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    Application of molecular SERS nanosensors: where we stand and where we are headed towards?
    (Berlin ; Heidelberg : Springer, 2020) Jahn I.J.; Mühlig A.; Cialla-May D.
    Molecular specific and highly sensitive detection is the driving force of the surface-enhanced Raman spectroscopy (SERS) community. The technique opens the window to the undisturbed monitoring of cellular processes in situ or to the quantification of small molecular species that do not deliver Raman signals. The smart design of molecular SERS nanosensors makes it possible to indirectly but specifically detect, e.g. reactive oxygen species, carbon monoxide or potentially toxic metal ions. Detection schemes evolved over the years from simple metallic colloidal nanoparticles functionalized with sensing molecules that show uncontrolled aggregation to complex nanostructures with magnetic properties making the analysis of complex environmental samples possible. The present article gives the readership an overview of the present research advancements in the field of molecular SERS sensors, highlighting future trends. © 2020, The Author(s).
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    FLIm 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, Jürgen
    Biomaterials 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.
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    A Review on Data Fusion of Multidimensional Medical and Biomedical Data
    (Basel : MDPI, 2022) Azam, Kazi Sultana Farhana; Ryabchykov, Oleg; Bocklitz, Thomas
    Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis and prognosis. In this paper, we present an overview of the advances achieved over the last decades in data fusion approaches in the context of the medical and biomedical fields. We collected approaches for interpreting multiple sources of data in different combinations: image to image, image to biomarker, spectra to image, spectra to spectra, spectra to biomarker, and others. We found that the most prevalent combination is the image-to-image fusion and that most data fusion approaches were applied together with deep learning or machine learning methods.
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    Linear and non-linear optical imaging of cancer cells with silicon nanoparticles
    (Basel : Molecular Diversity Preservation International (MDPI), 2016) Tolstik, Elen; Osminkina, Liubov A.; Akimov, Denis; Gongalsky, Maksim B.; Kudryavtsev, Andrew A.; Timoshenko, Victor Yu.; Heintzmann, Rainer; Sivakov, Vladimir; Popp, Jürgen
    New approaches for visualisation of silicon nanoparticles (SiNPs) in cancer cells are realised by means of the linear and nonlinear optics in vitro. Aqueous colloidal solutions of SiNPs with sizes of about 10–40 nm obtained by ultrasound grinding of silicon nanowires were introduced into breast cancer cells (MCF-7 cell line). Further, the time-varying nanoparticles enclosed in cell structures were visualised by high-resolution structured illumination microscopy (HR-SIM) and micro-Raman spectroscopy. Additionally, the nonlinear optical methods of two-photon excited fluorescence (TPEF) and coherent anti-Stokes Raman scattering (CARS) with infrared laser excitation were applied to study the localisation of SiNPs in cells. Advantages of the nonlinear methods, such as rapid imaging, which prevents cells from overheating and larger penetration depth compared to the single-photon excited HR-SIM, are discussed. The obtained results reveal new perspectives of the multimodal visualisation and precise detection of the uptake of biodegradable non-toxic SiNPs by cancer cells and they are discussed in view of future applications for the optical diagnostics of cancer tumours.
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    A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species
    (Basel : MDPI, 2019) Silge, Anja; Moawad, Amira A.; Bocklitz, Thomas; Fischer, Katja; Rösch, Petra; Roesler, Uwe; Elschner, Mandy C.; Popp, Jürgen; Neubauer, Heinrich
    Burkholderia (B.) mallei, the causative agent of glanders, and B. pseudomallei, the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and similar clinical symptoms in human and animals make the differentiation from each other and other Burkholderia species challenging. The increased resistance against many antibiotics implies the need for fast and robust identification methods. The use of Raman microspectroscopy in microbial diagnostic has the potential for rapid and reliable identification. Single bacterial cells are directly probed and a broad range of phenotypic information is recorded, which is subsequently analyzed by machine learning methods. Burkholderia were handled under biosafety level 1 (BSL 1) conditions after heat inactivation. The clusters of the spectral phenotypes and the diagnostic relevance of the Burkholderia spp. were considered for an advanced hierarchical machine learning approach. The strain panel for training involved 12 B. mallei, 13 B. pseudomallei and 11 other Burkholderia spp. type strains. The combination of top- and sub-level classifier identified the mallei-complex with high sensitivities (>95%). The reliable identification of unknown B. mallei and B. pseudomallei strains highlighted the robustness of the machine learning-based Raman spectroscopic assay. © 2019 by the authors
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    Direct raman spectroscopic measurements of biological nitrogen fixation under natural conditions: An analytical approach for studying nitrogenase activity
    (Columbus, Ohio : American Chemical Society, 2016) Jochum, Tobias; Fastnacht, Agnes; Trumbore, Susan E.; Popp, Jürgen; Frosch, Torsten
    Biological N2 fixation is a major input of bioavailable nitrogen, which represents the most frequent factor limiting the agricultural production throughout the world. Especially, the symbiotic association between legumes and Rhizobium bacteria can provide substantial amounts of nitrogen (N) and reduce the need for industrial fertilizers. Despite its importance in the global N cycle, rates of biological nitrogen fixation have proven difficult to quantify. In this work, we propose and demonstrate a simple analytical approach to measure biological N2 fixation rates directly without a proxy or isotopic labeling. We determined a mean N2 fixation rate of 78 ± 5 μmol N2 (g dry weight nodule)-1 h-1 of a Medicago sativa-Rhizobium consortium by continuously analyzing the amount of atmospheric N2 in static environmental chambers with Raman gas spectroscopy. By simultaneously analyzing the CO2 uptake and photosynthetic plant activity, we think that a minimum CO2 mixing ratio might be needed for natural N2 fixation and only used the time interval above this minimum CO2 mixing ratio for N2 fixation rate calculations. The proposed approach relies only on noninvasive measurements of the gas phase and, given its simplicity, indicates the potential to estimate biological nitrogen fixation of legume symbioses not only in laboratory experiments. The same methods can presumably also be used to detect N2 fluxes by denitrification from ecosystems to the atmosphere. (Figure Presented).
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    Detection of Protein Glycosylation Using Tip-Enhanced Raman Scattering
    (Columbus, Ohio : American Chemical Society, 2016) Cowcher, David P.; Deckert-Gaudig, Tanja; Brewster, Victoria L.; Ashton, Lorna; Deckert, Volker; Goodacre, Royston
    The correct glycosylation of biopharmaceutical glycoproteins and their formulations is essential for them to have the desired therapeutic effect on the patient. It has recently been shown that Raman spectroscopy can be used to quantify the proportion of glycosylated protein from mixtures of native and glycosylated forms of bovine pancreatic ribonuclease (RNase). Here we show the first steps toward not only the detection of glycosylation status but the characterization of glycans themselves from just a few protein molecules at a time using tip-enhanced Raman scattering (TERS). While this technique generates complex data that are very dependent on the protein orientation, with the careful development of combined data preprocessing, univariate and multivariate analysis techniques, we have shown that we can distinguish between the native and glycosylated forms of RNase. Many glycoproteins contain populations of subtly different glycoforms; therefore, with stricter orientation control, we believe this has the potential to lead to further glycan characterization using TERS, which would have use in biopharmaceutical synthesis and formulation research.
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    Modified PCA and PLS: Towards a better classification in Raman spectroscopy–based biological applications
    (New York, NY : Wiley Interscience, 2020) Guo, Shuxia; Rösch, Petra; Popp, Jürgen; Bocklitz, Thomas
    Raman spectra of biological samples often exhibit variations originating from changes of spectrometers, measurement conditions, and cultivation conditions. Such unwanted variations make a classification extremely challenging, especially if they are more significant compared with the differences between groups to be separated. A classifier is prone to such unwanted variations (ie, intragroup variations) and can fail to learn the patterns that can help separate different groups (ie, intergroup differences). This often leads to a poor generalization performance and a degraded transferability of the trained model. A natural solution is to separate the intragroup variations from the intergroup differences and build the classifier based on merely the latter information, for example, by a well-designed feature extraction. This forms the idea of this contribution. Herein, we modified two commonly applied feature extraction approaches, principal component analysis (PCA) and partial least squares (PLS), in order to extract merely the features representing the intergroup differences. Both of the methods were verified with two Raman spectral datasets measured from bacterial cultures and colon tissues of mice, respectively. In comparison to ordinary PCA and PLS, the modified PCA was able to improve the prediction on the testing data that bears significant difference to the training data, while the modified PLS could help avoid overfitting and lead to a more stable classification. © 2019 The Authors. Journal of Chemometrics published by John Wiley & Sons Ltd
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    Correlation 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, Ute
    Biofilm-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.
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    Isolation of bacteria from artificial bronchoalveolar lavage fluid using density gradient centrifugation and their accessibility by Raman spectroscopy
    (Berlin [u.a.] : Springer, 2021) Wichmann, Christina; Rösch, Petra; Popp, Jürgen
    Raman spectroscopy is an analytical method to identify medical samples of bacteria. Because Raman spectroscopy detects the biochemical properties of a cell, there are many factors that can influence and modify the Raman spectra of bacteria. One possible influence is a proper method for isolation of the bacteria. Medical samples in particular never occur in purified form, so a Raman-compatible isolation method is needed which does not affect the bacteria and thus the resulting spectra. In this study, we present a Raman-compatible method for isolation of bacteria from bronchoalveolar lavage (BAL) fluid using density gradient centrifugation. In addition to measuring the bacteria from a patient sample, the yield and the spectral influence of the isolation on the bacteria were investigated. Bacteria isolated from BAL fluid show additional peaks in comparison to pure culture bacteria, which can be attributed to components in the BAL sample. The isolation gradient itself has no effect on the spectra, and with a yield of 63% and 78%, the method is suitable for isolation of low concentrations of bacteria from a complex matrix. Graphical abstract.