Accurate quantification of microorganisms in PCR-inhibiting environmental DNA extracts by a novel internal amplification control approach using Biotrove OpenArrays.

ABSTRACT: PCR-based detection assays are prone to inhibition by substances present in environmental samples, thereby potentially leading to inaccurate target quantification or false-negative results. Internal amplification controls (IACs) have been developed to help alleviate this problem but are generally applied in a single concentration, thereby yielding less-than-optimal results across the wide range of microbial gene target concentrations possible in environmental samples (J. Hoorfar, B. Malorny, A. Abdulmawjood, N. Cook, M. Wagner, and P. Fach, J. Clin. Microbiol. 42:1863-1868, 2004). Increasing the number of IACs for each quantitative PCR (qPCR) sample individually, however, typically reduces sensitivity and, more importantly, the reliability of quantification. Fortunately, current advances in high-throughput qPCR platforms offer the possibility of multiple reactions for a single sample simultaneously, thereby allowing the implementation of more than one IAC concentration per sample. Here, we describe the development of a novel IAC approach that is specifically designed for the state-of-the-art Biotrove OpenArray platform. Different IAC targets were applied at a range of concentrations, yielding a calibration IAC curve for each individual DNA sample. The developed IACs were optimized, tested, and validated by using more than 5,000 unique qPCR amplifications, allowing accurate quantification of microorganisms when applied to soil DNA extracts containing various levels of PCR-inhibiting compounds. To our knowledge, this is the first study using a suite of IACs at different target concentrations to monitor PCR inhibition across a wide target range, thereby allowing reliable and accurate quantification of microorganisms in PCR-inhibiting DNA extracts. The developed IAC is ideally suited for high-throughput screenings of, for example, ecological and agricultural samples on next-generation qPCR platforms.

SUBMITTER: van Doorn R 

PROVIDER: S-EPMC2786501 | biostudies-literature | 2009 Nov

REPOSITORIES: biostudies-literature