Contents. Education Bustin obtained his B.A. And PhD from in molecular genetics. Career Following the merger with and Queen Mary University of London, Bustin was promoted to Reader in Molecular Medicine in 2002, followed by the award of a personal chair as Professor of Molecular Science in 2004 at.
Feb 9, 2018 - quantification, for evaluating data from quantitative PCR can be used. By Real-time PCR technique via various relative and absolute quantification. The Real-time PCR Encyclopaedia A–Z of Quantitative PCR.
As of 2015, Bustin held the position of Professor of Molecular Medicine at.: 219 He is a fellow of the. Bustin also co-founded and edits the journal to provide a peer-reviewed outlet for 'high-quality quantitative studies'.: 219 Research His research group’s general areas of interest are the small and large bowel, as well as with particular emphasis on investigating the process of invasion and metastasis. An important aim is to translate molecular techniques into clinical practice by including molecular parameters into clinical tumor staging. To this end, Bustin has published many papers on PCR techniques, in particular, the subject of his most cited paper, published in 2000.
He also developed the MIQE guidelines in a 2009 paper published in, the goal of which is to create guidelines for how PCR should be performed to ensure that PCR results are being reliably conducted and interpreted, as well as to make replication of experiments easier. This paper is the fifth most cited one ever to be published in Clinical Chemistry, with over 1700 citations on as of September 2013. Testimony Autism omnibus trial Bustin testified on behalf of the Department of Justice in the about what he stated was the unreliability of the O'Leary lab's results with regard to testing for contamination. The lab had claimed to find in the intestines of children with developmental disorders. Bustin describes his conclusions with regard to the lab's alleged detection of measles virus RNA as follows: 'My clear conclusion then was that O'Leary's results were caused by defective experimental technique and inappropriate interpretation of results, since he was detecting DNA, and measles virus does not exist as DNA.'
Bustin was described as 'one of the most highly qualified and credible expert witnesses I the Special Master have ever encountered.' In addition to his testimony, Bustin published an analysis of 's 2002 study, which had been published in the journal. This analysis, like Bustin's testimony, concluded that 'The only conclusion possible is that the assays were detecting contaminating DNA. Since MeV is an RNA-only virus and never exists in DNA form, these data must be ignored and it is my opinion that the authors should withdraw this publication from the peer-reviewed literature.' Lundy murders Bustin testified in the trials pertaining to the in 2015, criticizing tests that had claimed to detect human brain cells on Mark Lundy's shirt.
References. Retrieved 24 September 2013. Retrieved 12 August 2013. McGee, Patrick (10 May 2007).
Drug Discovery & Development. Retrieved 12 December 2013. ^ Bustin, Stephen (2013). Retrieved 12 August 2013. Perkel, Jeffrey M.
(1 December 2013). Retrieved 21 February 2014.
Anglia Ruskin University. Retrieved 30 September 2016. Bustin, Stephen (2008). European Pharmaceutical Review (1): 11–17. ^ Perkel, Jeffrey (1 May 2015). 'GUIDING OUR PCR EXPERIMENTS'. Anglia Ruskin University.
Retrieved 2018-01-18. Retrieved 30 August 2015.
30 September 2010. Retrieved 11 August 2013. Nolan, T.; Hands, R. E.; Bustin, S. 'Quantification of mRNA using real-time RT-PCR'. Nature Protocols.
1 (3): 1559–1582. Mueller, R.; Bustin, S. 'Real-time reverse transcription PCR (qRT-PCR) and its potential use in clinical diagnosis'. Clinical Science. 109 (4): 365–379.
'Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays'. Journal of Molecular Endocrinology. 25 (2): 169–193. A.; Benes, V.; Garson, J.
A.; Hellemans, J.; Huggett, J.; Kubista, M.; Mueller, R.; Nolan, T.; Pfaffl, M. W.; Shipley, G. L.; Vandesompele, J.; Wittwer, C.
'The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments'. Clinical Chemistry. 55 (4): 611–622. Retrieved 11 August 2013. Retrieved 9 September 2013. Marx, Vivien (2013). 10 (5): 391–395.:.
Retrieved 27 September 2013. Bustin, Stephen (8 December 2008). Retrieved 11 August 2013. Fitzpatrick, Michael (4 July 2007). Retrieved 12 December 2013.
'Why There Is no Link Between Measles Virus and Autism'. Recent Advances in Autism Spectrum Disorders - Volume I. Feinstein, Adam (2010). A History of Autism: Conversations with the Pioneers. Quilliam, Rebecca (11 March 2015). Retrieved 30 August 2015.
Galuszka, Jono (9 March 2015). Retrieved 30 August 2015. External links. publications indexed.
Background Research into gene expression enables scientists to decipher the complex regulatory networks that control fundamental biological processes. Quantitative real-time PCR (qPCR) is a powerful and ubiquitous method for interrogation of gene expression.
Accurate quantification is essential for correct interpretation of qPCR data. However, conventional relative and absolute quantification methodologies often give erroneous results or are laborious to perform. To overcome these failings, we developed an accurate, simple to use, universal calibrator, AccuCal.
Significant differences in gene expression between tissues, disease states or treatment groups steer the direction of much research. It is imperative therefore, that mRNA quantification methods are standardized, accurate and unbiased. Due to its sensitivity, qPCR has become the standard method for measuring levels of gene expression. Quantification of PCR may be relative or absolute, and traditionally has been performed using non-specific intercalating dyes or gene-specific fluorescent probes. These methods, although widely used, are known to have many fundamental problems, despite considerable efforts over the last 20 years to overcome these. Relative quantification using intercalating dyes is the most common method used. It is simple and cheap to perform, but relies on the use of one or more reference genes, against which the mRNA concentrations of the genes of interest (GOIs) are normalized.
The optimal number and choice of reference genes is determined empirically, but various useful computational methods help researchers in this regard ,. A suitable reference gene must be stably expressed between the experimental groups, have similar amplification efficiency and abundance to the GOIs. In reality this is rare, and reference genes often introduce bias into an experiment, leading to erroneous interpretation of results ,.
Absolute quantification is performed by constructing a standard curve for each GOI and plotting the quantification cycle (Cq) values against logquantity of a dilution series of known GOI amount. These standards, comprising purified PCR product, plasmid DNA constructs or synthetic oligonucleotides spanning the PCR amplicon, are amplified, as are any experimental errors. This is important as the standard curve provides both the efficiency of the amplification primers and the amount of GOI in the unknown samples.
Ideally, a new standard curve is generated each time a sample is quantified, but in practice, due to the complexity of the method, many researchers generate a standard curve once and use it repeatedly to quantify samples over a period of time. This produces inaccurate results as the efficiency of amplification may vary across samples, with time, or between the target used to generate the standard curve and the ‘real’ target within a complex sample. The Minimum Information for publication of Quantitative real-time PCR Experiments (MIQE) guidelines were introduced to facilitate standardization of the experimental and reporting practices in qPCR, to enable more reliable and unequivocal interpretation of qPCR results. These have helped enormously, but the fundamental problems associated with identifying suitable reference genes for an experiment, or having to generate standard curves for each GOI, are still present and can result in misinterpreted data. AccuCal™, a universal Accurate Calibrator, was developed to address these problems and aid in standardizing measurement in qPCR.
1 Quantification of PCR amplified nucleic acid using AccuCal calibrator. A The workflow associated with using AccuCal to quantify input nucleic acid amount in each PCR, b AccuCal calibrator was diluted so that 0, 40, 60, 80, 120, 140 and 200 ng in Sso Fast EvaGreen Supermix were added to respective wells of a PCR plate and subjected to 40 amplification cycles. C The fluorescence intensity of each AccuCal calibrator (after subtraction of mean 0 ng AccuCal fluorescence) was plotted against the amount (pmols) and a linear regression line fitted to generate the calibration curve. D Ten-fold dilutions of lambda DNA, ranging from 4.5 × 10 6 – 4.5 × 10 1 copies/PCR, were amplified in quadruplicate in Sso Fast EvaGreen Supermix on the same plate as the AccuCal calibrators. E The calibration curve was used, alongside the calculated efficiency of each amplification reaction and the cycle numbers between the take-off point (Cq) and second derivative maxima for each amplification reaction, to quantify the mean starting amount of DNA in each PCR. The standard error of the mean is also presented.
F The theoretical and determined number of copies/PCR, plus SEM, were plotted against each other and a regression line drawn to demonstrate the agreement between the two values To determine the AccuCal-D range to use, the initial optimization was performed under the same reaction conditions as for DNA amplifications. In the example shown, a range of 0–140 ng, was optimal, as this spanned the exponential portion of the amplification curves, where the amount of amplified target is directly proportional to the input amount , , and gave a linear calibration curve with R 2 value of 0.9987 (Fig., and Additional file ). This determination only needs to be performed once, provided reaction conditions of all subsequent PCRs remain constant.
To show the quantification accuracy of AccuCal-D, we amplified serial ten-fold dilutions of known quantities of a 92 bp amplicon from lambda DNA, from 4.5 × 10 6 – 4.5 × 10 1 copies, in quadruplicate alongside AccuCal-D, at the predetermined amounts, and plotted the calibration curve (Fig. The efficiency of each amplification reaction was then determined by RealCount using known algorithms. Finally, using the efficiency values and calibration curve, the mean amount of input DNA, and standard error of the mean, was calculated for all cycles during the exponential phase of each amplification curve using RealCount (Fig. A regression analysis between the determined values and the theoretical amount seeded into the PCR yielded an R 2 of 0.9977 (Fig.
) demonstrating the utility of the AccuCal-D method and its accuracy in absolute quantification of real-time qPCR. AccuCal-D relies on an intercalating dye to generate fluorescence, but the dye:AccuCal-D fluorescence ratio is unknown. To understand this relationship, we developed a probe-based version of AccuCal, AccuCal-P. A 92 bp amplicon from a range of concentrations of lambda DNA was amplified and detected using either a FAM-labelled hydrolysis probe or EvaGreen intercalating dye. Both AccuCal-D and FAM-labelled AccuCal-P were included on the PCR plate and were used independently to quantify the lambda DNA detected by both markers. The quantification using either AccuCal-D or AccuCal-P, for both sets of PCR amplifications, yielded indistinguishable results for each dilution with no significant differences between the slopes when theoretical number of copies is plotted against determined number of copies (slopes = 0.9601, 0.9653, 0.9623 and 0.9701, R 2 = 1 for each; Fig.
And Additional file ). AccuCal-P and the hydrolysis probe are labelled with one FAM moiety per DNA molecule, and report the same fluorescence per DNA molecule as the EvaGreen dye does under these qPCR conditions. 2 Quantification using both AccuCal-D and AccuCal-P. A Five, ten-fold dilutions of a known quantity of lambda DNA, ranging from 4.5 × 10 5 to 4.5 × 10 1, were amplified twice in quadruplicate and detected using either EvaGreen, the intercalating dye in Sso Fast mastermix, or a FAM-labelled hydrolysis probe specific to the target amplicon. In both cases, AccuCal-D and AccuCal-P calibrators were included on the same plate and used to independently quantify the starting amount of input DNA in each PCR.
The theoretical amount versus the calculated amount, determined by either AccuCal-D or AccuCal-P, using the EvaGreen dye (EG) or the hydrolysis probe (P), was plotted and the linear regression of each is shown in the graph on the right. B Five, ten-fold dilutions of a known quantity of lambda DNA in quadruplicate were amplified in Sso Fast mastermix using primers to give a 501 bp amplicon. AccuCal-D and AccuCal-P calibrators were included on the same plate and were used to independently quantify the starting amount of lambda DNA in each PCR. The theoretical amount versus the calculated amount, determined by either AccuCal-D or AccuCal-P, for the 501 bp amplicon, was plotted and the linear regression of each is shown in the graph on the right.
C Five, ten-fold dilutions (3 one-hundred fold dilutions on the Eco) of a known quantity of lambda DNA were amplified in various mastermixes (see ) on the different qPCR platforms indicated over 2–10 PCR runs. The theoretical amount versus the mean calculated amount, determined by AccuCal-D, across all platforms was plotted and the linear regression is shown in the graph on the right. The mean number of calculated copies/PCR and SEM are shown in each case To determine the range of amplicon sizes for which AccuCal-D quantification can be used, we also amplified lambda amplicons of 501 bp. Amplicons of 92 bp to 501 bp covers the spectrum of amplicon sizes that are typically amplified by qPCR. Again, AccuCal-P and a FAM-labelled template-specific hydrolysis probe were used as a comparator for AccuCal-D and intercalating dye. The results show that the quantification is similar for both amplicon sizes whether this is calculated using AccuCal-D or AccuCal-P, with neither slope differing significantly from 1 (Fig. This suggests that the dye and probe fluorescence remains constant over this range of amplicon sizes and therefore AccuCal can be reliably used to quantify any amplicon within this range.
To evaluate the performance of AccuCal-D in a variety of dye-based mastermixes on a number of real-time qPCR platforms, eight independent research groups were provided with AccuCal-D and reagents for lambda amplification (92 bp amplicon). Each laboratory amplified their GOIs and known input amounts of lambda under a range of conditions typical for those laboratories. The results show that AccuCal-D provides an accurate, absolute quantification of known concentrations of lambda DNA in these varied and independent tests (Fig.
When compared collectively across all platforms, the mean determined quantification correlates perfectly with the theoretical number of copies in each PCR (Fig., slope = 1). When integrated onto each qPCR run under the same conditions as the GOI(s), AccuCal provides robust absolute quantification over a range of input amounts and amplicon sizes, in dye- or probe-based assays. AccuCal provides confidence in relative quantification analysis Relative quantification e.g. ΔΔCq and Pfaffl analyses, has traditionally been the simplest and most commonly used method of PCR quantification. Although AccuCal provides absolute quantification, it can be applied relatively. To compare AccuCal-D with ΔΔCq and Pfaffl analyses, we assessed levels of CD40 and Interleukin 7 receptor alpha chain (IL7R) variants. Activation of human peripheral blood mononuclear cells (PBMCs) reveals a repertoire of splice variants of these genes which reflect a predisposition to multiple sclerosis ,.
We conducted experiments to measure levels of CD40 and IL7R in human PBMCs via qPCR following 24 h activation with varying amounts of phorbol myristate acetate (PMA) and ionomycin (PMA/I). Absolute quantification of the qPCR was performed using AccuCal-D and RealCount (Fig. And Additional file ). Relative quantification was assessed by expressing the absolute AccuCal-D values relative to the no PMA/ionomycin control, or by traditional ΔΔCq or Pfaffl analyses using glyceraldehyde 3-phosphate dehydrogenase ( GAPDH) as a reference gene and the unstimulated cells as a control (Fig. For Pfaffl analysis, the efficiencies calculated by RealCount were used. 3 Quantification of CD40, IL7R and GAPDH in PBMCs stimulated with 0–1x PMA/ionomycin. A Absolute quantification of CD40, IL7R and GAPDH in PBMCs stimulated with 0, 0.25x, 0.5x and 1x PMA/ionomycin (20 ng ml −1 PMA, 500 ng ml −1 ionomycin; PMA/I) by RealCount software following qPCR using AccuCal-D calibrators.
B Relative expression levels of CD40 and IL7R in PBMCs stimulated with 0, 0.25x, 0.5x and 1x PMA/ionomycin (20 ng ml −1 PMA, 500 ng ml −1 ionomycin). The hatched bars are relative expression levels determined by ΔΔCq using GAPDH as the reference gene and no PMA/ionomycin as the control sample, solid bars are relative expression levels determined by Pfaffl analysis, using GAPDH as reference gene, unstimulated cells as controls and individual efficiency values calculated by RealCount software, and the checkered bars are quantified by RealCount software following inclusion of AccuCal-D in the same PCR run, and expressed relative to the no PMA/ionomycin control. C Representative overlay graphs from flow cytometry showing relative measurement of CD40 and IL7R in the same population of PBMCs stimulated with 0 ( red), 0.25x ( blue), 0.5x ( green) and 1x PMA/ionomycin (20 ng ml −1 PMA, 500 ng ml −1 ionomycin; orange) as in ( a). Prostate epithelium-specific phosphatase and tensin homolog knockout (pePTENKO) induces prostate pathology and modifies prostate specific androgen receptor (AR) expression in mice as determined by immunohistochemistry (Fig.
And Additional file ) or Western blot (Fig. The Western analysis showed that levels of β-actin (ACTB) protein were constant and were used to determine relative protein expression levels. The AR protein content was significantly greater ( p = 0.008) in prostate tissue from pePTENKO mice compared to wild-type (WT; Fig. 4 Quantification of protein and mRNA levels of androgen receptor (AR, Ar) in mouse anterior prostate. A Representative immunohistochemistry showing AR protein expression (brown staining) and differential pathology in prostate of WT and pePTENKO mice.
B Quantification of AR protein by Western blot in anterior prostates of WT ( n = 2) and pePTENKO ( n = 4) mice, using β-actin (ACTB) as a loading control to determine relative protein levels. C Relative quantification of Ar by ΔΔCq and Pfaffl analyses using Actb as the reference gene and WT as the control.
![A-Z Of Quantitative Pcr Pdf Download A-Z Of Quantitative Pcr Pdf Download](http://ecx.images-amazon.com/images/I/71XuOWQ6l7L.jpg)
D qPCR of Ar and Actb in WT ( blue curves, n = 7 in duplicate) and pePTENKO ( red curves, n = 5 in duplicate) mice. E Comparison of theoretical versus determined quantification of serial dilutions of plasmids containing Ar or Actb amplicons, by either traditional standard curves ( blue diamonds and line) or use of AccuCal and RealCount ( red squares and line). F Absolute mRNA copy number quantification of Ar and Actb reference gene in the anterior prostate of WT ( n = 7) and pePTENKO ( n = 5) mice as determined by RT-qPCR with AccuCal calibrators and RealCount software (AC) or standard curves (Std).
G Absolute quantification of a number of reference genes using AccuCal and RealCount for both WT ( n = 7) and pePTENKO ( n = 5) mice. H Comparison of relative quantification methodologies for Ar. ΔΔCq and Pfaffl analyses used either Actb or Hmbs as the reference gene and WT as the control, and AccuCal (AC) and standard curve (Std) absolute values were expressed in a relative manner to WT as the control. All graphed data is displayed as mean ± SEM. Traditional relative and absolute methods of qPCR have many, well-accepted flaws and errors. The MIQE guidelines sought to minimize these, but the problems associated with reference genes, and the need to construct a standard curve for each GOI, remain.
To overcome these limitations, an accurate, universal calibrator (AccuCal) was developed. AccuCal can be included in any dye- (AccuCal-D) or probe-based (AccuCal-P) qPCR experiment. The technology works robustly for amplicons up to 500 bp in length over a dynamic range of ≥10 5 copies, and in a range of mastermixes, real-time PCR platforms and laboratories. A range of AccuCal concentrations is included in each qPCR run and used to generate a calibration curve to quantify the amount of any GOI. Significantly, AccuCal fluoresces proportionally to the amount of DNA in the well but is not PCR amplified, thus minimizing errors in quantification (e.g.
Due to errors in pipetting or spectrophotometric estimation of input nucleic acid concentrations). Customized software, RealCount, automates the quantification calculations, streamlining data analysis. Essential to current relative quantification methods are reference genes and the assumption that these do not change between treatments or groups.
Many studies have shown that commonly used reference genes vary with experimental conditions and between tissues, while some, such as Actb and GAPDH, have pseudogenes which may produce specific amplification products in an mRNA-independent fashion. The MIQE guidelines recommend the use of multiple reference genes to provide a more accurate normalization. However, in some experiments, this can be very difficult to achieve, as exemplified in our mouse prostate example. AccuCal provides quantification independently of reference genes and is therefore a much simpler method to use and is devoid of these problems. Reference genes are also often included in gene expression studies to account for differences in reverse transcription (RT) efficiencies between experiments. These have been shown to often result in relative gene differences of 2–5 fold or more depending upon the RNA concentration and integrity, the RT enzyme used, the priming strategy employed, the sample used and reaction conditions. RT differences have also been shown to be gene dependent which questions the validity of using any gene as a normalizer for RT and PCR and may mask results, leading to erroneous interpretation of data.
Methods that help resolve differences in RT efficiency are required, but in their absence, differences in gene expression. In summary, we have shown that AccuCal provides an easy alternative to traditional qPCR quantification methods. AccuCal removes the bias of troublesome reference genes and provides the accuracy of standard curves without the hassle. It can be used in every qPCR experiment to standardize dye- or probe-based assays. RealCount software automates the quantification process. The simplicity of AccuCal, its broad utility and the ability to quantify all GOIs on a PCR plate, make AccuCal a truly universal calibrator.
AccuCal calibrators AccuCal-D (Accugen) is a proprietary 90 bp, 44% GC content, double-stranded DNA calibrator that can be used to provide an accurate, absolute quantification in qPCR using intercalating dyes. AccuCal-P (Accugen) comprises a range of proprietary 21 bp, 62% GC content, single-stranded DNA calibrators that are labelled on the 5′ end by conventional means with any single fluorophore molecule per moiety and can be used for absolute quantification in probe-based qPCRs. In these experiments, AccuCal-P was labelled with FAM, but any fluorophore that matches the excitation and emission spectra of the fluorophore on the detection probe for the gene(s) of interest (GOIs) can be used. Multiple Accual-P calibrators labelled with different fluorophores can also be added simultaneously to the same well to enable multiplexing if desired. The methodology for using AccuCal-D and AccuCal-P, collectively referred to as AccuCal, is the same. Generating an AccuCal calibration curve We performed an initial calibration run on each qPCR platform using a range of dilutions of AccuCal-D or AccuCal-P as appropriate, from 0 ng up to 500 ng per well to determine the optimal range of AccuCal to use.
AccuCal was diluted in nuclease-free water (Sigma) and made up in the same PCR master mix, and to the same volume, as used during PCR, omitting primers and template. The calibrator, although not amplified, was subjected to PCR cycling under the conditions used for amplifying the GOIs, and the fluorescence data acquired at the end of each cycle as normal. We then determined the optimal range of AccuCal to use by importing the raw fluorescence data into RealCount software (Accugen), subtracting the background fluorescence reading, which is provided by the 0 ng AccuCal (comprising water and master mix only), and choosing those concentrations that produce a linear calibration curve within the detection limits of the platform in question. Typically, the ideal range is between 0 ng and 200 ng and should span the detectable exponential portion of the amplification curve between the take-off point and the second derivative maxima. At least six concentrations of AccuCal spanning the optimal range and including a 0 ng control is then used on every subsequent PCR, preferably in duplicate, to produce a calibration curve.
Quantification using AccuCal and RealCount Following qPCR amplification of the GOIs, and inclusion of the pre-determined range of AccuCal calibrators, the raw fluorescence data was imported into RealCount software and the calibration curve automatically plotted. The software calculates the efficiency of individual qPCR amplifications over the exponential portion of the amplification curve using a published algorithm.
From the calibration curve, we determined the pmols of DNA over the exponential portion of each amplification curve and calculated the mean initial input DNA using the equation pmz = pm/E n, where pmz is pmols at time zero, E is efficiency and n is cycle number. The pmz is converted into copies/PCR using pmz × 6.022 × 10 23 × 10 −12. The software provides a mean, standard deviation and standard error of the mean output for the quantification of the initial input amount of the gene(s) of interest in the qPCR reaction during the entire detectable exponential phase.
We undertook amplification of a ten-fold dilution series of lambda DNA ( Hind III digest, New England Biolabs), ranging from 4.5 × 10 6 – 4.5 × 10 1 and quantified using a NanoDrop 1000 spectrophotometer (Thermo Scientific), in Sso Fast EvaGreen Supermix (Bio-Rad) as per manufacturer’s instructions, in a 20 μl final volume. The expected amplicon size is 92 bp and the primer sequences are listed in Table. PCR cycling was performed at 95 °C, 2 min, followed by 40 cycles of 95 °C, 5 s; 60 °C, 30 s on a RotorGene-6000 (Qiagen), with the fluorescence acquired at the end of each cycle and the gain set to 7 in the green channel.
A melt curve performed at the end of the amplification was undertaken to confirm that there is only a single product amplified in each reaction.