Oral Presentation Australian Society for Microbiology Annual Scientific Meeting 2019

Identification and removal of contaminating microbial DNA from PCR reagents (#275)

Lisa F Stinson 1 , Jeff A Keelan 1 , Matthew S Payne 1
  1. Division of Obstetrics and Gynaecology, Faculty of Health & Medical Sciences, University of Western Australia, Perth, WA, Australia

Background: Over the past decade microbiome studies have increased in popularity, due to the increasingly user‐friendly workflows and affordability of 16S rRNA gene sequencing. However, in recent years, it has become apparent that many studies are plagued by entrenched methodological errors, resulting in the production of large amounts of erroneous data which have been spuriously interpreted. One of the major problems facing microbiome research is reagent-derived contamination, which can compromise the integrity of microbiome data, particularly in low-biomass samples.

Method: Using a commercially available dsDNase treatment protocol we have decontaminated our PCR master mix to assess the extent to which our DNA extraction kit and PCR master mix introduce contamination to bacterial DNA profiles generated by 16S rRNA gene sequencing. Four blank extraction controls (ECs; extracted in separate batches) and two blank PCR controls (NTCs) were processed with and without decontaminated PCR master mix. The resultant bacterial DNA levels/profiles were assessed by qPCR, endpoint PCR, and 16S rRNA gene sequencing.

Results: The vast majority of contamination in our workflow was derived from our PCR master mix. Decontaminated NTCs appeared to be true negatives upon qPCR and endpoint PCR screening. ECs amplified using decontaminated master mix appeared an average of 4.4 cycles later than those amplified without decontaminated master mix by qPCR, and were undetectable by endpoint PCR. Importantly, dsDNase treatment resulted in a 99% reduction in the number of contaminating bacterial sequence reads following Ion Torrent 16S rRNA gene sequencing.    

Conclusions: We have identified the PCR master mix as the primary source of contamination in our workflow, and shown that enzymatic removal of this contamination drastically reduced the blank signal and improved precision. Decontamination of PCR master mixes may have the potential to improve the sensitivity and accuracy of low‐biomass microbiome studies.