Lin-P'ing Choo-Smith

IDENTIFICATION OF MEDICALLY RELEVANT MICROORGANISMS BY VIBRATIONAL SPECTROSCOPY

In the recent years, vibrational spectroscopies (infrared and Raman spectroscopy) have been developed for all sorts of analyses in microbiology. Important features of these methods are the relative ease with which measurements can be performed. Furthermore, in order to obtain infrared or Raman spectra, there is only a limited amount of sample handling involved without the need for expensive chemicals, labels or dyes. Here, we review the potential application of vibrational spectroscopies for the use in medical microbiology. After describing some of the basics of the techniques, considerations on reproducibility and standardisation are presented. Finally, the use of infrared and Raman spectroscopy for the (rapid) identification of medically relevant microorganisms is discussed. It can be concluded that vibrational spectroscopies show high potential as novel methods in medical microbiology.

Prospective Study of the Performance of Vibrational Spectroscopies for Rapid Identification of Bacterial and Fungal Pathogens Recovered from Blood Cultures

ABSTRACT Rapid identification of microbial pathogens reduces infection-related morbidity and mortality of hospitalized patients. Raman spectra and Fourier transform infrared (IR) spectra constitute highly specific spectroscopic fingerprints of microorganisms by which they can be identified. Little biomass is required, so that spectra of microcolonies can be obtained. A prospective clinical study was carried out in which the causative pathogens of bloodstream infections in hospitalized patients were identified. Reference libraries of Raman and IR spectra of bacterial and yeast pathogens highly prevalent in bloodstream infections were created. They were used to develop identification models based on linear discriminant analysis and artificial neural networks. These models were tested by carrying out vibrational spectroscopic identification in parallel with routine diagnostic phenotypic identification. Whereas routine identification has a typical turnaround time of 1 to 2 days, Raman and IR spectra of microcolonies were collected 6 to 8 h after microbial growth was detected by an automated blood culture system. One hundred fifteen samples were analyzed by Raman spectroscopy, of which 109 contained bacteria and 6 contained yeasts. One hundred twenty-one samples were analyzed by IR spectroscopy. Of these, 114 yielded bacteria and 7 were positive for yeasts. High identification accuracy was achieved in both the Raman (92.2%, 106 of 115) and IR (98.3%, 119 of 121) studies. Vibrational spectroscopic techniques enable simple, rapid, and accurate microbial identification. These advantages can be easily transferred to other applications in diagnostic microbiology, e.g., to accelerate identification of fastidious microorganisms.

Classification and identification of enterococci: a comparative phenotypic, genotypic, and vibrational spectroscopic study

ABSTRACT Rapid and accurate identification of enterococci at the species level is an essential task in clinical microbiology since these organisms have emerged as one of the leading causes of nosocomial infections worldwide. Vibrational spectroscopic techniques (infrared [IR] and Raman) could provide potential alternatives to conventional typing methods, because they are fast, easy to perform, and economical. We present a comparative study using phenotypic, genotypic, and vibrational spectroscopic techniques for typing a collection of 18Enterococcus strains comprising six different species. Classification of the bacteria by Fourier transform (FT)-IR spectroscopy in combination with hierarchical cluster analysis revealed discrepancies for certain strains when compared with results obtained from automated phenotypic systems, such as API and MicroScan. Further diagnostic evaluation using genotypic methods—i.e., PCR of the species-specific ligase and glycopeptide resistance genes, which is limited to the identification of only four Enterococcusspecies and 16S RNA sequencing, the “gold standard” for identification of enterococci—confirmed the results obtained by the FT-IR classification. These results were later reproduced by three different laboratories, using confocal Raman microspectroscopy, FT-IR attenuated total reflectance spectroscopy, and FT-IR microspectroscopy, demonstrating the discriminative capacity and the reproducibility of the technique. It is concluded that vibrational spectroscopic techniques have great potential as routine methods in clinical microbiology.

Investigating Microbial (Micro)colony Heterogeneity by Vibrational Spectroscopy

ABSTRACT Fourier transform infrared and Raman microspectroscopy are currently being developed as new methods for the rapid identification of clinically relevant microorganisms. These methods involve measuring spectra from microcolonies which have been cultured for as little as 6 h, followed by the nonsubjective identification of microorganisms through the use of multivariate statistical analyses. To examine the biological heterogeneity of microorganism growth which is reflected in the spectra, measurements were acquired from various positions within (micro)colonies cultured for 6, 12, and 24 h. The studies reveal that there is little spectral variance in 6-h microcolonies. In contrast, the 12- and 24-h cultures exhibited a significant amount of heterogeneity. Hierarchical cluster analysis of the spectra from the various positions and depths reveals the presence of different layers in the colonies. Further analysis indicates that spectra acquired from the surface of the colonies exhibit higher levels of glycogen than do the deeper layers of the colony. Additionally, the spectra from the deeper layers present with higher RNA levels than the surface layers. Therefore, the 6-h colonies with their limited heterogeneity are more suitable for inclusion in a spectral database to be used for classification purposes. These results also demonstrate that vibrational spectroscopic techniques can be useful tools for studying the nature of colony development and biofilm formation.

Discriminating Vital Tumor from Necrotic Tissue in Human Glioblastoma Tissue Samples by Raman Spectroscopy

Vital and necrotic glioblastoma tissues were studied by Raman microspectroscopy to identify possibilities for the development of an in vivo Raman method for real-time intraoperative brain biopsy guidance. The histologic malignancy grade of gliomas depends on the presence of parameters such as endothelial proliferation and necrosis, which are often not evenly distributed within the tumor. Because tissue samples obtained by stereotactic surgery are relatively small, sampling errors may easily occur by missing these crucial features. Although necrosis is important for grading, specimens containing only necrosis are diagnostically useless. Raman microspectroscopic mapping experiments were performed on unfixed cryosections of glioblastoma, obtained from 20 patients. After spectral acquisition, a clustering analysis was performed, resulting in groups of similar spectra. Each cluster was assigned a color, and pseudo-color Raman maps of the tissue sections were constructed. After the Raman experiments, the tissue sections were stained for histopathologic analysis, enabling identification of the histologic origin of the Raman spectra and assignment of the Raman spectral clusters to either vital or necrotic tissue. A classification model for discrimination between vital and necrotic tumor tissue based on linear discriminant analysis was developed. The classification model was evaluated using independent Raman data obtained from nine other tissue sections and yielded 100% accuracy. Information about the biochemical differences between necrosis and vital tumor was obtained by the analysis of difference spectra. Necrotic tissue was found to consistently contain higher levels of cholesterol (-esters). This in vitro result indicates that Raman spectra contain the information to distinguish vital glioblastoma from necrosis and makes Raman spectroscopy a powerful candidate for guidance of stereotactic brain biopsy.

Rapid identification of Candida species by confocal Raman microspectroscopy

ABSTRACT Candida species are important nosocomial pathogens associated with high mortality rates. Rapid detection and identification of Candida species can guide a clinician at an early stage to prescribe antifungal drugs or to adjust empirical therapy when resistant species are isolated. Confocal Raman microspectroscopy is highly suitable for the rapid identification of Candida species, since Raman spectra can be directly obtained from microcolonies on a solid culture medium after only 6 h of culturing. In this study, we have used a set of 42 Candida strains comprising five species that are frequently encountered in clinical microbiology to test the feasibility of the technique for the rapid identification of Candida species. The procedure was started either from a culture on Sabouraud medium or from a positive vial of an automated blood culture system. Prior to Raman measurements, strains were subcultured on Sabouraud medium for 6 h to form microcolonies. Using multivariate statistical analyses, a high prediction accuracy (97 to 100%) was obtained with the Raman method. Identification with Raman microspectroscopy may therefore be significantly faster than identification with commercial identification systems that allow various species to be identified and that often require 24 to 48 h before a reliable identification is obtained. We conclude that confocal Raman microspectroscopy offers a rapid, accurate, and easy-to-use alternative for the identification of clinically relevant Candida species.

Raman spectroscopic studies on bacteria

Routine clinical microbiological identification of pathogenic micro-organisms is largely based on nutritional and biochemical tests. Laboratory results can be presented to a clinician after 2 - 3 days for most clinically relevant micro- organisms. Most of this time is required to obtain pure cultures and enough biomass for the tests to be performed. In the case of severely ill patients, this unavoidable time delay associated with such identification procedures can be fatal. A novel identification method based on confocal Raman microspectroscopy will be presented. With this method it is possible to obtain Raman spectra directly from microbial microcolonies on the solid culture medium, which have developed after only 6 hours of culturing for most commonly encountered organisms. Not only does this technique enable rapid (same day) identifications, but also preserves the sample allowing it to be double-checked with traditional tests. This, combined with the speed and minimal sample handling indicate that confocal Raman microspectroscopy has much potential as a powerful new tool in clinical diagnostic microbiology.

A novel method for rapid identification of micro-organisms using confocal Raman microspectroscopy

For effective treatment of infection, it is critical to know the identity and antibiotic susceptibility profile of the causative micro-organism(s). Without rapid laboratory results that provide this information, the clinician is faced with the difficult task of prescribing appropriate antibiotics which target the micro-organisms and importantly, to which the micro-organisms are not already resistant. Ineffective antibiotics not only result in further deterioration of the patient’s condition, but can also contribute to the emerging problem of drug resistant micro-organisms. The current microbiological diagnostic methods involve initial culturing of the micro-organism for approximately 16 hours to obtain a mass of 106 to 108 cells. The biomass is then used for biochemical assays and antibiotic susceptibility testing. These routine methods require 2–3 days before a result is known. In life threatening situations, this time delay cannot be afforded. Recent methods such as DNA amplification routines are attractive since little sample material is required and test results can be obtained in 1 day. Despite their high sensitivity, these techniques still experience technical hurdles such as the problem of cross-contamination [1]. Moreover, they are costly and involve highly trained personnel. Thus there is a need for novel methods which can rapidly (within hours to 1 day of receipt of samples) provide the clinician with the identity and antibiotic susceptibility profile of micro-organisms responsible for infection.