Kochi Toyomane, Yuri Kimura, Takashi Fukagawa, Takayuki Yamagishi, Ken Watanabe, Tomoko Akutsu, Ai Asahi, Satoshi Kubota, Kazumasa Sekiguchi
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引用次数: 0
Abstract
The high specificity of the human skin microbiome is expected to provide a new marker for personal identification. Metagenomic sequencing of clustered regularly interspaced short palindromic repeats (CRISPRs), which we call metaCRISPR typing, was shown to achieve personal identification accurately. However, the intra-individual variability observed in previous studies, which may be due to poor DNA yields from skin samples, has resulted in non-reproducible results. Furthermore, whether metaCRISPR typing can assist in the forensic human DNA analysis of low-biomass samples, from which the information obtained is insufficient, is unknown. In the present study, we sequenced serially diluted control streptococcal CRISPRs cloned into plasmids to determine the minimum copy number required to obtain reproducible results from metaCRISPR typing. We found that at least 102 copies of CRISPRs are necessary to obtain reproducible results. We then analyzed the skin swab samples using both metaCRISPR typing and human DNA typing. When the DNA extracted from the skin swabs was diluted, no information was obtained from six out of eight samples by human DNA typing. On the other hand, beta diversity indices of spacer sequences compared with reference samples were below 0.8 for three out of six samples, for which no information was obtained from human DNA analysis, indicating that the spacers observed in these samples were similar to those in the references. These results indicate that metaCRISPR typing may contribute to the identification of individuals from whom the samples were obtained, even in cases where human DNA yields are insufficient to perform human DNA analysis.IMPORTANCEPrevious studies have developed new personal identification methods utilizing personal differences in the skin microbiome. However, intra-individual diversity of skin microbiome may preclude the application of microbiome-based personal identification. Moreover, no study has compared microbiome-based personal identification and practical human DNA analysis. Here, we revealed that the results of metaCRISPR typing, a previously developed microbiome-based personal identification method, are stable if the copy number of the marker gene is sufficient. We then analyzed the skin swab samples using both metaCRISPR typing and human DNA analysis. Our results indicate that metaCRISPR typing may provide additional information for personal identification using low-biomass samples that cannot be used for conventional human DNA analysis.
人类皮肤微生物组的高度特异性有望为个人识别提供新的标记。聚类规律性间隔短回文重复序列(CRISPRs)的元基因组测序(我们称之为元CRISPR分型)已被证明能准确实现个人身份鉴定。然而,在以往的研究中观察到的个体内变异可能是由于皮肤样本的DNA产量较低,导致结果不可再现。此外,元CRISPR分型能否帮助对生物量低的样本进行法医人类DNA分析还不得而知,因为从低生物量样本中获得的信息并不充分。在本研究中,我们对克隆到质粒中的串联稀释对照链球菌CRISPR进行了测序,以确定元CRISPR分型获得可重复结果所需的最小拷贝数。我们发现,要获得可重复的结果,至少需要 102 个 CRISPRs 拷贝。然后,我们使用元CRISPR分型和人类DNA分型对皮肤拭子样本进行了分析。当稀释从皮肤拭子中提取的 DNA 时,8 个样本中有 6 个无法通过人类 DNA 分型获得信息。另一方面,在人类 DNA 分析未获得信息的 6 个样本中,有 3 个样本的间隔序列与参考样本相比的β多样性指数低于 0.8,这表明在这些样本中观察到的间隔序列与参考样本中的间隔序列相似。这些结果表明,即使在人类 DNA 产量不足以进行人类 DNA 分析的情况下,元CRISPR 分型也可能有助于识别样本的来源。然而,皮肤微生物组的个体内多样性可能会妨碍基于微生物组的个人识别方法的应用。此外,还没有研究对基于微生物组的个人识别方法和实用的人类 DNA 分析方法进行比较。在这里,我们发现,如果标记基因的拷贝数足够多,先前开发的基于微生物组的个人识别方法--元CRISPR分型--的结果是稳定的。然后,我们使用 metaCRISPR 分型和人类 DNA 分析方法对皮肤拭子样本进行了分析。我们的研究结果表明,元CRISPR分型法可以利用无法进行常规人类DNA分析的低生物量样本为个人身份鉴定提供更多信息。
mSystemsBiochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍:
mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.