Identifying personal microbiomes using metagenomic codes

Abstract

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. forensic genetics | microbial ecology | metagenomics | human microbiome | strain variation R ecent large-scale investigations of the human microbiome have revealed great variability in the body site-specific community structure and function of microbial organisms across healthy individuals (1, 2). In addition, it has been shown that features of the human microbiome might stably associate with individuals over substantial periods of time (3-5). These observations suggest that individuals might be uniquely and stably identified within a population based on their resident microbiota. However, to date there have been no rigorous efforts to quantitatively establish the feasibility of microbiome-based identifiability. To do so requires demonstrating (i) that one can identify a "metagenomic code" that is specific to an individual in a sample population; (ii) that the code can be robustly redetected at a later time; (iii) that the code is unlikely to erroneously match a previously unseen sample; and (iv) that such codes can be constructed for a sizeable fraction of individuals (Fig.

Integrated multi-omics of the human gut microbiome in a case study of familial type 1 diabetes

“…The unused single-end reads were combined with the unmapped reads and cd-hit-dup from the CD-HIT software suite 63 was used to remove duplicate reads. Velvet was then run over a range of k-mer sizes (27,31,35,39,43,47,51,55,59,63) with the IDBA-UD contigs as long read input (velveth parameters: -long contig.fa, velvetg parameter: -conserveLong yes). Afterwards, all newly assembled contig sequences from the different k-mer runs and the original IDBA-UD contigs were concatenated and clustered using cd-hit from the CD-HIT software suite (parameter: -c 0.99) to remove redundancy.…”

“…The microbial consortia of the gut are known to be among the most stable human-associated microbial communities 2 , and sample donors remain identifiable from these based on metagenomic data when compared to data sets from earlier samples 39 . We investigated whether the patterns of individuality are also discernible on the other omic levels.…”

Personal microbiomes and next-generation sequencing for laboratory-based education

“…We obtained IRB approval for both the use of student microbiome samples and the students' participation in educational research. We note that while human microbiome data are often not considered to be specific to a person, recent publications have demonstrated that microbiomes may be used to uniquely identify individuals (Franzosa et al 2015;.…”

Microbiomes raise privacy concerns

“…The finding 1 , published in Proceedings of the National Academy of Sciences on 11 May, suggests that it might be possible to identify a participant in an anonymous study of the body's microbial denizens -its microbiome -and to reveal details about that person's health, diet or ethnicity. A publicly available trove of microbiome DNA maintained by the US National Institutes of Health (NIH), meanwhile, already contains potentially identifiable human DNA, according to a study 2 published in Genome Research on 29 April.…”

“…"Right now, it's a little bit of a Wild West as far as microbiome data management goes," says Curtis Huttenhower, a computational biologist at the Harvard T. H. Chan School of Public Health in Boston, Massachusetts, who led the latest study 1 . "As the field develops, we need to make sure there's a realization that our microbiomes are highly unique.…”