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

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.

Spatiotemporal Stability of an Ammonia-Oxidizing Community in a Nitrogen-Saturated Forest Soil.

Elevated levels of nitrogen input into various terrestrial environments in recent decades have led to increases in soil nitrate production and leaching. However, nitrifying potential and nitrifying activity tend to be highly variable over space and time, making broad-scale estimates of nitrate production difficult. This study investigates whether the high spatiotemporal variation in nitrate production might be explained by differences in the structure of ammonia-oxidizing bacterial communities in nitrogen-saturated coniferous forest soils. The diversity of ammonia-oxidizing bacteria of the b-subgroup Proteobacteria was therefore investigated using two different PCR-based approaches. The first targeted the 16S rRNA gene and involved temporal temperature gradient electrophoresis (TTGE) of specifically amplified PCR products, with subsequent band excision and nucleotide sequence determination. The second approach involved the cloning and sequencing of PCR-amplified amoA gene fragments. All recovered 16S rDNA sequences were closely related to the culture strain Nitrosospira sp. AHB1, which was isolated from an acid soil and is affiliated with Nitrosospira cluster 2, a sequence group previously shown to be associated with acid environments. All amoA-like sequences also showed a close affinity with this acid-tolerant Nitrosospira strain, although greater sequence variation could be detected in the amoA analysis. The ammonia-oxidizing bacterial community in the nitrogen-saturated coniferous forest soil was determined to be very stable, showing little variation between different organic layers and throughout the year, despite large differences in the total Bacterial community structure as determined by 16S rDNA DGGE community fingerprinting. These results suggest that environmental heterogeneity affecting ammonia oxidizer numbers and activity, and not ammonia oxidizer community structure, is chiefly responsible for spatial and temporal variation in nitrate production in these acid forest soils.