Stephan Stöckel

Direct analysis of clinical relevant single bacterial cells from cerebrospinal fluid during bacterial meningitis by means of micro-Raman spectroscopy

Bacterial meningitis is a relevant public health concern. Despite the availability of modern treatment strategies it is still a life-threatening disease that causes significant morbidity and mortality. Therefore, an initial treatment approach plays an important role. For in-time identification of specific bacterial pathogens of the cerebrospinal fluid (CSF) and emerged antimicrobial and adjunctive treatment, microbiological examination is of major importance. This contribution spotlights the potential of micro-Raman spectroscopy as a biomedical assay for direct analysis of bacteria in cerebrospinal fluid of patients with bacterial meningitis. The influence of miscellaneous artificial environments on several bacterial species present during bacterial meningitis was studied by means of Raman spectroscopy. The application of chemometric data interpretation via hierarchical cluster analysis (HCA) allows for the differentiation of in vitro cultured bacterial cells and can also be achieved on a single cell level. Moreover as proof of principle the investigation of a CSF sample obtained from a patient with meningococcal meningitis showed that the cerebrospinal fluid matrix does not mask the Raman spectrum of a bacterial cell notably since via chemometric analysis with HCA an identification of N. meningitidis cells from patients with bacterial meningitis could be achieved.

Raman Spectroscopic Detection of Anthrax Endospores in Powder Samples

Polymerase chain reaction (PCR) is becoming the method of choice for detecting microorganisms concealed in complex matrices or “hoax materials” like household dry powders, food, and soil.[1] However, adding samples directly to a PCR reaction is in most cases not possible because of the presence of PCR inhibitors in the sample.[2] Thus, in order to reliably use PCR, one must either enrich the culture prior to the analysis, which is time-consuming for fastidious organisms, or extract the total DNA directly from the sample, which requires an extraction technique capable of processing different sample types. However, since most DNA extraction methods are often not generic in that sense, they lead to unreliable DNA recovery yields.[2, 3]

Identification of meat-associated pathogens via Raman microspectroscopy

The development of fast and reliable sensing techniques to detect food-borne microorganisms is a permanent concern in food industry and health care. For this reason, Raman microspectroscopy was applied to rapidly detect pathogens in meat, which could be a promising supplement to currently established methods. In this context, a spectral database of 19 species of the most important harmful and non-pathogenic bacteria associated with meat and poultry was established. To create a meat-like environment the microbial species were prepared on three different agar types. The whole amount of Raman data was taken as a basis to build up a three level classification model by means of support vector machines. Subsequent to a first classifier that differentiates between Raman spectra of Gram-positive and Gram-negative bacteria, two decision knots regarding bacterial genus and species follow. The different steps of the classification model achieved accuracies in the range of 90.6%-99.5%. This database was then challenged with independently prepared test samples. By doing so, beef and poultry samples were spiked with different pathogens associated with food-borne diseases and then identified. The test samples were correctly assigned to their genus and for the most part down to the species-level i.e. a differentiation from closely-related non-pathogenic members was achieved.

Raman Spectroscopy as a Potential Tool for Detection of Brucella spp. in Milk

ABSTRACT Detection of Brucella, causing brucellosis, is very challenging, since the applied techniques are mostly time-demanding and not standardized. While the common detection system relies on the cultivation of the bacteria, further classical typing up to the biotype level is mostly based on phenotypic or genotypic characteristics. The results of genotyping do not always fit the existing taxonomy, and misidentifications between genetically closely related genera cannot be avoided. This situation gets even worse, when detection from complex matrices, such as milk, is necessary. For these reasons, the availability of a method that allows early and reliable identification of possible Brucella isolates for both clinical and epidemiological reasons would be extremely useful. We evaluated micro-Raman spectroscopy in combination with chemometric analysis to identify Brucella from agar plates and directly from milk: prior to these studies, the samples were inactivated via formaldehyde treatment to ensure a higher working safety. The single-cell Raman spectra of different Brucella, Escherichia, Ochrobactrum, Pseudomonas, and Yersinia spp. were measured to create two independent databases for detection in media and milk. Identification accuracies of 92% for Brucella from medium and 94% for Brucella from milk were obtained while analyzing the single-cell Raman spectra via support vector machine. Even the identification of the other genera yielded sufficient results, with accuracies of >90%. In summary, micro-Raman spectroscopy is a promising alternative for detecting Brucella. The measurements we performed at the single-cell level thus allow fast identification within a few hours without a demanding process for sample preparation.

Raman spectroscopy-compatible inactivation method for pathogenic endospores.

ABSTRACT Micro-Raman spectroscopy is a fast and sensitive tool for the detection, classification, and identification of biological organisms. The vibrational spectrum inherently serves as a fingerprint of the biochemical composition of each bacterium and thus makes identification at the species level, or even the subspecies level, possible. Therefore, microorganisms in areas susceptible to bacterial contamination, e.g., clinical environments or food-processing technology, can be sensed. Within the scope of point-of-care-testing also, detection of intentionally released biosafety level 3 (BSL-3) agents, such as Bacillus anthracis endospores, or their products is attainable. However, no Raman spectroscopy-compatible inactivation method for the notoriously resistant Bacillus endospores has been elaborated so far. In this work we present an inactivation protocol for endospores that permits, on the one hand, sufficient microbial inactivation and, on the other hand, the recording of Raman spectroscopic signatures of single endospores, making species-specific identification by means of highly sophisticated chemometrical methods possible. Several physical and chemical inactivation methods were assessed, and eventually treatment with 20% formaldehyde proved to be superior to the other methods in terms of sporicidal capacity and information conservation in the Raman spectra. The latter fact has been verified by successfully using self-learning machines (such as support vector machines or artificial neural networks) to identify inactivated B. anthracis-related endospores with adequate accuracies within the range of the limited model database employed.

LOC-SERS: A Promising Closed System for the Identification of Mycobacteria

A closed droplet based lab-on-a-chip (LOC) device has been developed for the differentiation of six species of mycobacteria, i.e., both Mycobacterium tuberculosis complex (MTC) and nontuberculous mycobacteria (NTM), using surface-enhanced Raman spectroscopy (SERS). The combination of a fast and simple bead-beating module for the disruption of the bacterial cell with the LOC-SERS device enables the application of an easy and reliable system for bacteria discrimination. Without extraction or further treatment of the sample, the obtained SERS spectra are dominated by the cell-wall component mycolic acid. For the differentiation, a robust data set was recorded using a droplet based LOC-SERS device. Thus, more than 2100 individual SERS spectra of the bacteria suspension were obtained in 1 h. The differentiation of bacteria using LOC-SERS provides helpful information for physicians to define the conditions for the treatment of individual patients.

Cultivation-Free Raman Spectroscopic Investigations of Bacteria

Raman spectroscopy is currently advertised as a hot and ambitious technology that has all of the features needed to characterize and identify bacteria. Raman spectroscopy is rapid, easy to use, noninvasive, and it could complement established microbiological and biomolecular methods in the near future. To bring this vision closer to reality, ongoing research is being conducted on spectral fingerprinting. This can yield a wealth of information, from even single bacteria from various habitats which can be further improved by combining Raman spectroscopy with methods such as stable isotope probing to elucidate microbial interactions. In conjunction with extensive statistical analysis, Raman spectroscopy will allow identification of (non)pathogenic bacteria at different taxonomic levels.

Quantitative SERS studies by combining LOC-SERS with the standard addition method.

AbstractHere, we report on a proof-of-concept study highlighting a new approach for quantitative surface enhanced Raman spectroscopy (SERS) measurements. This has been achieved by implementing the standard addition method (SAM) within a lab-on-a-chip (LOC) system. The approach has been successfully tested to quantify congo red as a model analyte even in the presence of the chemically related molecule methyl red. Thus, the developed concept demonstrates its potential to quantify analytes via SERS in the presence of other SERS active molecules. Graphical AbstractCongo red was quantified by means of the standard addition method implemented in the lab-on-a-chip device. Due to the developed approach, a direct detection out of the sample and in the presence of an interfering substance was possible.

Single virus detection by means of atomic force microscopy in combination with advanced image analysis

In the present contribution virions of five different virus species, namely Varicella-zoster virus, Porcine teschovirus, Tobacco mosaic virus, Coliphage M13 and Enterobacteria phage PsP3, are investigated using atomic force microscopy (AFM). From the resulting height images quantitative features like maximal height, area and volume of the viruses could be extracted and compared to reference values. Subsequently, these features were accompanied by image moments, which quantify the morphology of the virions. Both types of features could be utilized for an automatic discrimination of the five virus species. The accuracy of this classification model was 96.8%. Thus, a virus detection on a single-particle level using AFM images is possible. Due to the application of advanced image analysis the morphology could be quantified and used for further analysis. Here, an automatic recognition by means of a classification model could be achieved in a reliable and objective manner.

Single particle analysis of herpes simplex virus: comparing the dimensions of one and the same virions via atomic force and scanning electron microscopy

AbstractCurrently, two types of direct methods to characterize and identify single virions are available: electron microscopy (EM) and scanning probe techniques, especially atomic force microscopy (AFM). AFM in particular provides morphologic information even of the ultrastructure of viral specimens without the need to cultivate the virus and to invasively alter the sample prior to the measurements. Thus, AFM can play a critical role as a frontline method in diagnostic virology. Interestingly, varying morphological parameters for virions of the same type can be found in the literature, depending on whether AFM or EM was employed and according to the respective experimental conditions during the AFM measurements. Here, an inter-methodological proof of principle is presented, in which the same single virions of herpes simplex virus 1 were probed by AFM previously and after they were measured by scanning electron microscopy (SEM). Sophisticated chemometric analyses then allowed a calculation of morphological parameters of the ensemble of single virions and a comparison thereof. A distinct decrease in the virions’ dimensions was found during as well as after the SEM analyses and could be attributed to the sample preparation for the SEM measurements. Graphical abstractThe herpes simplex virus is investigated with scanning electron and atomic force microscopy in view of varying dimensions