A rapid two-step algorithm detects and identifies clinical macrolide and beta-lactam antibiotic resistance in clinical bacterial isolates.
OBJECTIVE
Aiming to identify macrolide and beta-lactam resistance in clinical bacterial isolates rapidly and accurately, a two-step algorithm was developed based on detection of eight antibiotic resistance genes.


METHODS
Targeting at genes linked to bacterial macrolide (msrA, ermA, ermB, and ermC) and beta-lactam (blaTEM, blaSHV, blaCTX-M-1, blaCTX-M-9) antibiotic resistances, this method includes a multiplex real-time PCR, a melting temperature profile analysis as well as a liquid bead microarray assay. Liquid bead microarray assay is applied only when indistinguishable Tm profile is observed.


RESULTS
The clinical validity of this method was assessed on clinical bacterial isolates. Among the total 580 isolates that were determined by our diagnostic method, 75% of them were identified by the multiplex real-time PCR with melting temperature analysis alone, while the remaining 25% required both multiplex real-time PCR with melting temperature analysis and liquid bead microarray assay for identification. Compared with the traditional phenotypic antibiotic susceptibility test, an overall agreement of 81.2% (kappa=0.614, 95% CI=0.550-0.679) was observed, with a sensitivity and specificity of 87.7% and 73% respectively. Besides, the average test turnaround time is 3.9h, which is much shorter in comparison with more than 24h for the traditional phenotypic tests.


CONCLUSIONS
Having the advantages of the shorter operating time and comparable high sensitivity and specificity with the traditional phenotypic test, our two-step algorithm provides an efficient tool for rapid determination of macrolide and beta-lactam antibiotic resistances in clinical bacterial isolates.
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China. Electronic address: luxuedong2004@aliyun.com.
Xuedong
X
Lu
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China.
Shuping
S
Nie
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China.
Chengjing
C
Xia
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China.
Lie
L
Huang
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China.
Ying
Y
He
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China.
Runxiang
R
Wu
Department of Laboratory Medicine, Futian Hospital, Guangdong Medical College, Shenzhen 518033, China; Department of Cell and Molecular Biology, Uppsala University, Biomedical Center, Box 596, SE-751 24 Uppsala, Sweden. Electronic address: li.zhang@icm.uu.se.
Li
L
Zhang
D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D001419:Bacteria / Q000187:drug effects* / Q000302:isolation & purification; D001424:Bacterial Infections / Q000382:microbiology; D004269:DNA, Bacterial / Q000235:genetics* / Q000302:isolation & purification; D024881:Drug Resistance, Bacterial; D005798:Genes, Bacterial; D006801:Humans; D018942:Macrolides / Q000494:pharmacology*; D046228:Microarray Analysis / Q000379:methods*; D008826:Microbial Sensitivity Tests / Q000379:methods; D060885:Multiplex Polymerase Chain Reaction / Q000379:methods*; D013997:Time Factors; D044366:Transition Temperature; D047090:beta-Lactams / Q000494:pharmacology*
D000900:Anti-Bacterial Agents; D004269:DNA, Bacterial; D018942:Macrolides; D047090:beta-Lactams
Antibiotic resistance genes; Clinical bacterial isolates; Two-step algorithm