ArticleJournal of clinical microbiology2005
Computational approach involving use of the internal transcribed spacer 1 region for identification of Mycobacterium species.
Article in Journal of clinical microbiology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- A novel in silico molecular tool for comprehensive differentiation of Mycobacterium species.Scientific reports · 2025Article
- Evaluation of nucleotide MALDI-TOF-MS for the identification ofFrontiers in cellular and infection microbiology · 2024Article
- Rapid Identification of Clinically RelevantJournal of clinical microbiology · 2019Article
- Differentiation and phylogenetic relationships in Mycobacterium spp with special reference to the RNase P RNA gene rnpB.Current microbiology · 2014Article
- Clinical microbiology informatics.Clinical microbiology reviews · 2014Review
- Prevalence and drug resistance of nontuberculous mycobacteria, northern China, 2008-2011.Emerging infectious diseases · 2014Article
- Laboratory diagnosis of tuberculosis in resource-poor countries: challenges and opportunities.Clinical microbiology reviews · 2011Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rapid and reliable identification of clinically significant Mycobacterium species is a challenge for diagnostic laboratories. This study evaluates a unique sequence-dependent identification algorithm called MycoAlign for the differential identification of Mycobacterium species. The MycoAlign system uses pan-Mycobacterium-specific primer amplification in combination with a customized database and algorithm. The results of testing were compared with conventional phenotypic assays and GenBank sequence comparisons using the 16S rRNA target. Discrepant results were retested and evaluated using a third independent database. The custom database was generated using the hypervariable sequences of the internal transcribed spacer 1 (ITS-1) region of the rRNA gene complex from characterized Mycobacterium species. An automated sequence-validation process was used to control quality and specificity of evaluated sequence. A total of 181 Mycobacterium strains (22 reference strains and 159 phenotypically identified clinical isolates) and seven nonmycobacterial clinical isolates were evaluated in a comparative study to validate the accuracy of the MycoAlign algorithm. MycoAlign correctly identified all referenced strains and matched species in 94% of the phenotypically identified Mycobacterium clinical isolates. The ITS-1 sequence target showed a higher degree of specificity in terms of Mycobacterium identification than the 16S rRNA sequence by use of GenBank BLAST. This study showed the MycoAlign algorithm to be a reliable and rapid approach for the identification of Mycobacterium species and confirmed the superiority of the ITS-1 region sequence over the 16S rRNA gene sequence as a target for sequence-based species identification.
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Registered trials
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