being the initial amount of the DNA molecules. An illustrative
example is provided.
Inhibition
of real-time RT–PCR quantification due to tissue-specific
contaminants
Ales Tichopad, Andrea Didier, Michael W.
Pfaffl (2004)
Molecular and
Cellular Probes (18): 45-50

Real-time reverse
transcription–polymerase chain reaction (RT–PCR) is currently
considered the most sensitive method to study low abundance gene
expression. Since comparison of gene expression levels in various
tissues is often the purpose of an experiment, we studied a
tissue-linked effect on nucleic acid amplification. Based on the raw
data generated by a LightCycler instrument, we propose a descriptive
mathematical model of PCR amplification. This model allowed us to study
amplification kinetics of four common housekeeping genes in total RNA
samples derived from various bovine tissues. We observed that unknown
tissue-specific factors can influence amplification kinetics but this
affect can be ameliorated,
in part, by appropriate primer selection.
Locked nucleic acid
(LNA) single nucleotide polymorphism (SNP) genotype analysis and
validation using real-time PCR.
Johnson MP, Haupt LM, Griffiths LR.
Nucleic Acids Res. 2004 Mar 26;32(6):e55.
Genomics Research Centre, School of Health Science,
Griffith University Gold
Coast, PMB 50, Gold Coast Mail Centre, QLD 9726,
Australia.

With an increased
emphasis on
genotyping of single nucleotide polymorphisms (SNPs) in disease
association
studies, the genotyping platform of choice is constantly evolving. In
addition,
the development of more specific SNP assays and appropriate genotype
validation applications
is becoming increasingly critical to elucidate ambiguous
genotypes. In this study, we have used SNP specific Locked Nucleic Acid
(LNA)
hybridization probes on a real-time PCR platform to genotype an
association cohort
and propose three criteria to address ambiguous genotypes. Based on the
kinetic properties of PCR amplification, the three criteria address PCR
amplification efficiency, the net fluorescent difference between
maximal and
minimal fluorescent signals and the beginning of the exponential growth
phase of
the reaction.
Initially observed SNP allelic discrimination curves were
confirmed by DNA sequencing (n = 50) and application of our three
genotype criteria
corroborated both sequencing and observed real-time PCR results. In
addition, the
tested Caucasian association cohort was in Hardy-Weinberg equilibrium
and
observed allele frequencies were very similar to two independently
tested
Caucasian association cohorts for the same tested SNP. We present here
a novel
approach to effectively determine ambiguous genotypes generated from a
real-time PCR platform. Application of our three novel criteria
provides an easy to
use semi-automated genotype confirmation protocol.
Sigmoidal
curve-fitting redefines quantitative real-time PCR with the prospective
of developing automated high-throughput applications.
Rutledge RG
Natural Resources Canada, 1055 du P.E.P.S, Sainte-Foy,
Quebec, Canada G1V 4C7.
Nucleic Acids Res. 2004 32(22): e178.

Quantitative real-time PCR has
revolutionized many aspects of genetic research, biomedical diagnostics
and
pathogen detection.
Nevertheless, the full potential of this technology has yet to be
realized, primarily due to the limitations of the threshold-based
methodologies
that are currently used for quantitative analysis. Prone to errors
caused
by variations
in reaction preparation and amplification conditions, these
approaches necessitate construction of standard curves for each target
sequence,
significantly limiting the development of high-throughput applications
that
demand substantive levels of reliability and automation. In this study,
an
alternative approach based upon fitting of fluorescence data to a
four-parametric sigmoid function is shown to dramatically increase both
the utility and
reliability of quantitative real-time PCR. By mathematically modeling
individual
amplification reactions, quantification can be achieved without the use
of
standard curves and without prior knowledge of amplification
efficiency. Combined
with provision of quantitative scale via optical calibration, sigmoidal
curve-fitting could confer the capability for fully automated
quantification of
nucleic acids with unparalleled accuracy and reliability.
Improved real-time
RT-PCR method for high-throughput measurements using second derivative
calculation and double correction.
Van Luu-The, Paquet N, Calvo E, Cumps J.
Molecular Endocrinology and Oncology Research Center,
Laval University, Quebec, Canada.
Biotechniques. 2005 38(2): 287-293

Quantification of mRNA expression
levels using real-time reverse transcription PCR (RT-PCR) is
increasingly used
to validate results of DNA microarrays or GeneChips. It requires an
improved
method that is more robust and more suitable for high-throughput
measurements.
In this report, we compare a user non-influent, second derivative
method with that of a user influent, fit point method that is widely
used in the
literature. We also describe the advantage of using a double
correction: one
correction using the expression levels of a housekeeping gene of an
experiment
as an internal standard and a second using reference expression levels
of the
same housekeeping gene in the tissue or cells. The first correction
permits one
to decrease errors due to sample preparation and handling, while
the second
correction permits one to avoid the variation of the results with the
variability of housekeeping in each tissue, especially in experiments
using
various treatments. The data indicate that the real-time PCR method is
highly
efficient with an efficiency coefficient close to the theoretical value
of two. The
results also show that the second derivative method is more accurate
than the
fit point method in quantifying low gene expression levels. Using
triplicate experiments,
we show that measurement variations using our method are
low with
a mean of variation coefficients of <1%.
Gene
expression of HIF-1 α and XRCC4 measured
in human samples by real-time RT-PCR
using
the sigmoidal curve-fitting method.
Hao
Qiu, Karine Durand, Hélène Rabinovitch-Chable, Michel
Rigaud, Virgile Gazaille,
Pierre
Clavère, and Franck G. Sturtz
BioTechniques
42:355-362 (March 2007)

Quantitative
reverse transcription PCR (RT-PCR) has become an important tool for
studying functional gene expression. However, the most often used
cycle threshold (CT)-based method, primarily related to the required
amplification efficiency determination via serial dilution,
can call into question the level of quantitative reliability and
accuracy that can be achieved, in addition to the impracticalities
inherent to CT-based methodologies. In this study, an alternative
method, named the sigmoidal curve-fitting (SCF) method, was compared
with the classic CT method for two target genes (XRCC4 and HIF-1α) and
a reference gene (HPRT). The PCR conditions were
optimized for each gene on a LightCycler® apparatus. Fluorescence
data were fitted to a four-parametric sigmoidal function,
and the initial messenger RNA (mRNA) copy number was determined by a
theoretical fluorescence (F0) value calculated from each
fitting curve. The relative expression of the target gene versus that
of the reference gene was calculated using an equation based
upon these F0 values. The results show that the F0 value had a good
linearity with the initial number of target genes between 107 and
101 copies. The reproducibility tests showed that the variations of
initial target quantity were well reflected by F0 values.
Relative expression of target gene calculated by the SCF method and by
the CT method showed similar results. In our hands, the SCF method
gave reliable results and a more precise error description of
quantitative RT-PCR.
Model based analysis
of real-time PCR data from DNA binding dye protocols.
Alvarez
MJ, Vila-Ortiz GJ, Salibe MC, Podhajcer OL, Pitossi FJ.
Gentron
Research Unit, Arenales Piso, Buenos Aires C1061AAO, Argentina.
BMC
Bioinformatics. 2007 8:85.
BACKGROUND:
Reverse transcription followed by real-time PCR is widely used for
quantification of
specific mRNA, and with the use of double-stranded DNA binding dyes it
is becoming a
standard for microarray data validation. Despite the kinetic
information
generated by real-time PCR, most popular analysis methods assume
constant
amplification efficiency among samples, introducing strong biases when
amplification efficiencies are not the same.
RESULTS: We present here a new
mathematical model based on the classic exponential description of the
PCR, but modeling
amplification efficiency as a sigmoidal function of the product yield.
The
model was validated with experimental results and used for the
development of a
new method for real-time PCR data analysis. This model based method for
real-time PCR data analysis showed the best accuracy and precision
compared
with previous methods when used for quantification of in-silico
generated
and experimental real-time PCR results. Moreover, the method is
suitable for the
analyses of samples with similar or dissimilar amplification
efficiency.
CONCLUSION: The presented method showed the best accuracy and
precision. Moreover,
it does not depend on calibration curves, making it ideal for fully
automated
high-throughput applications.
A kinetic-based
sigmoidal model for the polymerase chain reaction and its application
to high-capacity
absolute quantitative real-time PCR
Robert
G Rutledge & Donald Stewart
BMC
Biotechnology 2008, Published: 8 May 2008

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.
Conclusions: 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.
A
new real-time PCR method to overcome significant quantitative
inaccuracy due to slight amplification inhibition.
BMC
Bioinformatics 2008, 9:326
Michele
Guescini, Davide Sisti, Marco BL Rocchi, Laura Stocchi, Vilberto Stocchi

Background: Real-time
PCR analysis is a sensitive DNA
quantification technique that has recently
gained considerable attention in
biotechnology, microbiology and molecular
diagnostics. Although, the cycle-threshold (Ct) method is the present
“gold standard”, it is far from being a
standard assay. Uniform reaction efficiency
among samples is the most important
assumption of this method.
Nevertheless, some authors have reported that
it may not be correct and a slight PCR efficiency decrease of about 4%
could result in an error of up to 400% using the Ct method. This
reaction efficiency decrease may be caused by inhibiting agents
used during nucleic acid extraction or copurified from the
biological sample. We propose a new method (Cy0) that does not require
the assumption of equal reaction efficiency between unknowns and
standard curve.
Results: The Cy0
method is based on the
fit of Richards’ equation to
real-time PCR data by nonlinear
regression in order to obtain the
best fit estimators of reaction
parameters. Subsequently, these parameters were used to calculate the
Cy0 value that minimizes the dependence of its value on PCR kinetic.
The Ct, second derivative (Cp), sigmoidal curve fitting method (SCF)
and Cy0 methods were compared using two
criteria: precision and accuracy. Our
results demonstrated that, in optimal
amplification conditions, these four methods
are equally precise and
accurate. However, when PCR efficiency was slightly decreased, diluting
amplification mix quantity or adding a biological inhibitor such as
IgG, the SCF, Ct and Cp methods were markedly impaired
while the Cy0 method gave significantly more
accurate and precise results.
Conclusion: Our
results demonstrate that Cy0 represents a significant improvement
over the standard methods for obtaining a
reliable and precise nucleic acid
quantification even in suboptimal amplification
conditions overcoming the underestimation
caused by the presence of some PCR inhibitors.
WEB
INTERFACE - Cy0 is a new method in Real-time PCR analysis that
does not
require the assumption of equal efficiency between unknowns and
standard curve (Michele Guescini, Davide Sisti, & Renato
Panebianco, 2010)
Highly
accurate sigmoidal fitting of real-time PCR data by introducing
a parameter for asymmetry.
Andrej-Nikolai
Spiess, Caroline Feig and Christian Ritz
BMC
Bioinformatics 2008, 9:221

Background: Fitting
four-parameter
sigmoidal models is one of the methods established in the analysis of
quantitative real-time PCR (qPCR) data. We had observed that these
models are not optimal in the
fitting outcome due to the inherent constraint of symmetry around the
point of inflection. Thus, we
found it necessary to employ a mathematical algorithm that circumvents
this problem
and which utilizes an additional parameter for accommodating
asymmetrical structures insigmoidal qPCR data.
Results: The four-parameter models
were compared to their five-parameter counterparts by means of nested
F-tests based on the residual variance, thus acquiring a statistical
measure for higher performance.
For nearly all qPCR data we examined, five-parameter models resulted in
a significantly
better fit. Furthermore, accuracy and precision for the estimation of
efficiencies and calculation of
quantitative ratios were assessed with four independent dilution
datasets and compared to the most
commonly used quantification methods. It could be shown that the
fiveparameter model exhibits an
accuracy and precision more similar to the non-sigmoidal
quantification
methods.
Conclusion: The five-parameter
sigmoidal models outperform the established four-parameter model with
high
statistical significance. The estimation of essential PCR parameters
such as PCR efficiency, threshold
cycles and initial template fluorescence is more robust and has smaller
variance.
The model is implemented in the qpcR package for the freely available
statistical R environment. The
package can be downloaded from the author's homepage.
qPCR:
an R package for sigmoidal model selection
in
quantitative real-time
polymerase chain reaction analysis.
Christian
Ritz and Andrej-Nikolai Spiess
BIOINFORMATICS
APPLICATIONS NOTE Vol. 24 no. 13 2008, pages 1549–1551

Summary: The qpcR library is an
add-on to the free R statistical environment performing sigmoidal model
selection in realtime quantitative polymerase chain reaction (PCR) data
analysis. Additionally, the package implements the most commonly used
algorithms for real-time PCR data analysis and is capable of extensive
statistical comparison for the selection and evaluation of the
different models based on several measures of goodness of fit.
Availability: www.dr-spiess.de/qpcR.html.
Supplementary Information:
Statistical evaluations of the implemented methods can be found at www.dr-spiess.de under
‘Supplemental Data’.
Critical evaluation
of methods used to
determine amplification efficiency refutes the exponential character of
real-time PCR
Rutledge &
Stewart 2008
BMC Molecular Biology 2008, 9:96
The
challenge of determining amplification efficiency has long been a
predominant aspect of implementing real-time qPCR, playing a critical
role in the accuracy and reliability that can be achieved. Based upon
analysis of amplification profile position, standard curves are
currently the gold standard for amplification efficiency determination.
However, in addition to being highly resource intensive, the efficacy
of this approach is limited by the necessary assumption that all
samples are amplified with the same efficiency as predicted by a
standard curve. These limitations have driven efforts to develop
methods for determining amplification efficiency by analyzing the
fluorescence readings from individual amplification reactions. The most
prominent approach is based on analysis of the "log-linear region",
founded upon the presumption that amplification efficiency is constant
within this region. Nevertheless, a recently developed sigmoidal model
has provided new insights that challenge such historically held views,
dictating that amplification efficiency is not only dynamic, but is
linearly coupled to amplicon DNA quantity. Called "linear regression of
efficiency" or LRE, this kinetic-based approach redefines amplification
efficiency as the maximal efficiency (Emax) generated at the onset of
thermocycling.
Assessing
the performance capabilities of LRE-based assays for absolute
quantitative real-time PCR.
Rutledge RG, Stewart D.
PLoS One. 2010 5(3):e9731.

BACKGROUND: Linear
regression of efficiency or LRE introduced a new paradigm for
conducting absolute quantification, which does not require standard
curves, can generate absolute accuracies of +/-25% and has single
molecule sensitivity. Derived from adapting the classic Boltzmann
sigmoidal function to PCR, target quantity is calculated directly from
the fluorescence readings within the central region of an amplification
profile, generating 4-8 determinations from each amplification reaction.
FINDINGS: Based on
generating a linear representation of PCR amplification, the
highly visual nature of LRE analysis is illustrated by varying reaction
volume and amplification efficiency, which also demonstrates how LRE
can be used to model PCR. Examining the dynamic range of LRE further
demonstrates that quantitative accuracy can be maintained down to a
single target molecule, and that target quantification below ten
molecules conforms to that predicted by Poisson distribution. Essential
to the universality of optical calibration, the fluorescence intensity
generated by SYBR Green I (FU/bp) is shown to be independent of GC
content and amplicon size, further verifying that absolute scale can be
established using a single quantitative standard. Two high-performance
lambda amplicons are also introduced that in addition to producing
highly precise optical calibrations, can be used as benchmarks for
performance testing. The utility of limiting dilution assay for
conducting platform-independent absolute quantification is also
discussed, along with the utility of defining assay performance in
terms of absolute accuracy.
CONCLUSIONS: Founded on
the ability to exploit lambda gDNA as a universal
quantitative standard, LRE provides the ability to conduct absolute
quantification using few resources beyond those needed for sample
preparation and amplification. Combined with the quantitative and
quality control capabilities of LRE, this kinetic-based approach has
the potential to fundamentally transform how real-time qPCR is
conducted.
LRE Analyzer Hompage
- Enabling large-scale absolute quantification
Installation
files for the most current version of the LRE Analyzer are available on
the LRE qPCR Open Source download page.
The LRE Analyzer is a fully featured
desktop application that provides the automated analysis and
data storage capabilities required by large-scale qPCR projects,
wanting to exploit the many advantages of absolute quantification.
Foremost is the universal perspective provided by absolute
quantification, which among other attributes, provides the ability to
directly compare quantitative data derived from diverse sources, such
as from different assays, instruments and/or research groups.
Furthermore, absolute quantification has important implications for
gene expression profiling, in that it provides the foundation for
comparing transcript quantities produced by any gene to any other gene,
within and between any sample.
Based on the application of sigmoidal mathematics in combination with
utilizing lambda gDNA as a universal quantitative standard, the LRE
Analyzer provides the ability to conduct absolute quantification
without construction of standard curves. In addition to enabling
large-scale absolute quantification, the LRE Analyzer also expands the
fundamental capabilities of qPCR, reflected in part by the quality
control capabilities it provides that are not possible using
conventional methods.
Getting Started
The LRE Analyzer has an extensive help set that provides an in-depth
introduction to LRE, in addition to guidelines on how to implement LRE
quantification. Demonstration database files are provided to help
illustrate how the program functions. The Introduction to LRE page
provides basic background information about how LRE quantification is
conducted, with the LRE Video Overview page providing a three part
video describing how LRE was conceived, along with a detailed overview
of methods that were used to evaluate the accuracy and dynamic range of
LRE quantification. The LRE Literature page provides links to
LRE-related publications, in addition to two earlier qPCR studies that
were instrumental in the development of LRE.
Navigation
Improving
qPCR efficiency in environmental samples by selective removal of humic
acids with DAX-8.
Schriewer A, Wehlmann A, Wuertz S.
J Microbiol Methods. 2011 Jan

Quantitative PCR is becoming the method of choice for the
detection of pathogenic microorganisms and other targets in the
environment. A major obstacle when amplifying DNA is the presence of
inhibiting substances like humic acids that decrease the efficiency of
PCR. We combined the polymeric adsorbent Supelite™ Dax-8 with a
large-volume (10mL) nucleic acid extraction method to decrease the
humic acid content prior to qPCR quantification in water samples. The
method was tested by spiking with humic acid standards and the
bacterial surrogate Acinetobacter baylyi ADP1. Improvements in qPCR
detection of ADP1 after application of Dax-8 resin (5 and 10w/v %) were
compared with the effects of added bovine serum albumin (BSA) (50, 100
and 200ng/μL). Both additions improved detection of ADP1 by
counteracting inhibitory effects. There were no changes in mean cycle
threshold difference (ΔC(T)) after application of DAX-8 compared to the
control despite some loss of DNA, whereas significant increases
occurred for BSA, irrespective of BSA concentration applied. The use of
DAX-8 leads to an increase in qPCR amplification efficiency in contrast
to BSA. The commonly used method to calculate genomic sample
concentrations by comparing measured CT values relative to standard
curves is only valid if amplification efficiencies of both are
sufficiently similar. Dax-8 can provide this efficiency by removing
humic acids permanently from nucleic acid extracts and has the
potential to significantly increase the reliability of reported
non-detects and measured results obtained by qPCR in environmental
monitoring.
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