Accurate Digital Polymerase Chain Reaction Quantification of Challenging Samples Applying Inhibitor-Tolerant DNA Polymerases

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

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 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.

Detaljer

Författare
Enheter & grupper
Externa organisationer
  • Linköping University
  • Göteborgs universitet
  • Chalmers University of Technology
  • National Institute of Standards and Technology (NIST)
  • Swedish National Forensic Center
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Analytisk kemi

Nyckelord

Originalspråkengelska
Sidor (från-till)1642-1649
Antal sidor8
TidskriftAnalytical Chemistry
Volym89
Utgivningsnummer3
StatusPublished - 2017 feb 7
PublikationskategoriForskning
Peer review utfördJa

Relaterad forskningsoutput

Maja Sidstedt, 2019 maj 24, Lund University, Division of Applied Microbiology: Department of Chemistry, Lund University. 172 s.

Forskningsoutput: AvhandlingDoktorsavhandling (sammanläggning)

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