Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer
Differentiation between mitis group streptococci (MGS) bacteria in routine laboratory tests has become important for obtaining accurate epidemiological information on the characteristics of MGS and understanding their clinical significance. The most reliable method of MGS species identification is m...
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Frontiers Media S.A.
2020-01-01
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Series: | Frontiers in Cellular and Infection Microbiology |
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Online Access: | https://www.frontiersin.org/article/10.3389/fcimb.2020.00011/full |
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doaj-60216cd7122e46658df346a60829eeb5 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Kazuo Imai Kazuo Imai Rina Nemoto Masahiro Kodana Norihito Tarumoto Norihito Tarumoto Jun Sakai Jun Sakai Toru Kawamura Kenji Ikebuchi Kotaro Mitsutake Takashi Murakami Takashi Murakami Shigefumi Maesaki Shigefumi Maesaki Taku Fujiwara Satoshi Hayakawa Tomonori Hoshino Mitsuko Seki Mitsuko Seki Takuya Maeda Takuya Maeda |
spellingShingle |
Kazuo Imai Kazuo Imai Rina Nemoto Masahiro Kodana Norihito Tarumoto Norihito Tarumoto Jun Sakai Jun Sakai Toru Kawamura Kenji Ikebuchi Kotaro Mitsutake Takashi Murakami Takashi Murakami Shigefumi Maesaki Shigefumi Maesaki Taku Fujiwara Satoshi Hayakawa Tomonori Hoshino Mitsuko Seki Mitsuko Seki Takuya Maeda Takuya Maeda Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer Frontiers in Cellular and Infection Microbiology mitis group streptococci MinION WIMP Kraken whole genome sequencing |
author_facet |
Kazuo Imai Kazuo Imai Rina Nemoto Masahiro Kodana Norihito Tarumoto Norihito Tarumoto Jun Sakai Jun Sakai Toru Kawamura Kenji Ikebuchi Kotaro Mitsutake Takashi Murakami Takashi Murakami Shigefumi Maesaki Shigefumi Maesaki Taku Fujiwara Satoshi Hayakawa Tomonori Hoshino Mitsuko Seki Mitsuko Seki Takuya Maeda Takuya Maeda |
author_sort |
Kazuo Imai |
title |
Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer |
title_short |
Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer |
title_full |
Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer |
title_fullStr |
Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer |
title_full_unstemmed |
Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore Sequencer |
title_sort |
rapid and accurate species identification of mitis group streptococci using the minion nanopore sequencer |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Cellular and Infection Microbiology |
issn |
2235-2988 |
publishDate |
2020-01-01 |
description |
Differentiation between mitis group streptococci (MGS) bacteria in routine laboratory tests has become important for obtaining accurate epidemiological information on the characteristics of MGS and understanding their clinical significance. The most reliable method of MGS species identification is multilocus sequence analysis (MLSA) with seven house-keeping genes; however, because this method is time-consuming, it is deemed unsuitable for use in most clinical laboratories. In this study, we established a scheme for identifying 12 species of MGS (S. pneumoniae, S. pseudopneumoniae, S. mitis, S. oralis, S. peroris, S. infantis, S. australis, S. parasanguinis, S. sinensis, S. sanguinis, S. gordonii, and S. cristatus) using the MinION nanopore sequencer (Oxford Nanopore Technologies, Oxford, UK) with the taxonomic aligner “What's in My Pot?” (WIMP; Oxford Nanopore's cloud-based analysis platform) and Kraken2 pipeline with the custom database adjusted for MGS species identification. The identities of the species in reference genomes (n = 514), clinical isolates (n = 31), and reference strains (n = 4) were confirmed via MLSA. The nanopore simulation reads were generated from reference genomes, and the optimal cut-off values for MGS species identification were determined. For 31 clinical isolates (S. pneumoniae = 8, S. mitis = 17 and S. oralis = 6) and 4 reference strains (S. pneumoniae = 1, S. mitis = 1, S. oralis = 1, and S. pseudopneumoniae = 1), a sequence library was constructed via a Rapid Barcoding Sequencing Kit for multiplex and real-time MinION sequencing. The optimal cut-off values for the identification of MGS species for analysis by WIMP and Kraken2 pipeline were determined. The workflow using Kraken2 pipeline with a custom database identified all 12 species of MGS, and WIMP identified 8 MGS bacteria except S. infantis, S. australis, S. peroris, and S. sinensis. The results obtained by MinION with WIMP and Kraken2 pipeline were consistent with the MGS species identified by MLSA analysis. The practical advantage of whole genome analysis using the MinION nanopore sequencer is that it can aid in MGS surveillance. We concluded that MinION sequencing with the taxonomic aligner enables accurate MGS species identification and could contribute to further epidemiological surveys. |
topic |
mitis group streptococci MinION WIMP Kraken whole genome sequencing |
url |
https://www.frontiersin.org/article/10.3389/fcimb.2020.00011/full |
work_keys_str_mv |
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doaj-60216cd7122e46658df346a60829eeb52020-11-25T01:22:40ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882020-01-011010.3389/fcimb.2020.00011506260Rapid and Accurate Species Identification of Mitis Group Streptococci Using the MinION Nanopore SequencerKazuo Imai0Kazuo Imai1Rina Nemoto2Masahiro Kodana3Norihito Tarumoto4Norihito Tarumoto5Jun Sakai6Jun Sakai7Toru Kawamura8Kenji Ikebuchi9Kotaro Mitsutake10Takashi Murakami11Takashi Murakami12Shigefumi Maesaki13Shigefumi Maesaki14Taku Fujiwara15Satoshi Hayakawa16Tomonori Hoshino17Mitsuko Seki18Mitsuko Seki19Takuya Maeda20Takuya Maeda21Department of Infectious Disease and Infection Control, Saitama Medical University, Saitama, JapanCenter for Clinical Infectious Diseases and Research, Saitama Medical University, Saitama, JapanDepartment of Microbiology, Saitama Medical University, Saitama, JapanDepartment of Laboratory Medicine, Saitama Medical University, Saitama, JapanDepartment of Infectious Disease and Infection Control, Saitama Medical University, Saitama, JapanCenter for Clinical Infectious Diseases and Research, Saitama Medical University, Saitama, JapanDepartment of Infectious Disease and Infection Control, Saitama Medical University, Saitama, JapanCenter for Clinical Infectious Diseases and Research, Saitama Medical University, Saitama, JapanDepartment of Laboratory Medicine, Saitama Medical University, Saitama, JapanDepartment of Laboratory Medicine, Saitama Medical University, Saitama, JapanDepartment of Infectious Diseases and Infection Control, International Medical Center, Saitama Medical University, Saitama, JapanCenter for Clinical Infectious Diseases and Research, Saitama Medical University, Saitama, JapanDepartment of Microbiology, Saitama Medical University, Saitama, JapanDepartment of Infectious Disease and Infection Control, Saitama Medical University, Saitama, JapanCenter for Clinical Infectious Diseases and Research, Saitama Medical University, Saitama, JapanDepartment of Pediatric Dentistry, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, JapanDivision of Microbiology, Department of Pathology and Microbiology, Nihon University School of Medicine, Tokyo, JapanDivision of Pediatric Dentistry, Meikai University School of Dentistry, Sakado, JapanDivision of Microbiology, Department of Pathology and Microbiology, Nihon University School of Medicine, Tokyo, JapanDivision of Pediatric Dentistry, Meikai University School of Dentistry, Sakado, JapanCenter for Clinical Infectious Diseases and Research, Saitama Medical University, Saitama, JapanDepartment of Laboratory Medicine, Saitama Medical University, Saitama, JapanDifferentiation between mitis group streptococci (MGS) bacteria in routine laboratory tests has become important for obtaining accurate epidemiological information on the characteristics of MGS and understanding their clinical significance. The most reliable method of MGS species identification is multilocus sequence analysis (MLSA) with seven house-keeping genes; however, because this method is time-consuming, it is deemed unsuitable for use in most clinical laboratories. In this study, we established a scheme for identifying 12 species of MGS (S. pneumoniae, S. pseudopneumoniae, S. mitis, S. oralis, S. peroris, S. infantis, S. australis, S. parasanguinis, S. sinensis, S. sanguinis, S. gordonii, and S. cristatus) using the MinION nanopore sequencer (Oxford Nanopore Technologies, Oxford, UK) with the taxonomic aligner “What's in My Pot?” (WIMP; Oxford Nanopore's cloud-based analysis platform) and Kraken2 pipeline with the custom database adjusted for MGS species identification. The identities of the species in reference genomes (n = 514), clinical isolates (n = 31), and reference strains (n = 4) were confirmed via MLSA. The nanopore simulation reads were generated from reference genomes, and the optimal cut-off values for MGS species identification were determined. For 31 clinical isolates (S. pneumoniae = 8, S. mitis = 17 and S. oralis = 6) and 4 reference strains (S. pneumoniae = 1, S. mitis = 1, S. oralis = 1, and S. pseudopneumoniae = 1), a sequence library was constructed via a Rapid Barcoding Sequencing Kit for multiplex and real-time MinION sequencing. The optimal cut-off values for the identification of MGS species for analysis by WIMP and Kraken2 pipeline were determined. The workflow using Kraken2 pipeline with a custom database identified all 12 species of MGS, and WIMP identified 8 MGS bacteria except S. infantis, S. australis, S. peroris, and S. sinensis. The results obtained by MinION with WIMP and Kraken2 pipeline were consistent with the MGS species identified by MLSA analysis. The practical advantage of whole genome analysis using the MinION nanopore sequencer is that it can aid in MGS surveillance. We concluded that MinION sequencing with the taxonomic aligner enables accurate MGS species identification and could contribute to further epidemiological surveys.https://www.frontiersin.org/article/10.3389/fcimb.2020.00011/fullmitis group streptococciMinIONWIMPKrakenwhole genome sequencing |