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We evaluated the disk susceptibility data of 671 nontyphoid Salmonella isolates collected from different parts of Taiwan from March 2001 to August 2001 and 1,261 nontyphoid Salmonella isolates from the [...]

Background A mass spectrometry-based assessment of methicillin resistance in Staphylococcus aureus would have huge potential in addressing fast and effective prediction of antibiotic resistance. Since delays in the traditional antibiotic susceptibility testing, methicillin-resistant S. aureus remains a serious threat to human health. Results Here, linking a 7 years of longitudinal study from two cohorts in the Taiwan area of over 20 000 individually resolved methicillin susceptibility testing results, we identify associations of methicillin resistance with the demographics and mass spectrometry data. When combined together, these connections allow for machine-learning-based predictions of methicillin resistance, with an area under the receiver operating characteristic curve of >0.85 in both the discovery [95% confidence interval (CI) 0.88–0.90] and replication (95% CI 0.84–0.86) populations. Conclusions Our predictive model facilitates early detection for methicillin resistance of patients with S. aureus infection. The large-scale antibiotic resistance study has unbiasedly highlighted putative candidates that could improve trials of treatment efficiency and inform on prescriptions. [ABSTRACT FROM AUTHOR]

Abstract Background Mycobacteria can be quickly and simply identified by PCR restriction-enzyme analysis (PRA), but misidentification can occur because of similarities in band sizes that are critical for discriminating among species. Capillary electrophoresis can provide computer-aided band discrimination. The aim of this research was to develop an algorithm for identifying mycobacteria by combined rpoB duplex PRA (DPRA) and hsp65 PRA with capillary electrophoresis. Results Three hundred and seventy-six acid-fast bacillus smear-positive BACTEC cultures, including 200 Mycobacterium tuberculosis complexes (MTC) and 176 non-tuberculous mycobacteria (NTM) were analyzed. With combined hsp65 and rpoB DPRA, the accuracy rate was 100% (200 isolates) for the MTC and 91.4% (161 isolates) for the NTM. Among the discordant results (8.6%) for the NTM, one isolate of Mycobacterial species and an isolate of M. flavescens were found as new sub-types in hsp65 PRA. Conclusions This effective and novel identification algorithm using combined rpoB DPRA and hsp65 PRA with capillary electrophoresis can rapidly identify mycobacteria and find new sub-types in hsp65 PRA. In addition, it is complementary to 16 S rDNA sequencing.

Candida albicans bloodstream infection (BSI) is epidemiologically important because of its increasing frequency and serious outcome. Strain typing and delineation of the species are essential for understanding the phylogenetic relationship and clinical significance. Microsatellite CAI genotyping and multilocus sequence typing (MLST) were performed on 285 C. albicans bloodstream isolates from patients in Chang Gung Memorial Hospital at Linkou (CGMHL), Taiwan from 2003 to 2011. Data regarding demographics, comorbidities, risk factors, and clinical outcomes were recorded within adult patients with C. albicans BSI. Both CAI genotyping and MLST yielded comparable discriminatory power for C. albicans characterization. Besides, the distribution of CAI repetition showed a satisfactory phylogenetic association, which could be a good alternative method in the molecular phylogenetics of C. albicans and epidemiological studies. As for the clinical scenario, clade 17 isolates with CAI alleles either possessing 29 or more repetitions were related to higher 14-day and 30-day mortality, and shorter median survival days. [ABSTRACT FROM AUTHOR]

Recent studies have demonstrated that the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) could be used to detect superbugs, such as methicillin-resistant Staphylococcus aureus (MRSA). Due to an increasingly clinical need to classify between MRSA and methicillin-sensitive Staphylococcus aureus (MSSA) efficiently and effectively, we were motivated to develop a systematic pipeline based on a large-scale dataset of MS spectra. However, the shifting problem of peaks in MS spectra induced a low effectiveness in the classification between MRSA and MSSA isolates. Unlike previous works emphasizing on specific peaks, this study employs a binning method to cluster MS shifting ions into several representative peaks. A variety of bin sizes were evaluated to coalesce drifted or shifted MS peaks to a well-defined structured data. Then, various machine learning methods were performed to carry out the classification between MRSA and MSSA samples. Totally 4858 MS spectra of unique S. aureus isolates, including 2500 MRSA and 2358 MSSA instances, were collected by Chang Gung Memorial Hospitals, at Linkou and Kaohsiung branches, Taiwan. Based on the evaluation of Pearson correlation coefficients and the strategy of forward feature selection, a total of 200 peaks (with the bin size of 10 Da) were identified as the marker attributes for the construction of predictive models. These selected peaks, such as bins 2410–2419, 2450–2459 and 6590–6599 Da, have indicated remarkable differences between MRSA and MSSA, which were effective in the prediction of MRSA. The independent testing has revealed that the random forest model can provide a promising prediction with the area under the receiver operating characteristic curve (AUC) at 0.8450. When comparing to previous works conducted with hundreds of MS spectra, the proposed scheme demonstrates that incorporating machine learning method with a large-scale dataset of clinical MS spectra may be a feasible means for clinical physicians on the administration of correct antibiotics in shorter turn-around-time, which could reduce mortality, avoid drug resistance and shorten length of stay in hospital in the future. [ABSTRACT FROM AUTHOR]

Abstract Background The control of tuberculosis in densely populated cities is complicated by close human-to-human contacts and potential transmission of pathogens from multiple sources. We conducted a molecular epidemiologic analysis of 356 Mycobacterium tuberculosis (MTB) isolates from patients presenting pulmonary tuberculosis in metropolitan Taipei. Classical antibiogram studies and genetic characterization, using mycobacterial interspersed repetitive-unit-variable-number tandem-repeat (MIRU-VNTR) typing and spoligotyping, were applied after culture. Methods A total of 356 isolates were genotyped by standard spoligotyping and the strains were compared with in the international spoligotyping database (SpolDB4). All isolates were also categorized using the 15 loci MIRU-VNTR typing method and combin with NTF locus and RD deletion analyses. Results Of 356 isolates spoligotyped, 290 (81.4%) displayed known spoligotypes and 66 were not identified in the database. Major spoligotypes found were Beijing lineages (52.5%), followed by Haarlem lineages (13.5%) and EAI plus EAI-like lineages (11%). When MIRU-VNTR was employed, 140 patterns were identified, including 36 clusters by 252 isolates and 104 unique patterns, and the largest cluster comprised 95 isolates from the Beijing family. The combination of spoligotyping and MIRU-VNTR revealed that 236 (67%) of the 356 isolates were clustered in 43 genotypes. Strains of the Beijing family was more likely to be of modern strain and a higher percentage of multiple drug resistance than other families combined (P = 0.08). Patients infected with Beijing strains were younger than those with other strains (mean 58.7 vs. 64.2, p = 0.02). Moreover, 85.3% of infected persons younger than 25 years had Beijing modern strain, suggesting a possible recent spread in the young population by this family of TB strain in Taipei. Conclusion Our data on MTB genotype in Taipei suggest that MTB infection has not been optimally controlled. Control efforts should be reinforced in view of the high prevalence of the Beijing strain in young population and association with drug resistance.

Abstract Background: To evaluate the prevalence and microbiological characterization of community-acquired (CA) methicillin-resistant Staphylococcus aureus (MRSA) nasal carriage in a kindergarten. Methods: Point prevalence study. Nasal swabs were collected from healthy children younger than 7 years of age who were attending a kindergarten in Taipei, Taiwan. A parent questionnaire regarding MRSA risk factors was administered simultaneously. All CA-MRSA colonization isolates were archived for subsequent antimicrobial susceptibility and molecular typing. Results: Of the 68 children who participated in the study, 17 (25%) had S. aureus isolated from nasal swabs. Nine (13.2%) of the 68 children had CA-MRSA carriage, and none of them had any identified risk factors. Antimicrobial susceptibility testing revealed all of the 9 CA-MRSA colonization isolates had uniformly high resistance (100%) to both clindamycin and erythromycin, the macrolide-lincosamide-streptogramin-constitutive phenotype and the ermB gene. Pulsed-field gel electrophoresis revealed 8 (88.9%) of 9 CA-MRSA colonization isolates were genetically related and multilocus sequence typing revealed all isolates had sequence type 59. All of the colonization isolates carried the staphylococcal cassette chromosome mec type IV, but none were positive for the Panton-Valentine leukocidin genes. Conclusion: The results of this study suggest that a single predominant CA-MRSA colonization strain featuring high clindamycin resistance circulated in this kindergarten. Additionally, due to the established transmissibility of colonization isolates, the high prevalence of nasal carriage of CA-MRSA among healthy attendees in kindergartens may indicate the accelerated spread of CA-MRSA in the community.