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Article: Evaluation of experimental protocols for shotgun whole-genome metagenomic discovery of antibiotic resistance genes

TitleEvaluation of experimental protocols for shotgun whole-genome metagenomic discovery of antibiotic resistance genes
Authors
Keywordsmetagenomics
microbiome
next generation sequencing
bioinformatics
experimental design
Issue Date2020
PublisherIEEE.
Citation
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, Epub 2020-06-22, p. 1-1 How to Cite?
AbstractShotgun metagenomics has enabled the discovery of antibiotic resistance genes (ARGs). Although there have been numerous studies benchmarking the bioinformatics methods for shotgun metagenomic data analysis, there has not yet been a study that systematically evaluates the performance of different experimental protocols on metagenomic species profiling and ARG detection. In this study, we generated 35 whole genome shotgun metagenomic sequencing data sets for five samples (three human stool and two microbial standard) using seven experimental protocols (KAPA or Flex kits at 50ng, 10ng, or 5ng input amounts; XT kit at 1ng input amount). Using this comprehensive resource, we evaluated the seven protocols in terms of robust detection of ARGs and microbial abundance estimation at various sequencing depths. We found that the data generated by the seven protocols are largely similar. The inter-protocol variability is significantly smaller than the variability between samples or sequencing depths. We found that a sequencing depth of more than 30M is suitable for human stool samples. A higher input amount (50ng) is generally favorable for the KAPA and Flex kits. This systematic benchmarking study sheds light on the impact of sequencing depth, experimental protocol, and DNA input amount on ARG detection in human stool samples.
Persistent Identifierhttp://hdl.handle.net/10722/283999
ISSN
2019 Impact Factor: 3.015
2015 SCImago Journal Rankings: 0.706

 

DC FieldValueLanguage
dc.contributor.authorYu, KHO-
dc.contributor.authorFang, X-
dc.contributor.authorYao, H-
dc.contributor.authorNg, B-
dc.contributor.authorLeung, TK-
dc.contributor.authorWang, LL-
dc.contributor.authorLin, CH-
dc.contributor.authorChan, A-
dc.contributor.authorLeung, WK-
dc.contributor.authorLeung, SY-
dc.contributor.authorHo, J-
dc.date.accessioned2020-07-20T05:55:13Z-
dc.date.available2020-07-20T05:55:13Z-
dc.date.issued2020-
dc.identifier.citationIEEE/ACM Transactions on Computational Biology and Bioinformatics, 2020, Epub 2020-06-22, p. 1-1-
dc.identifier.issn1545-5963-
dc.identifier.urihttp://hdl.handle.net/10722/283999-
dc.description.abstractShotgun metagenomics has enabled the discovery of antibiotic resistance genes (ARGs). Although there have been numerous studies benchmarking the bioinformatics methods for shotgun metagenomic data analysis, there has not yet been a study that systematically evaluates the performance of different experimental protocols on metagenomic species profiling and ARG detection. In this study, we generated 35 whole genome shotgun metagenomic sequencing data sets for five samples (three human stool and two microbial standard) using seven experimental protocols (KAPA or Flex kits at 50ng, 10ng, or 5ng input amounts; XT kit at 1ng input amount). Using this comprehensive resource, we evaluated the seven protocols in terms of robust detection of ARGs and microbial abundance estimation at various sequencing depths. We found that the data generated by the seven protocols are largely similar. The inter-protocol variability is significantly smaller than the variability between samples or sequencing depths. We found that a sequencing depth of more than 30M is suitable for human stool samples. A higher input amount (50ng) is generally favorable for the KAPA and Flex kits. This systematic benchmarking study sheds light on the impact of sequencing depth, experimental protocol, and DNA input amount on ARG detection in human stool samples.-
dc.languageeng-
dc.publisherIEEE.-
dc.relation.ispartofIEEE/ACM Transactions on Computational Biology and Bioinformatics-
dc.rightsIEEE/ACM Transactions on Computational Biology and Bioinformatics. Copyright © IEEE.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectmetagenomics-
dc.subjectmicrobiome-
dc.subjectnext generation sequencing-
dc.subjectbioinformatics-
dc.subjectexperimental design-
dc.titleEvaluation of experimental protocols for shotgun whole-genome metagenomic discovery of antibiotic resistance genes-
dc.typeArticle-
dc.identifier.emailYu, KHO: yuken@hku.hk-
dc.identifier.emailYao, H: viphbyao@hku.hk-
dc.identifier.emailNg, B: ypng@hku.hk-
dc.identifier.emailLeung, TK: tkleung@hku.hk-
dc.identifier.emailLin, CH: nicklin@hku.hk-
dc.identifier.emailChan, A: chansw3@hku.hk-
dc.identifier.emailLeung, WK: waikleung@hku.hk-
dc.identifier.emailLeung, SY: suetyi@hku.hk-
dc.identifier.emailHo, J: jwkho@hku.hk-
dc.identifier.authorityChan, A=rp00288-
dc.identifier.authorityLeung, WK=rp01479-
dc.identifier.authorityLeung, SY=rp00359-
dc.identifier.authorityHo, J=rp02436-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCBB.2020.3004063-
dc.identifier.hkuros311050-
dc.identifier.volumeEpub 2020-06-22-
dc.identifier.spage1-
dc.identifier.epage1-
dc.publisher.placeUnited States-

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