Literature DB >> 12682128

Evaluation of the MicroSeq system for identification of mycobacteria by 16S ribosomal DNA sequencing and its integration into a routine clinical mycobacteriology laboratory.

Leslie Hall1, Kelly A Doerr, Sherri L Wohlfiel, Glenn D Roberts.   

Abstract

An evaluation of the MicroSeq 500 microbial identification system by nucleic acid sequencing and the Mayo Clinic experience with its integration into a routine clinical laboratory setting are described. Evaluation of the MicroSeq 500 microbial identification system was accomplished with 59 American Type Culture Collection (ATCC) strains and 328 clinical isolates of mycobacteria identified by conventional and 16S ribosomal DNA sequencing by using the MicroSeq 500 microbial identification system. Nucleic acid sequencing identified 58 of 59 (98.3%) ATCC strains to the species level or to the correct group or complex level. The identification results for 219 of 243 clinical isolates (90.1%) with a distance score of <1% were concordant with the identifications made by phenotypic methods. The remaining 85 isolates had distance scores of >1%; 35 (41.1%) were identified to the appropriate species level or group or complex level; 13 (15.3%) were identified to the species level. All 85 isolates were determined to be mycobacterial species, either novel species or species that exhibited significant genotypic divergence from an organism in the database with the closest match. Integration of nucleic acid sequencing into the routine mycobacteriology laboratory and use of the MicroSeq 500 microbial identification system and Mayo Clinic databases containing additional genotypes of common species and added species significantly reduced the number of organisms that could not be identified by phenotypic methods. The turnaround time was shortened to 24 h, and results were reported much earlier. A limited number of species could not be differentiated from one another by 16S ribosomal DNA sequencing; however, the method provides for the identification of unusual species and more accurate identifications and offers the promise of being the most accurate method available.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12682128      PMCID: PMC153882          DOI: 10.1128/JCM.41.4.1447-1453.2003

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  22 in total

1.  Identification of non-tuberculous mycobacteria: 16S rRNA gene sequence analysis vs. conventional methods.

Authors:  N M El Amin; H S Hanson; B Pettersson; B Petrini; L V Von Stedingk
Journal:  Scand J Infect Dis       Date:  2000

2.  Sequence-based identification of Mycobacterium species using the MicroSeq 500 16S rDNA bacterial identification system.

Authors:  J B Patel; D G Leonard; X Pan; J M Musser; R E Berman; I Nachamkin
Journal:  J Clin Microbiol       Date:  2000-01       Impact factor: 5.948

3.  Identification of clinical isolates of Mycobacterium spp. by sequence analysis of the 16S ribosomal RNA gene. Experience from a clinical laboratory.

Authors:  M Holberg-Petersen; M Steinbakk; K J Figenschau; E Jantzen; J Eng; K K Melby
Journal:  APMIS       Date:  1999-02       Impact factor: 3.205

4.  Identification of 54 mycobacterial species by PCR-restriction fragment length polymorphism analysis of the hsp65 gene.

Authors:  F Brunello; M Ligozzi; E Cristelli; S Bonora; E Tortoli; R Fontana
Journal:  J Clin Microbiol       Date:  2001-08       Impact factor: 5.948

5.  Identification of Mycobacterium spp. by using a commercial 16S ribosomal DNA sequencing kit and additional sequencing libraries.

Authors:  J L Cloud; H Neal; R Rosenberry; C Y Turenne; M Jama; D R Hillyard; K C Carroll
Journal:  J Clin Microbiol       Date:  2002-02       Impact factor: 5.948

6.  Necessity of quality-controlled 16S rRNA gene sequence databases: identifying nontuberculous Mycobacterium species.

Authors:  C Y Turenne; L Tschetter; J Wolfe; A Kabani
Journal:  J Clin Microbiol       Date:  2001-10       Impact factor: 5.948

7.  Differentiation of phylogenetically related slowly growing mycobacteria by their gyrB sequences.

Authors:  H Kasai; T Ezaki; S Harayama
Journal:  J Clin Microbiol       Date:  2000-01       Impact factor: 5.948

8.  Burden of unidentifiable mycobacteria in a reference laboratory.

Authors:  E Tortoli; A Bartoloni; E C Böttger; S Emler; C Garzelli; E Magliano; A Mantella; N Rastogi; L Rindi; C Scarparo; P Urbano
Journal:  J Clin Microbiol       Date:  2001-11       Impact factor: 5.948

9.  Evaluation of recA sequences for identification of Mycobacterium species.

Authors:  K S Blackwood; C He; J Gunton; C Y Turenne; J Wolfe; A M Kabani
Journal:  J Clin Microbiol       Date:  2000-08       Impact factor: 5.948

10.  Mycobacterium doricum sp. nov.

Authors:  E Tortoli; C Piersimoni; R M Kroppenstedt; J I Montoya-Burgos; U Reischl; A Giacometti; S Emler
Journal:  Int J Syst Evol Microbiol       Date:  2001-11       Impact factor: 2.747

View more
  65 in total

1.  Simultaneous sequence analysis of the 16S rRNA and rpoB genes by use of RipSeq software to identify Mycobacterium species.

Authors:  Keith E Simmon; Øyvind Kommedal; Øystein Saebo; Bjarte Karlsen; Cathy A Petti
Journal:  J Clin Microbiol       Date:  2010-07-07       Impact factor: 5.948

2.  Comparison of Bruker Biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometer to BD Phoenix automated microbiology system for identification of gram-negative bacilli.

Authors:  Ryan T Saffert; Scott A Cunningham; Sherry M Ihde; Kristine E Monson Jobe; Jayawant Mandrekar; Robin Patel
Journal:  J Clin Microbiol       Date:  2011-01-05       Impact factor: 5.948

3.  Mycobacterium and Aerobic Actinomycete Culture: Are Two Medium Types and Extended Incubation Times Necessary?

Authors:  Patricia J Simner; Kelly A Doerr; Lory K Steinmetz; Nancy L Wengenack
Journal:  J Clin Microbiol       Date:  2016-02-10       Impact factor: 5.948

Review 4.  Molecular diagnostics in tuberculosis.

Authors:  V C C Cheng; W W Yew; K Y Yuen
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2005-11       Impact factor: 3.267

Review 5.  Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases.

Authors:  Jill E Clarridge
Journal:  Clin Microbiol Rev       Date:  2004-10       Impact factor: 26.132

6.  Evaluation of 16S rRNA sequencing and reevaluation of a short biochemical scheme for identification of clinically significant Bacteroides species.

Authors:  Yuli Song; Chengxu Liu; Mauricio Bolanos; Julia Lee; Maureen McTeague; Sydney M Finegold
Journal:  J Clin Microbiol       Date:  2005-04       Impact factor: 5.948

Review 7.  Sequence-based identification of new bacteria: a proposition for creation of an orphan bacterium repository.

Authors:  M Drancourt; D Raoult
Journal:  J Clin Microbiol       Date:  2005-09       Impact factor: 5.948

8.  Computational approach involving use of the internal transcribed spacer 1 region for identification of Mycobacterium species.

Authors:  Amr M Mohamed; Dan J Kuyper; Peter C Iwen; Hesham H Ali; Dhundy R Bastola; Steven H Hinrichs
Journal:  J Clin Microbiol       Date:  2005-08       Impact factor: 5.948

9.  Faster identification of pathogens in positive blood cultures by fluorescence in situ hybridization in routine practice.

Authors:  Remco P H Peters; Paul H M Savelkoul; Alberdina M Simoons-Smit; Sven A Danner; Christina M J E Vandenbroucke-Grauls; Michiel A van Agtmael
Journal:  J Clin Microbiol       Date:  2006-01       Impact factor: 5.948

10.  Identification of Mycobacterium species by secA1 sequences.

Authors:  Adrian M Zelazny; Leslie B Calhoun; Li Li; Yvonne R Shea; Steven H Fischer
Journal:  J Clin Microbiol       Date:  2005-03       Impact factor: 5.948

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.