Your Microbiome Has A Unique 'Fingerprint'
A new study shows that the microbial communities we carry in and on
our bodies, the human microbiome, contain the potential to uniquely
identify individuals, much like fingerprints.
Researchers and demonstrated that personal microbiomes 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.
They 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.
"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 T.H. Chan
School of Public Health.
"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. "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."
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