Abstract
BackgroundClinical microbiology laboratories have to accurately identify clinical microbes. However, some isolates are difficult to identify by the automated biochemical text platforms, which are called “difficult-to-identify” microbes in this study. Therefore, the ability of 16S ribosomal DNA (16S rDNA) and internal transcribed spacer 2 (ITS2) sequencing to identify these “difficult-to-identify” bacteria and fungi was assessed in this study.MethodsSamples obtained from a teaching hospital over the past three years were examined. The 16S rDNA of four standard strains, 18 clinical common isolates, and 47 “difficult-to-identify” clinical bacteria were amplified by PCR and sequenced. The ITS2 of eight standard strains and 31 “difficult-to-identify” clinical fungi were also amplified by PCR and sequenced. The sequences of 16S rDNA and ITS2 were compared to reference data available in GenBank by using the BLASTN program. These microbes were identified according to the percentage of similarity to reference sequences of strains in GenBank.ResultsThe results from molecular sequencing methods correlated well with automated microbiological identification systems for common clinical isolates. Sequencing results of the standard strains were consistent with their known phenotype. Overall, 47 “difficult-to-identify” clinical bacteria were identified as 35 genera or species by sequence analysis (with 10 of these identified isolates first reported in clinical specimens in China and two first identified in the international literature). 31 “difficult-to-identify” clinical fungi tested could be identified as 15 genera or species by sequence analysis (with two of these first reported in China).ConclusionsOur results show the importance of 16S rDNA and internal ITS2 sequencing for the molecular identification of “difficult-to-identify” bacteria and fungi. The development of this method with advantages of convenience, availability, and cost-effectiveness will make it worth extending into clinical practice in developing countries.
Highlights
In clinical microbiology laboratories, traditional culture and biochemical techniques remain the primary methodology for identifying most pathogens
Staphylococcus aureus ATCC29213, Escherichia coli ATCC25922, Pseudomonas aeruginosa ATCC27853, Mycobacterium tuberculosis H37Rv, Candida albicans ATCC90029, Candida tropicalis ATCC13803, Candida glabrata ATCC15126, Candida parapsilosis ATCC22019, Aspergillus fumigatus ATCC96918, Aspergillus flavus ATCC28539, Aspergillus terreus ATCC1012, Aspergillus niger ATCC16404, and other clinically common species were used as controls in this study
Identification of bacteria by 16S ribosomal DNA (rDNA) sequence analysis The 16 s rRNA amplicons of some isolates including 5 standard strains and clinical isolates showed on electropherograms (Figure 1)
Summary
Traditional culture and biochemical techniques remain the primary methodology for identifying most pathogens. With the development of technology, automated microbiology system for the identification of pathogens has been introduced in many laboratories. The identification of organisms by sequencing DNA encoding 16S rRNA has been described in case reports that focus on the identification of different bacterial species or genera [1,2,3,4]. The development of an inexpensive and efficient application of molecular identification procedures would help with the clinical identification of “difficult-to-identify” bacteria and fungi according to 16S rRNA and ITS2 sequences. Some isolates are difficult to identify by the automated biochemical text platforms, which are called “difficult-to-identify” microbes in this study. The ability of 16S ribosomal DNA (16S rDNA) and internal transcribed spacer 2 (ITS2) sequencing to identify these “difficult-to-identify” bacteria and fungi was assessed in this study
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