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Automated and rapid identification of multidrug resistant Escherichia coli against the lead drugs of acylureidopenicillins, cephalosporins, and fluoroquinolones using specific Raman marker bands
A Raman-based, strain-independent, semi-automated method is presented that allows the rapid (<3 hours) determination of antibiotic susceptibility of bacterial pathogens isolated from clinical samples. Applying a priori knowledge about the mode of action of the respective antibiotic, we identified characteristic Raman marker bands in the spectrum and calculated batch-wise weighted sum scores from standardized Raman intensity differences between spectra of antibiotic exposed and nonexposed samples of the same strains. The lead substances for three relevant antibiotic classes (fluoroquinolone ciprofloxacin, third-generation cephalosporin cefotaxime, ureidopenicillin piperacillin) against multidrug-resistant Gram-negative bacteria (MRGN) revealed a high sensitivity and specificity for the susceptibility testing of two Escherichia coli laboratory strains and 12 clinical isolates. The method benefits from the parallel incubation of control and treated samples, which reduces the variance due to alterations in cultivation conditions and the standardization of differences between batches leading to long-term comparability of Raman measurements. © 2020 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
PHONA - photonische Nanomaterialien : Schlussbericht ; Laufzeit des Vorhabens: 01.12.2009-30.11.2014
[no abstract available]
Response of the wood-decay fungus Schizophyllum commune to co-occurring microorganisms
Microorganisms are constantly interacting in a given environment by a constant exchange of signaling molecules. In timber, wood-decay fungi will come into contact with other fungi and bacteria. In naturally bleached wood, dark, pigmented lines arising from confrontation of two fungi often hint at such interactions. The metabolites (and pigment) exchange was investigated using the lignicolous basidiomycete Schizophyllum commune, and co-occurring fungi and bacteria inoculated directly on sterilized wood, or on media. In interactions with competitive wood degrading fungi, yeasts or bacteria, different competition strategies and communication types were observed, and stress reactions, as well as competitor-induced enzymes or pigments were analyzed. Melanin, indole, flavonoids and carotenoids were shown to be induced in S. commune interactions. The induced genes included multi-copper oxidases lcc1, lcc2, mco1, mco2, mco3 and mco4, possibly involved in both pigment production and lignin degradation typical for wood bleaching by wood-decay fungi.
Laser spectroscopic technique for direct identification of a single virus I: FASTER CARS
From the famous 1918 H1N1 influenza to the present COVID-19 pandemic, the need for improved viral detection techniques is all too apparent. The aim of the present paper is to show that identification of individual virus particles in clinical sample materials quickly and reliably is near at hand. First of all, our team has developed techniques for identification of virions based on a modular atomic force microscopy (AFM). Furthermore, femtosecond adaptive spectroscopic techniques with enhanced resolution via coherent anti-Stokes Raman scattering (FASTER CARS) using tip-enhanced techniques markedly improves the sensitivity [M. O. Scully, et al, Proc. Natl. Acad. Sci. U.S.A. 99, 10994-11001 (2002)].
Fusion of MALDI Spectrometric Imaging and Raman Spectroscopic Data for the Analysis of Biological Samples
Despite of a large number of imaging techniques for the characterization of biological samples, no universal one has been reported yet. In this work, a data fusion approach was investigated for combining Raman spectroscopic data with matrix-assisted laser desorption/ionization (MALDI) mass spectrometric data. It betters the image analysis of biological samples because Raman and MALDI information can be complementary to each other. While MALDI spectrometry yields detailed information regarding the lipid content, Raman spectroscopy provides valuable information about the overall chemical composition of the sample. The combination of Raman spectroscopic and MALDI spectrometric imaging data helps distinguishing different regions within the sample with a higher precision than would be possible by using either technique. We demonstrate that a data weighting step within the data fusion is necessary to reveal additional spectral features. The selected weighting approach was evaluated by examining the proportions of variance within the data explained by the first principal components of a principal component analysis (PCA) and visualizing the PCA results for each data type and combined data. In summary, the presented data fusion approach provides a concrete guideline on how to combine Raman spectroscopic and MALDI spectrometric imaging data for biological analysis.
Beyond endoscopic assessment in inflammatory bowel disease: real-time histology of disease activity by non-linear multimodal imaging
Assessing disease activity is a prerequisite for an adequate treatment of inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis. In addition to endoscopic mucosal healing, histologic remission poses a promising end-point of IBD therapy. However, evaluating histological remission harbors the risk for complications due to the acquisition of biopsies and results in a delay of diagnosis because of tissue processing procedures. In this regard, non-linear multimodal imaging techniques might serve as an unparalleled technique that allows the real-time evaluation of microscopic IBD activity in the endoscopy unit. In this study, tissue sections were investigated using the non-linear multimodal microscopy combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited auto fluorescence (TPEF) and second-harmonic generation (SHG). After the measurement a gold-standard assessment of histological indexes was carried out based on a conventional H&E stain. Subsequently, various geometry and intensity related features were extracted from the multimodal images. An optimized feature set was utilized to predict histological index levels based on a linear classifier. Based on the automated prediction, the diagnosis time interval is decreased. Therefore, non-linear multimodal imaging may provide a real-time diagnosis of IBD activity suited to assist clinical decision making within the endoscopy unit.
Counterfeit and substandard test of the antimalarial tablet Riamet® by means of Raman hyperspectral multicomponent analysis
The fight against counterfeit pharmaceuticals is a global issue of utmost importance, as failed medication results in millions of deaths every year. Particularly affected are antimalarial tablets. A very important issue is the identification of substandard tablets that do not contain the nominal amounts of the active pharmaceutical ingredient (API), and the differentiation between genuine products and products without any active ingredient or with a false active ingredient. This work presents a novel approach based on fiber-array based Raman hyperspectral imaging to qualify and quantify the antimalarial APIs lumefantrine and artemether directly and non-invasively in a tablet in a time-efficient way. The investigations were carried out with the antimalarial tablet Riamet® and self-made model tablets, which were used as examples of counterfeits and substandard. Partial least-squares regression modeling and density functional theory calculations were carried out for quantification of lumefantrine and artemether and for spectral band assignment. The most prominent differentiating vibrational signatures of the APIs were presented.
Nonresonant Raman spectroscopy of isolated human retina samples complying with laser safety regulations for in vivo measurements
Retinal diseases, such as age-related macular degeneration, are leading causes of vision impairment, increasing in incidence worldwide due to an aging society. If diagnosed early, most cases could be prevented. In contrast to standard ophthalmic diagnostic tools, Raman spectroscopy can provide a comprehensive overview of the biochemical composition of the retina in a label-free manner. A proof of concept study of the applicability of nonresonant Raman spectroscopy for retinal investigations is presented. Raman imaging provides valuable insights into the molecular composition of an isolated ex vivo human retina sample by probing the entire molecular fingerprint, i.e., the lipid, protein, carotenoid, and nucleic acid content. The results are compared to morphological information obtained by optical coherence tomography of the sample. The challenges of in vivo Raman studies due to laser safety limitations and predefined optical parameters given by the eye itself are explored. An in-house built setup simulating the optical pathway in the human eye was developed and used to demonstrate that even under laser safety regulations and the above-mentioned optical restrictions, Raman spectra of isolated ex vivo human retinas can be recorded. The results strongly support that in vivo studies using nonresonant Raman spectroscopy are feasible and that these studies provide comprehensive molecular information of the human retina. © The Authors. Published by SPIE.
Evaluation of shifted excitation Raman difference spectroscopy and comparison to computational background correction methods applied to biochemical Raman spectra
Raman spectroscopy provides label-free biochemical information from tissue samples without complicated sample preparation. The clinical capability of Raman spectroscopy has been demonstrated in a wide range of in vitro and in vivo applications. However, a challenge for in vivo applications is the simultaneous excitation of auto-fluorescence in the majority of tissues of interest, such as liver, bladder, brain, and others. Raman bands are then superimposed on a fluorescence background, which can be several orders of magnitude larger than the Raman signal. To eliminate the disturbing fluorescence background, several approaches are available. Among instrumentational methods shifted excitation Raman difference spectroscopy (SERDS) has been widely applied and studied. Similarly, computational techniques, for instance extended multiplicative scatter correction (EMSC), have also been employed to remove undesired background contributions. Here, we present a theoretical and experimental evaluation and comparison of fluorescence background removal approaches for Raman spectra based on SERDS and EMSC.
Online investigation of respiratory quotients in Pinus sylvestris and Picea abies during drought and shading by means of cavity-enhanced Raman multi-gas spectrometry
Photosynthesis and respiration are major components of the plant carbon balance. During stress, like drought, carbohydrate supply from photosynthesis is reduced and the Krebs cycle respiration must be fueled with other stored carbon compounds. However, the dynamics of storage use are still unknown. The respiratory quotient (RQ, CO2 released per O2 consumed during respiration) is an excellent indicator of the nature of the respiration substrate. In plant science, however, online RQ measurements have been challenging or even impossible so far due to very small gas exchange fluxes during respiration. Here we apply cavity-enhanced multi-gas Raman spectrometry (CERS) for online in situ RQ measurements in drought-tolerant pine (Pinus sylvestris [L.]) and drought-intolerant spruce (Picea abies [L. H. Karst]). Two different treatments, drought and shading, were applied to reduce photosynthesis and force dependency on stored substrates. Changes in respiration rates and RQ values were continuously monitored over periods of several days with low levels of variance. The results show that both species switched from COH-dominated respiration (RQ = 1.0) to a mixture of substrates during shading (RQ = 0.77–0.81), while during drought only pine did so (RQ = 0.75). The gas phase measurements were complemented by concentration measurements of non-structural carbohydrates and lipids. These first results suggest a physiological explanation for greater drought tolerance in pine. CERS was proven as powerful technique for non-consumptive and precise real-time monitoring of respiration rates and respirational quotients for the investigation of plant metabolism under drought stress conditions that are predicted to increase with future climate change.