This study sampled the public and private spaces of a college dormitory in order to determine the effect that individual microbial signatures had on the microbiota of common spaces.
The study determined that through their movements in an environment, humans unintentionally leave a microbial trail. This may enable the identification of individuals based on the "microbial signatures" they shed in built environments. In a living environment shared by humans, however, individual microbial trails intersect in the shared environments; and through interaction with common surfaces, these trails become homogenized, potentially confounding crime-scene examiners' ability to link individuals to their associated microbiota. The current study compared classification methods for linking dorm residents to their rooms and personal effects in a common dormitory environment. For classifying individuals, minimum entropy decomposition (MED) was determined to be the best choice, based on its high error ratio and ability to recover higher importance scores for all taxa. It appears that the exact sequence variants produced by DADA2 and MED generally are better at identifying individuals than OTU-clustering methods such as UPARSE. This is expected, since exact sequence variants avoid grouping together closely related sequences that could be indicative of individuals. Materials and methods of this study are described in detail. 5 figures, 2 tables, and 80 references
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