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- ItemCharacterization of antibiotic and biocide resistance genes and virulence factors of staphylococcus species associated with bovine mastitis in Rwanda(Basel : MDPI AG, 2020) Antók, Fruzsina Irén; Mayrhofer, Rosa; Marbach, Helene; Masengesho, Jean Claude; Keinprecht, Helga; Nyirimbuga, Vedaste; Fischer, Otto; Lepuschitz, Sarah; Ruppitsch, Werner; Ehling-Schulz, Monika; Feßler, Andrea T.; Schwarz, Stefan; Monecke, Stefan; Ehricht, Ralf; Grunert, Tom; Spergser, Joachim; Loncaric, IgorThe present study was conducted from July to August 2018 on milk samples taken at dairy farms in the Northern Province and Kigali District of Rwanda in order to identify Staphylococcus spp. associated with bovine intramammary infection. A total of 161 staphylococcal isolates originating from quarter milk samples of 112 crossbred dairy cattle were included in the study. Antimicrobial susceptibility testing was performed and isolates were examined for the presence of various resistance genes. Staphylococcus aureus isolates were also analyzed for the presence of virulence factors, genotyped by spa typing and further phenotypically subtyped for capsule expression using Fourier Transform Infrared (FTIR) spectroscopy. Selected S. aureus were characterized using DNA microarray technology, multi-locus sequence typing (MLST) and whole-genome sequencing. All mecA-positive staphylococci were further genotyped using dru typing. In total, 14 different staphylococcal species were detected, with S. aureus being most prevalent (26.7%), followed by S. xylosus (22.4%) and S. haemolyticus (14.9%). A high number of isolates was resistant to penicillin and tetracycline. Various antimicrobial and biocide resistance genes were detected. Among S. aureus, the Panton–Valentine leukocidin (PVL) genes, as well as bovine leukocidin (LukM/LukF-P83) genes, were detected in two and three isolates, respectively, of which two also carried the toxic shock syndrome toxin gene tsst-1 bovine variant. t1236 was the predominant spa type. FTIR-based capsule serotyping revealed a high prevalence of non-encapsulated S. aureus isolates (89.5%). The majority of the selected S. aureus isolates belonged to clonal complex (CC) 97 which was determined using DNA microarray based assignment. Three new MLST sequence types were detected. © 2019 by the authors. Licensee MDPI, Basel, Switzerland.
- 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.
- ItemBacteriomimetic Liposomes Improve Antibiotic Activity of a Novel Energy-Coupling Factor Transporter Inhibitor(Basel : MDPI, 2021) Drost, Menka; Diamanti, Eleonora; Fuhrmann, Kathrin; Goes, Adriely; Shams, Atanaz; Haupenthal, Jörg; Koch, Marcus; Hirsch, Anna K. H.; Fuhrmann, GregorLiposomes have been studied for decades as nanoparticulate drug delivery systems for cytostatics, and more recently, for antibiotics. Such nanoantibiotics show improved antibacterial efficacy compared to the free drug and can be effective despite bacterial recalcitrance. In this work, we present a loading method of bacteriomimetic liposomes for a novel, hydrophobic compound (HIPS5031) inhibiting energy-coupling factor transporters (ECF transporters), an underexplored antimicrobial target. The liposomes were composed of DOPG (18:1 (Δ9-cis) phosphatidylglycerol) and CL (cardiolipin), resembling the cell membrane of Gram-positive Staphylococcus aureus and Streptococcus pneumoniae, and enriched with cholesterol (Chol). The size and polydispersity of the DOPG/CL/± Chol liposomes remained stable over 8 weeks when stored at 4 °C. Loading of the ECF transporter inhibitor was achieved by thin film hydration and led to a high encapsulation efficiency of 33.19% ± 9.5% into the DOPG/CL/Chol liposomes compared to the phosphatidylcholine liposomes (DMPC/DPPC). Bacterial growth inhibition assays on the model organism Bacillus subtilis revealed liposomal HIPS5031 as superior to the free drug, showing a 3.5-fold reduction in CFU/mL at a concentration of 9.64 µM. Liposomal HIPS5031 was also shown to reduce B. subtilis biofilm. Our findings present an explorative basis for bacteriomimetic liposomes as a strategy against drug-resistant pathogens by surpassing the drug-formulation barriers of innovative, yet unfavorably hydrophobic, antibiotics.