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      Identification and removal of contaminating microbial DNA from PCR reagents: impact on low-biomass microbiome analyses

      1 , 1 , 1
      Letters in Applied Microbiology
      Wiley

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          Abstract

          Reagent-derived contamination can compromise the integrity of microbiome data, particularly in low microbial biomass samples. This contamination has recently been attributed to the 'kitome' (contamination introduced by the DNA extraction kit), prior to which attention was mostly paid to potential contamination introduced by PCR reagents. In this study, we assessed the proportion to which our DNA extraction kit and PCR master mix introduce contaminating microbial DNA to bacterial microbial profiles generated by 16S rRNA gene sequencing. Utilizing a commercial dsDNase treatment protocol to decontaminate the PCR master mix, we demonstrated that the vast majority of contaminating DNA was derived from the PCR master mix. Importantly, this contamination was almost completely eliminated using the simple dsDNase treatment, resulting in a 99% reduction in contaminating bacterial reads. We suggest that dsDNase treatment of PCR reagents should be explored as a simple and effective way of reducing contamination in low-biomass microbiome studies and producing more robust and reliable data. SIGNIFICANCE AND IMPACT OF THE STUDY: Reagent contamination with microbial DNA is a major problem in microbiome studies of low microbial biomass samples. Levels of such contaminating DNA often outweigh what is present in the sample and heavily confound subsequent data analysis. Previous studies have suggested this contamination is primarily derived from DNA extraction kits. Here, we identified the PCR master mix as the primary source of contamination, and showed that enzymatic removal of the 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.

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          Inherent bacterial DNA contamination of extraction and sequencing reagents may affect interpretation of microbiota in low bacterial biomass samples

          Background The advent and use of highly sensitive molecular biology techniques to explore the microbiota and microbiome in environmental and tissue samples have detected the presence of contaminating microbial DNA within reagents. These microbial DNA contaminants may distort taxonomic distributions and relative frequencies in microbial datasets, as well as contribute to erroneous interpretations and identifications. Results We herein report on the occurrence of bacterial DNA contamination within commonly used DNA extraction kits and PCR reagents and the effect of these contaminates on data interpretation. When compared to previous reports, we identified an additional 88 bacterial genera as potential contaminants of molecular biology grade reagents, bringing the total number of known contaminating microbes to 181 genera. Many of the contaminants detected are considered normal inhabitants of the human gastrointestinal tract and the environment and are often indistinguishable from those genuinely present in the sample. Conclusions Laboratories working on bacterial populations need to define contaminants present in all extraction kits and reagents used in the processing of DNA. Any unusual and/or unexpected findings need to be viewed as possible contamination as opposed to unique findings. Electronic supplementary material The online version of this article (doi:10.1186/s13099-016-0103-7) contains supplementary material, which is available to authorized users.
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            Optimizing methods and dodging pitfalls in microbiome research

            Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors. Electronic supplementary material The online version of this article (doi:10.1186/s40168-017-0267-5) contains supplementary material, which is available to authorized users.
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              Recognizing the reagent microbiome

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                Author and article information

                Journal
                Letters in Applied Microbiology
                Lett Appl Microbiol
                Wiley
                02668254
                November 23 2018
                Affiliations
                [1 ]Division of Obstetrics and Gynaecology; Faculty of Health & Medical Sciences; The University of Western Australia; Perth WA Australia
                Article
                10.1111/lam.13091
                30383890
                92aa4b7e-f67e-4ac7-8a17-83c650564074
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://onlinelibrary.wiley.com/termsAndConditions#vor

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