The use of Raman spectroscopy in the epidemiology of methicillin-resistant Staphylococcus aureus of human- and animal-related clonal lineages

Wulf, M.W.H.; Willemse-Erix, Diana; Verduin, C. M.; Puppels, Gerwin J.; Belkum, Alex van; Maquelin, Kees

doi:10.1111/j.1469-0691.2011.03517.x

Cited by 25 publications

(22 citation statements)

References 9 publications

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“…Our findings are comparable to those of a study performed by Wulf et al (14). In this study, the observed concordance between SCRA and the gold standard of PFGE was 97%, whereas in our study the observed concordance between SCRA and PFGE was 95%.…”

Section: Discussionsupporting

confidence: 89%

Good Performance of the SpectraCell RA System for Typing of Methicillin-Resistant Staphylococcus aureus Isolates

et al. 2013

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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.

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Section: Discussionsupporting

confidence: 89%

Good Performance of the SpectraCell RA System for Typing of Methicillin-Resistant Staphylococcus aureus Isolates

et al. 2013

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“…We hypothesized that Raman spectroscopy possibly could be used for this type of analysis. In recent years several researchers showed a high discriminative power in the field of identifying bacteria but also in several forms of cancer in which Raman spectroscopy showed to be able to diagnose prostate and bladder cancer in vitro , premalignant lesions on cervical cancer, and diagnosis of skin cancer …”

Section: Resultsmentioning

confidence: 99%

Raman spectroscopy can discriminate distinct glioma subtypes as defined by RNA expression profiling

Jachtenberg

Schut

French

et al. 2013

J Raman Spectroscopy

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Raman spectroscopy is a molecular spectroscopic technique that can measure the molecular composition of tissue samples within seconds without any extraction processes or dyes. In microbiology, Raman spectroscopy is used to identify bacteriae. In glioblastoma tissue, it was reported that necrosis, normal brain and tumor can be discriminated using Raman spectroscopy. Therefore, we hypothesized that Raman spectroscopy could discriminate glioblastoma tissue from different glioma subtypes defined by RNA expression profiling. We analyzed 20 glioma samples from two distinct molecular subtypes. Both subtypes consisted of glioblastoma samples showing a variety in glioma grading and typing. The Raman spectroscopic results could be grouped in two distinct clusters in an unsupervised cluster analysis. Further analysis of these clusters showed that they were fully congruent with the two clusters as defined by RNA expression profiling. Conclusion: our results demonstrate that Raman spectroscopy can discriminate between different molecular subtypes of glioma and, therefore, may prove to be a valuable tool in in vitro cancer research. Copyright © 2013 John Wiley & Sons, Ltd.

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“…Furthermore, spectral shifts also occurred when ampicillin resistance was activated [28]. Raman spectroscopy has been successfully employed for the investigation of epidemic outbreaks of infections in hospitals, including the analysis of heterogeneity in isolated clones [29–31]. Raman-based characterization has been used in addition to common methods such as serotyping, pulse field gel electrophoreses and genotyping using amplified fragment length polymorphism or 16S RNA sequencing to characterize microorganisms on a subclonal level [18, 19, 30, 32].…”

Section: Raman Spectroscopy and Its Application In Microbiology Andmentioning

confidence: 99%

Raman spectroscopy in biomedicine – non‐invasive in vitro analysis of cells and extracellular matrix components in tissues

Brauchle

Schenke‐Layland

2012

Biotechnology Journal

119

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Raman spectroscopy is an established laser-based technology for the quality assurance of pharmaceutical products. Over the past few years, Raman spectroscopy has become a powerful diagnostic tool in the life sciences. Raman spectra allow assessment of the overall molecular constitution of biological samples, based on specific signals from proteins, nucleic acids, lipids, carbohydrates, and inorganic crystals. Measurements are non-invasive and do not require sample processing, making Raman spectroscopy a reliable and robust method with numerous applications in biomedicine. Moreover, Raman spectroscopy allows the highly sensitive discrimination of bacteria. Rama spectra retain information on continuous metabolic processes and kinetics such as lipid storage and recombinant protein production. Raman spectra are specific for each cell type and provide additional information on cell viability, differentiation status, and tumorigenicity. In tissues, Raman spectroscopy can detect major extracellular matrix components and their secondary structures. Furthermore, the non-invasive characterization of healthy and pathological tissues as well as quality control and process monitoring of in vitro-engineered matrix is possible. This review provides comprehensive insight to the current progress in expanding the applicability of Raman spectroscopy for the characterization of living cells and tissues, and serves as a good reference point for those starting in the field.

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The use of Raman spectroscopy in the epidemiology of methicillin-resistant Staphylococcus aureus of human- and animal-related clonal lineages

Cited by 25 publications

References 9 publications

Good Performance of the SpectraCell RA System for Typing of Methicillin-Resistant Staphylococcus aureus Isolates

Good Performance of the SpectraCell RA System for Typing of Methicillin-Resistant Staphylococcus aureus Isolates

Raman spectroscopy can discriminate distinct glioma subtypes as defined by RNA expression profiling

Raman spectroscopy in biomedicine – non‐invasive in vitro analysis of cells and extracellular matrix components in tissues

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