Detection and differentiation of causative organisms of onychomycosis in an ex vivo nail model by means of Raman spectroscopy

BackgroundOnychomycosis is worldwide the most prevalent infection of the nail. It is mainly caused by the dermatophytes Trichophyton rubrum and Trichophyton mentagrophytes and to a lesser extent Trichophyton tonsurans. The yeast Candida albicans and the mould Scopulariopsis brevicaulis can also cause onychomycosis. Management of these nail conditions may require appropriate treatment methods and therefore the identification of the causative species can be of importance. However, the determination of agents causing onychomycosis is still not optimal. ObjectivesTo detect and differentiate causative organisms of onychomycosis in an ex vivo nail model by means of Raman spectroscopy. The work focusses is on the discriminative power of Raman spectroscopy for detection of differences between T. rubrum, T. mentagrophytus and T. tonsurans on human nail and distinguishing these dermatophytic from the non-dermatophytic species S. brevicaulis and C. albicans. MethodsRaman spectra (200/sample) were taken from 50-m human nail slices infected with T. rubrum, T. mentagrophytus, T. tonsurans, S. brevicaulis or C. albicans using a 2500 High-Performance Raman Module and 785-nm diode laser. Processed spectra were analysed by sorting the correlation matrix and presented as dendrogram and heat map. Raman spectra from suspended dermatophytic microconidia were taken for mutual comparisons. ResultsSpectral differences between the dermatophytes T. rubrum, T. mentagrophytus and T. tonsurans (635-795, 840-894, 1018-1112, 1206-1372, 1566-1700/cm) and the non-dermatophytes S. brevicaulis and C. albicans (442-610, 692-758, 866-914, 1020-1100, 1138-1380,1492-1602/cm) growing on nail were confirmed by clustering correlation showing two main clusters. Dissimilarities between tested dermatophytes were also found with T. rubrum being most different. Raman spectra of the dermatophytic microconidia varied over the whole tested 400-1800/cm range. ConclusionImportant dermatophytic and non-dermatophytic agents of onychomycosis growing on ex vivo human nail can be distinguished specifically and non-invasively by Raman spectroscopy

Rapid Identification of Mycobacteria by Raman Spectroscopy▿

A number of rapid identification methods have been developed to improve the accuracy for diagnosis of tuberculosis and to speed up the presumptive identification of Mycobacterium species. Most of these methods have been validated for a limited group of microorganisms only. Here, Raman spectroscopy was compared to 16S rRNA sequencing for the identification of Mycobacterium tuberculosis complex strains and the most frequently found strains of nontuberculous mycobacteria (NTM). A total of 63 strains, belonging to eight distinct species, were analyzed. The sensitivity of Raman spectroscopy for the identification of Mycobacterium species was 95.2%. All M. tuberculosis strains were correctly identified (7 of 7; 100%), as were 54 of 57 NTM strains (94%). The differentiation between M. tuberculosis and NTM was invariably correct for all strains. Moreover, the reproducibility of Raman spectroscopy was evaluated for killed mycobacteria (by heat and formalin) versus viable mycobacteria. The spectra of the heat-inactivated bacteria showed minimal differences compared to the spectra of viable mycobacteria. Therefore, the identification of mycobacteria appears possible without biosafety level 3 precautions. Raman spectroscopy provides a novel answer to the need for rapid species identification of cultured mycobacteria in a clinical diagnostic setting

Epidemiology of Staphylococcus aureus harboring the mecA or Panton-Valentine leukocidin genes in hospitals in Java and Bali, Indonesia

Data of Staphylococcus aureus carriage in Indonesian hospitals are scarce. Therefore, the epidemiology of S. aureus among surgery patients in three academic hospitals in Indonesia was studied. In total, 366 of 1,502 (24.4%) patients carried S. aureus. The methicillin-resistant S. aureus (MRSA) carriage rate was 4.3%, whereas 1.5% of the patients carried Panton-Valentine leukocidin (PVL)-positive methicillin-sensitive S. aureus (MSSA). Semarang and Malang city (odds ratio [OR] 9.4 and OR 9.0), being male (OR 2.4), hospitalization for more than 5 days (OR 11.708), and antibiotic therapy during hospitalization (OR 2.6) were independent determinants for MRSA carriage, whereas prior hospitalization (OR 2.5) was the only one risk factor for PVL-positive MSSA carriage. Typing of MRSA strains by Raman spectroscopy showed three large clusters assigned type 21, 24, and 38, all corresponding to ST239-MRSA-SCCmec type III. In conclusion, MRSA and PVL-positive MSSA are present among patients in surgical wards in Indonesian academic hospitals. Copyrigh

Detecting and Tracking Nosocomial Methicillin-Resistant Staphylococcus aureus

Rapid detection and differentiation of methicillin-resistant Staphylococcus aureus (MRSA) is critical for the early diagnosis of difficult-to-treat nosocomial and community acquired clinical infections and improved epidemiological surveillance. We developed a microfluidics chip coupled with surface enhanced Raman scattering (SERS) spectroscopy (532 nm) “lab-on-a-chip” system to rapidly detect and differentiate methicillin-sensitive S. aureus (MSSA) and MRSA using clinical isolates from China and the United States. A total of 21 MSSA isolates and 37 MRSA isolates recovered from infected humans were first analyzed by using polymerase chain reaction (PCR) and multilocus sequence typing (MLST). The mecA gene, which refers resistant to methicillin, was detected in all the MRSA isolates and different allelic profiles were identified assigning isolates as either previously identified or novel clones. A total of 17,400 SERS spectra of the 58 S. aureus isolates were collected within 3.5 hours using this optofluidic platform. Intra- and inter-laboratory spectral reproducibility yielded a differentiation index value of 3.43 to 4.06 and demonstrated the feasibility of using this optofluidic system at different laboratories for bacterial identification. A global SERS-based dendrogram model for MRSA and MSSA identification and differentiation to the strain level was established and cross-validated (Simpson index of diversity of 0.989) and had an average recognition rate of 95% for S. aureus isolates associated with a recent outbreak in China. SERS typing correlated well with MLST indicating that it has high sensitivity and selectivity and would be suitable for determining the origin and possible spread of MRSA. A SERS-based partial least-squares regression model could quantify the actual concentration of a specific MRSA isolate in a bacterial mixture at levels from 5 to 100% (regression coefficient, > 0.98; residual prediction deviation, >10.05). This optofluidic platform has advantages over traditional genotyping for ultrafast, automated and reliable detection and epidemiological surveillance of bacterial infections

Good performance of the spectracellRA system for typing of methicillin-resistant staphylococcus aureus isolates

Typing of methicillin-resistant Staphylococcus aureus (MRSA) remains necessary in order to assess whether transmission of MRSA occurred and to what extent infection prevention measures need to be taken. Raman spectroscopy (SpectraCellRA [SCRA]; RiverD International, Rotterdam, The Netherlands) is a recently developed tool for bacterial typing. In this study, the performance (typeability, discriminatory power, reproducibility, workflow, and costs) of the SCRA system was evaluated for typing of MRSA strains isolated from patients and patients' household members who were infected with or colonized by MRSA. We analyzed a well-documented collection of 113 MRSA strains collected from 54 households. The epidemiological relationship between the MRSA strains within one household was used as the gold standard. Pulsed-field gel electrophoresis (PFGE) was used for discrepancy analysis. The results of SCRA analysis on the strain level corresponded with epidemiological data for 108 of 113 strains, a concordance of 95.6%. When analyzed at the household level, the results of SCRA were correct for 49 out of 54 households, a concordance of 90.7%. Concordance on the strain level with epidemiological data for PFGE was 93.6% (103/110 isolates typed). Concordance on the household level with epidemiological data for PFGE was 93.5% (49/53 households analyzed). With PFGE regarded as the reference standard, the conclusions reached with Raman spectroscopy were identical to those reached with PFGE in 100 of 105 cases (95.2%). The reproducibility of SCRA was found to be 100%. We conclude that the SpectraCellRA system is a fast, easy-to-use, and highly reproducible typing platform for outbreak analysis that can compete with the currently used typing techniques. Copyrigh