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Article: In silico analysis of 16S ribosomal RNA gene sequencing-based methods for identification of medically important anaerobic bacteria

TitleIn silico analysis of 16S ribosomal RNA gene sequencing-based methods for identification of medically important anaerobic bacteria
Authors
Issue Date2007
PublisherB M J Publishing Group. The Journal's web site is located at http://jcp.bmjjournals.com/
Citation
Journal Of Clinical Pathology, 2007, v. 60 n. 5, p. 576-579 How to Cite?
AbstractThis study is the first study that provides useful guidelines to clinical microbiologists and technicians on the usefulness of full 16S rRNA sequencing, 5′-end 527-bp 16S rRNA sequencing and the existing MicroSeq full and 500 16S rDNA bacterial identification system (MicroSeq, Perkin-Elmer Applied Biosystems Division, Foster City, California, USA) databases for the identification of all existing medically important anaerobic bacteria. Full and 527-bp 16S rRNA sequencing are able to identify 52-63% of 130 Gram-positive anaerobic rods, 72-73% of 86 Gram-negative anaerobic rods and 78% of 23 anaerobic cocci. The existing MicroSeq databases are able to identify only 19-25% of 130 Gram-positive anaerobic rods, 38% of 86 Gram-negative anaerobic rods and 39% of 23 anaerobic cocci. These represent only 45-46% of those that should be confidently identified by full and 527-bp 16S rRNA sequencing. To improve the usefulness of MicroSeq, bacterial species that should be confidently identified by full and/or 527-bp 16S rRNA sequencing but not included in the existing MicroSeq databases should be included.
Persistent Identifierhttp://hdl.handle.net/10722/57298
ISSN
2015 Impact Factor: 2.912
2015 SCImago Journal Rankings: 1.260
PubMed Central ID
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWoo, PCYen_HK
dc.contributor.authorChung, LMWen_HK
dc.contributor.authorTeng, JLLen_HK
dc.contributor.authorTse, Hen_HK
dc.contributor.authorPang, SSYen_HK
dc.contributor.authorLau, VYTen_HK
dc.contributor.authorWong, VWKen_HK
dc.contributor.authorKam, KLen_HK
dc.contributor.authorLau, SKPen_HK
dc.contributor.authorYuen, KYen_HK
dc.date.accessioned2010-04-12T01:32:21Z-
dc.date.available2010-04-12T01:32:21Z-
dc.date.issued2007en_HK
dc.identifier.citationJournal Of Clinical Pathology, 2007, v. 60 n. 5, p. 576-579en_HK
dc.identifier.issn0021-9746en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57298-
dc.description.abstractThis study is the first study that provides useful guidelines to clinical microbiologists and technicians on the usefulness of full 16S rRNA sequencing, 5′-end 527-bp 16S rRNA sequencing and the existing MicroSeq full and 500 16S rDNA bacterial identification system (MicroSeq, Perkin-Elmer Applied Biosystems Division, Foster City, California, USA) databases for the identification of all existing medically important anaerobic bacteria. Full and 527-bp 16S rRNA sequencing are able to identify 52-63% of 130 Gram-positive anaerobic rods, 72-73% of 86 Gram-negative anaerobic rods and 78% of 23 anaerobic cocci. The existing MicroSeq databases are able to identify only 19-25% of 130 Gram-positive anaerobic rods, 38% of 86 Gram-negative anaerobic rods and 39% of 23 anaerobic cocci. These represent only 45-46% of those that should be confidently identified by full and 527-bp 16S rRNA sequencing. To improve the usefulness of MicroSeq, bacterial species that should be confidently identified by full and/or 527-bp 16S rRNA sequencing but not included in the existing MicroSeq databases should be included.en_HK
dc.languageengen_HK
dc.publisherB M J Publishing Group. The Journal's web site is located at http://jcp.bmjjournals.com/en_HK
dc.relation.ispartofJournal of Clinical Pathologyen_HK
dc.rightsJournal of Clinical Pathology. Copyright © B M J Publishing Group.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject.meshBacteria, Anaerobic - classification - geneticsen_HK
dc.subject.meshBacterial Typing Techniques - methodsen_HK
dc.subject.meshRNA, Bacterial - geneticsen_HK
dc.subject.meshRNA, Ribosomal, 16S - geneticsen_HK
dc.subject.meshSequence Analysis, RNA - methodsen_HK
dc.titleIn silico analysis of 16S ribosomal RNA gene sequencing-based methods for identification of medically important anaerobic bacteriaen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0021-9746&volume=60&issue=5&spage=576&epage=579&date=2007&atitle=In+silico+analysis+of+16S+ribosomal+RNA+gene+sequencing-based+methods+for+identification+of+medically+important+anaerobic+bacteriaen_HK
dc.identifier.emailWoo, PCY:pcywoo@hkucc.hku.hken_HK
dc.identifier.emailTeng, JLL:llteng@hku.hken_HK
dc.identifier.emailTse, H:herman@graduate.hku.hken_HK
dc.identifier.emailLau, SKP:skplau@hkucc.hku.hken_HK
dc.identifier.emailYuen, KY:kyyuen@hkucc.hku.hken_HK
dc.identifier.authorityWoo, PCY=rp00430en_HK
dc.identifier.authorityTeng, JLL=rp00277en_HK
dc.identifier.authorityTse, H=rp00519en_HK
dc.identifier.authorityLau, SKP=rp00486en_HK
dc.identifier.authorityYuen, KY=rp00366en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1136/jcp.2006.038653en_HK
dc.identifier.pmid17046845-
dc.identifier.pmcidPMC1994535-
dc.identifier.scopuseid_2-s2.0-34249903335en_HK
dc.identifier.hkuros132683-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34249903335&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume60en_HK
dc.identifier.issue5en_HK
dc.identifier.spage576en_HK
dc.identifier.epage579en_HK
dc.identifier.isiWOS:000246594100027-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridWoo, PCY=7201801340en_HK
dc.identifier.scopusauthoridChung, LMW=15847898900en_HK
dc.identifier.scopusauthoridTeng, JLL=7202560229en_HK
dc.identifier.scopusauthoridTse, H=7006070596en_HK
dc.identifier.scopusauthoridPang, SSY=16426170100en_HK
dc.identifier.scopusauthoridLau, VYT=16426066500en_HK
dc.identifier.scopusauthoridWong, VWK=36894794400en_HK
dc.identifier.scopusauthoridKam, KL=16426096200en_HK
dc.identifier.scopusauthoridLau, SKP=7401596211en_HK
dc.identifier.scopusauthoridYuen, KY=36078079100en_HK

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