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Silge A.,Friedrich - Schiller University of Jena | Silge A.,InfectoGnostics Research Campus Jena | Abdou E.,Friedrich - Schiller University of Jena | Abdou E.,InfectoGnostics Research Campus Jena | And 16 more authors.
Cellular Microbiology | Year: 2015

Macrophages are the primary habitat of pathogenic mycobacteria during infections. Current research about the host-pathogen interaction on the cellular level is still going on. The present study proves the potential of Raman microspectroscopy as a label-free and non-invasive method to investigate intracellular mycobacteria in situ. Therefore, macrophages were infected with Mycobacterium gordonae, a mycobacterium known to cause inflammation linked to intracellular survival in macrophages. Here, we show that Raman maps provided spatial and spectral information about the position of bacteria within determined cell margins of macrophages in two-dimensional scans and in three-dimensional image stacks. Simultaneously, the relative intracellular concentration and distributions of cellular constituents such as DNA, proteins and lipids provided phenotypic information about the infected macrophages. Locations of bacteria outside or close to the outer membrane of the macrophages were notably different in their spectral pattern compared with intracellular once. Furthermore, accumulations of bacteria inside of macrophages exhibit distinct spectral/molecular information because of the chemical composition of the intracellular microenvironment. The data show that the connection of microscopically and chemically gained information provided by Raman microspectroscopy offers a new analytical way to detect and to characterize the mycobacterial infection of macrophages. © 2014 John Wiley & Sons Ltd.


Hidi I.J.,Friedrich - Schiller University of Jena | Hidi I.J.,Institute of Photonic Technology | Jahn M.,Friedrich - Schiller University of Jena | Jahn M.,Institute of Photonic Technology | And 8 more authors.
Journal of Physical Chemistry C | Year: 2016

The pharmacokinetics of antibiotics such as levofloxacin exhibits large interindividual differences, questioning the value of fixed dose regimens and warranting individual dosing based on therapeutic drug monitoring. Here, in a proof of principal study, it is shown that levofloxacin can be detected in human urine samples by employing lab-on-a-chip surface enhanced Raman spectroscopy (LoC-SERS). First, artificial urine is used as a matrix in order to get insights into the influence of different parameters such as matrix complexity, aggregation time, and matrix dilution on the overall SERS signal. Second, three anonymized individual and three pooled urine samples originating from patients undergoing either no or unknown medical treatments have been spiked with the target analyte. Measurements were performed with a benchtop and a portable Raman setup. In all six samples urinary levofloxacin concentrations between 0.45 mM (162.6 μg/mL) and 1.8 mM (650.5 μg/mL) have been successfully detected. According to the literature, the normal levofloxacin concentration in urine is 1.38 mM ± 0.68 mM with a minimum measured concentration of 0.45 mM after 4 h from the administration of a 500 mg dose. The presented results therefore show that LoC-SERS is a promising bioanalytical tool for urine analysis. © 2016 American Chemical Society.


Schumacher W.,Friedrich - Schiller University of Jena | Schumacher W.,InfectoGnostics Research Campus Jena | Stockel S.,Friedrich - Schiller University of Jena | Stockel S.,InfectoGnostics Research Campus Jena | And 5 more authors.
Journal of Raman Spectroscopy | Year: 2014

In this contribution a newmethod for improving the accuracy of classification and identification experiments is presented. For this purpose the four most applied dimension reduction methods (principal component analysis, independent component analysis, partial least square dimension reduction and the linear discriminant analysis) are used as starting point for the optimization method. The optimization is done by a specially designed genetic algorithm, which is best suited for this kind of experiments. The presented multi-level chemometric approach has been tested for a Raman dataset containing over 2200 Raman spectra of eight classes of bacteria species (Bacillus anthracis, Bacillus cereus, Bacillus licheniformis, Bacillus mycoides, Bacillus subtilis, Bacillus thuringiensis, Bacillus weihenstephanensis and Paenibacillus polymyxa). The optimization of the dimension reduction improved the accuracy for classification by 6% compared with the accuracy, if the standard dimension reduction is applied. The identification rate is improved by 14% compared with the dimension reduction. The testing in a classification and identification experiment showed the robustness of the algorithm. Copyright © 2014 John Wiley & Sons, Ltd.


Guo S.,Friedrich - Schiller University of Jena | Bocklitz T.,Friedrich - Schiller University of Jena | Bocklitz T.,InfectoGnostics Research Campus Jena | Popp J.,Friedrich - Schiller University of Jena | And 2 more authors.
Analyst | Year: 2016

In the last decade Raman-spectroscopy has become an invaluable tool for biomedical diagnostics. However, a manual rating of the subtle spectral differences between normal and abnormal disease states is not possible or practical. Thus it is necessary to combine Raman-spectroscopy with chemometrics in order to build statistical models predicting the disease states directly without manual intervention. Within chemometrical analysis a number of corrections have to be applied to receive robust models. Baseline correction is an important step of the pre-processing, which should remove spectral contributions of fluorescence effects and improve the performance and robustness of statistical models. However, it is demanding, time-consuming, and depends on expert knowledge to select an optimal baseline correction method and its parameters every time working with a new dataset. To circumvent this issue we proposed a genetic algorithm based method to automatically optimize the baseline correction. The investigation was carried out in three main steps. Firstly, a numerical quantitative marker was defined to evaluate the baseline estimation quality. Secondly, a genetic algorithm based methodology was established to search the optimal baseline estimation with the defined quantitative marker as evaluation function. Finally, classification models were utilized to benchmark the performance of the optimized baseline. For comparison, model based baseline optimization was carried out applying the same classifiers. It was proven that our method could provide a semi-optimal and stable baseline estimation without any chemical knowledge required or any additional spectral information used. © The Royal Society of Chemistry 2016.


Silge A.,Friedrich - Schiller University of Jena | Silge A.,InfectoGnostics Research Campus Jena | Schumacher W.,Friedrich - Schiller University of Jena | Schumacher W.,InfectoGnostics Research Campus Jena | And 7 more authors.
Systematic and Applied Microbiology | Year: 2014

The identification of Pseudomonas aeruginosa from samples of bottled natural mineral water by the analysis of subcultures is time consuming and other species of the authentic Pseudomonas group can be a problem. Therefore, this study aimed to investigate the influence of different aquatic environmental conditions (pH, mineral content) and growth phases on the cultivation-free differentiation between water-conditioned Pseudomonas spp. by applying Raman microspectroscopy. The final dataset was comprised of over 7500 single-cell Raman spectra, including the species Pseudomonas aeruginosa, P. fluorescens and P. putida, in order to prove the feasibility of the introduced approach. The collection of spectra was standardized by automated measurements of viable stained bacterial cells. The discrimination was influenced by the growth phase at the beginning of the water adaptation period and by the type of mineral water. Different combinations of the parameters were tested and they resulted in accuracies of up to 85% for the identification of P. aeruginosa from independent samples by applying chemometric analysis. © 2014 Elsevier GmbH.


Pahlow S.,Friedrich - Schiller University of Jena | Pahlow S.,InfectoGnostics Research Campus Jena | Meisel S.,Friedrich - Schiller University of Jena | Meisel S.,InfectoGnostics Research Campus Jena | And 11 more authors.
Advanced Drug Delivery Reviews | Year: 2015

Bacterial detection is a highly topical research area, because various fields of application will benefit from the progress being made. Consequently, new and innovative strategies which enable the investigation of complex samples, like body fluids or food stuff, and improvements regarding the limit of detection are of general interest. Within this review the prospects of Raman spectroscopy as a reliable tool for identifying bacteria in complex samples are discussed.The main emphasis of this work is on important aspects of applying Raman spectroscopy for the detection of bacteria like sample preparation and the identification process. Several approaches for a Raman compatible isolation of bacterial cells have been developed and applied to different matrices. Here, an overview of the limitations and possibilities of these methods is provided. Furthermore, the utilization of Raman spectroscopy for diagnostic purposes, food safety and environmental issues is discussed under a critical view. © 2015 Elsevier B.V.


Pahlow S.,Friedrich - Schiller University of Jena | Pahlow S.,InfectoGnostics Research Campus Jena | Stockel S.,Friedrich - Schiller University of Jena | Stockel S.,InfectoGnostics Research Campus Jena | And 12 more authors.
Analytical Chemistry | Year: 2016

Pyoverdine is a substance which is excreted by fluorescent pseudomonads in order to scavenge iron from their environment. Due to specific receptors of the bacterial cell wall, the iron loaded pyoverdine molecules are recognized and transported into the cell. This process can be exploited for developing efficient isolation and enrichment strategies for members of the Pseudomonas genus, which are capable of colonizing various environments and also include human pathogens like P. aeruginosa and the less virulent P. fluorescens. A significant advantage over antibody based systems is the fact that siderophores like pyoverdine can be considered as "immutable ligands," since the probability for mutations within the siderophore uptake systems of bacteria is very low. While each species of Pseudomonas usually produces structurally unique pyoverdines, which can be utilized only by the producer strain, cross reactivity does occur. In order to achieve a reliable identification of the captured pathogens, further investigations of the isolated cells are necessary. In this proof of concept study, we combine the advantages of an isolation strategy relying on "immutable ligands" with the high specificity and speed of Raman microspectroscopy. In order to isolate the bacterial cells, pyoverdine was immobilized covalently on planar aluminum chip substrates. After capturing, single cell Raman spectra of the isolated species were acquired. Due to the specific spectroscopic fingerprint of each species, the bacteria can be identified. This approach allows a very rapid detection of potential pathogens, since time-consuming culturing steps are unnecessary. We could prove that pyoverdine based isolation of bacteria is fully Raman compatible and further investigated the capability of this approach by isolating and identifying P. aeruginosa and P. fluorescens from tap water samples, which are both opportunistic pathogens and can pose a threat for immunocompromised patients. © 2015 American Chemical Society.


Silge A.,Friedrich - Schiller University of Jena | Silge A.,InfectoGnostics Research Campus Jena | Bocklitz T.,Friedrich - Schiller University of Jena | Bocklitz T.,InfectoGnostics Research Campus Jena | And 7 more authors.
Analytical and Bioanalytical Chemistry | Year: 2016

Metal oxide nanoparticles (NP) are applied in the fields of biomedicine, pharmaceutics, and in consumer products as textiles, cosmetics, paints, or fuels. In this context, the functionalization of the NP surface is a common method to modify and modulate the product performance. A chemical surface modification of NP such as an amino-functionalization can be used to achieve a positively charged and hydrophobic surface. Surface functionalization is known to affect the interaction of nanomaterials (NM) with cellular macromolecules and the responses of tissues or cells, like the uptake of particles by phagocytic cells. Therefore, it is important to assess the possible risk of those modified NP for human health and environment. By applying Raman microspectroscopy, we verified in situ the interaction of amino-modified ZrO2 NP with cultivated macrophages. The results demonstrated strong adhesion properties of the NP to the cell membrane and internalization into the cells. The intracellular localization of the NP was visualized via Raman depth scans of single cells. After the cells were treated with sodium azide (NaN3) and 2-deoxy-glucose to inhibit the phagocytic activity, NP were still detected inside cells to comparable percentages. The observed tendency of amino-modified ZrO2 NP to interact with the cultivated macrophages may influence membrane integrity and cellular functions of alveolar macrophages in the respiratory system. [Figure not available: see fulltext.] © 2016 Springer-Verlag Berlin Heidelberg


Monecke S.,TU Dresden | Monecke S.,Alere Technologies GmbH | Monecke S.,Infectognostics Research Campus Jena | Engelmann I.,Alere Technologies GmbH | And 3 more authors.
Molecular and Cellular Probes | Year: 2015

Spoligotyping is a widely used typing method for the Mycobacterium tuberculosis complex. Protocols and platforms can be adapted for direct use on patient samples. Serial dilutions of genomic DNA from Mycobacterium bovis BCG strain DSM45071 were spoligotyped by array hybridization using 32 different commercial PCR polymerase preparations. In samples with very low concentrations of mycobacterial DNA, commercially available PCR polymerases differed in their performance, and some yielded no, or false, identification. Direct spoligotyping from samples with very low concentrations of mycobacterial DNA thus requires careful selection of polymerase and strict standardization. © 2015 Elsevier Ltd.


Liebe S.,Institute of Sugar Beet Research | Christ D.S.,Institute of Sugar Beet Research | Ehricht R.,Alere Technologies GmbH | Ehricht R.,InfectoGnostics Research Campus Jena | Varrelmann M.,Institute of Sugar Beet Research
Phytopathology | Year: 2016

Sugar beet root rot diseases that occur during the cropping season or in storage are accompanied by high yield losses and a severe reduction of processing quality. The vast diversity of microorganism species involved in rot development requires molecular tools allowing simultaneous identification of many different targets. Therefore, a new microarray technology (ArrayTube) was applied in this study to improve diagnosis of sugar beet root rot diseases. Based on three marker genes (internal transcribed spacer, translation elongation factor 1 alpha, and 16S ribosomal DNA), 42 well-performing probes enabled the identification of prevalent field pathogens (e.g., Aphanomyces cochlioides), storage pathogens (e.g., Botrytis cinerea), and ubiquitous spoilage fungi (e.g., Penicillium expansum). All probes were proven for specificity with pure cultures from 73 microorganism species as well as for in planta detection of their target species using inoculated sugar beet tissue. Microarray-based identification of root rot pathogens in diseased field beets was successfully confirmed by classical detection methods. The high discriminatory potential was proven by Fusarium species differentiation based on a single nucleotide polymorphism. The results demonstrate that the ArrayTube constitute an innovative tool allowing a rapid and reliable detection of plant pathogens particularly when multiple microorganism species are present. © 2016 The American Phytopathological Society.

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