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- ItemCharacterisation of Methicillin-Resistant Staphylococcus aureus from Alexandria, Egypt(Basel : MDPI, 2023) Monecke, Stefan; Bedewy, Amira K.; Müller, Elke; Braun, Sascha D.; Diezel, Celia; Elsheredy, Amel; Kader, Ola; Reinicke, Martin; Ghazal, Abeer; Rezk, Shahinda; Ehricht, RalfThe present study aims to characterise clinical MRSA isolates from a tertiary care centre in Egypt’s second-largest city, Alexandria. Thirty isolates collected in 2020 were genotypically characterised by microarray to detect their resistance and virulence genes and assign them to clonal complexes (CC) and strains. Isolates belonged to 11 different CCs and 14 different strains. CC15-MRSA-[V+fus] (n = 6), CC1-MRSA-[V+fus+tir+ccrA/B-1] (PVL+) (n = 5) as well as CC1-MRSA-[V+fus+tir+ccrA/B-1] and CC1153-MRSA-[V+fus] (PVL+) (both with n = 3) were the most common strains. Most isolates (83%) harboured variant or composite SCCmec V or VI elements that included the fusidic acid resistance gene fusC. The SCCmec [V+fus+tir+ccrA/B-1] element of one of the CC1 isolates was sequenced, revealing a presence not only of fusC but also of blaZ, aacA-aphD and other resistance genes. PVL genes were also common (40%). The hospital-acquired MRSA CC239-III strain was only found twice. A comparison to data from a study on strains collected in 2015 (Montelongo et al., 2022) showed an increase in fusC and PVL carriage and a decreasing prevalence of the CC239 strain. These observations indicate a diffusion of community-acquired strains into hospital settings. The beta-lactam use in hospitals and the widespread fusidic acid consumption in the community might pose a selective pressure that favours MRSA strains with composite SCCmec elements comprising mecA and fusC. This is an unsettling trend, but more MRSA typing data from Egypt are required.
- ItemSemantic segmentation of non-linear multimodal images for disease grading of inflammatory bowel disease: A segnet-based application([Sétubal] : SCITEPRESS - Science and Technology Publications Lda., 2019) Pradhan, Pranita; Meyer, Tobias; Vieth, Michael; Stallmach, Andreas; Waldner, Maximilian; Schmitt, Michael; Popp, Juergen; Bocklitz, Thomas; De Marsico, Maria; Sanniti di Baja, Gabriella; Fred, AnaNon-linear multimodal imaging, the combination of coherent anti-stokes Raman scattering (CARS), two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), has shown its potential to assist the diagnosis of different inflammatory bowel diseases (IBDs). This label-free imaging technique can support the ‘gold-standard’ techniques such as colonoscopy and histopathology to ensure an IBD diagnosis in clinical environment. Moreover, non-linear multimodal imaging can measure biomolecular changes in different tissue regions such as crypt and mucosa region, which serve as a predictive marker for IBD severity. To achieve a real-time assessment of IBD severity, an automatic segmentation of the crypt and mucosa regions is needed. In this paper, we semantically segment the crypt and mucosa region using a deep neural network. We utilized the SegNet architecture (Badrinarayanan et al., 2015) and compared its results with a classical machine learning approach. Our trained SegNet mod el achieved an overall F1 score of 0.75. This model outperformed the classical machine learning approach for the segmentation of the crypt and mucosa region in our study.
- ItemSurface-Enhanced Raman Spectroscopy to Characterize Different Fractions of Extracellular Vesicles from Control and Prostate Cancer Patients(Basel : MDPI, 2021) Osei, Eric Boateng; Paniushkina, Liliia; Wilhelm, Konrad; Popp, Jürgen; Nazarenko, Irina; Krafft, ChristophExtracellular vesicles (EVs) are membrane-enclosed structures ranging in size from about 60 to 800 nm that are released by the cells into the extracellular space; they have attracted interest as easily available biomarkers for cancer diagnostics. In this study, EVs from plasma of control and prostate cancer patients were fractionated by differential centrifugation at 5000× g, 12,000× g and 120,000× g. The remaining supernatants were purified by ultrafiltration to produce EV-depleted free-circulating (fc) fractions. Spontaneous Raman and surface-enhanced Raman spectroscopy (SERS) at 785 nm excitation using silver nanoparticles (AgNPs) were employed as label-free techniques to collect fingerprint spectra and identify the fractions that best discriminate between control and cancer patients. SERS spectra from 10 µL droplets showed an enhanced Raman signature of EV-enriched fractions that were much more intense for cancer patients than controls. The Raman spectra of dehydrated pellets of EV-enriched fractions without AgNPs were dominated by spectral contributions of proteins and showed variations in S-S stretch, tryptophan and protein secondary structure bands between control and cancer fractions. We conclude that the AgNPs-mediated SERS effect strongly enhances Raman bands in EV-enriched fractions, and the fractions, EV12 and EV120 provide the best separation of cancer and control patients by Raman and SERS spectra.
- ItemFiber-based SORS-SERDS system and chemometrics for the diagnostics and therapy monitoring of psoriasis inflammatory disease in vivo(Washington, DC : Optica, 2021-1-28) Schleusener, Johannes; Guo, Shuxia; Darvin, Maxim E.; Thiede, Gisela; Chernavskaia, Olga; Knorr, Florian; Lademann, Jürgen; Popp, Jürgen; Bocklitz, Thomas W.Psoriasis is considered a widespread dermatological disease that can strongly affect the quality of life. Currently, the treatment is continued until the skin surface appears clinically healed. However, lesions appearing normal may contain modifications in deeper layers. To terminate the treatment too early can highly increase the risk of relapses. Therefore, techniques are needed for a better knowledge of the treatment process, especially to detect the lesion modifications in deeper layers. In this study, we developed a fiber-based SORS-SERDS system in combination with machine learning algorithms to non-invasively determine the treatment efficiency of psoriasis. The system was designed to acquire Raman spectra from three different depths into the skin, which provide rich information about the skin modifications in deeper layers. This way, it is expected to prevent the occurrence of relapses in case of a too short treatment. The method was verified with a study of 24 patients upon their two visits: the data is acquired at the beginning of a standard treatment (visit 1) and four months afterwards (visit 2). A mean sensitivity of ≥85% was achieved to distinguish psoriasis from normal skin at visit 1. At visit 2, where the patients were healed according to the clinical appearance, the mean sensitivity was ≈65%.
- ItemAutofluorescence guided welding of heart tissue by laser pulse bursts at 1550 nm(Washington, DC : Optica, 2020) Litvinova, Karina; Chernysheva, Maria; Stegemann, Berthold; Leyva, FranciscoWound healing and other surgical technologies traditionally solved by suturing and stapling have recently been enhanced by the application of laser tissue welding. The usage of high energy laser radiation to anastomose tissues eliminates a foreign body reaction, reduces scar formation, and allows for the creation of watertight closure. In the current work, we show that an ultrafast pulsed fibre laser beam with 183 µJ·cm−2 energy fluence at 1550 nm provides successful welding of dissected chicken heart walls with the tensile strength of 1.03±0.12 kg·cm−2 equal to that of native tissue. The welding process was monitored employing fluorescence spectroscopy that detects the biochemical composition of tissues. We believe that fluorescence spectroscopy guided laser tissue welding is a promising approach for decreasing wound healing times and the avoiding risks of postoperative complications.
- ItemCharacterization and prediction of the mechanism of action of antibiotics through NMR metabolomics(London : BioMed Central, 2016) Hoerr, Verena; Duggan, Gavin E.; Zbytnuik, Lori; Poon, Karen K.H.; Große, Christina; Neugebauer, Ute; Methling, Karen; Löffler, Bettina; Vogel, Hans J.Background: The emergence of antibiotic resistant pathogenic bacteria has reduced our ability to combat infectious diseases. At the same time the numbers of new antibiotics reaching the market have decreased. This situation has created an urgent need to discover novel antibiotic scaffolds. Recently, the application of pattern recognition techniques to identify molecular fingerprints in ‘omics’ studies, has emerged as an important tool in biomedical research and laboratory medicine to identify pathogens, to monitor therapeutic treatments or to develop drugs with improved metabolic stability, toxicological profile and efficacy. Here, we hypothesize that a combination of metabolic intracellular fingerprints and extracellular footprints would provide a more comprehensive picture about the mechanism of action of novel antibiotics in drug discovery programs. Results: In an attempt to integrate the metabolomics approach as a classification tool in the drug discovery processes, we have used quantitative 1H NMR spectroscopy to study the metabolic response of Escherichia coli cultures to different antibiotics. Within the frame of our study the effects of five different and well-known antibiotic classes on the bacterial metabolome were investigated both by intracellular fingerprint and extracellular footprint analysis. The metabolic fingerprints and footprints of bacterial cultures were affected in a distinct manner and provided complementary information regarding intracellular and extracellular targets such as protein synthesis, DNA and cell wall. While cell cultures affected by antibiotics that act on intracellular targets showed class-specific fingerprints, the metabolic footprints differed significantly only when antibiotics that target the cell wall were applied. In addition, using a training set of E. coli fingerprints extracted after treatment with different antibiotic classes, the mode of action of streptomycin, tetracycline and carbenicillin could be correctly predicted. Conclusion: The metabolic profiles of E. coli treated with antibiotics with intracellular and extracellular targets could be separated in fingerprint and footprint analysis, respectively and provided complementary information. Based on the specific fingerprints obtained for different classes of antibiotics, the mode of action of several antibiotics could be predicted. The same classification approach should be applicable to studies of other pathogenic bacteria.
- ItemBioactive secondary metabolites with multiple activities from a fungal endophyte(Oxford : Wiley-Blackwell, 2016) Bogner, Catherine W.; Kamdem, Ramsay S.T.; Sichtermann, Gisela; Matthäus, Christian; Hölscher, Dirk; Popp, Jürgen; Proksch, Peter; Grundler, Florian M.W.; Schouten, AlexanderIn order to replace particularly biohazardous nematocides, there is a strong drive to finding natural product-based alternatives with the aim of containing nematode pests in agriculture. The metabolites produced by the fungal endophyte Fusarium oxysporum 162 when cultivated on rice media were isolated and their structures elucidated. Eleven compounds were obtained, of which six were isolated from a Fusarium spp. for the first time. The three most potent nematode-antagonistic compounds, 4-hydroxybenzoic acid, indole-3-acetic acid (IAA) and gibepyrone D had LC50 values of 104, 117 and 134 μg ml−1, respectively, after 72 h. IAA is a well-known phytohormone that plays a role in triggering plant resistance, thus suggesting a dual activity, either directly, by killing or compromising nematodes, or indirectly, by inducing defence mechanisms against pathogens (nematodes) in plants. Such compounds may serve as important leads in the development of novel, environmental friendly, nematocides.
- ItemTargeted delivery of a phosphoinositide 3-kinase γ inhibitor to restore organ function in sepsis(Heidelberg : EMBO Press, 2021) Press, Adrian T.; Babic, Petra; Hoffmann, Bianca; Müller, Tina; Foo, Wanling; Hauswald, Walter; Benecke, Jovana; Beretta, Martina; Cseresnyés, Zoltán; Hoeppener, Stephanie; Nischang, Ivo; Coldewey, Sina M.; Gräler, Markus H.; Bauer, Reinhard; Gonnert, Falk; Gaßler, Nikolaus; Wetzker, Reinhard; Figge, Marc Thilo; Schubert, Ulrich S.; Bauer, MichaelJaundice, the clinical hallmark of infection-associated liver dysfunction, reflects altered membrane organization of the canalicular pole of hepatocytes and portends poor outcomes. Mice lacking phosphoinositide 3-kinase-γ (PI3Kγ) are protected against membrane disintegration and hepatic excretory dysfunction. However, they exhibit a severe immune defect that hinders neutrophil recruitment to sites of infection. To exploit the therapeutic potential of PI3Kγ inhibition in sepsis, a targeted approach to deliver drugs to hepatic parenchymal cells without compromising other cells, in particular immune cells, seems warranted. Here, we demonstrate that nanocarriers functionalized through DY-635, a fluorescent polymethine dye, and a ligand of organic anion transporters can selectively deliver therapeutics to hepatic parenchymal cells. Applying this strategy to a murine model of sepsis, we observed the PI3Kγ-dependent restoration of biliary canalicular architecture, maintained excretory liver function, and improved survival without impairing host defense mechanisms. This strategy carries the potential to expand targeted nanomedicines to disease entities with systemic inflammation and concomitantly impaired barrier functionality.
- ItemBenchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry(Oxford : Oxford University Press, 2015) Oetjen, Janina; Veselkov, Kirill; Watrous, Jeramie; McKenzie, James S.; Becker, Michael; Hauberg-Lotte, Lena; Kobarg, Jan Hendrik; Strittmatter, Nicole; Mróz, Anna K.; Hoffmann, Franziska; Trede, Dennis; Palmer, Andrew; Schiffler, Stefan; Steinhorst, Klaus; Aichler, Michaela; Goldin, Robert; Guntinas-Lichius, Orlando; von Eggeling, Ferdinand; Thiele, Herbert; Maedler, Kathrin; Walch, Axel; Maass, Peter; Dorrestein, Pieter C.; Takats, Zoltan; Alexandrov, TheodoreBackground: Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms. Findings: High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma. Conclusions: With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.
- ItemWhat the Phage: a scalable workflow for the identification and analysis of phage sequences(Oxford : Oxford University Press, 2022) Marquet, Mike; Hölzer, Martin; Pletz, Mathias W; Viehweger, Adrian; Makarewicz, Oliwia; Ehricht, Ralf; Brandt, ChristianPhages are among the most abundant and diverse biological entities on earth. Phage prediction from sequence data is a crucial first step to understanding their impact on the environment. A variety of bacteriophage prediction tools have been developed over the years. They differ in algorithmic approach, results, and ease of use. We, therefore, developed "What the Phage"(WtP), an easy-to-use and parallel multitool approach for phage prediction combined with an annotation and classification downstream strategy, thus supporting the user's decision-making process by summarizing the results of the different prediction tools in charts and tables. WtP is reproducible and scales to thousands of datasets through a workflow manager (Nextflow). WtP is freely available under a GPL-3.0 license (https://github.com/replikation/What_the_Phage).