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Most probable number with visual based LAMP for the quantification of reductive dehalogenase genes in groundwater samples
, R.D. Stedtfeld, P.B. Hatzinger, S.A. Hashsham, A.M. Cupples
Published in Elsevier B.V.
PMID: 29031631
Volume: 143
Pages: 44 - 49
The remediation of chlorinated solvent contaminated sites frequently involves bioaugmentation with mixed cultures containing Dehalococcoides mccartyi. Their activity is then examined by quantifying reductive dehalogenase (RDase) genes. Recently, we described a rapid, low cost approach, based on loop mediated isothermal amplification (LAMP), which allowed for the visual detection of RDase genes from groundwater. In that study, samples were concentrated (without DNA extraction), incubated in a water bath (avoiding the use of a thermal cycler) and amplification was visualized by the addition of SYBR green (post incubation). Despite having a detection limit less than the threshold recommended for effective remediation, the application of the assay was limited because of the semi-quantitative nature of the data. Moreover, the assay was prone to false positives due to the aerosolization of amplicons. In this study, deoxyuridine triphosphate (dUTP) and uracil DNA glycosylase (UNG) were incorporated into the assay to reduce the probability of false positives. Optimization experiments revealed a UNG concentration of 0.2 units per reaction was adequate for degrading trace levels of AUGC based contamination (~ 1.4 × 104 gene copies/reaction) without significant changes to the detection limit (~ 100 gene copies/reaction). Additionally, the optimized assay was used with the most probable number (MPN) method to quantify RDase genes (vcrA and tceA) in multiple groundwater samples from a chlorinated solvent contaminated site. Using this approach, gene concentrations were significantly correlated to concentrations obtained using traditional methods (qPCR and DNA templates). Although the assay underestimated RDase genes concentrations, a strong correlation (R2 = 0.78 and 0.94) was observed between the two data sets. The regression equations obtained will be valuable to determine gene copies in groundwater using the newly developed, low cost and time saving method. © 2017 Elsevier B.V.
About the journal
JournalData powered by TypesetJournal of Microbiological Methods
PublisherData powered by TypesetElsevier B.V.