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Qualitative and Quantitative Analysis for Microbiome Data Matching between Objects

마이크로바이옴 데이터 일치를 위한 물체들 사이의 정량 및 정성적 분석

  • You, Hee Sang (Department of Biomedical Laboratory Science, School of Medicine, Eulji University) ;
  • Ok, Yeon Jeong (Department of Biomedical Laboratory Science, School of Medicine, Eulji University) ;
  • Lee, Song Hee (Department of Biomedical Laboratory Science, School of Medicine, Eulji University) ;
  • Lee, So Lip (Department of Biomedical Laboratory Science, School of Medicine, Eulji University) ;
  • Lee, Young Ju (Department of Biomedical Laboratory Science, School of Medicine, Eulji University) ;
  • Lee, Min Ho (Department of Senior Healthcare, BK21 Plus Program, Graduate School, Eulji University) ;
  • Hyun, Sung Hee (Department of Biomedical Laboratory Science, School of Medicine, Eulji University)
  • 유희상 (을지대학교 의과대학 임상병리학과) ;
  • 옥연정 (을지대학교 의과대학 임상병리학과) ;
  • 이송희 (을지대학교 의과대학 임상병리학과) ;
  • 이소립 (을지대학교 의과대학 임상병리학과) ;
  • 이영주 (을지대학교 의과대학 임상병리학과) ;
  • 이민호 (을지대학교 일반대학원 BK21플러스 시니어헬스케어학과) ;
  • 현성희 (을지대학교 의과대학 임상병리학과)
  • Received : 2020.05.04
  • Accepted : 2020.07.14
  • Published : 2020.09.30

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.

미생물 연구에서 대량의 마이크로바이옴 데이터를 효율적으로 얻는 기술이 발전해왔지만, 마이크로바이옴 빅 데이터를 적절하게 분석하는 도구는 여전히 부족하다. 또한 빈약한 데이터베이스를 사용하여 미생물 군집을 분석하면 잘못된 결과를 초래할 수 있다. 따라서 본 연구는 대량의 미생물 데이터베이스 분석을 위한 적절한 방법을 설계하고자 하였다. 박테리아는 개인의 손끝과 개인 소지품(휴대 전화 및 랩탑 키보드)에서 수집되었다. 박테리아로부터 게놈 DNA를 추출하고 16S rRNA 유전자를 표적으로 하여 차세대 시퀀싱을 실시하였다. 손끝과 개인 소지품 간의 박테리아 매칭 비율의 정확성은 공식과 함께 환경 및 인간관련 데이터베이스를 사용하여 확인하였다. 적절한 분석을 설계하기 위해 다음 세가지 범주를 기준으로: 정성적 분석과 정량적 분석 비교, 성별에 관계없이 모든 참여자뿐만 아니라 동일 성별 참여자 내 비교, 환경(eDB) 및 인간 관련 데이터 베이스(hDB)를 이용하여 샘플간 비교하였다. 결과는 정성적 분석과 동일 성별 참가자 내에서의 비교 및 hDB의 사용이 비교적 정확한 결과를 제공하였다. 우리의 연구는 인간 유래 미생물을 사용하여 대량의 미생물학적 데이터를 포함하는 연구를 수행할 때 정확한 결과를 얻을 수 있는 분석 방법을 제공한다.

Keywords

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