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마이크로바이옴 데이터 일치를 위한 물체들 사이의 정량 및 정성적 분석

Qualitative and Quantitative Analysis for Microbiome Data Matching between Objects

대한임상검사과학회지 2020년 52권 3호 p.202 ~ 213
You Hee-Sang, 옥연정, 이송희, 이소립, 이영주, 이민호, 현성희,
소속 상세정보
 ( You Hee-Sang ) - Eulji University School of Medicine Department of Biomedical Laboratory Science
옥연정 ( Ok Yeon-Jeong ) - Eulji University School of Medicine Department of Biomedical Laboratory Science
이송희 ( Lee Song-Hee ) - Eulji University School of Medicine Department of Biomedical Laboratory Science
이소립 ( Lee So-Lip ) - Eulji University School of Medicine Department of Biomedical Laboratory Science
이영주 ( Lee Young-Ju ) - Eulji University School of Medicine Department of Biomedical Laboratory Science
이민호 ( Lee Min-Ho ) - Eulji University Graduate School Department of Senior Healthcare BK21 Plus Program
현성희 ( Hyun Sung-Hee ) - Eulji University School of Medicine Department of Biomedical Laboratory Science

Abstract


Although technological advances have allowed the efficient collection of large amounts of microbiome data for microbiological studies, proper analysis tools for such big data are still lacking. Additionally, analyses of microbial communities using poor databases can lead to misleading results. Hence, this study aimed to design an appropriate method for the analysis of big microbial databases. Bacteria were collected from the fingertips and personal belongings (mobile phones and laptop keyboards) of individuals. The genomic DNA was extracted from these bacteria and subjected to next-generation sequencing by targeting the 16S rRNA gene. The accuracy of the bacterial matching percentage between the fingertips and personal belongings was verified using a formula and an environment-related and human-related database. To design appropriate analysis, the bacterial matching accuracy was calculated based on the following three categories: comparison between qualitative and quantitative analysis, comparisons within same-gender participants as well as all participants regardless of gender, and comparison between the use of a human-related bacterial database (hDB) and environment-related bacterial database (eDB). The results showed that qualitative analysis, comparisons within same-gender participants, and the use of hDB provided relatively accurate results. This study provides an analytical method to obtain accurate results when conducting studies involving big microbiological data using human-derived microorganisms.

키워드

Environment-related bacterial database (eDB); Human-related bacterial database (hDB); Microbiota matching; Qualitative analysis; Quantitative analysis

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