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- ItemDetection 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, RoystonThe 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.
- ItemComparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study(Columbus, Ohio : American Chemical Society, 2020) Guo S.; Beleites C.; Neugebauer U.; Abalde-Cela S.; Afseth N.K.; Alsamad F.; Anand S.; Araujo-Andrade C.; Aškrabić S.; Avci E.; Baia M.; Baranska M.; Baria E.; Batista De Carvalho L.A.E.; De Bettignies P.; Bonifacio A.; Bonnier F.; Brauchle E.M.; Byrne H.J.; Chourpa I.; Cicchi R.; Cuisinier F.; Culha M.; Dahms M.; David C.; Duponchel L.; Duraipandian S.; El-Mashtoly S.F.; Ellis D.I.; Eppe G.; Falgayrac G.; Gamulin O.; Gardner B.; Gardner P.; Gerwert K.; Giamarellos-Bourboulis E.J.; Gizurarson S.; Gnyba M.; Goodacre R.; Grysan P.; Guntinas-Lichius O.; Helgadottir H.; Grošev V.M.; Kendall C.; Kiselev R.; Kölbach M.; Krafft C.; Krishnamoorthy S.; Kubryck P.; Lendl B.; Loza-Alvarez P.; Lyng F.M.; Machill S.; Malherbe C.; Marro M.; Marques M.P.M.; Matuszyk E.; Morasso C.F.; Moreau M.; Muhamadali H.; Mussi V.; Notingher I.; Pacia M.Z.; Pavone F.S.; Penel G.; Petersen D.; Piot O.; Rau J.V.; Richter M.; Rybarczyk M.K.; Salehi H.; Schenke-Layland K.; Schlücker S.; Schosserer M.; Schütze K.; Sergo V.; Sinjab F.; Smulko J.; Sockalingum G.D.; Stiebing C.; Stone N.; Untereiner V.; Vanna R.; Wieland K.; Popp J.; Bocklitz T.The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies. © 2020 American Chemical Society.
- ItemTowards multiple readout application of plasmonic arrays(Frankfurt, M. : Beilstein-Institut zur Förderung der Chemischen Wissenschaften, 2011) Cialla, D.; Weber, K.; Böhme, R.; Hübner, U.; Schneidewind, H.; Zeisberger, M.; Mattheis, R.; Möller, R.; Popp, J.In order to combine the advantages of fluorescence and surface-enhanced Raman spectroscopy (SERS) on the same chip platform, a nanostructured gold surface with a unique design, allowing both the sensitive detection of fluorescence light together with the specific Raman fingerprint of the fluorescent molecules, was established. This task requires the fabrication of plasmonic arrays that permit the binding of molecules of interest at different distances from the metallic surface. The most efficient SERS enhancement is achieved for molecules directly adsorbed on the metallic surface due to the strong field enhancement, but where, however, the fluorescence is quenched most efficiently. Furthermore, the fluorescence can be enhanced efficiently by careful adjustment of the optical behavior of the plasmonic arrays. In this article, the simultaneous application of SERS and fluorescence, through the use of various gold nanostructured arrays, is demonstrated by the realization of a DNA detection scheme. The results shown open the way to more flexible use of plasmonic arrays in bioanalytics.
- ItemMultimodal nonlinear imaging of atherosclerotic plaques differentiation of triglyceride and cholesterol deposits(Singapore [u.a.] : World Scientific Publishing, 2014) Matthäus, C.; Cicchi, R.; Meyer, T.; Lattermann, A.; Schmitt, M.; Romeike, B.F.M.; Krafft, C.; Dietzek, B.; Brehm, B.R.; Pavone, F.S.; Popp, J.Cardiovascular diseases in general and atherothrombosis as the most common of its individual disease entities is the leading cause of death in the developed countries. Therefore, visualization and characterization of inner arterial plaque composition is of vital diagnostic interest, especially for the early recognition of vulnerable plaques. Established clinical techniques provide valuable morphological information but cannot deliver information about the chemical composition of individual plaques. Therefore, spectroscopic imaging techniques have recently drawn considerable attention. Based on the spectroscopic properties of the individual plaque components, as for instance different types of lipids, the composition of atherosclerotic plaques can be analyzed qualitatively as well as quantitatively. Here, we compare the feasibility of multimodal nonlinear imaging combining two-photon fluorescence (TPF), coherent anti-Stokes Raman scattering (CARS) and second-harmonic generation (SHG) microscopy to contrast composition and morphology of lipid deposits against the surrounding matrix of connective tissue with diffraction limited spatial resolution. In this contribution, the spatial distribution of major constituents of the arterial wall and atherosclerotic plaques like elastin, collagen, triglycerides and cholesterol can be simultaneously visualized by a combination of nonlinear imaging methods, providing a powerful label-free complement to standard histopathological methods with great potential for in vivo application.
- ItemNanowire-supported plasmonic waveguide for remote excitation of surface-enhanced Raman scattering(London : Nature Publishing Group, 2014) Huang, Y.; Fang, Y.; Zhang, Z.; Zhu, L.; Sun, M.Due to its amazing ability to manipulate light at the nanoscale, plasmonics has become one of the most interesting topics in the field of light-matter interaction. As a promising application of plasmonics, surface-enhanced Raman scattering (SERS) has been widely used in scientific investigations and material analysis. The large enhanced Raman signals are mainly caused by the extremely enhanced electromagnetic field that results from localized surface plasmon polaritons. Recently, a novel SERS technology called remote SERS has been reported, combining both localized surface plasmon polaritons and propagating surface plasmon polaritons (PSPPs, or called plasmonic waveguide), which may be found in prominent applications in special circumstances compared to traditional local SERS. In this article, we review the mechanism of remote SERS and its development since it was first reported in 2009. Various remote metal systems based on plasmonic waveguides, such as nanoparticle-nanowire systems, single nanowire systems, crossed nanowire systems and nanowire dimer systems, are introduced, and recent novel applications, such as sensors, plasmon-driven surface-catalyzed reactions and Raman optical activity, are also presented. Furthermore, studies of remote SERS in dielectric and organic systems based on dielectric waveguides remind us that this useful technology has additional, tremendous application prospects that have not been realized in metal systems.
- ItemRaman-spectroscopy based cell identification on a microhole array chip(Basel : MDPI AG, 2014) Neugebauer, U.; Kurz, C.; Bocklitz, T.; Berger, T.; Velten, T.; Clement, J.H.; Krafft, C.; Popp, J.Circulating tumor cells (CTCs) from blood of cancer patients are valuable prognostic markers and enable monitoring responses to therapy. The extremely low number of CTCs makes their isolation and characterization a major technological challenge. For label-free cell identification a novel combination of Raman spectroscopy with a microhole array platform is described that is expected to support high-throughput and multiplex analyses. Raman spectra were registered from regularly arranged cells on the chip with low background noise from the silicon nitride chip membrane. A classification model was trained to distinguish leukocytes from myeloblasts (OCI-AML3) and breast cancer cells (MCF-7 and BT-20). The model was validated by Raman spectra of a mixed cell population. The high spectral quality, low destructivity and high classification accuracy suggests that this approach is promising for Raman activated cell sorting.