Terminal restriction fragment length polymorphism profiling of bacterial flora derived from single human hair shafts can discriminate individuals

Nishi, Eiji; Watanabe, Kota; Tashiro, Yukihiro; Sakai, Kokki

doi:10.1016/j.legalmed.2017.01.002

Cited by 18 publications

(8 citation statements)

References 36 publications

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“…The densities of the bacteria present on several sites of the human body have been reported, including 10 2 cells cm −2 on dried skin and 10 7 cells cm −2 on wet skin (12), 10 6 cells mL −1 in saliva (27), and 10 10 cells g −1 of the intestinal content (19). We previously showed the amount of bacterial DNA obtained from scalp hairs (both roots and shafts) (21), but not cell densities. In the present study, we quantified bacterial cell densities on scalp hairs both by counting on SEM and qPCR, revealing high densities of ca .…”

Section: Discussionmentioning

confidence: 99%

“…However, they focused on differences in the community structures on pubic hair between sexes. In contrast, we previously reported a specific individual bacterial community structure on the roots and shafts of scalp hairs by terminal restriction fragment length polymorphism (T-RFLP); however, this method does not provide precise phylogenic information on the community structure (21). Quantitative PCR (qPCR) of bacteria on the shafts and roots of scalp hairs suggest the presence of an indigenous bacterial community.…”

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confidence: 97%

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Mode and Structure of the Bacterial Community on Human Scalp Hair

et al. 2019

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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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Section: Discussionmentioning

confidence: 99%

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confidence: 97%

Mode and Structure of the Bacterial Community on Human Scalp Hair

et al. 2019

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“…Individual-specific microbiome features with the greatest temporal stability (up to almost 3 years) include single-nucleotide variant (SNV) profiles of Propionibacterium acnes from the skin (9) and gene signatures (i.e., clade-specific markers and 1-kb genomic windows) from the gut microbiome (8). Strain-level signatures from shotgun sequencing provide far more depth of resolution than 16S rRNA based features, such as terminal restriction fragment length polymorphism profiles (18,22,23), OTU abundances (8, 19-21, 24, 25), and biological community distances (e.g., UniFrac distance) (17,20). Nucleotide diversity of strains, which measures the strain-level heterogeneity of the microbial population, also has been shown to be greater between individuals than within the same individual (26).…”

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confidence: 99%

Forensic Human Identification Using Skin Microbiomes

Schmedes

Woerner

Budowle

2017

Appl Environ Microbiol

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The human microbiome contributes significantly to the genetic content of the human body. Genetic and environmental factors help shape the microbiome, and as such, the microbiome can be unique to an individual. Previous studies have demonstrated the potential to use microbiome profiling for forensic applications, however a method has yet to identify stable features of skin microbiomes that produce high classification accuracies for samples collected over reasonably long time intervals. A novel approach is described to classify skin microbiomes to their donors by comparing two features types, pangenome presence/absence features and nucleotide diversities of stable clade-specific markers. Supervised learning was used to attribute skin microbiomes from 14 skin body sites from 12 healthy individuals sampled at three time points over a>2.5 year period with accuracies up to 100% for three body sites. Feature selection identified a reduced subset of markers from each body site that are highly individualizing, identifying 187 markers from 12 clades. Classification accuracies were compared in a formal model testing framework, and the results of this indicate that learners trained on nucleotide diversity perform significantly better than those trained on presence/absence encodings. This study used supervised learning to identify individuals with high accuracy and associated stable features from skin microbiomes over a period of up to almost 3 years. These selected features provide a preliminary marker panel for future development of a robust and reproducible method for skin microbiome profiling for forensic human identification. A novel approach is described to attribute skin microbiomes, collected over a period of >2.5 years, to their individual hosts with a high degree of accuracy. Nucleotide diversities of stable clade-specific markers with supervised learning was used to classify skin microbiomes from a particular individual with up to 100% classification accuracy for three body sites. Attribute selection was used to identify 187 genetic markers from 12 clades which provide the greatest differentiation of individual skin microbiomes from 14 skin sites. This study performs skin microbiome profiling from a supervised learning approach and obtains high classification accuracy for samples collected from individuals over a relatively long time period for potential application to forensic human identification.

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“…Tridico et al analysed bacterial community structures on pubic and scalp hair and showed that they were only different in females 14 . We have previously reported the special features of bacterial community structures on scalp hair 15 – 17 . A specific individual bacterial community structure on scalp hair could be identified using the terminal restriction fragment length polymorphism method 15 .…”

Section: Introductionmentioning

confidence: 99%

“…We have previously reported the special features of bacterial community structures on scalp hair 15 – 17 . A specific individual bacterial community structure on scalp hair could be identified using the terminal restriction fragment length polymorphism method 15 . Furthermore, we analysed the bacterial community structure on portions of human scalp hair shafts and roots from six individuals, using 16S amplicon sequencing, and found that the major bacteria on human scalp hair shafts are indigenous and derived from hair roots 16 .…”

Section: Introductionmentioning

confidence: 99%

Host factors that shape the bacterial community structure on scalp hair shaft

Watanabe

Yamada

Nishi

et al. 2021

Sci Rep

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In this study, we performed 16S rRNA amplicon sequencing analysis of scalp hair shaft from 109 volunteers, who were surveyed using a questionnaire about daily scalp hair care, and employed multiple statistical analyses to elucidate the factors that contribute to the formation of bacterial community structures on scalp hair shaft. Scalp hair microbiota were found to be specific for each individual. Their microbiota were clearly divided into two clusters. Genus level richness of Pseudomonas (Ps) and Cutibacterium (Cu) contributed to the clusters. The clusters around Pseudomonas and Cutibacterium were named Ps-type and Cu-type, respectively. The host gender influenced the bacterial cell numbers of the major genera that included Cutibacterium, Lawsonella, Moraxella, and Staphylococcus on scalp hair shaft. In addition to host intrinsic factors, extrinsic factors such as hair styling and colouring affected the bacterial cell numbers of the major genera. These factors and chemical treatments, such as bleaching and perming, also affected the Ps-type to Cu-type ratios. These results suggest that bacterial community structures on scalp hair shaft are influenced by both intrinsic and extrinsic factors.

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Terminal restriction fragment length polymorphism profiling of bacterial flora derived from single human hair shafts can discriminate individuals

Cited by 18 publications

References 36 publications

Mode and Structure of the Bacterial Community on Human Scalp Hair

Mode and Structure of the Bacterial Community on Human Scalp Hair

Forensic Human Identification Using Skin Microbiomes

Host factors that shape the bacterial community structure on scalp hair shaft

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