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postgraduate thesis: Update and evaluation of 16SpathDB, an automated comprehensive database for identification of medically important bacteria by 16S rRNA gene sequencing

TitleUpdate and evaluation of 16SpathDB, an automated comprehensive database for identification of medically important bacteria by 16S rRNA gene sequencing
Authors
Issue Date2013
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Yeung, S. [楊兆恩]. (2013). Update and evaluation of 16SpathDB, an automated comprehensive database for identification of medically important bacteria by 16S rRNA gene sequencing. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5091599
AbstractIdentification of pathogens is one of the important duties of clinical microbiology laboratory. Traditionally, phenotypic tests are used to identify the bacteria. However, due to some limitations of the phenotypic tests, the bacteria may not be identified sometimes and cannot be identified promptly. 16S rRNA gene sequencing is a rapid and accurate method to achieve this target. It is especially useful for identify rare or slow growing bacteria. However, the interpretation of the 16S rRNA gene sequencing result is one of the challenging duties to laboratory technicians and microbiologists. Apart from the well known 16S rRNA gene databases such as Genbank, The Ribosomal Database Project (RDP-II), MicroSeq databases, Ribosomal Differentiation of medical Microorganism database (RIDOM), SmartGene IDNS, 16SpathDB is an automated and comprehensive database for interpret the 16S rRNA gene result. The 16SpathDB first version was established in 2011. In this study, 16SpathDB was updated based on the all clinical important bacteria present in the 10th edition of the Manual of Clinical Microbiology (MCM)(Versalovic. et al., 2011) into this new version of database, 16SpathDB 2.0. The database was evaluated by using 689 16S rRNA gene sequences from 689 complete genomes of medically important bacteria. Among the 689 16S rRNA gene sequences, none was wrongly identified by 16SpathDB 2.0, with 247 (35.8%) 16S rRNA gene sequences reported in only one single bacterial species with more than 98% nucleotide identity with the query sequence (category 1), 440 (63.9%) reported as more than one bacterial species having more than 98% nucleotide identity with the query sequence (category 2), 2 (0.3%) reported to the genus level (category 3), and none reported as “no species in 16SpathDB 2.0 found to be sharing high nucleotide identity to your query sequence” (category 4). 16SpathDB 2.0 is an updated, automated, user-friendly, efficient and accurate database for 16S rRNA gene sequence interpretation in clinical microbiology laboratories.
DegreeMaster of Medical Sciences
SubjectPathogenic bacteria
Nucleotide sequence
Dept/ProgramMicrobiology
Persistent Identifierhttp://hdl.handle.net/10722/193552

 

DC FieldValueLanguage
dc.contributor.authorYeung, Shiu-yan-
dc.contributor.author楊兆恩-
dc.date.accessioned2014-01-13T23:10:38Z-
dc.date.available2014-01-13T23:10:38Z-
dc.date.issued2013-
dc.identifier.citationYeung, S. [楊兆恩]. (2013). Update and evaluation of 16SpathDB, an automated comprehensive database for identification of medically important bacteria by 16S rRNA gene sequencing. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5091599-
dc.identifier.urihttp://hdl.handle.net/10722/193552-
dc.description.abstractIdentification of pathogens is one of the important duties of clinical microbiology laboratory. Traditionally, phenotypic tests are used to identify the bacteria. However, due to some limitations of the phenotypic tests, the bacteria may not be identified sometimes and cannot be identified promptly. 16S rRNA gene sequencing is a rapid and accurate method to achieve this target. It is especially useful for identify rare or slow growing bacteria. However, the interpretation of the 16S rRNA gene sequencing result is one of the challenging duties to laboratory technicians and microbiologists. Apart from the well known 16S rRNA gene databases such as Genbank, The Ribosomal Database Project (RDP-II), MicroSeq databases, Ribosomal Differentiation of medical Microorganism database (RIDOM), SmartGene IDNS, 16SpathDB is an automated and comprehensive database for interpret the 16S rRNA gene result. The 16SpathDB first version was established in 2011. In this study, 16SpathDB was updated based on the all clinical important bacteria present in the 10th edition of the Manual of Clinical Microbiology (MCM)(Versalovic. et al., 2011) into this new version of database, 16SpathDB 2.0. The database was evaluated by using 689 16S rRNA gene sequences from 689 complete genomes of medically important bacteria. Among the 689 16S rRNA gene sequences, none was wrongly identified by 16SpathDB 2.0, with 247 (35.8%) 16S rRNA gene sequences reported in only one single bacterial species with more than 98% nucleotide identity with the query sequence (category 1), 440 (63.9%) reported as more than one bacterial species having more than 98% nucleotide identity with the query sequence (category 2), 2 (0.3%) reported to the genus level (category 3), and none reported as “no species in 16SpathDB 2.0 found to be sharing high nucleotide identity to your query sequence” (category 4). 16SpathDB 2.0 is an updated, automated, user-friendly, efficient and accurate database for 16S rRNA gene sequence interpretation in clinical microbiology laboratories.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject.lcshPathogenic bacteria-
dc.subject.lcshNucleotide sequence-
dc.titleUpdate and evaluation of 16SpathDB, an automated comprehensive database for identification of medically important bacteria by 16S rRNA gene sequencing-
dc.typePG_Thesis-
dc.identifier.hkulb5091599-
dc.description.thesisnameMaster of Medical Sciences-
dc.description.thesislevelMaster-
dc.description.thesisdisciplineMicrobiology-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b5091599-
dc.date.hkucongregation2013-

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