Accurate Digital Polymerase Chain Reaction Quantification of Challenging Samples Applying Inhibitor-Tolerant DNA Polymerases
(2017) In Analytical Chemistry 89(3). p.1642-1649- Abstract
Digital PCR (dPCR) enables absolute quantification of nucleic acids by partitioning of the sample into hundreds or thousands of minute reactions. By assuming a Poisson distribution for the number of DNA fragments present in each chamber, the DNA concentration is determined without the need for a standard curve. However, when analyzing nucleic acids from complex matrixes such as soil and blood, the dPCR quantification can be biased due to the presence of inhibitory compounds. In this study, we evaluated the impact of varying the DNA polymerase in chamber-based dPCR for both pure and impure samples using the common PCR inhibitor humic acid (HA) as a model. We compared the TaqMan Universal PCR Master Mix with two alternative DNA... (More)
Digital PCR (dPCR) enables absolute quantification of nucleic acids by partitioning of the sample into hundreds or thousands of minute reactions. By assuming a Poisson distribution for the number of DNA fragments present in each chamber, the DNA concentration is determined without the need for a standard curve. However, when analyzing nucleic acids from complex matrixes such as soil and blood, the dPCR quantification can be biased due to the presence of inhibitory compounds. In this study, we evaluated the impact of varying the DNA polymerase in chamber-based dPCR for both pure and impure samples using the common PCR inhibitor humic acid (HA) as a model. We compared the TaqMan Universal PCR Master Mix with two alternative DNA polymerases: ExTaq HS and Immolase. By using Bayesian modeling, we show that there is no difference among the tested DNA polymerases in terms of accuracy of absolute quantification for pure template samples, i.e., without HA present. For samples containing HA, there were great differences in performance: the TaqMan Universal PCR Master Mix failed to correctly quantify DNA with more than 13 pg/nL HA, whereas Immolase (1 U) could handle up to 375 pg/nL HA. Furthermore, we found that BSA had a moderate positive effect for the TaqMan Universal PCR Master Mix, enabling accurate quantification for 25 pg/nL HA. Increasing the amount of DNA polymerase from 1 to 5 U had a strong effect for ExTaq HS, elevating HA-tolerance four times. We also show that the average Cq values of positive reactions may be used as a measure of inhibition effects, e.g., to determine whether or not a dPCR quantification result is reliable. The statistical models developed to objectively analyze the data may also be applied in quality control. We conclude that the choice of DNA polymerase in dPCR is crucial for the accuracy of quantification when analyzing challenging samples.
(Less)
- author
- Sidstedt, Maja LU ; Romsos, Erica L ; Hedell, Ronny ; Ansell, Ricky ; Steffen, Carolyn R ; Vallone, Peter M ; Rådström, Peter LU and Hedman, Johannes LU
- organization
- publishing date
- 2017-02-07
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Journal Article
- in
- Analytical Chemistry
- volume
- 89
- issue
- 3
- pages
- 8 pages
- publisher
- The American Chemical Society (ACS)
- external identifiers
-
- scopus:85023766201
- wos:000393738300035
- pmid:28118703
- ISSN
- 1520-6882
- DOI
- 10.1021/acs.analchem.6b03746
- language
- English
- LU publication?
- yes
- id
- 92956524-0f2f-4150-adf0-d8aa4931aec3
- date added to LUP
- 2017-08-22 12:00:11
- date last changed
- 2024-04-14 16:09:41
@article{92956524-0f2f-4150-adf0-d8aa4931aec3,
abstract = {{<p>Digital PCR (dPCR) enables absolute quantification of nucleic acids by partitioning of the sample into hundreds or thousands of minute reactions. By assuming a Poisson distribution for the number of DNA fragments present in each chamber, the DNA concentration is determined without the need for a standard curve. However, when analyzing nucleic acids from complex matrixes such as soil and blood, the dPCR quantification can be biased due to the presence of inhibitory compounds. In this study, we evaluated the impact of varying the DNA polymerase in chamber-based dPCR for both pure and impure samples using the common PCR inhibitor humic acid (HA) as a model. We compared the TaqMan Universal PCR Master Mix with two alternative DNA polymerases: ExTaq HS and Immolase. By using Bayesian modeling, we show that there is no difference among the tested DNA polymerases in terms of accuracy of absolute quantification for pure template samples, i.e., without HA present. For samples containing HA, there were great differences in performance: the TaqMan Universal PCR Master Mix failed to correctly quantify DNA with more than 13 pg/nL HA, whereas Immolase (1 U) could handle up to 375 pg/nL HA. Furthermore, we found that BSA had a moderate positive effect for the TaqMan Universal PCR Master Mix, enabling accurate quantification for 25 pg/nL HA. Increasing the amount of DNA polymerase from 1 to 5 U had a strong effect for ExTaq HS, elevating HA-tolerance four times. We also show that the average Cq values of positive reactions may be used as a measure of inhibition effects, e.g., to determine whether or not a dPCR quantification result is reliable. The statistical models developed to objectively analyze the data may also be applied in quality control. We conclude that the choice of DNA polymerase in dPCR is crucial for the accuracy of quantification when analyzing challenging samples.</p>}},
author = {{Sidstedt, Maja and Romsos, Erica L and Hedell, Ronny and Ansell, Ricky and Steffen, Carolyn R and Vallone, Peter M and Rådström, Peter and Hedman, Johannes}},
issn = {{1520-6882}},
keywords = {{Journal Article}},
language = {{eng}},
month = {{02}},
number = {{3}},
pages = {{1642--1649}},
publisher = {{The American Chemical Society (ACS)}},
series = {{Analytical Chemistry}},
title = {{Accurate Digital Polymerase Chain Reaction Quantification of Challenging Samples Applying Inhibitor-Tolerant DNA Polymerases}},
url = {{http://dx.doi.org/10.1021/acs.analchem.6b03746}},
doi = {{10.1021/acs.analchem.6b03746}},
volume = {{89}},
year = {{2017}},
}