35
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Microbiota fingerprints lose individually identifying features over time

      research-article
      , ,
      Microbiome
      BioMed Central
      Built environment, Microbiota, Skin microbiota, Forensics

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Humans host individually unique skin microbiota, suggesting that microbiota traces transferred from skin to surfaces could serve as forensic markers analogous to fingerprints. While it is known that individuals leave identifiable microbiota traces on surfaces, it is not clear for how long these traces persist. Moreover, as skin and surface microbiota change with time, even persistent traces may lose their forensic potential as they would cease to resemble the microbiota of the person who left them. We followed skin and surface microbiota within households for four seasons to determine whether accurate microbiota-based matching of individuals to their households could be achieved across long time delays.

          Results

          While household surface microbiota traces could be matched to the correct occupant or occupants with 67% accuracy, accuracy decreased substantially when skin and surface samples were collected in different seasons, and particularly when surface samples were collected long after skin samples. Most OTUs persisted on skin or surfaces for less than one season, indicating that OTU loss was the major cause of decreased matching accuracy. OTUs that were more useful for individual identification persisted for less time and were less likely to be deposited from skin to surface, suggesting a trade-off between the longevity and identifying value of microbiota traces.

          Conclusions

          While microbiota traces have potential forensic value, unlike fingerprints they are not static and may degrade in a way that preferentially erases features useful in identifying individuals.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s40168-016-0209-7) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references11

          • Record: found
          • Abstract: found
          • Article: not found

          Identifying personal microbiomes using metagenomic codes.

          Community composition within the human microbiome varies across individuals, but it remains unknown if this variation is sufficient to uniquely identify individuals within large populations or stable enough to identify them over time. We investigated this by developing a hitting set-based coding algorithm and applying it to the Human Microbiome Project population. Our approach defined body site-specific metagenomic codes: sets of microbial taxa or genes prioritized to uniquely and stably identify individuals. Codes capturing strain variation in clade-specific marker genes were able to distinguish among 100s of individuals at an initial sampling time point. In comparisons with follow-up samples collected 30-300 d later, ∼30% of individuals could still be uniquely pinpointed using metagenomic codes from a typical body site; coincidental (false positive) matches were rare. Codes based on the gut microbiome were exceptionally stable and pinpointed >80% of individuals. The failure of a code to match its owner at a later time point was largely explained by the loss of specific microbial strains (at current limits of detection) and was only weakly associated with the length of the sampling interval. In addition to highlighting patterns of temporal variation in the ecology of the human microbiome, this work demonstrates the feasibility of microbiome-based identifiability-a result with important ethical implications for microbiome study design. The datasets and code used in this work are available for download from huttenhower.sph.harvard.edu/idability.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            PrimerProspector: de novo design and taxonomic analysis of barcoded polymerase chain reaction primers

            Motivation: PCR amplification of DNA is a key preliminary step in many applications of high-throughput sequencing technologies, yet design of novel barcoded primers and taxonomic analysis of novel or existing primers remains a challenging task. Results: PrimerProspector is an open-source software package that allows researchers to develop new primers from collections of sequences and to evaluate existing primers in the context of taxonomic data. Availability: PrimerProspector is open-source software available at http://pprospector.sourceforge.net Contact: rob.knight@colorado.edu Supplementary information: Supplementary data are available at Bioinformatics online.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              VizBin - an application for reference-independent visualization and human-augmented binning of metagenomic data

              Background Metagenomics is limited in its ability to link distinct microbial populations to genetic potential due to a current lack of representative isolate genome sequences. Reference-independent approaches, which exploit for example inherent genomic signatures for the clustering of metagenomic fragments (binning), offer the prospect to resolve and reconstruct population-level genomic complements without the need for prior knowledge. Results We present VizBin, a Java™-based application which offers efficient and intuitive reference-independent visualization of metagenomic datasets from single samples for subsequent human-in-the-loop inspection and binning. The method is based on nonlinear dimension reduction of genomic signatures and exploits the superior pattern recognition capabilities of the human eye-brain system for cluster identification and delineation. We demonstrate the general applicability of VizBin for the analysis of metagenomic sequence data by presenting results from two cellulolytic microbial communities and one human-borne microbial consortium. The superior performance of our application compared to other analogous metagenomic visualization and binning methods is also presented. Conclusions VizBin can be applied de novo for the visualization and subsequent binning of metagenomic datasets from single samples, and it can be used for the post hoc inspection and refinement of automatically generated bins. Due to its computational efficiency, it can be run on common desktop machines and enables the analysis of complex metagenomic datasets in a matter of minutes. The software implementation is available at https://claczny.github.io/VizBin under the BSD License (four-clause) and runs under Microsoft Windows™, Apple Mac OS X™ (10.7 to 10.10), and Linux. Electronic supplementary material The online version of this article (doi:10.1186/s40168-014-0066-1) contains supplementary material, which is available to authorized users.
                Bookmark

                Author and article information

                Contributors
                david@wilkox.org
                mhyleung@cityu.edu.hk
                (852) 3442 4625 , patrick.kh.lee@cityu.edu.hk
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                9 January 2017
                9 January 2017
                2017
                : 5
                : 1
                Affiliations
                School of Energy and Environment, City University of Hong Kong, B5423-AC1, Tat Chee Avenue, Kowloon, Hong Kong, Special Administrative Region of China
                Article
                209
                10.1186/s40168-016-0209-7
                5234115
                28086968
                271bce38-0850-4b70-9483-8e99171bad32
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 May 2016
                : 22 November 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002920, Research Grants Council, University Grants Committee;
                Award ID: 11211815
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                built environment,microbiota,skin microbiota,forensics
                built environment, microbiota, skin microbiota, forensics

                Comments

                Comment on this article