A.W.W. receives core research funding from the Scottish Government’s Rural and Environment Science and Analytical Services (RESAS) division. I thank Paul Scott, Wellcome Sanger Institute, for his title suggestions for this commentary.Peer reviewedPublisher PD

Walker, Alan W.

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A.W.W. receives core research funding from the Scottish Government’s Rural and Environment Science and Analytical Services (RESAS) division. I thank Paul Scott, Wellcome Sanger Institute, for his title suggestions for this commentary.Peer reviewe

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A Lot on Your Plate? Well-to-Well Contamination as anAdditional Confounder in Microbiome Sequence AnalysesAlan W. WalkeraaRowett Institute, University of Aberdeen, Aberdeen, United KingdomABSTRACT DNA sequence-based microbiome studies can be impacted by a rangeof different methodological artefacts. Contamination originating from laboratory kitsand reagents can lead to erroneous results, particularly in samples containing a lowmicrobial biomass. Minich and colleagues (mSystems 4:e00186-19, 2019, https://doi.org/10.1128/mSystems.00186-19) report on a different form of contamination,cross-contamination between samples that are processed together. They ﬁnd thattransfer of material between samples in 96-well plates is a common occurrence. TheDNA extraction step, particularly when carried out automatedly, is identiﬁed as themajor source of this contamination type. Well-to-well contamination distorts diver-sity measures, with low-biomass samples particularly affected. This report has impor-tant implications for attempts to decontaminate microbiome sequencing results. Ascontamination is derived from both external sources and crossover between sam-ples, it is not appropriate to simply remove sequence variants that are detected innegative-control blanks, and more-nuanced decontamination approaches may be re-quired.KEYWORDS contamination, microbiome, sequencingThe last 15 years have seen a rapid escalation in research on microbial communities,largely driven by the advent and widespread adoption of high-throughput se-quencing techniques (1, 2). These sequence-based methodologies have allowed us tocharacterize the microbial world at scales and depths that would have been unthink-able just a decade or so ago.While it has been an incredibly productive and exciting time for microbiomeresearch, some of the results generated using sequence-based approaches have beencontroversial and occasionally contradict conventional knowledge. Studies have “dis-covered” diverse microbial communities in environments that were previously consid-ered to be largely sterile or have associated unexpected microbes with environmentswhere it is difﬁcult to ﬁnd plausible explanations for their presence.It is important, therefore, to emphasize that, while incredibly powerful, DNA se-quencing approaches are fundamentally just techniques, and all techniques havebiases and limitations (3, 4). Indeed, there are well-described biases introduced duringsteps such as sample collection and storage, DNA extraction, template ampliﬁcation,and bioinformatics analyses, all of which have the potential to skew results andsubsequent interpretations (3, 5).A further potential problem with DNA sequence-based microbiome proﬁling meth-ods is contamination, as the laboratory kits and reagents that are used to processsamples for subsequent sequencing are not sterile. Contamination arising from thesesources was ﬁrst reported in the 1990s (6), and more recent work has demonstrated theimpact that these contaminants can have on modern microbiome proﬁling studies(7–12). The impact is particularly dramatic on samples containing a low biomass, as theCitationWalker AW. 2019. A lot on your plate?Well-to-well contamination as an additionalconfounder in microbiome sequence analyses.mSystems 4:e00362-19. https://doi.org/10.1128/mSystems.00362-19.Copyright © 2019 Walker. This is an open-access article distributed under the terms ofthe Creative Commons Attribution 4.0International license.Address correspondence toalan.walker@abdn.ac.uk.For the article discussed, see https://doi.org/10.1128/mSystems.00186-19.The views expressed in this article do notnecessarily reﬂect the views of the journal or ofASM.PublishedCOMMENTARYApplied and Environmental ScienceJuly/August 2019 Volume 4 Issue 4 e00362-19 msystems.asm.org 125 June 2019 on June 27, 2019 by guesthttp://msystems.asm.org/Downloaded from background level of contamination can effectively “swamp” any underlying real signalin these samples and therefore lead to erroneous conclusions (7).In addition to external sources of contamination, there can also be cross-contamination between samples within a given study. Certain steps in the process ofgenerating microbiome sequence data can involve numerous samples being processedsimultaneously, often in 96-well plates. Cross-contamination is a problem that has beenacknowledged by researchers working in the ﬁeld of microbiome research previously(12), but it remains underreported and largely unquantiﬁed.In a series of experiments, Minich et al. (13) investigated the potential extent ofwell-to-well contamination in sequence-based microbiome studies. Using 96-well plateformats, with either individual wells containing unique bacterial species or no-templatecontrol wells that had not been spiked with any bacteria, Minich and colleagues wereable to demonstrate that well-to-well contamination indeed occurs quite frequently.They found that individual samples were most commonly cross-contaminated by wellsin close vicinity, that highly abundant organisms were more likely to be transferred toother wells as contaminants than lower-abundance ones, and that by erroneouslyintroducing additional bacteria to samples, well-to-well contamination impacted mea-sures of diversity. They also found that low-biomass recipient samples were more likelyto be affected by this form of contamination than high-biomass ones. Furthermore,they demonstrated that transfer of material from well to well predominantly occurredduring the DNA extraction step, with samples that had been processed automatedlyusing robots showing a greater degree of well-to-well cross-contamination than thosethat had been processed manually.These results have particular relevance for decontamination of microbiome dataduring sequence analysis. One way to account for contamination is to simply removesequence types that are detected in negative controls, the reasoning being that anysequence type present in the negative control, which should of course have nosequences present as no template DNA was added, must be derived from an externalcontaminant. However, the work by Minich et al. nicely demonstrates that it is possiblefor erroneous reads to appear in negative-control samples that are not derived frombackground kit/reagent contamination. Rather, these are derived from other samplesthat are present on the same sequencing run, and so simply removing any sequencein a negative control risks removing species that are genuinely present in othersamples. Critically, since highly abundant organisms are most likely to be transferrederroneously to other wells, this sort of approach might remove dominant and poten-tially important members of a microbial community.Their ﬁndings also have relevance for those who wish to use microbiome data fordiagnostic purposes. There is signiﬁcant interest in using sequence proﬁling to identifymicrobial biomarkers for a broad range of different environmental and health concerns(14). The work of Minich and colleagues demonstrates that additional care may need tobe taken to ensure that biomarkers of interest that are detected in a given sample aretruly present and not just derived from well-to-well contamination.The study also highlights potential concerns with automation. As the costs ofsequencing have fallen, microbiome studies have steadily increased in size, with somenow incorporating many thousands of samples (2, 15). Clearly, the laboriousness andexpense of carrying out all the required processing steps manually make automatingparts of this process appealing. However, as the authors suggest, their results indicatethat for some critical samples, particularly those that contain low biomass, it may beprudent to consider processing these manually in order to reduce well-to-well con-tamination.Finally, although the authors provide many useful suggestions on how to mitigatethe impact of well-to-well contamination, their results serve as an additional reminderthat, where possible, there is still value in using non-sequence-based approaches tostudy microbial communities (16). As others have argued previously, results that havebeen veriﬁed and reproduced using multiple different methodologies are more likely tobe robust (17).CommentaryJuly/August 2019 Volume 4 Issue 4 e00362-19 msystems.asm.org 2 on June 27, 2019 by guesthttp://msystems.asm.org/Downloaded from Regardless, greater understanding of the problem of well-to-well contamination isa welcome development, which should help to guide improvements to microbiomesequencing protocols moving forward.ACKNOWLEDGMENTSA.W.W. receives core research funding from the Scottish Government’s Rural andEnvironment Science and Analytical Services (RESAS) division.I thank Paul Scott, Wellcome Sanger Institute, for his title suggestions for thiscommentary.REFERENCES1. Mullard A. 2008. Microbiology: the inside story. Nature 453:578–580.https://doi.org/10.1038/453578a.2. 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McDonald D, Hyde E, Debelius JW, Morton JT, Gonzalez A, Ackermann G,Aksenov AA, Behsaz B, Brennan C, Chen Y, DeRight Goldasich L, Dor-restein PC, Dunn RR, Fahimipour AK, Gaffney J, Gilbert JA, Gogul G,Green JL, Hugenholtz P, Humphrey G, Huttenhower C, Jackson MA,Janssen S, Jeste DV, Jiang L, Kelley ST, Knights D, Kosciolek T, Ladau J,Leach J, Marotz C, Meleshko D, Melnik AV, Metcalf JL, Mohimani H,Montassier E, Navas-Molina J, Nguyen TT, Peddada S, Pevzner P, PollardKS, Rahnavard G, Robbins-Pianka A, Sangwan N, Shorenstein J, Smarr L,Song SJ, Spector T, Swafford AD, Thackray VG, et al. 2018. American Gut:an open platform for citizen science microbiome research. mSystems3:e00031-18. https://doi.org/10.1128/mSystems.00031-18.16. Theis KR, Romero R, Winters AD, Greenberg JM, Gomez-Lopez N, Alhous-seini A, Bieda J, Maymon E, Pacora P, Fettweis JM, Buck GA, Jefferson KK,Strauss JF, Erez O, Hassan SS. 2019. Does the human placenta deliveredat term have a microbiota? Results of cultivation, quantitative real-timePCR, 16S rRNA gene sequencing, and metagenomics. Am J ObstetGynecol 220:267.e1–267.e39. https://doi.org/10.1016/j.ajog.2018.10.018.17. Munafò MR, Davey Smith G. 2018. Robust research needs many lines ofevidence. Nature 553:399–401. https://doi.org/10.1038/d41586-018-01023-3.CommentaryJuly/August 2019 Volume 4 Issue 4 e00362-19 msystems.asm.org 3 on June 27, 2019 by guesthttp://msystems.asm.org/Downloaded from 

A Lot on Your Plate? Well-to-Well Contamination as an Additional Confounder in Microbiome Sequence Analyses

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A Lot on Your Plate? Well-to-Well Contamination as an Additional Confounder in Microbiome Sequence Analyses

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