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논문 기본 정보

자료유형
학술저널
저자정보
양지훈 (연세대학교) Adina Howe (Iowa State University USA) 이재진 (Iowa State University USA) 유근제 (한국해양대학교) 박준홍 (연세대학교)
저널정보
한국미생물생명공학회 Journal of Microbiology and Biotechnology Journal of Microbiology and Biotechnology 제30권 제9호
발행연도
2020.1
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1,335 - 1,342 (8page)

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The identification of bacterial pathogens to humans is critical for environmental microbial risk assessment. However, current methods for identifying pathogens in environmental samples are limited in their ability to detect highly diverse bacterial communities and accurately differentiate pathogens from commensal bacteria. In the present study, we suggest an improved approach using a combination of identification results obtained from multiple databases, including the multilocus sequence typing (MLST) database, virulence factor database (VFDB), and pathosystems resource integration center (PATRIC) databases to resolve current challenges. By integrating the identification results from multiple databases, potential bacterial pathogens in metagenomes were identified and classified into eight different groups. Based on the distribution of genes in each group, we proposed an equation to calculate the metagenomic pathogen identification index (MPII) of each metagenome based on the weighted abundance of identified sequences in each database. We found that the accuracy of pathogen identification was improved by using combinations of multiple databases compared to that of individual databases. When the approach was applied to environmental metagenomes, metagenomes associated with activated sludge were estimated with higher MPII than other environments (i.e., drinking water, ocean water, ocean sediment, and freshwater sediment). The calculated MPII values were statistically distinguishable among different environments (p < 0.05). These results demonstrate that the suggested approach allows more for more accurate identification of the pathogens associated with metagenomes.

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