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Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

ABSTRACT: 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.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.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.

SUBMITTER: Salter SJ

PROVIDER: S-EPMC4228153 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

Salter Susannah J SJ Cox Michael J MJ Turek Elena M EM Calus Szymon T ST Cookson William O WO Moffatt Miriam F MF Turner Paul P Parkhill Julian J Loman Nicholas J NJ Walker Alan W AW

BMC biology 20141112

<h4>Background</h4>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.<h4>Results</h4>In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laborato ...[more]

PMID: 25387460

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Project description:In low-microbial biomass samples such as bovine milk, contaminants can outnumber endogenous bacteria. Because of this, milk microbiome research suffers from a critical knowledge gap, namely, does non-mastitis bovine milk contain a native microbiome? In this study, we sampled external and internal mammary epithelia and stripped and cisternal milk and used numerous negative controls, including air and sampling controls and extraction and library preparation blanks, to identify the potential sources of contamination. Two algorithms were used to mathematically remove contaminants and track the potential movement of microbes among samples. Results suggest that the majority (i.e., >75%) of sequence data generated from bovine milk and mammary epithelium samples represents contaminating DNA. Contaminants in milk samples were primarily sourced from DNA extraction kits and the internal and external skin of the teat, while teat canal and apex samples were mainly contaminated during the sampling process. After decontamination, the milk microbiome displayed a more dispersed, less diverse, and compositionally distinct bacterial profile compared with epithelial samples. Similar microbial compositions were observed between cisternal and stripped milk samples, as well as between teat apex and canal samples. Staphylococcus and Acinetobacter were the predominant genera detected in milk sample sequences, and bacterial culture showed growth of Staphylococcus and Corynebacterium spp. in 50% (7/14) of stripped milk samples and growth of Staphylococcus spp. in 7% (1/14) of cisternal milk samples. Our study suggests that microbiome data generated from milk samples obtained from clinically healthy bovine udders may be heavily biased by contaminants that enter the sample during sample collection and processing workflows.IMPORTANCEObtaining a non-contaminated sample of bovine milk is challenging due to the nature of the sampling environment and the route by which milk is typically extracted from the mammary gland. Furthermore, the very low bacterial biomass of bovine milk exacerbates the impacts of contaminant sequences in downstream analyses, which can lead to severe biases. Our finding showed that bovine milk contains very low bacterial biomass and each contamination event (including sampling procedure and DNA extraction process) introduces bacteria and/or DNA fragments that easily outnumber the native bacterial cells. This finding has important implications for our ability to draw robust conclusions from milk microbiome data, especially if the data have not been subjected to rigorous decontamination procedures. Based on these findings, we strongly urge researchers to include numerous negative controls into their sampling and sample processing workflows and to utilize several complementary methods for identifying potential contaminants within the resulting sequence data. These measures will improve the accuracy, reliability, reproducibility, and interpretability of milk microbiome data and research.

Project description:BACKGROUND:Xenotropic murine leukaemia viruses (MLV-X) are endogenous gammaretroviruses that infect cells from many species, including humans. Xenotropic murine leukaemia virus-related virus (XMRV) is a retrovirus that has been the subject of intense debate since its detection in samples from humans with prostate cancer (PC) and chronic fatigue syndrome (CFS). Controversy has arisen from the failure of some studies to detect XMRV in PC or CFS patients and from inconsistent detection of XMRV in healthy controls. RESULTS:Here we demonstrate that Taqman PCR primers previously described as XMRV-specific can amplify common murine endogenous viral sequences from mouse suggesting that mouse DNA can contaminate patient samples and confound specific XMRV detection. To consider the provenance of XMRV we sequenced XMRV from the cell line 22Rv1, which is infected with an MLV-X that is indistinguishable from patient derived XMRV. Bayesian phylogenies clearly show that XMRV sequences reportedly derived from unlinked patients form a monophyletic clade with interspersed 22Rv1 clones (posterior probability >0.99). The cell line-derived sequences are ancestral to the patient-derived sequences (posterior probability >0.99). Furthermore, pol sequences apparently amplified from PC patient material (VP29 and VP184) are recombinants of XMRV and Moloney MLV (MoMLV) a virus with an envelope that lacks tropism for human cells. Considering the diversity of XMRV we show that the mean pairwise genetic distance among env and pol 22Rv1-derived sequences exceeds that of patient-associated sequences (Wilcoxon rank sum test: p = 0.005 and p < 0.001 for pol and env, respectively). Thus XMRV sequences acquire diversity in a cell line but not in patient samples. These observations are difficult to reconcile with the hypothesis that published XMRV sequences are related by a process of infectious transmission. CONCLUSIONS:We provide several independent lines of evidence that XMRV detected by sensitive PCR methods in patient samples is the likely result of PCR contamination with mouse DNA and that the described clones of XMRV arose from the tumour cell line 22Rv1, which was probably infected with XMRV during xenografting in mice. We propose that XMRV might not be a genuine human pathogen.

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Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

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Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

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