Literature DB >> 12624023

Conventional methods versus 16S ribosomal DNA sequencing for identification of nontuberculous mycobacteria: cost analysis.

Victoria J Cook1, Christine Y Turenne, Joyce Wolfe, Ryan Pauls, Amin Kabani.   

Abstract

The clinical profile of nontuberculous mycobacteria (NTM) has been raised by the human immunodeficiency virus and AIDS pandemic. Different laboratory techniques, often molecular based, are available to facilitate the rapid and accurate identification of NTM. The expense of these advanced techniques has been questioned. At the National Reference Center for Mycobacteriology and the Health Sciences Center, University of Manitoba, in Winnipeg, Canada, we performed a direct cost analysis of laboratory techniques for commercial DNA probe-negative (Gen-Probe, Inc., San Diego, Calif.), difficult-to-identify NTM. We compared the costs associated with conventional phenotypic methodology (biochemical testing, pigment production, growth, and colony characteristics) and genotypic methodology (16S ribosomal DNA [rDNA] sequence-based identification). We revealed a higher cost per sample with conventional methods, and this cost varied with organism characteristics: $80.93 for slowly growing, biochemically active NTM; $173.23 for slowly growing, biochemically inert NTM; and $129.40 for rapidly growing NTM. The cost per sample using 16S rDNA sequencing was $47.91 irrespective of organism characteristics, less than one-third of the expense associated with phenotypic identification of biochemically inert, slow growers. Starting with a pure culture, the turnaround time to species identification is 1 to 2 days for 16S rDNA sequencing compared to 2 to 6 weeks for biochemical testing. The accuracy of results comparing both methodologies is briefly discussed. 16S rDNA sequencing provides a cost-effective alternative in the identification of clinically relevant forms of probe-negative NTM. This concept is not only useful in mycobacteriology but also is highly applicable in other areas of clinical microbiology.

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Year:  2003        PMID: 12624023      PMCID: PMC150297          DOI: 10.1128/JCM.41.3.1010-1015.2003

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


  18 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.  RIDOM: Ribosomal Differentiation of Medical Micro-organisms Database.

Authors:  Dag Harmsen; Jörg Rothgänger; Matthias Frosch; Jürgen Albert
Journal:  Nucleic Acids Res       Date:  2002-01-01       Impact factor: 16.971

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.  Application of the Sherlock Mycobacteria Identification System using high-performance liquid chromatography in a clinical laboratory.

Authors:  J A Kellogg; D A Bankert; G S Withers; W Sweimler; T E Kiehn; G E Pfyffer
Journal:  J Clin Microbiol       Date:  2001-03       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

Review 9.  Mycolic acid analysis by high-performance liquid chromatography for identification of Mycobacterium species.

Authors:  W R Butler; L S Guthertz
Journal:  Clin Microbiol Rev       Date:  2001-10       Impact factor: 26.132

10.  Disseminated "Mycobacterium genavense" infection in patients with AIDS.

Authors:  E C Böttger; A Teske; P Kirschner; S Bost; H R Chang; V Beer; B Hirschel
Journal:  Lancet       Date:  1992-07-11       Impact factor: 79.321

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  18 in total

Review 1.  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

2.  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

3.  Comparison of traditional phenotypic identification methods with partial 5' 16S rRNA gene sequencing for species-level identification of nonfermenting Gram-negative bacilli.

Authors:  Joann L Cloud; Dag Harmsen; Peter C Iwen; James J Dunn; Gerri Hall; Paul Rocco Lasala; Karen Hoggan; Deborah Wilson; Gail L Woods; Alexander Mellmann
Journal:  J Clin Microbiol       Date:  2010-02-17       Impact factor: 5.948

4.  Use of the MGB Eclipse system and SmartCycler PCR for differentiation of Mycobacterium chelonae and M. abscessus.

Authors:  Joann L Cloud; Karen Hoggan; Evgeniy Belousov; Samuel Cohen; Barbara A Brown-Elliott; Linda Mann; Rebecca Wilson; Wade Aldous; Richard J Wallace; Gail L Woods
Journal:  J Clin Microbiol       Date:  2005-08       Impact factor: 5.948

5.  Biochip system for rapid and accurate identification of mycobacterial species from isolates and sputum.

Authors:  Lingxiang Zhu; Guanglu Jiang; Shengfen Wang; Can Wang; Qiang Li; Hao Yu; Yang Zhou; Bing Zhao; Hairong Huang; Wanli Xing; Keith Mitchelson; Jing Cheng; Yanlin Zhao; Yong Guo
Journal:  J Clin Microbiol       Date:  2010-08-04       Impact factor: 5.948

6.  Novel real-time simultaneous amplification and testing method to accurately and rapidly detect Mycobacterium tuberculosis complex.

Authors:  Zhenling Cui; Yongzhong Wang; Liang Fang; Ruijuan Zheng; Xiaochen Huang; Xiaoqin Liu; Gang Zhang; Dongmei Rui; Jinliang Ju; Zhongyi Hu
Journal:  J Clin Microbiol       Date:  2012-01-11       Impact factor: 5.948

7.  Bovine tuberculosis in South Darfur State, Sudan: an abattoir study based on microscopy and molecular detection methods.

Authors:  El Tigani A Asil; Sulieman M El Sanousi; Ahmed Gameel; Haytham El Beir; Maha Fathelrahman; Nasir M Terab; Magzoub A Muaz; Mohamed E Hamid
Journal:  Trop Anim Health Prod       Date:  2012-07-29       Impact factor: 1.559

8.  Assessment of partial sequencing of the 65-kilodalton heat shock protein gene (hsp65) for routine identification of Mycobacterium species isolated from clinical sources.

Authors:  Alan McNabb; Diane Eisler; Kathy Adie; Marie Amos; Mabel Rodrigues; Gwen Stephens; William A Black; Judith Isaac-Renton
Journal:  J Clin Microbiol       Date:  2004-07       Impact factor: 5.948

9.  16S rRNA gene sequencing is a non-culture method of defining the specific bacterial etiology of ventilator-associated pneumonia.

Authors:  Li-Ping Xia; Long-Yan Bian; Min Xu; Ying Liu; Ai-Ling Tang; Wen-Qin Ye
Journal:  Int J Clin Exp Med       Date:  2015-10-15

10.  Comparison of three methods for rapid identification of mycobacterial clinical isolates to the species level.

Authors:  Xueqiong Wu; Junxian Zhang; Jianqin Liang; Yang Lu; Hongmin Li; Chuihuan Li; Jun Yue; Lishui Zhang; Zhihui Liu
Journal:  J Clin Microbiol       Date:  2007-03-14       Impact factor: 5.948

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