Quantification of Bias Related to the Extraction of DNA Directly from Soils

Abstract

In recent years, several protocols based on the extraction of nucleic acids directly from the soil matrix after lysis treatment have been developed for the detection of microorganisms in soil. Extraction efficiency has often been evaluated based on the recovery of a specific gene sequence from an organism inoculated into the soil. The aim of the present investigation was to improve the extraction, purification, and quantification of DNA derived from as large a portion of the soil microbial community as possible, with special emphasis placed on obtaining DNA from gram-positive bacteria, which form structures that are difficult to disrupt. Furthermore, we wanted to identify and minimize the biases related to each step in the procedure. Six soils, covering a range of pHs, clay contents, and organic matter contents, were studied. Lysis was carried out by soil grinding, sonication, thermal shocks, and chemical treatments. DNA was extracted from the indigenous microflora as well as from inoculated bacterial cells, spores, and hyphae, and the quality and quantity of the DNA were determined by gel electrophoresis and dot blot hybridization. Lysis efficiency was also estimated by microscopy and viable cell counts. Grinding increased the extracellular DNA yield compared with the yield obtained without any lysis treatment, but none of the subsequent treatments clearly increased the DNA yield. Phage λ DNA was inoculated into the soils to mimic the fate of extracellular DNA. No more than 6% of this DNA could be recovered from the different soils. The clay content strongly influenced the recovery of DNA. The adsorption of DNA to clay particles decreased when the soil was pretreated with RNA in order to saturate the adsorption sites. We also investigated different purification techniques and optimized the PCR methods in order to develop a protocol based on hybridization of the PCR products and quantification by phosphorimaging.

Quantitative, longitudinal profiling of the primate fecal microbiota reveals idiosyncratic, dynamic communities

“…0 0 5 1 0 0 0 1 0 0 5 0 EFM129 UNIV8 UNIV338 UNIV533 UNIV1392 EFS127 BIF164 ECO446 CC482/EREC482 LAA1023/LAA1023R BAC1195 LB158 BAC303 UNIV1369 UNIV1492 UNIV357 100 bp of feces, we employed qPCR. Quantitative PCR is the current replacement for slot blots in direct quantification of target genes in complex microbial mixtures, although it is not without biases inherent in any amplification method (Suzuki and Giovannoni, 1996;von Wintzingerode et al ., 1997;Polz and Cavanaugh, 1998;Suzuki et al ., 1998;Frostegard et al ., 1999;Crosby and Criddle, 2003). Cost considerations limited our use of qPCR to monoplex detection with SyberGreen for the two dominant groups, C. coccoides-E. rectale ( CcEr ) group and Lactobacillus; their abundance assured that for most specimens in all animals quantification would not be compromised by low target concentrations.…”

Sampling strategy in molecular microbial ecology: influence of soil sample size on DNA fingerprinting analysis of fungal and bacterial communities

“…1). These DNA yields were in the same order of magnitude of those classically obtained in different soil environments with various protocols (Zhou et al ., 1996;Kuske et al ., 1998;Frostegard et al ., 1999). For Auxonne and Châteaurenard soils, DNA yields were positively correlated with the size of the samples (R of 0.90 and 0.88, respectively), this trend being more marked for samples > 1 g. This observation could be related to a technical bias limiting DNA recovery in samples smaller than 1 g such as a lower lysis efficiency.…”

Isolation, characterization and comparison of bacteria from swine faeces and manure storage pits

“…The application of non-cultivation based methods of examination of microbial communities; for example, PCR amplification of rRNA genes and sequence based identification of resident microorganisms, offers an attractive alternative to overcome these limitations. However, these methods do not come without their own limitations including: PCR bias, amplification of genes from dead organisms, and variation in the number of rRNA genes with species (Gobel, 1995;Wilson, 1997;Olive and Bean, 1999;Frostegard et al ., 1999). Furthermore, though much can be learned about the diversity of microorganisms present from the analysis of clone libraries, this sort of analysis tells us little about the phenotype of the organisms present.…”