Current Techniques in Mycobacterial Detection and Speciation

Herold, Christopher D.; Fitzgerald, Robert L.; Herold, David A.; Forbes, Betty A.

doi:10.3109/10408369609083058

Cited by 16 publications

(9 citation statements)

References 112 publications

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“…The predictive value of the SMIS species identifications (the probability that SMIS assignments of unknown isolates to each of the mycobacterial species or groups was correct) was 85% overall but ranged from only 27% (of 11 value of an SMIS identification of an isolate as belonging to that group was 100% because no isolate of any other species was misidentified by the system as M. chelonae-abscessus. Of the 370 mycobacterial isolates studied, 115 (31%) had to be analyzed a second time because the initial SMIS results were either incorrect (38 isolates) or the isolates were unidentified (77 isolates).…”

Section: Resultsmentioning

confidence: 99%

“…HPLC technology may largely replace biochemical methods for the routine identification of Mycobacterium species because of the ability of HPLC systems to facilitate the rapid, accurate identification of a large variety of species and to do so at a relatively low cost (11). To permit chromatographic identification of isolates as soon as their agar colonies were detectable, a fluorescence detector was used in the present study instead of a UV detector because the former is 200-fold more sensitive (13).…”

Section: Discussionmentioning

confidence: 99%

“…The identity of some isolates (including Mycobacterium lentiflavum, M. malmoense, Mycobacterium simiae, and members of the Mycobacterium terrae complex) was established or confirmed using 16S rRNA gene sequencing (16,17,30) and/or PCR-restriction enzyme analysis of the 65-kDa hsp-encoding gene (31). Biochemical tests and phenotypic characteristics including colony morphology, pigment, and growth rate (7,11,14,15,21,30) were used to identify isolates of all other species.…”

Section: Methodsmentioning

confidence: 99%

“…There are numerous recognized species of mycobacterial pathogens and additional species that have not yet been associated with human disease (7). Traditionally, a battery of conventional tests including determination of colony morphology and pigment production, growth rate, and biochemical reactions has been used to identify mycobacteria to the species level (7,11,14,15,21,30). Disadvantages of this approach include the inherent delays in providing clinically relevant information, which may lead to increased health care costs, the extensive training and experience required to reliably perform many of the assays, interassay variability of results, strain variation within species causing both unexpected biochemical test results and atypical phenotypic characteristics, the possibilities of either misidentification or the inability to identify pathogens, and the limitation of this approach to the identification of only the more common mycobacterial species whose properties and characteristics have been fully documented (7,11,12,17,20,21,30,32,33).…”

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confidence: 99%

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Application of the Sherlock Mycobacteria Identification System Using High-Performance Liquid Chromatography in a Clinical Laboratory

et al. 2001

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There is a growing need for a more accurate, rapid, and cost-effective alternative to conventional tests for identification of clinical isolates of Mycobacterium species. Therefore, the ability of the Sherlock Mycobacteria Identification System (SMIS; MIDI, Inc.) using computerized software and a Hewlett-Packard series 1100 high-performance liquid chromatograph to identify mycobacteria was compared to identification using phenotypic characteristics, biochemical tests, probes (Gen-Probe, Inc.), gas-liquid chromatography, and, when necessary, PCR-restriction enzyme analysis of the 65-kDa heat shock protein gene and 16S rRNA gene sequencing. Culture, harvesting, saponification, extraction, derivatization, and chromatography were performed following MIDI's instructions. Of 370 isolates and stock cultures tested, 327 (88%) were given species names by the SMIS. SMIS software correctly identified 279 of the isolates (75% of the total number of isolates and 85% of the named isolates). The overall predictive value of accuracy (correct calls divided by total calls of a species) for SMIS species identification was 85%, ranging from only 27% (3 of 11) for M. asiaticum to 100% for species or groups including M. malmoense (8 of 8), M. nonchromogenicum (11 of 11), and the M. chelonaeabscessus complex (21 of 21). By determining relative peak height ratios (RPHRs) and relative retention times (RRTs) of selected mycolic acid peaks, as well as phenotypic properties, all 48 SMIS-misidentified isolates and 39 (91%) of the 43 unidentified isolates could be correctly identified. Material and labor costs per isolate were $10.94 for SMIS, $26.58 for probes, and $42.31 for biochemical identification. The SMIS, combined with knowledge of RPHRs, RRTs, and phenotypic characteristics, offers a rapid, reasonably accurate, cost-effective alternative to more traditional methods of mycobacterial species identification.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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confidence: 99%

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Application of the Sherlock Mycobacteria Identification System Using High-Performance Liquid Chromatography in a Clinical Laboratory

et al. 2001

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“…For an extensive review on published results one should consult Richeldi et al (1995), Herold et al (1996), Sandin (1996) and Forbes (1997). This variability is not surprising given the fact that laboratories differ in terms of extraction procedures, target and primer sequences, sample input, PCR conditions and detection methods.…”

Section: Performance Of In-house Polymerase Chain Reaction Assays Andmentioning

confidence: 99%