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.
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