Bacterial communities on various parts of the human body are distinct. We were the first to report the existence of a stable bacterial community on human scalp hair and demonstrated that an analysis of its structure by terminal restriction fragment length polymorphism (T-RFLP) is helpful for individual discrimination. However, the ecology of the bacterial community on human scalp hair has not yet been elucidated in detail. We herein investigated the mode, quantity, and phylogeny of bacterial communities on the human hair shaft and root and showed the results obtained from one representative individual. Direct SEM observations of hair, without a pretreatment, confirmed the ubiquitous presence of bacteria-like coccoids and rods on the shaft and root of hair from the human scalp, with 105–106 cells cm−2 of hair and 107 cells cm−2 of hair, respectively. These values corresponded to the 16S rRNA gene copy numbers obtained by qPCR. These numbers were not significantly affected by detergent washing. These results represented those obtained from many individuals with different hair lengths, ages, and gender. The major OTUs on the human scalp hair shaft and root were the same and included two species of Pseudomonas (phylum Proteobacteria), Cutibacterium and Lawsonella (phylum Actinobacteria), and Staphylococcus (phylum Firmicutes). These results suggest that major bacteria on the human hair shaft are indigenous and derived from the hair root.

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DNA typing from forensic evidence is commonly used to identify individuals. However, when the quantity of the forensic evidence is insufficient, successful identification using DNA typing is impossible. Such evidence may also contain DNA from bacteria that occur naturally on the skin. In this study, we aimed to establish a profiling method using terminal restriction fragment length polymorphisms (T-RFLPs) of the amplified bacterial 16S ribosomal RNA (rRNA) gene. First, the extraction and digestion processes were investigated, and the T-RFLP profiling method using the 16S rRNA gene amplicon was optimized. We then used this method to compare the profiles of bacterial flora from the hands of 12 different individuals. We found that the T-RFLP profiles from one person on different days displayed higher similarity than those between individuals. In a principal component analysis (PCA), T-RFLPs from each individual were closely clustered in 11 out of 12 cases. The clusters could be distinguished from each other, even when the samples were collected from different conditions. No major change of the profile was observed after six months except in two cases. When handprints on glass plates were compared, 11 of 12 individuals were assigned to a few clusters including the cluster corresponding to the correct individual. In conclusion, a method for reproducible T-RFLP profiling of bacteria from trace amounts of handprints was established. The profiles were obtained for particular individuals clustered in PCA and were experimentally separable from other individuals in most cases. This technique could provide useful information for narrowing down a suspect in a criminal investigation.

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