Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

February 10, 2015

Biological Dirty Data

Filed under: Bioinformatics — Patrick Durusau @ 10:46 am

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses by Susannah J Salter, et al. (BMC Biology 2014, 12:87 doi:10.1186/s12915-014-0087-z)

Abstract:

Background

The study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents.

Results

In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination.

Conclusions

These results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised.

I first saw this in a tweet by Nick Loman, asking

what’s the point in publishing stuff like biomedcentral.com/1741-7007/12/87 if no-ones gonna act on it

I’m not sure what Nick’s criteria is for “no-ones gonna act on it,” but perhaps softly saying results could be better with better control for contamination isn’t a stark enough statement of the issue. Try:

Reagent and Laboratory Contamination – Garbage In, Garbage Out

Uncontrolled and/or unaccounted for contamination is certainly garbage in and results that contain uncontrolled and/or unaccounted for contamination fits my notion of garbage out.

Phrased as the choice between producing garbage and producing quality research frames the issue in such a way as to produce an impetus for change. Yes?

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