![]() Sequence analysis software compares genes analyzed from unknown bacteria to a proprietary 16S rDNA sequence library. Genomic DNA extracted from bacteria is amplified and then sequenced. The MicroSeq 16S rRNA gene kit (Perkin-Elmer Applied Biosystems Division, Foster City, Calif.) allows identification of bacteria based on the sequences of their 16S rRNA gene ( 21, 32). The amplified segment is sequenced and compared with known databases to identify a close relative ( 8, 20, 22, 25, 29, 30). Broad-range PCR primers recognize conserved sequences in a variety of bacteria, while amplifying highly variable regions between the primer binding sites ( 3, 6, 14, 31, 39, 41). Typically, genotypic identification of bacteria involves the use of conserved sequences within phylogenetically informative genetic targets, such as the small-subunit (16S) rRNA gene ( 20, 23, 30, 41, 43). Genotypic identification is emerging as an alternative or complement to established phenotypic methods. ![]() Such systems may reduce subjectivity and turnaround time, but they still rely on phenotypic identification. ![]() (Newark, Del.), based on the cellular fatty acid profile ( 27, 37). Such systems include the carbon source utilization system developed by Biolog, Inc., based on panels of biochemical reactions ( 18, 24), and the gas-liquid chromatography system developed by MIDI, Inc. Several commercial systems offer computer-assisted identification of a wide variety of bacterial organisms. In addition, when phenotypic methods are used to identify bacteria, interpretation of test results involves substantial subjective judgement ( 34). For many slow-growing and fastidious organisms, traditional phenotypic identification is difficult and time-consuming. The improved turnaround time provided by genotypic identification systems may translate into improved clinical outcomes.Īccurate identification of bacterial isolates is an essential task of the clinical microbiology laboratory. ![]() These data show that MicroSeq provides rapid, unambiguous identification of clinical bacterial isolates. In comparison to the full 16S rDNA sequences, the first 527 bp provided identical genus information for all 72 isolates and identical species information for 67 (93.1%) isolates. Four Acinetobacter and three Bordetella isolates which could not be identified to the species level by conventional methods were identified by MicroSeq. Compared to lengthy conventional methods, Sherlock, Microlog, and MicroSeq were able to identify 56 of 72 (77.8%), 63 of 72 (87.5%), and 70 of 72 (97.2%) isolates to the genus level ( P = 0.002) and 44 to 65 (67.7%), 55 of 65 (84.6%), and 58 of 65 (89.2%) isolates to the species level ( P = 0.005), respectively. We used identification systems based on cellular fatty acid profiles (Sherlock MIDI, Inc., Newark, Del.), carbon source utilization (Microlog Biolog, Inc., Hayward, Calif.), and 16S rRNA gene sequence (MicroSeq Perkin-Elmer Applied Biosystems Division, Foster City, Calif.) to evaluate 72 unusual aerobic gram-negative bacilli isolated from clinical specimens at the Mayo Clinic. Rapid and accurate identification of bacterial pathogens is a fundamental goal of clinical microbiology, but one that is difficult or impossible for many slow-growing and fastidious organisms.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |