Kees Maquelin

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.

Discrimination of Acinetobacter genomic species by AFLP fingerprinting.

AFLP is a novel genomic fingerprinting method based on the selective PCR amplification of restriction fragments. The usability of this method for the differentiation of genomic species in the genus Acinetobacter was investigated. A total of 151 classified strains (representing 18 genomic species, including type, reference, and field strains) and 8 unclassified strains were analyzed. By using a single set of restriction enzymes (HindIII and TaqI) and one particular set of selective PCR primers, all strains could be allocated to the correct genomic species and all groups were properly separated, with minimal intraspecific similarity levels ranging from 29 to 74%. Strains belonging to genomic species 8 (Acinetobacter lwoffii sensu stricto) and 9 grouped together in one cluster. The closely related DNA groups 1 (Acinetobacter calcoaceticus), 2 (Acinetobacter baumannii), 3 and 13TU (sensu Tjernberg & Ursing 1989) were clearly distinguishable, with intraspecific linkage levels above 50%. Strains of the independently described genomic species 13BJ (sensu Bouvet & Jeanjean 1989) and 14TU linked together at a relatively low level (33%). Although a previous DNA-DNA hybridization study seemed to justify the unification of these genomic species, AFLP analysis actually divides the 13BJ-14TU group into three well-separated subgroups. Finally, four unclassified strains obtained from diverse sources and origins grouped convincingly together, with a similarity linkage level of approximately 50%. These strains showed no similarities in their AFLP patterns with any of the other 155 strains studied and may represent a thus-far-undescribed Acinetobacter species. Based on these results, AFLP should be regarded as an important auxiliary method for the delineation of genomic species. Furthermore, because AFLP provides a detailed insight into the infraspecific structure of Acinetobacter taxa, the method also represents a highly effective means for the confirmation of strain identity in the epidemiology of acinetobacters.

Discriminating basal cell carcinoma from perilesional skin using high wave-number Raman spectroscopy

An expanding body of literature suggests Raman spectroscopy is a promising tool for skin cancer diagnosis and in-vivo tumor border demarcation. The development of an in-vivo diagnostic tool is, however, hampered by the fact that construction of fiber optic probes suitable for Raman spectroscopy in the so-called fingerprint region is complicated. In contrast, the use of the high wave-number region allows for fiber optic probes with a very simple design. We investigate whether high wave-number Raman spectroscopy (2800 to 3125 cm(-1)) is able to provide sufficient information for noninvasive discrimination between basal cell carcinoma (BCC) and noninvolved skin. Using a simple fiber optic probe, Raman spectra are obtained from 19 BCC biopsy specimens and 9 biopsy specimens of perilesional skin. A linear discriminant analysis (LDA)-based tissue classification model is developed, which discriminates between BCC and noninvolved skin with high accuracy. This is a crucial step in the development of clinical dermatological applications based on fiber optic Raman spectroscopy.

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.

Rapid Identification of Mycobacteria by Raman Spectroscopy

ABSTRACT 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.

Optical Fingerprinting in Bacterial Epidemiology: Raman Spectroscopy as a Real-Time Typing Method

Hospital-acquired infections (HAI) increase morbidity and mortality and constitute a high financial burden on health care systems. An effective weapon against HAI is early detection of potential outbreaks and sources of contamination. Such monitoring requires microbial typing with sufficient reproducibility and discriminatory power. Here, a microbial-typing method is presented, based on Raman spectroscopy. This technique provides strain-specific optical fingerprints in a few minutes instead of several hours to days, as is the case with genotyping methods. Although the method is generally applicable, we used 118 Staphylococcus aureus isolates to illustrate that the discriminatory power matches that of established genotyping techniques (numerical index of diversity [D] = 0.989) and that concordance with the gold standard (pulsed-field gel electrophoresis) is high (95%). The Raman clustering of isolates was reproducible to the strain level for five independent cultures, despite the various culture times from 18 h to 24 h. Furthermore, this technique was able to classify stored (−80°C) and recent isolates of a methicillin-resistant Staphylococcus aureus-colonized individual during surveillance studies and did so days earlier than established genotyping techniques did. Its high throughput and ease of use make it suitable for use in routine diagnostic laboratory settings. This will set the stage for continuous, automated, real-time epidemiological monitoring of bacterial infections in a hospital, which can then be followed by timely corrective action by infection prevention teams.

Rapid typing of extended-spectrum β-lactamase- and carbapenemase-producing Escherichia coli and Klebsiella pneumoniae isolates by use of spectracell RA

ABSTRACT Enterobacteriaceae are important pathogens of both nosocomial and community-acquired infections. In particular, strains with broad-spectrum beta-lactamases increasingly cause problems in health care settings. Rapid and reliable typing systems are key tools to identify transmission, so that targeted infection control measures can be taken. In this study, we evaluated the performance of Raman spectroscopic analysis (RA) for the typing of multiresistant Escherichia coli and Klebsiella pneumoniae isolates using the SpectraCell RA bacterial strain analyzer (River Diagnostics). Analysis of 96 unrelated isolates revealed that RA generated highly reproducible spectra and exhibited a discriminatory power that is comparable to pulsed-field gel electrophoresis. Furthermore, adequate results were obtained for three collections of clinical isolates. RA was able to discriminate outbreak-related isolates from isolates that were not involved in an outbreak or transmission. Furthermore, it was found that the RA approach recognized clones, irrespective of the extended-spectrum β-lactamase type. It can be concluded that RA is a suitable typing technique for E. coli and K. pneumoniae isolates. Combining high reproducibility, speed, and ease-of-use, this technique may play an important role in monitoring the epidemiology of these important nosocomial species.