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- ItemRaman spectroscopy follows time-dependent changes in T lymphocytes isolated from spleen of endotoxemic mice(Rockville : American Association of Immunologists, 2019) Ramoji, Anuradha; Ryabchykov, Oleg; Galler, Kerstin; Tannert, Astrid; Markwart, Robby; Requardt, Robert Pascal; Rubio, Ignacio; Bauer, Michael; Bocklitz, Thomas W.; Popp, Jürgen; Neugebauer, UteT lymphocytes (T cells) are highly specialized members of the adaptive immune system and hold the key to the understanding the hosts’ response toward invading pathogen or pathogen-associated molecular patterns such as LPS. In this study, noninvasive Raman spectroscopy is presented as a label-free method to follow LPS-induced changes in splenic T cells during acute and postacute inflammatory phases (1, 4, 10, and 30 d) with a special focus on CD4+ and CD8+ T cells of endotoxemic C57BL/6 mice. Raman spectral analysis reveals highest chemical differences between CD4+ and CD8+ T cells originating from the control and LPS-treated mice during acute inflammation, and the differences are visible up to 10 d after the LPS insult. In the postacute phase, CD4+ and CD8+ T cells from treated and untreated mice could not be differentiated anymore, suggesting that T cells largely regained their original status. In sum, the biological information obtained from Raman spectra agrees with immunological readouts demonstrating that Raman spectroscopy is a well-suited, label-free method for following splenic T cell activation in systemic inflammation from acute to postacute phases. The method can also be applied to directly study tissue sections as is demonstrated for spleen tissue one day after LPS insult.T lymphocytes (T cells) are highly specialized members of the adaptive immune system and hold the key to the understanding the hosts’ response toward invading pathogen or pathogen-associated molecular patterns such as LPS. In this study, noninvasive Raman spectroscopy is presented as a label-free method to follow LPS-induced changes in splenic T cells during acute and postacute inflammatory phases (1, 4, 10, and 30 d) with a special focus on CD4+ and CD8+ T cells of endotoxemic C57BL/6 mice. Raman spectral analysis reveals highest chemical differences between CD4+ and CD8+ T cells originating from the control and LPS-treated mice during acute inflammation, and the differences are visible up to 10 d after the LPS insult. In the postacute phase, CD4+ and CD8+ T cells from treated and untreated mice could not be differentiated anymore, suggesting that T cells largely regained their original status. In sum, the biological information obtained from Raman spectra agrees with immunological readouts demonstrating that Raman spectroscopy is a well-suited, label-free method for following splenic T cell activation in systemic inflammation from acute to postacute phases. The method can also be applied to directly study tissue sections as is demonstrated for spleen tissue one day after LPS insult.
- ItemNew perspectives for viability studies with high-content analysis Raman spectroscopy (HCA-RS)(Berlin : Nature Publishing, 2019) Mondol, Abdullah S.; Töpfer, Natalie; Rüger, Jan; Neugebauer, Ute; Popp, Jürgen; Schie, Iwan W.Raman spectroscopy has been widely used in clinical and molecular biological studies, providing high chemical specificity without the necessity of labels and with little-to-no sample preparation. However, currently performed Raman-based studies of eukaryotic cells are still very laborious and time-consuming, resulting in a low number of sampled cells and questionable statistical validations. Furthermore, the approach requires a trained specialist to perform and analyze the experiments, rendering the method less attractive for most laboratories. In this work, we present a new high-content analysis Raman spectroscopy (HCA-RS) platform that overcomes the current challenges of conventional Raman spectroscopy implementations. HCA-RS allows sampling of a large number of cells under different physiological conditions without any user interaction. The performance of the approach is successfully demonstrated by the development of a Raman-based cell viability assay, i.e., the effect of doxorubicin concentration on monocytic THP-1 cells. A statistical model, principal component analysis combined with support vector machine (PCA-SVM), was found to successfully predict the percentage of viable cells in a mixed population and is in good agreement to results obtained by a standard cell viability assay. This study demonstrates the potential of Raman spectroscopy as a standard high-throughput tool for clinical and biological applications.
- ItemCorrelation of crystal violet biofilm test results of Staphylococcus aureus clinical isolates with Raman spectroscopic read-out(Chichester [u.a.] : Wiley, 2021) Ebert, Christina; Tuchscherr, Lorena; Unger, Nancy; Pöllath, Christine; Gladigau, Frederike; Popp, Jürgen; Löffler, Bettina; Neugebauer, UteBiofilm-related infections occur quite frequently in hospital settings and require rapid diagnostic identification as they are recalcitrant to antibiotic therapy and make special treatment necessary. One of the standard microbiological in vitro tests is the crystal violet test. It indirectly determines the amount of biofilm by measuring the optical density (OD) of the crystal violet-stained biofilm matrix and cells. However, this test is quite time-consuming, as it requires bacterial cultivation up to several days. In this study, we correlate fast Raman spectroscopic read-out of clinical Staphylococcus aureus isolates from 47 patients with different disease background with their biofilm-forming characteristics. Included were low (OD < 10), medium (OD ≥ 10 and ≤20), and high (OD > 20) biofilm performers as determined by the crystal violet test. Raman spectroscopic analysis of the bacteria revealed most spectral differences between high and low biofilm performers in the fingerprint region between 750 and 1150 cm−1. Using partial least square regression (PLSR) analysis on the Raman spectra involving the three categories of biofilm formation, it was possible to obtain a slight linear correlation of the Raman spectra with the biofilm OD values. The PLSR loading coefficient highlighted spectral differences between high and low biofilm performers for Raman bands that represent nucleic acids, carbohydrates, and proteins. Our results point to a possible application of Raman spectroscopy as a fast prediction tool for biofilm formation of bacterial strains directly after isolation from the infected patient. This could help clinicians make timely and adapted therapeutic decision in future.
- 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
- ItemStructural insights into heme binding to IL-36α proinflammatory cytokine(Berlin : Nature Publishing, 2019) Wißbrock, Amelie; Goradia, Nishit; Kumar, Amit; Paul George, Ajay Abisheck; Kühl, Toni; Bellstedt, Peter; Ramachandran, Ramadurai; Hoffmann, Patrick; Galler, Kerstin; Popp, Jürgen; Neugebauer, Ute; Hampel, Kornelia; Zimmermann, Bastian; Adam, Susanne; Wiendl, Maximilian; Krönke, Gerhard; Hamza, Iqbal; Heinemann, Stefan H.; Frey, Silke; Hueber, Axel J.; Ohlenschläger, Oliver; Imhof, DianaCytokines of the interleukin (IL)-1 family regulate immune and inflammatory responses. The recently discovered IL-36 family members are involved in psoriasis, rheumatoid arthritis, and pulmonary diseases. Here, we show that IL-36α interacts with heme thereby contributing to its regulation. Based on in-depth spectroscopic analyses, we describe two heme-binding sites in IL-36α that associate with heme in a pentacoordinated fashion. Solution NMR analysis reveals structural features of IL-36α and its complex with heme. Structural investigation of a truncated IL-36α supports the notion that the N-terminus is necessary for association with its cognate receptor. Consistent with our structural studies, IL-36-mediated signal transduction was negatively regulated by heme in synovial fibroblast-like synoviocytes from rheumatoid arthritis patients. Taken together, our results provide a structural framework for heme-binding proteins and add IL-1 cytokines to the group of potentially heme-regulated proteins.
- Item3-Step flow focusing enables multidirectional imaging of bioparticles for imaging flow cytometry(Cambridge : RSC, 2020) Kleiber, Andreas; Ramoji, Anuradha; Mayer, Günter; Neugebauer, Ute; Popp, Jürgen; Henkel, ThomasMultidirectional imaging flow cytometry (mIFC) extends conventional imaging flow cytometry (IFC) for the image-based measurement of 3D-geometrical features of particles. The innovative core is a flow rotation unit in which a vertical sample lamella is incrementally rotated by 90 degrees into a horizontal lamella. The required multidirectional views are generated by guiding all particles at a controllable shear flow position of the parabolic velocity profile of the capillary slit detection chamber. All particles pass the detection chamber in a two-dimensional sheet under controlled rotation while each particle is imaged multiple times. This generates new options for automated particle analysis. In an experimental application, we used our system for the accurate classification of 15 species of pollen based on 3D-morphological information. We demonstrate how the combination of multi directional imaging with advanced machine learning algorithms can improve the accuracy of automated bio-particle classification. As an additional benefit, we significantly decrease the number of false positives in the classification of foreign particles,i.e.those elements which do not belong to one of the trained classes by the 3D-extension of the classification algorithm. © The Royal Society of Chemistry 2020.
- ItemSingle cell analysis in native tissue: Quantification of the retinoid content of hepatic stellate cells([London] : Macmillan Publishers Limited, part of Springer Nature, 2016) Galler, Kerstin; Requardt, Robert Pascal; Glaser, Uwe; Markwart, Robby; Bocklitz, Thomas; Bauer, Michael; Popp, Jürgen; Neugebauer, UteHepatic stellate cells (HSCs) are retinoid storing cells in the liver: The retinoid content of those cells changes depending on nutrition and stress level. There are also differences with regard to a HSC’s anatomical position in the liver. Up to now, retinoid levels were only accessible from bulk measurements of tissue homogenates or cell extracts. Unfortunately, they do not account for the intercellular variability. Herein, Raman spectroscopy relying on excitation by the minimally destructive wavelength 785 nm is introduced for the assessment of the retinoid state of single HSCs in freshly isolated, unprocessed murine liver lobes. A quantitative estimation of the cellular retinoid content is derived. Implications of the retinoid content on hepatic health state are reported. The Raman-based results are integrated with histological assessments of the tissue samples. This spectroscopic approach enables single cell analysis regarding an important cellular feature in unharmed tissue.
- ItemVibrational Spectroscopic Investigation of Blood Plasma and Serum by Drop Coating Deposition for Clinical Application(Basel : Molecular Diversity Preservation International (MDPI), 2021) Huang, Jing; Ali, Nairveen; Quansah, Elsie; Guo, Shuxia; Noutsias, Michel; Meyer-Zedler, Tobias; Bocklitz, Thomas; Popp, Jürgen; Neugebauer, Ute; Ramoji, AnuradhaIn recent decades, vibrational spectroscopic methods such as Raman and FT-IR spectroscopy are widely applied to investigate plasma and serum samples. These methods are combined with drop coating deposition techniques to pre-concentrate the biomolecules in the dried droplet to improve the detected vibrational signal. However, most often encountered challenge is the inhomogeneous redistribution of biomolecules due to the coffee-ring effect. In this study, the variation in biomolecule distribution within the dried-sample droplet has been investigated using Raman and FT-IR spectroscopy and fluorescence lifetime imaging method. The plasma-sample from healthy donors were investigated to show the spectral differences between the inner and outer-ring region of the dried-sample droplet. Further, the preferred location of deposition of the most abundant protein albumin in the blood during the drying process of the plasma has been illustrated by using deuterated albumin. Subsequently, two patients with different cardiac-related diseases were investigated exemplarily to illustrate the variation in the pattern of plasma and serum biomolecule distribution during the drying process and its impact on patient-stratification. The study shows that a uniform sampling position of the droplet, both at the inner and the outer ring, is necessary for thorough clinical characterization of the patient’s plasma and serum sample using vibrational spectroscopy.
- 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.