A new study shows that the microbial communities we
carry in and on our bodies—known as the human
microbiome—have the potential to uniquely identify
individuals, much like a fingerprint. Harvard T.H.
Chan School of Public Health researchers and
colleagues demonstrated that personal microbiome
contain enough distinguishing features to identify
an individual over time from among a research study
population of hundreds of people.
The study, the first to rigorously show that
identifying people from microbiome data is feasible,
suggests that we have surprisingly unique microbial
inhabitants, but could raise potential privacy
concerns for subjects enrolled in human microbiome
research projects. The study appears online May 11,
2015 in the journal PNAS..
Taken together, DNA sequences from four microbial
species distinguish the starred person's microbiome
from the microbiomes of five other people - Image:
Eric Franzosa
“Linking a human DNA sample to a database of human
DNA ‘fingerprints’ is the basis for forensic
genetics, which is now a decades-old field. We’ve
shown that the same sort of linking is possible
using DNA sequences from microbes inhabiting the
human body—no human DNA required.
This opens the door to connecting human microbiome
samples between databases, which has the potential
to expose sensitive subject information—for example,
a sexually-transmitted infection, detectable from
the microbiome sample itself,” said lead author Eric
Franzosa, research fellow in the Department of
Biostatistics at Harvard Chan.
Franzosa and colleagues used publicly available
microbiome data produced through the Human
Microbiome Project (HMP), which surveyed microbes in
the stool, saliva, skin, and other body sites from
up to 242 individuals over a months-long period.
The authors adapted a classical computer science
algorithm to combine stable and distinguishing
sequence features from individuals’ initial
microbiome samples into individual-specific “codes.”
They then compared the codes to microbiome samples
collected from the same individuals’ at follow-up
visits and to samples from independent groups of
individuals.
The results showed that the codes were unique among
hundreds of individuals, and that a large fraction
of individuals’ microbial “fingerprints” remained
stable over a one-year sampling period. The codes
constructed from gut samples were particularly
stable, with more than 80% of individuals
identifiable up to a year after the sampling period.
“Although the potential for any data privacy
concerns from purely microbial DNA is very low, it’s
important for researchers to know that such issues
are theoretically possible,” said senior author
Curtis Huttenhower, associate professor of
computational biology and bioinformatics at Harvard
Chan School. “Perhaps even more exciting are the
implications of the study for microbial ecology,
since it suggests our unique microbial residents are
tuned to the environment of our body—our genetics,
diet, and developmental history—in such a way that
they stick with us and help to fend off
less-friendly microbial invaders over time.”
For more information
“Identifying personal microbiomes using metagenomics
codes,” Eric A. Franzosa, Katherine Huang, James F.
Meadow, Dirk Gevers, Katherine P. Lemon, Brendan J.
M. Bohannan, Curtis Huttenhower, PNAS, online May
11, 2015
doi:10.1073/pnas.1423854112
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