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- ItemAutomated and rapid identification of multidrug resistant Escherichia coli against the lead drugs of acylureidopenicillins, cephalosporins, and fluoroquinolones using specific Raman marker bands(Weinheim : Wiley-VCH-Verl., 2020) Götz, Theresa; Dahms, Marcel; Kirchhoff, Johanna; Beleites, Claudia; Glaser, Uwe; Bohnert, Jürgen A.; Pletz, Mathias W.; Popp, Jürgen; Schlattmann, Peter; Neugebauer, UteA 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
- ItemResponse of the wood-decay fungus Schizophyllum commune to co-occurring microorganisms(San Francisco, California, US : PLOS, 2020) Krause, Katrin; Jung, Elke-Martina; Lindner, Julia; Hardiman, Imam; Petschner, Jessica; Madhavan, Soumya; Matthäus, Christian; Kai, Marco; Menezes, Riya Christina; Popp, Jürgen; Svatoš, Aleš; Kothe, ErikaMicroorganisms 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.
- ItemLaser spectroscopic technique for direct identification of a single virus I: FASTER CARS(Washington, DC : National Acad. of Sciences, 2020) Deckert, Volker; Deckert-Gaudig, Tanja; Cialla-May, Dana; Popp, Jürgen; Zell, Roland; Deinhard-Emmer, Stefanie; Sokolov, Alexei V.; Yi, Zhenhuan; Scully, Marlan O.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)].
- ItemFLIm and raman spectroscopy for investigating biochemical changes of bovine pericardium upon genipin cross-linking(Basel : MDPI, 2020) Shaik, Tanveer Ahmed; Alfonso-Garcia, Alba; Richter, Martin; Korinth, Florian; Krafft, Christoph; Marcu, Laura; Popp, JürgenBiomaterials used in tissue engineering and regenerative medicine applications benefit from longitudinal monitoring in a non-destructive manner. Label-free imaging based on fluorescence lifetime imaging (FLIm) and Raman spectroscopy were used to monitor the degree of genipin (GE) cross-linking of antigen-removed bovine pericardium (ARBP) at three incubation time points (0.5, 1.0, and 2.5 h). Fluorescence lifetime decreased and the emission spectrum redshifted compared to that of uncross-linked ARBP. The Raman signature of GE-ARBP was resonance-enhanced due to the GE cross-linker that generated new Raman bands at 1165, 1326, 1350, 1380, 1402, 1470, 1506, 1535, 1574, 1630, 1728, and 1741 cm-1. These were validated through density functional theory calculations as cross-linker-specific bands. A multivariate multiple regression model was developed to enhance the biochemical specificity of FLIm parameters fluorescence intensity ratio (R2 = 0.92) and lifetime (R2 = 0.94)) with Raman spectral results. FLIm and Raman spectroscopy detected biochemical changes occurring in the collagenous tissue during the cross-linking process that were characterized by the formation of a blue pigment which affected the tissue fluorescence and scattering properties. In conclusion, FLIm parameters and Raman spectroscopy were used to monitor the degree of cross-linking non-destructively. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
- ItemNoise Sources and Requirements for Confocal Raman Spectrometers in Biosensor Applications(Basel : MDPI, 2021) Jahn, Izabella J.; Grjasnow, Alexej; John, Henry; Weber, Karina; Popp, Jürgen; Hauswald, WalterRaman spectroscopy probes the biochemical composition of samples in a non-destructive, non-invasive and label-free fashion yielding specific information on a molecular level. Nevertheless, the Raman effect is very weak. The detection of all inelastically scattered photons with highest efficiency is therefore crucial as well as the identification of all noise sources present in the system. Here we provide a study for performance comparison and assessment of different spectrometers for confocal Raman spectroscopy in biosensor applications. A low-cost, home-built Raman spectrometer with a complementary metal-oxide-semiconductor (CMOS) camera, a middle price-class mini charge-coupled device (CCD) Raman spectrometer and a laboratory grade confocal Raman system with a deeply cooled CCD detector are compared. It is often overlooked that the sample itself is the most important “optical” component in a Raman spectrometer and its properties contribute most significantly to the signal-to-noise ratio. For this purpose, different representative samples: a crystalline silicon wafer, a polypropylene sample and E. coli bacteria were measured under similar conditions using the three confocal Raman spectrometers. We show that biosensor applications do not in every case profit from the most expensive equipment. Finally, a small Raman database of three different bacteria species is set up with the middle price-class mini CCD Raman spectrometer in order to demonstrate the potential of a compact setup for pathogen discrimination.
- ItemFLIM data analysis based on Laguerre polynomial decomposition and machine-learning(Bellingham, Wash. : SPIE, 2021) Guo, Shuxia; Silge, Anja; Bae, Hyeonsoo; Tolstik, Tatiana; Meyer, Tobias; Matziolis, Georg; Schmitt, Michael; Popp, Jürgen; Bocklitz, ThomasSignificance: The potential of fluorescence lifetime imaging microscopy (FLIM) is recently being recognized, especially in biological studies. However, FLIM does not directly measure the lifetimes, rather it records the fluorescence decay traces. The lifetimes and/or abundances have to be estimated from these traces during the phase of data processing. To precisely estimate these parameters is challenging and requires a well-designed computer program. Conventionally employed methods, which are based on curve fitting, are computationally expensive and limited in performance especially for highly noisy FLIM data. The graphical analysis, while free of fit, requires calibration samples for a quantitative analysis. Aim: We propose to extract the lifetimes and abundances directly from the decay traces through machine learning (ML). Approach: The ML-based approach was verified with simulated testing data in which the lifetimes and abundances were known exactly. Thereafter, we compared its performance with the commercial software SPCImage based on datasets measured from biological samples on a time-correlated single photon counting system. We reconstructed the decay traces using the lifetime and abundance values estimated by ML and SPCImage methods and utilized the root-mean-squared-error (RMSE) as marker. Results: The RMSE, which represents the difference between the reconstructed and measured decay traces, was observed to be lower for ML than for SPCImage. In addition, we could demonstrate with a three-component analysis the high potential and flexibility of the ML method to deal with more than two lifetime components.
- ItemA polyyne toxin produced by an antagonistic bacterium blinds and lyses a Chlamydomonad alga(Washington, DC : National Acad. of Sciences, 2021) Hotter, Vivien; Zopf, David; Kim, Hak Joong; Silge, Anja; Schmitt, Michael; Aiyar, Prasad; Fleck, Johanna; Matthäus, Christian; Hniopek, Julian; Yan, Qing; Loper, Joyce; Sasso, Severin; Hertweck, Christian; Popp, Jürgen; Mittag, MariaAlgae are key contributors to global carbon fixation and form the basis of many food webs. In nature, their growth is often supported or suppressed by microorganisms. The bacterium Pseudomonas protegens Pf-5 arrests the growth of the green unicellular alga Chlamydomonas reinhardtii, deflagellates the alga by the cyclic lipopeptide orfamide A, and alters its morphology [P. Aiyar et al., Nat. Commun. 8, 1756 (2017)]. Using a combination of Raman microspectroscopy, genome mining, and mutational analysis, we discovered a polyyne toxin, protegencin, which is secreted by P. protegens, penetrates the algal cells, and causes destruction of the carotenoids of their primitive visual system, the eyespot. Together with secreted orfamide A, protegencin thus prevents the phototactic behavior of C. reinhardtii. A mutant of P. protegens deficient in protegencin production does not affect growth or eyespot carotenoids of C. reinhardtii. Protegencin acts in a direct and destructive way by lysing and killing the algal cells. The toxic effect of protegencin is also observed in an eyeless mutant and with the colony-forming Chlorophyte alga Gonium pectorale. These data reveal a two-pronged molecular strategy involving a cyclic lipopeptide and a conjugated tetrayne used by bacteria to attack select Chlamydomonad algae. In conjunction with the bloom-forming activity of several chlorophytes and the presence of the protegencin gene cluster in over 50 different Pseudomonas genomes [A. J. Mullins et al., bioRxiv [Preprint] (2021). https://www.biorxiv.org/content/10.1101/2021.03.05.433886v1 (Accessed 17 April 2021)], these data are highly relevant to ecological interactions between Chlorophyte algae and Pseudomonadales bacteria.
- ItemAssessment of shifted excitation Raman difference spectroscopy in highly fluorescent biological samples(Cambridge : Soc., 2021) Korinth, Florian; Shaik, Tanveer Ahmed; Popp, Jürgen; Krafft, ChristophShifted excitation Raman difference spectroscopy (SERDS) can be used as an instrumental baseline correction technique to retrieve Raman bands in highly fluorescent samples. Genipin (GE) cross-linked equine pericardium (EP) was used as a model system since a blue pigment is formed upon cross-linking, which results in a strong fluorescent background in the Raman spectra. EP was cross-linked with 0.25% GE solution for 0.5 h, 2 h, 4 h, 6 h, 12 h, and 24 h, and compared with corresponding untreated EP. Raman spectra were collected with three different excitation wavelengths. For the assessment of the SERDS technique, the preprocessed SERDS spectra of two excitation wavelengths (784 nm-786 nm) were compared with the mathematical baseline-corrected Raman spectra at 785 nm excitation using extended multiplicative signal correction, rubberband, the sensitive nonlinear iterative peak and polynomial fitting algorithms. Whereas each baseline correction gave poor quality spectra beyond 6 h GE crosslinking with wave-like artefacts, the SERDS technique resulted in difference spectra, that gave superior reconstructed spectra with clear collagen and resonance enhanced GE pigment bands with lower standard deviation. Key for this progress was an advanced difference optimization approach that is described here. Furthermore, the results of the SERDS technique were independent of the intensity calibration because the system transfer response was compensated by calculating the difference spectrum. We conclude that this SERDS strategy can be transferred to Raman studies on biological and non-biological samples with a strong fluorescence background at 785 nm and also shorter excitation wavelengths which benefit from more intense scattering intensities and higher quantum efficiencies of CCD detectors. This journal is
- ItemNovel Biobased Self-Healing Ionomers Derived from Itaconic Acid Derivates(Weinheim : Wiley-VCH, 2021) Meurer, Josefine; Hniopek, Julian; Dahlke, Jan; Schmitt, Michael; Popp, Jürgen; Zechel, Stefan; Hager, Martin D.This article presents novel biobased ionomers featuring self-healing abilities. These smart materials are synthesized from itaconic acid derivates. Large quantities of itaconic acid can be produced from diverse biomass like corn, rice, and others. This study presents a comprehensive investigation of their thermal and mechanical properties via differential scanning calorimetry (DSC), thermo gravimetric analysis (TGA), and FT-Raman and FT-IR measurements as well as dynamic mechanic analysis. Within all these measurements, different kinds of structure-property relationships could be derived from these measurements. For example, the proportion of ionic groups enormously influences the self-healing efficiency. The investigation of the self-healing abilities reveals healing efficiencies up to 99% in 2 h at 90 °C for the itaconic acid based ionomer with the lowest ionic content. © 2020 The Authors. Macromolecular Rapid Communications published by Wiley-VCH GmbH
- ItemPredictive Modeling of Antibiotic Susceptibility in E. Coli Strains Using the U-Net Network and One-Class Classification(New York, NY : IEEE, 2020) Ali, Nairveen; Kirchhoff, Johanna; Onoja, Patrick Igoche; Tannert, Astrid; Neugebauer, Ute; Popp, Jürgen; Bocklitz, ThomasThe antibiotic resistance of bacterial pathogens has become one of the most serious global health issues due to misusing and overusing of antibiotics. Recently, different technologies were developed to determine bacteria susceptibility towards antibiotics; however, each of these technologies has its advantages and limitations in clinical applications. In this contribution, we aim to assess and automate the detection of bacterial susceptibilities towards three antibiotics; i.e. ciprofloxacin, cefotaxime and piperacillin using a combination of image processing and machine learning algorithms. Therein, microscopic images were collected from different E. coli strains, then the convolutional neural network U-Net was implemented to segment the areas showing bacteria. Subsequently, the encoder part of the trained U-Net was utilized as a feature extractor, and the U-Net bottleneck features were utilized to predict the antibiotic susceptibility of E. coli strains using a one-class support vector machine (OCSVM). This one-class model was always trained on images of untreated controls of each bacterial strain while the image labels of treated bacteria were predicted as control or non-control images. If an image of treated bacteria is predicted as control, we assume that these bacteria resist this antibiotic. In contrast, the sensitive bacteria show different morphology of the control bacteria; therefore, images collected from these treated bacteria are expected to be classified as non-control. Our results showed 83% area under the receiver operating characteristic (ROC) curve when OCSVM models were built using the U-Net bottleneck features of control bacteria images only. Additionally, the mean sensitivities of these one-class models are 91.67% and 86.61% for cefotaxime and piperacillin; respectively. The mean sensitivity for the prediction of ciprofloxacin is only 59.72% as the bacteria morphology was not fully detected by the proposed method.