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COMPARATIVE ANALYSIS OF METHODS FOR THE PURIFICATION OF DNA FROM LOW-BIOMASS SAMPLES BASED ON TOTAL YIELD AND CONSERVED MICROBIAL DIVERSITY
Authors:MYRON T LA DUC  SHARIFF OSMAN  KASTHURI VENKATESWARAN
Institution:Jet Propulsion Laboratory
California Institute of Technology
Pasadena, CA 91109
Abstract:Despite advances in the specificity and sensitivity of molecular biological technologies, the efficient recovery of DNA from low-biomass samples remains extremely challenging. Optimal methods to purify biomolecules from such environments should (1) achieve the greatest total yield and (2) reflect the true microbial diversity of the sample. These attributes were assessed from five DNA purification regimes: a standard-manual procedure, MoBio Ultraclean and Promega Wizard kits, and an automated Axcyte AutoLyser method with and without bead-beating agitation. A homogenous mixture of known concentrations of nine distinct bacterial lineages isolated from low-biomass environments was prepared and suitable aliquots of subsamples were processed in parallel. DNA products from each of these methods were then subjected to polymerase chain reaction (PCR), quantitative PCR and 16S rRNA clone-library analysis. The Axcyte AutoLyser outperformed all other purification regimes examined. This automated method consistently both yielded the highest concentration of PCR-amplifiable DNA, and reported species composition most consistent with the starting solution.

PRACTICAL APPLICATIONS


This communication carefully examines the effectiveness of common DNA purification regimes as well as an automated method. Comparative analyses convincingly demonstrate that the different methods not only result in different recovery of genomic DNA, but more importantly, different estimations of microbial diversity in the sample. This report will hopefully inspire investigators from various industries (pharmaceutical, ecological, medical, semiconductor, etc.) who find themselves in the initial phases of large-scale studies to devote a significant effort into optimizing sample extraction protocols to achieve the most accurate information.
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